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Dumas A, Bouchard C, Drapeau P, Lindsay LR, Ogden NH, Leighton PA. The risk of contact between visitors and Borrelia burgdorferi-infected ticks is associated with fine-scale landscape features in a southeastern Canadian nature park. BMC Public Health 2024; 24:1180. [PMID: 38671429 PMCID: PMC11055428 DOI: 10.1186/s12889-024-18673-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 04/21/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND Infectious diseases are emerging across temperate regions of the world, and, for some, links have been made between landscapes and emergence dynamics. For tick-borne diseases, public parks may be important exposure sites for people living in urbanized areas of North America and Europe. In most cases, we know more about the ecological processes that determine the hazard posed by ticks as disease vectors than we do about how human population exposure varies in urban natural parks. METHODS In this study, infrared counters were used to monitor visitor use of a public natural park in southern Quebec, Canada. A risk index representing the probability of encounters between humans and infected vectors was constructed. This was done by combining the intensity of visitor trail use and the density of infected nymphs obtained from field surveillance. Patterns of risk were examined using spatial cluster analysis. Digital forest data and park infrastructure data were then integrated using spatially explicit models to test whether encounter risk levels and its components vary with forest fragmentation indicators and proximity to park infrastructure. RESULTS Results suggest that, even at a very fine scales, certain landscape features and infrastructure can be predictors of risk levels. Both visitors and Borrelia burgdorferi-infected ticks concentrated in areas where forest cover was dominant, so there was a positive association between forest cover and the risk index. However, there were no associations between indicators of forest fragmentation and risk levels. Some high-risk clusters contributed disproportionately to the risk distribution in the park relative to their size. There were also two high-risk periods, one in early summer coinciding with peak nymphal activity, and one in early fall when park visitation was highest. CONCLUSIONS Here, we demonstrate the importance of integrating indicators of human behaviour visitation with tick distribution data to characterize risk patterns for tick-borne diseases in public natural areas. Indeed, understanding the environmental determinants of human-tick interactions will allow organisations to deploy more effective risk reduction interventions targeted at key locations and times, and improve the management of public health risks associated with tick-borne diseases in public spaces.
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Affiliation(s)
- Ariane Dumas
- Department of Pathology and Microbiology, Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada.
- Epidemiology of Zoonoses and Public Health Research Unit (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada.
| | - Catherine Bouchard
- Epidemiology of Zoonoses and Public Health Research Unit (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, QC, Canada
| | - Pierre Drapeau
- Department of Biological Sciences, Centre for Forest Research, Université du Québec À Montréal, Montreal, QC, Canada
| | - L Robbin Lindsay
- One Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Nicholas H Ogden
- Epidemiology of Zoonoses and Public Health Research Unit (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, QC, Canada
| | - Patrick A Leighton
- Department of Pathology and Microbiology, Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
- Epidemiology of Zoonoses and Public Health Research Unit (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
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Milwid RM, Gabriele-Rivet V, Ogden NH, Turgeon P, Fazil A, London D, de Montigny S, Rees EE. A methodology for estimating SARS-CoV-2 importation risk by air travel into Canada between July and November 2021. BMC Public Health 2024; 24:1088. [PMID: 38641571 PMCID: PMC11027292 DOI: 10.1186/s12889-024-18563-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 04/09/2024] [Indexed: 04/21/2024] Open
Abstract
BACKGROUND Estimating rates of disease importation by travellers is a key activity to assess both the risk to a country from an infectious disease emerging elsewhere in the world and the effectiveness of border measures. We describe a model used to estimate the number of travellers infected with SARS-CoV-2 into Canadian airports in 2021, and assess the impact of pre-departure testing requirements on importation risk. METHODS A mathematical model estimated the number of essential and non-essential air travellers infected with SARS-CoV-2, with the latter requiring a negative pre-departure test result. The number of travellers arriving infected (i.e. imported cases) depended on air travel volumes, SARS-CoV-2 exposure risk in the departure country, prior infection or vaccine acquired immunity, and, for non-essential travellers, screening from pre-departure molecular testing. Importation risk was estimated weekly from July to November 2021 as the number of imported cases and percent positivity (PP; i.e. imported cases normalised by travel volume). The impact of pre-departure testing was assessed by comparing three scenarios: baseline (pre-departure testing of all non-essential travellers; most probable importation risk given the pre-departure testing requirements), counterfactual scenario 1 (no pre-departure testing of fully vaccinated non-essential travellers), and counterfactual scenario 2 (no pre-departure testing of non-essential travellers). RESULTS In the baseline scenario, weekly imported cases and PP varied over time, ranging from 145 to 539 cases and 0.15 to 0.28%, respectively. Most cases arrived from the USA, Mexico, the United Kingdom, and France. While modelling suggested that essential travellers had a higher weekly PP (0.37 - 0.65%) than non-essential travellers (0.12 - 0.24%), they contributed fewer weekly cases (62 - 154) than non-essential travellers (84 - 398 per week) given their lower travel volume. Pre-departure testing was estimated to reduce imported cases by one third (counterfactual scenario 1) to one half (counterfactual scenario 2). CONCLUSIONS The model results highlighted the weekly variation in importation by traveller group (e.g., reason for travel and country of departure) and enabled a framework for measuring the impact of pre-departure testing requirements. Quantifying the contributors of importation risk through mathematical simulation can support the design of appropriate public health policy on border measures.
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Affiliation(s)
- Rachael M Milwid
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, QC, Canada
- Epidemiology of Zoonoses and Public Health Research Unit, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, QC, Canada
| | - Vanessa Gabriele-Rivet
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, QC, Canada.
- Epidemiology of Zoonoses and Public Health Research Unit, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, QC, Canada.
| | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, QC, Canada
- Department of Pathology and Microbiology, Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
- Epidemiology of Zoonoses and Public Health Research Unit, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, QC, Canada
| | - Patricia Turgeon
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, QC, Canada
- Department of Pathology and Microbiology, Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
- Epidemiology of Zoonoses and Public Health Research Unit, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, QC, Canada
| | - Aamir Fazil
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Guelph, ON, Canada
| | - David London
- Physique Des Particules, Université de Montréal, Faculté Des Arts Et Des Sciences, Montréal, QC, Canada
| | - Simon de Montigny
- Emergency Management Branch, Global Public Health Intelligence Network Tiger Team, Public Health Agency of Canada, Ottawa, ON, Canada
| | - Erin E Rees
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, QC, Canada
- Department of Pathology and Microbiology, Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
- Epidemiology of Zoonoses and Public Health Research Unit, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, QC, Canada
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Logan JJ, Sawada M, Knudby A, Ramsay T, Blanford JI, Ogden NH, Kulkarni MA. Knowledge, protective behaviours, and perception of Lyme disease in an area of emerging risk: results from a cross-sectional survey of adults in Ottawa, Ontario. BMC Public Health 2024; 24:867. [PMID: 38509528 PMCID: PMC10956326 DOI: 10.1186/s12889-024-18348-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 03/13/2024] [Indexed: 03/22/2024] Open
Abstract
BACKGROUND The number of Lyme disease risk areas in Canada is growing. In regions with emerging tick populations, it is important to emphasize peridomestic risk and the importance of protective behaviours in local public health communication. This study aims to identify characteristics associated with high levels of Lyme disease knowledge and adoption of protective behaviours among residents in the Ottawa, Ontario region. METHODS A geographically stratified web survey was conducted in November 2020 (n = 2018) to determine knowledge, attitudes, and practices regarding Lyme disease among adult residents. Responses were used to calculate: (i) composite scores for knowledge and adoption of protective practices; and (ii) an exposure risk index based on reported activity in woodlands during the spring-to-fall tick exposure risk period. RESULTS 60% of respondents had a high knowledge of Lyme disease, yet only 14% indicated they often use five or more measures to protect themselves. Factors strongly associated with a high level of Lyme disease knowledge included being 55 or older (Odds Ratio (OR) = 2.04), living on a property with a yard (OR = 3.22), having a high exposure index (OR = 1.59), and knowing someone previously infected with Lyme disease (OR = 2.05). Strong associations with the adoption of a high number of protective behaviours were observed with membership in a non-Indigenous racialized group (OR = 1.70), living on a property with a yard (OR = 2.37), previous infection with Lyme disease (OR = 2.13), prior tick bite exposure (OR = 1.62), and primarily occupational activity in wooded areas (OR = 2.31). CONCLUSIONS This study highlights the dynamics between Lyme disease knowledge, patterns of exposure risk awareness, and vigilance of personal protection in a Canadian region with emerging Lyme disease risk. Notably, this study identified gaps between perceived local risk and protective behaviours, presenting opportunities for targeted enhanced communication efforts in areas of Lyme disease emergence.
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Affiliation(s)
- James J Logan
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada.
| | - Michael Sawada
- Laboratory for Applied Geomatics and GIS Science (LAGGISS), Department of Geography, Environment & Geomatics, University of Ottawa, Ottawa, ON, Canada
| | - Anders Knudby
- Department of Geography, Environment & Geomatics, University of Ottawa, Ottawa, ON, Canada
| | - Tim Ramsay
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
- Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - Justine I Blanford
- Department of Earth Observation Science, Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands
| | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, QC, Canada
| | - Manisha A Kulkarni
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
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Cissé B, Lapen DR, Chalvet-Monfray K, Ogden NH, Ludwig A. Modeling West Nile Virus transmission in birds and humans: Advantages of using a cellular automata approach. Infect Dis Model 2024; 9:278-297. [PMID: 38328278 PMCID: PMC10847944 DOI: 10.1016/j.idm.2024.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 12/13/2023] [Accepted: 01/10/2024] [Indexed: 02/09/2024] Open
Abstract
In Canada, the periodic circulation of West Nile Virus (WNV) is difficult to predict and, beyond climatic factors, appears to be related to the migratory movements of infected birds from the southern United States. This hypothesis has not yet been explored in a spatially distributed model. The main objective of this work was to develop a spatially explicit dynamic model for the transmission of WNV in Canada, that allows us to explore non-climate related hypotheses associated with WNV transmission. A Cellular Automata (CA) approach for multiple hosts (birds and humans) is used for a test region in eastern Ontario, Canada. The tool is designed to explore the role of host and vector spatial heterogeneity, host migration, and vector feeding preferences. We developed a spatialized compartmental SEIRDS-SEI model for WNV transmission with a study region divided into 4 k m 2 rectangular cells. We used 2010-2021 bird data from the eBird project and 2010-2019 mosquito data collected by Ontario Public Health to mimic bird and mosquito seasonal variation. We considered heterogeneous bird densities (high and low suitability areas) and homogeneous mosquito and human densities. In high suitability areas for birds, we identified 5 entry points for WNV-infected birds. We compared our simulations with pools of WNV-infected field collected mosquitoes. Simulations and sensitivity analyses were performed using MATLAB software. The results showed good correspondence between simulated and observed epidemics, supporting the validity of our model assumptions and calibration. Sensitivity analysis showed that a 5% increase or decrease in each parameter of our model except for the biting rate of bird by mosquito (c ( B , M ) ) and mosquito natural mortality rate (d M ), had a very limited effect on the total number of cases (newly infected birds and humans), prevalence peak, or date of occurrence. We demonstrate the utility of the CA approach for studying WNV transmission in a heterogeneous landscape with multiple hosts.
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Affiliation(s)
- Baki Cissé
- Public Health Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, Canada
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
| | - David R. Lapen
- Ottawa Research and Development Centre, Science and Technology Branch, Agriculture and Agri-Food Canada, Ottawa, K1A 0C6, Canada
| | - K. Chalvet-Monfray
- Université de Lyon, INRAE, VetAgro Sup, UMR EPIA, Marcy l’Etoile, France
- Université Clermont Auvergne, INRAE, VetAgro Sup, UMR EPIA, Saint-Genès-Champanelle, France
| | - Nicholas H. Ogden
- Public Health Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, Canada
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
| | - Antoinette Ludwig
- Public Health Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, Canada
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
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Ogden NH, Dumas A, Gachon P, Rafferty E. Estimating the Incidence and Economic Cost of Lyme Disease Cases in Canada in the 21st Century with Projected Climate Change. Environ Health Perspect 2024; 132:27005. [PMID: 38349724 PMCID: PMC10863724 DOI: 10.1289/ehp13759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 01/11/2024] [Accepted: 01/16/2024] [Indexed: 02/15/2024]
Abstract
BACKGROUND Lyme disease (LD) is emerging in Canada owing to the range expansion of the tick vector Ixodes scapularis (I. scapularis). OBJECTIVES Our objective was to estimate future LD incidence in Canada, and economic costs, for the 21st century with projected climate change. METHODS Future regions of climatic suitability for I. scapularis were projected from temperature output of the North American Coordinated Regional Climate Downscaling Experiment regional climate model ensemble using greenhouse gas Representative Concentration Pathways (RCPs) 4.5 and 8.5. Once regions became climatically suitable for ticks, an algorithm derived from tick and LD case surveillance data projected subsequent increasing LD incidence. Three scenarios (optimistic, intermediate, and pessimistic) for maximum incidence at endemicity were selected based on LD surveillance, and underreporting estimates, from the United States. Health care and productivity cost estimates of LD cases were obtained from the literature. RESULTS Projected annual LD cases for Canada ranged from 120,000 to > 500,000 by 2050. Variation in incidence was mostly due to the maximum incidence at endemicity selected, with minor contributions from variations among climate models and RCPs. Projected annual costs were substantial, ranging from CA $ 0.5 billion to $ 2.0 billion a year by 2050. There was little difference in projected incidence and economic cost between RCPs, and from 2050 to 2100, because projected climate up to 2050 is similar for RCP4.5 and RCP8.5 (mitigation of greenhouse gas emissions captured in RCP4.5 does not impact climate before the 2050s) and by 2050 the most densely populated areas of the study region are projected to be climatically suitable for ticks. CONCLUSIONS Future incidence and economic costs of LD in Canada are likely to be substantial, but uncertainties remain. Because densely populated areas of Canada are projected to become endemic under conservative climate change scenarios, mitigation of greenhouse gas emissions is unlikely to provide substantial health co-benefits for LD. https://doi.org/10.1289/EHP13759.
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Affiliation(s)
- Nicholas H. Ogden
- Public Health Risk Sciences Division, Scientific Operations and Response, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, Quebec, Canada
- Groupe de recherche en épidémiologie des zoonoses et santé publique, Université de Montréal, St-Hyacinthe, Quebec, Canada
- Centre de recherche en santé publique, Université de Montréal, Montréal, Québec, Canada
| | - Ariane Dumas
- Public Health Risk Sciences Division, Scientific Operations and Response, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, Quebec, Canada
| | - Philippe Gachon
- Étude et Simulation du Climat à l’Échelle Régionale centre, Université du Québec à Montréal, Montréal, Québec, Canada
- Department of Geography, Université du Québec à Montréal, Montréal, Québec, Canada
| | - Ellen Rafferty
- Institute of Health Economics, Edmonton, Alberta, Canada
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Milwid RM, Li M, Fazil A, Maheu-Giroux M, Doyle CM, Xia Y, Cox J, Grace D, Dvorakova M, Walker SC, Mishra S, Ogden NH. Exploring the dynamics of the 2022 mpox outbreak in Canada. J Med Virol 2023; 95:e29256. [PMID: 38054533 DOI: 10.1002/jmv.29256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 10/24/2023] [Accepted: 11/11/2023] [Indexed: 12/07/2023]
Abstract
The 2022 mpox outbreak predominantly impacted gay, bisexual, and other men who have sex with men (gbMSM). Two models were developed to support situational awareness and management decisions in Canada. A compartmental model characterized epidemic drivers at national/provincial levels, while an agent-based model (ABM) assessed municipal-level impacts of vaccination. The models were parameterized and calibrated using empirical case and vaccination data between 2022 and 2023. The compartmental model explored: (1) the epidemic trajectory through community transmission, (2) the potential for transmission among non-gbMSM, and (3) impacts of vaccination and the proportion of gbMSM contributing to disease transmission. The ABM incorporated sexual-contact data and modeled: (1) effects of vaccine uptake on disease dynamics, and (2) impacts of case importation on outbreak resurgence. The calibrated, compartmental model followed the trajectory of the epidemic, which peaked in July 2022, and died out in December 2022. Most cases occurred among gbMSM, and epidemic trajectories were not consistent with sustained transmission among non-gbMSM. The ABM suggested that unprioritized vaccination strategies could increase the outbreak size by 47%, and that consistent importation (≥5 cases per 10 000) is necessary for outbreak resurgence. These models can inform time-sensitive situational awareness and policy decisions for similar future outbreaks.
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Affiliation(s)
- Rachael M Milwid
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, Canada
| | - Michael Li
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Canada
- Department of Mathematics and Statistics, McMaster University, Hamilton, Canada
| | - Aamir Fazil
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Canada
| | - Mathieu Maheu-Giroux
- Department of Epidemiology and Biostatistics, School of Population and Global Health, McGill University, Montréal, Canada
| | - Carla M Doyle
- Department of Epidemiology and Biostatistics, School of Population and Global Health, McGill University, Montréal, Canada
| | - Yiqing Xia
- Department of Epidemiology and Biostatistics, School of Population and Global Health, McGill University, Montréal, Canada
| | - Joseph Cox
- Department of Epidemiology and Biostatistics, School of Population and Global Health, McGill University, Montréal, Canada
- STBBI Surveillance Division, Infectious Diseases and Vaccination Programs Branch, Public Health Agency of Canada, Montréal, Canada
| | - Daniel Grace
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Milada Dvorakova
- Research Institute of the McGill University Health Centre, Montreal, Canada
| | - Steven C Walker
- Department of Mathematics and Statistics, McMaster University, Hamilton, Canada
| | - Sharmistha Mishra
- Department of Medicine, Faculty of Medicine, University of Toronto, Toronto, Canada
- MAP Centre for Urban Health Solutions, Ki Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Canada
- Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada
- Institute of Health Policy, Management and Evaluation, and Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- ICES, Toronto, Canada
| | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, Canada
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Mechai S, Coatsworth H, Ogden NH. Possible effect of mutations on serological detection of Borrelia burgdorferi sensu stricto ospC major groups: An in-silico study. PLoS One 2023; 18:e0292741. [PMID: 37815990 PMCID: PMC10564231 DOI: 10.1371/journal.pone.0292741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 09/27/2023] [Indexed: 10/12/2023] Open
Abstract
The outer surface protein C (OspC) of the agent of Lyme disease, Borrelia burgdorferi sensu stricto, is a major lipoprotein surface-expressed during early-phase human infections. Antibodies to OspC are used in serological diagnoses. This study explored the hypothesis that serological test sensitivity decreases as genetic similarity of ospC major groups (MGs) of infecting strains, and ospC A (the MG in the strain B31 used to prepare antigen for serodiagnosis assays) decreases. We used a previously published microarray dataset to compare serological reactivity to ospC A (measured as pixel intensity) versus reactivity to 22 other ospC MGs, within a population of 55 patients diagnosed by two-tier serological testing using B. burgdorferi s.s. strain B31 as antigen, in which the ospC MG is OspC A. The difference in reactivity of sera to ospC A and reactivity to each of the other 22 ospC MGs (termed 'reactivity difference') was the outcome variable in regression analysis in which genetic distance of the ospC MGs from ospC A was the explanatory variable. Genetic distance was computed for the whole ospC sequence, and 9 subsections, from Neighbour Joining phylogenetic trees of the 23 ospC MGs. Regression analysis was conducted using genetic distance for the full ospC sequence, and the subsections individually. There was a significant association between the reactivity difference and genetic distance of ospC MGs from ospC A: increased genetic distance reduced reactivity to OspC A. No single ospC subsection sequence fully explained the relationship between genetic distance and reactivity difference. An analysis of single nucleotide polymorphisms supported a biological explanation via specific amino acid modifications likely to change protein binding affinity. This adds support to the hypothesis that genetic diversity of B. burgdorferi s.s. (here specifically OspC) may impact serological diagnostic test performance. Further prospective studies are necessary to explore the clinical implications of these findings.
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Affiliation(s)
- Samir Mechai
- Public Health Risk Sciences, National Microbiology Laboratory Branch, Public Health Agency of Canada, St Hyacinthe, QC, Canada
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, St Hyacinthe, QC, Canada
| | - Heather Coatsworth
- One Health Division, National Microbiology Laboratory Branch, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Nicholas H. Ogden
- Public Health Risk Sciences, National Microbiology Laboratory Branch, Public Health Agency of Canada, St Hyacinthe, QC, Canada
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, St Hyacinthe, QC, Canada
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Talbot B, Kulkarni MA, Rioux-Rousseau M, Siebels K, Kotchi SO, Ogden NH, Ludwig A. Ecological Niche and Positive Clusters of Two West Nile Virus Vectors in Ontario, Canada. Ecohealth 2023; 20:249-262. [PMID: 37985537 PMCID: PMC10757704 DOI: 10.1007/s10393-023-01653-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 05/16/2023] [Accepted: 07/30/2023] [Indexed: 11/22/2023]
Abstract
West Nile virus (WNV) is a mosquito-borne pathogen associated with uncommon but severe neurological complications in humans, especially among the elderly and immune-compromised. In Northeastern North America, the Culex pipiens/restuans complex and Aedes vexans are the two principal vector mosquito species/species groups of WNV. Using a 10-year surveillance dataset of WNV vector captures at 118 sites across an area of 40,000 km2 in Eastern Ontario, Canada, the ecological niches of Cx. pipiens/restuans and Aedes vexans were modeled by random forest analysis. Spatiotemporal clusters of WNV-positive mosquito pools were identified using Kulldorf's spatial scan statistic. The study region encompasses land cover types and climate representative of highly populated Southeastern Canada. We found highest vector habitat suitability in the eastern half of the study area, where temperatures are generally warmer (variable importance > 0.40) and residential and agricultural cropland cover is more prominent (variable importance > 0.25). We found spatiotemporal clusters of high WNV infection rates around the city of Ottawa in both mosquito vector species. These results support the previous literature in the same region and elsewhere suggesting areas surrounding highly populated areas are also high-risk areas for vector-borne zoonoses such as the WNV.
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Affiliation(s)
- Benoit Talbot
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada.
- Research Group on Epidemiology of Zoonoses and Public Health (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada.
| | - Manisha A Kulkarni
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada
| | - Maxime Rioux-Rousseau
- Research Group on Epidemiology of Zoonoses and Public Health (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Saint- Hyacinthe, QC, and Guelph, ON, Canada
| | - Kevin Siebels
- Research Group on Epidemiology of Zoonoses and Public Health (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Saint- Hyacinthe, QC, and Guelph, ON, Canada
| | - Serge Olivier Kotchi
- Research Group on Epidemiology of Zoonoses and Public Health (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Saint- Hyacinthe, QC, and Guelph, ON, Canada
- Signal, Image Processing and Multimedia (STIM), Research Unit and Digital Expertise (UREN), Université Virtuelle de Côte d'Ivoire, Abidjan, Côte d'Ivoire
| | - Nicholas H Ogden
- Research Group on Epidemiology of Zoonoses and Public Health (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Saint- Hyacinthe, QC, and Guelph, ON, Canada
| | - Antoinette Ludwig
- Research Group on Epidemiology of Zoonoses and Public Health (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Saint- Hyacinthe, QC, and Guelph, ON, Canada
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Logan JJ, Hoi AG, Sawada M, Knudby A, Ramsay T, Blanford JI, Ogden NH, Kulkarni MA. Risk factors for Lyme disease resulting from residential exposure amidst emerging Ixodes scapularis populations: A neighbourhood-level analysis of Ottawa, Ontario. PLoS One 2023; 18:e0290463. [PMID: 37616268 PMCID: PMC10449184 DOI: 10.1371/journal.pone.0290463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Accepted: 08/08/2023] [Indexed: 08/26/2023] Open
Abstract
Lyme disease is an emerging health threat in Canada due to the continued northward expansion of the main tick vector, Ixodes scapularis. It is of particular concern to populations living in expanding peri-urban areas where residential development and municipal climate change response impact neighbourhood structure and composition. The objective of this study was to estimate associations of socio-ecological characteristics with residential Lyme disease risk at the neighbourhood scale. We used Lyme disease case data for 2017-2020 reported for Ottawa, Ontario to determine where patients' residential property, or elsewhere within their neighbourhood, was the suspected site of tick exposure. Cases meeting this exposure definition (n = 118) were aggregated and linked to neighbourhood boundaries. We calculated landscape characteristics from composited and classified August 2018 PlanetScope satellite imagery. Negative binomial generalized linear models guided by a priori hypothesized relationships explored the association between hypothesized interactions of landscape structure and the outcome. Increases in median household income, the number of forest patches, the proportion of forested area, forest edge density, and mean forest patch size were associated with higher residential Lyme disease incidence at the neighbourhood scale, while increases in forest shape complexity and average distance to forest edge were associated with reduced incidence (P<0.001). Among Ottawa neighbourhoods, the combined effect of forest shape complexity and average forest patch size was associated with higher residential Lyme disease incidence (P<0.001). These findings suggest that Lyme disease risk in residential settings is associated with urban design elements. This is particularly relevant in urban centres where local ecological changes may impact the presence of emerging tick populations and how residents interact with tick habitat. Further research into the mechanistic underpinnings of these associations would be an asset to both urban development planning and public health management.
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Affiliation(s)
- James J. Logan
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Amber Gigi Hoi
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Michael Sawada
- Department of Geography, Environment and Geomatics, University of Ottawa, Ottawa, Ontario, Canada
- Laboratory for Applied Geomatics and GIS Science, Department of Geography, Environment and Geomatics, University of Ottawa, Ottawa, Ontario, Canada
| | - Anders Knudby
- Department of Geography, Environment and Geomatics, University of Ottawa, Ottawa, Ontario, Canada
| | - Tim Ramsay
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
- Ottawa Hospital Research Institute, University of Ottawa, Ottawa, Ontario, Canada
| | - Justine I. Blanford
- Department of Earth Observation Science, Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands
| | - Nicholas H. Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Quebec, Canada
| | - Manisha A. Kulkarni
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
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10
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Zinck CB, Raveendram Thampy P, Uhlemann EME, Adam H, Wachter J, Suchan D, Cameron ADS, Rego ROM, Brisson D, Bouchard C, Ogden NH, Voordouw MJ. Variation among strains of Borrelia burgdorferi in host tissue abundance and lifetime transmission determine the population strain structure in nature. PLoS Pathog 2023; 19:e1011572. [PMID: 37607182 PMCID: PMC10473547 DOI: 10.1371/journal.ppat.1011572] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 09/01/2023] [Accepted: 07/23/2023] [Indexed: 08/24/2023] Open
Abstract
Pathogen life history theory assumes a positive relationship between pathogen load in host tissues and pathogen transmission. Empirical evidence for this relationship is surprisingly rare due to the difficulty of measuring transmission for many pathogens. The comparative method, where a common host is experimentally infected with a set of pathogen strains, is a powerful approach for investigating the relationships between pathogen load and transmission. The validity of such experimental estimates of strain-specific transmission is greatly enhanced if they can predict the pathogen population strain structure in nature. Borrelia burgdorferi is a multi-strain, tick-borne spirochete that causes Lyme disease in North America. This study used 11 field-collected strains of B. burgdorferi, a rodent host (Mus musculus, C3H/HeJ) and its tick vector (Ixodes scapularis) to determine the relationship between pathogen load in host tissues and lifetime host-to-tick transmission (HTT). Mice were experimentally infected via tick bite with 1 of 11 strains. Lifetime HTT was measured by infesting mice with I. scapularis larval ticks on 3 separate occasions. The prevalence and abundance of the strains in the mouse tissues and the ticks were determined by qPCR. We used published databases to obtain estimates of the frequencies of these strains in wild I. scapularis tick populations. Spirochete loads in ticks and lifetime HTT varied significantly among the 11 strains of B. burgdorferi. Strains with higher spirochete loads in the host tissues were more likely to infect feeding larval ticks, which molted into nymphal ticks that had a higher probability of B. burgdorferi infection (i.e., higher HTT). Our laboratory-based estimates of lifetime HTT were predictive of the frequencies of these strains in wild I. scapularis populations. For B. burgdorferi, the strains that establish high abundance in host tissues and that have high lifetime transmission are the strains that are most common in nature.
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Affiliation(s)
- Christopher B. Zinck
- Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Prasobh Raveendram Thampy
- Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Eva-Maria E. Uhlemann
- Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Hesham Adam
- Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Jenny Wachter
- Vaccine and Infectious Disease Organization, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Danae Suchan
- Institute for Microbial Systems and Society, Faculty of Science, University of Regina, Regina, Saskatchewan, Canada
- Department of Biology, University of Regina, Regina, Saskatchewan, Canada
| | - Andrew D. S. Cameron
- Institute for Microbial Systems and Society, Faculty of Science, University of Regina, Regina, Saskatchewan, Canada
- Department of Biology, University of Regina, Regina, Saskatchewan, Canada
| | - Ryan O. M. Rego
- Biology Centre, Institute of Parasitology, Czech Academy of Sciences, České Budějovice, Czech Republic
- Faculty of Science, University of South Bohemia, České Budějovice, Czech Republic
| | - Dustin Brisson
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Catherine Bouchard
- Public Health Risk Sciences, National Microbiology Laboratory, Public Health Agency of Canada, St Hyacinthe, Quebec, Canada
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Montreal, Canada
| | - Nicholas H. Ogden
- Public Health Risk Sciences, National Microbiology Laboratory, Public Health Agency of Canada, St Hyacinthe, Quebec, Canada
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Montreal, Canada
- Centre de recherche en santé publique (CReSP), Université de Montréal, Montreal, QC, Canada
| | - Maarten J. Voordouw
- Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
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11
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Tardy O, Acheson ES, Bouchard C, Chamberland É, Fortin A, Ogden NH, Leighton PA. Mechanistic movement models to predict geographic range expansions of ticks and tick-borne pathogens: Case studies with Ixodes scapularis and Amblyomma americanum in eastern North America. Ticks Tick Borne Dis 2023; 14:102161. [PMID: 36996508 DOI: 10.1016/j.ttbdis.2023.102161] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 03/02/2023] [Accepted: 03/03/2023] [Indexed: 03/30/2023]
Abstract
The geographic range of the blacklegged tick, Ixodes scapularis, is expanding northward from the United States into southern Canada, and studies suggest that the lone star tick, Amblyomma americanum, will follow suit. These tick species are vectors for many zoonotic pathogens, and their northward range expansion presents a serious threat to public health. Climate change (particularly increasing temperature) has been identified as an important driver permitting northward range expansion of blacklegged ticks, but the impacts of host movement, which is essential to tick dispersal into new climatically suitable regions, have received limited investigation. Here, a mechanistic movement model was applied to landscapes of eastern North America to explore 1) relationships between multiple ecological drivers and the speed of the northward invasion of blacklegged ticks infected with the causative agent of Lyme disease, Borrelia burgdorferi sensu stricto, and 2) its capacity to simulate the northward range expansion of infected blacklegged ticks and uninfected lone star ticks under theoretical scenarios of increasing temperature. Our results suggest that the attraction of migratory birds (long-distance tick dispersal hosts) to resource-rich areas during their spring migration and the mate-finding Allee effect in tick population dynamics are key drivers for the spread of infected blacklegged ticks. The modeled increases in temperature extended the climatically suitable areas of Canada for infected blacklegged ticks and uninfected lone star ticks towards higher latitudes by up to 31% and 1%, respectively, and with an average predicted speed of the range expansion reaching 61 km/year and 23 km/year, respectively. Differences in the projected spatial distribution patterns of these tick species were due to differences in climate envelopes of tick populations, as well as the availability and attractiveness of suitable habitats for migratory birds. Our results indicate that the northward invasion process of lone star ticks is primarily driven by local dispersal of resident terrestrial hosts, whereas that of blacklegged ticks is governed by long-distance migratory bird dispersal. The results also suggest that mechanistic movement models provide a powerful approach for predicting tick-borne disease risk patterns under complex scenarios of climate, socioeconomic and land use/land cover changes.
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12
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Rakotoarinia MR, Seidou O, Lapen DR, Leighton PA, Ogden NH, Ludwig A. Future land-use change predictions using Dyna-Clue to support mosquito-borne disease risk assessment. Environ Monit Assess 2023; 195:815. [PMID: 37286856 PMCID: PMC10246872 DOI: 10.1007/s10661-023-11394-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Accepted: 05/15/2023] [Indexed: 06/09/2023]
Abstract
Mosquitoes are known vectors for viral diseases in Canada, and their distribution is driven by climate and land use. Despite that, future land-use changes have not yet been used as a driver in mosquito distribution models in North America. In this paper, we developed land-use change projections designed to address mosquito-borne disease (MBD) prediction in a 38 761 km2 area of Eastern Ontario. The landscape in the study area is marked by urbanization and intensive agriculture and hosts a diverse mosquito community. The Dyna-CLUE model was used to project land-use for three time horizons (2030, 2050, and 2070) based on historical trends (from 2014 to 2020) for water, forest, agriculture, and urban land uses. Five scenarios were generated to reflect urbanization, agricultural expansion, and natural areas. An ensemble of thirty simulations per scenario was run to account for land-use conversion uncertainty. The simulation closest to the average map generated was selected to represent the scenario. A concordance matrix generated using map pair analysis showed a good agreement between the simulated 2020 maps and 2020 observed map. By 2050, the most significant changes are predicted to occur mainly in the southeastern region's rural and forested areas. By 2070, high deforestation is expected in the central west. These results will be integrated into risk models predicting mosquito distribution to study the possibility of humans' increased exposure risk to MBDs.
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Affiliation(s)
- Miarisoa Rindra Rakotoarinia
- Département de Pathologie Et Microbiologie, Faculté de Médecine Vétérinaire, Université de Montréal, 3200 Sicotte, Saint-Hyacinthe, Québec, J2S 2M2, Canada.
- Groupe de Recherche en Épidémiologie Des Zoonoses Et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, 3200 Sicotte, Saint-Hyacinthe, Québec, J2S 2M2, Canada.
| | - Ousmane Seidou
- Department of Civil Engineering, University of Ottawa, 161 Louis Pasteur, Ottawa, ON, K1N 6N5, Canada
| | - David R Lapen
- Ottawa Research and Development Centre, Agriculture and Agri-Food Canada, 960 Carling Ave, Ottawa, ON, K1A 0C6, Canada
| | - Patrick A Leighton
- Département de Pathologie Et Microbiologie, Faculté de Médecine Vétérinaire, Université de Montréal, 3200 Sicotte, Saint-Hyacinthe, Québec, J2S 2M2, Canada
- Groupe de Recherche en Épidémiologie Des Zoonoses Et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, 3200 Sicotte, Saint-Hyacinthe, Québec, J2S 2M2, Canada
| | - Nicholas H Ogden
- Groupe de Recherche en Épidémiologie Des Zoonoses Et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, 3200 Sicotte, Saint-Hyacinthe, Québec, J2S 2M2, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 3190 Sicotte, Saint-Hyacinthe, Québec, J2S 2M2, Canada
| | - Antoinette Ludwig
- Groupe de Recherche en Épidémiologie Des Zoonoses Et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, 3200 Sicotte, Saint-Hyacinthe, Québec, J2S 2M2, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 3190 Sicotte, Saint-Hyacinthe, Québec, J2S 2M2, Canada
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13
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Tuite AR, Ng V, Ximenes R, Diener A, Rafferty E, Ogden NH, Tunis M. Quantifying the economic gains associated with COVID-19 vaccination in the Canadian population: A cost-benefit analysis. Can Commun Dis Rep 2023; 49:263-273. [PMID: 38440772 PMCID: PMC10911688 DOI: 10.14745/ccdr.v49i06a03] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
Background Vaccination has been a key part of Canada's coronavirus disease 2019 (COVID-19) pandemic response. Although the clinical benefits of vaccination are clear, an understanding of the population-level benefits of vaccination relative to the programmatic costs is of value. The objective of this article is to quantify the economic impact of COVID-19 vaccination in the Canadian population between December 2020 and March 2022. Methods We conducted a model-based cost-benefit analysis of Canada's COVID-19 vaccination program. We used an epidemiological model to estimate the number of COVID-19 symptomatic cases, hospitalizations, post-COVID condition (PCC) cases, and deaths in the presence and absence of vaccination. Median, lower and upper 95% credible interval (95% CrI) outcome values from 100 model simulations were used to estimate the direct and indirect costs of illness, including the value of health. We used a societal perspective and a 1.5% discount rate. Results We estimated that the costs of the vaccination program were far outweighed by the savings associated with averted infections and associated downstream consequences. Vaccination increased the net benefit by CAD $298.1 billion (95% CrI: 27.2-494.6) compared to the no vaccination counterfactual. The largest benefits were due to averted premature mortality, resulting in an estimated $222.0 billion (95% CrI: 31.2-379.0) benefit. Conclusion Our model-based economic evaluation provides a retrospective assessment of COVID-19 vaccination during the first 16 months of the program in Canada and suggests that it was welfare-improving, considering the decreased hospitalizations and use of healthcare resources, deaths averted and lower morbidity from conditions such as PCC.
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Affiliation(s)
- Ashleigh R Tuite
- Centre for Immunization and Respiratory Infectious Diseases, Public Health Agency of Canada, Ottawa, ON
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON
| | - Victoria Ng
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, QC and Guelph, ON
| | - Raphael Ximenes
- Centre for Immunization and Respiratory Infectious Diseases, Public Health Agency of Canada, Ottawa, ON
| | - Alan Diener
- Policy Research, Economics, and Analytics Unit, Strategic Policy Branch, Health Canada, Ottawa, ON
| | | | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, QC and Guelph, ON
| | - Matthew Tunis
- Centre for Immunization and Respiratory Infectious Diseases, Public Health Agency of Canada, Ottawa, ON
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14
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Bouchard C, Dumas A, Baron G, Bowser N, Leighton PA, Lindsay LR, Milord F, Ogden NH, Aenishaenslin C. Integrated human behavior and tick risk maps to prioritize Lyme disease interventions using a 'One Health' approach. Ticks Tick Borne Dis 2023; 14:102083. [PMID: 36435167 DOI: 10.1016/j.ttbdis.2022.102083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 10/25/2022] [Accepted: 11/09/2022] [Indexed: 11/21/2022]
Abstract
Lyme disease (LD) risk is emerging rapidly in Canada due to range expansion of its tick vectors, accelerated by climate change. The risk of contracting LD varies geographically due to variability in ecological characteristics that determine the hazard (the densities of infected host-seeking ticks) and vulnerability of the human population determined by their knowledge and adoption of preventive behaviors. Risk maps are commonly used to support public health decision-making on Lyme disease, but the ability of the human public to adopt preventive behaviors is rarely taken into account in their development, which represents a critical gap. The objective of this work was to improve LD risk mapping using an integrated social-behavioral and ecological approach to: (i) compute enhanced integrated risk maps for prioritization of interventions and (ii) develop a spatially-explicit assessment tool to examine the relative contribution of different risk factors. The study was carried out in the Estrie region located in southern Québec. The blacklegged tick, Ixodes scapularis, infected with the agent of LD is widespread in Estrie and as a result, regional LD incidence is the highest in the province. LD knowledge and behaviors in the population were measured in a cross-sectional health survey conducted in 2018 reaching 10,790 respondents in Estrie. These data were used to create an index for the social-behavioral component of risk in 2018. Local Empirical Bayes estimator technique were used to better quantify the spatial variance in the levels of adoption of LD preventive activities. For the ecological risk analysis, a tick abundance model was developed by integrating data from ongoing long-term tick surveillance programs from 2007 up to 2018. Social-behavioral and ecological components of the risk measures were combined to create vulnerability index maps and, with the addition of human population densities, prioritization index maps. Map predictions were validated by testing the association of high-risk areas with the current spatial distribution of human cases of LD and reported tick exposure. Our results demonstrated that social-behavioral and ecological components of LD risk have markedly different distributions within Estrie. The occurrence of human LD cases or reported tick exposure in a municipality was positively associated with tick density and the prioritization risk index (p < 0.001). This research is a second step towards a more comprehensive integrated LD risk assessment approach, examining social-behavioral risk factors that interact with ecological risk factors to influence the management of emerging tick-borne diseases, an approach that could be applied more widely to vector-borne and zoonotic diseases.
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Affiliation(s)
- Catherine Bouchard
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada; Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculté de médecine vétérinaire (FMV), Université de Montréal, Saint-Hyacinthe, Québec, Canada.
| | - Ariane Dumas
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculté de médecine vétérinaire (FMV), Université de Montréal, Saint-Hyacinthe, Québec, Canada
| | - Geneviève Baron
- Direction de la santé publique de l'Estrie, CIUSSS de l'Estrie-CHUS, Sherbrooke, Québec, Canada
| | - Natasha Bowser
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculté de médecine vétérinaire (FMV), Université de Montréal, Saint-Hyacinthe, Québec, Canada; Centre de recherche en santé publique, Université de Montréal et CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada
| | - Patrick A Leighton
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculté de médecine vétérinaire (FMV), Université de Montréal, Saint-Hyacinthe, Québec, Canada; Centre de recherche en santé publique, Université de Montréal et CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada
| | - L Robbin Lindsay
- Zoonotic Diseases and Special Pathogens, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - François Milord
- Direction de santé publique de la Montérégie, Centre intégré de santé et de services sociaux Montérégie-Centre, Longueuil, Canada
| | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada; Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculté de médecine vétérinaire (FMV), Université de Montréal, Saint-Hyacinthe, Québec, Canada; Centre de recherche en santé publique, Université de Montréal et CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada
| | - Cécile Aenishaenslin
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculté de médecine vétérinaire (FMV), Université de Montréal, Saint-Hyacinthe, Québec, Canada; Centre de recherche en santé publique, Université de Montréal et CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada
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15
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Yuan P, Tan Y, Yang L, Aruffo E, Ogden NH, Bélair J, Heffernan J, Arino J, Watmough J, Carabin H, Zhu H. Assessing transmission risks and control strategy for monkeypox as an emerging zoonosis in a metropolitan area. J Med Virol 2023; 95:e28137. [PMID: 36089815 DOI: 10.1002/jmv.28137] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 08/11/2022] [Accepted: 08/26/2022] [Indexed: 01/11/2023]
Abstract
To model the spread of monkeypox (MPX) in a metropolitan area for assessing the risk of possible outbreaks, and identifying essential public health measures to contain the virus spread. The animal reservoir is the key element in the modeling of zoonotic disease. Using a One Health approach, we model the spread of the MPX virus in humans considering potential animal hosts such as rodents (e.g., rats, mice, squirrels, chipmunks, etc.) and emphasize their role and transmission of the virus in a high-risk group, including gay and bisexual men-who-have-sex-with-men (gbMSM). From model and sensitivity analysis, we identify key public health factors and present scenarios under different transmission assumptions. We find that the MPX virus may spill over from gbMSM high-risk groups to broader populations if the efficiency of transmission increases in the higher-risk group. However, the risk of outbreak can be greatly reduced if at least 65% of symptomatic cases can be isolated and their contacts traced and quarantined. In addition, infections in an animal reservoir will exacerbate MPX transmission risk in the human population. Regions or communities with a higher proportion of gbMSM individuals need greater public health attention. Tracing and quarantine (or "effective quarantine" by postexposure vaccination) of contacts with MPX cases in high-risk groups would have a significant effect on controlling the spreading. Also, monitoring for animal infections would be prudent.
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Affiliation(s)
- Pei Yuan
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, Centre for Diseases Modeling (CDM), York University, Toronto, Canada.,Centre for Diseases Modeling (CDM), York University, Toronto, Canada
| | - Yi Tan
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, Centre for Diseases Modeling (CDM), York University, Toronto, Canada.,Centre for Diseases Modeling (CDM), York University, Toronto, Canada
| | - Liu Yang
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, Centre for Diseases Modeling (CDM), York University, Toronto, Canada.,Centre for Diseases Modeling (CDM), York University, Toronto, Canada.,School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, China
| | - Elena Aruffo
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, Centre for Diseases Modeling (CDM), York University, Toronto, Canada.,Centre for Diseases Modeling (CDM), York University, Toronto, Canada
| | - Nicholas H Ogden
- Centre for Diseases Modeling (CDM), York University, Toronto, Canada.,Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Ottawa, Canada
| | - Jacques Bélair
- Centre for Diseases Modeling (CDM), York University, Toronto, Canada.,Département de Mathématiques et de Statistique, Université de Montréal, Montréal, Québec, Canada
| | - Jane Heffernan
- Centre for Diseases Modeling (CDM), York University, Toronto, Canada.,Department of Mathematics and Statistics, York University, Toronto, Canada
| | - Julien Arino
- Centre for Diseases Modeling (CDM), York University, Toronto, Canada.,Department of Mathematics, University of Manitoba, Winnipeg, Manitoba, Canada
| | - James Watmough
- Centre for Diseases Modeling (CDM), York University, Toronto, Canada.,Department of Mathematics and Statistics, University of New Brunswick, Fredericton, New Brunswick, Canada
| | - Hélène Carabin
- Département de Pathologie et Microbiologie, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada.,Département de médecine sociale et préventive, École de santé publique de l'université de Montréal, Montréal, Québec, Canada.,Centre de Recherche en Santé Publique (CReSP), de l'université de Montréal et du CIUSS du Centre Sud de Montréal, Montréal, Québec, Canada.,Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Université de Montréal, Saint-Hyacinthe, Québec, Canada
| | - Huaiping Zhu
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, Centre for Diseases Modeling (CDM), York University, Toronto, Canada.,Centre for Diseases Modeling (CDM), York University, Toronto, Canada
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Yuan P, Tan Y, Yang L, Aruffo E, Ogden NH, Bélair J, Arino J, Heffernan J, Watmough J, Carabin H, Zhu H. Modeling vaccination and control strategies for outbreaks of monkeypox at gatherings. Front Public Health 2022; 10:1026489. [PMID: 36504958 PMCID: PMC9732364 DOI: 10.3389/fpubh.2022.1026489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 10/31/2022] [Indexed: 11/27/2022] Open
Abstract
Background The monkeypox outbreak in non-endemic countries in recent months has led the World Health Organization (WHO) to declare a public health emergency of international concern (PHEIC). It is thought that festivals, parties, and other gatherings may have contributed to the outbreak. Methods We considered a hypothetical metropolitan city and modeled the transmission of the monkeypox virus in humans in a high-risk group (HRG) and a low-risk group (LRG) using a Susceptible-Exposed-Infectious-Recovered (SEIR) model and incorporated gathering events. Model simulations assessed how the vaccination strategies combined with other public health measures can contribute to mitigating or halting outbreaks from mass gathering events. Results The risk of a monkeypox outbreak was high when mass gathering events occurred in the absence of public health control measures. However, the outbreaks were controlled by isolating cases and vaccinating their close contacts. Furthermore, contact tracing, vaccinating, and isolating close contacts, if they can be implemented, were more effective for the containment of monkeypox transmission during summer gatherings than a broad vaccination campaign among HRG, when accounting for the low vaccination coverage in the overall population, and the time needed for the development of the immune responses. Reducing the number of attendees and effective contacts during the gathering could also prevent a burgeoning outbreak, as could restricting attendance through vaccination requirements. Conclusion Monkeypox outbreaks following mass gatherings can be made less likely with some restrictions on either the number and density of attendees in the gathering or vaccination requirements. The ring vaccination strategy inoculating close contacts of confirmed cases may not be enough to prevent potential outbreaks; however, mass gatherings can be rendered less risky if that strategy is combined with public health measures, including identifying and isolating cases and contact tracing. Compliance with the community and promotion of awareness are also indispensable to containing the outbreak.
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Affiliation(s)
- Pei Yuan
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, Toronto, ON, Canada,Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, ON, Canada
| | - Yi Tan
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, Toronto, ON, Canada,Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, ON, Canada
| | - Liu Yang
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, Toronto, ON, Canada,Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, ON, Canada,School of Mathematics and Statistics, Northeast Normal University, Changchun, China
| | - Elena Aruffo
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, Toronto, ON, Canada,Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, ON, Canada
| | - Nicholas H. Ogden
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, ON, Canada,Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, QC, Canada
| | - Jacques Bélair
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, ON, Canada,Département de Mathématiques et de Statistique, Université de Montréal, Montréal, QC, Canada
| | - Julien Arino
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, ON, Canada,Department of Mathematics, University of Manitoba, Winnipeg, MB, Canada
| | - Jane Heffernan
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, ON, Canada,Department of Mathematics and Statistics, York University, Toronto, ON, Canada
| | - James Watmough
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, ON, Canada,Department of Mathematics and Statistics, University of New Brunswick, Fredericton, NB, Canada
| | - Hélène Carabin
- Département de Pathologie et Microbiologie, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, QC, Canada,Département de médecine sociale et préventive, École de santé publique de l'Université de Montréal, Montréal, QC, Canada,Centre de Recherche en Santé Publique (CReSP) de l'université de Montréal et du CIUSS du Centre Sud de Montréal, Montréal, QC, Canada,Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Université de Montréal, Saint-Hyacinthe, QC, Canada
| | - Huaiping Zhu
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, Toronto, ON, Canada,Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, ON, Canada,*Correspondence: Huaiping Zhu
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17
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Pelletier J, Rocheleau JP, Aenishaenslin C, Dimitri Masson G, Lindsay LR, Ogden NH, Bouchard C, Leighton PA. Fluralaner Baits Reduce the Infestation of Peromyscus spp. Mice (Rodentia: Cricetidae) by Ixodes scapularis (Acari: Ixodidae) Larvae and Nymphs in a Natural Environment. J Med Entomol 2022; 59:2080-2089. [PMID: 35980603 DOI: 10.1093/jme/tjac106] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Indexed: 06/15/2023]
Abstract
The development of interventions that reduce Lyme disease incidence remains a challenge. Reservoir-targeted approaches aiming to reduce tick densities or tick infection prevalence with Borrelia burgdorferi have emerged as promising ways to reduce the density of infected ticks. Acaricides of the isoxazoline family offer high potential for reducing infestation of ticks on small mammals as they have high efficacy at killing feeding ticks for a long period. Fluralaner baits were recently demonstrated as effective, in the laboratory, at killing Ixodes scapularis larvae infesting Peromyscus mice, the main reservoir for B. burgdorferi in northeastern North America. Here, effectiveness of this approach for reducing the infestation of small mammals by immature stages of I. scapularis was tested in a natural environment. Two densities of fluralaner baits (2.1 baits/1,000 m2 and 4.4 baits/1,000 m2) were used during three years in forest plots. The number of I. scapularis larvae and nymphs per mouse from treated and control plots were compared. Fluralaner baiting reduced the number of larvae per mouse by 68% (CI95: 51-79%) at 2.1 baits/1,000 m2 and by 86% (CI95: 77-92%) at 4.4 baits/1,000 m2. The number of nymphs per mouse was reduced by 72% (CI95: 22-90%) at 4.4 baits/1,000 m2 but was not significantly reduced at 2.1 baits/1,000 m2. Reduction of Peromyscus mouse infestation by immature stages of I. scapularis supports the hypothesis that an approach targeting reservoirs of B. burgdorferi with isoxazolines has the potential to reduce tick-borne disease risk by decreasing the density of infected ticks in the environment.
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Affiliation(s)
- Jérôme Pelletier
- Département de pathologie et microbiologie, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Groupe de recherche en épidémiologie des zoonoses et santé publique, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Centre de recherche en santé publique de l'Université de Montréal et du CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada
| | - Jean-Philippe Rocheleau
- Groupe de recherche en épidémiologie des zoonoses et santé publique, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Département de santé animale, CÉGEP de Saint-Hyacinthe, Saint-Hyacinthe, Québec, Canada
| | - Cécile Aenishaenslin
- Département de pathologie et microbiologie, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Groupe de recherche en épidémiologie des zoonoses et santé publique, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Centre de recherche en santé publique de l'Université de Montréal et du CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada
| | - Gabrielle Dimitri Masson
- Département de pathologie et microbiologie, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Groupe de recherche en épidémiologie des zoonoses et santé publique, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
| | - L Robbin Lindsay
- One Health Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Nicholas H Ogden
- Groupe de recherche en épidémiologie des zoonoses et santé publique, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada
| | - Catherine Bouchard
- Groupe de recherche en épidémiologie des zoonoses et santé publique, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada
| | - Patrick A Leighton
- Département de pathologie et microbiologie, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Groupe de recherche en épidémiologie des zoonoses et santé publique, Faculté de médecine vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Centre de recherche en santé publique de l'Université de Montréal et du CIUSSS du Centre-Sud-de-l'Île-de-Montréal, Montréal, Québec, Canada
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18
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Hammond-Collins K, Tremblay M, Milord F, Baron G, Bouchard C, Kotchi SO, Lambert L, Leighton P, Ogden NH, Rees EE. An ecological approach to predict areas with established populations of Ixodes scapularis in Quebec, Canada. Ticks Tick Borne Dis 2022; 13:102040. [PMID: 36137391 DOI: 10.1016/j.ttbdis.2022.102040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 08/28/2022] [Accepted: 09/11/2022] [Indexed: 10/31/2022]
Abstract
Public health management of Lyme disease (LD) is a dynamic challenge in Canada. Climate warming is driving the northward expansion of suitable habitat for the tick vector, Ixodes scapularis. Information about tick population establishment is used to inform the risk of LD but is challenged by sampling biases from surveillance data. Misclassifying areas as having no established tick population underestimates the LD risk classification. We used a logistic regression model at the municipal level to predict the probability of I. scapularis population establishment based on passive tick surveillance data during the period of 2010-2017 in southern Quebec. We tested for the effect of abiotic and biotic factors hypothesized to influence tick biology and ecology. Additional variables controlled for sampling biases in the passive surveillance data. In our final selected model, tick population establishment was positively associated with annual cumulative degree-days > 0°C, precipitation and deer density, and negatively associated with coniferous and mixed forest types. Sampling biases from passive tick surveillance were controlled for using municipal population size and public health instructions on tick submissions. The model performed well as indicated by an area under the curve (AUC) of 0.92, sensitivity of 86% and specificity of 81%. Our model enables prediction of I. scapularis population establishment in areas which lack data from passive tick surveillance and may improve the sensitivity of LD risk categorization in these areas. A more sensitive system of LD risk classification is important for increasing awareness and use of protective measures employed against ticks, and decreasing the morbidity associated with LD.
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Affiliation(s)
| | - Mathieu Tremblay
- Direction de santé publique de la Montérégie, 1255 rue Beauregard, Longueuil, QC, Canada
| | - François Milord
- Direction de santé publique de la Montérégie, 1255 rue Beauregard, Longueuil, QC, Canada; Université de Sherbrooke, 2500 Boulevard de l'Université, Sherbrooke, QC, Canada
| | - Geneviève Baron
- Université de Sherbrooke, 2500 Boulevard de l'Université, Sherbrooke, QC, Canada; Direction de Santé Publique de l'Estrie, 300 rue King Est, Bureau 300, Sherbrooke, QC, Canada
| | - Catherine Bouchard
- Public Health Agency of Canada, 3200 rue Sicotte, Saint-Hyacinthe, QC, Canada; Faculty of Veterinary Medicine, Université de Montréal, 3190 rue Sicotte, Saint-Hyacinthe, QC, Canada; Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, QC, Canada
| | - Serge Olivier Kotchi
- Public Health Agency of Canada, 3200 rue Sicotte, Saint-Hyacinthe, QC, Canada; Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, QC, Canada
| | - Louise Lambert
- Direction de santé publique de la Montérégie, 1255 rue Beauregard, Longueuil, QC, Canada
| | - Patrick Leighton
- Faculty of Veterinary Medicine, Université de Montréal, 3190 rue Sicotte, Saint-Hyacinthe, QC, Canada; Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, QC, Canada
| | - Nicholas H Ogden
- Public Health Agency of Canada, 3200 rue Sicotte, Saint-Hyacinthe, QC, Canada; Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, QC, Canada
| | - Erin E Rees
- Public Health Agency of Canada, 3200 rue Sicotte, Saint-Hyacinthe, QC, Canada; Faculty of Veterinary Medicine, Université de Montréal, 3190 rue Sicotte, Saint-Hyacinthe, QC, Canada; Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, QC, Canada
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19
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Zinck CB, Thampy PR, Rego ROM, Brisson D, Ogden NH, Voordouw M. Borrelia burgdorferi strain and host sex influence pathogen prevalence and abundance in the tissues of a laboratory rodent host. Mol Ecol 2022; 31:5872-5888. [PMID: 36112076 DOI: 10.1111/mec.16694] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 08/31/2022] [Accepted: 09/02/2022] [Indexed: 01/13/2023]
Abstract
Experimental infections with different pathogen strains give insight into pathogen life history traits. The purpose of the present study was to compare variation in tissue infection prevalence and spirochete abundance among strains of Borrelia burgdorferi in a rodent host (Mus musculus, C3H/HeJ). Male and female mice were experimentally infected via tick bite with one of 12 strains. Ear tissue biopsies were taken at days 29, 59 and 89 postinfection, and seven tissues were collected at necropsy. The presence and abundance of spirochetes in the mouse tissues were measured by quantitative polymerase chain reaction. To determine the frequencies of our strains in nature, their multilocus sequence types were matched to published data sets. For the infected mice, 56.6% of the tissues were infected with B. burgdorferi. The mean spirochete load in the mouse necropsy tissues varied 4.8-fold between the strains. The mean spirochete load in the ear tissue biopsies decreased rapidly over time for some strains. The percentage of infected tissues in male mice (65.4%) was significantly higher compared to female mice (50.5%). The mean spirochete load in the seven tissues was 1.5× higher in male mice compared to female mice; this male bias was 15.3× higher in the ventral skin. Across the 11 strains, the mean spirochete loads in the infected mouse tissues were positively correlated with the strain-specific frequencies in their tick vector populations. The study suggests that laboratory-based estimates of pathogen abundance in host tissues can predict the strain composition of this important tick-borne pathogen in nature.
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Affiliation(s)
- Christopher B Zinck
- Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Prasobh Raveendran Thampy
- Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Ryan O M Rego
- Biology Centre, Institute of Parasitology, Czech Academy of Sciences, České Budějovice, Czechia
- Faculty of Science, University of South Bohemia, České Budějovice, Czechia
| | - Dustin Brisson
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Nicholas H Ogden
- Public Health Risk Sciences, National Microbiology Laboratory, Public Health Agency of Canada, St Hyacinthe, Quebec, Canada
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, and Centre de Recherche en Santé Publique (CReSP), Université de Montréal, Montreal, Quebec, Canada
| | - Maarten Voordouw
- Department of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
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20
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Yuan P, Tan Y, Yang L, Aruffo E, Ogden NH, Yang G, Lu H, Lin Z, Lin W, Ma W, Fan M, Wang K, Shen J, Chen T, Zhu H. Assessing the mechanism of citywide test-trace-isolate Zero-COVID policy and exit strategy of COVID-19 pandemic. Infect Dis Poverty 2022; 11:104. [PMID: 36192815 PMCID: PMC9529335 DOI: 10.1186/s40249-022-01030-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 09/16/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Countries that aimed for eliminating the cases of COVID-19 with test-trace-isolate policy are found to have lower infections, deaths, and better economic performance, compared with those that opted for other mitigation strategies. However, the continuous evolution of new strains has raised the question of whether COVID-19 eradication is still possible given the limited public health response capacity and fatigue of the epidemic. We aim to investigate the mechanism of the Zero-COVID policy on outbreak containment, and to explore the possibility of eradication of Omicron transmission using the citywide test-trace-isolate (CTTI) strategy. METHODS We develop a compartmental model incorporating the CTTI Zero-COVID policy to understand how it contributes to the SARS-CoV-2 elimination. We employ our model to mimic the Delta outbreak in Fujian Province, China, from September 10 to October 9, 2021, and the Omicron outbreak in Jilin Province, China for the period from March 1 to April 1, 2022. Projections and sensitivity analyses were conducted using dynamical system and Latin Hypercube Sampling/ Partial Rank Correlation Coefficient (PRCC). RESULTS Calibration results of the model estimate the Fujian Delta outbreak can end in 30 (95% confidence interval CI: 28-33) days, after 10 (95% CI: 9-11) rounds of citywide testing. The emerging Jilin Omicron outbreak may achieve zero COVID cases in 50 (95% CI: 41-57) days if supported with sufficient public health resources and population compliance, which shows the effectiveness of the CTTI Zero-COVID policy. CONCLUSIONS The CTTI policy shows the capacity for the eradication of the Delta outbreaks and also the Omicron outbreaks. Nonetheless, the implementation of radical CTTI is challenging, which requires routine monitoring for early detection, adequate testing capacity, efficient contact tracing, and high isolation compliance, which constrain its benefits in regions with limited resources. Moreover, these challenges become even more acute in the face of more contagious variants with a high proportion of asymptomatic cases. Hence, in regions where CTTI is not possible, personal protection, public health control measures, and vaccination are indispensable for mitigating and exiting the COVID-19 pandemic.
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Affiliation(s)
- Pei Yuan
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada.,Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada
| | - Yi Tan
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada.,Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada
| | - Liu Yang
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada.,Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada.,School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, China
| | - Elena Aruffo
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada.,Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada
| | - Nicholas H Ogden
- Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada.,Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Canada
| | - Guojing Yang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education and School of Tropical Medicine and Laboratory Medicine, The First Affiliated Hospital of Hainan Medical University, Hainan Medical University, Haikou, Hainan, China.
| | - Haixia Lu
- School of Arts and Science, Suqian University, Suqian, Jiangsu, China
| | - Zhigui Lin
- School of Mathematical Science, Yangzhou University, Yangzhou, Jiangsu, China
| | - Weichuan Lin
- School of Mathematics and Statistics, Fujian Normal University, Fuzhou, Fujian, China
| | - Wenjun Ma
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, Guangdong, China.,Disease Control and Prevention Institute, Jinan University, Guangzhou, Guangdong, China
| | - Meng Fan
- School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, China
| | - Kaifa Wang
- School of Mathematics and Statistics, Southwest University, Chongqing, China
| | - Jianhe Shen
- School of Mathematics and Statistics, Fujian Normal University, Fuzhou, Fujian, China
| | - Tianmu Chen
- School of Public Health and State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Xiamen University, Xiamen, Fujian, China
| | - Huaiping Zhu
- Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada. .,Canadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada.
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21
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Rees EE, Avery BP, Carabin H, Carson CA, Champredon D, de Montigny S, Dougherty B, Nasri BR, Ogden NH. Effectiveness of non-pharmaceutical interventions to reduce SARS-CoV-2 transmission in Canada and their association with COVID-19 hospitalization rates. Can Commun Dis Rep 2022; 48:438-448. [PMID: 38162959 PMCID: PMC10756332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
Background Non-pharmaceutical interventions (NPIs) aim to reduce the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections mostly by limiting contacts between people where virus transmission can occur. However, NPIs limit social interactions and have negative impacts on economic, physical, mental and social well-being. It is, therefore, important to assess the impact of NPIs on reducing the number of coronavirus disease 2019 (COVID-19) cases and hospitalizations to justify their use. Methods Dynamic regression models accounting for autocorrelation in time series data were used with data from six Canadian provinces (British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, Québec) to assess 1) the effect of NPIs (measured using a stringency index) on SARS-CoV-2 transmission (measured by the effective reproduction number), and 2) the effect of the number of hospitalized COVID-19 patients on the stringency index. Results Increasing stringency index was associated with a statistically significant decrease in the transmission of SARS-CoV-2 in Alberta, Saskatchewan, Manitoba, Ontario and Québec. The effect of stringency on transmission was time-lagged in all of these provinces except for Ontario. In all provinces except for Saskatchewan, increasing hospitalization rates were associated with a statistically significant increase in the stringency index. The effect of hospitalization on stringency was time-lagged. Conclusion These results suggest that NPIs have been effective in Canadian provinces, and that their implementation has been, in part, a response to increasing hospitalization rates of COVID-19 patients.
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Affiliation(s)
- Erin E Rees
- Public Health Risk Sciences Division, National Microbiology Laboratory (PHRSD), Public Health Agency of Canada, Saint-Hyacinthe, QC and Guelph, ON
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC
- Centre de recherche en santé publique (CReSP), Université de Montréal, Montréal, QC
| | - Brent P Avery
- Food-borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-borne and Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON
| | - Hélène Carabin
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC
- Centre de recherche en santé publique (CReSP), Université de Montréal, Montréal, QC
- Faculty of Veterinary Medicine, Université de Montréal, Montréal, QC
| | - Carolee A Carson
- Food-borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-borne and Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON
| | - David Champredon
- Public Health Risk Sciences Division, National Microbiology Laboratory (PHRSD), Public Health Agency of Canada, Saint-Hyacinthe, QC and Guelph, ON
| | - Simon de Montigny
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC
- School of Public Health, Université de Montréal, Montréal, QC
- Centre de recherche du CHU Sainte-Justine, Université de Montréal, Montréal, QC
| | - Brendan Dougherty
- Food-borne Disease and Antimicrobial Resistance Surveillance Division, Centre for Food-borne and Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, ON
| | - Bouchra R Nasri
- Centre de recherche en santé publique (CReSP), Université de Montréal, Montréal, QC
- School of Public Health, Université de Montréal, Montréal, QC
| | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory (PHRSD), Public Health Agency of Canada, Saint-Hyacinthe, QC and Guelph, ON
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, QC
- Centre de recherche en santé publique (CReSP), Université de Montréal, Montréal, QC
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22
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Ogden NH, Turgeon P, Fazil A, Clark J, Gabriele-Rivet V, Tam T, Ng V. Counterfactuals of effects of vaccination and public health measures on COVID-19 cases in Canada: What could have happened? Can Commun Dis Rep 2022; 48:292-302. [PMID: 37334255 PMCID: PMC10275398 DOI: 10.14745/ccdr.v48i78a01] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
This study illustrates what may have happened, in terms of coronavirus disease 2019 (COVID-19) infections, hospitalizations and deaths in Canada, had public health measures not been used to control the COVID-19 epidemic, and had restrictions been lifted with low levels of vaccination, or no vaccination, of the Canadian population. The timeline of the epidemic in Canada, and the public health interventions used to control the epidemic, are reviewed. Comparisons against outcomes in other countries and counterfactual modelling illustrate the relative success of control of the epidemic in Canada. Together, these observations show that without the use of restrictive measures and without high levels of vaccination, Canada could have experienced substantially higher numbers of infections and hospitalizations and almost a million deaths.
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Affiliation(s)
- Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, QC and Guelph, ON
| | - Patricia Turgeon
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, QC and Guelph, ON
| | - Aamir Fazil
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, QC and Guelph, ON
| | - Julia Clark
- Office of the Chief Public Health Officer, Public Health Agency of Canada, Ottawa, ON
| | - Vanessa Gabriele-Rivet
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, QC and Guelph, ON
| | - Theresa Tam
- Office of the Chief Public Health Officer, Public Health Agency of Canada, Ottawa, ON
| | - Victoria Ng
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, QC and Guelph, ON
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Slatculescu AM, Duguay C, Ogden NH, Sander B, Desjardins M, Cameron DW, Kulkarni MA. Spatiotemporal trends and socioecological factors associated with Lyme disease in eastern Ontario, Canada from 2010-2017. BMC Public Health 2022; 22:736. [PMID: 35418084 PMCID: PMC9006558 DOI: 10.1186/s12889-022-13167-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 03/31/2022] [Indexed: 11/12/2022] Open
Abstract
Currently, there is limited knowledge about socioeconomic, neighbourhood, and local ecological factors that contribute to the growing Lyme disease incidence in the province of Ontario, Canada. In this study, we sought to identify these factors that play an important role at the local scale, where people are encountering ticks in their communities. We used reported human Lyme disease case data and tick surveillance data submitted by the public from 2010–2017 to analyze trends in tick exposure, spatiotemporal clusters of infection using the spatial scan statistic and Local Moran’s I statistic, and socioecological risk factors for Lyme disease using a multivariable negative binomial regression model. Data were analyzed at the smallest geographic unit, consisting of 400–700 individuals, for which census data are disseminated in Canada. We found significant heterogeneity in tick exposure patterns based on location of residence, with 65.2% of Lyme disease patients from the city of Ottawa reporting tick exposures outside their health unit of residence, compared to 86.1%—98.1% of patients from other, largely rural, health units, reporting peri-domestic exposures. We detected eight spatiotemporal clusters of human Lyme disease incidence in eastern Ontario, overlapping with three clusters of Borrelia burgdorferi-infected ticks. When adjusting for population counts, Lyme disease case counts increased with larger numbers of Borrelia burgdorferi-infected ticks submitted by the public, higher proportion of treed landcover, lower neighbourhood walkability due to fewer intersections, dwellings, and points of interest, as well as with regions of higher residential instability and lower ethnic concentration (Relative Risk [RR] = 1.25, 1.02, 0.67–0.04, 1.34, and 0.57, respectively, p < .0001). Our study shows that there are regional differences in tick exposure patterns in eastern Ontario and that multiple socioecological factors contribute to Lyme disease risk in this region.
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Affiliation(s)
- Andreea M Slatculescu
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, 600 Peter Morand Crescent, Ottawa, ON, K1G 5Z3, Canada.
| | - Claudia Duguay
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, 600 Peter Morand Crescent, Ottawa, ON, K1G 5Z3, Canada
| | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, QC, Canada
| | - Beate Sander
- Toronto Health Economics and Technology Assessment Collaborative, University Health Network, Toronto, ON, Canada.,Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.,Public Health Ontario, Toronto, ON, Canada.,ICES, Toronto, ON, Canada
| | - Marc Desjardins
- Department of Pathology and Laboratory Medicine, University of Ottawa, Ottawa, ON, Canada.,Division of Microbiology, Eastern Ontario Regional Laboratory Association, Ottawa, ON, Canada
| | - D William Cameron
- Department of Biochemistry, Microbiology and Immunology, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada.,Chronic Disease Program, Ottawa Hospital Research Institute, Ottawa, ON, Canada.,Department of Medicine, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Manisha A Kulkarni
- School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, 600 Peter Morand Crescent, Ottawa, ON, K1G 5Z3, Canada
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24
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Yuan P, Li J, Aruffo E, Gatov E, Li Q, Zheng T, Ogden NH, Sander B, Heffernan J, Collier S, Tan Y, Li J, Arino J, Bélair J, Watmough J, Kong JD, Moyles I, Zhu H. Efficacy of a "stay-at-home" policy on SARS-CoV-2 transmission in Toronto, Canada: a mathematical modelling study. CMAJ Open 2022; 10:E367-E378. [PMID: 35440484 PMCID: PMC9022937 DOI: 10.9778/cmajo.20200242] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Globally, nonpharmaceutical interventions for COVID-19, including stay-at-home policies, limitations on gatherings and closure of public spaces, are being lifted. We explored the effect of lifting a stay-at-home policy on virus resurgence under different conditions. METHODS Using confirmed case data from Toronto, Canada, between Feb. 24 and June 24, 2020, we ran a compartmental model with household structure to simulate the impact of the stay-at-home policy considering different levels of compliance. We estimated threshold values for the maximum number of contacts, probability of transmission and testing rates required for the safe reopening of the community. RESULTS After the implementation of the stay-at-home policy, the contact rate outside the household fell by 39% (from 11.58 daily contacts to 7.11). The effective reproductive number decreased from 3.56 (95% confidence interval [CI] 3.02-4.14) on Mar. 12 to 0.84 (95% CI 0.79-0.89) on May 6. Strong adherence to stay-at-home policies appeared to prevent SARS-CoV-2 resurgence, but extending the duration of stay-at-home policies beyond 2 months had little added effect on cumulative cases (25 958 for 65 days of a stay-at-home policy and 23 461 for 95 days, by July 2, 2020) and deaths (1404 for 65 days and 1353 for 95 days). To avoid a resurgence, the average number of contacts per person per day should be kept below 9, with strict nonpharmaceutical interventions in place. INTERPRETATION Our study demonstrates that the stay-at-home policy implemented in Toronto in March 2020 had a substantial impact on mitigating the spread of SARS-CoV-2. In the context of the early pandemic, before the emergence of variants of concern, reopening schools and workplaces was possible only with other nonpharmaceutical interventions in place.
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Affiliation(s)
- Pei Yuan
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Juan Li
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Elena Aruffo
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Evgenia Gatov
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Qi Li
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Tingting Zheng
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Nicholas H Ogden
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Beate Sander
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Jane Heffernan
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Sarah Collier
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Yi Tan
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Jun Li
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Julien Arino
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Jacques Bélair
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - James Watmough
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Jude Dzevela Kong
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Iain Moyles
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
| | - Huaiping Zhu
- Canadian Centre for Disease Modeling (Yuan, Juan Li, Aruffo, Q. Li, Zheng, Heffernan, Tan, Jun Li, Arino, Bélair, Watmough, Kong, Moyles, Zhu), and Department of Mathematics and Statistics (Yuan, Aruffo, Heffernan, Tan, Kong, Moyles, Zhu), York University, Toronto, Ont.; Complex Systems Research Center (Juan Li), Shanxi University, Taiyuan, Shanxi, China; Toronto Public Health (Gatov, Collier), City of Toronto, Toronto, Ont.; Department of Mathematics (Q. Li), Shanghai Normal University, Shanghai, China; College of Mathematics and System Science (Zheng), Xinjiang University, Urumqi, Xinjiang, China; Public Health Risk Sciences Division (Ogden), National Microbiology Laboratory, Public Health Agency of Canada, Sainte-Hyacinthe, Que.; Toronto Health Economics and Technology Assessment (THETA) Collaborative (Sander), University Health Network; Dalla Lana School of Public Health (Sander), University of Toronto, Toronto, Ont.; School of Mathematics and Statistics (Jun Li), Xidian University, Xi'an, Shaanxi, China; Department of Mathematics (Arino), University of Manitoba, Winnipeg, Man.; Département de mathématiques et de statistique (Bélair), Université de Montréal, Montréal, Que.; Department of Mathematics and Statistics (Watmough), University of New Brunswick, Fredericton, NB
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Rakotoarinia MR, Blanchet FG, Gravel D, Lapen DR, Leighton PA, Ogden NH, Ludwig A. Effects of land use and weather on the presence and abundance of mosquito-borne disease vectors in a urban and agricultural landscape in Eastern Ontario, Canada. PLoS One 2022; 17:e0262376. [PMID: 35271575 PMCID: PMC8912203 DOI: 10.1371/journal.pone.0262376] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 02/21/2022] [Indexed: 11/19/2022] Open
Abstract
Weather and land use can significantly impact mosquito abundance and presence, and by consequence, mosquito-borne disease (MBD) dynamics. Knowledge of vector ecology and mosquito species response to these drivers will help us better predict risk from MBD. In this study, we evaluated and compared the independent and combined effects of weather and land use on mosquito species occurrence and abundance in Eastern Ontario, Canada. Data on occurrence and abundance (245,591 individuals) of 30 mosquito species were obtained from mosquito capture at 85 field sites in 2017 and 2018. Environmental variables were extracted from weather and land use datasets in a 1-km buffer around trapping sites. The relative importance of weather and land use on mosquito abundance (for common species) or occurrence (for all species) was evaluated using multivariate hierarchical statistical models. Models incorporating both weather and land use performed better than models that include weather only for approximately half of species (59% for occurrence model and 50% for abundance model). Mosquito occurrence was mainly associated with temperature whereas abundance was associated with precipitation and temperature combined. Land use was more often associated with abundance than occurrence. For most species, occurrence and abundance were positively associated with forest cover but for some there was a negative association. Occurrence and abundance of some species (47% for occurrence model and 88% for abundance model) were positively associated with wetlands, but negatively associated with urban (Culiseta melanura and Anopheles walkeri) and agriculture (An. quadrimaculatus, Cs. minnesotae and An. walkeri) environments. This study provides predictive relationships between weather, land use and mosquito occurrence and abundance for a wide range of species including those that are currently uncommon, yet known as arboviruses vectors. Elucidation of these relationships has the potential to contribute to better prediction of MBD risk, and thus more efficiently targeted prevention and control measures.
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Affiliation(s)
- Miarisoa Rindra Rakotoarinia
- Département de Pathologie et Microbiologie, Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
| | - F. Guillaume Blanchet
- Département de Biologie, Université de Sherbrooke, Sherbrooke, Canada
- Département de Mathématique, Université de Sherbrooke, Sherbrooke, Canada
- Département des Sciences de la Santé Communautaire, Université de Sherbrooke, Sherbrooke, Canada
| | - Dominique Gravel
- Département de Biologie, Université de Sherbrooke, Sherbrooke, Canada
| | - David R. Lapen
- Eastern Cereal and Oilseed Research Center, Agriculture and Agrifood Canada, Ottawa, Canada
| | - Patrick A. Leighton
- Département de Pathologie et Microbiologie, Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
| | - Nicholas H. Ogden
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Public Health Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, Canada
| | - Antoinette Ludwig
- Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Faculté de Médecine Vétérinaire, Université de Montréal, Saint-Hyacinthe, Québec, Canada
- Public Health Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, Canada
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Yuan P, Aruffo E, Tan Y, Yang L, Ogden NH, Fazil A, Zhu H. Projections of the transmission of the Omicron variant for Toronto, Ontario, and Canada using surveillance data following recent changes in testing policies. Infect Dis Model 2022; 7:83-93. [PMID: 35372735 PMCID: PMC8964508 DOI: 10.1016/j.idm.2022.03.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 03/21/2022] [Accepted: 03/22/2022] [Indexed: 12/24/2022] Open
Abstract
At the end of 2021, with the rapid escalation of COVID19 cases due to the Omicron variant, testing centers in Canada were overwhelmed. To alleviate the pressure on the PCR testing capacity, many provinces implemented new strategies that promote self testing and adjust the eligibility for PCR tests, making the count of new cases underreported. We designed a novel compartmental model which captures the new testing guidelines, social behaviours, booster vaccines campaign and features of the newest variant Omicron. To better describe the testing eligibility, we considered the population divided into high risk and non-high-risk settings. The model is calibrated using data from January 1 to February 9, 2022, on cases and severe outcomes in Canada, the province of Ontario and City of Toronto. We conduct analyses on the impact of PCR testing capacity, self testing, different levels of reopening and vaccination coverage on cases and severe outcomes. Our results show that the total number of cases in Canada, Ontario and Toronto are 2.34 (95%CI: 1.22–3.38), 2.20 (95%CI: 1.15–3.72), and 1.97(95%CI: 1.13–3.41), times larger than reported cases, respectively. The current testing strategy is efficient if partial restrictions, such as limited capacity in public spaces, are implemented. Allowing more people to have access to PCR reduces the daily cases and severe outcomes; however, if PCR test capacity is insufficient, then it is important to promote self testing. Also, we found that reopening to a pre-pandemic level will lead to a resurgence of the infections, peaking in late March or April 2022. Vaccination and adherence to isolation protocols are important supports to the testing policies to mitigate any possible spread of the virus.
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Affiliation(s)
- Pei Yuan
- Laboratory of Mathematical Parallel Systems (LAMPS), Centre for Diseases Modelling, Department of Mathematics and Statistics, York University, Toronto, ON, Canada
| | - Elena Aruffo
- Laboratory of Mathematical Parallel Systems (LAMPS), Centre for Diseases Modelling, Department of Mathematics and Statistics, York University, Toronto, ON, Canada
| | - Yi Tan
- Laboratory of Mathematical Parallel Systems (LAMPS), Centre for Diseases Modelling, Department of Mathematics and Statistics, York University, Toronto, ON, Canada
| | - Liu Yang
- Laboratory of Mathematical Parallel Systems (LAMPS), Centre for Diseases Modelling, Department of Mathematics and Statistics, York University, Toronto, ON, Canada
| | | | - Aamir Fazil
- Public Health Agency of Canada (PHAC), Ottawa, ON, Canada
| | - Huaiping Zhu
- Laboratory of Mathematical Parallel Systems (LAMPS), Centre for Diseases Modelling, Department of Mathematics and Statistics, York University, Toronto, ON, Canada
- Corresponding author. 4700 Keele Street, Toronto, Ontario, M3J1P3, Canada.
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Tardy O, Vincenot CE, Bouchard C, Ogden NH, Leighton PA. Context-dependent host dispersal and habitat fragmentation determine heterogeneity in infected tick burdens: an agent-based modelling study. R Soc Open Sci 2022. [PMID: 35360357 DOI: 10.5061/dryad.nzs7h44rx] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
As the incidence of tick-borne diseases has sharply increased over the past decade, with serious consequences for human and animal health, there is a need to identify ecological drivers contributing to heterogeneity in tick-borne disease risk. In particular, the relative importance of animal host dispersal behaviour in its three context-dependent phases of emigration, transfer and settlement is relatively unexplored. We built a spatially explicit agent-based model to investigate how the host dispersal process, in concert with the tick and host demographic processes, habitat fragmentation and the pathogen transmission process, affects infected tick distributions among hosts. A sensitivity analysis explored the impacts of different input parameters on infected tick burdens on hosts and infected tick distributions among hosts. Our simulations indicate that ecological predictors of infected tick burdens differed among the post-egg life stages of ticks, with tick attachment and detachment, tick questing activity and pathogen transmission dynamics identified as key processes, in a coherent way. We also found that the type of host settlement strategy and the proportion of habitat suitable for hosts determined super-spreading of infected ticks. We developed a theoretical mechanistic framework that can serve as a first step towards applied studies of on-the-ground public health intervention strategies.
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Affiliation(s)
- Olivia Tardy
- Research Group on Epidemiology of Zoonoses and Public Health, Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2
| | - Christian E Vincenot
- Department of Social Informatics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501, Japan
| | - Catherine Bouchard
- Research Group on Epidemiology of Zoonoses and Public Health, Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2
| | - Nicholas H Ogden
- Research Group on Epidemiology of Zoonoses and Public Health, Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2
| | - Patrick A Leighton
- Research Group on Epidemiology of Zoonoses and Public Health, Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2
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Tardy O, Vincenot CE, Bouchard C, Ogden NH, Leighton PA. Context-dependent host dispersal and habitat fragmentation determine heterogeneity in infected tick burdens: an agent-based modelling study. R Soc Open Sci 2022; 9:220245. [PMID: 35360357 PMCID: PMC8965412 DOI: 10.1098/rsos.220245] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Accepted: 02/28/2022] [Indexed: 05/09/2023]
Abstract
As the incidence of tick-borne diseases has sharply increased over the past decade, with serious consequences for human and animal health, there is a need to identify ecological drivers contributing to heterogeneity in tick-borne disease risk. In particular, the relative importance of animal host dispersal behaviour in its three context-dependent phases of emigration, transfer and settlement is relatively unexplored. We built a spatially explicit agent-based model to investigate how the host dispersal process, in concert with the tick and host demographic processes, habitat fragmentation and the pathogen transmission process, affects infected tick distributions among hosts. A sensitivity analysis explored the impacts of different input parameters on infected tick burdens on hosts and infected tick distributions among hosts. Our simulations indicate that ecological predictors of infected tick burdens differed among the post-egg life stages of ticks, with tick attachment and detachment, tick questing activity and pathogen transmission dynamics identified as key processes, in a coherent way. We also found that the type of host settlement strategy and the proportion of habitat suitable for hosts determined super-spreading of infected ticks. We developed a theoretical mechanistic framework that can serve as a first step towards applied studies of on-the-ground public health intervention strategies.
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Affiliation(s)
- Olivia Tardy
- Research Group on Epidemiology of Zoonoses and Public Health, Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2
| | - Christian E. Vincenot
- Department of Social Informatics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501, Japan
| | - Catherine Bouchard
- Research Group on Epidemiology of Zoonoses and Public Health, Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2
| | - Nicholas H. Ogden
- Research Group on Epidemiology of Zoonoses and Public Health, Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2
| | - Patrick A. Leighton
- Research Group on Epidemiology of Zoonoses and Public Health, Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Quebec, Canada J2S 2M2
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Gabriele-Rivet V, Spence KL, Ogden NH, Fazil A, Turgeon P, Otten A, Waddell LA, Ng V. Modelling the impact of age-stratified public health measures on SARS-CoV-2 transmission in Canada. R Soc Open Sci 2021; 8:210834. [PMID: 34737875 PMCID: PMC8562391 DOI: 10.1098/rsos.210834] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 10/22/2021] [Indexed: 06/13/2023]
Abstract
Public health measures applied exclusively within vulnerable populations have been suggested as an alternative to community-wide interventions to mitigate SARS-CoV-2 transmission. With the population demography and healthcare capacity of Canada as an example, a stochastic age-stratified agent-based model was used to explore the progression of the COVID-19 epidemic under three intervention scenarios (infection-preventing vaccination, illness-preventing vaccination and shielding) in individuals above three age thresholds (greater than or equal to 45, 55 and 65 years) while lifting shutdowns and physical distancing in the community. Compared with a scenario with sustained community-wide measures, all age-stratified intervention scenarios resulted in a substantial epidemic resurgence, with hospital and ICU bed usage exceeding healthcare capacities even at the lowest age threshold. Individuals under the age threshold were severely impacted by the implementation of all age-stratified interventions, with large numbers of avoidable deaths. Among all explored scenarios, shielding older individuals led to the most detrimental outcomes (hospitalizations, ICU admissions and mortality) for all ages, including the targeted population. This study suggests that, in the absence of community-wide measures, implementing interventions exclusively within vulnerable age groups could result in unmanageable levels of infections, with serious outcomes within the population. Caution is therefore warranted regarding early relaxation of community-wide restrictions.
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Affiliation(s)
- Vanessa Gabriele-Rivet
- Public Health Risk Sciences Division, National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ontario and St-Hyacinthe, Québec, Canada
| | - Kelsey L. Spence
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
| | - Nicholas H. Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ontario and St-Hyacinthe, Québec, Canada
| | - Aamir Fazil
- Public Health Risk Sciences Division, National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ontario and St-Hyacinthe, Québec, Canada
| | - Patricia Turgeon
- Public Health Risk Sciences Division, National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ontario and St-Hyacinthe, Québec, Canada
| | - Ainsley Otten
- Public Health Risk Sciences Division, National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ontario and St-Hyacinthe, Québec, Canada
| | - Lisa A. Waddell
- Public Health Risk Sciences Division, National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ontario and St-Hyacinthe, Québec, Canada
| | - Victoria Ng
- Public Health Risk Sciences Division, National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ontario and St-Hyacinthe, Québec, Canada
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Dumas A, Bouchard C, Lindsay LR, Ogden NH, Leighton PA. Fine-scale determinants of the spatiotemporal distribution of Ixodes scapularis in Quebec (Canada). Ticks Tick Borne Dis 2021; 13:101833. [PMID: 34600416 DOI: 10.1016/j.ttbdis.2021.101833] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 07/16/2021] [Accepted: 09/03/2021] [Indexed: 10/20/2022]
Abstract
The tick vector of Lyme disease, Ixodes scapularis, is currently expanding its geographical distribution northward into southern Canada driving emergence of Lyme disease in the region. Despite large-scale studies that attributed different factors such as climate change and changes in land use to the geographical expansion of the tick, a comprehensive understanding of local patterns of tick abundance is still lacking in that region. Using a newly endemic periurban nature park located in Quebec (Canada) as a model, we explored intra-habitat patterns in tick distribution and their relationship with biotic and abiotic factors. We verified the hypotheses that (1) there is spatial heterogeneity in tick densities at the scale of the park and (2) these patterns can be explained by host availability, habitat characteristics and microclimatic conditions. During tick activity season in three consecutive years, tick, deer, rodent and bird abundance, as well as habitat characteristics and microclimatic conditions, were estimated at thirty-two sites. Patterns of tick distribution and abundance were investigated by spatial analysis. Generalised additive mixed models were constructed for each developmental stage of the tick and the relative importance of significant drivers on tick abundance were derived from final models. We found fine-scale spatial heterogeneity in densities of all tick stages across the park, with interannual variability in the location of hotspots. For all stages, the local density was related to the density of the previous stage in the previous season, in keeping with the tick's life cycle. Adult tick density was highest where drainage was moderate (neither waterlogged nor dry). Microclimatic conditions influenced the densities of immature ticks, through the effects of weather at the time of tick sampling (ambient temperature and relative humidity) and of the seasonal microclimate at the site level (degree-days and number of tick adverse moisture events). Seasonal phenology patterns were generally consistent with expected curves for the region, with exceptions in some years that may be attributable to founder events. This study highlights fine scale patterns of tick population dynamics thus providing fundamental knowledge in Lyme disease ecology and information applicable to the development of well-targeted prevention and control strategies for public natural areas affected by this growing problem in southern Canada.
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Affiliation(s)
- Ariane Dumas
- Department of Pathology and Microbiology, Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, Québec, Canada; Epidemiology of Zoonoses and Public Health Research Unit (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, Québec, Canada.
| | - Catherine Bouchard
- Epidemiology of Zoonoses and Public Health Research Unit (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, Québec, Canada; Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada
| | - L Robbin Lindsay
- Zoonotic Diseases and Special Pathogens Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Nicholas H Ogden
- Epidemiology of Zoonoses and Public Health Research Unit (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, Québec, Canada; Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada
| | - Patrick A Leighton
- Department of Pathology and Microbiology, Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, Québec, Canada; Epidemiology of Zoonoses and Public Health Research Unit (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, Saint-Hyacinthe, Québec, Canada
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31
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Ginsberg HS, Hickling GJ, Burke RL, Ogden NH, Beati L, LeBrun RA, Arsnoe IM, Gerhold R, Han S, Jackson K, Maestas L, Moody T, Pang G, Ross B, Rulison EL, Tsao JI. Correction: Why Lyme disease is common in the northern US, but rare in the south: The roles of host choice, host-seeking behavior, and tick density. PLoS Biol 2021; 19:e3001396. [PMID: 34495954 PMCID: PMC8425571 DOI: 10.1371/journal.pbio.3001396] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
[This corrects the article DOI: 10.1371/journal.pbio.3001066.].
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Sadeghieh T, Sargeant JM, Greer AL, Berke O, Dueymes G, Gachon P, Ogden NH, Ng V. Zika virus outbreak in Brazil under current and future climate. Epidemics 2021; 37:100491. [PMID: 34454353 DOI: 10.1016/j.epidem.2021.100491] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 08/06/2021] [Accepted: 08/17/2021] [Indexed: 11/25/2022] Open
Abstract
INTRODUCTION Zika virus (ZIKV) is primarily transmitted byAedes aegypti and Aedes albopictus mosquitoes between humans and non-human primates. Climate change may enhance virus reproduction in Aedes spp. mosquito populations, resulting in intensified ZIKV outbreaks. The study objective was to explore how an outbreak similar to the 2016 ZIKV outbreak in Brazil might unfold with projected climate change. METHODS A compartmental infectious disease model that included compartments for humans and mosquitoes was developed to fit the 2016 ZIKV outbreak data from Brazil using least squares optimization. To explore the impact of climate change, published polynomial relationships between temperature and temperature-sensitive mosquito population and virus transmission parameters (mosquito mortality, development rate, and ZIKV extrinsic incubation period) were used. Projections for future outbreaks were obtained by simulating transmission with effects of projected average monthly temperatures on temperature-sensitive model parameters at each of three future time periods: 2011-2040, 2041-2070, and 2071-2100. The projected future climate was obtained from an ensemble of regional climate models (RCMs) obtained from the Co-Ordinated Regional Downscaling Experiment (CORDEX) that used Representative Concentration Pathways (RCP) with two radiative forcing values, RCP4.5 and RCP8.5. A sensitivity analysis was performed to explore the impact of temperature-dependent parameters on the model outcomes. RESULTS Climate change scenarios impacted the model outcomes, including the peak clinical case incidence, cumulative clinical case incidence, time to peak incidence, and the duration of the ZIKV outbreak. Comparing 2070-2100 to 2016, using RCP4.5, the peak incidence was 22,030 compared to 10,473; the time to epidemic peak was 12 compared to 9 weeks, and the outbreak duration was 52 compared to 41 weeks. Comparing 2070-2100 to 2016, using RCP8.5, the peak incidence was 21,786 compared to 10,473; the time to epidemic peak was 11 compared to 9 weeks, and the outbreak duration was 50 compared to 41weeks. The increases are due to optimal climate conditions for mosquitoes, with the mean temperature reaching 28 °C in the warmest months. Under a high emission scenario (RCP8.5), mean temperatures extend above optimal for mosquito survival in the warmest months. CONCLUSION Outbreaks of ZIKV in locations similar to Brazil are expected to be more intense with a warming climate. As climate change impacts are becoming increasingly apparent on human health, it is important to quantify the effect and use this knowledge to inform decisions on prevention and control strategies.
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Affiliation(s)
- Tara Sadeghieh
- Population Medicine, University of Guelph, Guelph, Ontario, Canada; Centre for Public Health and Zoonoses, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada; Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario and St. Hyacinthe, Québec, Canada.
| | - Jan M Sargeant
- Population Medicine, University of Guelph, Guelph, Ontario, Canada; Centre for Public Health and Zoonoses, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
| | - Amy L Greer
- Population Medicine, University of Guelph, Guelph, Ontario, Canada; Centre for Public Health and Zoonoses, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
| | - Olaf Berke
- Population Medicine, University of Guelph, Guelph, Ontario, Canada; Centre for Public Health and Zoonoses, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
| | - Guillaume Dueymes
- ESCER (Étude et Simulation du Climat à l'Échelle Régionale) Centre, Université du Québec à Montréal, Québec, Canada
| | - Philippe Gachon
- ESCER (Étude et Simulation du Climat à l'Échelle Régionale) Centre, Université du Québec à Montréal, Québec, Canada
| | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario and St. Hyacinthe, Québec, Canada
| | - Victoria Ng
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario and St. Hyacinthe, Québec, Canada
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Tardy O, Bouchard C, Chamberland E, Fortin A, Lamirande P, Ogden NH, Leighton PA. Mechanistic movement models reveal ecological drivers of tick-borne pathogen spread. J R Soc Interface 2021; 18:20210134. [PMID: 34376091 PMCID: PMC8355688 DOI: 10.1098/rsif.2021.0134] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Identifying ecological drivers of tick-borne pathogen spread has great value for tick-borne disease management. However, theoretical investigations into the consequences of host movement behaviour on pathogen spread dynamics in heterogeneous landscapes remain limited because spatially explicit epidemiological models that incorporate more realistic mechanisms governing host movement are rare. We built a mechanistic movement model to investigate how the interplay between multiple ecological drivers affects the risk of tick-borne pathogen spread across heterogeneous landscapes. We used the model to generate simulations of tick dispersal by migratory birds and terrestrial hosts across theoretical landscapes varying in resource aggregation, and we performed a sensitivity analysis to explore the impacts of different parameters on the infected tick spread rate, tick infection prevalence and infected tick density. Our findings highlight the importance of host movement and tick population dynamics in explaining the infected tick spread rate into new regions. Tick infection prevalence and infected tick density were driven by predictors related to the infection process and tick population dynamics, respectively. Our results suggest that control strategies aiming to reduce tick burden on tick reproduction hosts and encounter rate between immature ticks and pathogen amplification hosts will be most effective at reducing tick-borne disease risk.
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Affiliation(s)
- Olivia Tardy
- Research Group on Epidemiology of Zoonoses and Public Health (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Québec, Canada J2S 2M2.,Centre for Public Health Research (CReSP), Université de Montréal and the CIUSSS du Centre-Sud-de-l'Île-de-Montréal, 7101 avenue du Parc, Montréal, Québec, Canada H3N 1X9
| | - Catherine Bouchard
- Research Group on Epidemiology of Zoonoses and Public Health (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Québec, Canada J2S 2M2.,Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 3200 rue Sicotte, Saint-Hyacinthe, Québec, Canada J2S 2M2
| | - Eric Chamberland
- Groupe Interdisciplinaire de Recherche en Éléments Finis (GIREF), Department of Mathematics and Statistics, Faculty of Science and Engineering, Université Laval, 1045 avenue de la Médecine, Québec, Québec, Canada G1V 0A6
| | - André Fortin
- Groupe Interdisciplinaire de Recherche en Éléments Finis (GIREF), Department of Mathematics and Statistics, Faculty of Science and Engineering, Université Laval, 1045 avenue de la Médecine, Québec, Québec, Canada G1V 0A6
| | - Patricia Lamirande
- Groupe Interdisciplinaire de Recherche en Éléments Finis (GIREF), Department of Mathematics and Statistics, Faculty of Science and Engineering, Université Laval, 1045 avenue de la Médecine, Québec, Québec, Canada G1V 0A6
| | - Nicholas H Ogden
- Research Group on Epidemiology of Zoonoses and Public Health (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Québec, Canada J2S 2M2.,Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 3200 rue Sicotte, Saint-Hyacinthe, Québec, Canada J2S 2M2.,Centre for Public Health Research (CReSP), Université de Montréal and the CIUSSS du Centre-Sud-de-l'Île-de-Montréal, 7101 avenue du Parc, Montréal, Québec, Canada H3N 1X9
| | - Patrick A Leighton
- Research Group on Epidemiology of Zoonoses and Public Health (GREZOSP), Faculty of Veterinary Medicine, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Québec, Canada J2S 2M2.,Centre for Public Health Research (CReSP), Université de Montréal and the CIUSSS du Centre-Sud-de-l'Île-de-Montréal, 7101 avenue du Parc, Montréal, Québec, Canada H3N 1X9
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Otto SP, Day T, Arino J, Colijn C, Dushoff J, Li M, Mechai S, Van Domselaar G, Wu J, Earn DJD, Ogden NH. The origins and potential future of SARS-CoV-2 variants of concern in the evolving COVID-19 pandemic. Curr Biol 2021; 31:R918-R929. [PMID: 34314723 PMCID: PMC8220957 DOI: 10.1016/j.cub.2021.06.049] [Citation(s) in RCA: 177] [Impact Index Per Article: 59.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
One year into the global COVID-19 pandemic, the focus of attention has shifted to the emergence and spread of SARS-CoV-2 variants of concern (VOCs). After nearly a year of the pandemic with little evolutionary change affecting human health, several variants have now been shown to have substantial detrimental effects on transmission and severity of the virus. Public health officials, medical practitioners, scientists, and the broader community have since been scrambling to understand what these variants mean for diagnosis, treatment, and the control of the pandemic through nonpharmaceutical interventions and vaccines. Here we explore the evolutionary processes that are involved in the emergence of new variants, what we can expect in terms of the future emergence of VOCs, and what we can do to minimise their impact.
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Affiliation(s)
- Sarah P Otto
- Department of Zoology and Biodiversity Research Centre, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
| | - Troy Day
- Department of Mathematics and Statistics, Department of Biology, Queen's University, Kingston, ON K7L 3N6, Canada
| | - Julien Arino
- Department of Mathematics and Data Science Nexus, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
| | - Caroline Colijn
- Department of Mathematics, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
| | - Jonathan Dushoff
- Department of Biology and M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Michael Li
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON N1G 3W4, Canada
| | - Samir Mechai
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St. Hyacinthe, QC J2S 2M2, Canada
| | - Gary Van Domselaar
- National Microbiology Laboratory - Public Health Agency of Canada, Winnipeg, MB R3E 3R2, Canada; Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB R3E 0J9, Canada
| | - Jianhong Wu
- Laboratory for Industrial and Applied Mathematics, York University, Toronto, ON M3J 1P3, Canada
| | - David J D Earn
- Department of Mathematics and Statistics and M.G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4K1, Canada
| | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St. Hyacinthe, QC J2S 2M2, Canada
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O'Brien SF, Drews SJ, Yi QL, Bloch EM, Ogden NH, Koffi JK, Lindsay LR, Gregoire Y, Delage G. Risk of transfusion-transmitted Babesia microti in Canada. Transfusion 2021; 61:2958-2968. [PMID: 34272882 DOI: 10.1111/trf.16595] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 07/05/2021] [Accepted: 07/06/2021] [Indexed: 01/21/2023]
Abstract
BACKGROUND Babesia microti has gained a foothold in Canada as tick vectors become established in broader geographic areas. B. microti infection is associated with mild or no symptoms in healthy individuals but is transfusion-transmissible and can be fatal in immunocompromised individuals. This is the first estimate of clinically significant transfusion-transmitted babesiosis (TTB) risk in Canada. STUDY DESIGN AND METHODS The proportion of B. microti-antibody (AB)/nucleic acid amplification test (NAT)-positive whole blood donations was estimated at 5.5% of the proportion of the general population with reported Lyme Disease (also tick-borne) based on US data. Monte Carlo simulation estimated the number and proportion of infectious red cell units for three scenarios: base, localized incidence (risk in Manitoba only), and donor study informed (prevalence from donor data). The model simulated 1,029,800 donations repeated 100,000 times for each. RESULTS In the base scenario 0.5 (0.01, 1.75), B. microti-NAT-positive donations would be expected per year, with 0.08 (0, 0.38) recipients suffering clinically significant TTB (1 every 12.5 years). In the localized incidence scenario, there were 0.21(0, 0.7) B. microti-NAT-positive donations, with 0.04 (0, 0.14) recipient infections (about 1 every 25 years). In the donor study informed scenario, there were 4.6 (0.3, 15.8) B. microti-NAT-positive donations expected, and 0.81 (0.05, 3.14) clinically significant TTB cases per year. DISCUSSION The likelihood of clinically relevant TTB is low. Testing would have very little utility in Canada at this time. Ongoing pathogen surveillance in tick vectors is important as B. microti prevalence appears to be slowly increasing in Canada.
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Affiliation(s)
- Sheila F O'Brien
- Epidemiology & Surveillance, Canadian Blood Services, Ottawa, Ontario, Canada.,School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | - Steven J Drews
- Department of Microbiology, Canadian Blood Services, Edmonton, Alberta, Canada.,Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Qi-Long Yi
- Epidemiology & Surveillance, Canadian Blood Services, Ottawa, Ontario, Canada
| | - Evan M Bloch
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Quebec, Canada
| | - Jules K Koffi
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Quebec, Canada
| | - Leslie Robbin Lindsay
- Zoonotic Diseases & Special Pathogens, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Yves Gregoire
- Epidemiology and Statistics, Héma-Québec, Quebec City, Quebec, Canada
| | - Gilles Delage
- Medical Microbiology, Héma-Québec, Montreal, Quebec, Canada
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Ogden NH, Beard CB, Ginsberg HS, Tsao JI. Possible Effects of Climate Change on Ixodid Ticks and the Pathogens They Transmit: Predictions and Observations. J Med Entomol 2021; 58:1536-1545. [PMID: 33112403 PMCID: PMC9620468 DOI: 10.1093/jme/tjaa220] [Citation(s) in RCA: 62] [Impact Index Per Article: 20.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Indexed: 05/09/2023]
Abstract
The global climate has been changing over the last century due to greenhouse gas emissions and will continue to change over this century, accelerating without effective global efforts to reduce emissions. Ticks and tick-borne diseases (TTBDs) are inherently climate-sensitive due to the sensitivity of tick lifecycles to climate. Key direct climate and weather sensitivities include survival of individual ticks, and the duration of development and host-seeking activity of ticks. These sensitivities mean that in some regions a warming climate may increase tick survival, shorten life-cycles and lengthen the duration of tick activity seasons. Indirect effects of climate change on host communities may, with changes in tick abundance, facilitate enhanced transmission of tick-borne pathogens. High temperatures, and extreme weather events (heat, cold, and flooding) are anticipated with climate change, and these may reduce tick survival and pathogen transmission in some locations. Studies of the possible effects of climate change on TTBDs to date generally project poleward range expansion of geographical ranges (with possible contraction of ranges away from the increasingly hot tropics), upslope elevational range spread in mountainous regions, and increased abundance of ticks in many current endemic regions. However, relatively few studies, using long-term (multi-decade) observations, provide evidence of recent range changes of tick populations that could be attributed to recent climate change. Further integrated 'One Health' observational and modeling studies are needed to detect changes in TTBD occurrence, attribute them to climate change, and to develop predictive models of public- and animal-health needs to plan for TTBD emergence.
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Affiliation(s)
- Nicholas H. Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, QC, Canada J2S 2M2
- Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP), Faculté de médecine vétérinaire, Université de Montréal, St-Hyacinthe, QC, Canada J2S 2M2
- Corresponding author,
| | - C. Ben Beard
- Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, 3156 Rampart Road, Fort Collins, CO 80521
| | - Howard S. Ginsberg
- U.S. Geological Survey, Patuxent Wildlife Research Center, Rhode Island Field Station, University of Rhode Island, Kingston, RI 02881
| | - Jean I. Tsao
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824
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Mechai S, Bilodeau G, Lung O, Roy M, Steeves R, Gagne N, Baird D, Lapen DR, Ludwig A, Ogden NH. Mosquito Identification From Bulk Samples Using DNA Metabarcoding: a Protocol to Support Mosquito-Borne Disease Surveillance in Canada. J Med Entomol 2021; 58:1686-1700. [PMID: 33822118 DOI: 10.1093/jme/tjab046] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Indexed: 06/12/2023]
Abstract
Approximately 80 species of mosquitoes (Diptera: Culicidae) have been documented in Canada. Exotic species such as Aedes albopictus (Skuse) (Diptera: Culicidae) are becoming established. Recently occurring endemic mosquito-borne diseases (MBD) in Canada including West-Nile virus (WNV) and Eastern Equine Encephalitis (EEE) are having significant public health impacts. Here we explore the use of DNA metabarcoding to identify mosquitoes from CDC light-trap collections from two locations in eastern Canada. Two primer pairs (BF2-BR2 and F230) were used to amplify regions of the cytochrome c oxidase subunit I (CO1) gene. High throughput sequencing was conducted using an Illumina MiSeq platform and GenBank-based species identification was applied using a QIIME 1.9 bioinformatics pipeline. From a site in southeastern Ontario, Canada, 26 CDC light trap collections of 72 to >300 individual mosquitoes were used to explore the capacity of DNA metabarcoding to identify and quantify captured mosquitoes. The DNA metabarcoding method identified 33 species overall while 24 species were identified by key. Using replicates from each trap, the dried biomass needed to identify the majority of species was determined to be 76 mg (equivalent to approximately 72 mosquitoes), and at least two replicates from the dried biomass would be needed to reliably detect the majority of species in collections of 144-215 mosquitoes and three replicates would be advised for collections with >215 mosquitoes. This study supports the use of DNA metabarcoding as a mosquito surveillance tool in Canada which can help identify the emergence of new mosquito-borne disease potential threats.
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Affiliation(s)
- S Mechai
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada
| | - G Bilodeau
- Ottawa Plant Laboratory, Canadian Food Inspection Agency, Ottawa, Ontario, Canada
| | - O Lung
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - M Roy
- Aquatic Animal Health Section, Fisheries & Oceans Canada, Moncton, New Brunswick, Canada
| | - R Steeves
- Aquatic Animal Health Section, Fisheries & Oceans Canada, Moncton, New Brunswick, Canada
| | - N Gagne
- Aquatic Animal Health Section, Fisheries & Oceans Canada, Moncton, New Brunswick, Canada
| | - D Baird
- Environment and Climate Change Canada, Canadian Rivers Institute, Department of Biology, University of New Brunswick, Fredericton, New Brunswick, Canada
| | - D R Lapen
- Ottawa Research Development Centre, Agriculture & Agri-Food Canada, Ottawa, Ontario, Canada
| | - A Ludwig
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada
| | - N H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Québec, Canada
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Ng V, Fazil A, Waddell LA, Turgeon P, Otten A, Ogden NH. Modelling the impact of shutdowns on resurging SARS-CoV-2 transmission in Canada. R Soc Open Sci 2021; 8:210233. [PMID: 34123390 PMCID: PMC8190545 DOI: 10.1098/rsos.210233] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 04/29/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Shutdowns are enacted when alternative public health measures are insufficient to control the epidemic and the population is largely susceptible. An age-stratified agent-based model was developed to explore the impact of shutdowns to control SARS-CoV-2 transmission in Canada under the assumption that current efforts to control the epidemic remains insufficient and in the absence of a vaccine. METHODS We estimated the current levels of interventions in Canada to generate a baseline scenario from 7 February to 7 September 2020. Four aspects of shutdowns were explored in scenarios that ran from 8 September 2020 to 7 January 2022, these included the impact of how quickly shutdowns are implemented, the duration of shutdowns, the minimum break (delays) between shutdowns and the types of sectors to shutdown. Comparisons among scenarios were made using cases, hospitalizations, deaths and shutdown days during the 700-day model runs. RESULTS We found a negative relationship between reducing SARS-CoV-2 transmission and the number of shutdown days. However, we also found that for shutdowns to be optimally effective, they need to be implemented fast with minimal delay, initiated when community transmission is low, sustained for an adequate period and be stringent and target multiple sectors, particularly those driving transmission. By applying shutdowns in this manner, the total number of shutdown days could be reduced compared to delaying the shutdowns until further into the epidemic when transmission is higher and/or implementing short insufficient shutdowns that would require frequent re-implementation. This paper contrasts a range of shutdown strategies and trade-offs between health outcomes and economic metrics that need to be considered within the local context. INTERPRETATION Given the immense socioeconomic impact of shutdowns, they should be avoided where possible and used only when other public health measures are insufficient to control the epidemic. If used, the time it buys to delay the epidemic should be used to enhance other equally effective, but less disruptive, public health measures.
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Affiliation(s)
- Victoria Ng
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario and St Hyacinthe, Quebec, Canada
| | - Aamir Fazil
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario and St Hyacinthe, Quebec, Canada
| | - Lisa A. Waddell
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario and St Hyacinthe, Quebec, Canada
| | - Patricia Turgeon
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario and St Hyacinthe, Quebec, Canada
| | - Ainsley Otten
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario and St Hyacinthe, Quebec, Canada
| | - Nicholas H. Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario and St Hyacinthe, Quebec, Canada
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Champredon D, Fazil A, Ogden NH. Simple mathematical modelling approaches to assessing the transmission risk of SARS-CoV-2 at gatherings. Can Commun Dis Rep 2021; 47:184-194. [PMID: 34035664 PMCID: PMC8127697 DOI: 10.14745/ccdr.v47i04a02] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
BACKGROUND Gatherings may contribute significantly to the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). For this reason, public health interventions have sought to constrain unrepeated or recurrent gatherings to curb the coronavirus disease 2019 (COVID-19) pandemic. Unfortunately, the range of different types of gatherings hinders specific guidance from setting limiting parameters (e.g. total size, number of cohorts, the extent of physical distancing). METHODS We used a generic modelling framework, based on fundamental probability principles, to derive simple formulas to assess introduction and transmission risks associated with gatherings, as well as the potential efficiency of some testing strategies to mitigate these risks. RESULTS Introduction risk can be broadly assessed with the population prevalence and the size of the gathering, while transmission risk at a gathering is mainly driven by the gathering size. For recurrent gatherings, the cohort structure does not have a significant impact on transmission between cohorts. Testing strategies can mitigate risk, but frequency of testing and test performance are factors in finding a balance between detection and false positives. CONCLUSION The generality of the modelling framework used here helps to disentangle the various factors affecting transmission risk at gatherings and may be useful for public health decision-making.
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Affiliation(s)
- David Champredon
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON
| | - Aamir Fazil
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, ON
| | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St.-Hyacinthe, QC and Guelph, ON
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Sadeghieh T, Sargeant JM, Greer AL, Berke O, Dueymes G, Gachon P, Ogden NH, Ng V. Yellow fever virus outbreak in Brazil under current and future climate. Infect Dis Model 2021; 6:664-677. [PMID: 33997536 PMCID: PMC8090996 DOI: 10.1016/j.idm.2021.04.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 02/20/2021] [Accepted: 04/05/2021] [Indexed: 11/26/2022] Open
Abstract
Introduction Yellow fever (YF) is primarily transmitted by Haemagogus species of mosquitoes. Under climate change, mosquitoes and the pathogens that they carry are expected to develop faster, potentially impacting the case count and duration of YF outbreaks. The aim of this study was to determine how YF virus outbreaks in Brazil may change under future climate, using ensemble simulations from regional climate models under RCP4.5 and RCP8.5 scenarios for three time periods: 2011–2040 (short-term), 2041–2070 (mid-term), and 2071–2100 (long-term). Methods A compartmental model was developed to fit the 2017/18 YF outbreak data in Brazil using least squares optimization. To explore the impact of climate change, temperature-sensitive mosquito parameters were set to change over projected time periods using polynomial equations fitted to their relationship with temperature according to the average temperature for years 2011–2040, 2041–2070, and 2071–2100 for climate change scenarios using RCP4.5 and RCP8.5, where RCP4.5/RCP8.5 corresponds to intermediate/high radiative forcing values and to moderate/higher warming trends. A sensitivity analysis was conducted to determine how the temperature-sensitive parameters impacted model results, and to determine how vaccination could play a role in reducing YF in Brazil. Results Yellow fever case projections for Brazil from the models varied when climate change scenarios were applied, including the peak clinical case incidence, cumulative clinical case incidence, time to peak incidence, and the outbreak duration. Overall, a decrease in YF cases and outbreak duration was observed. Comparing the observed incidence in 2017/18 to the projected incidence in 2070–2100, for RCP4.5, the cumulative case incidence decreased from 184 to 161, and the outbreak duration decreased from 21 to 20 weeks. For RCP8.5, the peak case incidence decreased from 184 to 147, and the outbreak duration decreased from 21 to 17 weeks. The observed decrease was primarily due to temperature increasing beyond that suitable for Haemagogus mosquito survival. Conclusions Climate change is anticipated to have an impact on mosquito-borne diseases. We found outbreaks of YF may reduce in intensity as temperatures increase in Brazil; however, temperature is not the only factor involved with disease transmission. Other factors must be explored to determine the attributable impact of climate change on mosquito-borne diseases.
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Affiliation(s)
- Tara Sadeghieh
- Population Medicine, University of Guelph, Guelph, Ontario, Canada.,Centre for Public Health and Zoonoses, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada.,Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario, St. Hyacinthe, Québec, Canada
| | - Jan M Sargeant
- Population Medicine, University of Guelph, Guelph, Ontario, Canada.,Centre for Public Health and Zoonoses, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
| | - Amy L Greer
- Population Medicine, University of Guelph, Guelph, Ontario, Canada.,Centre for Public Health and Zoonoses, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
| | - Olaf Berke
- Population Medicine, University of Guelph, Guelph, Ontario, Canada.,Centre for Public Health and Zoonoses, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
| | - Guillaume Dueymes
- ESCER (Étude et Simulation du Climat à l'Échelle Régionale) Centre, Université du Québec à Montréal, Québec, Canada
| | - Philippe Gachon
- ESCER (Étude et Simulation du Climat à l'Échelle Régionale) Centre, Université du Québec à Montréal, Québec, Canada
| | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario, St. Hyacinthe, Québec, Canada
| | - Victoria Ng
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario, St. Hyacinthe, Québec, Canada
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Scarabel F, Pellis L, Ogden NH, Wu J. A renewal equation model to assess roles and limitations of contact tracing for disease outbreak control. R Soc Open Sci 2021; 8:202091. [PMID: 33868698 PMCID: PMC8025303 DOI: 10.1098/rsos.202091] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Accepted: 03/17/2021] [Indexed: 05/07/2023]
Abstract
We propose a deterministic model capturing essential features of contact tracing as part of public health non-pharmaceutical interventions to mitigate an outbreak of an infectious disease. By incorporating a mechanistic formulation of the processes at the individual level, we obtain an integral equation (delayed in calendar time and advanced in time since infection) for the probability that an infected individual is detected and isolated at any point in time. This is then coupled with a renewal equation for the total incidence to form a closed system describing the transmission dynamics involving contact tracing. We define and calculate basic and effective reproduction numbers in terms of pathogen characteristics and contact tracing implementation constraints. When applied to the case of SARS-CoV-2, our results show that only combinations of diagnosis of symptomatic infections and contact tracing that are almost perfect in terms of speed and coverage can attain control, unless additional measures to reduce overall community transmission are in place. Under constraints on the testing or tracing capacity, a temporary interruption of contact tracing may, depending on the overall growth rate and prevalence of the infection, lead to an irreversible loss of control even when the epidemic was previously contained.
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Affiliation(s)
- Francesca Scarabel
- LIAM—Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, Toronto, Ontario, Canada
- Fields-CQAM Laboratory of Mathematics for Public Health, York University, Toronto, Ontario, Canada
- CDLab—Computational Dynamics Laboratory, Department of Mathematics, Computer Science and Physics, University of Udine, Italy
| | - Lorenzo Pellis
- Department of Mathematics, University of Manchester, UK
- The Alan Turing Institute, London, UK
| | - Nicholas H. Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, Quebec, Canada
| | - Jianhong Wu
- LIAM—Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, Toronto, Ontario, Canada
- Fields-CQAM Laboratory of Mathematics for Public Health, York University, Toronto, Ontario, Canada
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Burrows H, Talbot B, McKay R, Slatculescu A, Logan J, Thickstun C, Lindsay LR, Dibernardo A, Koffi JK, Ogden NH, Kulkarni MA. A multi-year assessment of blacklegged tick (Ixodes scapularis) population establishment and Lyme disease risk areas in Ottawa, Canada, 2017-2019. PLoS One 2021; 16:e0246484. [PMID: 33539458 PMCID: PMC7861446 DOI: 10.1371/journal.pone.0246484] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 01/19/2021] [Indexed: 11/20/2022] Open
Abstract
Canadians face an emerging threat of Lyme disease due to the northward expansion of the tick vector, Ixodes scapularis. We evaluated the degree of I. scapularis population establishment and Borrelia burgdorferi occurrence in the city of Ottawa, Ontario, Canada from 2017–2019 using active surveillance at 28 sites. We used a field indicator tool developed by Clow et al. to determine the risk of I. scapularis establishment for each tick cohort at each site using the results of drag sampling. Based on results obtained with the field indicator tool, we assigned each site an ecological classification describing the pattern of tick colonization over two successive cohorts (cohort 1 was comprised of ticks collected in fall 2017 and spring 2018, and cohort 2 was collected in fall 2018 and spring 2019). Total annual site-specific I. scapularis density ranged from 0 to 16.3 ticks per person-hour. Sites with the highest density were located within the Greenbelt zone, in the suburban/rural areas in the western portion of the city of Ottawa, and along the Ottawa River; the lowest densities occurred at sites in the suburban/urban core. B. burgdorferi infection rates exhibited a similar spatial distribution pattern. Of the 23 sites for which data for two tick cohorts were available, 11 sites were classified as “high-stable”, 4 were classified as “emerging”, 2 were classified as “low-stable”, and 6 were classified as “non-zero”. B. burgdorferi-infected ticks were found at all high-stable sites, and at one emerging site. These findings suggest that high-stable sites pose a risk of Lyme disease exposure to the community as they have reproducing tick populations with consistent levels of B. burgdorferi infection. Continued surveillance for I. scapularis, B. burgdorferi, and range expansion of other tick species and emerging tick-borne pathogens is important to identify areas posing a high risk for human exposure to tick-borne pathogens in the face of ongoing climate change and urban expansion.
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Affiliation(s)
- Holly Burrows
- Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Benoit Talbot
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Roman McKay
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Andreea Slatculescu
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - James Logan
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Charles Thickstun
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - L. Robbin Lindsay
- Zoonotic Diseases and Special Pathogens Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Antonia Dibernardo
- Zoonotic Diseases and Special Pathogens Division, National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Jules K. Koffi
- Centre for Foodborne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Saint-Hyacinthe, Quebec, Canada
| | - Nicholas H. Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Quebec, Canada
| | - Manisha A. Kulkarni
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
- * E-mail:
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Ginsberg HS, Hickling GJ, Burke RL, Ogden NH, Beati L, LeBrun RA, Arsnoe IM, Gerhold R, Han S, Jackson K, Maestas L, Moody T, Pang G, Ross B, Rulison EL, Tsao JI. Why Lyme disease is common in the northern US, but rare in the south: The roles of host choice, host-seeking behavior, and tick density. PLoS Biol 2021; 19:e3001066. [PMID: 33507921 PMCID: PMC7842935 DOI: 10.1371/journal.pbio.3001066] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 12/22/2020] [Indexed: 12/28/2022] Open
Abstract
Lyme disease is common in the northeastern United States, but rare in the southeast, even though the tick vector is found in both regions. Infection prevalence of Lyme spirochetes in host-seeking ticks, an important component to the risk of Lyme disease, is also high in the northeast and northern midwest, but declines sharply in the south. As ticks must acquire Lyme spirochetes from infected vertebrate hosts, the role of wildlife species composition on Lyme disease risk has been a topic of lively academic discussion. We compared tick–vertebrate host interactions using standardized sampling methods among 8 sites scattered throughout the eastern US. Geographical trends in diversity of tick hosts are gradual and do not match the sharp decline in prevalence at southern sites, but tick–host associations show a clear shift from mammals in the north to reptiles in the south. Tick infection prevalence declines north to south largely because of high tick infestation of efficient spirochete reservoir hosts (rodents and shrews) in the north but not in the south. Minimal infestation of small mammals in the south results from strong selective attachment to lizards such as skinks (which are inefficient reservoirs for Lyme spirochetes) in the southern states. Selective host choice, along with latitudinal differences in tick host-seeking behavior and variations in tick densities, explains the geographic pattern of Lyme disease in the eastern US. Lyme disease is common in the northeastern United States, but rare in the southeast, even though the tick vector is found in both regions. This study shows that this is largely because the tick vectors attach abundantly to rodents (which are good hosts for the Lyme bacteria) in the north, and to lizards (which are relatively poor hosts for Lyme bacteria) in the south.
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Affiliation(s)
- Howard S. Ginsberg
- US Geological Survey, Patuxent Wildlife Research Center, Woodward-PSE, University of Rhode Island, Kingston, Rhode Island, United States of America
- Department of Plant Sciences and Entomology, University of Rhode Island, Kingston, Rhode Island, United States of America
- * E-mail:
| | - Graham J. Hickling
- Center for Wildlife Health, University of Tennessee Institute of Agriculture, Knoxville, Tennessee, United States of America
| | - Russell L. Burke
- Department of Biology, Hofstra University, Hempstead, New York, United States of America
| | - Nicholas H. Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Ste-Hyacinthe, Quebec, Canada
| | - Lorenza Beati
- US National Tick Collection, Institute for Coastal Plain Science, Georgia Southern University, Statesboro, Georgia, United States of America
| | - Roger A. LeBrun
- Department of Plant Sciences and Entomology, University of Rhode Island, Kingston, Rhode Island, United States of America
| | - Isis M. Arsnoe
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, United States of America
| | - Richard Gerhold
- Center for Wildlife Health, University of Tennessee Institute of Agriculture, Knoxville, Tennessee, United States of America
| | - Seungeun Han
- Comparative Medicine and Integrative Biology, Michigan State University, East Lansing, Michigan, United States of America
| | - Kaetlyn Jackson
- Department of Biology, Hofstra University, Hempstead, New York, United States of America
| | - Lauren Maestas
- Center for Wildlife Health, University of Tennessee Institute of Agriculture, Knoxville, Tennessee, United States of America
| | - Teresa Moody
- Center for Wildlife Health, University of Tennessee Institute of Agriculture, Knoxville, Tennessee, United States of America
| | - Genevieve Pang
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, United States of America
| | - Breann Ross
- Department of Biology, Hofstra University, Hempstead, New York, United States of America
| | - Eric L. Rulison
- Department of Plant Sciences and Entomology, University of Rhode Island, Kingston, Rhode Island, United States of America
| | - Jean I. Tsao
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, United States of America
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Dougherty BP, Smith BA, Carson CA, Ogden NH. Exploring the percentage of COVID-19 cases reported in the community in Canada and associated case fatality ratios. Infect Dis Model 2020; 6:123-132. [PMID: 33313456 PMCID: PMC7718109 DOI: 10.1016/j.idm.2020.11.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 11/30/2020] [Indexed: 01/02/2023] Open
Abstract
While surveillance can identify changes in COVID-19 transmission patterns over time and space, sections of the population at risk, and the efficacy of public health measures, reported cases of COVID-19 are generally understood to only capture a subset of the actual number of cases. Our primary objective was to estimate the percentage of cases reported in the general community, considered as those that occurred outside of long-term care facilities (LTCFs), in specific provinces and Canada as a whole. We applied a methodology using the delay-adjusted case fatality ratio (CFR) to all cases and deaths, as well as those representing the general community. Our second objective was to assess whether the assumed CFR (mean = 1.38%) was appropriate for calculating underestimation of cases in Canada. Estimates were developed for the period from March 11th, 2020 to September 16th, 2020. Estimates of the percentage of cases reported (PrCR) and CFR varied spatially and temporally across Canada. For the majority of provinces, and for Canada as a whole, the PrCR increased through the early stages of the pandemic. The estimated PrCR in general community settings for all of Canada increased from 18.1% to 69.0% throughout the entire study period. Estimates were greater when considering only those data from outside of LTCFs. The estimated upper bound CFR in general community settings for all of Canada decreased from 9.07% on March 11th, 2020 to 2.00% on September 16th, 2020. Therefore, the true CFR in the general community in Canada was likely less than 2% on September 16th. According to our analysis, some provinces, such as Alberta, Manitoba, Newfoundland and Labrador, Nova Scotia, and Saskatchewan reported a greater percentage of cases as of September 16th, compared to British Columbia, Ontario, and Québec. This could be due to differences in testing rates and criteria, demographics, socioeconomic factors, race, and access to healthcare among the provinces. Further investigation into these factors could reveal differences among provinces that could partially explain the variation in estimates of PrCR and CFR identified in our study. The estimates provide context to the summative state of the pandemic in Canada, and can be improved as knowledge of COVID-19 reporting rates and disease characteristics are advanced.
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Affiliation(s)
- Brendan P. Dougherty
- Centre for Food-borne and Environmental Zoonotic Infectious Diseases, Public Health Agency of Canada, 370 Speedvale Ave W., Guelph, ON, N1H 7M7, Canada
| | - Ben A. Smith
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 370 Speedvale Ave W., Guelph, ON, N1H 7M7, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St. Hyacinthe, QC, J2S 2M2, Canada
| | - Carolee A. Carson
- Centre for Food-borne and Environmental Zoonotic Infectious Diseases, Public Health Agency of Canada, 370 Speedvale Ave W., Guelph, ON, N1H 7M7, Canada
| | - Nicholas H. Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, 370 Speedvale Ave W., Guelph, ON, N1H 7M7, Canada
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St. Hyacinthe, QC, J2S 2M2, Canada
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McCarthy Z, Xiao Y, Scarabel F, Tang B, Bragazzi NL, Nah K, Heffernan JM, Asgary A, Murty VK, Ogden NH, Wu J. Quantifying the shift in social contact patterns in response to non-pharmaceutical interventions. J Math Ind 2020; 10:28. [PMID: 33282625 PMCID: PMC7707617 DOI: 10.1186/s13362-020-00096-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 11/25/2020] [Indexed: 05/03/2023]
Abstract
Social contact mixing plays a critical role in influencing the transmission routes of infectious diseases. Moreover, quantifying social contact mixing patterns and their variations in a rapidly evolving pandemic intervened by changing public health measures is key for retroactive evaluation and proactive assessment of the effectiveness of different age- and setting-specific interventions. Contact mixing patterns have been used to inform COVID-19 pandemic public health decision-making; but a rigorously justified methodology to identify setting-specific contact mixing patterns and their variations in a rapidly developing pandemic, which can be informed by readily available data, is in great demand and has not yet been established. Here we fill in this critical gap by developing and utilizing a novel methodology, integrating social contact patterns derived from empirical data with a disease transmission model, that enables the usage of age-stratified incidence data to infer age-specific susceptibility, daily contact mixing patterns in workplace, household, school and community settings; and transmission acquired in these settings under different physical distancing measures. We demonstrated the utility of this methodology by performing an analysis of the COVID-19 epidemic in Ontario, Canada. We quantified the age- and setting (household, workplace, community, and school)-specific mixing patterns and their evolution during the escalation of public health interventions in Ontario, Canada. We estimated a reduction in the average individual contact rate from 12.27 to 6.58 contacts per day, with an increase in household contacts, following the implementation of control measures. We also estimated increasing trends by age in both the susceptibility to infection by SARS-CoV-2 and the proportion of symptomatic individuals diagnosed. Inferring the age- and setting-specific social contact mixing and key age-stratified epidemiological parameters, in the presence of evolving control measures, is critical to inform decision- and policy-making for the current COVID-19 pandemic.
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Affiliation(s)
- Zachary McCarthy
- Fields-CQAM Laboratory of Mathematics for Public Health (MfPH), York University, Toronto, Ontario Canada
- Laboratory for Industrial and Applied Mathematics, York University, Toronto, Ontario Canada
| | - Yanyu Xiao
- Department of Mathematical Sciences, University of Cincinnati, Cincinnati, OH USA
| | - Francesca Scarabel
- Fields-CQAM Laboratory of Mathematics for Public Health (MfPH), York University, Toronto, Ontario Canada
- Laboratory for Industrial and Applied Mathematics, York University, Toronto, Ontario Canada
- CDLab—Computational Dynamics Laboratory, Department of Mathematics, Computer Science and Physics, University of Udine, 33100 Udine, Italy
| | - Biao Tang
- Fields-CQAM Laboratory of Mathematics for Public Health (MfPH), York University, Toronto, Ontario Canada
- Laboratory for Industrial and Applied Mathematics, York University, Toronto, Ontario Canada
| | - Nicola Luigi Bragazzi
- Fields-CQAM Laboratory of Mathematics for Public Health (MfPH), York University, Toronto, Ontario Canada
- Laboratory for Industrial and Applied Mathematics, York University, Toronto, Ontario Canada
| | - Kyeongah Nah
- Fields-CQAM Laboratory of Mathematics for Public Health (MfPH), York University, Toronto, Ontario Canada
- Laboratory for Industrial and Applied Mathematics, York University, Toronto, Ontario Canada
| | - Jane M. Heffernan
- Modelling Infection and Immunity Lab, Centre for Disease Modelling, Department of Mathematics and Statistics, York University, Toronto, Ontario Canada
| | - Ali Asgary
- Disaster & Emergency Management, School of Administrative Studies & Advanced Disaster & Emergency Rapid-Response Simulation (ADERSIM), York University, Toronto, Ontario Canada
| | - V. Kumar Murty
- Department of Mathematics, University of Toronto, Toronto, Ontario Canada
- The Fields Institute for Research in Mathematical Sciences, Toronto, Ontario Canada
| | - Nicholas H. Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, Quebec Canada
| | - Jianhong Wu
- Fields-CQAM Laboratory of Mathematics for Public Health (MfPH), York University, Toronto, Ontario Canada
- Laboratory for Industrial and Applied Mathematics, York University, Toronto, Ontario Canada
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Ng V, Fazil A, Waddell LA, Bancej C, Turgeon P, Otten A, Atchessi N, Ogden NH. Effets projetés des mesures de santé publique non pharmacologiques visant à prévenir la recrudescence de la transmission du SRAS-CoV-2 au Canada. CMAJ 2020; 192:E1673-E1685. [PMID: 33257338 PMCID: PMC7721389 DOI: 10.1503/cmaj.200990-f] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/21/2020] [Indexed: 11/01/2022] Open
Abstract
CONTEXTE: Il faudra prendre des mesures continues contre la transmission communautaire du coronavirus du syndrome respiratoire aigu sévère 2 (SRAS-CoV-2) pour prévenir d’autres vagues d’infection. Nous avons exploré les effets des interventions non pharmacologiques sur la transmission projetée du SRAS-CoV-2 au Canada. MÉTHODES: Nous avons créé un modèle de la population canadienne à base d’agents intégrant l’âge qui simule les effets des mesures de santé publique, selon leur intensité actuelle et projetée, sur la transmission du SRAS-CoV-2. Les mesures étudiées sont le dépistage et l’isolement des cas, la recherche de contacts et la mise en quarantaine, l’éloignement sanitaire et la fermeture des espaces partagés. Nous avons évalué l’effet des mesures prises individuellement et celui des mesures combinées. RÉSULTATS: En l’absence de mesures, 64,6 % (intervalle de crédibilité [ICr] à 95 % : 63,9 %–65,0 %) des Canadiens contracteraient le SRAS-CoV-2 (taux d’attaque global), et 3,6 % (ICr à 95 % 2,4 %–3,8 %) des personnes infectées en mourraient. En poursuivant le dépistage et la recherche de contacts à la même intensité que pendant la période de référence, sans maintenir l’éloignement sanitaire ou refermer certains endroits, le pays connaîtrait un taux d’attaque global de 56,1 % (ICr à 95 % 0,05 %–57,1 %); si ces mesures étaient accrues, le taux d’attaque chuterait à 0,4 % (ICr à 95 % 0,03 %–23,5 %). En combinant ce dernier scénario et le maintien de l’éloignement sanitaire, le taux tomberait à 0,2 % (ICr à 95 % 0,03 %–1,7 %). Ce scénario est le seul qui garderait la demande en soins hospitaliers et intensifs sous la capacité, qui préviendrait presque tous les décès et qui mettrait fin à l’épidémie. La prolongation de la fermeture des écoles aurait un effet minime, mais réduirait la transmission en milieu scolaire. Par contre, la prolongation de la fermeture des lieux de travail et des lieux publics réduirait de manière marquée le taux d’attaque et mettait habituellement ou toujours fin à l’épidémie, selon les différents scénarios simulés. INTERPRÉTATION: Le contrôle de la transmission du SRAS-CoV-2 passera par l’amélioration et le maintien des mesures, tant communautaires qu’individuelles. Autrement, il y aura une recrudescence de l’épidémie, et un risque de surcharger le système de santé.
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Affiliation(s)
- Victoria Ng
- Division des sciences des risques pour la santé publique (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), Laboratoire national de microbiologie, Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Guelph (Ontario) et Saint-Hyacinthe (Québec); Centre de l'immunisation et des maladies respiratoires infectieuses (Bancej), Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Ottawa (Ontario); Bureau des programmes et de la planification en biosécurité (Atchessi), Centre de la biosûreté, Direction générale de l'infrastructure de sûreté sanitaire, Agence de la santé publique du Canada, Ottawa (Ontario)
| | - Aamir Fazil
- Division des sciences des risques pour la santé publique (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), Laboratoire national de microbiologie, Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Guelph (Ontario) et Saint-Hyacinthe (Québec); Centre de l'immunisation et des maladies respiratoires infectieuses (Bancej), Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Ottawa (Ontario); Bureau des programmes et de la planification en biosécurité (Atchessi), Centre de la biosûreté, Direction générale de l'infrastructure de sûreté sanitaire, Agence de la santé publique du Canada, Ottawa (Ontario)
| | - Lisa A Waddell
- Division des sciences des risques pour la santé publique (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), Laboratoire national de microbiologie, Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Guelph (Ontario) et Saint-Hyacinthe (Québec); Centre de l'immunisation et des maladies respiratoires infectieuses (Bancej), Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Ottawa (Ontario); Bureau des programmes et de la planification en biosécurité (Atchessi), Centre de la biosûreté, Direction générale de l'infrastructure de sûreté sanitaire, Agence de la santé publique du Canada, Ottawa (Ontario)
| | - Christina Bancej
- Division des sciences des risques pour la santé publique (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), Laboratoire national de microbiologie, Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Guelph (Ontario) et Saint-Hyacinthe (Québec); Centre de l'immunisation et des maladies respiratoires infectieuses (Bancej), Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Ottawa (Ontario); Bureau des programmes et de la planification en biosécurité (Atchessi), Centre de la biosûreté, Direction générale de l'infrastructure de sûreté sanitaire, Agence de la santé publique du Canada, Ottawa (Ontario)
| | - Patricia Turgeon
- Division des sciences des risques pour la santé publique (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), Laboratoire national de microbiologie, Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Guelph (Ontario) et Saint-Hyacinthe (Québec); Centre de l'immunisation et des maladies respiratoires infectieuses (Bancej), Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Ottawa (Ontario); Bureau des programmes et de la planification en biosécurité (Atchessi), Centre de la biosûreté, Direction générale de l'infrastructure de sûreté sanitaire, Agence de la santé publique du Canada, Ottawa (Ontario)
| | - Ainsley Otten
- Division des sciences des risques pour la santé publique (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), Laboratoire national de microbiologie, Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Guelph (Ontario) et Saint-Hyacinthe (Québec); Centre de l'immunisation et des maladies respiratoires infectieuses (Bancej), Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Ottawa (Ontario); Bureau des programmes et de la planification en biosécurité (Atchessi), Centre de la biosûreté, Direction générale de l'infrastructure de sûreté sanitaire, Agence de la santé publique du Canada, Ottawa (Ontario)
| | - Nicole Atchessi
- Division des sciences des risques pour la santé publique (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), Laboratoire national de microbiologie, Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Guelph (Ontario) et Saint-Hyacinthe (Québec); Centre de l'immunisation et des maladies respiratoires infectieuses (Bancej), Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Ottawa (Ontario); Bureau des programmes et de la planification en biosécurité (Atchessi), Centre de la biosûreté, Direction générale de l'infrastructure de sûreté sanitaire, Agence de la santé publique du Canada, Ottawa (Ontario)
| | - Nicholas H Ogden
- Division des sciences des risques pour la santé publique (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), Laboratoire national de microbiologie, Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Guelph (Ontario) et Saint-Hyacinthe (Québec); Centre de l'immunisation et des maladies respiratoires infectieuses (Bancej), Direction générale de la prévention et du contrôle des maladies infectieuses, Agence de la santé publique du Canada, Ottawa (Ontario); Bureau des programmes et de la planification en biosécurité (Atchessi), Centre de la biosûreté, Direction générale de l'infrastructure de sûreté sanitaire, Agence de la santé publique du Canada, Ottawa (Ontario)
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Han S, Hickling GJ, Ogden NH, Ginsberg HS, Kobbekaduwa V, Rulison EL, Beati L, Tsao JI. Seasonality of acarological risk of exposure to Borrelia miyamotoi from questing life stages of Ixodes scapularis collected from Wisconsin and Massachusetts, USA. Ticks Tick Borne Dis 2020; 12:101556. [PMID: 33035757 DOI: 10.1016/j.ttbdis.2020.101556] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 08/29/2020] [Accepted: 08/31/2020] [Indexed: 11/28/2022]
Abstract
Measures of acarological risk of exposure to Ixodes scapularis-borne disease agents typically focus on nymphs; however, the relapsing fever group spirochete Borrelia miyamotoi can be passed transovarially, and I. scapularis larvae are capable of transmitting B. miyamotoi to their hosts. To quantify the larval contribution to acarological risk, relative to nymphs and adults, we collected questing I. scapularis for 3 yr at Fort McCoy, Wisconsin (WI, n = 23,367 ticks), and Cape Cod, Massachusetts (MA, n = 4190) in the United States. Borrelia miyamotoi infection prevalence was estimated for I. scapularis larvae, nymphs, females, and males, respectively, as 0.88, 2.05, 0.63, and 1.22 % from the WI site and 0.33, 2.32, 2.83, and 2.11 % from the MA site. Densities of B. miyamotoi-infected ticks (DIT, per 1000 m2) were estimated for larvae, nymphs, females, and males, respectively, as 0.36, 0.14, 0.01, and 0.03 from the WI site and 0.05, 0.06, 0.03, and 0.02 from the MA site. Thus, although larval infection prevalence with B. miyamotoi was significantly lower than that of nymphs and similar to that of adults, because of their higher abundance, the larval contribution to the overall DIT was similar to that of nymphs and trended towards a greater contribution than adults. Assuming homogenous contact rates with humans, these results suggest that eco-epidemiological investigations of B. miyamotoi disease in North America should include larvae. A fuller appreciation of the epidemiological implications of these results, therefore, requires an examination of the heterogeneity in contact rates with humans among life stages.
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Affiliation(s)
- Seungeun Han
- Comparative Medicine and Integrative Biology program, College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, United States.
| | - Graham J Hickling
- Center for Wildlife Health, University of Tennessee Institute of Agriculture, Knoxville, TN 37996, United States.
| | - Nicholas H Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, St-Hyacinthe, QC J2S 2M2, Canada.
| | - Howard S Ginsberg
- U.S. Geological Survey, Patuxent Wildlife Research Center, Kingston, RI 02881, United States.
| | - Vishvapali Kobbekaduwa
- Comparative Medicine and Integrative Biology program, College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, United States.
| | - Eric L Rulison
- California Department of Transportation, Redding, CA 96001, United States.
| | - Lorenza Beati
- Department of Biology, Georgia Southern University, Statesboro, GA 30460, United States.
| | - Jean I Tsao
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, 48824, United States; Department of Large Animal Clinical Sciences, Michigan State University, East Lansing, MI, 48824, United States.
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Ng V, Fazil A, Waddell LA, Bancej C, Turgeon P, Otten A, Atchessi N, Ogden NH. Projected effects of nonpharmaceutical public health interventions to prevent resurgence of SARS-CoV-2 transmission in Canada. CMAJ 2020; 192:E1053-E1064. [PMID: 32778573 PMCID: PMC7513947 DOI: 10.1503/cmaj.200990] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/21/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Continual efforts to eliminate community transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will be needed to prevent additional waves of infection. We explored the impact of nonpharmaceutical interventions on projected SARS-CoV-2 transmission in Canada. METHODS We developed an age-structured agent-based model of the Canadian population simulating the impact of current and projected levels of public health interventions on SARS-CoV-2 transmission. Interventions included case detection and isolation, contact tracing and quarantine, physical distancing and community closures, evaluated alone and in combination. RESULTS Without any interventions, 64.6% (95% credible interval [CrI] 63.9%-65.0%) of Canadians will be infected with SARS-CoV-2 (total attack rate) and 3.6% (95% CrI 2.4%-3.8%) of those infected and symptomatic will die. If case detection and contact tracing continued at baseline levels without maintained physical distancing and reimplementation of restrictive measures, this combination brought the total attack rate to 56.1% (95% CrI 0.05%-57.1%), but it dropped to 0.4% (95% CrI 0.03%-23.5%) with enhanced case detection and contact tracing. Combining the latter scenario with maintained physical distancing reduced the total attack rate to 0.2% (95% CrI 0.03%-1.7%) and was the only scenario that consistently kept hospital and intensive care unit bed use under capacity, prevented nearly all deaths and eliminated the epidemic. Extending school closures had minimal effects but did reduce transmission in schools; however, extending closures of workplaces and mixed-age venues markedly reduced attack rates and usually or always eliminated the epidemic under any scenario. INTERPRETATION Controlling SARS-CoV-2 transmission will depend on enhancing and maintaining interventions at both the community and individual levels. Without such interventions, a resurgent epidemic will occur, with the risk of overwhelming our health care systems.
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Affiliation(s)
- Victoria Ng
- Public Health Risk Sciences Division (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ont., and St. Hyacinthe, Que.; Centre for Immunization and Respiratory Infectious Diseases (Bancej), Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Ottawa, Ont.; Office of Biosecurity Programs and Planning (Atchessi), Centre for Biosecurity, Health Security Infrastructure Branch, Public Health Agency of Canada, Ottawa, Ont.
| | - Aamir Fazil
- Public Health Risk Sciences Division (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ont., and St. Hyacinthe, Que.; Centre for Immunization and Respiratory Infectious Diseases (Bancej), Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Ottawa, Ont.; Office of Biosecurity Programs and Planning (Atchessi), Centre for Biosecurity, Health Security Infrastructure Branch, Public Health Agency of Canada, Ottawa, Ont
| | - Lisa A Waddell
- Public Health Risk Sciences Division (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ont., and St. Hyacinthe, Que.; Centre for Immunization and Respiratory Infectious Diseases (Bancej), Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Ottawa, Ont.; Office of Biosecurity Programs and Planning (Atchessi), Centre for Biosecurity, Health Security Infrastructure Branch, Public Health Agency of Canada, Ottawa, Ont
| | - Christina Bancej
- Public Health Risk Sciences Division (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ont., and St. Hyacinthe, Que.; Centre for Immunization and Respiratory Infectious Diseases (Bancej), Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Ottawa, Ont.; Office of Biosecurity Programs and Planning (Atchessi), Centre for Biosecurity, Health Security Infrastructure Branch, Public Health Agency of Canada, Ottawa, Ont
| | - Patricia Turgeon
- Public Health Risk Sciences Division (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ont., and St. Hyacinthe, Que.; Centre for Immunization and Respiratory Infectious Diseases (Bancej), Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Ottawa, Ont.; Office of Biosecurity Programs and Planning (Atchessi), Centre for Biosecurity, Health Security Infrastructure Branch, Public Health Agency of Canada, Ottawa, Ont
| | - Ainsley Otten
- Public Health Risk Sciences Division (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ont., and St. Hyacinthe, Que.; Centre for Immunization and Respiratory Infectious Diseases (Bancej), Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Ottawa, Ont.; Office of Biosecurity Programs and Planning (Atchessi), Centre for Biosecurity, Health Security Infrastructure Branch, Public Health Agency of Canada, Ottawa, Ont
| | - Nicole Atchessi
- Public Health Risk Sciences Division (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ont., and St. Hyacinthe, Que.; Centre for Immunization and Respiratory Infectious Diseases (Bancej), Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Ottawa, Ont.; Office of Biosecurity Programs and Planning (Atchessi), Centre for Biosecurity, Health Security Infrastructure Branch, Public Health Agency of Canada, Ottawa, Ont
| | - Nicholas H Ogden
- Public Health Risk Sciences Division (Ng, Fazil, Waddell, Turgeon, Otten, Ogden), National Microbiology Laboratory, Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Guelph, Ont., and St. Hyacinthe, Que.; Centre for Immunization and Respiratory Infectious Diseases (Bancej), Infectious Disease Prevention and Control Branch, Public Health Agency of Canada, Ottawa, Ont.; Office of Biosecurity Programs and Planning (Atchessi), Centre for Biosecurity, Health Security Infrastructure Branch, Public Health Agency of Canada, Ottawa, Ont
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Slatculescu AM, Clow KM, McKay R, Talbot B, Logan JJ, Thickstun CR, Jardine CM, Ogden NH, Knudby AJ, Kulkarni MA. Species distribution models for the eastern blacklegged tick, Ixodes scapularis, and the Lyme disease pathogen, Borrelia burgdorferi, in Ontario, Canada. PLoS One 2020; 15:e0238126. [PMID: 32915794 PMCID: PMC7485816 DOI: 10.1371/journal.pone.0238126] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 08/10/2020] [Indexed: 12/31/2022] Open
Abstract
The blacklegged tick, Ixodes scapularis, is established in several regions of Ontario, Canada, and continues to spread into new geographic areas across the province at a rapid rate. This poses a significant public health risk since I. scapularis transmits the Lyme disease-causing bacterium, Borrelia burgdorferi, and other pathogens of potential public health concern. The objective of this study was to develop species distribution models for I. scapularis and B. burgdorferi to predict and compare the potential distributions of the tick vector and the Lyme disease pathogen as well as the ecological factors most important for species establishment. Ticks were collected via tick dragging at 120 sites across southern, central, and eastern Ontario between 2015 and 2018 and tested for tick-borne pathogens. A maximum entropy (Maxent) approach was used to model the potential distributions of I. scapularis and B. burgdorferi. Two independent datasets derived from tick dragging at 25 new sites in 2019 and ticks submitted by the public to local health units between 2015 and 2017 were used to validate the predictive accuracy of the models. The model for I. scapularis showed high suitability for blacklegged ticks in eastern Ontario and some regions along the shorelines of the Great Lakes, and moderate suitability near Algonquin Provincial Park and the Georgian Bay with good predictive accuracy (tick dragging 2019: AUC = 0.898; ticks from public: AUC = 0.727). The model for B. burgdorferi showed a similar predicted distribution but was more constrained to eastern Ontario, particularly between Ottawa and Kingston, and along Lake Ontario, with similarly good predictive accuracy (tick dragging 2019: AUC = 0.958; ticks from public: AUC = 0.863. The ecological variables most important for predicting the distributions of I. scapularis and B. burgdorferi included elevation, distance to deciduous and coniferous forest, proportions of agricultural land, water, and infrastructure, mean summer/spring temperature, and cumulative annual degree days above 0°C. Our study presents a novel application of species distribution modelling for I. scapularis and B. burgdorferi in Ontario, Canada, and provides an up to date projection of their potential distributions for public health knowledge users.
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Affiliation(s)
| | - Katie M. Clow
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
| | - Roman McKay
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Benoit Talbot
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - James J. Logan
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Charles R. Thickstun
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Claire M. Jardine
- Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
- Canadian Wildlife Health Cooperative, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
| | - Nicholas H. Ogden
- Public Health Risk Sciences Division, National Microbiology Laboratory, Public Health Agency of Canada, Saint-Hyacinthe, Quebec, Canada
| | - Anders J. Knudby
- Department of Geography, Environment, and Geomatics, University of Ottawa, Ottawa, Ontario, Canada
| | - Manisha A. Kulkarni
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
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50
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Khan SU, Ogden NH, Fazil AA, Gachon PH, Dueymes GU, Greer AL, Ng V. Current and Projected Distributions of Aedes aegypti and Ae. albopictus in Canada and the U.S. Environ Health Perspect 2020; 128:57007. [PMID: 32441995 PMCID: PMC7263460 DOI: 10.1289/ehp5899] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
BACKGROUND Aedes aegypti and Ae. albopictus are mosquito vectors of more than 22 arboviruses that infect humans. OBJECTIVES Our objective was to develop regional ecological niche models for Ae. aegypti and Ae. albopictus in the conterminous United States and Canada with current observed and simulated climate and land-use data using boosted regression trees (BRTs). METHODS We used BRTs to assess climatic suitability for Ae. albopictus and Ae. aegypti mosquitoes in Canada and the United States under current and future projected climates. RESULTS Models for both species were mostly influenced by minimum daily temperature and demonstrated high accuracy for predicting their geographic ranges under the current climate. The northward range expansion of suitable niches for both species was projected under future climate models. Much of the United States and parts of southern Canada are projected to be suitable for both species by 2100, with Ae. albopictus projected to expand its range north earlier this century and further north than Ae. aegypti. DISCUSSION Our projections suggest that the suitable ecological niche for Aedes will expand with climate change in Canada and the United States, thus increasing the risk of Aedes-transmitted arboviruses. Increased surveillance for these vectors and the pathogens they carry would be prudent. https://doi.org/10.1289/EHP5899.
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Affiliation(s)
- Salah Uddin Khan
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
- National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario, and Saint-Hyacinthe, Québec, Canada
| | - Nicholas H. Ogden
- National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario, and Saint-Hyacinthe, Québec, Canada
| | - Aamir A. Fazil
- National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario, and Saint-Hyacinthe, Québec, Canada
| | - Philippe H. Gachon
- Étude et Simulation du Climat à l’Échelle Régionale centre, Université du Québec à Montréal, Québec, Canada
| | - Guillaume U. Dueymes
- Étude et Simulation du Climat à l’Échelle Régionale centre, Université du Québec à Montréal, Québec, Canada
| | - Amy L. Greer
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
| | - Victoria Ng
- National Microbiology Laboratory, Public Health Agency of Canada, Guelph, Ontario, and Saint-Hyacinthe, Québec, Canada
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