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Chen Y, Li N, Lourenço J, Wang L, Cazelles B, Dong L, Li B, Liu Y, Jit M, Bosse NI, Abbott S, Velayudhan R, Wilder-Smith A, Tian H, Brady OJ. Measuring the effects of COVID-19-related disruption on dengue transmission in southeast Asia and Latin America: a statistical modelling study. THE LANCET. INFECTIOUS DISEASES 2022; 22:657-667. [PMID: 35247320 PMCID: PMC8890758 DOI: 10.1016/s1473-3099(22)00025-1] [Citation(s) in RCA: 60] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 11/10/2021] [Accepted: 01/07/2022] [Indexed: 01/19/2023]
Abstract
BACKGROUND The COVID-19 pandemic has resulted in unprecedented disruption to society, which indirectly affects infectious disease dynamics. We aimed to assess the effects of COVID-19-related disruption on dengue, a major expanding acute public health threat, in southeast Asia and Latin America. METHODS We assembled data on monthly dengue incidence from WHO weekly reports, climatic data from ERA5, and population variables from WorldPop for 23 countries between January, 2014 and December, 2019 and fit a Bayesian regression model to explain and predict seasonal and multi-year dengue cycles. We compared model predictions with reported dengue data January to December, 2020, and assessed if deviations from projected incidence since March, 2020 are associated with specific public health and social measures (from the Oxford Coronavirus Government Response Tracer database) or human movement behaviours (as measured by Google mobility reports). FINDINGS We found a consistent, prolonged decline in dengue incidence across many dengue-endemic regions that began in March, 2020 (2·28 million cases in 2020 vs 4·08 million cases in 2019; a 44·1% decrease). We found a strong association between COVID-19-related disruption (as measured independently by public health and social measures and human movement behaviours) and reduced dengue risk, even after taking into account other drivers of dengue cycles including climatic and host immunity (relative risk 0·01-0·17, p<0·01). Measures related to the closure of schools and reduced time spent in non-residential areas had the strongest evidence of association with reduced dengue risk, but high collinearity between covariates made specific attribution challenging. Overall, we estimate that 0·72 million (95% CI 0·12-1·47) fewer dengue cases occurred in 2020 potentially attributable to COVID-19-related disruption. INTERPRETATION In most countries, COVID-19-related disruption led to historically low dengue incidence in 2020. Continuous monitoring of dengue incidence as COVID-19-related restrictions are relaxed will be important and could give new insights into transmission processes and intervention options. FUNDING National Key Research and Development Program of China and the Medical Research Council.
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Affiliation(s)
- Yuyang Chen
- State Key Laboratory of Remote Sensing Science, Center for Global Change and Public Health, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Naizhe Li
- State Key Laboratory of Remote Sensing Science, Center for Global Change and Public Health, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China; MOE Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing, China
| | - José Lourenço
- Biosystems and Integrative Sciences Institute, University of Lisbon, Lisbon, Portugal
| | - Lin Wang
- Department of Genetics, University of Cambridge, Cambridge, UK; Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, UMR2000, CNRS, Paris, France
| | - Bernard Cazelles
- Institut de Biologie de l'École Normale Supérieure UMR8197, Eco-Evolutionary Mathematics, École Normale Supérieure, Paris, France; Unité Mixte Internationnale 209, Mathematical and Computational Modeling of Complex Systems, Sorbonne Université, Paris, France
| | - Lu Dong
- MOE Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, Beijing, China
| | - Bingying Li
- State Key Laboratory of Remote Sensing Science, Center for Global Change and Public Health, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Yang Liu
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Mark Jit
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Nikos I Bosse
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Sam Abbott
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Raman Velayudhan
- Department of Control of Neglected Tropical Diseases, WHO, Geneva, Switzerland
| | - Annelies Wilder-Smith
- Department of Disease Control, London School of Hygiene & Tropical Medicine, London, UK; Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany
| | - Huaiyu Tian
- State Key Laboratory of Remote Sensing Science, Center for Global Change and Public Health, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China.
| | - Oliver J Brady
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.
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Sanchez-Gendriz I, de Souza GF, de Andrade IGM, Neto ADD, de Medeiros Tavares A, Barros DMS, de Morais AHF, Galvão-Lima LJ, de Medeiros Valentim RA. Data-driven computational intelligence applied to dengue outbreak forecasting: a case study at the scale of the city of Natal, RN-Brazil. Sci Rep 2022; 12:6550. [PMID: 35449179 PMCID: PMC9023501 DOI: 10.1038/s41598-022-10512-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Accepted: 04/08/2022] [Indexed: 01/01/2023] Open
Abstract
Dengue is recognized as a health problem that causes significant socioeconomic impacts throughout the world, affecting millions of people each year. A commonly used method for monitoring the dengue vector is to count the eggs that Aedes aegypti mosquitoes have laid in spatially distributed ovitraps. Given this approach, the present study uses a database collected from 397 ovitraps allocated across the city of Natal, RN—Brazil. The Egg Density Index for each neighborhood was computed weekly, over four complete years (from 2016 to 2019), and simultaneously analyzed with the dengue case incidence. Our results illustrate that the incidence of dengue is related to the socioeconomic level of the neighborhoods in the city of Natal. A deep learning algorithm was used to predict future dengue case incidence, either based on the previous weeks of dengue incidence or the number of eggs present in the ovitraps. The analysis reveals that ovitrap data allows earlier prediction (four to six weeks) compared to dengue incidence itself (one week). Therefore, the results validate that the quantification of Aedes aegypti eggs can be valuable for the early planning of public health interventions.
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Affiliation(s)
- Ignacio Sanchez-Gendriz
- Laboratory for Technological Innovation in Health (LAIS), Hospital Universitário Onofre Lopes, Federal University of Rio Grande Do Norte (UFRN), Natal, Rio Grande do Norte, Brazil. .,Department of Computer Engineering and Automation, UFRN, Natal, Rio Grande do Norte, Brazil.
| | - Gustavo Fontoura de Souza
- Advanced Nucleus of Technological Innovation (NAVI), Federal Institute of Rio Grande Do Norte (IFRN), Natal, Rio Grande do Norte, Brazil
| | - Ion G M de Andrade
- Laboratory for Technological Innovation in Health (LAIS), Hospital Universitário Onofre Lopes, Federal University of Rio Grande Do Norte (UFRN), Natal, Rio Grande do Norte, Brazil
| | | | | | - Daniele M S Barros
- Laboratory for Technological Innovation in Health (LAIS), Hospital Universitário Onofre Lopes, Federal University of Rio Grande Do Norte (UFRN), Natal, Rio Grande do Norte, Brazil
| | - Antonio Higor Freire de Morais
- Advanced Nucleus of Technological Innovation (NAVI), Federal Institute of Rio Grande Do Norte (IFRN), Natal, Rio Grande do Norte, Brazil
| | - Leonardo J Galvão-Lima
- Laboratory for Technological Innovation in Health (LAIS), Hospital Universitário Onofre Lopes, Federal University of Rio Grande Do Norte (UFRN), Natal, Rio Grande do Norte, Brazil
| | - Ricardo Alexsandro de Medeiros Valentim
- Laboratory for Technological Innovation in Health (LAIS), Hospital Universitário Onofre Lopes, Federal University of Rio Grande Do Norte (UFRN), Natal, Rio Grande do Norte, Brazil
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Huang JF, Zhao ZY, Lu WK, Rui J, Deng B, Liu WK, Yang TL, Li ZY, Li PH, Liu C, Luo L, Zhao B, Wang YF, Li Q, Wang MZ, Chen TM. Correlation between mumps and meteorological factors in Xiamen City, China: A modelling study. Infect Dis Model 2022; 7:127-137. [PMID: 35573860 PMCID: PMC9062423 DOI: 10.1016/j.idm.2022.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/18/2022] [Accepted: 04/18/2022] [Indexed: 11/26/2022] Open
Abstract
Objective Mumps is a seasonal infectious disease, always occurring in winter and spring. In this study, we aim to analyze its epidemiological characteristics, transmissibility, and its correlation with meteorological variables. Method A seasonal Susceptible–Exposed–Infectious/Asymptomatic–Recovered model and a next-generation matrix method were applied to estimate the time-dependent reproduction number (Rt). Results The seasonal double peak of annual incidence was mainly in May to July and November to December. There was high transmission at the median of Rt = 1.091 (ranged: 0 to 4.393). Rt was seasonally distributed mainly from February to April and from September to November. Correlations were found between temperature (Pearson correlation coefficient [r] ranged: from 0.101 to 0.115), average relative humidity (r = 0.070), average local pressure (r = -0.066), and the number of new cases. In addition, average local pressure (r = 0.188), average wind speed (r = 0.111), air temperature (r ranged: -0.128 to -0.150), average relative humidity (r = -0.203) and sunshine duration (r = -0.075) were all correlated with Rt. Conclusion A relatively high level of transmissibility has been found in Xiamen City, leading to a continuous epidemic of mumps. Meteorological factors, especially air temperature and relative humidity, may be more closely associated with mumps than other factors.
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Douwes‐Schultz D, Schmidt AM. Zero‐state coupled Markov switching count models for spatio‐temporal infectious disease spread. J R Stat Soc Ser C Appl Stat 2022. [DOI: 10.1111/rssc.12547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Dirk Douwes‐Schultz
- Department of Epidemiology Biostatistics and Occupational Health McGill University Montreal QC Canada
| | - Alexandra M. Schmidt
- Department of Epidemiology Biostatistics and Occupational Health McGill University Montreal QC Canada
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Surendran SN, Nagulan R, Sivabalakrishnan K, Arthiyan S, Tharsan A, Jayadas TTP, Raveendran S, Kumanan T, Ramasamy R. Reduced dengue incidence during the COVID-19 movement restrictions in Sri Lanka from March 2020 to April 2021. BMC Public Health 2022; 22:388. [PMID: 35209890 PMCID: PMC8866919 DOI: 10.1186/s12889-022-12726-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 02/07/2022] [Indexed: 02/07/2023] Open
Abstract
Background Dengue is the major mosquito-borne disease in Sri Lanka. After its first detection in January 2020, COVID-19 has become the major health issue in Sri Lanka. The impact of public health measures, notably restrictions on movement of people to curb COVID-19 transmission, on the incidence of dengue during the period March 2020 to April 2021 was investigated. Methods The incidence of dengue and COVID-19, rainfall and the public movement restrictions implemented to contain COVID-19 transmission were obtained from Sri Lanka government sources. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to predict the monthly dengue incidence from March 2020 to April 2021 for each of the country’s 25 districts based on five years of pre-pandemic data, and compared with the actual recorded incidence of dengue during this period. Ovitrap collections of Aedes larvae were performed in Jaffna city in the Jaffna district from August 2020 to April 2021 and the findings compared with similar collections made in the pre-pandemic period from March 2019 to December 2019. Results The recorded numbers of dengue cases for every month from March 2020 to April 2021 in the whole country and for all 25 districts over the same period were lower than the numbers of dengue cases predicted from data for the five years (2015–2019) immediately preceding the COVID-19 pandemic. The number of dengue cases recorded nationwide represented a 74% reduction from the predicted number of dengue cases for the March 2020 to April 2021 period. The numbers of Aedes larvae collected from ovitraps per month were reduced by 88.6% with a lower proportion of Ae. aegypti than Ae. albopictus in Jaffna city from August 2020 until April 2021 compared with March 2019 to December 2019. Conclusion Public health measures that restricted movement of people, closed schools, universities and offices to contain COVID-19 transmission unexpectedly led to a significant reduction in the reported numbers of dengue cases in Sri Lanka. This contrasts with findings reported from Singapore. The differences between the two tropical islands have significant implications for the epidemiology of dengue. Reduced access to blood meals and lower vector densities, particularly of Ae. aegypti, resulting from the restrictions on movement of people, are suggested to have contributed to the lower dengue incidence in Sri Lanka. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-12726-8.
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Affiliation(s)
- S N Surendran
- Department of Zoology, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka.
| | - R Nagulan
- Faculty of Applied Science, University of Vavuniya, Vavuniya, Sri Lanka
| | - K Sivabalakrishnan
- Department of Zoology, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka
| | - S Arthiyan
- Department of Zoology, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka
| | - A Tharsan
- Department of Zoology, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka
| | - T T P Jayadas
- Department of Zoology, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka
| | - S Raveendran
- Department of Geography, Faculty of Arts, University of Jaffna, Jaffna, Sri Lanka
| | - T Kumanan
- Department of Medicine, Faculty of Medicine, University of Jaffna, Jaffna, Sri Lanka
| | - R Ramasamy
- Department of Zoology, Faculty of Science, University of Jaffna, Jaffna, Sri Lanka.
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Romeo-Aznar V, Picinini Freitas L, Gonçalves Cruz O, King AA, Pascual M. Fine-scale heterogeneity in population density predicts wave dynamics in dengue epidemics. Nat Commun 2022; 13:996. [PMID: 35194017 PMCID: PMC8864019 DOI: 10.1038/s41467-022-28231-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Accepted: 01/12/2022] [Indexed: 02/05/2023] Open
Abstract
The spread of dengue and other arboviruses constitutes an expanding global health threat. The extensive heterogeneity in population distribution and potential complexity of movement in megacities of low and middle-income countries challenges predictive modeling, even as its importance to disease spread is clearer than ever. Using surveillance data at fine resolution from Rio de Janeiro, we document a scale-invariant pattern in the size of successive epidemics following DENV4 emergence. Using surveillance data at fine resolution following the emergence of the DENV4 dengue serotype in Rio de Janeiro, we document a pattern in the size of successive epidemics that is invariant to the scale of spatial aggregation. This pattern emerges from the combined effect of herd immunity and seasonal transmission, and is strongly driven by variation in population density at sub-kilometer scales. It is apparent only when the landscape is stratified by population density and not by spatial proximity as has been common practice. Models that exploit this emergent simplicity should afford improved predictions of the local size of successive epidemic waves.
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Affiliation(s)
- Victoria Romeo-Aznar
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
- Departamento de Ecología, Genética y Evolución, and Instituto IEGEBA (CONICET-UBA), Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, C1428EHA, Buenos Aires, Argentina
- Mansueto Institute for Urban Innovation, The University of Chicago, Chicago, IL, USA
| | - Laís Picinini Freitas
- Postgraduate Program of Epidemiology in Public Health - Escola Nacional de Saúde Pública Sergio Arouca - Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
- Programa de Computação Científica - Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | | | - Aaron A King
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA
- Center for the Study of Complex Systems, University of Michigan, Ann Arbor, MI, USA
- The Santa Fe Institute, Santa Fe, NM, USA
| | - Mercedes Pascual
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA.
- The Santa Fe Institute, Santa Fe, NM, USA.
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Dengue virus infection modifies mosquito blood-feeding behavior to increase transmission to the host. Proc Natl Acad Sci U S A 2022; 119:2117589119. [PMID: 35012987 PMCID: PMC8785958 DOI: 10.1073/pnas.2117589119] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/23/2021] [Indexed: 12/16/2022] Open
Abstract
Because dengue viruses are spread by mosquitoes during biting, transmission capacity depends on mosquito-biting behavior. For this reason, it is critical to understand how infection in mosquitoes influences biting. To answer this question, we deployed a multidisciplinary approach including high-resolution, multivariate biting behavior monitoring on mice, in vivo transmission assay, and mathematical modeling. We demonstrated that infected mosquitoes are more attracted to mice and bite more often to get the same amount of blood as uninfected mosquitoes. While the effect of increased attraction to host on transmission capacity is trivial, we showed that increased number of bites results in successive transmission. Eventually, we calculated that the infection-induced behavior changes tripled transmission capacity of mosquitoes. Mosquito blood-feeding behavior is a key determinant of the epidemiology of dengue viruses (DENV), the most-prevalent mosquito-borne viruses. However, despite its importance, how DENV infection influences mosquito blood-feeding and, consequently, transmission remains unclear. Here, we developed a high-resolution, video-based assay to observe the blood-feeding behavior of Aedes aegypti mosquitoes on mice. We then applied multivariate analysis on the high-throughput, unbiased data generated from the assay to ordinate behavioral parameters into complex behaviors. We showed that DENV infection increases mosquito attraction to the host and hinders its biting efficiency, the latter resulting in the infected mosquitoes biting more to reach similar blood repletion as uninfected mosquitoes. To examine how increased biting influences DENV transmission to the host, we established an in vivo transmission model with immuno-competent mice and demonstrated that successive short probes result in multiple transmissions. Finally, to determine how DENV-induced alterations of host-seeking and biting behaviors influence dengue epidemiology, we integrated the behavioral data within a mathematical model. We calculated that the number of infected hosts per infected mosquito, as determined by the reproduction rate, tripled when mosquito behavior was influenced by DENV infection. Taken together, this multidisciplinary study details how DENV infection modulates mosquito blood-feeding behavior to increase vector capacity, proportionally aggravating DENV epidemiology. By elucidating the contribution of mosquito behavioral alterations on DENV transmission to the host, these results will inform epidemiological modeling to tailor improved interventions against dengue.
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Selvarajoo S, Liew JWK, Chua TH, Tan W, Zaki RA, Ngui R, Sulaiman WYW, Ong PS, Vythilingam I. Dengue surveillance using gravid oviposition sticky (GOS) trap and dengue non-structural 1 (NS1) antigen test in Malaysia: randomized controlled trial. Sci Rep 2022; 12:571. [PMID: 35022501 PMCID: PMC8755775 DOI: 10.1038/s41598-021-04643-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 12/29/2021] [Indexed: 11/09/2022] Open
Abstract
Dengue remains a major public threat and existing dengue control/surveillance programs lack sensitivity and proactivity. More efficient methods are needed. A cluster randomized controlled trial was conducted for 18 months to determine the efficacy of using a combination of gravid oviposition sticky (GOS) traps and dengue non-structural 1 (NS1) antigen for early surveillance of dengue among Aedes mosquito. Eight residential apartments were randomly assigned into intervention and control groups. GOS traps were placed at the intervention apartments weekly to trap Aedes mosquitoes and these tested for dengue NS1 antigen. When dengue-positive pool was detected, the community were notified and advised to execute protective measures. Fewer dengue cases were recorded in the intervention group than the control. Detection of NS1-positive mosquitoes was significantly associated with GOS Aedes index (rs = 0.68, P < 0.01) and occurrence of dengue cases (rs = 0.31, P < 0.01). Participants' knowledge, attitude, and practice (KAP) toward dengue control indicated significant improvement for knowledge (P < 0.01), practice (P < 0.01) and total scores (P < 0.01). Most respondents thought this surveillance method is good (81.2%) and supported its use nationwide. Thus, GOS trap and dengue NS1 antigen test can supplement the current dengue surveillance/control, in alignment with the advocated integrated vector management for reducing Aedes-borne diseases.
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Affiliation(s)
- Sivaneswari Selvarajoo
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
| | - Jonathan Wee Kent Liew
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, 50603, Kuala Lumpur, Malaysia.,Enviromental Health Institute, National Environment Agency, Singapore, 569874, Singapore
| | - Tock H Chua
- Department of Pathobiology and Medical Diagnostics, Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, 88400, Kota Kinabalu, Sabah, Malaysia
| | - Wing Tan
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
| | - Rafdzah Ahmad Zaki
- Department of Social and Preventive Medicine, Faculty of Medicine, Centre for Epidemiology and Evidence Based Practice, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
| | - Romano Ngui
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
| | - Wan Yusoff Wan Sulaiman
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, 50603, Kuala Lumpur, Malaysia
| | - Poo Soon Ong
- Petaling Jaya City Council, 46675, Petaling Jaya, Selangor, Malaysia
| | - Indra Vythilingam
- Department of Parasitology, Faculty of Medicine, Universiti Malaya, 50603, Kuala Lumpur, Malaysia.
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Ferreira HDS, Nóbrega RS, Brito PVDS, Farias JP, Amorim JH, Moreira EBM, Mendez ÉC, Luiz WB. Impacts of El Niño Southern Oscillation on the dengue transmission dynamics in the Metropolitan Region of Recife, Brazil. Rev Soc Bras Med Trop 2022; 55:e0671. [PMID: 35674563 PMCID: PMC9176733 DOI: 10.1590/0037-8682-0671-2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Accepted: 04/13/2022] [Indexed: 11/28/2022] Open
Abstract
Background: This research addresses two questions: (1) how El Niño Southern Oscillation (ENSO) affects climate variability and how it influences dengue transmission in the Metropolitan Region of Recife (MRR), and (2) whether the epidemic in MRR municipalities has any connection and synchronicity. Methods: Wavelet analysis and cross-correlation were applied to characterize seasonality, multiyear cycles, and relative delays between the series. This study was developed into two distinct periods. Initially, we performed periodic dengue incidence and intercity epidemic synchronism analyses from 2001 to 2017. We then defined the period from 2001 to 2016 to analyze the periodicity of climatic variables and their coherence with dengue incidence. Results: Our results showed systematic cycles of 3-4 years with a recent shortening trend of 2-3 years. Climatic variability, such as positive anomalous temperatures and reduced rainfall due to changes in sea surface temperature (SST), is partially linked to the changing epidemiology of the disease, as this condition provides suitable environments for the Aedes aegypti lifecycle. Conclusion: ENSO may have influenced the dengue temporal patterns in the MRR, transiently reducing its main way of multiyear variability (3-4 years) to 2-3 years. Furthermore, when the epidemic coincided with El Niño years, it spread regionally and was highly synchronized.
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Affiliation(s)
| | - Ranyére Silva Nóbrega
- Universidade Federal de Pernambuco, Brasil; Universidade Federal de Campina Grande, Brasil
| | | | | | - Jaime Henrique Amorim
- Universidade Federal do Oeste da Bahia, Brasil; Universidade Estadual de Santa Cruz, Brasil
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Niraula P, Mateu J, Chaudhuri S. A Bayesian machine learning approach for spatio-temporal prediction of COVID-19 cases. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT : RESEARCH JOURNAL 2022; 36:2265-2283. [PMID: 35095341 PMCID: PMC8787453 DOI: 10.1007/s00477-021-02168-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/30/2021] [Indexed: 05/11/2023]
Abstract
Modeling the spread of infectious diseases in space and time needs to take care of complex dependencies and uncertainties. Machine learning methods, and neural networks, in particular, are useful in modeling this sort of complex problems, although they generally lack of probabilistic interpretations. We propose a neural network method embedded in a Bayesian framework for modeling and predicting the number of cases of infectious diseases in areal units. A key feature is that our combined model considers the impact of human movement on the spread of the infectious disease, as an additional random factor to the also considered spatial neighborhood and temporal correlation components. Our model is evaluated over a COVID-19 dataset for 245 health zones of Castilla-Leon (Spain). The results show that a Bayesian model informed by a neural network method is generally able to predict the number of cases of COVID-19 in both space and time, with the human mobility factor having a strong influence on the model, together with the number of infections and deaths in nearby areas.
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Affiliation(s)
- Poshan Niraula
- Department of Mathematics, University of Jaume I, Castellón, Spain
| | - Jorge Mateu
- Department of Mathematics, University of Jaume I, Castellón, Spain
| | - Somnath Chaudhuri
- Department of Mathematics, University of Jaume I, Castellón, Spain
- Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, Girona, Spain
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Yasri S, Wiwanitkit V. Getting dengue from vector mosquito bite at home: a reappraisal on chance based on molecular epidemiology data in Indochina. INTERNATIONAL JOURNAL OF MOLECULAR EPIDEMIOLOGY AND GENETICS 2021; 12:126-128. [PMID: 35126836 PMCID: PMC8784906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 12/14/2021] [Indexed: 06/14/2023]
Abstract
Dengue is an important vector borne viral infection. At present, it is endemic in many tropical countries. A molecular epidemiology of viral type in patients and mosquitoes can give useful epidemiology data for disease control. In Indochina, dengue is very common and the molecular epidemiology surveillance is continuously performed. Here, the authors reappraise on available local data from epidemiology studies of viral type in patients and mosquitoes in an endemic area of dengue in Indochina. According to analysis, the authors found that a considerable number of dengue patients do not have the same viral type with caught mosquito vector at their home. According to this study, a chance that a dengue patient gets pathogen from mosquito bite at home is 2.185%. The chance of getting dengue from the vector mosquito bite at home is not high. Hence, a public health policy to control of mosquito vector at home has to extend to universal control at any public places.
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Magnitude, Seasonal-variation, Serological and Hematological Profile of Dengue in a Tertiary Teaching Hospital, Karwar, India. JOURNAL OF PURE AND APPLIED MICROBIOLOGY 2021. [DOI: 10.22207/jpam.15.4.10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Dengue viral infection is the most widely spread arbo-viral disease in Indian subcontinent. High index of clinical suspicion especially during its peak season can be rewarding in diagnosing as well as early case management of anticipated DHF and DSS cases. To estimate the magnitude, seasonal-variation, serological as well as hematological aspects of dengue cases. This was a prospective observational study held in Microbiology and Hematology laboratories of our hospital for duration of one year from July-2019 to June-2020. All the suspected dengue cases were subjected to NS1-antigen, IgM and IgG antibody detection. The samples were also tested for platelet count, total count, haematocrit as well as hemoglobin estimation. All 1,550 dengue suspected cases were subjected to serological testing, among which 157 (10.1%) were positive. The most affected populations were the adult male. As the study was conducted for one year, we could observe the seasonal trend which peaked during post-monsoon. Out of 157 cases, 81.5%, 0.6% and 17.8% were determined as primary, secondary and old dengue cases respectively. There was a significant association between NS1 antigen and fever of </= 5 days duration with ‘p’ value< 0.00001. Thrombocytopenia, leucopenia and increased haematocrit were witnessed in 15.9%, 28.6% and 35% respectively. Our study shows that we had a high magnitude of primary cases that are prone to secondary dengue infection which might have a catastrophic effect giving rise to DHF, DSS or SD.
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Zhang T, Li J. Understanding and predicting the spatio-temporal spread of COVID-19 via integrating diffusive graph embedding and compartmental models. TRANSACTIONS IN GIS : TG 2021; 25:3025-3047. [PMID: 34512104 PMCID: PMC8420127 DOI: 10.1111/tgis.12803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
In order to find useful intervention strategies for the novel coronavirus (COVID-19), it is vital to understand how the disease spreads. In this study, we address the modeling of COVID-19 spread across space and time, which facilitates understanding of the pandemic. We propose a hybrid data-driven learning approach to capture the mobility-related spreading mechanism of infectious diseases, utilizing multi-sourced mobility and attributed data. This study develops a visual analytic approach that identifies and depicts the strength of the transmission pathways of COVID-19 between areal units by integrating data-driven deep learning and compartmental epidemic models, thereby engaging stakeholders (e.g., public health officials, managers from transportation agencies) to make informed intervention decisions and enable public messaging. A case study in the state of Colorado, USA was performed to demonstrate the applicability of the proposed transmission modeling approach in understanding the spatio-temporal spread of COVID-19 at the neighborhood level. Transmission path maps are presented and analyzed, demonstrating their utility in evaluating the effects of mitigation measures. In addition, integrated embeddings also support daily prediction of infected cases and role analysis of each area unit during the transmission of the virus.
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Affiliation(s)
- Tong Zhang
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote SensingWuhan UniversityWuhanChina
| | - Jing Li
- Department of Geography and the EnvironmentUniversity of DenverDenverCOUSA
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Jayadas TTP, Kumanan T, Gomes L, Jeewandara C, Malavige GN, Ranasinghe D, Jadi RS, Ramasamy R, Surendran SN. Regional Variation in Dengue Virus Serotypes in Sri Lanka and Its Clinical and Epidemiological Relevance. Diagnostics (Basel) 2021; 11:2084. [PMID: 34829432 PMCID: PMC8618005 DOI: 10.3390/diagnostics11112084] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 11/05/2021] [Accepted: 11/08/2021] [Indexed: 01/19/2023] Open
Abstract
Dengue is a significant health concern in Sri Lanka, but diagnosis of the infecting dengue virus (DENV) serotype has hitherto been largely restricted to the Colombo district in the western province. Salinity tolerant Aedes vectors are present in the island's northern Jaffna peninsula, which is undergoing rapid groundwater salinization. Virus serotypes were determined by RT-qPCR in 107 and 112 patients diagnosed by NS1 antigen positivity from the Jaffna district in 2018 and 2019, respectively, and related to clinical characteristics. DENV1 and DENV2 were the most common serotypes in both years. Infections with multiple serotypes were not detected. DENV1 was significantly more prevalent in 2019 than 2018, while DENV3 was significantly more prevalent in 2018 than 2019 among the Jaffna patients. Limited genomic sequencing identified DENV1 genotype-I and DENV3 genotype-I in Jaffna patients in 2018. Dengue was more prevalent in working age persons and males among the serotyped Jaffna patients. DENV1 and DENV2 were the predominant serotypes in 2019 in the Colombo district. However, DENV1 and DENV3 were significantly more prevalent in Colombo compared with Jaffna in 2019. The differences in the prevalence of DENV1 and DENV3 between the Jaffna and Colombo districts in 2019 have implications for dengue epidemiology and vaccination. Salinity-tolerant Aedes vector strains, widespread in the Jaffna peninsula, may have contributed to differences in serotype prevalence compared with the Colombo district in 2019. Significant associations were not identified between virus serotypes and clinical characteristics among Jaffna patients.
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Affiliation(s)
| | | | - Laksiri Gomes
- Centre for Dengue Research, Department of Immunology and Molecular Medicine, University of Sri Jayewardenepura, Nugegoda 10250, Sri Lanka; (L.G.); (C.J.); (G.N.M.); (D.R.)
| | - Chandima Jeewandara
- Centre for Dengue Research, Department of Immunology and Molecular Medicine, University of Sri Jayewardenepura, Nugegoda 10250, Sri Lanka; (L.G.); (C.J.); (G.N.M.); (D.R.)
| | - Gathsaurie N. Malavige
- Centre for Dengue Research, Department of Immunology and Molecular Medicine, University of Sri Jayewardenepura, Nugegoda 10250, Sri Lanka; (L.G.); (C.J.); (G.N.M.); (D.R.)
| | - Diyanath Ranasinghe
- Centre for Dengue Research, Department of Immunology and Molecular Medicine, University of Sri Jayewardenepura, Nugegoda 10250, Sri Lanka; (L.G.); (C.J.); (G.N.M.); (D.R.)
| | - Ramesh S. Jadi
- Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC 27599-7290, USA;
| | - Ranjan Ramasamy
- Department of Zoology, University of Jaffna, Jaffna 40000, Sri Lanka;
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Li C, Wu X, Sheridan S, Lee J, Wang X, Yin J, Han J. Interaction of climate and socio-ecological environment drives the dengue outbreak in epidemic region of China. PLoS Negl Trop Dis 2021; 15:e0009761. [PMID: 34606516 PMCID: PMC8489715 DOI: 10.1371/journal.pntd.0009761] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 08/24/2021] [Indexed: 11/18/2022] Open
Abstract
Transmission of dengue virus is a complex process with interactions between virus, mosquitoes and humans, influenced by multiple factors simultaneously. Studies have examined the impact of climate or socio-ecological factors on dengue, or only analyzed the individual effects of each single factor on dengue transmission. However, little research has addressed the interactive effects by multiple factors on dengue incidence. This study uses the geographical detector method to investigate the interactive effect of climate and socio-ecological factors on dengue incidence from two perspectives: over a long-time series and during outbreak periods; and surmised on the possibility of dengue outbreaks in the future. Results suggest that the temperature plays a dominant role in the long-time series of dengue transmission, while socio-ecological factors have great explanatory power for dengue outbreaks. The interactive effect of any two factors is greater than the impact of single factor on dengue transmission, and the interactions of pairs of climate and socio-ecological factors have more significant impact on dengue. Increasing temperature and surge in travel could cause dengue outbreaks in the future. Based on these results, three recommendations are offered regarding the prevention of dengue outbreaks: mitigating the urban heat island effect, adjusting the time and frequency of vector control intervention, and providing targeted health education to travelers at the border points. This study hopes to provide meaningful clues and a scientific basis for policymakers regarding effective interventions against dengue transmission, even during outbreaks.
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Affiliation(s)
- Chenlu Li
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Xiaoxu Wu
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
- Southern Marine Science and Engineering Guangdong Laboratory, Guangzhou, China
- * E-mail:
| | - Scott Sheridan
- Department of Geography, Kent State University, Kent, Ohio, United States of America
| | - Jay Lee
- Department of Geography, Kent State University, Kent, Ohio, United States of America
- College of Environment and Planning, Henan University, Kaifeng, China
| | - Xiaofeng Wang
- Center for Disease Surveillance and Information Services, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jie Yin
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
| | - Jiatong Han
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
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Sun H, Binder RA, Dickens B, de Sessions PF, Rabaa MA, Ho EXP, Cook AR, Carrillo FB, Monterrey JC, Kuan G, Balmaseda A, Ooi EE, Harris E, Sessions OM. Viral genome-based Zika virus transmission dynamics in a paediatric cohort during the 2016 Nicaragua epidemic. EBioMedicine 2021; 72:103596. [PMID: 34627081 PMCID: PMC8511802 DOI: 10.1016/j.ebiom.2021.103596] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 08/02/2021] [Accepted: 09/09/2021] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND Nicaragua experienced a large Zika epidemic in 2016, with up to 50% of the population in Managua infected. With the domesticated Aedes aegypti mosquito as its vector, it is widely assumed that Zika virus transmission occurs within the household and/or via human mobility. We investigated these assumptions by using viral genomes to trace Zika transmission spatially. METHODS We analysed serum samples from 119 paediatric Zika cases participating in the long-standing Paediatric Dengue Cohort Study in Managua, which was expanded to include Zika in 2015. An optimal spanning directed tree was constructed by minimizing the differences in viral sequence diversity composition between patient nodes, where low-frequency variants were used to increase the resolution of the inferred Zika outbreak dynamics. FINDINGS Out of the 18 houses where pairwise difference in sample collection dates among all the household members was within 30 days, we only found two where viruses from individuals within the same household were up to 10th-most closely linked to each other genetically. We also identified a substantial number of transmission events involving long geographical distances (n=30), as well as potential super-spreading events in the estimated transmission tree. INTERPRETATION Our finding highlights that community transmission, often involving long geographical distances, played a much more important role in epidemic spread than within-household transmission. FUNDING This study was supported by an NUS startup grant (OMS) and grants R01 AI099631 (AB), P01 AI106695 (EH), P01 AI106695-03S1 (FB), and U19 AI118610 (EH) from the US National Institutes of Health.
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Affiliation(s)
- Haoyang Sun
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Raquel A. Binder
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, CA, USA
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Borame Dickens
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | | | - Maia A. Rabaa
- The Hospital for Tropical Diseases, Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine, Nuffield Department of Medicine, Oxford University, Oxford, UK
| | | | - Alex R Cook
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Fausto Bustos Carrillo
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, CA, USA
- Sustainable Sciences Institute, Managua, Nicaragua
| | | | - Guillermina Kuan
- Sustainable Sciences Institute, Managua, Nicaragua
- Health Center Sócrates Flores Vivas, Ministry of Health, Managua, Nicaragua
| | - Angel Balmaseda
- Sustainable Sciences Institute, Managua, Nicaragua
- Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua
| | - Eng Eong Ooi
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Eva Harris
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, CA, USA
| | - October M. Sessions
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Department of Pharmacy, National University of Singapore, Singapore
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Fansiri T, Buddhari D, Pathawong N, Pongsiri A, Klungthong C, Iamsirithaworn S, Jones AR, Fernandez S, Srikiatkhachorn A, Rothman AL, Anderson KB, Thomas SJ, Endy TP, Ponlawat A. Entomological Risk Assessment for Dengue Virus Transmission during 2016-2020 in Kamphaeng Phet, Thailand. Pathogens 2021; 10:pathogens10101234. [PMID: 34684183 PMCID: PMC8538081 DOI: 10.3390/pathogens10101234] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 09/22/2021] [Accepted: 09/23/2021] [Indexed: 11/16/2022] Open
Abstract
Individual houses with high risks of dengue virus (DENV) transmission might be a source of virus transmission within the neighborhood. We conducted an entomological risk assessment for DENV transmission at the household level, comprising family cohort members residing in the same location, to assess the risk for dengue virus transmitted by mosquito vectors. The studies were conducted in Kamphaeng Phet Province, Thailand, during 2016-2020. Entomological investigations were performed in 35 cohort families on day 1 and day 14 after receiving dengue case reports. DENV was found in 22 Aedes samples (4.9%) out of 451 tested samples. A significantly higher DENV infection rate was detected in vectors collected on day 1 (6.64%) compared to those collected on day 14 (1.82%). Annual vector surveillance was carried out in 732 houses, with 1002 traps catching 3653 Aedes females. The majority of the 13,228 water containers examined were made from plastic and clay, with used tires serving as a primary container, with 59.55% larval abundance. Larval indices, as indicators of dengue epidemics and to evaluate disease and vector control approaches, were calculated. As a result, high values of larval indices indicated the considerably high risk of dengue transmission in these communities.
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Affiliation(s)
- Thanyalak Fansiri
- Department of Entomology, Armed Forces Research Institute of Medical Sciences (AFRIMS), Bangkok 10400, Thailand; (T.F.); (N.P.); (A.P.)
| | - Darunee Buddhari
- Department of Virology, Armed Forces Research Institute of Medical Sciences (AFRIMS), Bangkok 10400, Thailand; (D.B.); (C.K.); (A.R.J.); (S.F.)
| | - Nattaphol Pathawong
- Department of Entomology, Armed Forces Research Institute of Medical Sciences (AFRIMS), Bangkok 10400, Thailand; (T.F.); (N.P.); (A.P.)
| | - Arissara Pongsiri
- Department of Entomology, Armed Forces Research Institute of Medical Sciences (AFRIMS), Bangkok 10400, Thailand; (T.F.); (N.P.); (A.P.)
| | - Chonticha Klungthong
- Department of Virology, Armed Forces Research Institute of Medical Sciences (AFRIMS), Bangkok 10400, Thailand; (D.B.); (C.K.); (A.R.J.); (S.F.)
| | - Sopon Iamsirithaworn
- Department of Disease Control, Ministry of Public Health, Nonthaburi 11000, Thailand;
| | - Anthony R. Jones
- Department of Virology, Armed Forces Research Institute of Medical Sciences (AFRIMS), Bangkok 10400, Thailand; (D.B.); (C.K.); (A.R.J.); (S.F.)
| | - Stefan Fernandez
- Department of Virology, Armed Forces Research Institute of Medical Sciences (AFRIMS), Bangkok 10400, Thailand; (D.B.); (C.K.); (A.R.J.); (S.F.)
| | - Anon Srikiatkhachorn
- Faculty of Medicine, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand;
- Department of Cell and Molecular Biology, Institute for Immunology and Informatics, University of Rhode Island, Providence, RI 02903, USA;
| | - Alan L. Rothman
- Department of Cell and Molecular Biology, Institute for Immunology and Informatics, University of Rhode Island, Providence, RI 02903, USA;
| | - Kathryn B. Anderson
- Department of Medicine, SUNY Upstate Medical University, Syracuse, NY 13210, USA; (K.B.A.); (S.J.T.); (T.P.E.)
| | - Stephen J. Thomas
- Department of Medicine, SUNY Upstate Medical University, Syracuse, NY 13210, USA; (K.B.A.); (S.J.T.); (T.P.E.)
| | - Timothy P. Endy
- Department of Medicine, SUNY Upstate Medical University, Syracuse, NY 13210, USA; (K.B.A.); (S.J.T.); (T.P.E.)
| | - Alongkot Ponlawat
- Department of Entomology, Armed Forces Research Institute of Medical Sciences (AFRIMS), Bangkok 10400, Thailand; (T.F.); (N.P.); (A.P.)
- Correspondence:
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Dengue at the time of COVID-19 in the Philippines. Western Pac Surveill Response J 2021; 12:38-39. [PMID: 34540310 PMCID: PMC8421742 DOI: 10.5365/wpsar.2020.11.2.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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69
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Arnold CR, Srinivasan S, Rodriguez S, Rydzak N, Herzog CM, Gontu A, Bharti N, Small M, Rogers CJ, Schade MM, Kuchipudi SV, Kapur V, Read A, Ferrari MJ. SARS-CoV-2 Seroprevalence in a University Community: A Longitudinal Study of the Impact of Student Return to Campus on Infection Risk Among Community Members. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.02.17.21251942. [PMID: 33619497 PMCID: PMC7899462 DOI: 10.1101/2021.02.17.21251942] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
BACKGROUND Returning university students represent large-scale, transient demographic shifts and a potential source of transmission to adjacent communities during the COVID-19 pandemic. METHODS In this prospective longitudinal cohort study, we tested for IgG antibodies against SARS-CoV-2 in a non-random cohort of residents living in Centre County prior to the Fall 2020 term at the Pennsylvania State University and following the conclusion of the Fall 2020 term. We also report the seroprevalence in a non-random cohort of students collected at the end of the Fall 2020 term. RESULTS Of 1313 community participants, 42 (3.2%) were positive for SARS-CoV-2 IgG antibodies at their first visit between 07 August and 02 October 2020. Of 684 student participants who returned to campus for fall instruction, 208 (30.4%) were positive for SARS-CoV-2 antibodies between 26 October and 21 December. 96 (7.3%) community participants returned a positive IgG antibody result by 19 February. Only contact with known SARS-CoV-2-positive individuals and attendance at small gatherings (20-50 individuals) were significant predictors of detecting IgG antibodies among returning students (aOR, 95% CI: 3.1, 2.07-4.64; 1.52, 1.03-2.24; respectively). CONCLUSIONS Despite high seroprevalence observed within the student population, seroprevalence in a longitudinal cohort of community residents was low and stable from before student arrival for the Fall 2020 term to after student departure. The study implies that heterogeneity in SARS-CoV-2 transmission can occur in geographically coincident populations.
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Affiliation(s)
- Callum R.K. Arnold
- Department of Biology, Pennsylvania State University, University Park, PA, USA 16802
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
| | - Sreenidhi Srinivasan
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Sophie Rodriguez
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Natalie Rydzak
- Department of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Catherine M. Herzog
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Abhinay Gontu
- Department of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Nita Bharti
- Department of Biology, Pennsylvania State University, University Park, PA, USA 16802
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
| | - Meg Small
- College of Health and Human Development, Pennsylvania State University, University Park, PA, USA 16802
- Social Science Research Institute, Pennsylvania State University, University Park, PA, USA 16802
| | - Connie J. Rogers
- Department of Nutritional Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Margeaux M. Schade
- Social Science Research Institute, Pennsylvania State University, University Park, PA, USA 16802
| | - Suresh V Kuchipudi
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
- Department of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Vivek Kapur
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA 16802
- Department of Animal Science, Pennsylvania State University, University Park, PA, USA 16802
| | - Andrew Read
- Department of Biology, Pennsylvania State University, University Park, PA, USA 16802
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Matthew J. Ferrari
- Department of Biology, Pennsylvania State University, University Park, PA, USA 16802
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
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Lee GO, Vasco L, Márquez S, Zuniga-Moya JC, Van Engen A, Uruchima J, Ponce P, Cevallos W, Trueba G, Trostle J, Berrocal VJ, Morrison AC, Cevallos V, Mena C, Coloma J, Eisenberg JNS. A dengue outbreak in a rural community in Northern Coastal Ecuador: An analysis using unmanned aerial vehicle mapping. PLoS Negl Trop Dis 2021; 15:e0009679. [PMID: 34570788 PMCID: PMC8475985 DOI: 10.1371/journal.pntd.0009679] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 07/23/2021] [Indexed: 11/19/2022] Open
Abstract
Dengue is recognized as a major health issue in large urban tropical cities but is also observed in rural areas. In these environments, physical characteristics of the landscape and sociodemographic factors may influence vector populations at small geographic scales, while prior immunity to the four dengue virus serotypes affects incidence. In 2019, a rural northwestern Ecuadorian community, only accessible by river, experienced a dengue outbreak. The village is 2-3 hours by boat away from the nearest population center and comprises both Afro-Ecuadorian and Indigenous Chachi households. We used multiple data streams to examine spatial risk factors associated with this outbreak, combining maps collected with an unmanned aerial vehicle (UAV), an entomological survey, a community census, and active surveillance of febrile cases. We mapped visible water containers seen in UAV images and calculated both the green-red vegetation index (GRVI) and household proximity to public spaces like schools and meeting areas. To identify risk factors for symptomatic dengue infection, we used mixed-effect logistic regression models to account for the clustering of symptomatic cases within households. We identified 55 dengue cases (9.5% of the population) from 37 households. Cases peaked in June and continued through October. Rural spatial organization helped to explain disease risk. Afro-Ecuadorian (versus Indigenous) households experience more symptomatic dengue (OR = 3.0, 95%CI: 1.3, 6.9). This association was explained by differences in vegetation (measured by GRVI) near the household (OR: 11.3 95% 0.38, 38.0) and proximity to the football field (OR: 13.9, 95% 4.0, 48.4). The integration of UAV mapping with other data streams adds to our understanding of these dynamics.
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Affiliation(s)
- Gwenyth O. Lee
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Luis Vasco
- Instituto de Geografía, Universidad San Francisco de Quito, Quito, Ecuador
| | - Sully Márquez
- Instituto de Microbiología, Universidad San Francisco de Quito, Quito, Ecuador
| | - Julio C. Zuniga-Moya
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Amanda Van Engen
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Jessica Uruchima
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Patricio Ponce
- Gestión de Investigación, desarrollo e Innovación, Instituto Nacional de Investigación en Salud Pública (INSPI), Quito, Ecuador
| | - William Cevallos
- Instituto de Biomedicina, Universidad Central del Ecuador, Quito, Ecuador
| | - Gabriel Trueba
- Instituto de Microbiología, Universidad San Francisco de Quito, Quito, Ecuador
| | - James Trostle
- Department of Anthropology, Trinity College, Hartford, Connecticut, United States of America
| | - Veronica J. Berrocal
- Department of Statistics, University of California, Irvine, California, United States of America
| | - Amy C. Morrison
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicince, University of California, San Diego, California, United States
| | - Varsovia Cevallos
- Gestión de Investigación, desarrollo e Innovación, Instituto Nacional de Investigación en Salud Pública (INSPI), Quito, Ecuador
| | - Carlos Mena
- Instituto de Geografía, Universidad San Francisco de Quito, Quito, Ecuador
| | - Josefina Coloma
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, California, United States of America
| | - Joseph N. S. Eisenberg
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
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Cavany SM, España G, Vazquez-Prokopec GM, Scott TW, Perkins TA. Pandemic-associated mobility restrictions could cause increases in dengue virus transmission. PLoS Negl Trop Dis 2021; 15:e0009603. [PMID: 34370734 PMCID: PMC8375978 DOI: 10.1371/journal.pntd.0009603] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 08/19/2021] [Accepted: 06/28/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The COVID-19 pandemic has induced unprecedented reductions in human mobility and social contacts throughout the world. Because dengue virus (DENV) transmission is strongly driven by human mobility, behavioral changes associated with the pandemic have been hypothesized to impact dengue incidence. By discouraging human contact, COVID-19 control measures have also disrupted dengue vector control interventions, the most effective of which require entry into homes. We sought to investigate how and why dengue incidence could differ under a lockdown scenario with a proportion of the population sheltered at home. METHODOLOGY & PRINCIPAL FINDINGS We used an agent-based model with a realistic treatment of human mobility and vector control. We found that a lockdown in which 70% of the population sheltered at home and which occurred in a season when a new serotype invaded could lead to a small average increase in cumulative DENV infections of up to 10%, depending on the time of year lockdown occurred. Lockdown had a more pronounced effect on the spatial distribution of DENV infections, with higher incidence under lockdown in regions with higher mosquito abundance. Transmission was also more focused in homes following lockdown. The proportion of people infected in their own home rose from 54% under normal conditions to 66% under lockdown, and the household secondary attack rate rose from 0.109 to 0.128, a 17% increase. When we considered that lockdown measures could disrupt regular, city-wide vector control campaigns, the increase in incidence was more pronounced than with lockdown alone, especially if lockdown occurred at the optimal time for vector control. CONCLUSIONS & SIGNIFICANCE Our results indicate that an unintended outcome of lockdown measures may be to adversely alter the epidemiology of dengue. This observation has important implications for an improved understanding of dengue epidemiology and effective application of dengue vector control. When coordinating public health responses during a syndemic, it is important to monitor multiple infections and understand that an intervention against one disease may exacerbate another.
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Affiliation(s)
- Sean M. Cavany
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Guido España
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America
| | | | - Thomas W. Scott
- Department of Entomology and Nematology, University of California, Davis, Davis, California, United States of America
| | - T Alex Perkins
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America
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Brady OJ, Kucharski AJ, Funk S, Jafari Y, Loock MV, Herrera-Taracena G, Menten J, Edmunds WJ, Sim S, Ng LC, Hué S, Hibberd ML. Case-area targeted interventions (CATI) for reactive dengue control: Modelling effectiveness of vector control and prophylactic drugs in Singapore. PLoS Negl Trop Dis 2021; 15:e0009562. [PMID: 34379641 PMCID: PMC8357181 DOI: 10.1371/journal.pntd.0009562] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 06/14/2021] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Targeting interventions to areas that have recently experienced cases of disease is one strategy to contain outbreaks of infectious disease. Such case-area targeted interventions (CATI) have become an increasingly popular approach for dengue control but there is little evidence to suggest how precisely targeted or how recent cases need to be, to mount an effective response. The growing interest in the development of prophylactic and therapeutic drugs for dengue has also given new relevance for CATI strategies to interrupt transmission or deliver early treatment. METHODS/PRINCIPAL FINDINGS Here we develop a patch-based mathematical model of spatial dengue spread and fit it to spatiotemporal datasets from Singapore. Simulations from this model suggest CATI strategies could be effective, particularly if used in lower density areas. To maximise effectiveness, increasing the size of the radius around an index case should be prioritised even if it results in delays in the intervention being applied. This is partially because large intervention radii ensure individuals receive multiple and regular rounds of drug dosing or vector control, and thus boost overall coverage. Given equivalent efficacy, CATIs using prophylactic drugs are predicted to be more effective than adult mosquito-killing vector control methods and may even offer the possibility of interrupting individual chains of transmission if rapidly deployed. CATI strategies quickly lose their effectiveness if baseline transmission increases or case detection rates fall. CONCLUSIONS/SIGNIFICANCE These results suggest CATI strategies can play an important role in dengue control but are likely to be most relevant for low transmission areas where high coverage of other non-reactive interventions already exists. Controlled field trials are needed to assess the field efficacy and practical constraints of large operational CATI strategies.
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Affiliation(s)
- Oliver J. Brady
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Adam J. Kucharski
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Sebastian Funk
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Yalda Jafari
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Marnix Van Loock
- Janssen Global Public Health, Janssen Pharmaceutica NV, Beerse, Belgium
| | - Guillermo Herrera-Taracena
- Janssen Global Public Health, Janssen Research & Development, LLC, Horsham, Pennsylvania, United States of America
| | - Joris Menten
- Quantitative Sciences, Janssen Pharmaceutica NV, Beerse, Belgium
| | - W. John Edmunds
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Shuzhen Sim
- Environmental Health Institute, National Environment Agency, Singapore, Singapore
| | - Lee-Ching Ng
- Environmental Health Institute, National Environment Agency, Singapore, Singapore
| | - Stéphane Hué
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Martin L. Hibberd
- Department of Infection Biology, Faculty of Infectious Tropical Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
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73
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Schaber KL, Morrison AC, Elson WH, Astete-Vega H, Córdova-López JJ, Ríos López EJ, Flores WLQ, Santillan ASV, Scott TW, Waller LA, Kitron U, Barker CM, Perkins TA, Rothman AL, Vazquez-Prokopec GM, Elder JP, Paz-Soldan VA. The impact of dengue illness on social distancing and caregiving behavior. PLoS Negl Trop Dis 2021; 15:e0009614. [PMID: 34280204 PMCID: PMC8354465 DOI: 10.1371/journal.pntd.0009614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/10/2021] [Accepted: 06/30/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Human mobility among residential locations can drive dengue virus (DENV) transmission dynamics. Recently, it was shown that individuals with symptomatic DENV infection exhibit significant changes in their mobility patterns, spending more time at home during illness. This change in mobility is predicted to increase the risk of acquiring infection for those living with or visiting the ill individual. It has yet to be considered, however, whether social contacts are also changing their mobility, either by socially distancing themselves from the infectious individual or increasing contact to help care for them. Social, or physical, distancing and caregiving could have diverse yet important impacts on DENV transmission dynamics; therefore, it is necessary to better understand the nature and frequency of these behaviors including their effect on mobility. METHODOLOGY AND PRINCIPAL FINDINGS Through community-based febrile illness surveillance and RT-PCR infection confirmation, 67 DENV positive (DENV+) residents were identified in the city of Iquitos, Peru. Using retrospective interviews, data were collected on visitors and home-based care received during the illness. While 15% of participants lost visitors during their illness, 22% gained visitors; overall, 32% of all individuals (particularly females) received visitors while symptomatic. Caregiving was common (90%), particularly caring by housemates (91%) and caring for children (98%). Twenty-eight percent of caregivers changed their behavior enough to have their work (and, likely, mobility patterns) affected. This was significantly more likely when caring for individuals with low "health-related quality of well-being" during illness (Fisher's Exact, p = 0.01). CONCLUSIONS/SIGNIFICANCE Our study demonstrates that social contacts of individuals with dengue modify their patterns of visitation and caregiving. The observed mobility changes could impact a susceptible individual's exposure to virus or a presymptomatic/clinically inapparent individual's contribution to onward transmission. Accounting for changes in social contact mobility is imperative in order to get a more accurate understanding of DENV transmission.
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Affiliation(s)
- Kathryn L. Schaber
- Program of Population Biology, Ecology and Evolution, Emory University, Atlanta, Georgia, United States of America
| | - Amy C. Morrison
- Department of Virology and Emerging Infections, U.S. Naval Medical Research Unit No. 6, Lima and Iquitos, Peru
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, California, United States of America
| | - William H. Elson
- Department of Entomology and Nematology, University of California, Davis, California, United States of America
| | - Helvio Astete-Vega
- Department of Virology and Emerging Infections, U.S. Naval Medical Research Unit No. 6, Lima and Iquitos, Peru
| | - Jhonny J. Córdova-López
- Department of Entomology and Nematology, University of California, Davis, California, United States of America
| | - Esther Jennifer Ríos López
- Department of Virology and Emerging Infections, U.S. Naval Medical Research Unit No. 6, Lima and Iquitos, Peru
| | - W. Lorena Quiroz Flores
- Department of Virology and Emerging Infections, U.S. Naval Medical Research Unit No. 6, Lima and Iquitos, Peru
| | | | - Thomas W. Scott
- Department of Entomology and Nematology, University of California, Davis, California, United States of America
| | - Lance A. Waller
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Uriel Kitron
- Department of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America
| | - Christopher M. Barker
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, California, United States of America
| | - T. Alex Perkins
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Alan L. Rothman
- Institute for Immunology and Informatics and Department of Cell and Molecular Biology, University of Rhode Island, Providence, Rhode Island, United States of America
| | - Gonzalo M. Vazquez-Prokopec
- Program of Population Biology, Ecology and Evolution, Emory University, Atlanta, Georgia, United States of America
- Department of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America
| | - John P. Elder
- School of Public Health, San Diego State University, San Diego, California, United States of America
| | - Valerie A. Paz-Soldan
- Department of Global Community Health and Behavioral Sciences, Tulane School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America
- * E-mail:
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74
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Thinking clearly about social aspects of infectious disease transmission. Nature 2021; 595:205-213. [PMID: 34194045 DOI: 10.1038/s41586-021-03694-x] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 06/04/2021] [Indexed: 02/06/2023]
Abstract
Social and cultural forces shape almost every aspect of infectious disease transmission in human populations, as well as our ability to measure, understand, and respond to epidemics. For directly transmitted infections, pathogen transmission relies on human-to-human contact, with kinship, household, and societal structures shaping contact patterns that in turn determine epidemic dynamics. Social, economic, and cultural forces also shape patterns of exposure, health-seeking behaviour, infection outcomes, the likelihood of diagnosis and reporting of cases, and the uptake of interventions. Although these social aspects of epidemiology are hard to quantify and have limited the generalizability of modelling frameworks in a policy context, new sources of data on relevant aspects of human behaviour are increasingly available. Researchers have begun to embrace data from mobile devices and other technologies as useful proxies for behavioural drivers of disease transmission, but there is much work to be done to measure and validate these approaches, particularly for policy-making. Here we discuss how integrating local knowledge in the design of model frameworks and the interpretation of new data streams offers the possibility of policy-relevant models for public health decision-making as well as the development of robust, generalizable theories about human behaviour in relation to infectious diseases.
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75
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Nicolelis MAL, Raimundo RLG, Peixoto PS, Andreazzi CS. The impact of super-spreader cities, highways, and intensive care availability in the early stages of the COVID-19 epidemic in Brazil. Sci Rep 2021; 11:13001. [PMID: 34155241 PMCID: PMC8217556 DOI: 10.1038/s41598-021-92263-3] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 05/26/2021] [Indexed: 02/07/2023] Open
Abstract
Although international airports served as main entry points for SARS-CoV-2, the factors driving the uneven geographic spread of COVID-19 cases and deaths in Brazil remain mostly unknown. Here we show that three major factors influenced the early macro-geographical dynamics of COVID-19 in Brazil. Mathematical modeling revealed that the "super-spreading city" of São Paulo initially accounted for more than 85% of the case spread in the entire country. By adding only 16 other spreading cities, we accounted for 98-99% of the cases reported during the first 3 months of the pandemic in Brazil. Moreover, 26 federal highways accounted for about 30% of SARS-CoV-2's case spread. As cases increased in the Brazilian interior, the distribution of COVID-19 deaths began to correlate with the allocation of the country's intensive care units (ICUs), which is heavily weighted towards state capitals. Thus, severely ill patients living in the countryside had to be transported to state capitals to access ICU beds, creating a "boomerang effect" that contributed to skew the distribution of COVID-19 deaths. Therefore, if (i) a lockdown had been imposed earlier on in spreader-capitals, (ii) mandatory road traffic restrictions had been enforced, and (iii) a more equitable geographic distribution of ICU beds existed, the impact of COVID-19 in Brazil would be significantly lower.
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Affiliation(s)
- Miguel A L Nicolelis
- Department of Neurobiology, Duke University Medical Center, Box 103905, Durham, NC, 27710, USA.
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
- Department of Neurology, Duke University, Durham, NC, USA.
- Department of Neurosurgery, Duke University, Durham, NC, USA.
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA.
- Edmond and Lily Safra International Institute of Neurosciences, Natal, Brazil.
| | - Rafael L G Raimundo
- Department of Engineering and Environment and Postgraduate Program in Ecology and Environmental Monitoring (PPGEMA), Center for Applied Sciences and Education, Federal University of Paraíba-Campus IV, Rio Tinto, Paraíba, Brazil
| | - Pedro S Peixoto
- Department of Applied Mathematics, Institute of Mathematics and Statistics, University of São Paulo, São Paulo, Brazil
| | - Cecilia S Andreazzi
- Laboratory of Biology and Parasitology of Wild Reservoir Mammals, IOC, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
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76
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Elson WH, Reiner RC, Siles C, Bazan I, Vilcarromero S, Riley-Powell AR, Kawiecki AB, Astete H, Hontz RD, Barker CM, Vazquez-Prokopec GM, Morrison AC, Scott TW, Elder JP, Rothman AL, Paz-Soldan VA. Heterogeneity of Dengue Illness in Community-Based Prospective Study, Iquitos, Peru. Emerg Infect Dis 2021; 26:2077-2086. [PMID: 32818402 PMCID: PMC7454099 DOI: 10.3201/eid2609.191472] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Measuring heterogeneity of dengue illness is necessary to define suitable endpoints in dengue vaccine and therapeutic trials and will help clarify behavioral responses to illness. To quantify heterogeneity in dengue illness, including milder cases, we developed the Dengue Illness Perceptions Response (IPR) survey, which captured detailed symptom data, including intensity, duration, and character, and change in routine activities caused by illness. During 2016–2019, we collected IPR data daily during the acute phase of illness for 79 persons with a positive reverse transcription PCR result for dengue virus RNA. Most participants had mild ambulatory disease. However, we measured substantial heterogeneity in illness experience, symptom duration, and maximum reported intensity of individual symptoms. Symptom intensity was a more valuable predicter of major activity change during dengue illness than symptom presence or absence alone. These data suggest that the IPR measures clinically useful heterogeneity in dengue illness experience and its relation to altered human behavior.
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77
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McGough SF, Clemente L, Kutz JN, Santillana M. A dynamic, ensemble learning approach to forecast dengue fever epidemic years in Brazil using weather and population susceptibility cycles. J R Soc Interface 2021; 18:20201006. [PMID: 34129785 PMCID: PMC8205538 DOI: 10.1098/rsif.2020.1006] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Transmission of dengue fever depends on a complex interplay of human, climate and mosquito dynamics, which often change in time and space. It is well known that its disease dynamics are highly influenced by multiple factors including population susceptibility to infection as well as by microclimates: small-area climatic conditions which create environments favourable for the breeding and survival of mosquitoes. Here, we present a novel machine learning dengue forecasting approach, which, dynamically in time and space, identifies local patterns in weather and population susceptibility to make epidemic predictions at the city level in Brazil, months ahead of the occurrence of disease outbreaks. Weather-based predictions are improved when information on population susceptibility is incorporated, indicating that immunity is an important predictor neglected by most dengue forecast models. Given the generalizability of our methodology to any location or input data, it may prove valuable for public health decision-making aimed at mitigating the effects of seasonal dengue outbreaks in locations globally.
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Affiliation(s)
- Sarah F McGough
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02115, USA.,Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Leonardo Clemente
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02115, USA.,Tecnológico de Monterrey, 64849 Monterrey, Nuevo León, Mexico
| | - J Nathan Kutz
- Department of Applied Mathematics, University of Washington, Seattle, WA 98195, USA
| | - Mauricio Santillana
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02115, USA.,Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA.,Department of Pediatrics, Harvard Medical School, Harvard University, Boston, MA 02115, USA
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78
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Temperature, traveling, slums, and housing drive dengue transmission in a non-endemic metropolis. PLoS Negl Trop Dis 2021; 15:e0009465. [PMID: 34115753 PMCID: PMC8221794 DOI: 10.1371/journal.pntd.0009465] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 06/23/2021] [Accepted: 05/10/2021] [Indexed: 11/24/2022] Open
Abstract
Dengue is steadily increasing worldwide and expanding into higher latitudes. Current non-endemic areas are prone to become endemic soon. To improve understanding of dengue transmission in these settings, we assessed the spatiotemporal dynamics of the hitherto largest outbreak in the non-endemic metropolis of Buenos Aires, Argentina, based on detailed information on the 5,104 georeferenced cases registered during summer-autumn of 2016. The highly seasonal dengue transmission in Buenos Aires was modulated by temperature and triggered by imported cases coming from regions with ongoing outbreaks. However, local transmission was made possible and consolidated heterogeneously in the city due to housing and socioeconomic characteristics of the population, with 32.8% of autochthonous cases occurring in slums, which held only 6.4% of the city population. A hierarchical spatiotemporal model accounting for imperfect detection of cases showed that, outside slums, less-affluent neighborhoods of houses (vs. apartments) favored transmission. Global and local spatiotemporal point-pattern analyses demonstrated that most transmission occurred at or close to home. Additionally, based on these results, a point-pattern analysis was assessed for early identification of transmission foci during the outbreak while accounting for population spatial distribution. Altogether, our results reveal how social, physical, and biological processes shape dengue transmission in Buenos Aires and, likely, other non-endemic cities, and suggest multiple opportunities for control interventions. Dengue fever is mainly transmitted by a mosquito species that is highly urbanized, and lays eggs and develops mostly in artificial water containers. Dengue transmission is sustained year-round in most tropical regions of the world, but in many subtropical/temperate regions it occurs only in the warmest months. To improve understanding of dengue transmission in these regions, we analyzed one of the largest outbreaks in Buenos Aires city, a subtropical metropolis. Based on information on 5,104 georeferenced cases during summer-autumn 2016, we found that most transmission occurred in or near home, that slums had the highest risk of transmission, and that, outside slums, less-affluent neighborhoods of houses (vs. apartments) favored transmission. We showed that the cumulative effects of temperature over the previous few weeks set the temporal limits for transmission to occur, and that the outbreak was sparked by infected people arriving from regions with ongoing outbreaks. Additionally, we implemented a statistical method to identify transmission foci in real-time that improves targeting control interventions. Our results deepen the understanding of dengue transmission as a result of social, physical, and biological processes, and pose multiple opportunities for improving control of dengue and other mosquito-borne viruses such as Zika, chikungunya, and yellow fever.
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79
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Jiao J, Suarez GP, Fefferman NH. How public reaction to disease information across scales and the impacts of vector control methods influence disease prevalence and control efficacy. PLoS Comput Biol 2021; 17:e1008762. [PMID: 34181645 PMCID: PMC8270472 DOI: 10.1371/journal.pcbi.1008762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 07/09/2021] [Accepted: 05/28/2021] [Indexed: 11/10/2022] Open
Abstract
With the development of social media, the information about vector-borne disease incidence over broad spatial scales can cause demand for local vector control before local risk exists. Anticipatory intervention may still benefit local disease control efforts; however, infection risks are not the only focal concerns governing public demand for vector control. Concern for environmental contamination from pesticides and economic limitations on the frequency and magnitude of control measures also play key roles. Further, public concern may be focused more on ecological factors (i.e., controlling mosquito populations) or on epidemiological factors (i.e., controlling infection-carrying mosquitoes), which may lead to very different control outcomes. Here we introduced a generic Ross-MacDonald model, incorporating these factors under three spatial scales of disease information: local, regional, and global. We tailored and parameterized the model for Zika virus transmitted by Aedes aegypti mosquito. We found that sensitive reactivity caused by larger-scale incidence information could decrease average human infections per patch breeding capacity, however, the associated increase in total control effort plays a larger role, which leads to an overall decrease in control efficacy. The shift of focal concerns from epidemiological to ecological risk could relax the negative effect of the sensitive reactivity on control efficacy when mosquito breeding capacity populations are expected to be large. This work demonstrates that, depending on expected total mosquito breeding capacity population size, and weights of different focal concerns, large-scale disease information can reduce disease infections without lowering control efficacy. Our findings provide guidance for vector-control strategies by considering public reaction through social media.
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Affiliation(s)
- Jing Jiao
- National Institute for Mathematical and Biological Synthesis, The University of Tennessee, Knoxville, Tennessee, United States of America
- Department of Biological Science, Florida State University, Tallahassee, Florida, United States of America
| | - Gonzalo P. Suarez
- Department of Agriculture and Biological Engineering, University of Florida, Gainesville, Florida, United States of America
| | - Nina H. Fefferman
- National Institute for Mathematical and Biological Synthesis, The University of Tennessee, Knoxville, Tennessee, United States of America
- Ecology & Evolutionary Biology, The University of Tennessee, Knoxville, Tennessee, United States of America
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80
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Liyanage P, Rocklöv J, Tissera HA. The impact of COVID-19 lockdown on dengue transmission in Sri Lanka; A natural experiment for understanding the influence of human mobility. PLoS Negl Trop Dis 2021; 15:e0009420. [PMID: 34111117 PMCID: PMC8192006 DOI: 10.1371/journal.pntd.0009420] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 04/28/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Dengue is one of the major public health problems in Sri Lanka. Its outbreak pattern depends on a multitude of drivers, including human mobility. Here we evaluate the impact of COVID-19 related mobility restriction (lockdown) on the risk of dengue in Sri Lanka. METHODOLOGY Two-stage hierarchical models were fitted using an interrupted time-series design based on the notified dengue cases, January 2015 to July 2020. In the first stage model, the district level impact was estimated using quasi-Poisson regression models while accounting for temporal trends. Estimates were pooled at zonal and national levels in the second stage model using meta-analysis. The influence of the extended period of school closure on dengue in children in the western province was compared to adults. FINDINGS Statistically significant and homogeneous reduction of dengue risk was observed at all levels during the lockdown. Overall an 88% reduction in risk (RR 0.12; 95% CI from 0.08 to 0.17) was observed at the national level. The highest impact was observed among children aged less than 19 years showing a 92% reduction (RR 0.8; 95% CI from 0.03 to 0.25). We observed higher impact in the dry zone having 91% reduction (RR 0.09; 95% CI from 0.05 to 0.15) compared to wet zone showing 83% reduction (RR 0.17; 95% CI from 0.09 to 0.30). There was no indication that the overall health-seeking behaviour for dengue had a substantial influence on these estimates. SIGNIFICANCE This study offers a broad understanding of the change in risk of dengue during the COVID-19 pandemic and associated mobility restrictions in Sri Lanka. The analysis using the mobility restrictions as a natural experiment suggests mobility patterns to be a very important driver of dengue transmission.
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Affiliation(s)
- Prasad Liyanage
- Department of Epidemiology and Global Health, Umeå University, Umeå, Sweden
- Ministry of Health, Colombo, 01000, Sri Lanka
| | - Joacim Rocklöv
- Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden
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81
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Jiao J, Fefferman N. The dynamics of evolutionary rescue from a novel pathogen threat in a host metapopulation. Sci Rep 2021; 11:10932. [PMID: 34035424 PMCID: PMC8149858 DOI: 10.1038/s41598-021-90407-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 05/11/2021] [Indexed: 02/04/2023] Open
Abstract
When a novel disease strikes a naïve host population, there is evidence that the most immediate response can involve host evolution while the pathogen remains relatively unchanged. When hosts also live in metapopulations, there may be critical differences in the dynamics that emerge from the synergy among evolutionary, ecological, and epidemiological factors. Here we used a Susceptible-Infected-Recovery model to explore how spatial and temporal ecological factors may drive the epidemiological and rapid-evolutionary dynamics of host metapopulations. For simplicity, we assumed two host genotypes: wild type, which has a positive intrinsic growth rate in the absence of disease, and robust type, which is less likely to catch the infection given exposure but has a lower intrinsic growth rate in the absence of infection. We found that the robust-type host would be strongly selected for in the presence of disease when transmission differences between the two types is large. The growth rate of the wild type had dual but opposite effects on host composition: a smaller increase in wild-type growth increased wild-type competition and lead to periodical disease outbreaks over the first generations after pathogen introduction, while larger growth increased disease by providing more susceptibles, which increased robust host density but decreased periodical outbreaks. Increased migration had a similar impact as the increased differential susceptibility, both of which led to an increase in robust hosts and a decrease in periodical outbreaks. Our study provided a comprehensive understanding of the combined effects among migration, disease epidemiology, and host demography on host evolution with an unchanging pathogen. The findings have important implications for wildlife conservation and zoonotic disease control.
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Affiliation(s)
- Jing Jiao
- National Institute for Mathematical and Biological Synthesis, The University of Tennessee, 1122 Volunteer Blvd., Suite 106, Knoxville, TN, 37996, USA.
- Department of Biological Science, Florida State University, 319 Stadium Dr, Tallahassee, FL, 32304, USA.
| | - Nina Fefferman
- National Institute for Mathematical and Biological Synthesis, The University of Tennessee, 1122 Volunteer Blvd., Suite 106, Knoxville, TN, 37996, USA
- Ecology & Evolutionary Biology, The University of Tennessee, 1416 Circle Drive, Knoxville, TN, 37996, USA
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Wu SL, Bennett JB, Sánchez C. HM, Dolgert AJ, León TM, Marshall JM. MGDrivE 2: A simulation framework for gene drive systems incorporating seasonality and epidemiological dynamics. PLoS Comput Biol 2021; 17:e1009030. [PMID: 34019537 PMCID: PMC8186770 DOI: 10.1371/journal.pcbi.1009030] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 06/08/2021] [Accepted: 05/02/2021] [Indexed: 12/30/2022] Open
Abstract
Interest in gene drive technology has continued to grow as promising new drive systems have been developed in the lab and discussions are moving towards implementing field trials. The prospect of field trials requires models that incorporate a significant degree of ecological detail, including parameters that change over time in response to environmental data such as temperature and rainfall, leading to seasonal patterns in mosquito population density. Epidemiological outcomes are also of growing importance, as: i) the suitability of a gene drive construct for release will depend on its expected impact on disease transmission, and ii) initial field trials are expected to have a measured entomological outcome and a modeled epidemiological outcome. We present MGDrivE 2 (Mosquito Gene Drive Explorer 2): a significant development from the MGDrivE 1 simulation framework that investigates the population dynamics of a variety of gene drive architectures and their spread through spatially-explicit mosquito populations. Key strengths and fundamental improvements of the MGDrivE 2 framework are: i) the ability of parameters to vary with time and induce seasonal population dynamics, ii) an epidemiological module accommodating reciprocal pathogen transmission between humans and mosquitoes, and iii) an implementation framework based on stochastic Petri nets that enables efficient model formulation and flexible implementation. Example MGDrivE 2 simulations are presented to demonstrate the application of the framework to a CRISPR-based split gene drive system intended to drive a disease-refractory gene into a population in a confinable and reversible manner, incorporating time-varying temperature and rainfall data. The simulations also evaluate impact on human disease incidence and prevalence. Further documentation and use examples are provided in vignettes at the project’s CRAN repository. MGDrivE 2 is freely available as an open-source R package on CRAN (https://CRAN.R-project.org/package=MGDrivE2). We intend the package to provide a flexible tool capable of modeling gene drive constructs as they move closer to field application and to infer their expected impact on disease transmission. Malaria, dengue and other mosquito-borne diseases continue to pose a major global health burden through much of the world. Currently available tools, such as insecticides and antimalarial drugs, are not expected to be sufficient to eliminate these diseases from highly-endemic areas, hence there is interest in novel strategies including genetics-based approaches. In recent years, the advent of CRISPR-based gene-editing has greatly expanded the range of genetic control tools available, and MGDrivE 1 (Mosquito Gene Drive Explorer 1) was proposed to simulate the dynamics of these systems through spatially-structured mosquito populations. As the technology has advanced and potential field trials are being discussed, models are now needed that incorporate additional details, such as life history parameters that respond to daily and seasonal environmental fluctuations, and transmission of pathogens between mosquito and vertebrate hosts. Here, we present MGDrivE 2, a gene drive simulation framework that significantly improves upon MGDrivE 1 by addressing these modeling needs. MGDrivE 2 has also been reformulated as a stochastic Petri net, enabling model specification to be decoupled from simulation, making it easier to adapt the model for application to other insect and mammalian species.
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Affiliation(s)
- Sean L. Wu
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, California, United States of America
- * E-mail: (SLW); (JMM)
| | - Jared B. Bennett
- Biophysics Graduate Group, Division of Biological Sciences, College of Letters and Science, University of California, Berkeley, California, United States of America
| | - Héctor M. Sánchez C.
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, California, United States of America
| | - Andrew J. Dolgert
- Institute for Health Metrics and Evaluation, Seattle, Washington, United States of America
| | - Tomás M. León
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, California, United States of America
| | - John M. Marshall
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, California, United States of America
- Innovative Genomics Institute, University of California, Berkeley, California, United States of America
- * E-mail: (SLW); (JMM)
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83
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Lee SA, Jarvis CI, Edmunds WJ, Economou T, Lowe R. Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions. J R Soc Interface 2021; 18:20210096. [PMID: 34034534 PMCID: PMC8150046 DOI: 10.1098/rsif.2021.0096] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 04/26/2021] [Indexed: 12/14/2022] Open
Abstract
Spatial connectivity plays an important role in mosquito-borne disease transmission. Connectivity can arise for many reasons, including shared environments, vector ecology and human movement. This systematic review synthesizes the spatial methods used to model mosquito-borne diseases, their spatial connectivity assumptions and the data used to inform spatial model components. We identified 248 papers eligible for inclusion. Most used statistical models (84.2%), although mechanistic are increasingly used. We identified 17 spatial models which used one of four methods (spatial covariates, local regression, random effects/fields and movement matrices). Over 80% of studies assumed that connectivity was distance-based despite this approach ignoring distant connections and potentially oversimplifying the process of transmission. Studies were more likely to assume connectivity was driven by human movement if the disease was transmitted by an Aedes mosquito. Connectivity arising from human movement was more commonly assumed in studies using a mechanistic model, likely influenced by a lack of statistical models able to account for these connections. Although models have been increasing in complexity, it is important to select the most appropriate, parsimonious model available based on the research question, disease transmission process, the spatial scale and availability of data, and the way spatial connectivity is assumed to occur.
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Affiliation(s)
- Sophie A. Lee
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK
- Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Christopher I. Jarvis
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - W. John Edmunds
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | | | - Rachel Lowe
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK
- Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
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84
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Lowe R, Lee SA, O'Reilly KM, Brady OJ, Bastos L, Carrasco-Escobar G, de Castro Catão R, Colón-González FJ, Barcellos C, Carvalho MS, Blangiardo M, Rue H, Gasparrini A. Combined effects of hydrometeorological hazards and urbanisation on dengue risk in Brazil: a spatiotemporal modelling study. Lancet Planet Health 2021; 5:e209-e219. [PMID: 33838736 DOI: 10.1016/s2542-5196(20)30292-8] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 11/25/2020] [Accepted: 11/26/2020] [Indexed: 05/18/2023]
Abstract
BACKGROUND Temperature and rainfall patterns are known to influence seasonal patterns of dengue transmission. However, the effect of severe drought and extremely wet conditions on the timing and intensity of dengue epidemics is poorly understood. In this study, we aimed to quantify the non-linear and delayed effects of extreme hydrometeorological hazards on dengue risk by level of urbanisation in Brazil using a spatiotemporal model. METHODS We combined distributed lag non-linear models with a spatiotemporal Bayesian hierarchical model framework to determine the exposure-lag-response association between the relative risk (RR) of dengue and a drought severity index. We fit the model to monthly dengue case data for the 558 microregions of Brazil between January, 2001, and January, 2019, accounting for unobserved confounding factors, spatial autocorrelation, seasonality, and interannual variability. We assessed the variation in RR by level of urbanisation through an interaction between the drought severity index and urbanisation. We also assessed the effect of hydrometeorological hazards on dengue risk in areas with a high frequency of water supply shortages. FINDINGS The dataset included 12 895 293 dengue cases reported between 2001 and 2019 in Brazil. Overall, the risk of dengue increased between 0-3 months after extremely wet conditions (maximum RR at 1 month lag 1·56 [95% CI 1·41-1·73]) and 3-5 months after drought conditions (maximum RR at 4 months lag 1·43 [1·22-1·67]). Including a linear interaction between the drought severity index and level of urbanisation improved the model fit and showed the risk of dengue was higher in more rural areas than highly urbanised areas during extremely wet conditions (maximum RR 1·77 [1·32-2·37] at 0 months lag vs maximum RR 1·58 [1·39-1·81] at 2 months lag), but higher in highly urbanised areas than rural areas after extreme drought (maximum RR 1·60 [1·33-1·92] vs 1·15 [1·08-1·22], both at 4 months lag). We also found the dengue risk following extreme drought was higher in areas that had a higher frequency of water supply shortages. INTERPRETATION Wet conditions and extreme drought can increase the risk of dengue with different delays. The risk associated with extremely wet conditions was higher in more rural areas and the risk associated with extreme drought was exacerbated in highly urbanised areas, which have water shortages and intermittent water supply during droughts. These findings have implications for targeting mosquito control activities in poorly serviced urban areas, not only during the wet and warm season, but also during drought periods. FUNDING Royal Society, Medical Research Council, Wellcome Trust, National Institutes of Health, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, and Conselho Nacional de Desenvolvimento Científico e Tecnológico. TRANSLATION For the Portuguese translation of the abstract see Supplementary Materials section.
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Affiliation(s)
- Rachel Lowe
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
| | - Sophie A Lee
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Kathleen M O'Reilly
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Oliver J Brady
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Leonardo Bastos
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Scientific Computing Program, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - Gabriel Carrasco-Escobar
- Scripps Institution of Oceanography, University of California San Diego, San Diego, CA, USA; Health Innovation Laboratory, Institute of Tropical Medicine Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru
| | | | - Felipe J Colón-González
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Christovam Barcellos
- Health Information and Communication Institute, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - Marilia Sá Carvalho
- Scientific Computing Program, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
| | - Marta Blangiardo
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Håvard Rue
- Statistics Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Antonio Gasparrini
- Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK; Department of Public Health Environments and Society, London School of Hygiene & Tropical Medicine, London, UK; Centre for Statistical Modelling, London School of Hygiene & Tropical Medicine, London, UK
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85
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Morrison AC, Schwarz J, Mckenney JL, Cordova J, Rios JE, Quiroz WL, Vizcarra SA, Sopheab H, Bauer KM, Chhea C, Saphonn V, Hontz RD, Gorbach PM, Paz-Soldan VA. Potential for community based surveillance of febrile diseases: Feasibility of self-administered rapid diagnostic tests in Iquitos, Peru and Phnom Penh, Cambodia. PLoS Negl Trop Dis 2021; 15:e0009307. [PMID: 33901172 PMCID: PMC8101991 DOI: 10.1371/journal.pntd.0009307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 05/06/2021] [Accepted: 03/12/2021] [Indexed: 11/18/2022] Open
Abstract
Rapid diagnostic tests (RDTs) have the potential to identify infectious diseases quickly, minimize disease transmission, and could complement and improve surveillance and control of infectious and vector-borne diseases during outbreaks. The U.S. Defense Threat Reduction Agency's Joint Science and Technology Office (DTRA-JSTO) program set out to develop novel point-of-need RDTs for infectious diseases and deploy them for home use with no training. The aim of this formative study was to address two questions: 1) could community members in Iquitos, Peru and Phnom Penh, Cambodia competently use RDTs of different levels of complexity at home with visually based instructions provided, and 2) if an RDT were provided at no cost, would it be used at home if family members displayed febrile symptoms? Test kits with written and video (Peru only) instructions were provided to community members (Peru [n = 202]; Cambodia [n = 50]) or community health workers (Cambodia [n = 45]), and trained observers evaluated the competency level for each of the several steps required to successfully operate one of two multiplex RDTs on themselves or other consenting participant (i.e., family member). In Iquitos, >80% of residents were able to perform 11/12 steps and 7/15 steps for the two- and five-pathogen test, respectively. Competency in Phnom Penh never reached 80% for any of the 12 or 15 steps for either test; the percentage of participants able to perform a step ranged from 26-76% and 23-72%, for the two- and five-pathogen tests, respectively. Commercially available NS1 dengue rapid tests were distributed, at no cost, to households with confirmed exposure to dengue or Zika virus; of 14 febrile cases reported, six used the provided RDT. Our findings support the need for further implementation research on the appropriate level of instructions or training needed for diverse devices in different settings, as well as how to best integrate RDTs into existing local public health and disease surveillance programs at a large scale.
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Affiliation(s)
- Amy C Morrison
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, California, United States of America
- U.S. Naval Medical Research Unit No. 6 (NAMRU-6), Lima, Peru
| | - Julia Schwarz
- Icahn School of Medicine at Mt Sinai, New York, New York, United States of America
| | - Jennie L Mckenney
- University of California Fielding School of Public Health, Los Angeles, California, United States of America
| | - Jhonny Cordova
- Department of Entomology and Nematology, University of California, Davis, California, United States of America
| | - Jennifer E Rios
- U.S. Naval Medical Research Unit No. 6 (NAMRU-6), Lima, Peru
| | - W Lorena Quiroz
- U.S. Naval Medical Research Unit No. 6 (NAMRU-6), Lima, Peru
| | - S Alfonso Vizcarra
- Department of Entomology and Nematology, University of California, Davis, California, United States of America
| | - Heng Sopheab
- School of Public Health, National Institute of Public Health, Phnom Penh, Cambodia
| | - Karin M Bauer
- Tulane School of Public Health and Tropical Medicine, New Orleans, Lousiana, United States of America
- University of Washington, Seattle, Washington, United States of America
| | - Chhorvann Chhea
- School of Public Health, National Institute of Public Health, Phnom Penh, Cambodia
| | | | - Robert D Hontz
- U.S. Naval Medical Research Unit No. 6 (NAMRU-6), Lima, Peru
- U.S. Naval Medical Research Unit No. 2 (NAMRU-2), Singapore
| | - Pamina M Gorbach
- University of California Fielding School of Public Health, Los Angeles, California, United States of America
| | - Valerie A Paz-Soldan
- Tulane School of Public Health and Tropical Medicine, New Orleans, Lousiana, United States of America
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86
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Mayton EH, Hernandez HM, Vitek CJ, Christofferson RC. A Method for Repeated, Longitudinal Sampling of Individual Aedes aegypti for Transmission Potential of Arboviruses. INSECTS 2021; 12:292. [PMID: 33801709 PMCID: PMC8065608 DOI: 10.3390/insects12040292] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 03/24/2021] [Accepted: 03/25/2021] [Indexed: 11/21/2022]
Abstract
Mosquito-borne viruses are the cause of significant morbidity and mortality worldwide, especially in low- and middle-income countries. Assessing risk for viral transmission often involves characterization of the vector competence of vector-virus pairings. The most common determination of vector competence uses discreet, terminal time points, which cannot be used to investigate variation in transmission aspects, such as biting behavior, over time. Here, we present a novel method to longitudinally measure individual biting behavior and Zika virus (ZIKV) transmission. Individual mosquitoes were exposed to ZIKV, and from 9 to 24 days post-exposure, individuals were each offered a 180 μL bloodmeal every other day. Biting behavior was observed and characterized as either active probing, feeding, or no bite. The bloodmeal was then collected, spun down, serum collected, and tested for ZIKV RNA via qRT-PCR to determine individuals' vector competence over time. This included whether transmission to the bloodmeal was successful and the titer of expectorated virus. Additionally, serum was inoculated onto Vero cells in order to determine infectiousness of positive recovered sera. Results demonstrate heterogeneity in not only biting patterns but expectorated viral titers among individual mosquitoes over time. These findings demonstrate that the act of transmission is a complex process governed by mosquito behavior and mosquito-virus interaction, and herein we offer a method to investigate this phenomenon.
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Affiliation(s)
- E. Handly Mayton
- Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70803, USA;
| | - Heather M. Hernandez
- Center for Vector-Borne Diseases, The University of Texas Rio Grande Valley, Edinburg, TX 78539, USA; (H.M.H.); (C.J.V.)
| | - Christopher J. Vitek
- Center for Vector-Borne Diseases, The University of Texas Rio Grande Valley, Edinburg, TX 78539, USA; (H.M.H.); (C.J.V.)
| | - Rebecca C. Christofferson
- Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70803, USA;
- Center for Computation and Technology, Louisiana State University, Baton Rouge, LA 70803, USA
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87
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Abellana DP. Modelling the interdependent relationships among epidemic antecedents using fuzzy multiple attribute decision making (F-MADM) approaches. OPEN COMPUTER SCIENCE 2021. [DOI: 10.1515/comp-2020-0213] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Abstract
With the high incidence of the dengue epidemic in developing countries, it is crucial to understand its dynamics from a holistic perspective. This paper analyzes different types of antecedents from a cybernetics perspective using a structural modelling approach. The novelty of this paper is twofold. First, it analyzes antecedents that may be social, institutional, environmental, or economic in nature. Since this type of study has not been done in the context of the dengue epidemic modelling, this paper offers a fresh perspective on this topic. Second, the paper pioneers the use of fuzzy multiple attribute decision making (F-MADM) approaches for the modelling of epidemic antecedents. As such, the paper has provided an avenue for the cross-fertilization of knowledge between scholars working in soft computing and epidemiological modelling domains.
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Affiliation(s)
- Dharyll Prince Abellana
- Department of Computer Science , University of the Philippines – Cebu , Cebu City , Cebu , Philippines
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88
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Lippi CA, Stewart-Ibarra AM, Endy TP, Abbott M, Cueva C, Heras F, Polhemus M, Beltrán-Ayala E, Ryan SJ. Exploring the utility of social-ecological and entomological risk factors for dengue infection as surveillance indicators in the dengue hyper-endemic city of Machala, Ecuador. PLoS Negl Trop Dis 2021; 15:e0009257. [PMID: 33740003 PMCID: PMC8011822 DOI: 10.1371/journal.pntd.0009257] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 03/31/2021] [Accepted: 02/19/2021] [Indexed: 11/17/2022] Open
Abstract
The management of mosquito-borne diseases is a challenge in southern coastal Ecuador, where dengue is hyper-endemic and co-circulates with other arboviral diseases. Prior work in the region has explored social-ecological factors, dengue case data, and entomological indices. In this study, we bring together entomological and epidemiological data to describe links between social-ecological factors associated with risk of dengue transmission at the household level in Machala, Ecuador. Households surveys were conducted from 2014-2017 to assess the presence of adult Aedes aegypti (collected via aspiration) and to enumerate housing conditions, demographics, and mosquito prevention behaviors. Household-level dengue infection status was determined by laboratory diagnostics in 2014-2015. Bivariate analyses and multivariate logistic regression models were used to identify social-ecological variables associated with household presence of female Ae. aegypti and household dengue infection status, respectively. Aedes aegypti presence was associated with interruptions in water service and weekly trash collection, and household air conditioning was protective against mosquito presence. Presence of female Ae. aegypti was not associated with household dengue infections. We identified shaded patios and head of household employment status as risk factors for household-level dengue infection, while window screening in good condition was identified as protective against dengue infection. These findings add to our understanding of the systems of mosquito-borne disease transmission in Machala, and in the larger region of southern Ecuador, aiding in the development of improved vector surveillance efforts, and targeted interventions.
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Affiliation(s)
- Catherine A. Lippi
- Quantitative Disease Ecology and Conservation (QDEC) Lab Group, Department of Geography, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Anna M. Stewart-Ibarra
- Inter-American Institute for Global Change Research, Department of Montevideo, Montevideo, Uruguay
- Institute for Global Health and Translational Studies, State University of New York (SUNY) Upstate Medical University, Syracuse, New York, United States of America
- Department of Medicine, State University of New York (SUNY) Upstate Medical University, Syracuse, New York, United States of America
| | - Timothy P. Endy
- Institute for Global Health and Translational Studies, State University of New York (SUNY) Upstate Medical University, Syracuse, New York, United States of America
- Department of Medicine, State University of New York (SUNY) Upstate Medical University, Syracuse, New York, United States of America
- Department of Microbiology and Immunology, State University of New York (SUNY) Upstate Medical University, Syracuse, New York
| | - Mark Abbott
- Institute for Global Health and Translational Studies, State University of New York (SUNY) Upstate Medical University, Syracuse, New York, United States of America
- Department of Microbiology and Immunology, State University of New York (SUNY) Upstate Medical University, Syracuse, New York
| | - Cinthya Cueva
- Institute for Global Health and Translational Studies, State University of New York (SUNY) Upstate Medical University, Syracuse, New York, United States of America
| | - Froilán Heras
- Institute for Global Health and Translational Studies, State University of New York (SUNY) Upstate Medical University, Syracuse, New York, United States of America
- Department of Medicine, State University of New York (SUNY) Upstate Medical University, Syracuse, New York, United States of America
| | - Mark Polhemus
- Coalition for Epidemic Preparedness Innovations (CEPI), Washington, D.C., United States of America
| | | | - Sadie J. Ryan
- Quantitative Disease Ecology and Conservation (QDEC) Lab Group, Department of Geography, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
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89
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Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents. Nat Commun 2021; 12:1233. [PMID: 33623008 PMCID: PMC7902664 DOI: 10.1038/s41467-021-21496-7] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 01/26/2021] [Indexed: 11/08/2022] Open
Abstract
Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases, such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28–85% for vectors, 44–88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections. The effects of climate on vector-borne disease systems are highly context-dependent. Here, the authors incorporate laboratory-measured physiological traits of the mosquito Aedes aegypti into climate-driven mechanistic models to predict number, timing, and duration of outbreaks in Ecuador and Kenya.
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90
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Telle O, Nikolay B, Kumar V, Benkimoun S, Pal R, Nagpal BN, Paul RE. Social and environmental risk factors for dengue in Delhi city: A retrospective study. PLoS Negl Trop Dis 2021; 15:e0009024. [PMID: 33571202 PMCID: PMC7877620 DOI: 10.1371/journal.pntd.0009024] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Accepted: 12/01/2020] [Indexed: 12/16/2022] Open
Abstract
Global urbanization is leading to an inexorable spread of several major diseases that need to be stemmed. Dengue is one of these major diseases spreading in cities today, with its principal mosquito vector superbly adapted to the urban environment. Current mosquito control strategies are proving inadequate, especially in the face of such urbanisation and novel, evidence-based targeted approaches are needed. Through combined epidemiological and entomological approaches, we aimed to identify a novel sanitation strategy to alleviate the burden of dengue through how the dengue virus spreads through the community. We combined surveillance case mapping, prospective serological studies, year-round mosquito surveys, socio-economic and Knowledge Attitudes and Practices surveys across Delhi. We identified lack of access to tap water (≤98%) as an important risk factor for dengue virus IgG sero-positivity (adjusted Odds Ratio 4.69, 95% C.I. 2.06–10.67) and not poverty per se. Wealthier districts had a higher dengue burden despite lower mosquito densities than the Intermediary income communities (adjusted Odds Ratio 2.92, 95% C.I. 1.26–6.72). This probably reflects dengue being introduced by people travelling from poorer areas to work in wealthier houses. These poorer, high density areas, where temperatures are also warmer, also had dengue cases during the winter. Control strategies based on improved access to a reliable supply of tap water plus focal intervention in intra-urban heat islands prior to the dengue season could not only lead to a reduction in mosquito abundance but also eliminate the reservoir of dengue virus clearly circulating at low levels in winter in socio-economically disadvantaged areas. Identifying disease hotspots and individual risk factors for dengue can enable targeted intervention strategies. We conducted combined serological, entomological and socio-economic surveys across 18 areas within Delhi, taken from the total 1280 colonies (i.e. the administrative units of reference in Delhi) for which we classified their socio-economic typology. We additionally performed a Knowledge, Attitudes, Practices survey at a household level within the most socially disadvantaged sub-districts. Finally, we mapped all the winter dengue cases to 250 m x 250 m units along with their winter mean temperatures. We found that access to tap water was an important risk factor for exposure to dengue virus (DENV) and this was confirmed even within the socially disadvantaged sub-districts. The Wealthy colonies had a high burden of DENV infection despite low mosquito densities, likely linked to their connectedness through daily human mobility. The winter burden of dengue occurred majoritarily in the socio-economically disadvantaged colonies, which also have higher mean temperatures and urban heat islands. Improved access to tap water could lead to a reduction in dengue, not only for those directly affected but for the general population. Targeted intervention through mosquito control in winter in the socially disadvantaged areas could offer a rational strategy for optimising control efforts.
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Affiliation(s)
- Olivier Telle
- Géographie-cités, Université Paris-1 Panthéon-Sorbonne, Paris, France
- Centre for Policy Research, Dharam Marg, Delhi, India
- * E-mail:
| | - Birgit Nikolay
- Mathematical Modelling of Infectious Diseases, Institut Pasteur, Centre National de la Recherche Scientifique, Paris, France
| | - Vikram Kumar
- National Institute of Malaria Research, Sector 8, Dwarka, Delhi, India
| | - Samuel Benkimoun
- Géographie-cités, Université Paris-1 Panthéon-Sorbonne, Paris, France
- Centre de Sciences Humaines, UMIFRE 20 CNRS-MAE,Delhi, India
| | - Rupali Pal
- Centre de Sciences Humaines, UMIFRE 20 CNRS-MAE,Delhi, India
| | - BN Nagpal
- National Institute of Malaria Research, Sector 8, Dwarka, Delhi, India
| | - Richard E. Paul
- Institut Pasteur, Functional Genetics of Infectious Diseases Unit, Paris, France
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91
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Ong SQ, Ahmad H, Mohd Ngesom AM. Implications of the COVID-19 Lockdown on Dengue Transmission in Malaysia. Infect Dis Rep 2021; 13:148-160. [PMID: 33562890 PMCID: PMC7985789 DOI: 10.3390/idr13010016] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 01/28/2021] [Accepted: 02/01/2021] [Indexed: 11/30/2022] Open
Abstract
We aim to investigate the effect of large-scale human movement restrictions during the COVID-19 lockdown on both the dengue transmission and vector occurrences. This study compared the weekly dengue incidences during the period of lockdown to the previous years (2015 to 2019) and a Seasonal Autoregressive Integrated Moving Average (SARIMA) model that expected no movement restrictions. We found that the trend of dengue incidence during the first two weeks (stage 1) of lockdown decreased significantly with the incidences lower than the lower confidence level (LCL) of SARIMA. By comparing the magnitude of the gradient of decrease, the trend is 319% steeper than the trend observed in previous years and 650% steeper than the simulated model, indicating that the control of population movement did reduce dengue transmission. However, starting from stage 2 of lockdown, the dengue incidences demonstrated an elevation and earlier rebound by four weeks and grew with an exponential pattern. We revealed that Aedes albopictus is the predominant species and demonstrated a strong correlation with the locally reported dengue incidences, and therefore we proposed the possible diffusive effect of the vector that led to a higher acceleration of incidence rate.
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Affiliation(s)
- Song-Quan Ong
- CPUS, UOW Malaysia KDU Penang University College, 32, Jalan Anson, George Town 10400, Malaysia
- School of Computer Sciences, Universiti Sains Malaysia, Gelugor 11800, Malaysia
- Correspondence:
| | - Hamdan Ahmad
- Vector Control Research Unit, School of Biological Sciences, Universiti Sains Malaysia, Gelugor 11800, Malaysia;
| | - Ahmad Mohiddin Mohd Ngesom
- Faculty of Health Science, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, Kuala Lumpur 50300, Malaysia;
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92
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Mahmud AS, Kabir MI, Engø-Monsen K, Tahmina S, Riaz BK, Hossain MA, Khanom F, Rahman MM, Rahman MK, Sharmin M, Hossain DM, Yasmin S, Ahmed MM, Lusha MAF, Buckee CO. Megacities as drivers of national outbreaks: The 2017 chikungunya outbreak in Dhaka, Bangladesh. PLoS Negl Trop Dis 2021; 15:e0009106. [PMID: 33529229 PMCID: PMC7880496 DOI: 10.1371/journal.pntd.0009106] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 02/12/2021] [Accepted: 01/04/2021] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Several large outbreaks of chikungunya have been reported in the Indian Ocean region in the last decade. In 2017, an outbreak occurred in Dhaka, Bangladesh, one of the largest and densest megacities in the world. Population mobility and fluctuations in population density are important drivers of epidemics. Measuring population mobility during outbreaks is challenging but is a particularly important goal in the context of rapidly growing and highly connected cities in low- and middle-income countries, which can act to amplify and spread local epidemics nationally and internationally. METHODS We first describe the epidemiology of the 2017 chikungunya outbreak in Dhaka and estimate incidence using a mechanistic model of chikungunya transmission parametrized with epidemiological data from a household survey. We combine the modeled dynamics of chikungunya in Dhaka, with mobility estimates derived from mobile phone data for over 4 million subscribers, to understand the role of population mobility on the spatial spread of chikungunya within and outside Dhaka during the 2017 outbreak. RESULTS We estimate a much higher incidence of chikungunya in Dhaka than suggested by official case counts. Vector abundance, local demographics, and population mobility were associated with spatial heterogeneities in incidence in Dhaka. The peak of the outbreak in Dhaka coincided with the annual Eid holidays, during which large numbers of people traveled from Dhaka to other parts of the country. We show that travel during Eid likely resulted in the spread of the infection to the rest of the country. CONCLUSIONS Our results highlight the impact of large-scale population movements, for example during holidays, on the spread of infectious diseases. These dynamics are difficult to capture using traditional approaches, and we compare our results to a standard diffusion model, to highlight the value of real-time data from mobile phones for outbreak analysis, forecasting, and surveillance.
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Affiliation(s)
- Ayesha S. Mahmud
- Department of Demography, University of California, Berkeley, Berkeley, California, United States of America
- Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Md. Iqbal Kabir
- National Institute of Preventive and Social Medicine, Dhaka, Bangladesh
- Directorate General of Health Services, Dhaka, Bangladesh
| | | | - Sania Tahmina
- Directorate General of Health Services, Dhaka, Bangladesh
| | | | - Md. Akram Hossain
- National Institute of Preventive and Social Medicine, Dhaka, Bangladesh
| | - Fahmida Khanom
- National Institute of Preventive and Social Medicine, Dhaka, Bangladesh
| | | | | | | | | | | | | | | | - Caroline O. Buckee
- Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
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Schaber KL, Perkins TA, Lloyd AL, Waller LA, Kitron U, Paz-Soldan VA, Elder JP, Rothman AL, Civitello DJ, Elson WH, Morrison AC, Scott TW, Vazquez-Prokopec GM. Disease-driven reduction in human mobility influences human-mosquito contacts and dengue transmission dynamics. PLoS Comput Biol 2021; 17:e1008627. [PMID: 33465065 PMCID: PMC7845972 DOI: 10.1371/journal.pcbi.1008627] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 01/29/2021] [Accepted: 12/11/2020] [Indexed: 02/01/2023] Open
Abstract
Heterogeneous exposure to mosquitoes determines an individual’s contribution to vector-borne pathogen transmission. Particularly for dengue virus (DENV), there is a major difficulty in quantifying human-vector contacts due to the unknown coupled effect of key heterogeneities. To test the hypothesis that the reduction of human out-of-home mobility due to dengue illness will significantly influence population-level dynamics and the structure of DENV transmission chains, we extended an existing modeling framework to include social structure, disease-driven mobility reductions, and heterogeneous transmissibility from different infectious groups. Compared to a baseline model, naïve to human pre-symptomatic infectiousness and disease-driven mobility changes, a model including both parameters predicted an increase of 37% in the probability of a DENV outbreak occurring; a model including mobility change alone predicted a 15.5% increase compared to the baseline model. At the individual level, models including mobility change led to a reduction of the importance of out-of-home onward transmission (R, the fraction of secondary cases predicted to be generated by an individual) by symptomatic individuals (up to -62%) at the expense of an increase in the relevance of their home (up to +40%). An individual’s positive contribution to R could be predicted by a GAM including a non-linear interaction between an individual’s biting suitability and the number of mosquitoes in their home (>10 mosquitoes and 0.6 individual attractiveness significantly increased R). We conclude that the complex fabric of social relationships and differential behavioral response to dengue illness cause the fraction of symptomatic DENV infections to concentrate transmission in specific locations, whereas asymptomatic carriers (including individuals in their pre-symptomatic period) move the virus throughout the landscape. Our findings point to the difficulty of focusing vector control interventions reactively on the home of symptomatic individuals, as this approach will fail to contain virus propagation by visitors to their house and asymptomatic carriers. Human mobility patterns can play an integral role in vector-borne disease dynamics by characterizing an individual’s potential contacts with disease-transmitting vectors. Dengue virus is transmitted by a sedentary vector, but human mobility allows individuals to have contact with mosquitoes at their home and other houses they frequent (their activity space). When accounting for the decreased mobility of symptomatic dengue cases in an agent-based simulation model, however, we found a severely diminished role of the activity space in onward transmission. Those who received the majority of their mosquito contacts outside their home experienced decreases in expected bites and onward transmission when mobility changes were accounted for. Onward transmission was driven by a synergistic relationship between the number of mosquitoes in an individual’s home and their biting suitability, where even those with the highest biting suitability would have limited contribution to transmission given a low number of household mosquitoes. Reactive vector control, which often targets symptomatic cases, could be effective for slowing onward transmission from these cases, but will fail to control virus transmission due to the disproportionate contribution of asymptomatic infections.
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Affiliation(s)
- Kathryn L. Schaber
- Program of Population Biology, Ecology and Evolution, Emory University, Atlanta, Georgia, United States of America
| | - T. Alex Perkins
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Alun L. Lloyd
- Biomathematics Graduate Program and Department of Mathematics, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Lance A. Waller
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Uriel Kitron
- Department of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America
| | - Valerie A. Paz-Soldan
- Department of Global Community Health and Behavioral Sciences, Tulane School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America
| | - John P. Elder
- Graduate School of Public Health, San Diego State University, San Diego, California, United States of America
| | - Alan L. Rothman
- Institute for Immunology and Informatics and Department of Cell and Molecular Biology, University of Rhode Island, Providence, Rhode Island, United States of America
| | - David J. Civitello
- Department of Biology, Emory University, Atlanta, Georgia, United States of America
| | - William H. Elson
- Department of Entomology and Nematology, University of California Davis, Davis, California, United States of America
| | - Amy C. Morrison
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, California, United States of America
| | - Thomas W. Scott
- Department of Entomology and Nematology, University of California Davis, Davis, California, United States of America
| | - Gonzalo M. Vazquez-Prokopec
- Program of Population Biology, Ecology and Evolution, Emory University, Atlanta, Georgia, United States of America
- Department of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America
- * E-mail:
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94
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Effect of daily human movement on some characteristics of dengue dynamics. Math Biosci 2021; 332:108531. [PMID: 33460675 DOI: 10.1016/j.mbs.2020.108531] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Revised: 12/09/2020] [Accepted: 12/10/2020] [Indexed: 11/21/2022]
Abstract
Human movement is a key factor in infectious diseases spread such as dengue. Here, we explore a mathematical modeling approach based on a system of ordinary differential equations to study the effect of human movement on characteristics of dengue dynamics such as the existence of endemic equilibria, and the start, duration, and amplitude of the outbreak. The model considers that every day is divided into two periods: high-activity and low-activity. Periodic human movement between patches occurs in discrete times. Based on numerical simulations, we show unexpected scenarios such as the disease extinction in regions where the local basic reproductive number is greater than 1. In the same way, we obtain scenarios where outbreaks appear despite the fact that the local basic reproductive numbers in these regions are less than 1 and the outbreak size depends on the length of high-activity and low-activity periods.
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95
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Kiang MV, Santillana M, Chen JT, Onnela JP, Krieger N, Engø-Monsen K, Ekapirat N, Areechokchai D, Prempree P, Maude RJ, Buckee CO. Incorporating human mobility data improves forecasts of Dengue fever in Thailand. Sci Rep 2021; 11:923. [PMID: 33441598 PMCID: PMC7806770 DOI: 10.1038/s41598-020-79438-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 11/19/2020] [Indexed: 01/08/2023] Open
Abstract
Over 390 million people worldwide are infected with dengue fever each year. In the absence of an effective vaccine for general use, national control programs must rely on hospital readiness and targeted vector control to prepare for epidemics, so accurate forecasting remains an important goal. Many dengue forecasting approaches have used environmental data linked to mosquito ecology to predict when epidemics will occur, but these have had mixed results. Conversely, human mobility, an important driver in the spatial spread of infection, is often ignored. Here we compare time-series forecasts of dengue fever in Thailand, integrating epidemiological data with mobility models generated from mobile phone data. We show that geographically-distant provinces strongly connected by human travel have more highly correlated dengue incidence than weakly connected provinces of the same distance, and that incorporating mobility data improves traditional time-series forecasting approaches. Notably, no single model or class of model always outperformed others. We propose an adaptive, mosaic forecasting approach for early warning systems.
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Affiliation(s)
- Mathew V Kiang
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA
| | - Mauricio Santillana
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA.,Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA
| | - Jarvis T Chen
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jukka-Pekka Onnela
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Nancy Krieger
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Nattwut Ekapirat
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Darin Areechokchai
- Bureau of Vector Borne Disease, Ministry of Public Health, Nonthaburi, Thailand
| | - Preecha Prempree
- Bureau of Vector Borne Disease, Ministry of Public Health, Nonthaburi, Thailand
| | - Richard J Maude
- Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand.,Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK.,Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, 5th Floor, Boston, MA, 02115, USA
| | - Caroline O Buckee
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. .,Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, 5th Floor, Boston, MA, 02115, USA.
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96
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Kirstein OD, Ayora-Talavera G, Koyoc-Cardeña E, Chan Espinoza D, Che-Mendoza A, Cohuo-Rodriguez A, Granja-Pérez P, Puerta-Guardo H, Pavia-Ruz N, Dunbar MW, Manrique-Saide P, Vazquez-Prokopec GM. Natural arbovirus infection rate and detectability of indoor female Aedes aegypti from Mérida, Yucatán, Mexico. PLoS Negl Trop Dis 2021; 15:e0008972. [PMID: 33395435 PMCID: PMC7781390 DOI: 10.1371/journal.pntd.0008972] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 11/10/2020] [Indexed: 12/03/2022] Open
Abstract
Arbovirus infection in Aedes aegypti has historically been quantified from a sample of the adult population by pooling collected mosquitoes to increase detectability. However, there is a significant knowledge gap about the magnitude of natural arbovirus infection within areas of active transmission, as well as the sensitivity of detection of such an approach. We used indoor Ae. aegypti sequential sampling with Prokopack aspirators to collect all mosquitoes inside 200 houses with suspected active ABV transmission from the city of Mérida, Mexico, and tested all collected specimens by RT-PCR to quantify: a) the absolute arbovirus infection rate in individually tested Ae. aegypti females; b) the sensitivity of using Prokopack aspirators in detecting ABV-infected mosquitoes; and c) the sensitivity of entomological inoculation rate (EIR) and vectorial capacity (VC), two measures ABV transmission potential, to different estimates of indoor Ae. aegypti abundance. The total number of Ae. aegypti (total catch, the sum of all Ae. aegypti across all collection intervals) as well as the number on the first 10-min of collection (sample, equivalent to a routine adult aspiration session) were calculated. We individually tested by RT-PCR 2,161 Aedes aegypti females and found that 7.7% of them were positive to any ABV. Most infections were CHIKV (77.7%), followed by DENV (11.4%) and ZIKV (9.0%). The distribution of infected Aedes aegypti was overdispersed; 33% houses contributed 81% of the infected mosquitoes. A significant association between ABV infection and Ae. aegypti total catch indoors was found (binomial GLMM, Odds Ratio > 1). A 10-min indoor Prokopack collection led to a low sensitivity of detecting ABV infection (16.3% for detecting infected mosquitoes and 23.4% for detecting infected houses). When averaged across all infested houses, mean EIR ranged between 0.04 and 0.06 infective bites per person per day, and mean VC was 0.6 infectious vectors generated from a population feeding on a single infected host per house/day. Both measures were significantly and positively associated with Ae. aegypti total catch indoors. Our findings provide evidence that the accurate estimation and quantification of arbovirus infection rate and transmission risk is a function of the sampling effort, the local abundance of Aedes aegypti and the intensity of arbovirus circulation. Aedes-borne diseases comprise a serious public health burden in many parts of the world, usually affecting low income areas. The ability to detect virus circulation within a population may be key in responding to the threat of outbreaks, providing a cost-effective approach for triggering vector control. Unfortunately, gaps in the knowledge of natural Aedes-borne virus (ABV) infection in Aedes aegypti have led to uncertainties in the consideration of arbovirus surveillance in mosquitoes. Here, we show that the natural infection rate in a mosquito population may not be a function of where Aedes aegypti are, but rather where key human-mosquito contacts occur. Sampling 200 houses with suspected ABV active transmission led us to quantify high virus infection rates in all Aedes aegypti present in the house and use such information to estimate the sensitivity of indoor aspiration with Prokopack devices and two measures of ABV transmission potential. Our findings provide evidence that the accurate quantification of arbovirus infection rate and transmission risk is a function of the sampling effort, the local abundance of Aedes aegypti and the intensity of arbovirus circulation. Results from this study are relevant to understand the value of virus testing of vector populations, and for the design of entomological endpoints relevant for epidemiological trials quantifying the impact of vector control on ABVs.
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Affiliation(s)
- Oscar David Kirstein
- Department of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America
| | - Guadalupe Ayora-Talavera
- Laboratorio de Virología. Centro de Investigaciones Regionales “Dr. Hideyo Noguchi”, Universidad Autónoma de Yucatán, Mérida, Yucatán, México
| | - Edgar Koyoc-Cardeña
- Unidad Colaborativa de Bioensayos Entomológicos, Campus de Ciencias Biológicas y Agropecuarias, Universidad Autónoma de Yucatán, Mérida, Yucatán, México
| | - Daniel Chan Espinoza
- Unidad Colaborativa de Bioensayos Entomológicos, Campus de Ciencias Biológicas y Agropecuarias, Universidad Autónoma de Yucatán, Mérida, Yucatán, México
| | - Azael Che-Mendoza
- Unidad Colaborativa de Bioensayos Entomológicos, Campus de Ciencias Biológicas y Agropecuarias, Universidad Autónoma de Yucatán, Mérida, Yucatán, México
| | - Azael Cohuo-Rodriguez
- Unidad Colaborativa de Bioensayos Entomológicos, Campus de Ciencias Biológicas y Agropecuarias, Universidad Autónoma de Yucatán, Mérida, Yucatán, México
| | - Pilar Granja-Pérez
- Laboratorio Estatal de Salud Pública, Servicios de Salud de Yucatán, Mérida, Yucatán, México
| | - Henry Puerta-Guardo
- Unidad Colaborativa de Bioensayos Entomológicos, Campus de Ciencias Biológicas y Agropecuarias, Universidad Autónoma de Yucatán, Mérida, Yucatán, México
| | - Norma Pavia-Ruz
- Laboratorio de Hematología. Centro de Investigaciones Regionales “Dr. Hideyo Noguchi”, Universidad Autónoma de Yucatán, Mérida, Yucatán, México
| | - Mike W. Dunbar
- Department of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America
| | - Pablo Manrique-Saide
- Unidad Colaborativa de Bioensayos Entomológicos, Campus de Ciencias Biológicas y Agropecuarias, Universidad Autónoma de Yucatán, Mérida, Yucatán, México
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Abstract
PURPOSE OF REVIEW Societal lockdowns in response to the COVID-19 pandemic have led to unprecedented disruption to daily life across the globe. A collateral effect of these lockdowns may be a change to transmission dynamics of a wide range of infectious diseases that are all highly dependent on rates of contact between humans. With timing, duration and intensity of lockdowns varying country-to-country, the wave of lockdowns in 2020 present a unique opportunity to observe how changes in human contact rates, disease control and surveillance affect dengue virus transmission in a global natural experiment. We explore the theoretical basis for the impact of lockdowns on dengue transmission and surveillance then summarise the current evidence base from country reports. RECENT FINDINGS We find considerable variation in the intensity of dengue epidemics reported so far in 2020 with some countries experiencing historic low levels of transmission while others are seeing record outbreaks. Despite many studies warning of the risks of lockdown for dengue transmission, few empirically quantify the impact and issues such as the specific timing of the lockdowns and multi-annual cycles of dengue are not accounted for. In the few studies where such issues have been accounted for, the impact of lockdowns on dengue appears to be limited. SUMMARY Studying the impact of lockdowns on dengue transmission is important both in how we deal with the immediate COVID-19 and dengue crisis, but also over the coming years in the post-pandemic recovery period. It is clear lockdowns have had very different impacts in different settings. Further analyses might ultimately allow this unique natural experiment to provide insights into how to better control dengue that will ultimately lead to better long-term control.
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Affiliation(s)
- Oliver Brady
- Department of Disease Control, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK
| | - Annelies Wilder-Smith
- Department of Disease Control, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK
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98
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Li Y, Dou Q, Lu Y, Xiang H, Yu X, Liu S. Effects of ambient temperature and precipitation on the risk of dengue fever: A systematic review and updated meta-analysis. ENVIRONMENTAL RESEARCH 2020; 191:110043. [PMID: 32810500 DOI: 10.1016/j.envres.2020.110043] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/24/2019] [Revised: 05/21/2020] [Accepted: 08/04/2020] [Indexed: 05/16/2023]
Abstract
OBJECTIVES We systematically reviewed the published studies on the relationship between dengue fever and meteorological factors and applied a meta-analysis to explore the effects of ambient temperature and precipitation on dengue fever. METHODS We completed the literature search by the end of September 1st, 2019 using databases including Science Direct, PubMed, Web of Science, and Google Scholar. We extracted relative risks (RRs) in selected studies and converted all effect estimates to the RRs per 1 °C increase in temperature and 10 mm increase in precipitation, and combined all standardized RRs together using random-effect meta-analysis. RESULTS Our results show that dengue fever was significantly associated with both temperature and precipitation. Our subgroup analyses suggested that the effect of temperature on dengue fever was most pronounced in high-income subtropical areas. The pooled RR of dengue fever associated with the maximum temperature was much lower than the overall effect. CONCLUSIONS Temperature and precipitation are important risk factors for dengue fever. Future studies should focus on factors that can distort the effects of temperature and precipitation.
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Affiliation(s)
- Yanbing Li
- School of Health Sciences, Wuhan University, 115 Donghu Road, 430071, Wuhan, China
| | - Qiujun Dou
- School of Health Sciences, Wuhan University, 115 Donghu Road, 430071, Wuhan, China
| | - Yuanan Lu
- Environmental Health Laboratory, Department of Public Health Sciences, University Hawaii at Manoa, 1960 East West Rd, Biomed Bldg, D105, Honolulu, USA
| | - Hao Xiang
- School of Health Sciences, Wuhan University, 115 Donghu Road, 430071, Wuhan, China
| | - Xuejie Yu
- School of Health Sciences, Wuhan University, 115 Donghu Road, 430071, Wuhan, China
| | - Suyang Liu
- School of Health Sciences, Wuhan University, 115 Donghu Road, 430071, Wuhan, China.
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Kuno G. The Absence of Yellow Fever in Asia: History, Hypotheses, Vector Dispersal, Possibility of YF in Asia, and Other Enigmas. Viruses 2020; 12:E1349. [PMID: 33255615 PMCID: PMC7759908 DOI: 10.3390/v12121349] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 11/12/2020] [Accepted: 11/17/2020] [Indexed: 01/11/2023] Open
Abstract
Since the recent epidemics of yellow fever in Angola and Brazil as well as the importation of cases to China in 2016, there has been an increased interest in the century-old enigma, absence of yellow fever in Asia. Although this topic has been repeatedly reviewed before, the history of human intervention has never been considered a critical factor. A two-stage literature search online for this review, however, yielded a rich history indispensable for the debate over this medical enigma. As we combat the pandemic of COVID-19 coronavirus worldwide today, we can learn invaluable lessons from the historical events in Asia. In this review, I explore the history first and then critically examine in depth major hypotheses proposed in light of accumulated data, global dispersal of the principal vector, patterns of YF transmission, persistence of urban transmission, and the possibility of YF in Asia. Through this process of re-examination of the current knowledge, the subjects for research that should be conducted are identified. This review also reveals the importance of holistic approach incorporating ecological and human factors for many unresolved subjects, such as the enigma of YF absence in Asia, vector competence, vector dispersal, spillback, viral persistence and transmission mechanisms.
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Affiliation(s)
- Goro Kuno
- Centers for Disease Control and Prevention, Formerly Division of Vector-Borne Infectious Diseases, Fort Collins, CO 80521, USA
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Balingit JC, Carvajal TM, Saito-Obata M, Gamboa M, Nicolasora AD, Sy AK, Oshitani H, Watanabe K. Surveillance of dengue virus in individual Aedes aegypti mosquitoes collected concurrently with suspected human cases in Tarlac City, Philippines. Parasit Vectors 2020; 13:594. [PMID: 33239063 PMCID: PMC7687837 DOI: 10.1186/s13071-020-04470-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Accepted: 11/05/2020] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Vector control measures are critical for the prevention and reduction of dengue virus (DENV) transmission. Effective vector control is reliant not only on knowledge of mosquito abundance, but also on the timely and accurate detection of mosquito-borne infection. Mosquito-based virus surveillance programs typically rely on pool-based mosquito testing, although whether individual-based mosquito testing is a feasible alternative to this has not been widely studied. Applying an individual-based mosquito testing approach, we conducted a 1-month surveillance study of DENV in adult Aedes aegypti mosquitoes in homes of suspected dengue patients during the 2015 peak dengue season in Tarlac City, Philippines to more accurately assess the mosquito infection rate and identify the DENV serotypes and genotypes concurrently co-circulating in mosquitoes and patients there. METHODS We performed a one-step multiplex real-time reverse transcription-polymerase chain reaction (RT-PCR) assay for the simultaneous detection and serotyping of DENV in patients and individual female Ae. aegypti mosquitoes. Additionally, we performed sequencing and phylogenetic analyses to further characterize the detected DENV serotypes in mosquitoes and patients at the genotype level. RESULTS We collected a total of 583 adult Ae. aegypti mosquitoes, of which we individually tested 359 female mosquitoes for the presence of DENV. Ten (2.8%) of the 359 female mosquitoes were positive for the presence of DENV. We detected DENV-1, DENV-2, and DENV-4 in the field-collected mosquitoes, which was consistent with the serotypes concurrently found in infected patients. Sequencing and phylogenetic analyses of the detected DENV serotypes based on the partial sequence of the evelope (E) gene revealed three genotypes concurrently present in the sampled mosquitoes and patients during the study period, namely DENV-1 genotype IV, DENV-2 Cosmopolitan genotype, and DENV-4 genotype II. CONCLUSIONS We demonstrated the utility of a one-step multiplex real-time RT-PCR assay for the individual-based DENV surveillance of mosquitoes. Our findings reinforce the importance of detecting and monitoring virus activity in local mosquito populations, which are critical for dengue prevention and control.
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Affiliation(s)
- Jean Claude Balingit
- Center for Marine Environmental Studies (CMES), Ehime University, Matsuyama, Ehime Japan
- Graduate School of Science and Engineering, Ehime University, Matsuyama, Ehime Japan
| | - Thaddeus M. Carvajal
- Center for Marine Environmental Studies (CMES), Ehime University, Matsuyama, Ehime Japan
- Graduate School of Science and Engineering, Ehime University, Matsuyama, Ehime Japan
- Biological Control Research Unit, Center for Natural Science and Environmental Research, De La Salle University, Taft Avenue, Manila, Philippines
| | - Mariko Saito-Obata
- Department of Virology, Tohoku University Graduate School of Medicine, Sendai, Miyagi Japan
- Tohoku-RITM Collaborative Research Center on Emerging and Reemerging Infectious Diseases, Muntinlupa, Metro Manila Philippines
| | - Maribet Gamboa
- Center for Marine Environmental Studies (CMES), Ehime University, Matsuyama, Ehime Japan
- Graduate School of Science and Engineering, Ehime University, Matsuyama, Ehime Japan
| | - Amalea Dulcene Nicolasora
- Molecular Biology Laboratory, Research Institute for Tropical Medicine, Muntinlupa, Metro Manila Philippines
| | - Ava Kristy Sy
- Virology Department, Research Institute for Tropical Medicine, Muntinlupa, Metro Manila Philippines
| | - Hitoshi Oshitani
- Department of Virology, Tohoku University Graduate School of Medicine, Sendai, Miyagi Japan
| | - Kozo Watanabe
- Center for Marine Environmental Studies (CMES), Ehime University, Matsuyama, Ehime Japan
- Graduate School of Science and Engineering, Ehime University, Matsuyama, Ehime Japan
- Biological Control Research Unit, Center for Natural Science and Environmental Research, De La Salle University, Taft Avenue, Manila, Philippines
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