1
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Tapias-Rivera J, Martínez-Vega RA, Román-Pérez S, Santos-Luna R, Amaya-Larios IY, Diaz-Quijano FA, Ramos-Castañeda J. Microclimate factors related to dengue virus burden clusters in two endemic towns of Mexico. PLoS One 2024; 19:e0302025. [PMID: 38843173 PMCID: PMC11156286 DOI: 10.1371/journal.pone.0302025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 03/26/2024] [Indexed: 06/09/2024] Open
Abstract
In dengue-endemic areas, transmission control is limited by the difficulty of achieving sufficient coverage and sustainability of interventions. To maximize the effectiveness of interventions, areas with higher transmission could be identified and prioritized. The aim was to identify burden clusters of Dengue virus (DENV) infection and evaluate their association with microclimatic factors in two endemic towns from southern Mexico. Information from a prospective population cohort study (2·5 years of follow-up) was used, microclimatic variables were calculated from satellite information, and a cross-sectional design was conducted to evaluate the relationship between the outcome and microclimatic variables in the five surveys. Spatial clustering was observed in specific geographic areas at different periods. Both, land surface temperature (aPR 0·945; IC95% 0·895-0·996) and soil humidity (aPR 3·018; IC95% 1·013-8·994), were independently associated with DENV burden clusters. These findings can help health authorities design focused dengue surveillance and control activities in dengue endemic areas.
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Affiliation(s)
- Johanna Tapias-Rivera
- Maestría en Investigación en Enfermedades Infecciosas, Facultad de Ciencias Médicas y de la Salud, Instituto de Investigación Masira, Universidad de Santander, Bucaramanga, Santander, Colombia
| | - Ruth Aralí Martínez-Vega
- Escuela de Medicina, Facultad de Ciencias Médicas y de la Salud, Instituto de Investigación Masira, Universidad de Santander, Bucaramanga, Santander, Colombia
| | - Susana Román-Pérez
- Centro de Investigación en Evaluación y Encuestas, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, México
| | - Rene Santos-Luna
- Centro de Investigación en Evaluación y Encuestas, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, México
| | | | - Fredi Alexander Diaz-Quijano
- Department of Epidemiology–Laboratório de Inferência Causal em Epidemiologia (LINCE-USP), School of Public Health, University of São Paulo, São Paulo, Brazil
| | - José Ramos-Castañeda
- Centro de Investigaciones Sobre Enfermedades Infecciosas, Instituto Nacional de Salud Pública, Cuernavaca, Morelos, México
- Facultad de Ciencias de la Salud, Universidad Anahuac, Ciudad de México, México
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2
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Mondal A, Sánchez C. HM, Marshall JM. MGDrivE 3: A decoupled vector-human framework for epidemiological simulation of mosquito genetic control tools and their surveillance. PLoS Comput Biol 2024; 20:e1012133. [PMID: 38805562 PMCID: PMC11161092 DOI: 10.1371/journal.pcbi.1012133] [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: 10/06/2023] [Revised: 06/07/2024] [Accepted: 05/03/2024] [Indexed: 05/30/2024] Open
Abstract
Novel mosquito genetic control tools, such as CRISPR-based gene drives, hold great promise in reducing the global burden of vector-borne diseases. As these technologies advance through the research and development pipeline, there is a growing need for modeling frameworks incorporating increasing levels of entomological and epidemiological detail in order to address questions regarding logistics and biosafety. Epidemiological predictions are becoming increasingly relevant to the development of target product profiles and the design of field trials and interventions, while entomological surveillance is becoming increasingly important to regulation and biosafety. We present MGDrivE 3 (Mosquito Gene Drive Explorer 3), a new version of a previously-developed framework, MGDrivE 2, that investigates the spatial population dynamics of mosquito genetic control systems and their epidemiological implications. The new framework incorporates three major developments: i) a decoupled sampling algorithm allowing the vector portion of the MGDrivE framework to be paired with a more detailed epidemiological framework, ii) a version of the Imperial College London malaria transmission model, which incorporates age structure, various forms of immunity, and human and vector interventions, and iii) a surveillance module that tracks mosquitoes captured by traps throughout the simulation. Example MGDrivE 3 simulations are presented demonstrating the application of the framework to a CRISPR-based homing gene drive linked to dual disease-refractory genes and their potential to interrupt local malaria transmission. Simulations are also presented demonstrating surveillance of such a system by a network of mosquito traps. MGDrivE 3 is freely available as an open-source R package on CRAN (https://cran.r-project.org/package=MGDrivE2) (version 2.1.0), and extensive examples and vignettes are provided. We intend the software to aid in understanding of human health impacts and biosafety of mosquito genetic control tools, and continue to iterate per feedback from the genetic control community.
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Affiliation(s)
- Agastya Mondal
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, California, United States of America
| | - Héctor M. Sánchez C.
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, California, United States of America
| | - John M. Marshall
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, California, United States of America
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3
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Aogo RA, Zambrana JV, Sanchez N, Ojeda S, Kuan G, Balmaseda A, Gordon A, Harris E, Katzelnick LC. Effects of boosting and waning in highly exposed populations on dengue epidemic dynamics. Sci Transl Med 2023; 15:eadi1734. [PMID: 37967199 PMCID: PMC11001200 DOI: 10.1126/scitranslmed.adi1734] [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: 04/13/2023] [Accepted: 10/13/2023] [Indexed: 11/17/2023]
Abstract
Sequential infection with multiple dengue virus (DENV) serotypes is thought to induce enduring protection against dengue disease. However, long-term antibody waning has been observed after repeated DENV infection. Here, we provide evidence that highly immune Nicaraguan children and adults (n = 4478) experience boosting and waning of antibodies during and after major Zika and dengue epidemics. We develop a susceptible-infected-recovered-susceptible (SIRS-type) model that tracks immunity by titer rather than number of infections to show that boosts in highly immune individuals can contribute to herd immunity, delaying their susceptibility to transmissible infection. In contrast, our model of lifelong immunity in highly immune individuals, as previously assumed, results in complete disease eradication after introduction. Periodic epidemics under this scenario can only be sustained with a constant influx of infected individuals into the population or a high basic reproductive number. We also find that Zika virus infection can boost DENV immunity and produce delays and then surges in dengue epidemics, as observed with real epidemiological data. This work provides insight into factors shaping periodicity in dengue incidence and may inform vaccine efforts to maintain population immunity.
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Affiliation(s)
- Rosemary A. Aogo
- Viral Epidemiology and Immunity Unit, Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892-3203, USA
| | - Jose Victor Zambrana
- Sustainable Sciences Institute, Managua, 14007, Nicaragua
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
| | - Nery Sanchez
- Sustainable Sciences Institute, Managua, 14007, Nicaragua
| | - Sergio Ojeda
- Sustainable Sciences Institute, Managua, 14007, Nicaragua
| | - Guillermina Kuan
- Sustainable Sciences Institute, Managua, 14007, Nicaragua
- Centro de Salud Sócrates Flores Vivas, Ministry of Health, Managua, 12014, Nicaragua
| | - Angel Balmaseda
- Sustainable Sciences Institute, Managua, 14007, Nicaragua
- Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, 16064, Nicaragua
| | - Aubree Gordon
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
| | - Eva Harris
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, CA, 94720-3370, USA
| | - Leah C. Katzelnick
- Viral Epidemiology and Immunity Unit, Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892-3203, USA
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4
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Fung T, Clapham HE, Chisholm RA. Temporary Cross-Immunity as a Plausible Driver of Asynchronous Cycles of Dengue Serotypes. Bull Math Biol 2023; 85:124. [PMID: 37962713 DOI: 10.1007/s11538-023-01226-4] [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: 01/27/2023] [Accepted: 10/16/2023] [Indexed: 11/15/2023]
Abstract
Many infectious diseases exist as multiple variants, with interactions between variants potentially driving epidemiological dynamics. These diseases include dengue, which infects hundreds of millions of people every year and exhibits complex multi-serotype dynamics. Antibodies produced in response to primary infection by one of the four dengue serotypes can produce a period of temporary cross-immunity (TCI) to infection by other serotypes. After this period, the remaining antibodies can facilitate the entry of heterologous serotypes into target cells, thus enhancing severity of secondary infection by a heterologous serotype. This represents antibody-dependent enhancement (ADE). In this study, we analyze an epidemiological model to provide novel insights into the importance of TCI and ADE in producing cyclic outbreaks of dengue serotypes. Our analyses reveal that without TCI, such cyclic outbreaks are synchronous across serotypes and only occur when ADE produces high transmission rates. In contrast, the presence of TCI allows asynchronous cycles of serotypes by inducing a time lag between recovery from primary infection by one serotype and secondary infection by another, with such cycles able to occur without ADE. Our results suggest that TCI is a fundamental driver of asynchronous cycles of dengue serotypes and possibly other multi-variant diseases.
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Affiliation(s)
- Tak Fung
- Department of Biological Sciences, National University of Singapore, 16 Science Drive 4, Singapore, 117558, Singapore.
| | - Hannah E Clapham
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, Singapore, 117549, Singapore
| | - Ryan A Chisholm
- Department of Biological Sciences, National University of Singapore, 16 Science Drive 4, Singapore, 117558, Singapore
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5
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Mondal A, C. HMS, Marshall JM. MGDrivE 3: A decoupled vector-human framework for epidemiological simulation of mosquito genetic control tools and their surveillance. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.09.556958. [PMID: 37745458 PMCID: PMC10515759 DOI: 10.1101/2023.09.09.556958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Novel mosquito genetic control tools, such as CRISPR-based gene drives, hold great promise in reducing the global burden of vector-borne diseases. As these technologies advance through the research and development pipeline, there is a growing need for modeling frameworks incorporating increasing levels of entomological and epidemiological detail in order to address questions regarding logistics and biosafety. Epidemiological predictions are becoming increasingly relevant to the development of target product profiles and the design of field trials and interventions, while entomological surveillance is becoming increasingly important to regulation and biosafety. We present MGDrivE 3 (Mosquito Gene Drive Explorer 3), a new version of a previously-developed framework, MGDrivE 2, that investigates the spatial population dynamics of mosquito genetic control systems and their epidemiological implications. The new framework incorporates three major developments: i) a decoupled sampling algorithm allowing the vector portion of the MGDrivE framework to be paired with a more detailed epidemiological framework, ii) a version of the Imperial College London malaria transmission model, which incorporates age structure, various forms of immunity, and human and vector interventions, and iii) a surveillance module that tracks mosquitoes captured by traps throughout the simulation. Example MGDrivE 3 simulations are presented demonstrating the application of the framework to a CRISPR-based homing gene drive linked to dual disease-refractory genes and their potential to interrupt local malaria transmission. Simulations are also presented demonstrating surveillance of such a system by a network of mosquito traps. MGDrivE 3 is freely available as an open-source R package on CRAN (https://cran.r-project.org/package=MGDrivE2) (version 2.1.0), and extensive examples and vignettes are provided. We intend the software to aid in understanding of human health impacts and biosafety of mosquito genetic control tools, and continue to iterate per feedback from the genetic control community.
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Affiliation(s)
- Agastya Mondal
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, CA, 94720, USA
| | - Héctor M. Sánchez C.
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, CA, 94720, USA
| | - John M. Marshall
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, CA, 94720, USA
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6
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Li HH, Su MP, Wu SC, Tsou HH, Chang MC, Cheng YC, Tsai KN, Wang HW, Chen GH, Tang CK, Chung PJ, Tsai WT, Huang LR, Yueh YA, Chen HW, Pan CY, Akbari OS, Chang HH, Yu GY, Marshall JM, Chen CH. Mechanical transmission of dengue virus by Aedes aegypti may influence disease transmission dynamics during outbreaks. EBioMedicine 2023; 94:104723. [PMID: 37487418 PMCID: PMC10382859 DOI: 10.1016/j.ebiom.2023.104723] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 07/02/2023] [Accepted: 07/06/2023] [Indexed: 07/26/2023] Open
Abstract
BACKGROUND Dengue virus outbreaks are increasing in number and severity worldwide. Viral transmission is assumed to require a minimum time period of viral replication within the mosquito midgut. It is unknown if alternative transmission periods not requiring replication are possible. METHODS We used a mouse model of dengue virus transmission to investigate the potential of mechanical transmission of dengue virus. We investigated minimal viral titres necessary for development of symptoms in bitten mice and used resulting parameters to inform a new model of dengue virus transmission within a susceptible population. FINDINGS Naïve mice bitten by mosquitoes immediately after they took partial blood meals from dengue infected mice showed symptoms of dengue virus, followed by mortality. Incorporation of mechanical transmission into mathematical models of dengue virus transmission suggest that this supplemental transmission route could result in larger outbreaks which peak sooner. INTERPRETATION The potential of dengue transmission routes independent of midgut viral replication has implications for vector control strategies that target mosquito lifespan and suggest the possibility of similar mechanical transmission routes in other disease-carrying mosquitoes. FUNDING This study was funded by grants from the National Health Research Institutes, Taiwan (04D2-MMMOST02), the Human Frontier Science Program (RGP0033/2021), the National Institutes of Health (1R01AI143698-01A1, R01AI151004 and DP2AI152071) and the Ministry of Science and Technology, Taiwan (MOST104-2321-B-400-016).
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Affiliation(s)
- Hsing-Han Li
- National Mosquito-Borne Disease Control Research Center, NHRI, Miaoli, 350401, Taiwan; National Institute of Infectious Diseases and Vaccinology, NHRI, Miaoli, 350401, Taiwan; Division of Biological Sciences, Section of Cell and Developmental Biology, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Matthew P Su
- Graduate School of Science, Nagoya University, Nagoya, 464-8602, Japan; Institute for Advanced Research, Nagoya University, Nagoya, 464-8601, Japan
| | - Shih-Cheng Wu
- National Mosquito-Borne Disease Control Research Center, NHRI, Miaoli, 350401, Taiwan; National Institute of Infectious Diseases and Vaccinology, NHRI, Miaoli, 350401, Taiwan; Department of Clinical Laboratory Sciences and Medical Biotechnology, College of Medicine, National Taiwan University, Taipei, 10048, Taiwan; Department of Laboratory Medicine, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, 10021, Taiwan
| | - Hsiao-Hui Tsou
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, 350401, Taiwan; Graduate Institute of Biostatistics, College of Public Health, China Medical University, Taichung, 40402, Taiwan
| | - Meng-Chun Chang
- Department of Life Science & Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan
| | - Yu-Chieh Cheng
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, 350401, Taiwan
| | - Kuen-Nan Tsai
- Institute of Molecular and Genomic Medicine, NHRI, Miaoli, 350401, Taiwan
| | - Hsin-Wei Wang
- National Mosquito-Borne Disease Control Research Center, NHRI, Miaoli, 350401, Taiwan; National Institute of Infectious Diseases and Vaccinology, NHRI, Miaoli, 350401, Taiwan
| | - Guan-Hua Chen
- National Institute of Infectious Diseases and Vaccinology, NHRI, Miaoli, 350401, Taiwan; Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan
| | - Cheng-Kang Tang
- National Institute of Infectious Diseases and Vaccinology, NHRI, Miaoli, 350401, Taiwan; Program of Plant Protection and Health, Academy of Circular Economy, National Chung Hsing University, Taichung, 402202, Taiwan
| | - Pei-Jung Chung
- National Institute of Infectious Diseases and Vaccinology, NHRI, Miaoli, 350401, Taiwan
| | - Wan-Ting Tsai
- National Institute of Infectious Diseases and Vaccinology, NHRI, Miaoli, 350401, Taiwan
| | - Li-Rung Huang
- Institute of Molecular and Genomic Medicine, NHRI, Miaoli, 350401, Taiwan
| | - Yueh Andrew Yueh
- Institute of Biotechnology and Pharmaceutical Research, NHRI, Miaoli, 350401, Taiwan
| | - Hsin-Wei Chen
- National Institute of Infectious Diseases and Vaccinology, NHRI, Miaoli, 350401, Taiwan
| | - Chao-Ying Pan
- Department of Health, Kaohsiung City Government, Kaohsiung, 800852, Taiwan
| | - Omar S Akbari
- Division of Biological Sciences, Section of Cell and Developmental Biology, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Hsiao-Han Chang
- Department of Life Science & Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan
| | - Guann-Yi Yu
- National Institute of Infectious Diseases and Vaccinology, NHRI, Miaoli, 350401, Taiwan
| | - John M Marshall
- Divisions of Biostatistics and Epidemiology, School of Public Health, University of California, Berkeley, CA, 94720, USA
| | - Chun-Hong Chen
- National Mosquito-Borne Disease Control Research Center, NHRI, Miaoli, 350401, Taiwan; National Institute of Infectious Diseases and Vaccinology, NHRI, Miaoli, 350401, Taiwan.
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7
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Sánchez-González G, Condé R. Mathematical modeling of Dengue virus serotypes propagation in Mexico. PLoS One 2023; 18:e0288392. [PMID: 37450471 PMCID: PMC10348539 DOI: 10.1371/journal.pone.0288392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 06/26/2023] [Indexed: 07/18/2023] Open
Abstract
The Dengue virus (DENV) constitutes a major vector borne virus disease worldwide. Prediction of the DENV spread dynamics, prevalence and infection rates are crucial elements to guide the public health services effort towards meaningful actions. The existence of four DENV serotypes further complicates the virus proliferation forecast. The different serotypes have varying clinical impacts, and the symptomatology of the infection is dependent on the infection history of the patient. Therefore, changes in the prevalent DENV serotype found in one location have a profound impact on the regional public health. The prediction of the spread and intensity of infection of the individual DENV serotypes in specific locations would allow the authorities to plan local pesticide spray to control the vector as well as the purchase of specific antibody therapy. Here we used a mathematical model to predict serotype-specific DENV prevalence and overall case burden in Mexico.
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Affiliation(s)
- Gilberto Sánchez-González
- Centro de Investigación Sobre Enfermedades Infecciosas, Instituto Nacional de Salud Pública, Morelos, México
| | - Renaud Condé
- Centro de Investigación Sobre Enfermedades Infecciosas, Instituto Nacional de Salud Pública, Morelos, México
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8
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Zhou W, Tang B, Bai Y, Shao Y, Xiao Y, Tang S. The resurgence risk of COVID-19 in China in the presence of immunity waning and ADE: A mathematical modelling study. Vaccine 2022; 40:7141-7150. [PMID: 36328883 PMCID: PMC9597525 DOI: 10.1016/j.vaccine.2022.10.043] [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: 08/28/2021] [Revised: 09/24/2022] [Accepted: 10/19/2022] [Indexed: 01/27/2023]
Abstract
The mass vaccination program has been actively promoted since the end of 2020. However, waning immunity, antibody-dependent enhancement (ADE), and increased transmissibility of variants make the herd immunity untenable and the implementation of dynamic zero-COVID policy challenging in China. To explore how long the vaccination program can prevent China at low resurgence risk, and how these factors affect the long-term trajectory of the COVID-19 epidemics, we developed a dynamic transmission model of COVID-19 incorporating vaccination and waning immunity, calibrated using the data of accumulative vaccine doses administered and the COVID-19 epidemic in 2020 in mainland China. The prediction suggests that the vaccination coverage with at least one dose reach 95.87%, and two doses reach 77.92% on 31 August 2021. However, despite the mass vaccination, randomly introducing infected cases in the post-vaccination period causes large outbreaks quickly with waning immunity, particularly for SARS-CoV-2 variants with higher transmissibility. The results showed that with the current vaccination program and 50% of the population wearing masks, mainland China can be protected at low resurgence risk until 8 January 2023. However, ADE and higher transmissibility for variants would significantly shorten the low-risk period by over 1 year. Furthermore, intermittent outbreaks can occur while the peak values of the subsequent outbreaks decrease, indicating that subsequent outbreaks boosted immunity in the population level, further indicating that follow-up vaccination programs can help mitigate or avoid the possible outbreaks. The findings revealed that the integrated effects of multiple factors: waning immunity, ADE, relaxed interventions, and higher variant transmissibility, make controlling COVID-19 challenging. We should prepare for a long struggle with COVID-19, and not entirely rely on the COVID-19 vaccine.
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Affiliation(s)
- Weike Zhou
- School of Mathematics and Statistics, Shaanxi Normal University, Xi’an 710119, PR China
| | - Biao Tang
- School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, PR China
| | - Yao Bai
- Department of Infection Disease Control and Prevention, Xi’an Center for Disease Prevention and Control, Xi’an, 710043, PR China
| | - Yiming Shao
- State Key Laboratory for Infectious Disease Prevention and Control, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, PR China
| | - Yanni Xiao
- School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, PR China,Corresponding author
| | - Sanyi Tang
- School of Mathematics and Statistics, Shaanxi Normal University, Xi’an 710119, PR China,Corresponding author
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9
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Gutierrez JA, Laneri K, Aparicio JP, Sibona GJ. Meteorological indicators of dengue epidemics in non-endemic Northwest Argentina. Infect Dis Model 2022; 7:823-834. [DOI: 10.1016/j.idm.2022.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 10/11/2022] [Accepted: 10/12/2022] [Indexed: 11/07/2022] Open
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10
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How heterogeneous is the dengue transmission profile in Brazil? A study in six Brazilian states. PLoS Negl Trop Dis 2022; 16:e0010746. [PMID: 36095004 PMCID: PMC9499305 DOI: 10.1371/journal.pntd.0010746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 09/22/2022] [Accepted: 08/17/2022] [Indexed: 11/19/2022] Open
Abstract
Dengue is a vector-borne disease present in most tropical countries, infecting an average of 50 to 100 million people per year. Socioeconomic, demographic, and environmental factors directly influence the transmission cycle of the dengue virus (DENV). In Brazil, these factors vary between regions producing different profiles of dengue transmission and challenging the epidemiological surveillance of the disease. In this article, we aimed at classifying the profiles of dengue transmission in 1,823 Brazilian municipalities, covering different climates, from 2010 to 2019. Time series data of dengue cases were obtained from six states: Ceará and Maranhão in the semiarid Northeast, Minas Gerais in the countryside, Espírito Santo and Rio de Janeiro in the tropical Atlantic coast, and Paraná in the subtropical region. To describe the time series, we proposed a set of epi-features of the magnitude and duration of the dengue epidemic cycles, totaling 13 indicators. Using these epi-features as inputs, a multivariate cluster algorithm was employed to classify the municipalities according to their dengue transmission profile. Municipalities were classified into four distinct dengue transmission profiles: persistent transmission (7.8%), epidemic (21.3%), episodic/epidemic (43.2%), and episodic transmission (27.6%). Different profiles were associated with the municipality’s population size and climate. Municipalities with higher incidence and larger populations tended to be classified as persistent transmission, suggesting the existence of critical community size. This association, however, varies depending on the state, indicating the importance of other factors. The proposed classification is useful for developing more specific and precise surveillance protocols for regions with different dengue transmission profiles, as well as more precise public policies for dengue prevention. Dengue is one of the fastest-growing vector-borne diseases in the world. Currently, vaccines are experimental and are not very effective, so prevention depends on the control of the mosquito Aedes aegypti. Health promotion campaigns aimed at encouraging people to reduce mosquito breeding sites have limited effect. In addition, the heterogeneity of the territories that have dengue becomes a major challenge for the epidemiological surveillance of the disease. Brazil has a territory of continental size, and single standardized surveillance is not very effective for monitoring this arbovirus. Classifying types of dengue dynamics based on features of the epidemiological cycle in each location has the potential to increase the precision of surveillance and control strategies. In our study, we were able to classify areas according to different dengue transmission profiles, ranging from episodic to persistent transmission. These results can provide tools to guide actions aimed at achieving the World Health Organization’s goals of eliminating neglected tropical diseases in countries that have the virus.
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11
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Freitas LP, Carabali M, Yuan M, Jaramillo-Ramirez GI, Balaguera CG, Restrepo BN, Zinszer K. Spatio-temporal clusters and patterns of spread of dengue, chikungunya, and Zika in Colombia. PLoS Negl Trop Dis 2022; 16:e0010334. [PMID: 35998165 PMCID: PMC9439233 DOI: 10.1371/journal.pntd.0010334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 09/02/2022] [Accepted: 07/12/2022] [Indexed: 12/03/2022] Open
Abstract
Background Colombia has one of the highest burdens of arboviruses in South America. The country was in a state of hyperendemicity between 2014 and 2016, with co-circulation of several Aedes-borne viruses, including a syndemic of dengue, chikungunya, and Zika in 2015. Methodology/Principal findings We analyzed the cases of dengue, chikungunya, and Zika notified in Colombia from January 2014 to December 2018 by municipality and week. The trajectory and velocity of spread was studied using trend surface analysis, and spatio-temporal high-risk clusters for each disease in separate and for the three diseases simultaneously (multivariate) were identified using Kulldorff’s scan statistics. During the study period, there were 366,628, 77,345 and 74,793 cases of dengue, chikungunya, and Zika, respectively, in Colombia. The spread patterns for chikungunya and Zika were similar, although Zika’s spread was accelerated. Both chikungunya and Zika mainly spread from the regions on the Atlantic coast and the south-west to the rest of the country. We identified 21, 16, and 13 spatio-temporal clusters of dengue, chikungunya and Zika, respectively, and, from the multivariate analysis, 20 spatio-temporal clusters, among which 7 were simultaneous for the three diseases. For all disease-specific analyses and the multivariate analysis, the most-likely cluster was identified in the south-western region of Colombia, including the Valle del Cauca department. Conclusions/Significance The results further our understanding of emerging Aedes-borne diseases in Colombia by providing useful evidence on their potential site of entry and spread trajectory within the country, and identifying spatio-temporal disease-specific and multivariate high-risk clusters of dengue, chikungunya, and Zika, information that can be used to target interventions. Dengue, chikungunya, and Zika are diseases transmitted to humans by the bite of infected Aedes mosquitoes. Between 2014 and 2016 chikungunya and Zika viruses started causing outbreaks in Colombia, one of the countries historically most affected by dengue. We used case counts of the diseases by municipality and week to study the spread trajectory of chikungunya and Zika within Colombia’s territory, and to identify space-time high-risk clusters, i.e., the areas and time periods that dengue, chikungunya, and Zika were more present. Chikungunya and Zika spread similarly in Colombia, but Zika spread faster. The Atlantic coast, a famous touristic destination in the country, was likely the place of entry of chikungunya and Zika in Colombia. The south-western region was identified as a high-risk cluster for all three diseases in separate and simultaneously. This region has a favorable climate for the Aedes mosquitoes and other characteristics that facilitate the diseases’ transmission, such as social deprivation and high population mobility. Our results provide useful information on the locations that should be prioritized for interventions to prevent the entry of new diseases transmitted by Aedes and to reduce the burden of dengue, chikungunya and Zika where they are established.
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Affiliation(s)
- Laís Picinini Freitas
- School of Public Health, University of Montreal, Montreal, Quebec, Canada
- Centre de Recherche en Santé Publique, Montreal, Quebec, Canada
| | - Mabel Carabali
- School of Public Health, University of Montreal, Montreal, Quebec, Canada
- Centre de Recherche en Santé Publique, Montreal, Quebec, Canada
| | - Mengru Yuan
- School of Public Health, University of Montreal, Montreal, Quebec, Canada
| | | | | | - Berta N. Restrepo
- Instituto Colombiano de Medicina Tropical, Universidad CES, Medellín, Colombia
| | - Kate Zinszer
- School of Public Health, University of Montreal, Montreal, Quebec, Canada
- Centre de Recherche en Santé Publique, Montreal, Quebec, Canada
- * E-mail:
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Hayashi K, Fujimoto M, Nishiura H. Quantifying the future risk of dengue under climate change in Japan. Front Public Health 2022; 10:959312. [PMID: 35991044 PMCID: PMC9389175 DOI: 10.3389/fpubh.2022.959312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 07/21/2022] [Indexed: 11/23/2022] Open
Abstract
Background In metropolitan Tokyo in 2014, Japan experienced its first domestic dengue outbreak since 1945. The objective of the present study was to quantitatively assess the future risk of dengue in Japan using climate change scenarios in a high-resolution geospatial environment by building on a solid theory as a baseline in consideration of future adaptation strategies. Methods Using climate change scenarios of the Model for Interdisciplinary Research on Climate version 6 (MIROC6), representative concentration pathway (RCP) 2.6, 4.5, and 8.5, we computed the daily average temperature and embedded this in the effective reproduction number of dengue, R(T), to calculate the extinction probability and interepidemic period across Japan. Results In June and October, the R(T) with daily average temperature T, was <1 as in 2022; however, an elevation in temperature increased the number of days with R(T) >1 during these months under RCP8.5. The time period with a risk of dengue transmission gradually extended to late spring (April–May) and autumn (October–November). Under the RCP8.5 scenario in 2100, the possibility of no dengue-free months was revealed in part of southernmost Okinawa Prefecture, and the epidemic risk extended to the entire part of northernmost Hokkaido Prefecture. Conclusion Each locality in Japan must formulate action plans in response to the presented scenarios. Our geographic analysis can help local governments to develop adaptation policies that include mosquito breeding site elimination, distribution of adulticides and larvicides, and elevated situation awareness to prevent transmission via bites from Aedes vectors.
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Chen Y, Liu T, Yu X, Zeng Q, Cai Z, Wu H, Zhang Q, Xiao J, Ma W, Pei S, Guo P. An ensemble forecast system for tracking dynamics of dengue outbreaks and its validation in China. PLoS Comput Biol 2022; 18:e1010218. [PMID: 35759513 PMCID: PMC9269975 DOI: 10.1371/journal.pcbi.1010218] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 07/08/2022] [Accepted: 05/17/2022] [Indexed: 02/05/2023] Open
Abstract
As a common vector-borne disease, dengue fever remains challenging to predict due to large variations in epidemic size across seasons driven by a number of factors including population susceptibility, mosquito density, meteorological conditions, geographical factors, and human mobility. An ensemble forecast system for dengue fever is first proposed that addresses the difficulty of predicting outbreaks with drastically different scales. The ensemble forecast system based on a susceptible-infected-recovered (SIR) type of compartmental model coupled with a data assimilation method called the ensemble adjusted Kalman filter (EAKF) is constructed to generate real-time forecasts of dengue fever spread dynamics. The model was informed by meteorological and mosquito density information to depict the transmission of dengue virus among human and mosquito populations, and generate predictions. To account for the dramatic variations of outbreak size in different seasons, the effective population size parameter that is sequentially updated to adjust the predicted outbreak scale is introduced into the model. Before optimizing the transmission model, we update the effective population size using the most recent observations and historical records so that the predicted outbreak size is dynamically adjusted. In the retrospective forecast of dengue outbreaks in Guangzhou, China during the 2011-2017 seasons, the proposed forecast model generates accurate projections of peak timing, peak intensity, and total incidence, outperforming a generalized additive model approach. The ensemble forecast system can be operated in real-time and inform control planning to reduce the burden of dengue fever.
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Affiliation(s)
- Yuliang Chen
- Department of Preventive Medicine, Shantou University Medical College, Shantou China
| | - Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Xiaolin Yu
- Department of Preventive Medicine, Shantou University Medical College, Shantou China
| | - Qinghui Zeng
- Department of Preventive Medicine, Shantou University Medical College, Shantou China
| | - Zixi Cai
- Shantou Center for Disease Control and Prevention, Shantou, China
| | - Haisheng Wu
- Department of Preventive Medicine, Shantou University Medical College, Shantou China
| | - Qingying Zhang
- Department of Preventive Medicine, Shantou University Medical College, Shantou China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Wenjun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
- * E-mail: (WM); (SP); (PG)
| | - Sen Pei
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, United States of America
- * E-mail: (WM); (SP); (PG)
| | - Pi Guo
- Department of Preventive Medicine, Shantou University Medical College, Shantou China
- * E-mail: (WM); (SP); (PG)
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Wu Q, Dong S, Li X, Yi B, Hu H, Guo Z, Lu J. Effects of COVID-19 Non-Pharmacological Interventions on Dengue Infection: A Systematic Review and Meta-Analysis. Front Cell Infect Microbiol 2022; 12:892508. [PMID: 35663468 PMCID: PMC9162155 DOI: 10.3389/fcimb.2022.892508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 04/19/2022] [Indexed: 11/30/2022] Open
Abstract
Non-pharmacological interventions (NPIs) implemented during the coronavirus disease 2019 (COVID-19) pandemic have demonstrated significant positive effects on other communicable diseases. Nevertheless, the response for dengue fever has been mixed. To illustrate the real implications of NPIs on dengue transmission and to determine the effective measures for preventing and controlling dengue, we performed a systematic review and meta-analysis of the available global data to summarize the effects comprehensively. We searched Embase, PubMed, and Web of Science in line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines from December 31, 2019, to March 30, 2022, for studies of NPI efficacy on dengue infection. We obtained the annual reported dengue cases from highly dengue-endemic countries in 2015–2021 from the European Centre for Disease Prevention and Control to determine the actual change in dengue cases in 2020 and 2021, respectively. A random-effects estimate of the pooled odds was generated with the Mantel-Haenszel method. Between-study heterogeneity was assessed using the inconsistency index (I2) and subgroup analysis according to country (dengue-endemic or non-endemic) was conducted. This review was registered with PROSPERO (CRD42021291487). A total of 17 articles covering 32 countries or regions were included in the review. Meta-analysis estimated a pooled relative risk of 0.39 (95% CI: 0.28–0.55), and subgroup revealed 0.06 (95% CI: 0.02-0.25) and 0.55 (95% CI: 0.44-0.68) in dengue non-endemic areas and dengue-endemic countries, respectively, in 2020. The majority of highly dengue-endemic countries in Asia and Americas reported 0–100% reductions in dengue cases in 2020 compared to previous years, while some countries (4/20) reported a dramatic increase, resulting in an overall increase of 11%. In contrast, there was an obvious reduction in dengue cases in 2021 in almost all countries (18/20) studied, with an overall 40% reduction rate. The overall effectiveness of NPIs on dengue varied with region and time due to multiple factors, but most countries reported significant reductions. Travel-related interventions demonstrated great effectiveness for reducing imported cases of dengue fever. Internal movement restrictions of constantly varying intensity and range are more likely to mitigate the entire level of dengue transmission by reducing the spread of dengue fever between regions within a country, which is useful for developing a more comprehensive and sustainable strategy for preventing and controlling dengue fever in the future.
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Affiliation(s)
- Qin Wu
- One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-sen University, Guangzhou, China
- National Medical Products Administration (NMPA) Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou, China
| | - Shuwen Dong
- One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-sen University, Guangzhou, China
- National Medical Products Administration (NMPA) Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou, China
| | - Xiaokang Li
- One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-sen University, Guangzhou, China
- National Medical Products Administration (NMPA) Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou, China
| | - Boyang Yi
- One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-sen University, Guangzhou, China
- National Medical Products Administration (NMPA) Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou, China
| | - Huan Hu
- One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-sen University, Guangzhou, China
- National Medical Products Administration (NMPA) Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou, China
| | - Zhongmin Guo
- Sun Yat-Sen College of Medical Science, Sun Yat-sen University, Guangzhou, China
- *Correspondence: Jiahai Lu, ; Zhongmin Guo,
| | - Jiahai Lu
- One Health Center of Excellence for Research and Training, School of Public Health, Sun Yat-sen University, Guangzhou, China
- National Medical Products Administration (NMPA) Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, Guangzhou, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou, China
- Research Institute of Sun Yat-Sen University in Shenzhen, Shenzhen, China
- Hainan Medical University ' One Health' " Research Center, Hainan Medical University, Hainan, China
- *Correspondence: Jiahai Lu, ; Zhongmin Guo,
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Wang J, Jiang L, Xu Y, He W, Zhang C, Bi F, Tan Y, Ning C. Epidemiology of influenza virus reinfection in Guangxi, China: a retrospective analysis of a nine-year influenza surveillance data. Int J Infect Dis 2022; 120:135-141. [PMID: 35477049 DOI: 10.1016/j.ijid.2022.04.045] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 04/07/2022] [Accepted: 04/20/2022] [Indexed: 10/18/2022] Open
Abstract
BACKGROUND Epidemiological characteristics profile of the reinfection of the influenza virus has not been well described. METHODS Included all influenza cases of Guangxi, China from January 2011 to December 2019 recorded in National Notifiable Infectious Disease Reporting Information System (NIDRIS) within 24 hours after diagnosis. RESULTS A total of 53,605.6 person-months and the median time of 8.7 months were observed for reinfection. The median age at the first influenza virus infection was 4.5 (IQR=2.0-7.5) years. The cumulative reinfection incidence was 2% at 6-month, 4% at 12-month, 5% at 24-month, and 7% after 59-month. Living in the rural area (HR=1.37 [95%CI, 1.29-1.45]), age ≤6 years (HR=11.43 [95%CI, 9.47-13.80]) were independent risk factors associated with influenza reinfection. Among 49 patients experiencing twice laboratory tests, 32 patients (65.3%) were with different virus types. The interval between two consecutive laboratory-confirmed episodes of the four groups differed (p=0.148), as the maximum was 72.9 months, and the minimum was 1.2 months. CONCLUSIONS The reinfection of the influenza virus in Guangxi independently and positively associated with the rural area and younger age. The unusually high frequency of reinfection points to a need for further prospective longitudinal studies to better investigate sufficient impact on different subtypes.
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Affiliation(s)
- Jing Wang
- Guangxi Center for Disease Prevention and Control, Nanning, Guangxi, China.
| | - Lina Jiang
- Guangxi Center for Disease Prevention and Control, Nanning, Guangxi, China.
| | - Yunan Xu
- Duke University, Durham, North Carolina, USA.
| | - Weitao He
- Guangxi Center for Disease Prevention and Control, Nanning, Guangxi, China.
| | - Chao Zhang
- Guangxi Center for Disease Prevention and Control, Nanning, Guangxi, China.
| | - Fuyin Bi
- Guangxi Center for Disease Prevention and Control, Nanning, Guangxi, China.
| | - Yi Tan
- Guangxi Center for Disease Prevention and Control, Nanning, Guangxi, China.
| | - Chuanyi Ning
- Guangxi Medical University, Nanning, Guangxi, China.
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Santana LMR, Baquero OS, Maeda AY, Nogueira JS, Chiaravalloti F. Spatio-temporal dynamics of dengue-related deaths and associated factors. Rev Inst Med Trop Sao Paulo 2022; 64:e30. [PMID: 35384961 PMCID: PMC8993154 DOI: 10.1590/s1678-9946202264030] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 02/16/2022] [Indexed: 11/25/2022] Open
Abstract
Since the reintroduction of dengue viruses in 1987, Sao Paulo State (SP), Brazil, has experienced recurrent epidemics in a growing number of municipalities, each time with more cases and deaths. In the present study, we investigated the spatio-temporal dynamics of dengue-related deaths and associated factors in SP. This was an ecological study with spatial and temporal components, based on notified dengue-related deaths in the municipalities of SP between 2007 and 2017. A latent Gaussian Bayesian model with Poisson probability distribution was used to estimate the standardized mortality ratios (SMR) for dengue and relative risks (RR) for the socioeconomic, demographic, healthcare-related, and epidemiological factors considered. Epidemiological factors included the annual information on the number of circulating serotypes. A total of 1,019 dengue-related deaths (0.22 per 100,000 inhabitant-years) between 2007 and 2017 were confirmed in SP by laboratory testing. Mortality increased with age, peaking at 70 years or older (1.41 deaths per 100,000 inhabitant-years). Mortality was highest in 2015, and the highest SMR values were found in the North, Northwest, West, and coastal regions of SP. An increase of one circulating serotype, one standard deviation in the number of years with cases, and one standard deviation in the degree of urbanization were associated with increases of 75, 35, and 45% in the risk of death from dengue, respectively. The risk of death from dengue increased with age, and the distribution of deaths was heterogeneous in space and time. The positive relationship found between the number of dengue serotypes circulating and years with cases at the municipality/micro-region level indicates that this information can be used to identify risk areas, intensify surveillance and control measures, and organize healthcare to better respond to this disease.
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Affiliation(s)
- Lidia Maria Reis Santana
- Secretaria de Estado de Saúde de São Paulo, Centro de Vigilância
Epidemiológica “Professor Alexandre Vranjac”, São Paulo, São Paulo, Brazil
- Universidade Federal de São Paulo, São Paulo, São Paulo,
Brazil
| | - Oswaldo Santos Baquero
- Universidade de São Paulo, Faculdade de Medicina Veterinária e
Zootecnia, São Paulo, São Paulo, Brazil
| | - Adriana Yurika Maeda
- Instituto Adolfo Lutz, Núcleo de Doenças de Transmissão
Vetorial, São Paulo, São Paulo, Brazil
| | - Juliana Silva Nogueira
- Instituto Adolfo Lutz, Núcleo de Doenças de Transmissão
Vetorial, São Paulo, São Paulo, Brazil
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Carabali M, Schmidt AM, Restrepo BN, Kaufman JS. A joint spatial marked point process model for dengue and severe dengue in Medellin, Colombia. Spat Spatiotemporal Epidemiol 2022; 41:100495. [DOI: 10.1016/j.sste.2022.100495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 01/19/2022] [Accepted: 02/28/2022] [Indexed: 11/16/2022]
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Ferreira HDS, Nóbrega RS, Brito PVDS, Farias JP, Amorim JH, Moreira EBM, Mendez ÉC, Luiz WB. Impacts of El Niño Southern Oscillation on the dengue transmission dynamics in the Metropolitan Region of Recife, Brazil. Rev Soc Bras Med Trop 2022; 55:e0671. [PMID: 35674563 PMCID: PMC9176733 DOI: 10.1590/0037-8682-0671-2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Accepted: 04/13/2022] [Indexed: 11/28/2022] Open
Abstract
Background: This research addresses two questions: (1) how El Niño Southern Oscillation (ENSO) affects climate variability and how it influences dengue transmission in the Metropolitan Region of Recife (MRR), and (2) whether the epidemic in MRR municipalities has any connection and synchronicity. Methods: Wavelet analysis and cross-correlation were applied to characterize seasonality, multiyear cycles, and relative delays between the series. This study was developed into two distinct periods. Initially, we performed periodic dengue incidence and intercity epidemic synchronism analyses from 2001 to 2017. We then defined the period from 2001 to 2016 to analyze the periodicity of climatic variables and their coherence with dengue incidence. Results: Our results showed systematic cycles of 3-4 years with a recent shortening trend of 2-3 years. Climatic variability, such as positive anomalous temperatures and reduced rainfall due to changes in sea surface temperature (SST), is partially linked to the changing epidemiology of the disease, as this condition provides suitable environments for the Aedes aegypti lifecycle. Conclusion: ENSO may have influenced the dengue temporal patterns in the MRR, transiently reducing its main way of multiyear variability (3-4 years) to 2-3 years. Furthermore, when the epidemic coincided with El Niño years, it spread regionally and was highly synchronized.
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Affiliation(s)
| | - Ranyére Silva Nóbrega
- Universidade Federal de Pernambuco, Brasil; Universidade Federal de Campina Grande, Brasil
| | | | | | - Jaime Henrique Amorim
- Universidade Federal do Oeste da Bahia, Brasil; Universidade Estadual de Santa Cruz, Brasil
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Katzelnick LC, Escoto AC, Huang AT, Garcia-Carreras B, Chowdhury N, Berry IM, Chavez C, Buchy P, Duong V, Dussart P, Gromowski G, Macareo L, Thaisomboonsuk B, Fernandez S, Smith DJ, Jarman R, Whitehead SS, Salje H, Cummings DA. Antigenic evolution of dengue viruses over 20 years. Science 2021; 374:999-1004. [PMID: 34793238 PMCID: PMC8693836 DOI: 10.1126/science.abk0058] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Infection with one of dengue viruses 1 to 4 (DENV1-4) induces protective antibodies against homotypic infection. However, a notable feature of dengue viruses is the ability to use preexisting heterotypic antibodies to infect Fcγ receptor–bearing immune cells, leading to higher viral load and immunopathological events that augment disease. We tracked the antigenic dynamics of each DENV serotype by using 1944 sequenced isolates from Bangkok, Thailand, between 1994 and 2014 (348 strains), in comparison with regional and global DENV antigenic diversity (64 strains). Over the course of 20 years, the Thailand DENV serotypes gradually evolved away from one another. However, for brief periods, the serotypes increased in similarity, with corresponding changes in epidemic magnitude. Antigenic evolution within a genotype involved a trade-off between two types of antigenic change (within-serotype and between-serotype), whereas genotype replacement resulted in antigenic change away from all serotypes. These findings provide insights into theorized dynamics in antigenic evolution.
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Affiliation(s)
- Leah C. Katzelnick
- Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, FL, 32611, United States
- Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, United States
| | - Ana Coello Escoto
- Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, FL, 32611, United States
- Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, United States
| | - Angkana T. Huang
- Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, FL, 32611, United States
- Department of Virology, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Bernardo Garcia-Carreras
- Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, FL, 32611, United States
| | - Nayeem Chowdhury
- Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, FL, 32611, United States
| | - Irina Maljkovic Berry
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MD, 20910, United States
| | - Chris Chavez
- Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, FL, 32611, United States
| | - Philippe Buchy
- GlaxoSmithKline (GSK) Vaccines, 637421 Singapore, Singapore
| | - Veasna Duong
- Institut Pasteur in Cambodia, Réseau International des Instituts Pasteur, Phnom Penh 12201, Cambodia
| | - Philippe Dussart
- Institut Pasteur in Cambodia, Réseau International des Instituts Pasteur, Phnom Penh 12201, Cambodia
| | - Gregory Gromowski
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MD, 20910, United States
| | - Louis Macareo
- Department of Virology, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Butsaya Thaisomboonsuk
- Department of Virology, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Stefan Fernandez
- Department of Virology, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Derek J. Smith
- Department of Zoology, University of Cambridge, Cambridge, CB2 3EJ, United Kingdom
| | - Richard Jarman
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MD, 20910, United States
| | - Stephen S. Whitehead
- Laboratory of Viral Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, United States
| | - Henrik Salje
- Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, FL, 32611, United States
- Department of Genetics, University of Cambridge, Cambridge, CB2 3EJ, United Kingdom
| | - Derek A.T. Cummings
- Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, FL, 32611, United States
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Simon LM, Rangel TF. Are Temperature Suitability and Socioeconomic Factors Reliable Predictors of Dengue Transmission in Brazil? FRONTIERS IN TROPICAL DISEASES 2021. [DOI: 10.3389/fitd.2021.758393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Dengue is an ongoing problem, especially in tropical countries. Like many other vector-borne diseases, the spread of dengue is driven by a myriad of climate and socioeconomic factors. Within developing countries, heterogeneities on socioeconomic factors are expected to create variable conditions for dengue transmission. However, the relative role of socioeconomic characteristics and their association with climate in determining dengue prevalence are poorly understood. Here we assembled essential socioeconomic factors over 5570 municipalities across Brazil and assessed their effect on dengue prevalence jointly with a previously predicted temperature suitability for transmission. Using a simultaneous autoregressive approach (SAR), we showed that the variability in the prevalence of dengue cases across Brazil is primarily explained by the combined effect of climate and socioeconomic factors. At some dengue seasons, the effect of temperature on transmission potential showed to be a more significant proxy of dengue cases. Still, socioeconomic factors explained the later increase in dengue prevalence over Brazil. In a heterogeneous country such as Brazil, recognizing the transmission drivers by vectors is a fundamental issue in effectively predicting and combating tropical diseases like dengue. Ultimately, it indicates that not considering socioeconomic factors in disease transmission predictions might compromise efficient surveillance strategies. Our study shows that sanitation, urbanization, and GDP are regional indicators that should be considered along with temperature suitability on dengue transmission, setting effective directions to mosquito-borne disease control.
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Katzelnick LC, Zambrana JV, Elizondo D, Collado D, Garcia N, Arguello S, Mercado JC, Miranda T, Ampie O, Mercado BL, Narvaez C, Gresh L, Binder RA, Ojeda S, Sanchez N, Plazaola M, Latta K, Schiller A, Coloma J, Carrillo FB, Narvaez F, Halloran ME, Gordon A, Kuan G, Balmaseda A, Harris E. Dengue and Zika virus infections in children elicit cross-reactive protective and enhancing antibodies that persist long term. Sci Transl Med 2021; 13:eabg9478. [PMID: 34613812 DOI: 10.1126/scitranslmed.abg9478] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Leah C Katzelnick
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, CA 94720-3370, USA.,Viral Epidemiology and Immunity Unit, Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892-3203, USA
| | | | | | | | - Nadezna Garcia
- Sustainable Sciences Institute, Managua 14007, Nicaragua
| | - Sonia Arguello
- Sustainable Sciences Institute, Managua 14007, Nicaragua
| | - Juan Carlos Mercado
- Sustainable Sciences Institute, Managua 14007, Nicaragua.,Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua 16064, Nicaragua
| | | | | | | | - César Narvaez
- Sustainable Sciences Institute, Managua 14007, Nicaragua
| | - Lionel Gresh
- Sustainable Sciences Institute, Managua 14007, Nicaragua
| | - Raquel A Binder
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, CA 94720-3370, USA.,Sustainable Sciences Institute, Managua 14007, Nicaragua
| | - Sergio Ojeda
- Sustainable Sciences Institute, Managua 14007, Nicaragua
| | - Nery Sanchez
- Sustainable Sciences Institute, Managua 14007, Nicaragua
| | | | - Krista Latta
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109-2029, USA
| | - Amy Schiller
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109-2029, USA
| | - Josefina Coloma
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, CA 94720-3370, USA
| | - Fausto Bustos Carrillo
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, CA 94720-3370, USA
| | | | - M Elizabeth Halloran
- Department of Biostatistics, University of Washington, Seattle, WA 98195-1617, USA.,Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA
| | - Aubree Gordon
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109-2029, USA
| | - Guillermina Kuan
- Sustainable Sciences Institute, Managua 14007, Nicaragua.,Centro de Salud Sócrates Flores Vivas, Ministry of Health, Managua 12014, Nicaragua
| | - Angel Balmaseda
- Sustainable Sciences Institute, Managua 14007, Nicaragua.,Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua 16064, Nicaragua
| | - Eva Harris
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, CA 94720-3370, USA
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22
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Lim JT, Dickens BS, Tan KW, Koo JR, Seah A, Ho SH, Ong J, Rajarethinam J, Soh S, Cook AR, Ng LC. Hyperendemicity associated with increased dengue burden. J R Soc Interface 2021; 18:20210565. [PMID: 34520691 PMCID: PMC8440027 DOI: 10.1098/rsif.2021.0565] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Over 105 million dengue infections are estimated to occur annually. Understanding the disease dynamics of dengue is often difficult due to multiple strains circulating within a population. Interactions between dengue serotype dynamics may result in complex cross-immunity dynamics at the population level and create difficulties in terms of formulating intervention strategies for the disease. In this study, a nationally representative 16-year time series with over 43 000 serotyped dengue infections was used to infer the long-run effects of between and within strain interactions and their impacts on past outbreaks. We used a novel identification strategy incorporating sign-identified Bayesian vector autoregressions, using structural impulse responses, historical decompositions and counterfactual analysis to conduct inference on dengue dynamics post-estimation. We found that on the population level: (i) across-serotype interactions on the population level were highly persistent, with a one time increase in any other serotype associated with long run decreases in the serotype of interest (range: 0.5–2.5 years) and (ii) over 38.7% of dengue cases of any serotype were associated with across-serotype interactions. The findings in this paper will substantially impact public health policy interventions with respect to dengue.
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Affiliation(s)
- Jue Tao Lim
- Environmental Health Institute, National Environmental Agency, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Borame Sue Dickens
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Ken Wei Tan
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Joel Ruihan Koo
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Annabel Seah
- Environmental Health Institute, National Environmental Agency, Singapore
| | - Soon Hoe Ho
- Environmental Health Institute, National Environmental Agency, Singapore
| | - Janet Ong
- Environmental Health Institute, National Environmental Agency, Singapore
| | | | - Stacy Soh
- Environmental Health Institute, National Environmental Agency, Singapore
| | - Alex R Cook
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Lee Ching Ng
- Environmental Health Institute, National Environmental Agency, Singapore.,School of Biological Sciences, Nanyang Technological University, Singapore
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23
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Cavany SM, España G, Vazquez-Prokopec GM, Scott TW, Perkins TA. Pandemic-associated mobility restrictions could cause increases in dengue virus transmission. PLoS Negl Trop Dis 2021; 15:e0009603. [PMID: 34370734 PMCID: PMC8375978 DOI: 10.1371/journal.pntd.0009603] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 08/19/2021] [Accepted: 06/28/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The COVID-19 pandemic has induced unprecedented reductions in human mobility and social contacts throughout the world. Because dengue virus (DENV) transmission is strongly driven by human mobility, behavioral changes associated with the pandemic have been hypothesized to impact dengue incidence. By discouraging human contact, COVID-19 control measures have also disrupted dengue vector control interventions, the most effective of which require entry into homes. We sought to investigate how and why dengue incidence could differ under a lockdown scenario with a proportion of the population sheltered at home. METHODOLOGY & PRINCIPAL FINDINGS We used an agent-based model with a realistic treatment of human mobility and vector control. We found that a lockdown in which 70% of the population sheltered at home and which occurred in a season when a new serotype invaded could lead to a small average increase in cumulative DENV infections of up to 10%, depending on the time of year lockdown occurred. Lockdown had a more pronounced effect on the spatial distribution of DENV infections, with higher incidence under lockdown in regions with higher mosquito abundance. Transmission was also more focused in homes following lockdown. The proportion of people infected in their own home rose from 54% under normal conditions to 66% under lockdown, and the household secondary attack rate rose from 0.109 to 0.128, a 17% increase. When we considered that lockdown measures could disrupt regular, city-wide vector control campaigns, the increase in incidence was more pronounced than with lockdown alone, especially if lockdown occurred at the optimal time for vector control. CONCLUSIONS & SIGNIFICANCE Our results indicate that an unintended outcome of lockdown measures may be to adversely alter the epidemiology of dengue. This observation has important implications for an improved understanding of dengue epidemiology and effective application of dengue vector control. When coordinating public health responses during a syndemic, it is important to monitor multiple infections and understand that an intervention against one disease may exacerbate another.
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Affiliation(s)
- Sean M. Cavany
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Guido España
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America
| | | | - Thomas W. Scott
- Department of Entomology and Nematology, University of California, Davis, Davis, California, United States of America
| | - T Alex Perkins
- Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, United States of America
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24
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Gjini E, Madec S. The ratio of single to co-colonization is key to complexity in interacting systems with multiple strains. Ecol Evol 2021; 11:8456-8474. [PMID: 34257910 PMCID: PMC8258234 DOI: 10.1002/ece3.7259] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 12/16/2020] [Accepted: 01/12/2021] [Indexed: 11/06/2022] Open
Abstract
The high number and diversity of microbial strains circulating in host populations have motivated extensive research on the mechanisms that maintain biodiversity. However, much of this work focuses on strain-specific and cross-immunity interactions. Another less explored mode of pairwise interaction is via altered susceptibilities to co-colonization in hosts already colonized by one strain. Diversity in such interaction coefficients enables strains to create dynamically their niches for growth and persistence, and "engineer" their common environment. How such a network of interactions with others mediates collective coexistence remains puzzling analytically and computationally difficult to simulate. Furthermore, the gradients modulating stability-complexity regimes in such multi-player endemic systems remain poorly understood. In a recent study (Madec & Gjini, Bulletin of Mathematical Biology, 82), we obtained an analytic representation for N-type coexistence in an SIS epidemiological model with co-colonization. We mapped multi-strain dynamics to a replicator equation using timescale separation. Here, we examine what drives coexistence regimes in such co-colonization system. We find the ratio of single to co-colonization, µ, critically determines the type of equilibrium and number of coexisting strains, and encodes a trade-off between overall transmission intensity R 0 and mean interaction coefficient in strain space, k. Preserving a given coexistence regime, under fixed trait variation, requires balancing between higher mean competition in favorable environments, and higher cooperation in harsher environments, and is consistent with the stress gradient hypothesis. Multi-strain coexistence tends to steady-state attractors for small µ, whereas as µ increases, dynamics tend to more complex attractors. Following strain frequencies, evolutionary dynamics in the system also display contrasting patterns with µ, interpolating between multi-stable and fluctuating selection for cooperation and mean invasion fitness, in the two extremes. This co-colonization framework could be applied more generally, to study invariant principles in collective coexistence, and to quantify how critical shifts in community dynamics get potentiated by mean-field and environmental gradients.
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Affiliation(s)
- Erida Gjini
- Instituto Gulbenkian de CiênciaOeirasPortugal
- Center for Computational and Stochastic MathematicsInstituto Superior TécnicoUniversity of LisbonLisbonPortugal
| | - Sten Madec
- Institut Denis PoissonUniversity of ToursToursFrance
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25
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Wu SL, Bennett JB, Sánchez C. HM, Dolgert AJ, León TM, Marshall JM. MGDrivE 2: A simulation framework for gene drive systems incorporating seasonality and epidemiological dynamics. PLoS Comput Biol 2021; 17:e1009030. [PMID: 34019537 PMCID: PMC8186770 DOI: 10.1371/journal.pcbi.1009030] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 06/08/2021] [Accepted: 05/02/2021] [Indexed: 12/30/2022] Open
Abstract
Interest in gene drive technology has continued to grow as promising new drive systems have been developed in the lab and discussions are moving towards implementing field trials. The prospect of field trials requires models that incorporate a significant degree of ecological detail, including parameters that change over time in response to environmental data such as temperature and rainfall, leading to seasonal patterns in mosquito population density. Epidemiological outcomes are also of growing importance, as: i) the suitability of a gene drive construct for release will depend on its expected impact on disease transmission, and ii) initial field trials are expected to have a measured entomological outcome and a modeled epidemiological outcome. We present MGDrivE 2 (Mosquito Gene Drive Explorer 2): a significant development from the MGDrivE 1 simulation framework that investigates the population dynamics of a variety of gene drive architectures and their spread through spatially-explicit mosquito populations. Key strengths and fundamental improvements of the MGDrivE 2 framework are: i) the ability of parameters to vary with time and induce seasonal population dynamics, ii) an epidemiological module accommodating reciprocal pathogen transmission between humans and mosquitoes, and iii) an implementation framework based on stochastic Petri nets that enables efficient model formulation and flexible implementation. Example MGDrivE 2 simulations are presented to demonstrate the application of the framework to a CRISPR-based split gene drive system intended to drive a disease-refractory gene into a population in a confinable and reversible manner, incorporating time-varying temperature and rainfall data. The simulations also evaluate impact on human disease incidence and prevalence. Further documentation and use examples are provided in vignettes at the project’s CRAN repository. MGDrivE 2 is freely available as an open-source R package on CRAN (https://CRAN.R-project.org/package=MGDrivE2). We intend the package to provide a flexible tool capable of modeling gene drive constructs as they move closer to field application and to infer their expected impact on disease transmission. Malaria, dengue and other mosquito-borne diseases continue to pose a major global health burden through much of the world. Currently available tools, such as insecticides and antimalarial drugs, are not expected to be sufficient to eliminate these diseases from highly-endemic areas, hence there is interest in novel strategies including genetics-based approaches. In recent years, the advent of CRISPR-based gene-editing has greatly expanded the range of genetic control tools available, and MGDrivE 1 (Mosquito Gene Drive Explorer 1) was proposed to simulate the dynamics of these systems through spatially-structured mosquito populations. As the technology has advanced and potential field trials are being discussed, models are now needed that incorporate additional details, such as life history parameters that respond to daily and seasonal environmental fluctuations, and transmission of pathogens between mosquito and vertebrate hosts. Here, we present MGDrivE 2, a gene drive simulation framework that significantly improves upon MGDrivE 1 by addressing these modeling needs. MGDrivE 2 has also been reformulated as a stochastic Petri net, enabling model specification to be decoupled from simulation, making it easier to adapt the model for application to other insect and mammalian species.
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Affiliation(s)
- Sean L. Wu
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, California, United States of America
- * E-mail: (SLW); (JMM)
| | - Jared B. Bennett
- Biophysics Graduate Group, Division of Biological Sciences, College of Letters and Science, University of California, Berkeley, California, United States of America
| | - Héctor M. Sánchez C.
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, California, United States of America
| | - Andrew J. Dolgert
- Institute for Health Metrics and Evaluation, Seattle, Washington, United States of America
| | - Tomás M. León
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, California, United States of America
| | - John M. Marshall
- Divisions of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, California, United States of America
- Innovative Genomics Institute, University of California, Berkeley, California, United States of America
- * E-mail: (SLW); (JMM)
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26
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Humphreys JM, Young KI, Cohnstaedt LW, Hanley KA, Peters DPC. Vector Surveillance, Host Species Richness, and Demographic Factors as West Nile Disease Risk Indicators. Viruses 2021; 13:934. [PMID: 34070039 PMCID: PMC8267946 DOI: 10.3390/v13050934] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 05/07/2021] [Accepted: 05/09/2021] [Indexed: 02/06/2023] Open
Abstract
West Nile virus (WNV) is the most common arthropod-borne virus (arbovirus) in the United States (US) and is the leading cause of viral encephalitis in the country. The virus has affected tens of thousands of US persons total since its 1999 North America introduction, with thousands of new infections reported annually. Approximately 1% of humans infected with WNV acquire neuroinvasive West Nile Disease (WND) with severe encephalitis and risk of death. Research describing WNV ecology is needed to improve public health surveillance, monitoring, and risk assessment. We applied Bayesian joint-spatiotemporal modeling to assess the association of vector surveillance data, host species richness, and a variety of other environmental and socioeconomic disease risk factors with neuroinvasive WND throughout the conterminous US. Our research revealed that an aging human population was the strongest disease indicator, but climatic and vector-host biotic interactions were also significant in determining risk of neuroinvasive WND. Our analysis also identified a geographic region of disproportionately high neuroinvasive WND disease risk that parallels the Continental Divide, and extends southward from the US-Canada border in the states of Montana, North Dakota, and Wisconsin to the US-Mexico border in western Texas. Our results aid in unraveling complex WNV ecology and can be applied to prioritize disease surveillance locations and risk assessment.
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Affiliation(s)
- John M. Humphreys
- Pest Management Research Unit, Agricultural Research Service, US Department of Agriculture, Sidney, MT 59270, USA
| | - Katherine I. Young
- Jornada Experimental Range Unit, Agricultural Research Service, US Department of Agriculture, Las Cruces, NM 88003, USA; (K.I.Y.); (D.P.C.P.)
- Arthropod-Borne Animal Disease Research Unit, Agricultural Research Service, US Department of Agriculture, Manhattan, KS 66502, USA;
| | - Lee W. Cohnstaedt
- Department of Biology, New Mexico State University, Las Cruces, NM 88003, USA;
| | - Kathryn A. Hanley
- Arthropod-Borne Animal Disease Research Unit, Agricultural Research Service, US Department of Agriculture, Manhattan, KS 66502, USA;
| | - Debra P. C. Peters
- Jornada Experimental Range Unit, Agricultural Research Service, US Department of Agriculture, Las Cruces, NM 88003, USA; (K.I.Y.); (D.P.C.P.)
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27
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Lying in wait: the resurgence of dengue virus after the Zika epidemic in Brazil. Nat Commun 2021; 12:2619. [PMID: 33976183 PMCID: PMC8113494 DOI: 10.1038/s41467-021-22921-7] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 04/07/2021] [Indexed: 12/19/2022] Open
Abstract
After the Zika virus (ZIKV) epidemic in the Americas in 2016, both Zika and dengue incidence declined to record lows in many countries in 2017–2018, but in 2019 dengue resurged in Brazil, causing ~2.1 million cases. In this study we use epidemiological, climatological and genomic data to investigate dengue dynamics in recent years in Brazil. First, we estimate dengue virus force of infection (FOI) and model mosquito-borne transmission suitability since the early 2000s. Our estimates reveal that DENV transmission was low in 2017–2018, despite conditions being suitable for viral spread. Our study also shows a marked decline in dengue susceptibility between 2002 and 2019, which could explain the synchronous decline of dengue in the country, partially as a result of protective immunity from prior ZIKV and/or DENV infections. Furthermore, we performed phylogeographic analyses using 69 newly sequenced genomes of dengue virus serotype 1 and 2 from Brazil, and found that the outbreaks in 2018–2019 were caused by local DENV lineages that persisted for 5–10 years, circulating cryptically before and after the Zika epidemic. We hypothesize that DENV lineages may circulate at low transmission levels for many years, until local conditions are suitable for higher transmission, when they cause major outbreaks. Zika and dengue incidence in the Americas declined in 2017–2018, but dengue resurged in 2019 in Brazil. This study uses epidemiological, climatological and genomic data to show that the decline of dengue may be explained by protective immunity from pre-exposure to ZIKV and/or DENV in prior years.
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28
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Alexander LW, Ben-Shachar R, Katzelnick LC, Kuan G, Balmaseda A, Harris E, Boots M. Boosting can explain patterns of fluctuations of ratios of inapparent to symptomatic dengue virus infections. Proc Natl Acad Sci U S A 2021; 118:e2013941118. [PMID: 33811138 PMCID: PMC8040803 DOI: 10.1073/pnas.2013941118] [Citation(s) in RCA: 3] [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] [Indexed: 11/18/2022] Open
Abstract
Dengue is the most prevalent arboviral disease worldwide, and the four dengue virus (DENV) serotypes circulate endemically in many tropical and subtropical regions. Numerous studies have shown that the majority of DENV infections are inapparent, and that the ratio of inapparent to symptomatic infections (I/S) fluctuates substantially year-to-year. For example, in the ongoing Pediatric Dengue Cohort Study (PDCS) in Nicaragua, which was established in 2004, the I/S ratio has varied from 16.5:1 in 2006-2007 to 1.2:1 in 2009-2010. However, the mechanisms explaining these large fluctuations are not well understood. We hypothesized that in dengue-endemic areas, frequent boosting (i.e., exposures to DENV that do not lead to extensive viremia and result in a less than fourfold rise in antibody titers) of the immune response can be protective against symptomatic disease, and this can explain fluctuating I/S ratios. We formulate mechanistic epidemiologic models to examine the epidemiologic effects of protective homologous and heterologous boosting of the antibody response in preventing subsequent symptomatic DENV infection. We show that models that include frequent boosts that protect against symptomatic disease can recover the fluctuations in the I/S ratio that we observe, whereas a classic model without boosting cannot. Furthermore, we show that a boosting model can recover the inverse relationship between the number of symptomatic cases and the I/S ratio observed in the PDCS. These results highlight the importance of robust dengue control efforts, as intermediate dengue control may have the potential to decrease the protective effects of boosting.
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Affiliation(s)
| | - Rotem Ben-Shachar
- Integrative Biology, University of California, Berkeley, CA 94720
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, CA 94720
| | - Leah C Katzelnick
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, CA 94720
| | - Guillermina Kuan
- Centro de Salud Sócrates Flores Vivas, Ministry of Health, 12014 Managua, Nicaragua
- Sustainable Sciences Institute, 14007 Managua, Nicaragua
| | - Angel Balmaseda
- Sustainable Sciences Institute, 14007 Managua, Nicaragua
- Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, 16064 Managua, Nicaragua
| | - Eva Harris
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, CA 94720
| | - Mike Boots
- Integrative Biology, University of California, Berkeley, CA 94720;
- Biosciences, University of Exeter, Penryn TR10 9EZ, United Kingdom
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29
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Quandelacy TM, Cummings DAT, Jiang CQ, Yang B, Kwok KO, Dai B, Shen R, Read JM, Zhu H, Guan Y, Riley S, Lessler J. Using serological measures to estimate influenza incidence in the presence of secular trends in exposure and immuno-modulation of antibody response. Influenza Other Respir Viruses 2021; 15:235-244. [PMID: 33108707 PMCID: PMC7902255 DOI: 10.1111/irv.12807] [Citation(s) in RCA: 3] [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: 06/08/2020] [Revised: 08/24/2020] [Accepted: 08/30/2020] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Influenza infection is often measured by a fourfold antibody titer increase over an influenza season (ie seroconversion). However, this approach may fail when influenza seasons are less distinct as it does not account for transient effects from recent infections. Here, we present a method to determine seroconversion for non-paired sera, adjusting for changes in individuals' antibody titers to influenza due to the transient impact of recent exposures, varied sampling times, and laboratory processes. METHODS We applied our method using data for five H3N2 strains collected from 942 individuals, aged 2-90 years, during the first two study visits of the Fluscape cohort study (2009-2012) in Guangzhou, China. RESULTS After adjustment, apparent seroconversion rates for non-circulating strains decreased while we observed a 20% increase in seroconversion rates to recently circulating strains. When examining seroconversion to the most recently circulating strain (A/Brisbane/20/2007) in our study, participants aged under 18, and over 64 had the highest seroconversion rates compared to other age groups. CONCLUSIONS Our results highlight the need for improved methods when using antibody titers as an endpoint in settings where there is no clear influenza "off" season. Methods, like those presented here, that use titers from circulating and non-circulating strains may be key.
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Affiliation(s)
- Talia M. Quandelacy
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
- Present address:
Centers for Disease Control and PreventionSan JuanPuerto Rico
| | - Derek A. T. Cummings
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
- Department of BiologyUniversity of FloridaGainesvilleFLUSA
| | | | - Bingyi Yang
- Department of BiologyUniversity of FloridaGainesvilleFLUSA
| | - Kin On Kwok
- The Jockey Club School of Public Health and Primary CareThe Chinese University of Hong KongHong Kong Special Administrative RegionChina
- Stanley Ho Centre for Emerging Infectious DiseasesHong Kong Special Administrative RegionThe Chinese University of Hong KongShatin, Hong KongChina
- Shenzhen Research InstituteThe Chinese University of Hong KongShenzhenChina
| | - Byran Dai
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
| | | | - Jonathan M. Read
- Center for Health Informatics Computing and StatisticsLancaster Medical SchoolLancaster UniversityLancasterUK
- Institute of Infection and Global HealthUniversity of LiverpoolLiverpoolUK
| | - Huachen Zhu
- State Key Laboratory of Emerging Infectious DiseasesSchool of Public HealthThe University of Hong KongHong KongChina
- Shantou University Medical CollegeShantouChina
| | - Yi Guan
- Shantou University Medical CollegeShantouChina
- School of Public HealthImperial College LondonLondonUK
| | - Steven Riley
- School of Public HealthImperial College LondonLondonUK
| | - Justin Lessler
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
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30
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Carabali M, Jaramillo-Ramirez GI, Rivera VA, Mina Possu NJ, Restrepo BN, Zinszer K. Assessing the reporting of Dengue, Chikungunya and Zika to the National Surveillance System in Colombia from 2014-2017: A Capture-recapture analysis accounting for misclassification of arboviral diagnostics. PLoS Negl Trop Dis 2021; 15:e0009014. [PMID: 33539393 PMCID: PMC7888590 DOI: 10.1371/journal.pntd.0009014] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 02/17/2021] [Accepted: 11/25/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Chikungunya, dengue, and Zika are three different arboviruses which have similar symptoms and are a major public health issue in Colombia. Despite the mandatory reporting of these arboviruses to the National Surveillance System in Colombia (SIVIGILA), it has been reported that the system captures less than 10% of diagnosed cases in some cities. METHODOLOGY/PRINCIPAL FINDINGS To assess the scope and degree of arboviruses reporting in Colombia between 2014-2017, we conducted an observational study of surveillance data using the capture-recapture approach in three Colombian cities. Using healthcare facility registries (capture data) and surveillance-notified cases (recapture data), we estimated the degree of reporting by clinical diagnosis. We fit robust Poisson regressions to identify predictors of reporting and estimated the predicted probability of reporting by disease and year. To account for the potential misclassification of the clinical diagnosis, we used the simulation extrapolation for misclassification (MC-SIMEX) method. A total of 266,549 registries were examined. Overall arboviruses' reporting ranged from 5.3% to 14.7% and varied in magnitude according to age and year of diagnosis. Dengue was the most notified disease (21-70%) followed by Zika (6-45%). The highest reporting rate was seen in 2016, an epidemic year. The MC-SIMEX corrected rates indicated underestimation of the reporting due to the potential misclassification bias. CONCLUSIONS These findings reflect challenges on arboviruses' reporting, and therefore, potential challenges on the estimation of arboviral burden in Colombia and other endemic settings with similar surveillance systems.
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Affiliation(s)
- Mabel Carabali
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
- * E-mail:
| | | | | | | | - Berta N. Restrepo
- Instituto Colombiano de Medicina Tropical- Universidad CES, Medellín, Colombia
| | - Kate Zinszer
- School of Public Health, University of Montreal, Montreal, Quebec, Canada
- Centre de Recherche en Santé Publique, Montreal, Quebec, Canada
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Xue L, Ren X, Magpantay F, Sun W, Zhu H. Optimal Control of Mitigation Strategies for Dengue Virus Transmission. Bull Math Biol 2021; 83:8. [PMID: 33404917 DOI: 10.1007/s11538-020-00839-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Accepted: 11/21/2020] [Indexed: 11/30/2022]
Abstract
Dengue virus is transmitted by Aedes mosquitoes, posing threat to people's health and leading to great economic cost in many tropical and subtropical regions. We develop an ordinary differential equation model taking into account multiple strains of dengue virus. Using the model, we assess the effectiveness of human vaccination considering its waning and failure. We derive the lower bound and upper bound for the final size of the epidemic. Sensitivity analysis quantifies the impact of parameters on the basic reproduction number. Different scenarios of vaccinating humans show that it is better to vaccinate humans at early stages. We find that the cumulative number of infected humans is small when the vaccination rate is high or the waning rate is low for previously infected humans. We analyze the necessary conditions for implementing optimal control and derive the corresponding optimal solutions for mitigation dengue virus transmission by applying Pontryagin's Maximum Principle. Our findings may provide guidance for the public health authorities to implement human vaccination and other mitigation strategies.
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Affiliation(s)
- Ling Xue
- College of Automation, Harbin Engineering University, Harbin, 150001, China.,College of Mathematical Sciences, Harbin Engineering University, Harbin, 150001, China
| | - Xue Ren
- College of Automation, Harbin Engineering University, Harbin, 150001, China.,College of Mathematical Sciences, Harbin Engineering University, Harbin, 150001, China
| | - Felicia Magpantay
- Department of Mathematics and Statistics, Queen's University, Kingston, K7L 3N6, Canada
| | - Wei Sun
- College of Mathematical Sciences, Harbin Engineering University, Harbin, 150001, China.
| | - Huaiping Zhu
- Department of Mathematics and Statistics, York University, Toronto, M3J 1P3, Canada
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Virtual Screening for Potential Inhibitors of Human Hexokinase II for the Development of Anti-Dengue Therapeutics. BIOTECH 2020; 10:biotech10010001. [PMID: 35822774 PMCID: PMC9245486 DOI: 10.3390/biotech10010001] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 12/11/2020] [Accepted: 12/24/2020] [Indexed: 11/17/2022] Open
Abstract
Dengue fever, which is a disease caused by the dengue virus (DENV), is a major unsolved issue in many tropical and sub-tropical regions of the world. The absence of treatment that effectively prevent further viral propagation inside the human’s body resulted in a high number of deaths globally each year. Thus, novel anti-dengue therapies are required for effective treatment. Human hexokinase II (HKII), which is the first enzyme in the glycolytic pathway, is an important drug target due to its significant impact on viral replication and survival in host cells. In this study, 23.1 million compounds were computationally-screened against HKII using the Ultrafast Shape Recognition with a CREDO Atom Types (USRCAT) algorithm. In total, 300 compounds with the highest similarity scores relative to three reference molecules, known as Alpha-D-glucose (GLC), Beta-D-glucose-6-phosphate (BG6), and 2-deoxyglucose (2DG), were aligned. Of these 300 compounds, 165 were chosen for further structure-based screening, based on their similarity scores, ADME analysis, the Lipinski’s Rule of Five, and virtual toxicity test results. The selected analogues were subsequently docked against each domain of the HKII structure (PDB ID: 2NZT) using AutoDock Vina programme. The three top-ranked compounds for each query were then selected from the docking results based on their binding energy, the number of hydrogen bonds formed, and the specific catalytic residues. The best docking results for each analogue were observed for the C-terminus of Chain B. The top-ranked analogues of GLC, compound 10, compound 26, and compound 58, showed predicted binding energies of −7.2, −7.0, and −6.10 kcal/mol and 7, 5, and 2 hydrogen bonds, respectively. The analogues of BG6, compound 30, compound 36, and compound 38, showed predicted binding energies of −7.8, −7.4, and −7.0 kcal/mol and 11, 9, and 5 hydrogen bonds, while the top three analogues of 2DG, known as compound 1, compound 4, and compound 31, showed predicted binding energies of −6.8, −6.3, and −6.3 kcal/mol and 4, 3, and 1 hydrogen bonds, sequentially. The highest-ranked compounds in the docking analysis were then selected for molecular dynamics simulation, where compound 10, compound 30, and compound 1, which are the analogues of GLC, BG6, and 2DG, have shown strong protein-ligand stability with an RMSD value of ±5.0 A° with a 5 H bond, ±4.0 A° with an 8 H bond, and ±0.5 A° with a 2 H bond, respectively, compared to the reference molecules throughout the 20 ns simulation time. Therefore, by using the computational studies, we proposed novel compounds, which may act as potential drugs against DENV by inhibiting HKII’s activity.
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Leach CB, Hoeting JA, Pepin KM, Eiras AE, Hooten MB, Webb CT. Linking mosquito surveillance to dengue fever through Bayesian mechanistic modeling. PLoS Negl Trop Dis 2020; 14:e0008868. [PMID: 33226987 PMCID: PMC7721181 DOI: 10.1371/journal.pntd.0008868] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 12/07/2020] [Accepted: 10/08/2020] [Indexed: 12/12/2022] Open
Abstract
Our ability to effectively prevent the transmission of the dengue virus through targeted control of its vector, Aedes aegypti, depends critically on our understanding of the link between mosquito abundance and human disease risk. Mosquito and clinical surveillance data are widely collected, but linking them requires a modeling framework that accounts for the complex non-linear mechanisms involved in transmission. Most critical are the bottleneck in transmission imposed by mosquito lifespan relative to the virus' extrinsic incubation period, and the dynamics of human immunity. We developed a differential equation model of dengue transmission and embedded it in a Bayesian hierarchical framework that allowed us to estimate latent time series of mosquito demographic rates from mosquito trap counts and dengue case reports from the city of Vitória, Brazil. We used the fitted model to explore how the timing of a pulse of adult mosquito control influences its effect on the human disease burden in the following year. We found that control was generally more effective when implemented in periods of relatively low mosquito mortality (when mosquito abundance was also generally low). In particular, control implemented in early September (week 34 of the year) produced the largest reduction in predicted human case reports over the following year. This highlights the potential long-term utility of broad, off-peak-season mosquito control in addition to existing, locally targeted within-season efforts. Further, uncertainty in the effectiveness of control interventions was driven largely by posterior variation in the average mosquito mortality rate (closely tied to total mosquito abundance) with lower mosquito mortality generating systems more vulnerable to control. Broadly, these correlations suggest that mosquito control is most effective in situations in which transmission is already limited by mosquito abundance.
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Affiliation(s)
- Clinton B. Leach
- Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, United States of America
- Department of Statistics, Colorado State University, Fort Collins, Colorado, United States of America
| | - Jennifer A. Hoeting
- Department of Statistics, Colorado State University, Fort Collins, Colorado, United States of America
| | - Kim M. Pepin
- National Wildlife Research Center, United States Department of Agriculture, Wildlife Services, Fort Collins, Colorado, United States of America
| | - Alvaro E. Eiras
- Departamento de Parasitologia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Mevin B. Hooten
- Department of Statistics, Colorado State University, Fort Collins, Colorado, United States of America
- U.S. Geological Survey, Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, Colorado, United States of America
- Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, Colorado, United States of America
| | - Colleen T. Webb
- Graduate Degree Program in Ecology, Colorado State University, Fort Collins, Colorado, United States of America
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Knerer G, Currie CSM, Brailsford SC. The economic impact and cost-effectiveness of combined vector-control and dengue vaccination strategies in Thailand: results from a dynamic transmission model. PLoS Negl Trop Dis 2020; 14:e0008805. [PMID: 33095791 PMCID: PMC7654761 DOI: 10.1371/journal.pntd.0008805] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2018] [Revised: 11/10/2020] [Accepted: 09/17/2020] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND AND AIMS Dengue fever is a major public health problem in tropical/subtropical regions. Prior economic analyses have predominantly evaluated either vaccination or vector-control programmes in isolation and do not really consider the incremental benefits and cost-effectiveness of mixed strategies and combination control. We estimated the cost-effectiveness of single and combined approaches in Thailand. METHODS The impacts of different control interventions were analysed using a previously published mathematical model of dengue epidemiology and control incorporating seasonality, age structure, consecutive infection, cross protection, immune enhancement and combined vector-host transmission. An economic model was applied to simulation results to estimate the cost-effectiveness of 4 interventions and their various combinations (6 strategies): i) routine vaccination of 1-year olds; ii) chemical vector control strategies targeting adult and larval stages separately; iii) environmental management/ public health education and awareness [EM/ PHEA]). Payer and societal perspectives were considered. The health burden of dengue fever was assessed using disability-adjusted life-years (DALYs) lost. Costs and effects were assessed for 10 years. Costs were discounted at 3% annually and updated to 2013 United States Dollars. Incremental cost-effectiveness analysis was carried out after strategies were rank-ordered by cost, with results presented in a table of incremental analysis. Sensitivity and scenario analyses were undertaken; and the impact and cost-effectiveness of Wolbachia was evaluated in exploratory scenario analyses. RESULTS From the payer and societal perspectives, 2 combination strategies were considered optimal, as all other control strategies were dominated. Vaccination plus adulticide plus EM/ PHEA was deemed cost-effective according to multiple cost-effectiveness criteria. From the societal perspective, incremental differences vs. adulticide and EM/ PHEA resulted in costs of $157.6 million and DALYs lost of 12,599, giving an expected ICER of $12,508 per DALY averted. Exploratory scenario analyses showed Wolbachia to be highly cost-effective ($343 per DALY averted) vs. other single control measures. CONCLUSIONS Our model shows that individual interventions can be cost-effective, but that important epidemiological reductions and economic impacts are demonstrated when interventions are combined as part of an integrated approach to combating dengue fever. Exploratory scenario analyses demonstrated the potential epidemiological and cost-effective impact of Wolbachia when deployed at scale on a nationwide basis. Our findings were robust in the face of sensitivity analyses.
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Affiliation(s)
- Gerhart Knerer
- Mathematical Sciences, University of Southampton, Highfield, Southampton, United Kingdom
- * E-mail:
| | - Christine S. M. Currie
- Mathematical Sciences, University of Southampton, Highfield, Southampton, United Kingdom
| | - Sally C. Brailsford
- Southampton Business School, University of Southampton, Highfield, Southampton, United Kingdom
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Simulation models of dengue transmission in Funchal, Madeira Island: Influence of seasonality. PLoS Negl Trop Dis 2020; 14:e0008679. [PMID: 33017443 PMCID: PMC7561266 DOI: 10.1371/journal.pntd.0008679] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 10/15/2020] [Accepted: 08/04/2020] [Indexed: 11/19/2022] Open
Abstract
The recent emergence and established presence of Aedes aegypti in the Autonomous Region of Madeira, Portugal, was responsible for the first autochthonous outbreak of dengue in Europe. The island has not reported any dengue cases since the outbreak in 2012. However, there is a high risk that an introduction of the virus would result in another autochthonous outbreak given the presence of the vector and permissive environmental conditions. Understanding the dynamics of a potential epidemic is critical for targeted local control strategies. Here, we adopt a deterministic model for the transmission of dengue in Aedes aegypti mosquitoes. The model integrates empirical and mechanistic parameters for virus transmission, under seasonally varying temperatures for Funchal, Madeira Island. We examine the epidemic dynamics as triggered by the arrival date of an infectious individual; the influence of seasonal temperature mean and variation on the epidemic dynamics; and performed a sensitivity analysis on the following quantities of interest: the epidemic peak size, time to peak, and the final epidemic size. Our results demonstrate the potential for summer and autumn season transmission of dengue, with the arrival date significantly affecting the distribution of the timing and peak size of the epidemic. Late-summer arrivals were more likely to produce large epidemics within a short peak time. Epidemics within this favorable period had an average of 11% of the susceptible population infected at the peak, at an average peak time of 95 days. We also demonstrated that seasonal temperature variation dramatically affects the epidemic dynamics, with warmer starting temperatures producing large epidemics with a short peak time and vice versa. Overall, our quantities of interest were most sensitive to variance in the date of arrival, seasonal temperature, transmission rates, mortality rate, and the mosquito population; the magnitude of sensitivity differs across quantities. Our model could serve as a useful guide in the development of effective local control and mitigation strategies for dengue fever in Madeira Island.
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Castillo Signor LDC, Edwards T, Escobar LE, Mencos Y, Matope A, Castaneda-Guzman M, Adams ER, Cuevas LE. Epidemiology of dengue fever in Guatemala. PLoS Negl Trop Dis 2020; 14:e0008535. [PMID: 32813703 PMCID: PMC7458341 DOI: 10.1371/journal.pntd.0008535] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 08/31/2020] [Accepted: 06/29/2020] [Indexed: 11/18/2022] Open
Abstract
Dengue fever occurs worldwide and about 1% of cases progress to severe haemorrhage and shock. Dengue is endemic in Guatemala and its surveillance system could document long term trends. We analysed 17 years of country-wide dengue surveillance data in Guatemala to describe epidemiological trends from 2000 to 2016.Data from the national dengue surveillance database were analysed to describe dengue serotype frequency, seasonality, and outbreaks. We used Poisson regression models to compare the number of cases each year with subsequent years and to estimate incidence ratios within serotype adjusted by age and gender. 91,554 samples were tested. Dengue was confirmed by RT-qPCR, culture or NS1-ELISA in 7097 (7.8%) cases and was IgM ELISA-positive in 19,290 (21.1%) cases. DENV1, DENV2, DENV3, and DENV4 were detected in 2218 (39.5%), 2580 (45.9%), 591 (10.5%), and 230 (4.1%) cases. DENV1 and DENV2 were the predominant serotypes, but all serotypes caused epidemics. The largest outbreak occurred in 2010 with 1080 DENV2 cases reported. The incidence was higher among adults during epidemic years, with significant increases in 2005, 2007, and 2013 DENV1 outbreaks, the 2010 DENV2 and 2003 DENV3 outbreaks. Adults had a lower incidence immediately after epidemics, which is likely linked to increased immunity. Dengue is the most common mosquito-borne virus, and a major cause of fever, with an estimated 390 million infections annually. Guatemala, in Central America, has had ongoing dengue transmission since the 1990s. Its national surveillance system monitors outbreaks and seasonal trends of infections to inform public health responses. We have analysed 17 years of surveillance data collected from 2000 to 2016, to describe seasonal trends, outbreak years, and the fluctuating prevalence of the four dengue serotypes. Laboratory data from 91,554 individual serum samples were included, of which 7.8% were positive for dengue. All four dengue serotypes circulate in the country, with dengue 1 and 2 being the predominant serotypes. This is important, as it increases the likelihood of dengue infections being followed by a new infection with a different serotype, which can lead to severe dengue. We also report that adults in Guatemala have a lower likelihood of infection the year after an epidemic, which might be linked to an increased immunity in the population.
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Affiliation(s)
| | - Thomas Edwards
- Centre for Drugs and Diagnostics Research, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Luis E. Escobar
- Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA, United States of America
| | - Yolanda Mencos
- Ministerio de Salud Publica y Asistencia Social de Guatemala, Guatemala City, Guatemala
| | - Agnes Matope
- Tropical Clinical Trials Unit. Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Mariana Castaneda-Guzman
- Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA, United States of America
| | - Emily R. Adams
- Centre for Drugs and Diagnostics Research, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
| | - Luis E. Cuevas
- Centre for Drugs and Diagnostics Research, Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- Tropical Clinical Trials Unit. Liverpool School of Tropical Medicine, Liverpool, United Kingdom
- * E-mail:
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A Two-Patch Mathematical Model for Temperature-Dependent Dengue Transmission Dynamics. Processes (Basel) 2020. [DOI: 10.3390/pr8070781] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Dengue fever has been a threat to public health not only in tropical regions but non-tropical regions due to recent climate change. Motivated by a recent dengue outbreak in Japan, we develop a two-patch model for dengue transmission associated with temperature-dependent parameters. The two patches represent a park area where mosquitoes prevail and a residential area where people live. Based on climate change scenarios, we investigate the dengue transmission dynamics between the patches. We employ an optimal control method to implement proper control measures in the two-patch model. We find that blockage between two patches for a short-term period is effective in a certain degree for the disease control, but to obtain a significant control effect of the disease, a long-term blockage should be implemented. Moreover, the control strategies such as vector control and transmission control are very effective, if they are implemented right before the summer outbreak. We also investigate the cost-effectiveness of control strategies such as vaccination, vector control and virus transmission control. We find that vector control and virus transmission control are more cost-effective than vaccination in case of Korea.
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Enslen AW, Lima Neto AS, Castro MC. Infestation measured by Aedes aegypti larval surveys as an indication of future dengue epidemics: an evaluation for Brazil. Trans R Soc Trop Med Hyg 2020; 114:506-512. [PMID: 32346740 DOI: 10.1093/trstmh/traa021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2019] [Revised: 03/08/2020] [Accepted: 03/13/2020] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Aedes aegypti rapid larval surveys are mandatory in Brazil. Here, we retrospectively examined whether the house index estimated by larval surveys served as a useful tool in anticipating epidemics within Brazilian municipalities from 2009-2015. METHODS We used correlation indices and classification analysis stratified by year, region, population size and time after the national larval survey. RESULTS We found no association between the house index and the proportion of municipalities experiencing an epidemic. The sensitivity of a high score house index in predicting an epidemic was 7.20% (95% CI 6.22 to 8.33%) for all years combined. The positive predictive value of a high score house index to predict a 'true epidemic' was 38.96%, lower than the negative predictive values of a low score house index for predicting 'no epidemic' (56.96%). The highest overall sensitivity was observed in the North region (20.15%; 95% CI 17.14 to 23.53%). The sensitivity of a high score house index demonstrated a monotonic decrease with increasing time from larval collection. CONCLUSIONS Larval surveys are surveillance tools with the potential to risk-stratify and guide dengue control programs towards judicious resource allocation. However, the national rapid larval survey performed in Brazil, in its present form, consistently underpredicts dengue epidemics.
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Affiliation(s)
- Andrew W Enslen
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston 02115, MA, USA
| | - Antonio S Lima Neto
- Fortaleza Municipal Health Secretariat (SMS-Fortaleza), Rua Capitão Gustavo 3552 - Joaquim Távora, Fortaleza, Ceará, 60120-075, Brazil.,University of Fortaleza (UNIFOR), Av. Washington Soares, 1321 - Edson Queiroz, Fortaleza, Ceará, 60811-905, Brazil
| | - Marcia C Castro
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston 02115, MA, USA
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Brett TS, Rohani P. Dynamical footprints enable detection of disease emergence. PLoS Biol 2020; 18:e3000697. [PMID: 32433658 PMCID: PMC7239390 DOI: 10.1371/journal.pbio.3000697] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Accepted: 04/23/2020] [Indexed: 12/21/2022] Open
Abstract
Developing methods for anticipating the emergence or reemergence of infectious diseases is both important and timely; however, traditional model-based approaches are stymied by uncertainty surrounding the underlying drivers. Here, we demonstrate an operational, mechanism-agnostic detection algorithm for disease (re-)emergence based on early warning signals (EWSs) derived from the theory of critical slowing down. Specifically, we used computer simulations to train a supervised learning algorithm to detect the dynamical footprints of (re-)emergence present in epidemiological data. Our algorithm was then challenged to forecast the slowly manifesting, spatially replicated reemergence of mumps in England in the mid-2000s and pertussis post-1980 in the United States. Our method successfully anticipated mumps reemergence 4 years in advance, during which time mitigation efforts could have been implemented. From 1980 onwards, our model identified resurgent states with increasing accuracy, leading to reliable classification starting in 1992. Additionally, we successfully applied the detection algorithm to 2 vector-transmitted case studies, namely, outbreaks of dengue serotypes in Puerto Rico and a rapidly unfolding outbreak of plague in 2017 in Madagascar. Taken together, these findings illustrate the power of theoretically informed machine learning techniques to develop early warning systems for the (re-)emergence of infectious diseases.
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Affiliation(s)
- Tobias S. Brett
- Odum School of Ecology, University of Georgia, Athens, Georgia, United States of America
- Center for the Ecology of Infectious Diseases, University of Georgia, Athens, Georgia, United States of America
| | - Pejman Rohani
- Odum School of Ecology, University of Georgia, Athens, Georgia, United States of America
- Center for the Ecology of Infectious Diseases, University of Georgia, Athens, Georgia, United States of America
- Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, Georgia, United States of America
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Muurlink OT, Taylor-Robinson AW. The 'lifecycle' of human beings: a call to explore vector-borne diseases from an ecosystem perspective. Infect Dis Poverty 2020; 9:37. [PMID: 32295629 PMCID: PMC7161208 DOI: 10.1186/s40249-020-00653-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Accepted: 02/07/2020] [Indexed: 11/21/2022] Open
Abstract
Background Dengue virus, an Aedes mosquito-borne flavivirus, is associated with close to 400 million reported infections per annum worldwide. Reduction of dengue virus transmission depends entirely on limiting Aedes breeding or preventing adult female contact with humans. Currently, the World Health Organization promotes the strategic approach of integrated vector management in order to optimise resources for mosquito control. Main text Neglected tropical disease researchers focus on geographical zones where the incidence of clinical cases, and prevalence of vectors, are high. In combatting those infectious diseases such as dengue that affect mainly low-income populations in developing regions, a mosquito-centric approach is frequently adopted. This prioritises environmental factors that facilitate or impede the lifecycle progression of the vector. Climatic variables (such as rainfall and wind speed) that impact the vector’s lifecycle either causally or by happenstance also affect the human host’s ‘lifecycle’, but in very different ways. The socioeconomic impacts of the same variables that influence vector control impact host vulnerability but at different points in the human lifecycle to those of the vector. Here, we argue that the vulnerability of the vector and that of the host interact in complex and unpredictable ways that are characteristic of (complex and intransigent) ‘wicked problems’. Moreover, they are treated by public health programs in ways that may ignore this complexity. This opinion draws on recent evidence showing that the best climate predictors of the scale of dengue outbreaks in Bangladesh cannot be explained through a simple vector-to-host causal model. Conclusions In mapping causal pathways for vector-borne diseases this article makes a case to elevate the lifecycle of the human host to a level closer in equivalence to that of the vector. Here, we suggest value may be gained from transferring Rittel and Webber’s concept of a wicked (social) problem to dengue, malaria and other mosquito-transmitted public health concerns. This would take a ‘problem definition’ rather than a ‘solution-finding’ approach, particularly when considering problems in which climate impacts simultaneously on human and vector vulnerability.
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Affiliation(s)
- Olav T Muurlink
- Centre for Sustainable Innovation, School of Business & Law, Central Queensland University, Brisbane, QLD, Australia
| | - Andrew W Taylor-Robinson
- Infectious Diseases Research Group, School of Health, Medical & Applied Sciences, Central Queensland University, Brisbane, QLD, Australia.
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Gulbudak H, Browne CJ. Infection severity across scales in multi-strain immuno-epidemiological Dengue model structured by host antibody level. J Math Biol 2020; 80:1803-1843. [PMID: 32157381 DOI: 10.1007/s00285-020-01480-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Revised: 01/19/2020] [Indexed: 01/08/2023]
Abstract
Infection by distinct Dengue virus serotypes and host immunity are intricately linked. In particular, certain levels of cross-reactive antibodies in the host may actually enhance infection severity leading to Dengue hemorrhagic fever (DHF). The coupled immunological and epidemiological dynamics of Dengue calls for a multi-scale modeling approach. In this work, we formulate a within-host model which mechanistically recapitulates characteristics of antibody dependent enhancement in Dengue infection. The within-host scale is then linked to epidemiological spread by a vector-host partial differential equation model structured by host antibody level. The coupling allows for dynamic population-wide antibody levels to be tracked through primary and secondary infections by distinct Dengue strains, along with waning of cross-protective immunity after primary infection. Analysis of both the within-host and between-host systems are conducted. Stability results in the epidemic model are formulated via basic and invasion reproduction numbers as a function of immunological variables. Additionally, we develop numerical methods in order to simulate the multi-scale model and assess the influence of parameters on disease spread and DHF prevalence in the population.
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Affiliation(s)
- Hayriye Gulbudak
- Mathematics Department, University of Louisiana at Lafayette, Lafayette, LA, USA.
| | - Cameron J Browne
- Mathematics Department, University of Louisiana at Lafayette, Lafayette, LA, USA
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Blight J, Alves E, Reyes-Sandoval A. Considering Genomic and Immunological Correlates of Protection for a Dengue Intervention. Vaccines (Basel) 2019; 7:E203. [PMID: 31816907 PMCID: PMC6963661 DOI: 10.3390/vaccines7040203] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 11/25/2019] [Accepted: 11/27/2019] [Indexed: 01/18/2023] Open
Abstract
Over three billion are at risk of dengue infection with more than 100 million a year presenting with symptoms that can lead to deadly haemorrhagic disease. There are however no treatments available and the only licensed vaccine shows limited efficacy and is able to enhance the disease in some cases. These failures have mainly been due to the complex pathology and lack of understanding of the correlates of protection for dengue virus (DENV) infection. With increasing data suggesting both a protective and detrimental effect for antibodies and CD8 T-cells whilst having complex environmental dynamics. This review discusses the roles of genomic and immunological aspects of DENV infection, providing both a historical interpretation and fresh discussion on how this information can be used for the next generation of dengue interventions.
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Affiliation(s)
- Joshua Blight
- Department of Life Sciences, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK; (J.B.); (E.A.)
- The Jenner Institute, Nuffield Department of Medicine, University of Oxford, The Henry Wellcome Building for Molecular Physiology, Roosevelt Drive, Oxford OX3 7BN, UK
| | - Eduardo Alves
- Department of Life Sciences, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK; (J.B.); (E.A.)
- The Jenner Institute, Nuffield Department of Medicine, University of Oxford, The Henry Wellcome Building for Molecular Physiology, Roosevelt Drive, Oxford OX3 7BN, UK
| | - Arturo Reyes-Sandoval
- The Jenner Institute, Nuffield Department of Medicine, University of Oxford, The Henry Wellcome Building for Molecular Physiology, Roosevelt Drive, Oxford OX3 7BN, UK
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Johansson MA, Apfeldorf KM, Dobson S, Devita J, Buczak AL, Baugher B, Moniz LJ, Bagley T, Babin SM, Guven E, Yamana TK, Shaman J, Moschou T, Lothian N, Lane A, Osborne G, Jiang G, Brooks LC, Farrow DC, Hyun S, Tibshirani RJ, Rosenfeld R, Lessler J, Reich NG, Cummings DAT, Lauer SA, Moore SM, Clapham HE, Lowe R, Bailey TC, García-Díez M, Carvalho MS, Rodó X, Sardar T, Paul R, Ray EL, Sakrejda K, Brown AC, Meng X, Osoba O, Vardavas R, Manheim D, Moore M, Rao DM, Porco TC, Ackley S, Liu F, Worden L, Convertino M, Liu Y, Reddy A, Ortiz E, Rivero J, Brito H, Juarrero A, Johnson LR, Gramacy RB, Cohen JM, Mordecai EA, Murdock CC, Rohr JR, Ryan SJ, Stewart-Ibarra AM, Weikel DP, Jutla A, Khan R, Poultney M, Colwell RR, Rivera-García B, Barker CM, Bell JE, Biggerstaff M, Swerdlow D, Mier-Y-Teran-Romero L, Forshey BM, Trtanj J, Asher J, Clay M, Margolis HS, Hebbeler AM, George D, Chretien JP. An open challenge to advance probabilistic forecasting for dengue epidemics. Proc Natl Acad Sci U S A 2019; 116:24268-24274. [PMID: 31712420 PMCID: PMC6883829 DOI: 10.1073/pnas.1909865116] [Citation(s) in RCA: 104] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue.
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Affiliation(s)
- Michael A Johansson
- Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan 00920, Puerto Rico;
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115
| | | | - Scott Dobson
- Data Analytics, Areté Associates, Northridge, CA 91324
| | - Jason Devita
- Data Analytics, Areté Associates, Northridge, CA 91324
| | - Anna L Buczak
- Systems Integration Branch, Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723
| | - Benjamin Baugher
- Systems Integration Branch, Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723
| | - Linda J Moniz
- Systems Integration Branch, Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723
| | - Thomas Bagley
- Systems Integration Branch, Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723
| | - Steven M Babin
- Systems Integration Branch, Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723
| | - Erhan Guven
- Systems Integration Branch, Johns Hopkins University Applied Physics Laboratory, Laurel, MD 20723
| | - Teresa K Yamana
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032
| | - Jeffrey Shaman
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032
| | - Terry Moschou
- Data to Decisions Cooperative Research Center, Kent Town, SA 5067, Australia
| | - Nick Lothian
- Data to Decisions Cooperative Research Center, Kent Town, SA 5067, Australia
| | - Aaron Lane
- Data to Decisions Cooperative Research Center, Kent Town, SA 5067, Australia
| | - Grant Osborne
- Data to Decisions Cooperative Research Center, Kent Town, SA 5067, Australia
| | - Gao Jiang
- Heinz College Information System Management, Carnegie Mellon University, Adelaide, SA 5000, Australia
| | - Logan C Brooks
- School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213
| | - David C Farrow
- School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Sangwon Hyun
- Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Ryan J Tibshirani
- School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213
- Department of Statistics, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Roni Rosenfeld
- School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213
| | - Justin Lessler
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205
| | - Nicholas G Reich
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA 01003
| | - Derek A T Cummings
- Department of Biology, University of Florida, Gainesville, FL 32611
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32611
| | - Stephen A Lauer
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA 01003
| | - Sean M Moore
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556
- Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556
| | - Hannah E Clapham
- Hospital for Tropical Diseases, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Rachel Lowe
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London WC1E 7HT, United Kingdom
- Climate and Health Program, Barcelona Institute for Global Health, 08003 Barcelona, Spain
| | - Trevor C Bailey
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter EX4 4QF, United Kingdom
| | | | - Marilia Sá Carvalho
- Scientific Computation Program, Oswaldo Cruz Foundation, Rio de Janeiro 21040-900, Brazil
| | - Xavier Rodó
- Climate and Health Program, Barcelona Institute for Global Health, 08003 Barcelona, Spain
- Catalan Institution for Research and Advanced Studies, 08010 Barcelona, Spain
| | - Tridip Sardar
- Catalan Institution for Research and Advanced Studies, 08010 Barcelona, Spain
| | - Richard Paul
- Department of Mathematical Biology, Indian Statistical Institute, Kolkata, India 700108
- Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, 606-8501 Kyoto, Japan
| | - Evan L Ray
- Department of Global Health, Centre National de la Recherche Scientifique, 75016 Paris, France
| | - Krzysztof Sakrejda
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA 01003
| | - Alexandria C Brown
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA 01003
| | - Xi Meng
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA 01003
| | - Osonde Osoba
- Department of Mathematics and Statistics, Mount Holyoke College, South Hadley, MA 01075
| | - Raffaele Vardavas
- Department of Mathematics and Statistics, Mount Holyoke College, South Hadley, MA 01075
| | | | - Melinda Moore
- Department of Mathematics and Statistics, Mount Holyoke College, South Hadley, MA 01075
| | | | - Travis C Porco
- Department of Computer Science and Software Engineering, Miami University, Oxford, OH 45056
| | - Sarah Ackley
- Department of Computer Science and Software Engineering, Miami University, Oxford, OH 45056
| | - Fengchen Liu
- Department of Computer Science and Software Engineering, Miami University, Oxford, OH 45056
| | - Lee Worden
- Department of Computer Science and Software Engineering, Miami University, Oxford, OH 45056
| | - Matteo Convertino
- F. I. Proctor Foundation for Research in Ophthalmology, University of California, San Francisco, CA 94122
| | - Yang Liu
- Information Science and Technology, Hokkaido University, Sapporo 060-0808, Japan
| | - Abraham Reddy
- Information Science and Technology, Hokkaido University, Sapporo 060-0808, Japan
| | - Eloy Ortiz
- Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Twin Cities, MN 55455
| | - Jorge Rivero
- Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Twin Cities, MN 55455
| | - Humberto Brito
- Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Twin Cities, MN 55455
- VectorAnalytica, Washington, DC 20007
| | - Alicia Juarrero
- Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Twin Cities, MN 55455
- Department of Aeronautical Engineering, Universidade de Sao Paolo, Sao Paolo 13566-590, Brazil
| | - Leah R Johnson
- Department of Philosophy, University of Miami, Coral Gables, FL 33146
| | | | - Jeremy M Cohen
- Department of Statistics, Virginia Tech, Blacksburg, VA 24060
| | - Erin A Mordecai
- Integrative Biology, University of South Florida, Tampa, FL 33620
| | - Courtney C Murdock
- Department of Biology, Stanford University, Stanford, CA 94305
- Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, GA 30602
| | - Jason R Rohr
- Department of Biological Sciences, University of Notre Dame, Notre Dame, IN 46556
- Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556
| | - Sadie J Ryan
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32611
- Odum School of Ecology, University of Georgia, Athens, GA 30602
- Department of Geography, University of Florida, Gainesville, FL 32608
| | | | - Daniel P Weikel
- Department of Medicine, State University of New York Upstate Medical University, Syracuse, NY 13421
| | - Antarpreet Jutla
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109
| | - Rakibul Khan
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109
| | - Marissa Poultney
- Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109
| | - Rita R Colwell
- Department of Civil and Environmental Engineering, West Virginia University, Morgantown, WV 26505
| | - Brenda Rivera-García
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, MD 20742
| | | | - Jesse E Bell
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, CA 95616
| | - Matthew Biggerstaff
- Department of Environmental, Agricultural, and Occupational Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198
| | - David Swerdlow
- Department of Environmental, Agricultural, and Occupational Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198
| | - Luis Mier-Y-Teran-Romero
- Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan 00920, Puerto Rico
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205
| | - Brett M Forshey
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA 30329
| | - Juli Trtanj
- Armed Forces Health Surveillance Branch, Department of Defense, Silver Spring, MD 20904
| | - Jason Asher
- Climate Program Office, National Oceanic and Atmospheric Administration, Silver Spring, MD 20910
| | - Matt Clay
- Climate Program Office, National Oceanic and Atmospheric Administration, Silver Spring, MD 20910
| | - Harold S Margolis
- Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan 00920, Puerto Rico
| | - Andrew M Hebbeler
- Leidos supporting the Biomedical Advanced Research and Development Authority, Department of Health and Human Services, Washington, DC 20201
- Bureau of Oceans, International Environmental and Scientific Affairs, US Department of State, Washington, DC 20520
| | - Dylan George
- Bureau of Oceans, International Environmental and Scientific Affairs, US Department of State, Washington, DC 20520
- Office of Science and Technology Policy, The White House, Washington, DC 20502
| | - Jean-Paul Chretien
- Bureau of Oceans, International Environmental and Scientific Affairs, US Department of State, Washington, DC 20520
- BNext, In-Q-Tel, Arlington, VA 22201
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Assessing the interplay between human mobility and mosquito borne diseases in urban environments. Sci Rep 2019; 9:16911. [PMID: 31729435 PMCID: PMC6858332 DOI: 10.1038/s41598-019-53127-z] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Accepted: 10/17/2019] [Indexed: 12/21/2022] Open
Abstract
Urbanization drives the epidemiology of infectious diseases to many threats and new challenges. In this research, we study the interplay between human mobility and dengue outbreaks in the complex urban environment of the city-state of Singapore. We integrate both stylized and mobile phone data-driven mobility patterns in an agent-based transmission model in which humans and mosquitoes are represented as agents that go through the epidemic states of dengue. We monitor with numerical simulations the system-level response to the epidemic by comparing our results with the observed cases reported during the 2013 and 2014 outbreaks. Our results show that human mobility is a major factor in the spread of vector-borne diseases such as dengue even on the short scale corresponding to intra-city distances. We finally discuss the advantages and the limits of mobile phone data and potential alternatives for assessing valuable mobility patterns for modeling vector-borne diseases outbreaks in cities.
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45
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A vector-host model to assess the impact of superinfection exclusion on vaccination strategies using dengue and yellow fever as case studies. J Theor Biol 2019; 484:110014. [PMID: 31557473 DOI: 10.1016/j.jtbi.2019.110014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 09/05/2019] [Accepted: 09/15/2019] [Indexed: 01/14/2023]
Abstract
Superinfection exclusion is a phenomenon whereby the co-infection of a host with a secondary pathogen is prevented due to a current infection by another closely-related pathogenic strain. We construct a novel vector-host mathematical model for two pathogens that exhibit superinfection exclusion and simultaneously account for vaccination strategies against them. We then derive the conditions under which an endemic disease will prevent the establishment of another through the action of superinfection exclusion and show that vaccination against the endemic strain can enable the previously suppressed strain to invade the population. Through appropriate parameterisation of the model for dengue and yellow fever we find that superinfection exclusion alone is unlikely to explain the absence of yellow fever in many regions where dengue is endemic, and that the rollout of the recently licensed dengue vaccine, Dengvaxia, is unlikely to enable the establishment of Yellow Fever in regions where it has previously been absent.
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46
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Dengue virus infection in people residing in Africa: a systematic review and meta-analysis of prevalence studies. Sci Rep 2019; 9:13626. [PMID: 31541167 PMCID: PMC6754462 DOI: 10.1038/s41598-019-50135-x] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Accepted: 08/19/2019] [Indexed: 01/05/2023] Open
Abstract
Better knowledge of the face of the current dengue virus (DENV) epidemiology in Africa can help to implement efficient strategies to curb the burden of dengue fever. We conducted this systematic review and meta-analysis to determine the prevalence of DENV infection in Africa. We searched PubMed, EMBASE, African Journals Online, and Africa Index Medicus from January 1st, 2000 to June 10th, 2019 without any language restriction. We used a random-effects model to pool studies. A total of 76 studies (80,977 participants; 24 countries) were included. No study had high risk of bias. Twenty-two (29%) had moderate and 54 (71%) had low risk of bias. In apparently healthy individuals, the pooled prevalence of DENV was 15.6% (95% confidence interval 9.9–22.2), 3.5% (0.8–7.8), and 0.0% (0.0–0.5) respectively for immunoglobulins (Ig) G, IgM, and for ribonucleic acid (RNA) in apparently healthy populations. In populations presenting with fever, the prevalence was 24.8% (13.8–37.8), 10.8% (3.8–20.6k) and 8.4% (3.7–14.4) for IgG, IgM, and for RNA respectively. There was heterogeneity in the distribution between different regions of Africa. The prevalence of DENV infection is high in the African continent. Dengue fever therefore deserves more attention from healthcare workers, researchers, and health policy makers.
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47
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Bell SM, Katzelnick L, Bedford T. Dengue genetic divergence generates within-serotype antigenic variation, but serotypes dominate evolutionary dynamics. eLife 2019; 8:42496. [PMID: 31385805 PMCID: PMC6731059 DOI: 10.7554/elife.42496] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Accepted: 08/05/2019] [Indexed: 01/11/2023] Open
Abstract
Dengue virus (DENV) exists as four genetically distinct serotypes, each of which is historically assumed to be antigenically uniform. Recent analyses suggest that antigenic heterogeneity may exist within each serotype, but its source, extent and impact remain unclear. Here, we construct a sequence-based model to directly map antigenic change to underlying genetic divergence. We identify 49 specific substitutions and four colinear substitution clusters that robustly predict dengue antigenic relationships. We report moderate antigenic diversity within each serotype, resulting in genotype-specific patterns of heterotypic cross-neutralization. We also quantify the impact of antigenic variation on real-world DENV population dynamics, and find that serotype-level antigenic fitness is a dominant driver of dengue clade turnover. These results provide a more nuanced understanding of the relationship between dengue genetic and antigenic evolution, and quantify the effect of antigenic fitness on dengue evolutionary dynamics.
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Affiliation(s)
- Sidney M Bell
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States.,Molecular and Cell Biology Program, University of Washington, Seattle, United States
| | - Leah Katzelnick
- Division of Infectious Diseases and Vaccinology, University of California, Berkeley, Berkeley, United States.,Department of Biology, University of Florida, Gainesville, United States
| | - Trevor Bedford
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States
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48
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Cross-serotype interactions and disease outcome prediction of dengue infections in Vietnam. Sci Rep 2019; 9:9395. [PMID: 31253823 PMCID: PMC6598999 DOI: 10.1038/s41598-019-45816-6] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Accepted: 06/04/2019] [Indexed: 11/30/2022] Open
Abstract
Dengue pathogenesis is extremely complex. Dengue infections are thought to induce life-long immunity from homologous challenges as well as a multi-factorial heterologous risk enhancement. Here, we use the data collected from a prospective cohort study of dengue infections in schoolchildren in Vietnam to disentangle how serotype interactions modulate clinical disease risk in the year following serum collection. We use multinomial logistic regression to correlate the yearly neutralizing antibody measurements obtained with each infecting serotype in all dengue clinical cases collected over the course of 6 years (2004–2009). This allowed us to extrapolate a fully discretised matrix of serotype interactions, revealing clear signals of increased risk of clinical illness in individuals primed with a previous dengue infection. The sequences of infections which produced a higher risk of dengue fever upon secondary infection are: DEN1 followed by DEN2; DEN1 followed by DEN4; DEN2 followed by DEN3; and DEN4 followed by DEN3. We also used this longitudinal data to train a machine learning algorithm on antibody titre differences between consecutive years to unveil asymptomatic dengue infections and estimate asymptomatic infection to clinical case ratios over time, allowing for a better characterisation of the population’s past exposure to different serotypes.
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49
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Pleydell DRJ, Bouyer J. Biopesticides improve efficiency of the sterile insect technique for controlling mosquito-driven dengue epidemics. Commun Biol 2019; 2:201. [PMID: 31149645 PMCID: PMC6541632 DOI: 10.1038/s42003-019-0451-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2018] [Accepted: 04/30/2019] [Indexed: 12/16/2022] Open
Abstract
Various mosquito control methods use factory raised males to suppress vector densities. But the efficiency of these methods is currently insufficient to prevent epidemics of arbovirus diseases such as dengue, chikungunya or Zika. Suggestions that the sterile insect technique (SIT) could be "boosted" by applying biopesticides to sterile males remain unquantified. Here, we assess mathematically the gains to SIT for Aedes control of either: boosting with the pupicide pyriproxifen (BSIT); or, contaminating mosquitoes at auto-dissemination stations. Thresholds in sterile male release rate and competitiveness are identified, above which mosquitoes are eliminated asymptotically. Boosting reduces these thresholds and aids population destabilisation, even at sub-threshold release rates. No equivalent bifurcation exists in the auto-dissemination sub-model. Analysis suggests that BSIT can reduce by over 95% the total release required to circumvent dengue epidemics compared to SIT. We conclude, BSIT provides a powerful new tool for the integrated management of mosquito borne diseases.
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Affiliation(s)
- David R. J. Pleydell
- CIRAD, INRA, University of Montpellier, UMR ASTRE, F-34398 Montpellier, France
- INRA, CIRAD, University of Montpellier, UMR ASTRE, F-97170 Petit Bourg Guadeloupe, France
| | - Jérémy Bouyer
- CIRAD, INRA, University of Montpellier, UMR ASTRE, F-34398 Montpellier, France
- Insect Pest Control Laboratory, Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture, IAEA, Vienna, Austria
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Oidtman RJ, Lai S, Huang Z, Yang J, Siraj AS, Reiner RC, Tatem AJ, Perkins TA, Yu H. Inter-annual variation in seasonal dengue epidemics driven by multiple interacting factors in Guangzhou, China. Nat Commun 2019; 10:1148. [PMID: 30850598 PMCID: PMC6408462 DOI: 10.1038/s41467-019-09035-x] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Accepted: 02/12/2019] [Indexed: 02/07/2023] Open
Abstract
Vector-borne diseases display wide inter-annual variation in seasonal epidemic size due to their complex dependence on temporally variable environmental conditions and other factors. In 2014, Guangzhou, China experienced its worst dengue epidemic on record, with incidence exceeding the historical average by two orders of magnitude. To disentangle contributions from multiple factors to inter-annual variation in epidemic size, we fitted a semi-mechanistic model to time series data from 2005-2015 and performed a series of factorial simulation experiments in which seasonal epidemics were simulated under all combinations of year-specific patterns of four time-varying factors: imported cases, mosquito density, temperature, and residual variation in local conditions not explicitly represented in the model. Our results indicate that while epidemics in most years were limited by unfavorable conditions with respect to one or more factors, the epidemic in 2014 was made possible by the combination of favorable conditions for all factors considered in our analysis.
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Affiliation(s)
- Rachel J Oidtman
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, 46556, IN, USA
| | - Shengjie Lai
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 200032, China
- WorldPop, Department of Geography and Environment, University of Southampton, Southampton, SO17 1BJ, UK
- Flowminder Foundation, Stockholm, SE-11355, Sweden
| | - Zhoujie Huang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 200032, China
| | - Juan Yang
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 200032, China
| | - Amir S Siraj
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, 46556, IN, USA
| | - Robert C Reiner
- Institute for Health and Metrics and Evaluation, University of Washington, Seattle, 98195, WA, USA
| | - Andrew J Tatem
- WorldPop, Department of Geography and Environment, University of Southampton, Southampton, SO17 1BJ, UK
- Flowminder Foundation, Stockholm, SE-11355, Sweden
| | - T Alex Perkins
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, 46556, IN, USA.
| | - Hongjie Yu
- School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, 200032, China.
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