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Cruz EI, Salazar FV, Aguila AMA, Villaruel-Jagmis MV, Ramos J, Paul RE. Current and lagged associations of meteorological variables and Aedes mosquito indices with dengue incidence in the Philippines. PLoS Negl Trop Dis 2024; 18:e0011603. [PMID: 39042669 PMCID: PMC11296630 DOI: 10.1371/journal.pntd.0011603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 08/02/2024] [Accepted: 06/27/2024] [Indexed: 07/25/2024] Open
Abstract
BACKGROUND Dengue is an increasing health burden that has spread throughout the tropics and sub-tropics. There is currently no effective vaccine and control is only possible through integrated vector management. Early warning systems (EWS) to alert potential dengue outbreaks are currently being explored but despite showing promise are yet to come to fruition. This study addresses the association of meteorological variables with both mosquito indices and dengue incidences and assesses the added value of additionally using mosquito indices for predicting dengue incidences. METHODOLOGY/PRINCIPAL FINDINGS Entomological surveys were carried out monthly for 14 months in six sites spread across three environmentally different cities of the Philippines. Meteorological and dengue data were acquired. Non-linear generalized additive models were fitted to test associations of the meteorological variables with both mosquito indices and dengue cases. Rain and the diurnal temperature range (DTR) contributed most to explaining the variation in both mosquito indices and number of dengue cases. DTR and minimum temperature also explained variation in dengue cases occurring one and two months later and may offer potentially useful variables for an EWS. The number of adult mosquitoes did associate with the number of dengue cases, but contributed no additional value to meteorological variables for explaining variation in dengue cases. CONCLUSIONS/SIGNIFICANCE The use of meteorological variables to predict future risk of dengue holds promise. The lack of added value of using mosquito indices confirms several previous studies and given the onerous nature of obtaining such information, more effort should be placed on improving meteorological information at a finer scale to evaluate efficacy in early warning of dengue outbreaks.
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Affiliation(s)
- Estrella I. Cruz
- Department of Medical Entomology, Research Institute for Tropical Medicine, Filinvest Corporate City, Alabang, Muntinlupa City, Philippines
| | - Ferdinand V. Salazar
- Department of Medical Entomology, Research Institute for Tropical Medicine, Filinvest Corporate City, Alabang, Muntinlupa City, Philippines
| | - Ariza Minelle A. Aguila
- Department of Medical Entomology, Research Institute for Tropical Medicine, Filinvest Corporate City, Alabang, Muntinlupa City, Philippines
| | - Mary Vinessa Villaruel-Jagmis
- Department of Medical Entomology, Research Institute for Tropical Medicine, Filinvest Corporate City, Alabang, Muntinlupa City, Philippines
| | - Jennifer Ramos
- Department of Medical Entomology, Research Institute for Tropical Medicine, Filinvest Corporate City, Alabang, Muntinlupa City, Philippines
| | - Richard E. Paul
- Ecology and Emergence of Arthropod-borne Pathogens unit, Institut Pasteur, Université Paris-Cité, Centre National de Recherche Scientifique (CNRS) UMR 2000, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) USC 1510, Paris, France
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Schlesinger M, Prieto Alvarado FE, Borbón Ramos ME, Sewe MO, Merle CS, Kroeger A, Hussain-Alkhateeb L. Enabling countries to manage outbreaks: statistical, operational, and contextual analysis of the early warning and response system (EWARS-csd) for dengue outbreaks. Front Public Health 2024; 12:1323618. [PMID: 38314090 PMCID: PMC10834665 DOI: 10.3389/fpubh.2024.1323618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 01/08/2024] [Indexed: 02/06/2024] Open
Abstract
Introduction Dengue is currently the fastest-spreading mosquito-borne viral illness in the world, with over half of the world's population living in areas at risk of dengue. As dengue continues to spread and become more of a health burden, it is essential to have tools that can predict when and where outbreaks might occur to better prepare vector control operations and communities' responses. One such predictive tool, the Early Warning and Response System for climate-sensitive diseases (EWARS-csd), primarily uses climatic data to alert health systems of outbreaks weeks before they occur. EWARS-csd uses the robust Distribution Lag Non-linear Model in combination with the INLA Bayesian regression framework to predict outbreaks, utilizing historical data. This study seeks to validate the tool's performance in two states of Colombia, evaluating how well the tool performed in 11 municipalities of varying dengue endemicity levels. Methods The validation study used retrospective data with alarm indicators (mean temperature and rain sum) and an outbreak indicator (weekly hospitalizations) from 11 municipalities spanning two states in Colombia from 2015 to 2020. Calibrations of different variables were performed to find the optimal sensitivity and positive predictive value for each municipality. Results The study demonstrated that the tool produced overall reliable early outbreak alarms. The median of the most optimal calibration for each municipality was very high: sensitivity (97%), specificity (94%), positive predictive value (75%), and negative predictive value (99%; 95% CI). Discussion The tool worked well across all population sizes and all endemicity levels but had slightly poorer results in the highly endemic municipality at predicting non-outbreak weeks. Migration and/or socioeconomic status are factors that might impact predictive performance and should be further evaluated. Overall EWARS-csd performed very well, providing evidence that it should continue to be implemented in Colombia and other countries for outbreak prediction.
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Affiliation(s)
- Mikaela Schlesinger
- Global Health Research Group, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden
| | - Franklyn Edwin Prieto Alvarado
- Directorate of Surveillance and Risk Analysis in Public Health, Instituto Nacional de Salud (INS) de Colombia, Bogota, Colombia
| | - Milena Edith Borbón Ramos
- Directorate of Surveillance and Risk Analysis in Public Health, Instituto Nacional de Salud (INS) de Colombia, Bogota, Colombia
| | - Maquins Odhiambo Sewe
- Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, Umeå, Sweden
| | - Corinne Simone Merle
- Special Program for Research and Training in Tropical Diseases (TDR-WHO), World Health Organization, Geneva, Switzerland
| | - Axel Kroeger
- Freiburg University, Center for Medicine, and Society (ZMG)/Institute of Infection Prevention, Freiburg, Germany
| | - Laith Hussain-Alkhateeb
- Global Health Research Group, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden
- Population Health Research Section, King Abdullah International Medical Research Center (KAIMRC), King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia
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Sugeno M, Kawazu EC, Kim H, Banouvong V, Pehlivan N, Gilfillan D, Kim H, Kim Y. Association between environmental factors and dengue incidence in Lao People's Democratic Republic: a nationwide time-series study. BMC Public Health 2023; 23:2348. [PMID: 38012549 PMCID: PMC10683213 DOI: 10.1186/s12889-023-17277-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 11/20/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Dengue fever is a vector-borne disease of global public health concern, with an increasing number of cases and a widening area of endemicity in recent years. Meteorological factors influence dengue transmission. This study aimed to estimate the association between meteorological factors (i.e., temperature and rainfall) and dengue incidence and the effect of altitude on this association in the Lao People's Democratic Republic (Lao PDR). METHODS We used weekly dengue incidence and meteorological data, including temperature and rainfall, from 18 jurisdictions in Lao PDR from 2015 to 2019. A two-stage distributed lag nonlinear model with a quasi-Poisson distribution was used to account for the nonlinear and delayed associations between dengue incidence and meteorological variables, adjusting for long-term time trends and autocorrelation. RESULTS A total of 55,561 cases were reported in Lao PDR from 2015 to 2019. The cumulative relative risk for the 90th percentile of weekly mean temperature (29 °C) over 22 weeks was estimated at 4.21 (95% confidence interval: 2.00-8.84), relative to the 25th percentile (24 °C). The cumulative relative risk for the weekly total rainfall over 12 weeks peaked at 82 mm (relative risk = 1.76, 95% confidence interval: 0.91-3.40) relative to no rain. However, the risk decreased significantly when heavy rain exceeded 200 mm. We found no evidence that altitude modified these associations. CONCLUSIONS We found a lagged nonlinear relationship between meteorological factors and dengue incidence in Lao PDR. These findings can be used to develop climate-based early warning systems and provide insights for improving vector control in the country.
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Affiliation(s)
- Masumi Sugeno
- Department of Global Environmental Health, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
| | - Erin C Kawazu
- Institute for Global Environmental Strategies, Hayama, Japan
| | - Hyun Kim
- School of Public Health, University of Minnesota Twin Cities, Minneapolis, USA
| | - Virasack Banouvong
- Lao PDR Centre for Malariology, Parasitology and Entomology, Vientiane Capital, Lao People's Democratic Republic
| | - Nazife Pehlivan
- Graduate School of Public Health, Seoul National University, 1 Gwanak-Ro, Gwanak-Gu, Seoul, 151-742, South Korea
| | - Daniel Gilfillan
- Fenner School of Environment and Society, Australian National University, Australian Capital Territory, Canberra, Australia
| | - Ho Kim
- Graduate School of Public Health, Seoul National University, 1 Gwanak-Ro, Gwanak-Gu, Seoul, 151-742, South Korea.
| | - Yoonhee Kim
- Department of Global Environmental Health, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan.
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Khan MB, Yang ZS, Lin CY, Hsu MC, Urbina AN, Assavalapsakul W, Wang WH, Chen YH, Wang SF. Dengue overview: An updated systemic review. J Infect Public Health 2023; 16:1625-1642. [PMID: 37595484 DOI: 10.1016/j.jiph.2023.08.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 07/24/2023] [Accepted: 08/01/2023] [Indexed: 08/20/2023] Open
Abstract
Dengue is caused by the dengue virus (DENVs) infection and clinical manifestations include dengue fever (DF), dengue hemorrhagic fever (DHF), or dengue shock syndrome (DSS). Due to a lack of antiviral drugs and effective vaccines, several therapeutic and control strategies have been proposed. A systemic literature review was conducted according to PRISMA guidelines to select proper references to give an overview of DENV infection. Results indicate that understanding the virus characteristics and epidemiology are essential to gain the basic and clinical knowledge as well as dengue disseminated pattern and status. Different factors and mechanisms are thought to be involved in the presentation of DHF and DSS, including antibody-dependent enhancement, immune dysregulation, viral virulence, host genetic susceptibility, and preexisting dengue antibodies. This study suggests that dissecting pathogenesis and risk factors as well as developing different types of therapeutic and control strategies against DENV infection are urgently needed.
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Affiliation(s)
- Muhammad Bilal Khan
- Center for Tropical Medicine and Infectious Disease Research, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; Department of Medical Laboratory Science and Biotechnology, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Zih-Syuan Yang
- Center for Tropical Medicine and Infectious Disease Research, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; Department of Medical Laboratory Science and Biotechnology, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Chih-Yen Lin
- Center for Tropical Medicine and Infectious Disease Research, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; Department of Medical Laboratory Science and Biotechnology, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Ming-Cheng Hsu
- Center for Tropical Medicine and Infectious Disease Research, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; Department of Medical Laboratory Science and Biotechnology, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Aspiro Nayim Urbina
- Center for Tropical Medicine and Infectious Disease Research, Kaohsiung Medical University, Kaohsiung 80708, Taiwan
| | - Wanchai Assavalapsakul
- Department of Microbiology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Wen-Hung Wang
- School of Medicine, College of Medicine, National Sun Yat-Sen University, Kaohsiung 804201, Taiwan
| | - Yen-Hsu Chen
- Center for Tropical Medicine and Infectious Disease Research, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; School of Medicine, College of Medicine, National Sun Yat-Sen University, Kaohsiung 804201, Taiwan; Division of Infectious Disease, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung 80708, Taiwan
| | - Sheng-Fan Wang
- Center for Tropical Medicine and Infectious Disease Research, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; Department of Medical Laboratory Science and Biotechnology, Kaohsiung Medical University, Kaohsiung 80708, Taiwan; Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung 80708, Taiwan.
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Sanchez Tejeda G, Benitez Valladares D, Correa Morales F, Toledo Cisneros J, Espinoza Tamarindo BE, Hussain-Alkhateeb L, Merle CS, Kroeger A. Early warning and response system for dengue outbreaks: Moving from research to operational implementation in Mexico. PLOS GLOBAL PUBLIC HEALTH 2023; 3:e0001691. [PMID: 37729119 PMCID: PMC10511095 DOI: 10.1371/journal.pgph.0001691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 07/19/2023] [Indexed: 09/22/2023]
Abstract
Dengue disease epidemics have increased in time and space due to climatic and non-climatic factors such as urbanization. In the absence of an effective vaccine, preventing dengue outbreak relies on vector control activities. Employing computerized tools to predict outbreaks and respond in advance has great potential for improving dengue disease control. Evidence of integrating or implementing such applications into control programs and their impact are scarce, and endemic countries demand for experience sharing and know-how transfer. Mexico has extensive experience of pre-validated EWARS (Early Warning And Response System), a tool that was developed in 2012 as part of a collaboration with the Special Program for Research and Training in Tropical Diseases Unit (TDR) at the World Health Organization and used at national level. The advancement of EWARS since 2014 and its stepwise integration into the national surveillance system has increased the appreciation of the need for integrated surveillance (including disease, vector and climate surveillance), and for linking inter-institutional and trans-sectoral information for holistic epidemiological intelligence. The integration of the EWARS software into the national surveillance platform in Mexico was a remarkable milestone and a successful experience. This manuscript describes the implementation process of EWARS in Mexico, which started in 2012 and further demonstrates benefits, threats, and opportunities of integrating EWARS into existing national surveillance programs.
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Affiliation(s)
- Gustavo Sanchez Tejeda
- Formerly CENAPRECE (Centro Nacional de Programas Preventivos y Control de Enfermedades), Secretaria de Salud, México City, México
| | - David Benitez Valladares
- Formerly CENAPRECE (Centro Nacional de Programas Preventivos y Control de Enfermedades), Secretaria de Salud, México City, México
| | | | | | | | - Laith Hussain-Alkhateeb
- Global Health Research Group, School of Public Health and Community Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Population Health Section, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia
| | - Corinne S. Merle
- Special Program for Research and Training in Tropical Diseases (TDR-WHO), World Health Organization, Geneva, Switzerland
| | - Axel Kroeger
- Centre for Medicine, and Society (ZMG), Freiburg University, Freiburg, Germany
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Robert MA, Rodrigues HS, Herrera D, de Mata Donado Campos J, Morilla F, Del Águila Mejía J, Guardado ME, Skewes R, Colomé-Hidalgo M. Spatiotemporal and meteorological relationships in dengue transmission in the Dominican Republic, 2015-2019. Trop Med Health 2023; 51:32. [PMID: 37269000 DOI: 10.1186/s41182-023-00517-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 04/30/2023] [Indexed: 06/04/2023] Open
Abstract
Dengue has broadened its global distribution substantially in the past two decades, and many endemic areas are experiencing increases in incidence. The Dominican Republic recently experienced its two largest outbreaks to date with 16,836 reported cases in 2015 and 20,123 reported cases in 2019. With continued increases in dengue transmission, developing tools to better prepare healthcare systems and mosquito control agencies is of critical importance. Before such tools can be developed, however, we must first better understand potential drivers of dengue transmission. To that end, we focus in this paper on determining relationships between climate variables and dengue transmission with an emphasis on eight provinces and the capital city of the Dominican Republic in the period 2015-2019. We present summary statistics for dengue cases, temperature, precipitation, and relative humidity in this period, and we conduct an analysis of correlated lags between climate variables and dengue cases as well as correlated lags among dengue cases in each of the nine locations. We find that the southwestern province of Barahona had the largest dengue incidence in both 2015 and 2019. Among all climate variables considered, lags between relative humidity variables and dengue cases were the most frequently correlated. We found that most locations had significant correlations with cases in other locations at lags of zero weeks. These results can be used to improve predictive models of dengue transmission in the country.
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Affiliation(s)
- Michael A Robert
- Department of Mathematics and Center for Emerging, Zoonotic, and Arthropod-Borne Pathogens (CeZAP), Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.
| | - Helena Sofia Rodrigues
- Escola Superior de Ciências Empresariais, Instituto Politécnico de Viana do Castelo, Valença, Portugal
- Centro de Investigação e Desenvolvimento em Matemática e Aplicações, Universidade de Aveiro, Aveiro, Portugal
| | - Demian Herrera
- Centro de Investigación en Salud Dr. Hugo Mendoza, Hospital Pediátrico Dr. Hugo Mendoza, Santo Domingo, Dominican Republic
| | - Juan de Mata Donado Campos
- Departamento de Medicina Preventiva y Salud Pública y Microbiología, Facultad de Medicina, Universidad Autónoma de Madrid, Madrid, Spain
- Instituto de Investigación Sanitaria del Hospital Universitario La Paz (IdiPAZ), Universidad Autónoma de Madrid, Madrid, Spain
- Consorcio de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Calle Monforte de Lemos 3-5, 28029, Madrid, Spain
| | - Fernando Morilla
- Departamento de Informática y Automática, Escuela Técnica Superior de Ingeniería Informática, Universidad Nacional de Educación a Distancia, Madrid, Spain
| | - Javier Del Águila Mejía
- Departamento de Medicina Preventiva y Salud Pública y Microbiología, Facultad de Medicina, Universidad Autónoma de Madrid, Madrid, Spain
| | - María Elena Guardado
- Instituto Tecnológico de Santo Domingo (INTEC), Santo Domingo, Dominican Republic
| | - Ronald Skewes
- Dirección General de Epidemiología, Ministerio de Salud, Santo Domingo, Dominican Republic
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Zhao L, Zou Y, David RE, Withington S, McFarlane S, Faust RA, Norton J, Xagoraraki I. Simple methods for early warnings of COVID-19 surges: Lessons learned from 21 months of wastewater and clinical data collection in Detroit, Michigan, United States. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 864:161152. [PMID: 36572285 PMCID: PMC9783093 DOI: 10.1016/j.scitotenv.2022.161152] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/19/2022] [Accepted: 12/19/2022] [Indexed: 05/12/2023]
Abstract
Wastewater-based epidemiology (WBE) has drawn great attention since the Coronavirus disease 2019 (COVID-19) pandemic, not only due to its capability to circumvent the limitations of traditional clinical surveillance, but also due to its potential to forewarn fluctuations of disease incidences in communities. One critical application of WBE is to provide "early warnings" for upcoming fluctuations of disease incidences in communities which traditional clinical testing is incapable to achieve. While intricate models have been developed to determine early warnings based on wastewater surveillance data, there is an exigent need for straightforward, rapid, broadly applicable methods for health departments and partner agencies to implement. Our purpose in this study is to develop and evaluate such early-warning methods and clinical-case peak-detection methods based on WBE data to mount an informed public health response. Throughout an extended wastewater surveillance period across Detroit, MI metropolitan area (the entire study period is from September 2020 to May 2022) we designed eight early-warning methods (three real-time and five post-factum). Additionally, we designed three peak-detection methods based on clinical epidemiological data. We demonstrated the utility of these methods for providing early warnings for COVID-19 incidences, with their counterpart accuracies evaluated by hit rates. "Hit rates" were defined as the number of early warning dates (using wastewater surveillance data) that captured defined peaks (using clinical epidemiological data) divided by the total number of early warning dates. Hit rates demonstrated that the accuracy of both real-time and post-factum methods could reach 100 %. Furthermore, the results indicate that the accuracy was influenced by approaches to defining peaks of disease incidence. The proposed methods herein can assist health departments capitalizing on WBE data to assess trends and implement quick public health responses to future epidemics. Besides, this study elucidated critical factors affecting early warnings based on WBE amid the COVID-19 pandemic.
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Affiliation(s)
- Liang Zhao
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, USA
| | - Yangyang Zou
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, USA
| | - Randy E David
- Detroit Health Department, 100 Mack Ave, Detroit, MI 48201, USA
| | | | - Stacey McFarlane
- Macomb County Health Division, 43525 Elizabeth Rd, Mount Clemens, MI 48043, USA
| | - Russell A Faust
- Oakland County Health Division, 1200 Telegraph Rd, Pontiac, MI 48341, USA
| | - John Norton
- Great Lakes Water Authority, 735 Randolph, Detroit, MI 48226, USA
| | - Irene Xagoraraki
- Department of Civil and Environmental Engineering, Michigan State University, 1449 Engineering Research Ct, East Lansing, MI 48823, USA.
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Tozan Y, Odhiambo Sewe M, Kim S, Rocklöv J. A Methodological Framework for Economic Evaluation of Operational Response to Vector-Borne Diseases Based on Early Warning Systems. Am J Trop Med Hyg 2023; 108:627-633. [PMID: 36646075 PMCID: PMC9978551 DOI: 10.4269/ajtmh.22-0471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 10/18/2022] [Indexed: 01/18/2023] Open
Abstract
Despite significant advances in improving the predictive models for vector-borne diseases, only a few countries have integrated an early warning system (EWS) with predictive and response capabilities into their disease surveillance systems. The limited understanding of forecast performance and uncertainties by decision-makers is one of the primary factors that precludes its operationalization in preparedness and response planning. Further, predictive models exhibit a decrease in forecast skill with longer lead times, a trade-off between forecast accuracy and timeliness and effectiveness of action. This study presents a methodological framework to evaluate the economic value of EWS-triggered responses from the health system perspective. Assuming an operational EWS in place, the framework makes explicit the trade-offs between forecast accuracy, timeliness of action, effectiveness of response, and costs, and uses the net benefit analysis, which measures the benefits of taking action minus the associated costs. Uncertainty in disease forecasts and other parameters is accounted for through probabilistic sensitivity analysis. The output is the probability distribution of the net benefit estimates at given forecast lead times. A non-negative net benefit and the probability of yielding such are considered a general signal that the EWS-triggered response at a given lead time is economically viable. In summary, the proposed framework translates uncertainties associated with disease forecasts and other parameters into decision uncertainty by quantifying the economic risk associated with operational response to vector-borne disease events of potential importance predicted by an EWS. The goal is to facilitate a more informed and transparent public health decision-making under uncertainty.
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Affiliation(s)
- Yesim Tozan
- School of Global Public Health, New York University, New York, New York
| | - Maquines Odhiambo Sewe
- Department of Public Health and Clinical Medicine, Epidemiology and Global Health & Umeå Centre for Global Health Research, Umeå University, Umeå, Sweden
| | - Sooyoung Kim
- School of Global Public Health, New York University, New York, New York
| | - Joacim Rocklöv
- Department of Public Health and Clinical Medicine, Epidemiology and Global Health & Umeå Centre for Global Health Research, Umeå University, Umeå, Sweden
- Heidelberg Institute of Global Health, Interdisciplinary Centre for Scientific Computing, Heidelberg University, Heidelberg, Germany
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9
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Aryaprema VS, Steck MR, Peper ST, Xue RD, Qualls WA. A systematic review of published literature on mosquito control action thresholds across the world. PLoS Negl Trop Dis 2023; 17:e0011173. [PMID: 36867651 PMCID: PMC10016652 DOI: 10.1371/journal.pntd.0011173] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 03/15/2023] [Accepted: 02/14/2023] [Indexed: 03/04/2023] Open
Abstract
BACKGROUND Despite the use of numerous methods of control measures, mosquito populations and mosquito-borne diseases are still increasing globally. Evidence-based action thresholds to initiate or intensify control activities have been identified as essential in reducing mosquito populations to required levels at the correct/optimal time. This systematic review was conducted to identify different mosquito control action thresholds existing across the world and associated surveillance and implementation characteristics. METHODOLOGY/PRINCIPAL FINDINGS Searches for literature published from 2010 up to 2021 were performed using two search engines, Google Scholar and PubMed Central, according to PRISMA guidelines. A set of inclusion/exclusion criteria were identified and of the 1,485 initial selections, only 87 were included in the final review. Thirty inclusions reported originally generated thresholds. Thirteen inclusions were with statistical models that seemed intended to be continuously utilized to test the exceedance of thresholds in a specific region. There was another set of 44 inclusions that solely mentioned previously generated thresholds. The inclusions with "epidemiological thresholds" outnumbered those with "entomological thresholds". Most of the inclusions came from Asia and those thresholds were targeted toward Aedes and dengue control. Overall, mosquito counts (adult and larval) and climatic variables (temperature and rainfall) were the most used parameters in thresholds. The associated surveillance and implementation characteristics of the identified thresholds are discussed here. CONCLUSIONS/SIGNIFICANCE The review identified 87 publications with different mosquito control thresholds developed across the world and published during the last decade. Associated surveillance and implementation characteristics will help organize surveillance systems targeting the development and implementation of action thresholds, as well as direct awareness towards already existing thresholds for those with programs lacking available resources for comprehensive surveillance systems. The findings of the review highlight data gaps and areas of focus to fill in the action threshold compartment of the IVM toolbox.
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Affiliation(s)
- Vindhya S. Aryaprema
- Anastasia Mosquito Control District, St. Augustine, Florida, United States of America
| | - Madeline R. Steck
- Anastasia Mosquito Control District, St. Augustine, Florida, United States of America
| | - Steven T. Peper
- Anastasia Mosquito Control District, St. Augustine, Florida, United States of America
| | - Rui-de Xue
- Anastasia Mosquito Control District, St. Augustine, Florida, United States of America
| | - Whitney A. Qualls
- Anastasia Mosquito Control District, St. Augustine, Florida, United States of America
- * E-mail:
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Thommes E, Coudeville L, Muhammad R, Martin M, Nelson CB, Chit A. Public health impact and cost-effectiveness of implementing a 'pre-vaccination screening' strategy with the dengue vaccine in Puerto Rico. Vaccine 2022; 40:7343-7351. [PMID: 36347720 DOI: 10.1016/j.vaccine.2022.10.071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 10/24/2022] [Accepted: 10/25/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND The World Health Organization (WHO) recommended 'pre-vaccination screening' as its preferred implementation strategy when using the licensed dengue vaccine (CYD-TDV; Dengvaxia, Sanofi), so that only individuals with previous dengue infection are vaccinated. The US Centers for Disease Control and Prevention (CDC) recommended use of CYD-TDV to prevent dengue in children with previous laboratory-confirmed dengue infection in regions where dengue is endemic. Here, we evaluate the public health impact and cost-effectiveness of a 'pre-vaccination screening' strategy in Puerto Rico. METHODS The current analysis builds upon a previously published transmission model used to assess the benefits/risks associated with dengue vaccination. For 'pre-vaccination screening', three alternative testing methods were assessed: one using an immunoglobulin G (IgG) enzyme-linked immunosorbent assay (ELISA) dengue serotest, another with dengue serotesting using a rapid diagnostic test (RDT), and one using both sequentially (as recommended in Puerto Rico). The time horizon considered was 10 years. RESULTS In Puerto Rico, the disability-adjusted life years (DALYs) averted for 'pre-vaccination screening' with an ELISA-based program, RDT-based program, and both sequentially would be a median 1,192 (95% CI: 716-2,232), 2,812 (95% CI: 1,579-5,019), and 1,017 (95% CI: 561-1,738), respectively. These benefits would arise from the reduction in cases: median 24,961 (95% CI: 17,480-36,782), 58,273 (95% CI: 40,729-84,796), 20,775 (95% CI: 14,637-30,374) fewer cases, respectively. The cost per DALY averted from a payer perspective would be US$12,518 (95 %CI: US$4,749-26,922), US$10,047 (95% CI: US$3,350-23,852), and US$12,334 (95% CI: US$4,965-26,444), respectively. All three strategies would be cost saving from a societal perspective. CONCLUSIONS Our study supports the WHO and CDC 'pre-vaccination screening' guidance for CYD-TDV implementation. In Puerto Rico, regardless of the testing strategy and even with a relatively low rate of testing, it would be cost-effective from a payer perspective and cost saving from a societal perspective.
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Affiliation(s)
- Edward Thommes
- Sanofi, 1755 Steeles Avenue W, Toronto, Ontario M2R 3T4, Canada; University of Guelph, 50 Stone Road E, Guelph, Ontario N1G 2W1, Canada; York University, 4700 Keele St, Toronto, Ontario M3J 1P3, Canada.
| | | | | | - Maria Martin
- Sanofi, 1 Discovery Drive, Swiftwater, PA 18370, USA.
| | | | - Ayman Chit
- Sanofi, 1 Discovery Drive, Swiftwater, PA 18370, USA; Leslie Dan Faculty of Pharmacy, University of Toronto, Ontario, Canada.
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Labadin J, Hong BH, Tiong WK, Gill BS, Perera D, Rigit ARH, Singh S, Tan CV, Ghazali SM, Jelip J, Mokhtar N, Rashid NBA, Bakar HBA, Lim JH, Taib NM, George A. Development and user testing study of MozzHub: a bipartite network-based dengue hotspot detector. MULTIMEDIA TOOLS AND APPLICATIONS 2022; 82:17415-17436. [PMID: 36404933 PMCID: PMC9649007 DOI: 10.1007/s11042-022-14120-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 10/14/2022] [Accepted: 10/25/2022] [Indexed: 06/16/2023]
Abstract
Traditionally, dengue is controlled by fogging, and the prime location for the control measure is at the patient's residence. However, when Malaysia was hit by the first wave of the Coronavirus disease (COVID-19), and the government-imposed movement control order, dengue cases have decreased by more than 30% from the previous year. This implies that residential areas may not be the prime locations for dengue-infected mosquitoes. The existing early warning system was focused on temporal prediction wherein the lack of consideration for spatial component at the microlevel and human mobility were not considered. Thus, we developed MozzHub, which is a web-based application system based on the bipartite network-based dengue model that is focused on identifying the source of dengue infection at a small spatial level (400 m) by integrating human mobility and environmental predictors. The model was earlier developed and validated; therefore, this study presents the design and implementation of the MozzHub system and the results of a preliminary pilot test and user acceptance of MozzHub in six district health offices in Malaysia. It was found that the MozzHub system is well received by the sample of end-users as it was demonstrated as a useful (77.4%), easy-to-operate system (80.6%), and has achieved adequate client satisfaction for its use (74.2%).
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Affiliation(s)
- Jane Labadin
- Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Malaysia
| | - Boon Hao Hong
- Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Malaysia
| | - Wei King Tiong
- Faculty of Computer Science and Information Technology, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Malaysia
| | | | - David Perera
- Institute for Health and Community Medicine, Universiti Malaysia Sarawak, 94300 Kota Samarahan, Malaysia
| | | | - Sarbhan Singh
- Institute for Medical Research, Ministry of Health, Kuala Lumpur, Malaysia
| | - Cia Vei Tan
- Institute for Medical Research, Ministry of Health, Kuala Lumpur, Malaysia
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12
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Liyanage P, Tozan Y, Tissera HA, Overgaard HJ, Rocklöv J. Assessing the associations between Aedes larval indices and dengue risk in Kalutara district, Sri Lanka: a hierarchical time series analysis from 2010 to 2019. Parasit Vectors 2022; 15:277. [PMID: 35922821 PMCID: PMC9351248 DOI: 10.1186/s13071-022-05377-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 06/26/2022] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Dengue is a major public health problem in Sri Lanka. Aedes vector surveillance and monitoring of larval indices are routine, long-established public health practices in the country. However, the association between Aedes larval indices and dengue incidence is poorly understood. It is crucial to evaluate lagged effects and threshold values of Aedes larval indices to set pragmatic targets for sustainable vector control interventions. METHODS Monthly Aedes larval indices and dengue cases in all 10 Medical Officer of Health (MOH) divisions in Kalutara district were obtained from 2010 to 2019. Using a novel statistical approach, a distributed lag non-linear model and a two-staged hierarchical meta-analysis, we estimated the overall non-linear and delayed effects of the Premise Index (PI), Breteau Index (BI) and Container Index (CI) on dengue incidence in Kalutara district. A set of MOH division-specific variables were evaluated within the same meta-analytical framework to determine their moderator effects on dengue risk. Using generalized additive models, we assessed the utility of Aedes larval indices in predicting dengue incidence. RESULTS We found that all three larval indices were associated with dengue risk at a lag of 1 to 2 months. The relationship between PI and dengue was homogeneous across MOH divisions, whereas that with BI and CI was heterogeneous. The threshold values of BI, PI and CI associated with dengue risk were 2, 15 and 45, respectively. All three indices showed a low to moderate accuracy in predicting dengue risk in Kalutara district. CONCLUSIONS This study showed the potential of vector surveillance information in Kalutara district in developing a threshold-based, location-specific early warning system with a lead time of 2 months. The estimated thresholds are nonetheless time-bound and may not be universally applicable. Whenever longitudinal vector surveillance data areavailable, the methodological framework we propose here can be used to estimate location-specific Aedes larval index thresholds in any other dengue-endemic setting.
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Affiliation(s)
- Prasad Liyanage
- grid.12650.300000 0001 1034 3451Department of Epidemiology and Global Health, Umeå University, Umeå, Sweden ,grid.466905.8Ministry of Health, Colombo, Sri Lanka
| | - Yesim Tozan
- grid.137628.90000 0004 1936 8753School of Global Public Health, New York University, New York, NY 10003 USA
| | | | - Hans J. Overgaard
- grid.19477.3c0000 0004 0607 975XFaculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway ,grid.9786.00000 0004 0470 0856Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
| | - Joacim Rocklöv
- grid.12650.300000 0001 1034 3451Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, SE-901 87 Umeå, Sweden ,grid.7700.00000 0001 2190 4373Heidelberg Institute of Global Health & the Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany
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Badolo A, Sombié A, Yaméogo F, Wangrawa DW, Sanon A, Pignatelli PM, Sanon A, Viana M, Kanuka H, Weetman D, McCall PJ. First comprehensive analysis of Aedes aegypti bionomics during an arbovirus outbreak in west Africa: Dengue in Ouagadougou, Burkina Faso, 2016–2017. PLoS Negl Trop Dis 2022; 16:e0010059. [PMID: 35793379 PMCID: PMC9321428 DOI: 10.1371/journal.pntd.0010059] [Citation(s) in RCA: 6] [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: 12/08/2021] [Revised: 07/26/2022] [Accepted: 06/16/2022] [Indexed: 11/19/2022] Open
Abstract
Background
Dengue’s emergence in West Africa was typified by the Burkina Faso outbreaks in 2016 and 2017, the nation’s largest to date. In both years, we undertook three-month surveys of Aedes populations in or near the capital city Ouagadougou, where the outbreaks were centered.
Methodology
In 1200LG (urban), Tabtenga (peri-urban) and Goundry (rural) localities, we collected indoor and outdoor resting mosquito adults, characterized larval habitats and containers producing pupae and reared immature stages to adulthood in the laboratory for identification. All mosquito adults were identified morphologically. Host species (from which bloodmeals were taken) were identified by PCR. Generalized mixed models were used to investigate relationships between adult or larval densities and multiple explanatory variables.
Results
From samples in 1,780 houses, adult Ae. aegypti were significantly more abundant in the two urban localities (Tabtenga and 1200 LG) in both years than in the rural site (Goundry), where Anopheles spp. were far more common. Results from adult collections indicated a highly exophilic and anthropophilic (>90% bloodmeals of human origin) vector population, but with a relatively high proportion of bloodfed females caught inside houses. Habitats producing most pupae were waste tires (37% of total pupae), animal troughs (44%) and large water barrels (30%).
While Stegomyia indices were not reliable indicators of adult mosquito abundance, shared influences on adult and immature stage densities included rainfall and container water level, collection month and container type/purpose. Spatial analysis showed autocorrelation of densities, with a partial overlap in adult and immature stage hotspots.
Conclusion
Results provide an evidence base for the selection of appropriate vector control methods to minimize the risk, frequency and magnitude of future outbreaks in Ouagadougou. An integrated strategy combining community-driven practices, waste disposal and insecticide-based interventions is proposed. The prospects for developing a regional approach to arbovirus control in West Africa or across Africa are discussed.
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Affiliation(s)
- Athanase Badolo
- Laboratoire d’Entomologie Fondamentale et Appliquée, Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso
- * E-mail: (AB); (PJM)
| | - Aboubacar Sombié
- Laboratoire d’Entomologie Fondamentale et Appliquée, Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso
| | - Félix Yaméogo
- Laboratoire d’Entomologie Fondamentale et Appliquée, Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso
| | - Dimitri W. Wangrawa
- Laboratoire d’Entomologie Fondamentale et Appliquée, Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso
- Université Norbert Zongo, Koudougou, Burkina Faso
| | - Aboubakar Sanon
- Laboratoire d’Entomologie Fondamentale et Appliquée, Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso
| | - Patricia M. Pignatelli
- Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Antoine Sanon
- Laboratoire d’Entomologie Fondamentale et Appliquée, Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso
| | - Mafalda Viana
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, United Kingdom
| | - Hirotaka Kanuka
- Department of Tropical Medicine, The Jikei University School of Medicine, Tokyo, Japan
- Center for Medical Entomology, The Jikei University School of Medicine, Tokyo, Japan
| | - David Weetman
- Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Philip J. McCall
- Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- * E-mail: (AB); (PJM)
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14
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Liyanage P, Tozan Y, Overgaard HJ, Aravinda Tissera H, Rocklöv J. Effect of El Niño-Southern Oscillation and local weather on Aedes dvector activity from 2010 to 2018 in Kalutara district, Sri Lanka: a two-stage hierarchical analysis. Lancet Planet Health 2022; 6:e577-e585. [PMID: 35809587 DOI: 10.1016/s2542-5196(22)00143-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 05/16/2022] [Accepted: 05/17/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Dengue, transmitted by Aedes mosquitoes, is a major public health problem in Sri Lanka. Weather affects the abundance, feeding patterns, and longevity of Aedes vectors and hence the risk of dengue transmission. We aimed to quantify the effect of weather variability on dengue vector indices in ten Medical Officer of Health (MOH) divisions in Kalutara, Sri Lanka. METHODS Monthly weather variables (rainfall, temperature, and Oceanic Niño Index [ONI]) and Aedes larval indices in each division in Kalutara were obtained from 2010 to 2018. Using a distributed lag non-linear model and a two-stage hierarchical analysis, we estimated and compared division-level and overall relationships between weather and premise index, Breteau index, and container index. FINDINGS From Jan 1, 2010, to Dec 31, 2018, three El Niño events (2010, 2015-16, and 2018) occurred. Increasing monthly cumulative rainfall higher than 200 mm at a lag of 0 months, mean temperatures higher than 31·5°C at a lag of 1-2 months, and El Niño conditions (ie, ONI >0·5) at a lag of 6 months were associated with an increased relative risk of premise index and Breteau index. Container index was found to be less sensitive to temperature and ONI, and rainfall. The associations of rainfall and temperature were rather homogeneous across divisions. INTERPRETATION Both temperature and ONI have the potential to serve as predictors of vector activity at a lead time of 1-6 months, while the amount of rainfall could indicate the magnitude of vector prevalence in the same month. This information, along with knowledge of the distribution of breeding sites, is useful for spatial risk prediction and implementation of effective Aedes control interventions. FUNDING None.
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Affiliation(s)
- Prasad Liyanage
- Department of Epidemiology and Global Health, Umeå University, Umeå, Sweden; Ministry of Health, Colombo, Sri Lanka.
| | - Yesim Tozan
- School of Global Public Health, New York University, New York, NY, USA
| | - Hans J Overgaard
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway; Department of Microbiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
| | | | - Joacim Rocklöv
- Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden; Heidelberg Institute of Global Health and Interdisciplinary Centre for Scientific Computing, Heidelberg University, Heidelberg, Germany
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de Lima CL, da Silva ACG, Moreno GMM, Cordeiro da Silva C, Musah A, Aldosery A, Dutra L, Ambrizzi T, Borges IVG, Tunali M, Basibuyuk S, Yenigün O, Massoni TL, Browning E, Jones K, Campos L, Kostkova P, da Silva Filho AG, dos Santos WP. Temporal and Spatiotemporal Arboviruses Forecasting by Machine Learning: A Systematic Review. Front Public Health 2022; 10:900077. [PMID: 35719644 PMCID: PMC9204152 DOI: 10.3389/fpubh.2022.900077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 05/03/2022] [Indexed: 11/13/2022] Open
Abstract
Arboviruses are a group of diseases that are transmitted by an arthropod vector. Since they are part of the Neglected Tropical Diseases that pose several public health challenges for countries around the world. The arboviruses' dynamics are governed by a combination of climatic, environmental, and human mobility factors. Arboviruses prediction models can be a support tool for decision-making by public health agents. In this study, we propose a systematic literature review to identify arboviruses prediction models, as well as models for their transmitter vector dynamics. To carry out this review, we searched reputable scientific bases such as IEE Xplore, PubMed, Science Direct, Springer Link, and Scopus. We search for studies published between the years 2015 and 2020, using a search string. A total of 429 articles were returned, however, after filtering by exclusion and inclusion criteria, 139 were included. Through this systematic review, it was possible to identify the challenges present in the construction of arboviruses prediction models, as well as the existing gap in the construction of spatiotemporal models.
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Affiliation(s)
- Clarisse Lins de Lima
- Nucleus for Computer Engineering, Polytechnique School of the University of Pernambuco, Poli-UPE, Recife, Brazil
| | - Ana Clara Gomes da Silva
- Nucleus for Computer Engineering, Polytechnique School of the University of Pernambuco, Poli-UPE, Recife, Brazil
| | | | | | - Anwar Musah
- Centre for Digital Public Health and Emergencies, Institute for Risk and Disaster Reduction, University College London, London, United Kingdom
| | - Aisha Aldosery
- Centre for Digital Public Health and Emergencies, Institute for Risk and Disaster Reduction, University College London, London, United Kingdom
| | - Livia Dutra
- Department of Atmospheric Sciences, IAG-USP, University of São Paulo, São Paulo, Brazil
| | - Tercio Ambrizzi
- Department of Atmospheric Sciences, IAG-USP, University of São Paulo, São Paulo, Brazil
| | - Iuri V. G. Borges
- Department of Atmospheric Sciences, IAG-USP, University of São Paulo, São Paulo, Brazil
| | - Merve Tunali
- Boǧaziçi University, Institute of Environmental Sciences, Istanbul, Turkey
| | - Selma Basibuyuk
- Boǧaziçi University, Institute of Environmental Sciences, Istanbul, Turkey
| | - Orhan Yenigün
- Boǧaziçi University, Institute of Environmental Sciences, Istanbul, Turkey
| | - Tiago Lima Massoni
- Department of Systems and Computing, Federal University of Campina Grande, Campina Grande, Brazil
| | - Ella Browning
- Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Kate Jones
- Centre for Biodiversity and Environment Research, Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Luiza Campos
- Department of Civil Environmental and Geomatic Engineering, University College London, London, United Kingdom
| | - Patty Kostkova
- Centre for Digital Public Health and Emergencies, Institute for Risk and Disaster Reduction, University College London, London, United Kingdom
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Baharom M, Ahmad N, Hod R, Abdul Manaf MR. Dengue Early Warning System as Outbreak Prediction Tool: A Systematic Review. Healthc Policy 2022; 15:871-886. [PMID: 35535237 PMCID: PMC9078425 DOI: 10.2147/rmhp.s361106] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 04/16/2022] [Indexed: 12/01/2022] Open
Abstract
Early warning system (EWS) for vector-borne diseases is incredibly complex due to numerous factors originating from human, environmental, vector and the disease itself. Dengue EWS aims to collect data that leads to prompt decision-making processes that trigger disease intervention strategies to minimize the impact on a specific population. Dengue EWS may have a similar structural design, functions, and analytical approaches but different performance and ability to predict outbreaks. Hence, this review aims to summarise and discuss the evidence of different EWSs, their performance, and their ability to predict dengue outbreaks. A systematic literature search was performed of four primary databases: Scopus, Web of Science, Ovid MEDLINE, and EBSCOhost. Eligible articles were evaluated using a checklist for assessing the quality of the studies. A total of 17 studies were included in this systematic review. All EWS models demonstrated reasonably good predictive abilities to predict dengue outbreaks. However, the accuracy of their predictions varied greatly depending on the model used and the data quality. The reported sensitivity ranged from 50 to 100%, while specificity was 74 to 94.7%. A range between 70 to 96.3% was reported for prediction model accuracy and 43 to 86% for PPV. Overall, meteorological alarm indicators (temperatures and rainfall) were the most frequently used and displayed the best performing indicator. Other potential alarm indicators are entomology (female mosquito infection rate), epidemiology, population and socioeconomic factors. EWS is an essential tool to support district health managers and national health planners to mitigate or prevent disease outbreaks. This systematic review highlights the benefits of integrating several epidemiological tools focusing on incorporating climatic, environmental, epidemiological and socioeconomic factors to create an early warning system. The early warning system relies heavily on the country surveillance system. The lack of timely and high-quality data is critical for developing an effective EWS.
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Affiliation(s)
- Mazni Baharom
- Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, 56000, Malaysia
| | - Norfazilah Ahmad
- Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, 56000, Malaysia
- Correspondence: Norfazilah Ahmad, Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, 56000, Malaysia, Tel +60391458781, Fax +60391456670, Email
| | - Rozita Hod
- Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, 56000, Malaysia
| | - Mohd Rizal Abdul Manaf
- Department of Community Health, Faculty of Medicine, Universiti Kebangsaan Malaysia, Bandar Tun Razak, Kuala Lumpur, 56000, Malaysia
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Cardenas R, Hussain-Alkhateeb L, Benitez-Valladares D, Sánchez-Tejeda G, Kroeger A. The Early Warning and Response System (EWARS-TDR) for dengue outbreaks: can it also be applied to chikungunya and Zika outbreak warning? BMC Infect Dis 2022; 22:235. [PMID: 35255839 PMCID: PMC8902764 DOI: 10.1186/s12879-022-07197-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 02/23/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND In the Americas, endemic countries for Aedes-borne diseases such as dengue, chikungunya, and Zika face great challenges particularly since the recent outbreaks of CHIKV and ZIKV, all transmitted by the same insect vectors Aedes aegypti and Ae. albopictus. The Special Program for Research and Training in Tropical Diseases (TDR-WHO) has developed together with partners an Early Warning and Response System (EWARS) for dengue outbreaks based on a variety of alarm signals with a high sensitivity and positive predictive value (PPV). The question is if this tool can also be used for the prediction of Zika and chikungunya outbreaks. METHODOLOGY We conducted in nine districts of Mexico and one large city in Colombia a retrospective analysis of epidemiological data (for the outbreak definition) and of climate and entomological data (as potential alarm indicators) produced by the national surveillance systems for dengue, chikungunya and Zika outbreak prediction covering the following outbreak years: for dengue 2012-2016, for Zika 2015-2017, for chikungunya 2014-2016. This period was divided into a "run in period" (to establish the "historical" pattern of the disease) and an "analysis period" (to identify sensitivity and PPV of outbreak prediction). RESULTS In Mexico, the sensitivity of alarm signals for correctly predicting an outbreak was 100% for dengue, and 97% for Zika (chikungunya data could not be obtained in Mexico); the PPV was 83% for dengue and 100% for Zika. The time period between alarm and start of the outbreak (i.e. the time available for early response activities) was for Zika 4-5 weeks. In Colombia the sensitivity of the outbreak prediction was 92% for dengue, 93% for chikungunya and 100% for Zika; the PPV was 68% for dengue, 92% for chikungunya and 54% for Zika; the prediction distance was for dengue 3-5 weeks, for chikungunya 10-13 weeks and for Zika 6-10 weeks. CONCLUSION EWARS demonstrated promising capability of timely disease outbreak prediction with an operational design likely to improve the coordination among stakeholders. However, the prediction validity varied substantially across different types of diseases and appeared less optimal in low endemic settings.
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Affiliation(s)
- Rocio Cardenas
- Instituto Departamental de Salud de Norte de Santander-IDS, Norte de Santander, Colombia. .,Centre for Medicine and Society, Master Programme Global Urban Health, Albert-Ludwigs-University Freiburg, Freiburg, Germany.
| | - Laith Hussain-Alkhateeb
- School of Public Health and Community Medicine, Sahlgrenska Academy, Institute of Medicine, Global Health, University of Gothenburg, Gothenburg, Sweden
| | - David Benitez-Valladares
- Programa de Enfermedades Transmitidas por Vector, Centro Nacional de Programas Preventivos y Control de Enfermedades, CENAPRECE, Secretaría de Salud de México, Ciudad de México, México
| | - Gustavo Sánchez-Tejeda
- Programa de Enfermedades Transmitidas por Vector, Centro Nacional de Programas Preventivos y Control de Enfermedades, CENAPRECE, Secretaría de Salud de México, Ciudad de México, México
| | - Axel Kroeger
- Special Programme for Research and Training in Tropical Diseases (TDR) at the World Health Organization in Geneva, Geneva, Switzerland.,Centre for Medicine and Society, Master Programme Global Urban Health, Albert-Ludwigs-University Freiburg, Freiburg, Germany
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Aryaprema VS, Steck MR, Peper ST, Farooq M, Xue RD, Qualls WA. Initial Survey of Mosquito Control Programs with Set Action Thresholds and Associated Surveillance Characteristics. JOURNAL OF THE AMERICAN MOSQUITO CONTROL ASSOCIATION 2022; 38:29-39. [PMID: 35276732 DOI: 10.2987/21-7050] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The establishment of action thresholds is becoming critical in mosquito control management to implement effective proactive control measures using limited available resources. As a part of a large-scale study to identify different mosquito control action thresholds used in different geographical regions, we conducted an initial survey to identify mosquito control programs that claim to have set action thresholds and to investigate their associated program characteristics. We identified 68% (USA), 60% (mainland Australia), 78% (Asia), 35% (Africa), and 50% (US military units) of the responding programs, which perform mosquito control, have set mosquito control action thresholds. More than 50% of the programs that have not set mosquito control action thresholds already collect basic surveillance information as do the programs with thresholds. Further investigations with the selected mosquito control programs from this initial survey will help develop guidelines on establishing action thresholds by identifying different types of actual action thresholds used by programs in different geographical settings and other related information.
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Affiliation(s)
| | - Madeline R Steck
- Anastasia Mosquito Control District, 120 EOC Drive, St. Augustine, FL 32092
| | - Steven T Peper
- Anastasia Mosquito Control District, 120 EOC Drive, St. Augustine, FL 32092
| | - Muhammad Farooq
- Anastasia Mosquito Control District, 120 EOC Drive, St. Augustine, FL 32092
| | - Rui-De Xue
- Anastasia Mosquito Control District, 120 EOC Drive, St. Augustine, FL 32092
| | - Whitney A Qualls
- Anastasia Mosquito Control District, 120 EOC Drive, St. Augustine, FL 32092
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Kingston R, Routledge I, Bhatt S, Bowman LR. Novel Epidemic Metrics to Communicate Outbreak Risk at the Municipality Level: Dengue and Zika in the Dominican Republic. Viruses 2022; 14:v14010162. [PMID: 35062366 PMCID: PMC8781936 DOI: 10.3390/v14010162] [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: 12/06/2021] [Revised: 01/11/2022] [Accepted: 01/12/2022] [Indexed: 12/28/2022] Open
Abstract
Arboviruses remain a significant cause of morbidity, mortality and economic cost across the global human population. Epidemics of arboviral disease, such as Zika and dengue, also cause significant disruption to health services at local and national levels. This study examined 2014-2016 Zika and dengue epidemic data at the sub-national level to characterise transmission across the Dominican Republic. For each municipality, spatio-temporal mapping was used to characterise disease burden, while data were age and sex standardised to quantify burden distributions among the population. In separate analyses, time-ordered data were combined with the underlying disease migration interval distribution to produce a network of likely transmission chain events, displayed using transmission chain likelihood matrices. Finally, municipal-specific reproduction numbers (Rm) were established using a Wallinga-Teunis matrix. Dengue and Zika epidemics peaked during weeks 39-52 of 2015 and weeks 14-27 of 2016, respectively. At the provincial level, dengue attack rates were high in Hermanas Mirabal and San José de Ocoa (58.1 and 49.2 cases per 10,000 population, respectively), compared with the Zika burden, which was highest in Independencia and San José de Ocoa (21.2 and 13.4 cases per 10,000 population, respectively). Across municipalities, high disease burden was observed in Cotuí (622 dengue cases per 10,000 population) and Jimani (32 Zika cases per 10,000 population). Municipal infector-infectee transmission likelihood matrices identified seven 0% likelihood transmission events throughout the dengue epidemic and two 0% likelihood transmission events during the Zika epidemic. Municipality reproduction numbers (Rm) were consistently higher, and persisted for a greater duration, during the Zika epidemic (Rm = 1.0) than during the dengue epidemic (Rm < 1.0). This research highlights the importance of disease surveillance in land border municipalities as an early warning for infectious disease transmission. It also demonstrates that a high number of importation events are required to sustain transmission in endemic settings, and vice versa for newly emerged diseases. The inception of a novel epidemiological metric, Rm, reports transmission risk using standardised spatial units, and can be used to identify high transmission risk municipalities to better focus public health interventions for dengue, Zika and other infectious diseases.
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Benitez-Valladares D, Kroeger A, Tejeda GS, Hussain-Alkhateeb L. Validation of the Early Warning and Response System (EWARS) for dengue outbreaks: Evidence from the national vector control program in Mexico. PLoS Negl Trop Dis 2021; 15:e0009261. [PMID: 34914703 PMCID: PMC8717980 DOI: 10.1371/journal.pntd.0009261] [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: 02/18/2021] [Revised: 12/30/2021] [Accepted: 11/14/2021] [Indexed: 11/19/2022] Open
Abstract
Background During 2017, twenty health districts (locations) implemented a dengue outbreak Early Warning and Response System (EWARS) in Mexico, which processes epidemiological, meteorological and entomological alarm indicators to predict dengue outbreaks and triggers early response activities. Out of the 20 priority districts where more than one fifth of all national disease transmission in Mexico occur, eleven districts were purposely selected and analyzed. Nine districts presented outbreak alarms by EWARS but without subsequent outbreaks (“non-outbreak districts”) and two presented alarms with subsequent dengue outbreaks (“outbreak districts”). This evaluation study assesses and compares the impact of alarm-informed response activities and the consequences of failing a timely and adequate response across the outbreak groups. Methods Five indicators of dengue outbreak response (larval control, entomological studies with water container interventions, focal spraying and indoor residual spraying) were quantitatively analyzed across two groups (”outbreak districts” and “non-outbreak districts”). However, for quality control purposes, only qualitative concluding remarks were derived from the fifth response indicator (fogging). Results The average coverage of vector control responses was significantly higher in non-outbreak districts and across all four indicators. In the “outbreak districts” the response activities started late and were of much lower intensity compared to “non-outbreak districts”. Vector control teams at districts-level demonstrated diverse levels of compliance with local guidelines for ‘initial’, ‘early’ and ‘late’ responses to outbreak alarms, which could potentially explain the different outcomes observed following the outbreak alarms. Conclusion Failing timely and adequate response of alarm signals generated by EWARS showed to negatively impact the disease outbreak control process. On the other hand, districts with adequate and timely response guided by alarm signals demonstrated successful records of outbreak prevention. This study presents important operational scenarios when failing or successding EWARS but warrants investigating the effectiveness and cost-effectiveness of EWARS using a more robust designs. While the Early Warning and Response System (EWARS) for dengue and other vector-borne diseases has significantly advanced in methodologies and applications in more recent time, evidence from the field on the implications of EWARS in the context of vector control and response is still rare. Assessing the effectiveness (and cost) of EWARS in reducing or mitigating disease outbreaks entails complex study designs, including randomized controlled trials. This study employs a pragmatic validation design; comparing groups of outbreak and non-outbreak districts from the Mexican national vector control and response program for dengue, all districts with implemented EWARS and generated alerts. The study authors have illustrated and discussed important operational implications when failing or succeeding timely and adequate response to EWARS alerts, revealing that responding to EWARS alerts in time and space, during or beyond the routine vector control and response process can significantly reduce unnecessary outbreaks and hospitalizations.
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Affiliation(s)
- David Benitez-Valladares
- Programa de Enfermedades Transmitidas por Vector, Centro Nacional de Programas Preventivos y Control de Enfermedades, CENAPRECE, Secretaría de Salud de México, Ciudad de México, México
| | - Axel Kroeger
- Special Programme for Research and Training in Tropical Diseases (TDR) at the World Health Organization in Geneva, Geneva, Switzerland
- Albert-Ludwigs-University Freiburg, Master Programme Global Urban Health, Freiburg, Germany
| | - Gustavo Sánchez Tejeda
- Programa de Enfermedades Transmitidas por Vector, Centro Nacional de Programas Preventivos y Control de Enfermedades, CENAPRECE, Secretaría de Salud de México, Ciudad de México, México
| | - Laith Hussain-Alkhateeb
- Global Health, School of Public Health and Community Medicine, Sahlgrenska Academy, University of Gothenburg, Sweden
- * E-mail:
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Integrating Spatial Modelling and Space-Time Pattern Mining Analytics for Vector Disease-Related Health Perspectives: A Case of Dengue Fever in Pakistan. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182212018. [PMID: 34831785 PMCID: PMC8618682 DOI: 10.3390/ijerph182212018] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 10/31/2021] [Accepted: 11/10/2021] [Indexed: 11/17/2022]
Abstract
The spatial–temporal assessment of vector diseases is imperative to design effective action plans and establish preventive strategies. Therefore, such assessments have potential public health planning-related implications. In this context, we here propose an integrated spatial disease evaluation (I-SpaDE) framework. The I-SpaDE integrates various techniques such as the Kernel Density Estimation, the Optimized Hot Spot Analysis, space–time assessment and prediction, and the Geographically Weighted Regression (GWR). It makes it possible to systematically assess the disease concentrations, patterns/trends, clustering, prediction dynamics, and spatially varying relationships between disease and different associated factors. To demonstrate the applicability and effectiveness of the I-SpaDE, we apply it in the second largest city of Pakistan, namely Lahore, using Dengue Fever (DF) during 2007–2016 as an example vector disease. The most significant clustering is evident during the years 2007–2008, 2010–2011, 2013, and 2016. Mostly, the clusters are found within the city’s central functional area. The prediction analysis shows an inclination of DF distribution from less to more urbanized areas. The results from the GWR show that among various socio-ecological factors, the temperature is the most significantly associated with the DF followed by vegetation and built-up area. While the results are important to understand the DF situation in the study area and have useful implications for public health planning, the proposed framework is flexible, replicable, and robust to be utilized in other similar regions, particularly in developing countries in the tropics and sub-tropics.
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Hussain-Alkhateeb L, Rivera Ramírez T, Kroeger A, Gozzer E, Runge-Ranzinger S. Early warning systems (EWSs) for chikungunya, dengue, malaria, yellow fever, and Zika outbreaks: What is the evidence? A scoping review. PLoS Negl Trop Dis 2021; 15:e0009686. [PMID: 34529649 PMCID: PMC8445439 DOI: 10.1371/journal.pntd.0009686] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Early warning systems (EWSs) are of increasing importance in the context of outbreak-prone diseases such as chikungunya, dengue, malaria, yellow fever, and Zika. A scoping review has been undertaken for all 5 diseases to summarize existing evidence of EWS tools in terms of their structural and statistical designs, feasibility of integration and implementation into national surveillance programs, and the users' perspective of their applications. METHODS Data were extracted from Cochrane Database of Systematic Reviews (CDSR), Google Scholar, Latin American and Caribbean Health Sciences Literature (LILACS), PubMed, Web of Science, and WHO Library Database (WHOLIS) databases until August 2019. Included were studies reporting on (a) experiences with existing EWS, including implemented tools; and (b) the development or implementation of EWS in a particular setting. No restrictions were applied regarding year of publication, language or geographical area. FINDINGS Through the first screening, 11,710 documents for dengue, 2,757 for Zika, 2,706 for chikungunya, 24,611 for malaria, and 4,963 for yellow fever were identified. After applying the selection criteria, a total of 37 studies were included in this review. Key findings were the following: (1) a large number of studies showed the quality performance of their prediction models but except for dengue outbreaks, only few presented statistical prediction validity of EWS; (2) while entomological, epidemiological, and social media alarm indicators are potentially useful for outbreak warning, almost all studies focus primarily or exclusively on meteorological indicators, which tends to limit the prediction capacity; (3) no assessment of the integration of the EWS into a routine surveillance system could be found, and only few studies addressed the users' perspective of the tool; (4) almost all EWS tools require highly skilled users with advanced statistics; and (5) spatial prediction remains a limitation with no tool currently able to map high transmission areas at small spatial level. CONCLUSIONS In view of the escalating infectious diseases as global threats, gaps and challenges are significantly present within the EWS applications. While some advanced EWS showed high prediction abilities, the scarcity of tool assessments in terms of integration into existing national surveillance systems as well as of the feasibility of transforming model outputs into local vector control or action plans tends to limit in most cases the support of countries in controlling disease outbreaks.
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Affiliation(s)
- Laith Hussain-Alkhateeb
- Global Health, School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | | | - Axel Kroeger
- Centre for Medicine and Society, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany
| | | | - Silvia Runge-Ranzinger
- Centre for Medicine and Society, Albert-Ludwigs-Universität Freiburg, Freiburg, Germany
- Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany
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Su Yin M, Bicout DJ, Haddawy P, Schöning J, Laosiritaworn Y, Sa-angchai P. Added-value of mosquito vector breeding sites from street view images in the risk mapping of dengue incidence in Thailand. PLoS Negl Trop Dis 2021; 15:e0009122. [PMID: 33684130 PMCID: PMC7971869 DOI: 10.1371/journal.pntd.0009122] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 03/18/2021] [Accepted: 01/11/2021] [Indexed: 11/19/2022] Open
Abstract
Dengue is an emerging vector-borne viral disease across the world. The primary dengue mosquito vectors breed in containers with sufficient water and nutrition. Outdoor containers can be detected from geotagged images using state-of-the-art deep learning methods. In this study, we utilize such container information from street view images in developing a risk mapping model and determine the added value of including container information in predicting dengue risk. We developed seasonal-spatial models in which the target variable dengue incidence was explained using weather and container variable predictors. Linear mixed models with fixed and random effects are employed in our models to account for different characteristics of containers and weather variables. Using data from three provinces of Thailand between 2015 and 2018, the models are developed at the sub-district level resolution to facilitate the development of effective targeted intervention strategies. The performance of the models is evaluated with two baseline models: a classic linear model and a linear mixed model without container information. The performance evaluated with the correlation coefficients, R-squared, and AIC shows the proposed model with the container information outperforms both baseline models in all three provinces. Through sensitivity analysis, we investigate the containers that have a high impact on dengue risk. Our findings indicate that outdoor containers identified from street view images can be a useful data source in building effective dengue risk models and that the resulting models have potential in helping to target container elimination interventions.
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Affiliation(s)
- Myat Su Yin
- Faculty of ICT, Mahidol University, Nakhon Pathom, Thailand
| | - Dominique J. Bicout
- Biomathematics and Epidemiology, EPSP-TIMC, UMR CNRS 5525, Grenoble-Alpes University, VetAgro Sup, Grenoble, France
- Laue–Langevin Institute, Theory group, Grenoble, France
| | - Peter Haddawy
- Faculty of ICT, Mahidol University, Nakhon Pathom, Thailand
- Bremen Spatial Cognition Center, University of Bremen, Bremen, Germany
| | - Johannes Schöning
- Bremen Spatial Cognition Center, University of Bremen, Bremen, Germany
| | - Yongjua Laosiritaworn
- Information Technology Center, Department of Disease Control, Ministry of Public Health, Bangkok, Thailand
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Liebig J, de Hoog F, Paini D, Jurdak R. Forecasting the probability of local dengue outbreaks in Queensland, Australia. Epidemics 2020; 34:100422. [PMID: 33340847 DOI: 10.1016/j.epidem.2020.100422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 10/25/2020] [Accepted: 11/18/2020] [Indexed: 10/22/2022] Open
Abstract
The global incidence of dengue is increasing, and many previously unaffected areas have reported local cases of the vector-borne disease in recent years. For the effective containment of local outbreaks health authorities rely on the prompt notification of new cases. However, due to severe under-reporting and misdiagnosis, non-endemic countries face difficulties in containing local outbreaks, and the possibility of dengue becoming endemic. Outbreak control measures in non-endemic countries are largely reactive and health authorities would benefit from a universal early warning system that forecasts the probability of dengue outbreaks for given times and locations. We develop a model that establishes a link between pre- and post-border risk of dengue outbreaks. Specifically, we predict the probability of travellers importing dengue from other countries as well as the probability of those travellers causing local outbreaks. Our model can act as an early warning system, forecasting likely times and places of dengue outbreaks. We run our model for the Australian state of Queensland over a period of twelve years. Our results reveal the airports where dengue infected travellers are most likely to arrive and geographic locations associated with high outbreak probabilities. Our results can be used by health authorities to better utilise prevention and control resources and lead to the development of new prevention measures.
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Affiliation(s)
- Jessica Liebig
- Health & Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Queensland, Australia.
| | - Frank de Hoog
- Data61, Commonwealth Scientific and Industrial Research Organisation, Canberra, Australian Capital Territory, Australia
| | - Dean Paini
- Health & Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Canberra, Australian Capital Territory, Australia
| | - Raja Jurdak
- School of Computer Science, Queensland University of Technology, Brisbane, Queensland, Australia; Data61, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Queensland, Australia
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Ramadona AL, Tozan Y, Lazuardi L, Rocklöv J. A combination of incidence data and mobility proxies from social media predicts the intra-urban spread of dengue in Yogyakarta, Indonesia. PLoS Negl Trop Dis 2019; 13:e0007298. [PMID: 30986218 PMCID: PMC6483276 DOI: 10.1371/journal.pntd.0007298] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Revised: 04/25/2019] [Accepted: 03/13/2019] [Indexed: 01/13/2023] Open
Abstract
Only a few studies have investigated the potential of using geotagged social media data for predicting the patterns of spatio-temporal spread of vector-borne diseases. We herein demonstrated the role of human mobility in the intra-urban spread of dengue by weighting local incidence data with geo-tagged Twitter data as a proxy for human mobility across 45 neighborhoods in Yogyakarta city, Indonesia. To estimate the dengue virus importation pressure in each study neighborhood monthly, we developed an algorithm to estimate a dynamic mobility-weighted incidence index (MI), which quantifies the level of exposure to virus importation in any given neighborhood. Using a Bayesian spatio-temporal regression model, we estimated the coefficients and predictiveness of the MI index for lags up to 6 months. Specifically, we used a Poisson regression model with an unstructured spatial covariance matrix. We compared the predictability of the MI index to that of the dengue incidence rate over the preceding months in the same neighborhood (autocorrelation) and that of the mobility information alone. We based our estimates on a volume of 1·302·405 geotagged tweets (from 118·114 unique users) and monthly dengue incidence data for the 45 study neighborhoods in Yogyakarta city over the period from August 2016 to June 2018. The MI index, as a standalone variable, had the highest explanatory power for predicting dengue transmission risk in the study neighborhoods, with the greatest predictive ability at a 3-months lead time. The MI index was a better predictor of the dengue risk in a neighborhood than the recent transmission patterns in the same neighborhood, or just the mobility patterns between neighborhoods. Our results suggest that human mobility is an important driver of the spread of dengue within cities when combined with information on local circulation of the dengue virus. The geotagged Twitter data can provide important information on human mobility patterns to improve our understanding of the direction and the risk of spread of diseases, such as dengue. The proposed MI index together with traditional data sources can provide useful information for the development of more accurate and efficient early warning and response systems.
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Affiliation(s)
- Aditya Lia Ramadona
- Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden
- Center for Environmental Studies, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Yesim Tozan
- College of Global Public Health, New York University, New York, United States of America
| | - Lutfan Lazuardi
- Department of Health Policy and Management, Faculty of Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia
| | - Joacim Rocklöv
- Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden
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Zaki R, Roffeei SN, Hii YL, Yahya A, Appannan M, Said MA, Wan NC, Aghamohammadi N, Hairi NN, Bulgiba A, Quam M, Rocklov J. Public perception and attitude towards dengue prevention activity and response to dengue early warning in Malaysia. PLoS One 2019; 14:e0212497. [PMID: 30818394 PMCID: PMC6394956 DOI: 10.1371/journal.pone.0212497] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Accepted: 02/04/2019] [Indexed: 11/18/2022] Open
Abstract
An early warning system for dengue is meant to predict outbreaks and prevent dengue cases by aiding timely decision making and deployment of interventions. However, only a system which is accepted and utilised by the public would be sustainable in the long run. This study aimed to explore the perception and attitude of the Malaysian public towards a dengue early warning system. The sample consisted of 847 individuals who were 18 years and above and living/working in the Petaling District, an area adjacent to Kuala Lumpur, Malaysia. A questionnaire consisting of personal information and three sub-measures of; i) perception, ii) attitude towards dengue early warning and iii) response towards early warning; was distributed to participants. We found that most of the respondents know about dengue fever (97.1%) and its association with climate factors (90.6%). Most of them wanted to help reduce the number of dengue cases in their area (91.5%). A small percentage of the respondents admitted that they were not willing to be involved in public activities, and 64% of them admitted that they did not check dengue situations or hotspots around their area regularly. Despite the high awareness on the relationship between climate and dengue, about 45% of respondents do not know or are not sure how this can be used to predict dengue. Respondents would like to know more about how climate data can be used to predict a dengue outbreak (92.7%). Providing more information on how climate can influence dengue cases would increase public acceptability and improve response towards climate-based warning system. The most preferred way of communicating early warning was through the television (66.4%). This study shows that the public in Petaling District considers it necessary to have a dengue warning system to be necessary, but more education is required.
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Affiliation(s)
- Rafdzah Zaki
- Centre for Epidemiology and Evidence-Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Malaysia
| | - Siti Norsyuhada Roffeei
- Centre for Epidemiology and Evidence-Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Malaysia
| | - Yien Ling Hii
- Epidemiology and Global Health, Department of Public Health and Clinical Medicine, Umea University, Umea, Sweden
| | - Abqariyah Yahya
- Centre for Epidemiology and Evidence-Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Malaysia
| | - Mahesh Appannan
- Centre for Epidemiology and Evidence-Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Malaysia
| | - Mas Ayu Said
- Centre for Epidemiology and Evidence-Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Malaysia
| | - Ng Chiu Wan
- Centre for Epidemiology and Evidence-Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Malaysia
| | - Nasrin Aghamohammadi
- Centre for Occupational and Environmental Health, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Malaysia
| | - Noran Naqiah Hairi
- Centre for Epidemiology and Evidence-Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Malaysia
| | - Awang Bulgiba
- Centre for Epidemiology and Evidence-Based Practice, Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Malaysia
| | - Mikkel Quam
- Epidemiology and Global Health, Department of Public Health and Clinical Medicine, Umea University, Umea, Sweden
| | - Joacim Rocklov
- Epidemiology and Global Health, Department of Public Health and Clinical Medicine, Umea University, Umea, Sweden
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Marques-Toledo CA, Bendati MM, Codeço CT, Teixeira MM. Probability of dengue transmission and propagation in a non-endemic temperate area: conceptual model and decision risk levels for early alert, prevention and control. Parasit Vectors 2019; 12:38. [PMID: 30651125 PMCID: PMC6335707 DOI: 10.1186/s13071-018-3280-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Accepted: 12/27/2018] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Dengue viruses have spread rapidly across tropical regions of the world in recent decades. Today, dengue transmission is observed in the Americas, Southeast Asia, Western Pacific, Africa and in non-endemic areas of the USA and Europe. Dengue is responsible for 16% of travel-related febrile illnesses. Although most prevalent in tropical areas, risk maps indicate that subtropical regions are suitable for transmission. Dengue-control programs in these regions should focus on minimizing virus importation, community engagement, improved vector surveillance and control. RESULTS We developed a conceptual model for the probability of local introduction and propagation of dengue, comprising disease vulnerability and receptivity, in a temperate area, considering risk factors and social media indicators. Using a rich data set from a temperate area in the south of Brazil (where there is active surveillance of mosquitoes, viruses and human cases), we used a conceptual model as a framework to build two probabilistic models to estimate the probability of initiation and propagation of local dengue transmission. The final models estimated with good accuracy the probabilities of local transmission and propagation, with three and four weeks in advance, respectively. Vulnerability indicators (number of imported cases and dengue virus circulation in mosquitoes) and a receptivity indicator (vector abundance) could be optimally integrated with tweets and temperature data to estimate probability of early local dengue transmission. CONCLUSIONS We demonstrated how vulnerability and receptivity indicators can be integrated into probabilistic models to estimate initiation and propagation of dengue transmission. The models successfully estimate disease risk in different scenarios and periods of the year. We propose a decision model with three different risk levels to assist in the planning of prevention and control measures in temperate regions at risk of dengue introduction.
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Affiliation(s)
- Cecilia A. Marques-Toledo
- Departamento de Bioquimica e Imunologia do Instituto de Ciencias Biologicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Maria Mercedes Bendati
- Vigilancia de Roedores e Vetores da Secretaria Municipal de Saude (CGVS/SMS), Porto Alegre, Brazil
| | - Claudia T. Codeço
- Programa de Computacao Cientifica, Fundacao Oswaldo Cruz, Rio de Janeiro, Brazil
| | - Mauro M. Teixeira
- Departamento de Bioquimica e Imunologia do Instituto de Ciencias Biologicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
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Bowman LR, Rocklöv J, Kroeger A, Olliaro P, Skewes R. A comparison of Zika and dengue outbreaks using national surveillance data in the Dominican Republic. PLoS Negl Trop Dis 2018; 12:e0006876. [PMID: 30395564 PMCID: PMC6237425 DOI: 10.1371/journal.pntd.0006876] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Revised: 11/15/2018] [Accepted: 09/26/2018] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Aedes-borne arboviruses continue to precipitate epidemics worldwide. In Dominican Republic, the appearance of Zika virus cases that closely followed a large dengue epidemic provided an opportunity to study the different transmission drivers behind these two flaviviruses. Retrospective datasets were used to collect information on the populations at risk and descriptive statistics were used to describe the outbreaks on a national scale. METHODOLOGY/ PRINCIPAL FINDINGS Expectedly, box plots showed that 75% of dengue was reported in those aged <20 years while Zika infections were more widely dispersed among the population. Dengue attack rates were marginally higher among males at 25.9 per 10,000 population vs. 21.5 per 10,000 population for females. Zika infections appeared to be highly clustered among females (73.8% (95% CI 72.6%, 75.0%; p<0.05)); age-adjusted Zika attack rates among females were 7.64 per 10,000 population compared with 2.72 per 10,000 population among males. R0 calculations stratified by sex also showed a significantly higher metric among females: 1.84 (1.82, 1.87; p<0.05) when compared to males at 1.72 (1.69, 1.75; p<0.05). However, GBS attack rates stratified by sex revealed slightly higher risk in males vs. females, at 0.62 and 0.57 per 10,000 population respectively. CONCLUSIONS/ SIGNIFICANCE Evidence suggests little impact of existing dengue immunity on reported attack rates of Zika at the population level. Confounding of R0 and incident risk calculations by sex-specific over-reporting can alter the reliability of epidemiological metrics, which could be addressed using associated proxy syndromes or conditions to explore seemingly sex-skewed incidence. The findings indicate that community awareness campaigns, through influencing short-term health seeking behaviour, remain the most plausible mechanism behind increased reporting among women of reproductive age, although biological susceptibility cannot yet be ruled out. Media campaigns and screening are therefore recommended for women of reproductive age during Zika outbreaks. Future research should focus on clinical Zika outcomes among dengue seropositive individuals.
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Affiliation(s)
- Leigh R. Bowman
- Department of Public Health and Clinical Medicine, Unit of Epidemiology and Global Health, Umeå University, Umeå, Sweden
- UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), Geneva, Switzerland
| | - Joacim Rocklöv
- Department of Public Health and Clinical Medicine, Unit of Epidemiology and Global Health, Umeå University, Umeå, Sweden
| | - Axel Kroeger
- UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), Geneva, Switzerland
| | - Piero Olliaro
- UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), Geneva, Switzerland
| | - Ronald Skewes
- Department of Public Health, Ministry of Health, Santo Domingo, Dominican Republic
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Scavuzzo JM, Trucco F, Espinosa M, Tauro CB, Abril M, Scavuzzo CM, Frery AC. Modeling Dengue vector population using remotely sensed data and machine learning. Acta Trop 2018; 185:167-175. [PMID: 29777650 DOI: 10.1016/j.actatropica.2018.05.003] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Revised: 05/03/2018] [Accepted: 05/03/2018] [Indexed: 11/30/2022]
Abstract
Mosquitoes are vectors of many human diseases. In particular, Aedes ægypti (Linnaeus) is the main vector for Chikungunya, Dengue, and Zika viruses in Latin America and it represents a global threat. Public health policies that aim at combating this vector require dependable and timely information, which is usually expensive to obtain with field campaigns. For this reason, several efforts have been done to use remote sensing due to its reduced cost. The present work includes the temporal modeling of the oviposition activity (measured weekly on 50 ovitraps in a north Argentinean city) of Aedes ægypti (Linnaeus), based on time series of data extracted from operational earth observation satellite images. We use are NDVI, NDWI, LST night, LST day and TRMM-GPM rain from 2012 to 2016 as predictive variables. In contrast to previous works which use linear models, we employ Machine Learning techniques using completely accessible open source toolkits. These models have the advantages of being non-parametric and capable of describing nonlinear relationships between variables. Specifically, in addition to two linear approaches, we assess a support vector machine, an artificial neural networks, a K-nearest neighbors and a decision tree regressor. Considerations are made on parameter tuning and the validation and training approach. The results are compared to linear models used in previous works with similar data sets for generating temporal predictive models. These new tools perform better than linear approaches, in particular nearest neighbor regression (KNNR) performs the best. These results provide better alternatives to be implemented operatively on the Argentine geospatial risk system that is running since 2012.
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Affiliation(s)
- Juan M Scavuzzo
- Facultad de Maremática, Atronomía, Física y Computación, Universidad Nacional de Córdoba, Argentina
| | - Francisco Trucco
- Facultad de Maremática, Atronomía, Física y Computación, Universidad Nacional de Córdoba, Argentina
| | | | - Carolina B Tauro
- Instituto de Altos Estudios Espaciales Mario Gulich, Universidad Nacional de Córdoba-Comisión Nacional de Actividades Espaciales, Argentina
| | | | - Carlos M Scavuzzo
- Instituto de Altos Estudios Espaciales Mario Gulich, Universidad Nacional de Córdoba-Comisión Nacional de Actividades Espaciales, Argentina.
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The role of inter-regional flows in the spread of epidemics in a city of regional influence with a tropical climate. Salud Colect 2018; 14:109-119. [PMID: 30020354 DOI: 10.18294/sc.2018.1206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Accepted: 06/01/2017] [Indexed: 11/24/2022] Open
Abstract
The aim of this research was to investigate the origin of imported cases of dengue in the city of Araraquara, Brazil and to describe the disease's main epidemiological characteristics. The study encompassed all confirmed cases of dengue recorded in the Information System for Notifiable Diseases (SINAN) [Sistema de Informação de Agravos de Notificação] from 1998 to 2013. Cases whose origin of infection was likely located outside Araraquara were considered imported. The epidemiological study entailed a descriptive analysis of the data, regarding the distribution of cases by sex, age, and classification of imported and autochthonous cases. A geographic information system was used to map flows and estimate distances. There were 6,913 confirmed cases, 419 of which were imported. In most cases, the origin of infection was located in the state of São Paulo as well as other Brazilian regions. The results indicate the relevance of imported cases and differences in the epidemiological profile with respect to age and sex. Conclusions indicate the need to increase epidemiological and environmental health surveillance at ports, airports, truck stops, and bus and train terminals.
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Early warning and response system (EWARS) for dengue outbreaks: Recent advancements towards widespread applications in critical settings. PLoS One 2018; 13:e0196811. [PMID: 29727447 PMCID: PMC5935393 DOI: 10.1371/journal.pone.0196811] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 04/22/2018] [Indexed: 11/19/2022] Open
Abstract
Background Dengue outbreaks are increasing in frequency over space and time, affecting people’s health and burdening resource-constrained health systems. The ability to detect early emerging outbreaks is key to mounting an effective response. The early warning and response system (EWARS) is a toolkit that provides countries with early-warning systems for efficient and cost-effective local responses. EWARS uses outbreak and alarm indicators to derive prediction models that can be used prospectively to predict a forthcoming dengue outbreak at district level. Methods We report on the development of the EWARS tool, based on users’ recommendations into a convenient, user-friendly and reliable software aided by a user’s workbook and its field testing in 30 health districts in Brazil, Malaysia and Mexico. Findings 34 Health officers from the 30 study districts who had used the original EWARS for 7 to 10 months responded to a questionnaire with mainly open-ended questions. Qualitative content analysis showed that participants were generally satisfied with the tool but preferred open-access vs. commercial software. EWARS users also stated that the geographical unit should be the district, while access to meteorological information should be improved. These recommendations were incorporated into the second-generation EWARS-R, using the free R software, combined with recent surveillance data and resulted in higher sensitivities and positive predictive values of alarm signals compared to the first-generation EWARS. Currently the use of satellite data for meteorological information is being tested and a dashboard is being developed to increase user-friendliness of the tool. The inclusion of other Aedes borne viral diseases is under discussion. Conclusion EWARS is a pragmatic and useful tool for detecting imminent dengue outbreaks to trigger early response activities.
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Spatio-temporal coherence of dengue, chikungunya and Zika outbreaks in Merida, Mexico. PLoS Negl Trop Dis 2018; 12:e0006298. [PMID: 29543910 PMCID: PMC5870998 DOI: 10.1371/journal.pntd.0006298] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Revised: 03/27/2018] [Accepted: 02/04/2018] [Indexed: 12/12/2022] Open
Abstract
Response to Zika virus (ZIKV) invasion in Brazil lagged a year from its estimated February 2014 introduction, and was triggered by the occurrence of severe congenital malformations. Dengue (DENV) and chikungunya (CHIKV) invasions tend to show similar response lags. We analyzed geo-coded symptomatic case reports from the city of Merida, Mexico, with the goal of assessing the utility of historical DENV data to infer CHIKV and ZIKV introduction and propagation. About 42% of the 40,028 DENV cases reported during 2008–2015 clustered in 27% of the city, and these clustering areas were where the first CHIKV and ZIKV cases were reported in 2015 and 2016, respectively. Furthermore, the three viruses had significant agreement in their spatio-temporal distribution (Kendall W>0.63; p<0.01). Longitudinal DENV data generated patterns indicative of the resulting introduction and transmission patterns of CHIKV and ZIKV, leading to important insights for the surveillance and targeted control to emerging Aedes-borne viruses. Over the past decades, Aedes-borne viruses (dengue, chikungunya, Zika) have become a major source of morbidity within urban areas. Worldwide, public health response to these viruses is reactive to the occurrence of symptomatic cases (a small proportion of all infections). Here we used geocoded passive surveillance data to determine if areas of historically persistent dengue transmission fuel the introduction and propagation of other Aedes-borne viruses. This article provides quantitative evidence of the strong spatio-temporal overlap that occurs between dengue, chikungunya and Zika, all transmitted by Aedes aegypti mosquitoes in the city. Additionally, it emphasizes the value of analyzing long-term geo-coded passive surveillance information to help identify areas for prioritizing surveillance and control. Findings from this article open a window for considering historical DENV data to make predictions of likely sources of invasion for other emerging Aedes-borne viruses, as well as to the consideration of spatially-targeted approaches for delivery of vector control and surveillance. Arbovirus control in complex urban environments can greatly benefit from exploiting existing spatial information for better delivery of interventions.
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Olliaro P, Fouque F, Kroeger A, Bowman L, Velayudhan R, Santelli AC, Garcia D, Skewes Ramm R, Sulaiman LH, Tejeda GS, Morales FC, Gozzer E, Garrido CB, Quang LC, Gutierrez G, Yadon ZE, Runge-Ranzinger S. Improved tools and strategies for the prevention and control of arboviral diseases: A research-to-policy forum. PLoS Negl Trop Dis 2018; 12:e0005967. [PMID: 29389959 PMCID: PMC5794069 DOI: 10.1371/journal.pntd.0005967] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Research has been conducted on interventions to control dengue transmission and respond to outbreaks. A summary of the available evidence will help inform disease control policy decisions and research directions, both for dengue and, more broadly, for all Aedes-borne arboviral diseases. METHOD A research-to-policy forum was convened by TDR, the Special Programme for Research and Training in Tropical Diseases, with researchers and representatives from ministries of health, in order to review research findings and discuss their implications for policy and research. RESULTS The participants reviewed findings of research supported by TDR and others. Surveillance and early outbreak warning. Systematic reviews and country studies identify the critical characteristics that an alert system should have to document trends reliably and trigger timely responses (i.e., early enough to prevent the epidemic spread of the virus) to dengue outbreaks. A range of variables that, according to the literature, either indicate risk of forthcoming dengue transmission or predict dengue outbreaks were tested and some of them could be successfully applied in an Early Warning and Response System (EWARS). Entomological surveillance and vector management. A summary of the published literature shows that controlling Aedes vectors requires complex interventions and points to the need for more rigorous, standardised study designs, with disease reduction as the primary outcome to be measured. House screening and targeted vector interventions are promising vector management approaches. Sampling vector populations, both for surveillance purposes and evaluation of control activities, is usually conducted in an unsystematic way, limiting the potentials of entomological surveillance for outbreak prediction. Combining outbreak alert and improved approaches of vector management will help to overcome the present uncertainties about major risk groups or areas where outbreak response should be initiated and where resources for vector management should be allocated during the interepidemic period. CONCLUSIONS The Forum concluded that the evidence collected can inform policy decisions, but also that important research gaps have yet to be filled.
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Affiliation(s)
- Piero Olliaro
- UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), World Health Organization, Geneva, Switzerland
| | - Florence Fouque
- UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), World Health Organization, Geneva, Switzerland
| | - Axel Kroeger
- UNICEF/UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR), World Health Organization, Geneva, Switzerland
- Global Health Department, Centre for Medicine and Society/Anthropology, Freiburg University, Freiburg im Breisgau, Germany
| | - Leigh Bowman
- Department of Vector Biology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Raman Velayudhan
- Department of Control of Neglected Tropical Diseases (WHO/NTD), World Health Organization, Geneva, Switzerland
| | | | - Diego Garcia
- Department of Communicable Diseases, Ministry of Health, Bogota, Colombia
| | - Ronald Skewes Ramm
- Program for the Prevention and Control of Dengue, Ministry of Health, Santo Domingo, Dominican Republic
| | | | - Gustavo Sanchez Tejeda
- Centro Nacional de Programas Preventivos y Control de Enfermedades (CENAPRECE), Ministry of Health, Mexico City, Mexico
| | - Fabiàn Correa Morales
- Centro Nacional de Programas Preventivos y Control de Enfermedades (CENAPRECE), Ministry of Health, Mexico City, Mexico
| | | | | | - Luong Chan Quang
- Department for Disease Control and Prevention, Pasteur Institute, Ho Chi Minh City, Vietnam
| | - Gamaliel Gutierrez
- PAHO/AMRO, World Health Organization, Washington, DC, United States of America
| | - Zaida E. Yadon
- PAHO/AMRO, World Health Organization, Rio de Janeiro, Brazil
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Abdul Rahman AA. ISQUA17-1024USING CLINICAL PATHWAY TO MANAGE DENGUE FEVER. Int J Qual Health Care 2017. [DOI: 10.1093/intqhc/mzx125.91] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Liyanage P, Tissera H, Sewe M, Quam M, Amarasinghe A, Palihawadana P, Wilder-Smith A, Louis VR, Tozan Y, Rocklöv J. A Spatial Hierarchical Analysis of the Temporal Influences of the El Niño-Southern Oscillation and Weather on Dengue in Kalutara District, Sri Lanka. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2016; 13:ijerph13111087. [PMID: 27827943 PMCID: PMC5129297 DOI: 10.3390/ijerph13111087] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Revised: 10/21/2016] [Accepted: 10/28/2016] [Indexed: 01/05/2023]
Abstract
Dengue is the major public health burden in Sri Lanka. Kalutara is one of the highly affected districts. Understanding the drivers of dengue is vital in controlling and preventing the disease spread. This study focuses on quantifying the influence of weather variability on dengue incidence over 10 Medical Officer of Health (MOH) divisions of Kalutara district. Weekly weather variables and data on dengue notifications, measured at 10 MOH divisions in Kalutara from 2009 to 2013, were retrieved and analysed. Distributed lag non-linear model and hierarchical-analysis was used to estimate division specific and overall relationships between weather and dengue. We incorporated lag times up to 12 weeks and evaluated models based on the Akaike Information Criterion. Consistent exposure-response patterns between different geographical locations were observed for rainfall, showing increasing relative risk of dengue with increasing rainfall from 50 mm per week. The strongest association with dengue risk centred around 6 to 10 weeks following rainfalls of more than 300 mm per week. With increasing temperature, the overall relative risk of dengue increased steadily starting from a lag of 4 weeks. We found similarly a strong link between the Oceanic Niño Index to weather patterns in the district in Sri Lanka and to dengue at a longer latency time confirming these relationships. Part of the influences of rainfall and temperature can be seen as mediator in the causal pathway of the Ocean Niño Index, which may allow a longer lead time for early warning signals. Our findings describe a strong association between weather, El Niño-Southern Oscillation and dengue in Sri Lanka.
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Affiliation(s)
- Prasad Liyanage
- Ministry of Health, Colombo 01000, Sri Lanka.
- Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, SE-901 87 Umeå, Sweden.
| | | | - Maquins Sewe
- Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, SE-901 87 Umeå, Sweden.
- KEMRI Centre for Global Health Research, Kisumu, Kenya, Box 1578, Kisumu 40100, Kenya.
| | - Mikkel Quam
- Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, SE-901 87 Umeå, Sweden.
| | | | | | - Annelies Wilder-Smith
- Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, SE-901 87 Umeå, Sweden.
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore.
| | - Valérie R Louis
- Institute of Public Health, University of Heidelberg Medical School, D-69120 Heidelberg, Germany.
| | - Yesim Tozan
- College of Global Public Health, New York University, New York, NY 10003, USA.
| | - Joacim Rocklöv
- Department of Public Health and Clinical Medicine, Epidemiology and Global Health, Umeå University, SE-901 87 Umeå, Sweden.
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Runge-Ranzinger S, Kroeger A, Olliaro P, McCall PJ, Sánchez Tejeda G, Lloyd LS, Hakim L, Bowman LR, Horstick O, Coelho G. Dengue Contingency Planning: From Research to Policy and Practice. PLoS Negl Trop Dis 2016; 10:e0004916. [PMID: 27653786 PMCID: PMC5031449 DOI: 10.1371/journal.pntd.0004916] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Accepted: 07/21/2016] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Dengue is an increasingly incident disease across many parts of the world. In response, an evidence-based handbook to translate research into policy and practice was developed. This handbook facilitates contingency planning as well as the development and use of early warning and response systems for dengue fever epidemics, by identifying decision-making processes that contribute to the success or failure of dengue surveillance, as well as triggers that initiate effective responses to incipient outbreaks. METHODOLOGY/PRINCIPAL FINDINGS Available evidence was evaluated using a step-wise process that included systematic literature reviews, policymaker and stakeholder interviews, a study to assess dengue contingency planning and outbreak management in 10 countries, and a retrospective logistic regression analysis to identify alarm signals for an outbreak warning system using datasets from five dengue endemic countries. Best practices for managing a dengue outbreak are provided for key elements of a dengue contingency plan including timely contingency planning, the importance of a detailed, context-specific dengue contingency plan that clearly distinguishes between routine and outbreak interventions, surveillance systems for outbreak preparedness, outbreak definitions, alert algorithms, managerial capacity, vector control capacity, and clinical management of large caseloads. Additionally, a computer-assisted early warning system, which enables countries to identify and respond to context-specific variables that predict forthcoming dengue outbreaks, has been developed. CONCLUSIONS/SIGNIFICANCE Most countries do not have comprehensive, detailed contingency plans for dengue outbreaks. Countries tend to rely on intensified vector control as their outbreak response, with minimal focus on integrated management of clinical care, epidemiological, laboratory and vector surveillance, and risk communication. The Technical Handbook for Surveillance, Dengue Outbreak Prediction/ Detection and Outbreak Response seeks to provide countries with evidence-based best practices to justify the declaration of an outbreak and the mobilization of the resources required to implement an effective dengue contingency plan.
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Affiliation(s)
- Silvia Runge-Ranzinger
- Institute of Public Health, University of Heidelberg, Heidelberg, Germany
- Special Programme for Research and Training WHO-TDR, Geneva, Switzerland
| | - Axel Kroeger
- Special Programme for Research and Training WHO-TDR, Geneva, Switzerland
- Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Piero Olliaro
- Special Programme for Research and Training WHO-TDR, Geneva, Switzerland
| | - Philip J. McCall
- Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | | | - Linda S. Lloyd
- Public Health Consultant, San Diego, California, United States of America
| | | | - Leigh R. Bowman
- Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Olaf Horstick
- Institute of Public Health, University of Heidelberg, Heidelberg, Germany
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