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Zhu G, Liu T, Xiao J, Zhang B, Song T, Zhang Y, Lin L, Peng Z, Deng A, Ma W, Hao Y. Effects of human mobility, temperature and mosquito control on the spatiotemporal transmission of dengue. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 651:969-978. [PMID: 30360290 DOI: 10.1016/j.scitotenv.2018.09.182] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 09/14/2018] [Accepted: 09/14/2018] [Indexed: 05/06/2023]
Abstract
Dengue transmission exhibits evident geographic variations and seasonal differences. Such heterogeneity is caused by various impact factors, in which temperature and host/vector behaviors could drive its spatiotemporal transmission, but mosquito control could stop its progression. These factors together contribute to the observed distributions of dengue incidence from surveillance systems. To effectively and efficiently monitor and response to dengue outbreak, it would be necessary to systematically model these factors and their impacts on dengue transmission. This paper introduces a new modeling framework with consideration of multi-scale factors and surveillance data to clarify the hidden dynamics accounting for dengue spatiotemporal transmission. The model is based on compartmental system which takes into account the biting-based interactions among humans, viruses and mosquitoes, as well as the essential impacts of human mobility, temperature and mosquito control. This framework was validated with real epidemic data by applying retrospectively to the 2014 dengue epidemic in the Pearl River Delta (PRD) in southern China. The results indicated that suitable condition of temperature could be responsible for the explosive dengue outbreak in the PRD, and human mobility could be the causal factor leading to its spatial transmission across different cities. It was further found that mosquito intervention has significantly reduced dengue incidence, where a total of 52,770 (95% confidence interval [CI]: 29,231-76,308) dengue cases were prevented in the PRD in 2014. The findings can offer new insights for improving the predictability and risk assessment of dengue epidemics. The model also can be readily extended to investigate the transmission dynamics of other mosquito-borne diseases.
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Affiliation(s)
- Guanghu Zhu
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; Department of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004, China; Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Tao Liu
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Jianpeng Xiao
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Bing Zhang
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Tie Song
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Yonghui Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Lifeng Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Zhiqiang Peng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Aiping Deng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Wenjun Ma
- Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China.
| | - Yuantao Hao
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
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Champagne C, Cazelles B. Comparison of stochastic and deterministic frameworks in dengue modelling. Math Biosci 2019; 310:1-12. [PMID: 30735695 DOI: 10.1016/j.mbs.2019.01.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Revised: 01/28/2019] [Accepted: 01/30/2019] [Indexed: 11/16/2022]
Abstract
We perform estimations of compartment models for dengue transmission in rural Cambodia with increasing complexity regarding both model structure and the account for stochasticity. On the one hand, we successively account for three embedded sources of stochasticity: observation noise, demographic variability and environmental hazard. On the other hand, complexity in the model structure is increased by introducing vector-borne transmission, explicit asymptomatic infections and interacting virus serotypes. Using two sources of case data from dengue epidemics in Kampong Cham (Cambodia), models are estimated in the bayesian framework, with Markov Chain Monte Carlo and Particle Markov Chain Monte Carlo. We highlight the advantages and drawbacks of the different formulations in a practical setting. Although in this case the deterministic models provide a good approximation of the mean trajectory for a low computational cost, the stochastic frameworks better reflect and account for parameter and simulation uncertainty.
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Affiliation(s)
- Clara Champagne
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS UMR 8197,46 rue d'Ulm, Paris 75005, France; CREST, ENSAE, Université Paris Saclay, 5, avenue Henry Le Chatelier, Palaiseau cedex 91764, France.
| | - Bernard Cazelles
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, CNRS UMR 8197,46 rue d'Ulm, Paris 75005, France; International Center for Mathematical and Computational Modeling of Complex Systems (UMMISCO), UMI 209 Sorbonne Université - IRD, Bondy cedex, France
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Yuan HY, Wen TH, Kung YH, Tsou HH, Chen CH, Chen LW, Lin PS. Prediction of annual dengue incidence by hydro-climatic extremes for southern Taiwan. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2019; 63:259-268. [PMID: 30680621 DOI: 10.1007/s00484-018-01659-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Revised: 10/30/2018] [Accepted: 12/03/2018] [Indexed: 05/16/2023]
Abstract
Dengue is one of the most rapidly spreading mosquito-borne viral diseases in the world. An increase in the incidence of dengue is commonly thought to be a consequence of variability of weather conditions. Taiwan, which straddles the Tropic of Cancer, is an excellent place to study the relationship between weather conditions and dengue fever cases since the island forms an isolated geographic environment. Therefore, clarifying the association between extreme weather conditions and annual dengue incidence is one of important issues for epidemic early warning. In this paper, we develop a Poisson regression model with extreme weather parameters for prediction of annual dengue incidence. A leave-one-out method is used to evaluate the performance of predicting dengue incidence. Our results indicate that dengue transmission has a positive relationship with the minimum temperature predictors during the early summer while a negative relationship with all the maximum 24-h rainfall predictors during the early epidemic phase of dengue outbreaks. Our findings provide a better understanding of the relationships between extreme weather and annual trends in dengue cases in Taiwan and it could have important implications for dengue forecasts in surrounding areas with similar meteorological conditions.
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Affiliation(s)
- Hsiang-Yu Yuan
- Department of Biomedical Sciences, City University of Hong Kong, Kowloon Tong, Hong Kong
| | - Tzai-Hung Wen
- Department of Geography, National Taiwan University, Taipei City, Taiwan
| | - Yi-Hung Kung
- National Mosquito-Borne Disease Control Research Center, National Health Research Institutes, 35 Keyan Road, Zhuna, Miaoli, 350, Taiwan
| | - Hsiao-Hui Tsou
- National Mosquito-Borne Disease Control Research Center, National Health Research Institutes, 35 Keyan Road, Zhuna, Miaoli, 350, Taiwan
- Institute of Population Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhuna, Miaoli, 350, Taiwan
| | - Chun-Hong Chen
- National Mosquito-Borne Disease Control Research Center, National Health Research Institutes, 35 Keyan Road, Zhuna, Miaoli, 350, Taiwan
- Institute of Infectious Diseases and Vaccinology, National Health Research Institutes, Zhuna, Taiwan
| | - Li-Wei Chen
- Institute of Population Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhuna, Miaoli, 350, Taiwan
| | - Pei-Sheng Lin
- National Mosquito-Borne Disease Control Research Center, National Health Research Institutes, 35 Keyan Road, Zhuna, Miaoli, 350, Taiwan.
- Institute of Population Health Sciences, National Health Research Institutes, 35 Keyan Road, Zhuna, Miaoli, 350, Taiwan.
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Effect of active case finding on dengue control: Implications from a mathematical model. J Theor Biol 2018; 464:50-62. [PMID: 30582932 DOI: 10.1016/j.jtbi.2018.12.027] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 12/18/2018] [Accepted: 12/19/2018] [Indexed: 11/21/2022]
Abstract
Dengue control in India is a challenging task due to complex healthcare settings. In yesteryears, an amplification of dengue infections in India posed the need for introspection of existing dengue control policies. Prior understanding of the impacts of control interventions is necessary for their future implementation. In this paper, we propose and analyze a compartmental model of dengue to assess the impact of active case finding (ACF) on dengue disease transmission. Currently, primary prevention of dengue is possible only with vector control and personal protection from the bites of infected mosquitoes. Although a few experimental studies are performed to assess ACF in dengue disease, but this is the first attempt to represent and study the dynamics of disease using ACF as a control strategy. Local and global dynamics of the system are studied. We use sensitivity analysis to see the effects of controllable parameters of the model on the basic reproduction number and total number of infective population. We find that decrease in the biting rate of mosquitoes, and increase in the rate of hospitalization and/or notification, death rate of mosquitoes and ACF for asymptomatic and symptomatic individuals play crucial role for the reduction of disease prevalence. We calibrate our model to the yearly dengue cases in eight dengue endemic states of India. The results of our study show that ACF of symptomatic individuals will have significant effect on dengue case reduction but ACF of asymptomatic individuals cannot be ignored. Our findings indicate that the healthcare organizations must focus on ACF of symptomatic as well as asymptomatic individuals along with personal protection and mosquitoes control to achieve rapid reduction of dengue cases in India.
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MacCormack-Gelles B, Lima Neto AS, Sousa GS, Nascimento OJ, Machado MMT, Wilson ME, Castro MC. Epidemiological characteristics and determinants of dengue transmission during epidemic and non-epidemic years in Fortaleza, Brazil: 2011-2015. PLoS Negl Trop Dis 2018; 12:e0006990. [PMID: 30507968 PMCID: PMC6292645 DOI: 10.1371/journal.pntd.0006990] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2017] [Revised: 12/13/2018] [Accepted: 11/12/2018] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND After being eliminated during the 1950s, dengue reemerged in Brazil in the 1980s. Since then, incidence of the disease has increased, as serotypes move within and between cities. The co-circulation of multiple serotypes contributes to cycles of epidemic and interepidemic years, and a seasonal pattern of transmission is observed annually. Little is known regarding possible differences in the epidemiology of dengue under epidemic and interepidemic scenarios. This study addresses this gap and aims to assess the epidemiological characteristics and determinants of epidemic and interepidemic dengue transmission, utilizing data from the 5th largest city in Brazil (Fortaleza), at fine spatial and temporal scales. METHODS/PRINCIPAL FINDINGS Longitudinal models of monthly rates of confirmed dengue cases were used to estimate the differential contribution of contextual factors to dengue transmission in Fortaleza between 2011 and 2015. Models were stratified by annual climatological schedules and periods of interepidemic and epidemic transmission, controlling for social, economic, structural, entomological, and environmental factors. Results revealed distinct seasonal patterns between interepidemic and epidemic years, with persistent transmission after June in interepidemic years. Dengue was strongly associated with violence across strata, and with poverty and irregular garbage collection during periods of low transmission, but not with other indicators of public service provision or structural deprivation. Scrapyards and sites associated with tire storage were linked to incidence differentially between seasons, with the strongest associations during transitional precipitation periods. Hierarchical clustering analysis suggests that the dengue burden concentrates in the southern periphery of the city, particularly during periods of minimal transmission. CONCLUSIONS/SIGNIFICANCE Our findings have direct programmatic implications. Vector control operations must be sustained after June even in non-epidemic years. More specifically, scrapyards and sites associated with tires (strongly associated with incidence during periods of minimal transmission), require sustained entomological surveillance, particularly during interepidemic intervals and in the urban periphery. Intersectoral collaborations that address urban violence are critical for facilitating the regular activities of vector control agents.
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Affiliation(s)
- Benjamin MacCormack-Gelles
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Antonio S. Lima Neto
- Fortaleza Municipal Health Secretariat (SMS-Fortaleza), Fortaleza, Ceará, Brazil
- University of Fortaleza (UNIFOR), Fortaleza, Ceará, Brazil
| | - Geziel S. Sousa
- Fortaleza Municipal Health Secretariat (SMS-Fortaleza), Fortaleza, Ceará, Brazil
| | - Osmar J. Nascimento
- Fortaleza Municipal Health Secretariat (SMS-Fortaleza), Fortaleza, Ceará, Brazil
| | | | - Mary E. Wilson
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- School of Medicine, University of California, San Francisco, California, United States of America
| | - Marcia C. Castro
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
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Tang B, Huo X, Xiao Y, Ruan S, Wu J. A conceptual model for optimizing vaccine coverage to reduce vector-borne infections in the presence of antibody-dependent enhancement. Theor Biol Med Model 2018; 15:13. [PMID: 30173664 PMCID: PMC6120075 DOI: 10.1186/s12976-018-0085-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Accepted: 07/13/2018] [Indexed: 11/10/2022] Open
Abstract
Background Many vector-borne diseases co-circulate, as the viruses from the same family are also transmitted by the same vector species. For example, Zika and dengue viruses belong to the same Flavivirus family and are primarily transmitted by a common mosquito species Aedes aegypti. Zika outbreaks have also commonly occurred in dengue-endemic areas, and co-circulation and co-infection of both viruses have been reported. As recent immunological cross-reactivity studies have confirmed that convalescent plasma following dengue infection can enhance Zika infection, and as global efforts of developing dengue and Zika vaccines are intensified, it is important to examine whether and how vaccination against one disease in a large population may affect infection dynamics of another disease due to antibody-dependent enhancement. Methods Through a conceptual co-infection dynamics model parametrized by reported dengue and Zika epidemic and immunological cross-reactivity characteristics, we evaluate impact of a hypothetical dengue vaccination program on Zika infection dynamics in a single season when only one particular dengue serotype is involved. Results We show that an appropriately designed and optimized dengue vaccination program can not only help control the dengue spread but also, counter-intuitively, reduce Zika infections. We identify optimal dengue vaccination coverages for controlling dengue and simultaneously reducing Zika infections, as well as the critical coverages exceeding which dengue vaccination will increase Zika infections. Conclusion This study based on a conceptual model shows the promise of an integrative vector-borne disease control strategy involving optimal vaccination programs, in regions where different viruses or different serotypes of the same virus co-circulate, and convalescent plasma following infection from one virus (serotype) can enhance infection against another virus (serotype). The conceptual model provides a first step towards well-designed regional and global vector-borne disease immunization programs.
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Affiliation(s)
- Biao Tang
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China.,Centre for Disease Modelling, Laboratory for Industrial and Applied Mathematics, York University, Toronto, M3J 1P3, Canada
| | - Xi Huo
- Centre for Disease Modelling, Laboratory for Industrial and Applied Mathematics, York University, Toronto, M3J 1P3, Canada.,Department of Mathematics, University of Miami, Coral Gables, 33146, USA
| | - Yanni Xiao
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China
| | - Shigui Ruan
- Department of Mathematics, University of Miami, Coral Gables, 33146, USA
| | - Jianhong Wu
- Centre for Disease Modelling, Laboratory for Industrial and Applied Mathematics, York University, Toronto, M3J 1P3, Canada.
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Moore SM, Ten Bosch QA, Siraj AS, Soda KJ, España G, Campo A, Gómez S, Salas D, Raybaud B, Wenger E, Welkhoff P, Perkins TA. Local and regional dynamics of chikungunya virus transmission in Colombia: the role of mismatched spatial heterogeneity. BMC Med 2018; 16:152. [PMID: 30157921 PMCID: PMC6116375 DOI: 10.1186/s12916-018-1127-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Accepted: 07/12/2018] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Mathematical models of transmission dynamics are routinely fitted to epidemiological time series, which must inevitably be aggregated at some spatial scale. Weekly case reports of chikungunya have been made available nationally for numerous countries in the Western Hemisphere since late 2013, and numerous models have made use of this data set for forecasting and inferential purposes. Motivated by an abundance of literature suggesting that the transmission of this mosquito-borne pathogen is localized at scales much finer than nationally, we fitted models at three different spatial scales to weekly case reports from Colombia to explore limitations of analyses of nationally aggregated time series data. METHODS We adapted the recently developed Disease Transmission Kernel (DTK)-Dengue model for modeling chikungunya virus (CHIKV) transmission, given the numerous similarities of these viruses vectored by a common mosquito vector. We fitted versions of this model specified at different spatial scales to weekly case reports aggregated at different spatial scales: (1) single-patch national model fitted to national data; (2) single-patch departmental models fitted to departmental data; and (3) multi-patch departmental models fitted to departmental data, where the multiple patches refer to municipalities within a department. We compared the consistency of simulations from fitted models with empirical data. RESULTS We found that model consistency with epidemic dynamics improved with increasing spatial granularity of the model. Specifically, the sum of single-patch departmental model fits better captured national-level temporal patterns than did a single-patch national model. Likewise, multi-patch departmental model fits better captured department-level temporal patterns than did single-patch departmental model fits. Furthermore, inferences about municipal-level incidence based on multi-patch departmental models fitted to department-level data were positively correlated with municipal-level data that were withheld from model fitting. CONCLUSIONS Our model performed better when posed at finer spatial scales, due to better matching between human populations with locally relevant risk. Confronting spatially aggregated models with spatially aggregated data imposes a serious structural constraint on model behavior by averaging over epidemiologically meaningful spatial variation in drivers of transmission, impairing the ability of models to reproduce empirical patterns.
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Affiliation(s)
- Sean M Moore
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA.
| | - Quirine A Ten Bosch
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, 75015, Paris, France
- CNRS UMR2000: Génomique évolutive, modélisation et santé (GEMS), Institut Pasteur, Paris, France
- Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, 75015, Paris, France
| | - Amir S Siraj
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA
| | - K James Soda
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA
| | - Guido España
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA
| | - Alfonso Campo
- Subdirección de Análisis de Riesgo y Respuesta Inmediata en Salud Pública, Instituto Nacional de Salud de Colombia, Bogotá, Colombia
| | - Sara Gómez
- Grupo de Enfermedades Transmisibles, Instituto Nacional de Salud de Colombia, Bogotá, Colombia
| | - Daniela Salas
- Grupo de Enfermedades Transmisibles, Instituto Nacional de Salud de Colombia, Bogotá, Colombia
| | | | | | | | - T Alex Perkins
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN, USA.
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Imran M, Usman M, Malik T, Ansari AR. Mathematical analysis of the role of hospitalization/isolation in controlling the spread of Zika fever. Virus Res 2018; 255:95-104. [PMID: 30003923 PMCID: PMC7127007 DOI: 10.1016/j.virusres.2018.07.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 06/27/2018] [Accepted: 07/03/2018] [Indexed: 11/27/2022]
Abstract
The Zika virus is transmitted to humans primarily through Aedes mosquitoes and through sexual contact. It is documented that the virus can be transmitted to newborn babies from their mothers. We consider a deterministic model for the transmission dynamics of the Zika virus infectious disease that spreads in, both humans and vectors, through horizontal and vertical transmission. The total populations of both humans and mosquitoes are assumed to be constant. Our models consist of a system of eight differential equations describing the human and vector populations during the different stages of the disease. We have included the hospitalization/isolation class in our model to see the effect of the controlling strategy. We determine the expression for the basic reproductive number R0 in terms of horizontal as well as vertical disease transmission rates. An in-depth stability analysis of the model is performed, and it is consequently shown, that the model has a globally asymptotically stable disease-free equilibrium when the basic reproduction number R0 < 1. It is also shown that when R0 > 1, there exists a unique endemic equilibrium. We showed that the endemic equilibrium point is globally asymptotically stable when it exists. We were able to prove this result in a reduced model. Furthermore, we conducted an uncertainty and sensitivity analysis to recognize the impact of crucial model parameters on R0. The uncertainty analysis yields an estimated value of the basic reproductive number R0 = 1.54. Assuming infection prevalence in the population under constant control, optimal control theory is used to devise an optimal hospitalization/isolation control strategy for the model. The impact of isolation on the number of infected individuals and the accumulated cost is assessed and compared with the constant control case.
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Affiliation(s)
- Mudassar Imran
- International Center for Applied Mathematics and Computational Bioengineering, Department of Mathematics and Natural Sciences, Gulf University for Science & Technology, Mishref, Kuwait.
| | - Muhammad Usman
- Department of Mathematics, University of Dayton, Dayton, OH 45469-2316, USA
| | - Tufail Malik
- Department of Science and Mathematics, Arizona State University, Mesa, AZ 85212, USA
| | - Ali R Ansari
- International Center for Applied Mathematics and Computational Bioengineering, Department of Mathematics and Natural Sciences, Gulf University for Science & Technology, Mishref, Kuwait
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Zou L, Chen J, Feng X, Ruan S. Analysis of a Dengue Model with Vertical Transmission and Application to the 2014 Dengue Outbreak in Guangdong Province, China. Bull Math Biol 2018; 80:2633-2651. [PMID: 30083966 DOI: 10.1007/s11538-018-0480-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Accepted: 07/23/2018] [Indexed: 11/25/2022]
Abstract
There is evidence showing that vertical transmission of dengue virus exists in Aedes mosquitoes. In this paper, we propose a deterministic dengue model with vertical transmission in mosquitoes by including aquatic mosquitoes (eggs, larvae and pupae), adult mosquitoes (susceptible, exposed and infectious) and human hosts (susceptible, exposed, infectious and recovered). We first analyze the existence and stability of disease-free equilibria, calculate the basic reproduction number and discuss the existence of the disease-endemic equilibrium. Then, we study the impact of vertical transmission of the virus in mosquitoes on the spread dynamics of dengue. We also use the model to simulate the reported infected human data from the 2014 dengue outbreak in Guangdong Province, China, carry out sensitivity analysis of the basic reproduction number in terms of the model parameters, and seek for effective control measures for the transmission of dengue virus.
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Affiliation(s)
- Lan Zou
- Department of Mathematics, Sichuan University, Chengdu, 610064, Sichuan, China
| | - Jing Chen
- Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, 3301 College Ave., Fort Lauderdale, FL, 33314, USA
| | - Xiaomei Feng
- Department of Mathematics, Yuncheng University, Yuncheng, 044000, Shanxi, China
| | - Shigui Ruan
- Department of Mathematics, University of Miami, Coral Gables, FL, 33146, USA.
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Lee H, Kim JE, Lee S, Lee CH. Potential effects of climate change on dengue transmission dynamics in Korea. PLoS One 2018; 13:e0199205. [PMID: 29953493 PMCID: PMC6023222 DOI: 10.1371/journal.pone.0199205] [Citation(s) in RCA: 37] [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: 03/15/2018] [Accepted: 06/04/2018] [Indexed: 11/22/2022] Open
Abstract
Dengue fever is a major international public health concern, with more than 55% of the world population at risk of infection. Recent climate changes related to global warming have increased the potential risk of domestic outbreaks of dengue in Korea. In this study, we develop a two-strain dengue model associated with climate-dependent parameters based on Representative Concentration Pathway (RCP) scenarios provided by the Korea Meteorological Administration. We assess the potential risks of dengue outbreaks by means of the vector capacity and intensity under various RCP scenarios. A sensitivity analysis of the temperature-dependent parameters is performed to explore the effects of climate change on dengue transmission dynamics. Our results demonstrate that a higher temperature significantly enhances the potential threat of domestic dengue outbreaks in Korea. Furthermore, we investigate the effects of countermeasures on the cumulative incidence of humans and vectors. The current main control measures (comprising only travel restrictions) for infected humans in Korea are not as effective as combined control measures (travel restrictions and vector control), dramatically reducing the possibilities of dengue outbreaks.
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Affiliation(s)
- Hyojung Lee
- Graduate School of Medicine, Hokkaido University, Sapporo, Japan
| | - Jung Eun Kim
- Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
| | - Sunmi Lee
- Department of Applied Mathematics, Kyung Hee University, Yongin, Republic of Korea
| | - Chang Hyeong Lee
- Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
- * E-mail:
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Zarnitsyna VI, Bulusheva I, Handel A, Longini IM, Halloran ME, Antia R. Intermediate levels of vaccination coverage may minimize seasonal influenza outbreaks. PLoS One 2018; 13:e0199674. [PMID: 29944709 PMCID: PMC6019388 DOI: 10.1371/journal.pone.0199674] [Citation(s) in RCA: 5] [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: 01/24/2018] [Accepted: 06/12/2018] [Indexed: 11/30/2022] Open
Abstract
For most pathogens, vaccination reduces the spread of the infection and total number of cases; thus, public policy usually advocates maximizing vaccination coverage. We use simple mathematical models to explore how this may be different for pathogens, such as influenza, which exhibit strain variation. Our models predict that the total number of seasonal influenza infections is minimized at an intermediate (rather than maximal) level of vaccination, and, somewhat counter-intuitively, further increasing the level of the vaccination coverage may lead to higher number of influenza infections and be detrimental to the public interest. This arises due to the combined effects of: competition between multiple co-circulating strains; limited breadth of protection afforded by the vaccine; and short-term strain-transcending immunity following natural infection. The study highlights the need for better quantification of the components of vaccine efficacy and longevity of strain-transcending cross-immunity in order to generate nuanced recommendations for influenza vaccine coverage levels.
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Affiliation(s)
- Veronika I. Zarnitsyna
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA, 30322, United States of America
- * E-mail: (VZ); (RA)
| | - Irina Bulusheva
- Department of Biological and Medical Physics, Moscow Institute of Physics and Technology, Dolgoprudny, 141701, Russia
| | - Andreas Handel
- Department of Epidemiology and Biostatistics, University of Georgia, Athens, GA, 30602, United States of America
| | - Ira M. Longini
- Department of Biostatistics, University of Florida, Gainesville, FL, 32611, United States of America
| | - M. Elizabeth Halloran
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, 98109, United States of America
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Rustom Antia
- Department of Biology, Emory University, Atlanta, GA, 30322, United States of America
- * E-mail: (VZ); (RA)
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Salje H, Cummings DAT, Rodriguez-Barraquer I, Katzelnick LC, Lessler J, Klungthong C, Thaisomboonsuk B, Nisalak A, Weg A, Ellison D, Macareo L, Yoon IK, Jarman R, Thomas S, Rothman AL, Endy T, Cauchemez S. Reconstruction of antibody dynamics and infection histories to evaluate dengue risk. Nature 2018; 557:719-723. [PMID: 29795354 PMCID: PMC6064976 DOI: 10.1038/s41586-018-0157-4] [Citation(s) in RCA: 183] [Impact Index Per Article: 30.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Accepted: 04/24/2018] [Indexed: 11/25/2022]
Abstract
As with many pathogens, most dengue infections are subclinical and therefore unobserved1. Coupled with limited understanding of the dynamical behavior of potential serological markers of infection, this observational problem has wide-ranging implications, including hampering our understanding of individual- and population-level correlates of infection and disease risk and how they change over time, assay interpretation and cohort design. We develop a framework that simultaneously characterizes antibody dynamics and identifies subclinical infections via Bayesian augmentation from detailed cohort data (3,451 individuals with blood draws every 91 days, 143,548 hemagglutination inhibition assay titer measurements)2,3. We identify 1,149 infections (95% CI: 1,135–1,163) that were not detected by active surveillance and estimate that 65% of infections are subclinical. Post infection, individuals develop a stable setpoint antibody load after 1y that places them within or outside a risk window. Individuals with pre-existing titers of ≤1:40 develop hemorrhagic fever 7.4 (95% CI: 2.5–8.2) times as often as naïve individuals compared to 0.0 times for individuals with titers >1:40 (95% CI: 0.0–1.3). PRNT titers ≤1:100 were similarly associated with severe disease. Across the population, variability in the force of infection results in large-scale temporal changes in infection and disease risk that correlate poorly with age.
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Affiliation(s)
- Henrik Salje
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France. .,CNRS UMR2000, Génomique évolutive, modélisation et santé (GEMS), Institut Pasteur, Paris, France. .,Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, France. .,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
| | - Derek A T Cummings
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.,Department of Biology, University of Florida, Gainesville, FL, USA.,Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | | | | | - Justin Lessler
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Chonticha Klungthong
- 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
| | - Ananda Nisalak
- Department of Virology, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Alden Weg
- Department of Virology, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Damon Ellison
- Department of Virology, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - Louis Macareo
- Department of Virology, Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand
| | - In-Kyu Yoon
- International Vaccine Institute, Seoul, South Korea
| | - Richard Jarman
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MD, USA
| | - Stephen Thomas
- Department of Medicine, Upstate Medical University of New York, Syracuse, NY, USA
| | - Alan L Rothman
- Institute for Immunology and Informatics, Department of Cell and Molecular Biology, University of Rhode Island, Providence, RI, USA
| | - Timothy Endy
- Department of Medicine, Upstate Medical University of New York, Syracuse, NY, USA
| | - Simon Cauchemez
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France.,CNRS UMR2000, Génomique évolutive, modélisation et santé (GEMS), Institut Pasteur, Paris, France.,Center of Bioinformatics, Biostatistics and Integrative Biology, Institut Pasteur, Paris, France
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63
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64
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Vincenti-Gonzalez MF, Tami A, Lizarazo EF, Grillet ME. ENSO-driven climate variability promotes periodic major outbreaks of dengue in Venezuela. Sci Rep 2018; 8:5727. [PMID: 29636483 PMCID: PMC5893565 DOI: 10.1038/s41598-018-24003-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Accepted: 03/20/2018] [Indexed: 11/19/2022] Open
Abstract
Dengue is a mosquito-borne viral disease of global impact. In Venezuela, dengue has emerged as one of the most important public health problems of urban areas with frequent epidemics since 2001. The long-term pattern of this disease has involved not only a general upward trend in cases but also a dramatic increase in the size and frequency of epidemic outbreaks. By assuming that climate variability has a relevant influence on these changes in time, we quantified the periodicity of dengue incidence in time-series of data from two northern regions of Venezuela. Disease cycles of 1 and 3-4 years (p < 0.05) were detected. We determined that dengue cycles corresponded with local climate and the El Niño Southern Oscillation (ENSO) variation at both seasonal and inter-annual scales (every 2-3 years). Dengue incidence peaks were more prevalent during the warmer and dryer years of El Niño confirming that ENSO is a regional climatic driver of such long-term periodicity through local changes in temperature and rainfall. Our findings support the evidence of the effect of climate on dengue dynamics and advocate the incorporation of climate information in the surveillance and prediction of this arboviral disease in Venezuela.
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Affiliation(s)
- M F Vincenti-Gonzalez
- Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - A Tami
- Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
- Departamento de Parasitología, Facultad de Ciencias de la Salud, Universidad de Carabobo, Valencia, Venezuela.
| | - E F Lizarazo
- Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - M E Grillet
- Laboratorio de Biología de Vectores y Parásitos, Instituto de Zoología y Ecología Tropical, Facultad de Ciencias, Universidad Central de Venezuela, Caracas, Venezuela.
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65
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Lourenço J, Tennant W, Faria NR, Walker A, Gupta S, Recker M. Challenges in dengue research: A computational perspective. Evol Appl 2018; 11:516-533. [PMID: 29636803 PMCID: PMC5891037 DOI: 10.1111/eva.12554] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Accepted: 09/08/2017] [Indexed: 01/12/2023] Open
Abstract
The dengue virus is now the most widespread arbovirus affecting human populations, causing significant economic and social impact in South America and South-East Asia. Increasing urbanization and globalization, coupled with insufficient resources for control, misguided policies or lack of political will, and expansion of its mosquito vectors are some of the reasons why interventions have so far failed to curb this major public health problem. Computational approaches have elucidated on dengue's population dynamics with the aim to provide not only a better understanding of the evolution and epidemiology of the virus but also robust intervention strategies. It is clear, however, that these have been insufficient to address key aspects of dengue's biology, many of which will play a crucial role for the success of future control programmes, including vaccination. Within a multiscale perspective on this biological system, with the aim of linking evolutionary, ecological and epidemiological thinking, as well as to expand on classic modelling assumptions, we here propose, discuss and exemplify a few major computational avenues-real-time computational analysis of genetic data, phylodynamic modelling frameworks, within-host model frameworks and GPU-accelerated computing. We argue that these emerging approaches should offer valuable research opportunities over the coming years, as previously applied and demonstrated in the context of other pathogens.
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Affiliation(s)
| | - Warren Tennant
- Centre for Mathematics and the EnvironmentUniversity of ExeterPenrynUK
| | | | | | | | - Mario Recker
- Centre for Mathematics and the EnvironmentUniversity of ExeterPenrynUK
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66
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Lauer SA, Sakrejda K, Ray EL, Keegan LT, Bi Q, Suangtho P, Hinjoy S, Iamsirithaworn S, Suthachana S, Laosiritaworn Y, Cummings DAT, Lessler J, Reich NG. Prospective forecasts of annual dengue hemorrhagic fever incidence in Thailand, 2010-2014. Proc Natl Acad Sci U S A 2018; 115:E2175-E2182. [PMID: 29463757 PMCID: PMC5877997 DOI: 10.1073/pnas.1714457115] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Dengue hemorrhagic fever (DHF), a severe manifestation of dengue viral infection that can cause severe bleeding, organ impairment, and even death, affects between 15,000 and 105,000 people each year in Thailand. While all Thai provinces experience at least one DHF case most years, the distribution of cases shifts regionally from year to year. Accurately forecasting where DHF outbreaks occur before the dengue season could help public health officials prioritize public health activities. We develop statistical models that use biologically plausible covariates, observed by April each year, to forecast the cumulative DHF incidence for the remainder of the year. We perform cross-validation during the training phase (2000-2009) to select the covariates for these models. A parsimonious model based on preseason incidence outperforms the 10-y median for 65% of province-level annual forecasts, reduces the mean absolute error by 19%, and successfully forecasts outbreaks (area under the receiver operating characteristic curve = 0.84) over the testing period (2010-2014). We find that functions of past incidence contribute most strongly to model performance, whereas the importance of environmental covariates varies regionally. This work illustrates that accurate forecasts of dengue risk are possible in a policy-relevant timeframe.
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Affiliation(s)
- Stephen A Lauer
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA 01003;
| | - Krzysztof Sakrejda
- Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA 01003
| | - Evan L Ray
- Department of Mathematics and Statistics, Mount Holyoke College, South Hadley, MA 01075
| | - Lindsay T Keegan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205
| | - Qifang Bi
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205
| | - Paphanij Suangtho
- Bureau of Epidemiology, Ministry of Public Health, Nonthaburi 11000, Thailand
| | - Soawapak Hinjoy
- Bureau of Epidemiology, Ministry of Public Health, Nonthaburi 11000, Thailand
| | - Sopon Iamsirithaworn
- Department of Disease Control, Bureau of Epidemiology, Ministry of Public Health, Nonthaburi 11000, Thailand
| | - Suthanun Suthachana
- Bureau of Epidemiology, Ministry of Public Health, Nonthaburi 11000, Thailand
| | | | - Derek A T Cummings
- Department of Biology and the Emerging Pathogens Institute, University of Florida, Gainesville, FL 32611
| | - 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
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67
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Paull SH, Horton DE, Ashfaq M, Rastogi D, Kramer LD, Diffenbaugh NS, Kilpatrick AM. Drought and immunity determine the intensity of West Nile virus epidemics and climate change impacts. Proc Biol Sci 2018; 284:rspb.2016.2078. [PMID: 28179512 DOI: 10.1098/rspb.2016.2078] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2016] [Accepted: 01/12/2017] [Indexed: 11/12/2022] Open
Abstract
The effect of global climate change on infectious disease remains hotly debated because multiple extrinsic and intrinsic drivers interact to influence transmission dynamics in nonlinear ways. The dominant drivers of widespread pathogens, like West Nile virus, can be challenging to identify due to regional variability in vector and host ecology, with past studies producing disparate findings. Here, we used analyses at national and state scales to examine a suite of climatic and intrinsic drivers of continental-scale West Nile virus epidemics, including an empirically derived mechanistic relationship between temperature and transmission potential that accounts for spatial variability in vectors. We found that drought was the primary climatic driver of increased West Nile virus epidemics, rather than within-season or winter temperatures, or precipitation independently. Local-scale data from one region suggested drought increased epidemics via changes in mosquito infection prevalence rather than mosquito abundance. In addition, human acquired immunity following regional epidemics limited subsequent transmission in many states. We show that over the next 30 years, increased drought severity from climate change could triple West Nile virus cases, but only in regions with low human immunity. These results illustrate how changes in drought severity can alter the transmission dynamics of vector-borne diseases.
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Affiliation(s)
- Sara H Paull
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA .,Research Applications Lab, National Center for Atmospheric Research, 3450 Mitchell Ln, Boulder, CO 80301, USA
| | - Daniel E Horton
- Department of Earth and Planetary Sciences, Northwestern University, Evanston, IL 60208, USA.,Department of Earth System Science and Woods Institute for the Environment, Stanford University, Stanford, CA 94305, USA
| | - Moetasim Ashfaq
- Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Deeksha Rastogi
- Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
| | - Laura D Kramer
- Wadsworth Center, New York State Department of Health, Slingerlands, NY 12159, USA.,School of Public Health, Department of Biomedical Sciences, SUNY, Albany, NY 12201, USA
| | - Noah S Diffenbaugh
- Department of Earth System Science and Woods Institute for the Environment, Stanford University, Stanford, CA 94305, USA
| | - A Marm Kilpatrick
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, 1156 High St, Santa Cruz, CA 95064, USA
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68
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Katzelnick LC, Gresh L, Halloran ME, Mercado JC, Kuan G, Gordon A, Balmaseda A, Harris E. Antibody-dependent enhancement of severe dengue disease in humans. Science 2017; 358:929-932. [PMID: 29097492 PMCID: PMC5858873 DOI: 10.1126/science.aan6836] [Citation(s) in RCA: 702] [Impact Index Per Article: 100.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2017] [Accepted: 09/29/2017] [Indexed: 01/09/2023]
Abstract
For dengue viruses 1 to 4 (DENV1-4), a specific range of antibody titer has been shown to enhance viral replication in vitro and severe disease in animal models. Although suspected, such antibody-dependent enhancement of severe disease has not been shown to occur in humans. Using multiple statistical approaches to study a long-term pediatric cohort in Nicaragua, we show that risk of severe dengue disease is highest within a narrow range of preexisting anti-DENV antibody titers. By contrast, we observe protection from all symptomatic dengue disease at high antibody titers. Thus, immune correlates of severe dengue must be evaluated separately from correlates of protection against symptomatic disease. These results have implications for studies of dengue pathogenesis and for vaccine development, because enhancement, not just lack of protection, is of concern.
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Affiliation(s)
- Leah C. Katzelnick
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, CA, USA
| | - Lionel Gresh
- Sustainable Sciences Institute, Managua, Nicaragua
| | - M. Elizabeth Halloran
- Department of Biostatistics, University of Washington, WA, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Juan Carlos Mercado
- Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua
| | - Guillermina Kuan
- Centro de Salud Sócrates Flores Vivas, Ministry of Health, Managua, Nicaragua
| | - Aubree Gordon
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Angel Balmaseda
- Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua
| | - Eva Harris
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, CA, USA
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69
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Faria NR, da Costa AC, Lourenço J, Loureiro P, Lopes ME, Ribeiro R, Alencar CS, Kraemer MUG, Villabona-Arenas CJ, Wu CH, Thézé J, Khan K, Brent SE, Romano C, Delwart E, Custer B, Busch MP, Pybus OG, Sabino EC. Genomic and epidemiological characterisation of a dengue virus outbreak among blood donors in Brazil. Sci Rep 2017; 7:15216. [PMID: 29123142 PMCID: PMC5680240 DOI: 10.1038/s41598-017-15152-8] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Accepted: 10/20/2017] [Indexed: 01/20/2023] Open
Abstract
Outbreaks caused by Dengue, Zika and Chikungunya viruses can spread rapidly in immunologically naïve populations. By analysing 92 newly generated viral genome sequences from blood donors and recipients, we assess the dynamics of dengue virus serotype 4 during the 2012 outbreak in Rio de Janeiro. Phylogenetic analysis indicates that the outbreak was caused by genotype II, although two isolates of genotype I were also detected for the first time in Rio de Janeiro. Evolutionary analysis and modelling estimates are congruent, indicating a reproduction number above 1 between January and June, and at least two thirds of infections being unnoticed. Modelling analysis suggests that viral transmission started in early January, which is consistent with multiple introductions, most likely from the northern states of Brazil, and with an increase in within-country air travel to Rio de Janeiro. The combination of genetic and epidemiological data from blood donor banks may be useful to anticipate epidemic spread of arboviruses.
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Affiliation(s)
- Nuno R Faria
- Department of Zoology, University of Oxford, Oxford, United Kingdom.
| | - Antonio Charlys da Costa
- Instituto de Medicina Tropical, Universidade de São Paulo, São Paulo, Brazil. .,LIM46, Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.
| | - José Lourenço
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Paula Loureiro
- Faculdade de Ciências Médicas, Fundação Hemope, Recife, Brazil
| | | | - Roberto Ribeiro
- Instituto de Medicina Tropical, Universidade de São Paulo, São Paulo, Brazil.,LIM46, Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | | | | | | | - Chieh-Hsi Wu
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - Julien Thézé
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Kamran Khan
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada.,Division of Infectious Diseases, University of Toronto, Toronto, Ontario, Canada
| | - Shannon E Brent
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Camila Romano
- Instituto de Medicina Tropical, Universidade de São Paulo, São Paulo, Brazil
| | - Eric Delwart
- Blood Systems Research Institute, San Francisco, California, USA.,University of California San Francisco, San Francisco, California, USA
| | - Brian Custer
- Blood Systems Research Institute, San Francisco, California, USA.,University of California San Francisco, San Francisco, California, USA
| | - Michael P Busch
- Blood Systems Research Institute, San Francisco, California, USA.,University of California San Francisco, San Francisco, California, USA
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Ester C Sabino
- Instituto de Medicina Tropical, Universidade de São Paulo, São Paulo, Brazil. .,LIM46, Departamento de Moléstias Infecciosas e Parasitárias, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.
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70
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Lourenço J, Maia de Lima M, Faria NR, Walker A, Kraemer MU, Villabona-Arenas CJ, Lambert B, Marques de Cerqueira E, Pybus OG, Alcantara LC, Recker M. Epidemiological and ecological determinants of Zika virus transmission in an urban setting. eLife 2017; 6:29820. [PMID: 28887877 PMCID: PMC5638629 DOI: 10.7554/elife.29820] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Accepted: 09/04/2017] [Indexed: 12/29/2022] Open
Abstract
The Zika virus has emerged as a global public health concern. Its rapid geographic expansion is attributed to the success of Aedes mosquito vectors, but local epidemiological drivers are still poorly understood. Feira de Santana played a pivotal role in the Chikungunya epidemic in Brazil and was one of the first urban centres to report Zika infections. Using a climate-driven transmission model and notified Zika case data, we show that a low observation rate and high vectorial capacity translated into a significant attack rate during the 2015 outbreak, with a subsequent decline in 2016 and fade-out in 2017 due to herd-immunity. We find a potential Zika-related, low risk for microcephaly per pregnancy, but with significant public health impact given high attack rates. The balance between the loss of herd-immunity and viral re-importation will dictate future transmission potential of Zika in this urban setting. Mosquitoes can transmit viruses that cause Zika, dengue and several other tropical diseases that affect humans. Zika virus usually causes mild symptoms, but it is thought that infection during pregnancy can lead to brain abnormalities, including microcephaly, where babies are born with an abnormally small head. Recent studies have shed light on how the Zika virus spread from Africa to reach South America, the Caribbean and North America. However, much less is known about the ecological factors that contribute to the spread of the virus within towns, cities and other local areas. In 2015, Brazil was struck by an outbreak of the Zika virus that led to an international public health emergency. Lourenço et al. used a mathematical model to explore the local conditions within Feira de Santana (a major urban center in Brazil) that contributed to the outbreak. The model took into account numerous factors, including temperature, humidity, rainfall and the mosquito life-cycle, which made it possible to reconstruct the history of the virus over the past three years and to make projections for the next decades. It revealed that most of the infections occured during 2015, with approximately 65% of the population infected. The incidences of new infections declined in 2016, as increasing numbers of local people had already been exposed to the virus and became immune. Temperature and humidity appeared to have played a critical role in sustaining the mosquito population carrying the Zika virus. Further analysis suggests that the risk of Zika virus causing microcephaly is very low – only 0.3–0.5% of the pregnant women in Feira de Santana who were infected with Zika gave birth to a baby with the condition. What therefore makes Zika a public health concern is the combination of a low risk with very high infection rates, which can affect a large number of pregnancies. This study will help researchers and policy makers to predict how the Zika virus will behave in the coming years. It also highlights the limitations and successes of the current system of surveillance. Moreover, it will help to identify critical time periods in the year when mosquito control strategies should be implemented to limit the spread of this virus. In future, this could help shape new local strategies to control Zika virus, dengue and other diseases carried by mosquitoes.
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Affiliation(s)
- José Lourenço
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Maricelia Maia de Lima
- Laboratory of Haematology, Genetics and Computational Biology, FIOCRUZ, SalvadorBahia, Brazil
| | | | - Andrew Walker
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | | | - Christian Julian Villabona-Arenas
- Institut de Recherche pour le Développement, UMI 233, INSERM U1175 and Institut de Biologie Computationnelle, LIRMM, Université de Montpellier, Montpellier, France
| | - Ben Lambert
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Erenilde Marques de Cerqueira
- Centre of PostGraduation in Collective Health, Department of Health, Universidade Estadual de Feira de Santana, Feira de SantanaBahia, Brazil
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Luiz Cj Alcantara
- Laboratory of Haematology, Genetics and Computational Biology, FIOCRUZ, SalvadorBahia, Brazil
| | - Mario Recker
- Centre for Mathematics and the Environment, University of Exeter, Penryn, United Kingdom
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71
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Moghadas SM, Shoukat A, Espindola AL, Pereira RS, Abdirizak F, Laskowski M, Viboud C, Chowell G. Asymptomatic Transmission and the Dynamics of Zika Infection. Sci Rep 2017; 7:5829. [PMID: 28724972 PMCID: PMC5517554 DOI: 10.1038/s41598-017-05013-9] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Accepted: 06/02/2017] [Indexed: 11/09/2022] Open
Abstract
Following the 2013-14 outbreak in French Polynesia, the Zika virus (ZIKV) epidemic spread widely to many countries where Aedes Aegypti as the main transmitting vector is endemic. The lack of a second wave of ZIKV infection in most affected regions may suggest that a sufficiently high level of herd immunity was reached during the first wave. We developed an agent-based transmission model to investigate the role of asymptomatic infection on the likelihood of observing a second wave, while accounting for its relative transmissibility. We found that, as the relative transmissibility of asymptomatic infection increases, a second wave is more likely to occur, despite an increase in the attack rate during the first wave. When the reproduction number varies between 1.9 and 2.8 based on estimates for Antioquia, Colombia, the attack rate varies between 4% and 26% for a low (below 10%) effectiveness of interventions in blunting the ZIKV transmission from symptomatic cases to mosquitoes. Moreover, the fraction of cases due to sexual transmission is estimated below 4% of the cumulative incidence. Our analyses underscore the need to quantify the transmissibility of asymptomatic infections, without which the overall attack rates and the level of herd immunity cannot be accurately estimated.
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Affiliation(s)
- Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Canada.
| | - Affan Shoukat
- Agent-Based Modelling Laboratory, York University, Toronto, Canada
| | - Aquino L Espindola
- Departamento de Física, Instituto de Ciências Exatas - ICEx, Universidade Federal Fluminense, Volta Redonda, RJ, Brazil
| | - Rafael S Pereira
- Departamento de Física, Instituto de Ciências Exatas - ICEx, Universidade Federal Fluminense, Volta Redonda, RJ, Brazil
| | - Fatima Abdirizak
- Division of Epidemiology and Biostatistics, School of Public Health, Georgia State University, Atlanta, GA, USA
| | - Marek Laskowski
- Agent-Based Modelling Laboratory, York University, Toronto, Canada
| | - Cecile Viboud
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| | - Gerardo Chowell
- Division of Epidemiology and Biostatistics, School of Public Health, Georgia State University, Atlanta, GA, USA
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
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72
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Cable J, Barber I, Boag B, Ellison AR, Morgan ER, Murray K, Pascoe EL, Sait SM, Wilson AJ, Booth M. Global change, parasite transmission and disease control: lessons from ecology. Philos Trans R Soc Lond B Biol Sci 2017; 372:20160088. [PMID: 28289256 PMCID: PMC5352815 DOI: 10.1098/rstb.2016.0088] [Citation(s) in RCA: 138] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/25/2016] [Indexed: 02/06/2023] Open
Abstract
Parasitic infections are ubiquitous in wildlife, livestock and human populations, and healthy ecosystems are often parasite rich. Yet, their negative impacts can be extreme. Understanding how both anticipated and cryptic changes in a system might affect parasite transmission at an individual, local and global level is critical for sustainable control in humans and livestock. Here we highlight and synthesize evidence regarding potential effects of 'system changes' (both climatic and anthropogenic) on parasite transmission from wild host-parasite systems. Such information could inform more efficient and sustainable parasite control programmes in domestic animals or humans. Many examples from diverse terrestrial and aquatic natural systems show how abiotic and biotic factors affected by system changes can interact additively, multiplicatively or antagonistically to influence parasite transmission, including through altered habitat structure, biodiversity, host demographics and evolution. Despite this, few studies of managed systems explicitly consider these higher-order interactions, or the subsequent effects of parasite evolution, which can conceal or exaggerate measured impacts of control actions. We call for a more integrated approach to investigating transmission dynamics, which recognizes these complexities and makes use of new technologies for data capture and monitoring, and to support robust predictions of altered parasite dynamics in a rapidly changing world.This article is part of the themed issue 'Opening the black box: re-examining the ecology and evolution of parasite transmission'.
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Affiliation(s)
- Joanne Cable
- School of Biosciences, Cardiff University, Cardiff CF10 3AX, UK
| | - Iain Barber
- Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester LE1 7RH, UK
| | - Brian Boag
- The James Hutton Institute, Invergowrie, Dundee DD2 5DA, UK
| | - Amy R Ellison
- School of Biosciences, Cardiff University, Cardiff CF10 3AX, UK
| | - Eric R Morgan
- School of Veterinary Sciences, University of Bristol, Bristol BS40 5DU, UK
| | - Kris Murray
- Grantham Institute - Climate Change and the Environment, Faculty of Natural Sciences, Imperial College London, Exhibition Road, London SW7 2AZ, UK
| | - Emily L Pascoe
- School of Biosciences, Cardiff University, Cardiff CF10 3AX, UK
- Department of Biodiversity and Molecular Ecology, Centre for Research and Innovation, Fondazione Edmund Mach, Via E. Mach 1, 38010 S. Michele all'Adige, Trentino, Italy
| | - Steven M Sait
- School of Biology, University of Leeds, Leeds LS2 9JT, UK
| | - Anthony J Wilson
- Vector-borne Viral Diseases Programme, The Pirbright Institute, Ash Road, Pirbright, Woking GU24 0NF, UK
| | - Mark Booth
- School of Medicine, Pharmacy and Health, Durham University, Durham TS17 6BH, UK
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73
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Optimal control problems of mosquito-borne disease subject to changes in feeding behavior of Aedes mosquitoes. Biosystems 2017; 156-157:23-39. [PMID: 28385591 DOI: 10.1016/j.biosystems.2017.03.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Revised: 03/12/2017] [Accepted: 03/30/2017] [Indexed: 11/23/2022]
Abstract
Dengue viruses (DENV) are transmitted to humans by the bite of Aedes mosquitoes. It is known that dengue virus infection in Aedes aegypti female mosquitoes makes a change in the feeding behavior of the infected mosquitoes. In this study, using the forces of infection, we incorporated the effect of changes in the feeding behavior of mosquitoes into the standard vector-borne SIR-SI model. It has been proved that both a single-strain model and a two-strain model exhibit forward bifurcations. Moreover, optimal implementations of control with specific prevention measures for dengue transmission are analyzed. As a result we found that more implementation of controls on the secondary infection of humans should be considered for the behavioral changes in feeding of the infected mosquitoes.
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74
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Kim JE, Lee H, Lee CH, Lee S. Assessment of optimal strategies in a two-patch dengue transmission model with seasonality. PLoS One 2017; 12:e0173673. [PMID: 28301523 PMCID: PMC5354280 DOI: 10.1371/journal.pone.0173673] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2016] [Accepted: 02/26/2017] [Indexed: 11/19/2022] Open
Abstract
Emerging and re-emerging dengue fever has posed serious problems to public health officials in many tropical and subtropical countries. Continuous traveling in seasonally varying areas makes it more difficult to control the spread of dengue fever. In this work, we consider a two-patch dengue model that can capture the movement of host individuals between and within patches using a residence-time matrix. A previous two-patch dengue model without seasonality is extended by adding host demographics and seasonal forcing in the transmission rates. We investigate the effects of human movement and seasonality on the two-patch dengue transmission dynamics. Motivated by the recent Peruvian dengue data in jungle/rural areas and coast/urban areas, our model mimics the seasonal patterns of dengue outbreaks in two patches. The roles of seasonality and residence-time configurations are highlighted in terms of the seasonal reproduction number and cumulative incidence. Moreover, optimal control theory is employed to identify and evaluate patch-specific control measures aimed at reducing dengue prevalence in the presence of seasonality. Our findings demonstrate that optimal patch-specific control strategies are sensitive to seasonality and residence-time scenarios. Targeting only the jungle (or endemic) is as effective as controlling both patches under weak coupling or symmetric mobility. However, focusing on intervention for the city (or high density areas) turns out to be optimal when two patches are strongly coupled with asymmetric mobility.
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Affiliation(s)
- Jung Eun Kim
- Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
| | - Hyojung Lee
- Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
| | - Chang Hyeong Lee
- Department of Mathematical Sciences, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
| | - Sunmi Lee
- Department of Applied Mathematics, Kyung Hee University, Yongin, Republic of Korea
- Institute of Natural Sciences, Kyung Hee University, Yongin, Republic of Korea
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75
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Katzelnick LC, Coloma J, Harris E. Dengue: knowledge gaps, unmet needs, and research priorities. THE LANCET. INFECTIOUS DISEASES 2017; 17:e88-e100. [PMID: 28185868 DOI: 10.1016/s1473-3099(16)30473-x] [Citation(s) in RCA: 117] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2016] [Revised: 08/29/2016] [Accepted: 10/18/2016] [Indexed: 01/09/2023]
Abstract
Dengue virus is a mosquito-borne pathogen that causes up to about 100 million cases of disease each year, placing a major public health, social, and economic burden on numerous low-income and middle-income countries. Major advances by investigators, vaccine developers, and affected communities are revealing new insights and enabling novel interventions and approaches to dengue prevention and control. Such research has highlighted further questions about both the basic understanding of dengue and efforts to develop new tools. In this report, the third in a Series on dengue, we discuss existing approaches to dengue diagnostics, disease prognosis, surveillance, and vector control in low-income and middle-income countries, as well as potential consequences of vaccine introduction. We also summarise current knowledge and recent insights into dengue epidemiology, immunology, and pathogenesis, and their implications for understanding natural infection and current and future vaccines.
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Affiliation(s)
- Leah C Katzelnick
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, CA, USA
| | - Josefina Coloma
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, CA, USA
| | - Eva Harris
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, CA, USA.
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76
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The Impact of the Newly Licensed Dengue Vaccine in Endemic Countries. PLoS Negl Trop Dis 2016; 10:e0005179. [PMID: 28002420 PMCID: PMC5176165 DOI: 10.1371/journal.pntd.0005179] [Citation(s) in RCA: 94] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2016] [Accepted: 11/09/2016] [Indexed: 11/22/2022] Open
Abstract
Background With approximately 3 billion people at risk of acquiring the infection, dengue fever is now considered the most important mosquito-borne viral disease in the world, with 390 million dengue infections occurring every year, of which 96 million manifest symptoms with any level of disease severity. Treatment of uncomplicated dengue cases is only supportive and severe dengue cases require hospital intensive care. A vaccine now licensed in several countries and developed by Sanofi Pasteur (CYD-TDV, named Dengvaxia), was able to protect, in the first 25 months of the two Phase III, 66% of a subset of 9–16 year old participants. However, a significantly lower efficacy (including negative vaccine efficacy) was noted for children younger than 9 years of age. Methodology/Principal Findings Analysis of year 3 results of phase III trials of Dengvaxia suggest high rates of protection of vaccinated partial dengue immunes but high rates of hospitalizations during breakthrough dengue infections of persons who were vaccinated when seronegative, with vaccine appearing to induce enhancing antibodies (ADE). An age structured model was developed based on Sanofi’s recommendation to vaccinate persons age 945 years in dengue endemic countries. The model was used to explore the clinical burden of two vaccination strategies: 1) Vaccinate 4 or 20% of individuals, ages 9–45 years, seropositives and seronegatives, and 2) vaccinate 4 or 20% of individuals, ages 9–45 years, who are dengue immune only. Conclusions/Significance Our results show that vaccinating dengue monotypic immune individuals prevents dengue hospitalizations, but at the same time dengue infections of vaccine-sensitized persons increases hospitalizations. When the vaccine is given only to partial immune individuals, after immunological screening of the population, disease burden decreases considerably. Caused by four antigenically related but distinct serotypes a tetravalent vaccine is needed to protect against the huge burden of dengue disease. Dengvaxia is a vaccine candidate now licensed in several countries for individuals 9–45 years of age living in endemic countries with at least 50% (preferably 70%) of seroprevalence. Modelers from Sanofi Pasteur have predicted that this vaccine has the potential to reduce by about 50% the disease burden within 5 years when 20% of an endemic country population is vaccinated, thus achieving a World Health Organization dengue prevention goal. In this paper, mathematical modeling is used to investigate the impact of the newly licensed dengue vaccine using different scenarios. Our results show that to achieve significant reduction in disease burden, the vaccination program is most effective if it includes only individuals that have been already exposed to at least one dengue virus. Immunological screening of the population prior to vaccination is advised and vaccination strategies must be planned based on epidemiological disease dynamics for each specific endemic region.
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77
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Gjini E, Madec S. A slow-fast dynamic decomposition links neutral and non-neutral coexistence in interacting multi-strain pathogens. THEOR ECOL-NETH 2016. [DOI: 10.1007/s12080-016-0320-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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78
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Shim E. Dengue Dynamics and Vaccine Cost-Effectiveness Analysis in the Philippines. Am J Trop Med Hyg 2016; 95:1137-1147. [PMID: 27601519 PMCID: PMC5094230 DOI: 10.4269/ajtmh.16-0194] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Accepted: 08/01/2016] [Indexed: 01/05/2023] Open
Abstract
Dengue is one of the most problematic vector-borne diseases in the Philippines, with an estimated 842,867 cases resulting in medical costs of $345 million U.S. dollars annually. In December 2015, the first dengue vaccine, known as chimeric yellow fever virus-dengue virus tetravalent dengue vaccine, was approved for use in the Philippines and is given to children 9 years of age. To estimate the cost-effectiveness of dengue vaccination in the Philippines, we developed an age-structured model of dengue transmission and vaccination. Using our model, we compared two vaccination scenarios entailing routine vaccination programs both with and without catch-up vaccination. Our results indicate that the higher the cost of vaccination, the less cost-effective the dengue vaccination program. With the current dengue vaccination program that vaccinates children 9 years of age, dengue vaccination is cost-effective for vaccination costs up to $70 from a health-care perspective and up to $75 from a societal perspective. Under a favorable scenario consisting of 1 year of catch-up vaccinations that target children 9-15 years of age, followed by regular vaccination of 9-year-old children, vaccination is cost-effective at costs up to $72 from a health-care perspective and up to $78 from a societal perspective. In general, dengue vaccination is expected to reduce the incidence of both dengue fever and dengue hemorrhagic fever /dengue shock syndrome. Our results demonstrate that even at relatively low vaccine efficacies, age-targeted vaccination may still be cost-effective provided the vaccination cost is sufficiently low.
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Affiliation(s)
- Eunha Shim
- Department of Mathematics, Soongsil University, Seoul, Republic of Korea
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79
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Tang B, Xiao Y, Wu J. Implication of vaccination against dengue for Zika outbreak. Sci Rep 2016; 6:35623. [PMID: 27774987 PMCID: PMC5075941 DOI: 10.1038/srep35623] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2016] [Accepted: 10/04/2016] [Indexed: 01/23/2023] Open
Abstract
Zika virus co-circulates with dengue in tropical and sub-tropical regions. Cases of co-infection by dengue and Zika have been reported, the implication of this co-infection for an integrated intervention program for controlling both dengue and Zika must be addressed urgently. Here, we formulate a mathematical model to describe the transmission dynamics of co-infection of dengue and Zika with particular focus on the effects of Zika outbreak by vaccination against dengue among human hosts. Our analysis determines specific conditions under which vaccination against dengue can significantly increase the Zika outbreak peak, and speed up the Zika outbreak peak timing. Our results call for further study about the co-infection to direct an integrated control to balance the benefits for dengue control and the damages of Zika outbreak.
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Affiliation(s)
- Biao Tang
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, PR China
- Centre for Disease Modelling, York Institute for Health Research, York University, Toronto, ON, M3J 1P3, Canada
| | - Yanni Xiao
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, PR China
| | - Jianhong Wu
- Centre for Disease Modelling, York Institute for Health Research, York University, Toronto, ON, M3J 1P3, Canada
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80
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NDII MZ, ALLINGHAM D, HICKSON RI, GLASS K. The effect of Wolbachia on dengue dynamics in the presence of two serotypes of dengue: symmetric and asymmetric epidemiological characteristics. Epidemiol Infect 2016; 144:2874-82. [PMID: 27097518 PMCID: PMC9150425 DOI: 10.1017/s0950268816000753] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2015] [Revised: 03/10/2016] [Accepted: 03/31/2016] [Indexed: 12/22/2022] Open
Abstract
An innovative strategy to reduce dengue transmission uses the bacterium Wolbachia. We analysed the effects of Wolbachia on dengue transmission dynamics in the presence of two serotypes of dengue using a mathematical model, allowing for differences in the epidemiological characteristics of the serotypes. We found that Wolbachia has a greater effect on secondary infections than on primary infections across a range of epidemiological characteristics. If one serotype is more transmissible than the other, it will dominate primary infections and Wolbachia will be less effective at reducing secondary infections of either serotype. Differences in the antibody-dependent enhancement of the two serotypes have considerably less effect on the benefits of Wolbachia than differences in transmission probability. Even if the antibody-dependent enhancement rate is high, Wolbachia is still effective in reducing dengue. Our findings suggest that Wolbachia will be effective in the presence of more than one serotype of dengue; however, a better understanding of serotype-specific differences in transmission probability may be needed to optimize delivery of a Wolbachia intervention.
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Affiliation(s)
- M. Z. NDII
- School of Mathematical and Physical Sciences, The University of Newcastle, Australia
- Department of Mathematics, Nusa Cendana University, Kupang-NTT, Indonesia
| | - D. ALLINGHAM
- School of Mathematical and Physical Sciences, The University of Newcastle, Australia
| | - R. I. HICKSON
- School of Mathematical and Physical Sciences, The University of Newcastle, Australia
- IBM Research – Australia, Melbourne, Australia
| | - K. GLASS
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia
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81
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Wang X, Tang S, Cheke RA. A stage structured mosquito model incorporating effects of precipitation and daily temperature fluctuations. J Theor Biol 2016; 411:27-36. [PMID: 27693525 DOI: 10.1016/j.jtbi.2016.09.015] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2016] [Revised: 09/15/2016] [Accepted: 09/19/2016] [Indexed: 10/20/2022]
Abstract
An outbreak of dengue fever in Guangdong province in 2014 was the most serious outbreak ever recorded in China. Given the known positive correlation between the abundance of mosquitoes and the number of dengue fever cases, a stage structured mosquito model was developed to investigate the cause of the large abundance of mosquitoes in 2014 and its implications for outbreaks of the disease. Data on the Breteau index (number of containers positive for larvae per 100 premises investigated), temperature and precipitation were used for model fitting. The egg laying rate, the development rate and the mortality rates of immatures and adults were obtained from the estimated parameters. Moreover, effects of daily fluctuations of temperature on these parameters were obtained and the effects of temperature and precipitation were analyzed by simulations. Our results indicated that the abundance of mosquitoes depended not only on the total annual precipitation but also on the distribution of the precipitation. The daily mean temperature had a nonlinear relationship with the abundance of mosquitoes, and large diurnal temperature differences can reduce the abundance of mosquitoes. In addition, effects of increasing precipitation and temperature were interdependent. Our findings suggest that the large abundance of mosquitoes in 2014 was mainly caused by the distribution of the precipitation. In the perspective of mosquito control, our results reveal that it is better to clear water early and spray insecticide between April and August in case of limited resources.
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Affiliation(s)
- Xia Wang
- School of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710119, PR China.
| | - Sanyi Tang
- School of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710119, PR China.
| | - Robert A Cheke
- Natural Resources Institute, University of Greenwich at Medway, Central Avenue, Chatham Maritime, Chatham, Kent ME4 4TB, UK
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de Lima TFM, Lana RM, de Senna Carneiro TG, Codeço CT, Machado GS, Ferreira LS, de Castro Medeiros LC, Davis Junior CA. DengueME: A Tool for the Modeling and Simulation of Dengue Spatiotemporal Dynamics. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2016; 13:E920. [PMID: 27649226 PMCID: PMC5036753 DOI: 10.3390/ijerph13090920] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/15/2016] [Revised: 08/17/2016] [Accepted: 09/01/2016] [Indexed: 12/31/2022]
Abstract
The prevention and control of dengue are great public health challenges for many countries, particularly since 2015, as other arboviruses have been observed to interact significantly with dengue virus. Different approaches and methodologies have been proposed and discussed by the research community. An important tool widely used is modeling and simulation, which help us to understand epidemic dynamics and create scenarios to support planning and decision making processes. With this aim, we proposed and developed DengueME, a collaborative open source platform to simulate dengue disease and its vector's dynamics. It supports compartmental and individual-based models, implemented over a GIS database, that represent Aedes aegypti population dynamics, human demography, human mobility, urban landscape and dengue transmission mediated by human and mosquito encounters. A user-friendly graphical interface was developed to facilitate model configuration and data input, and a library of models was developed to support teaching-learning activities. DengueME was applied in study cases and evaluated by specialists. Other improvements will be made in future work, to enhance its extensibility and usability.
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Affiliation(s)
- Tiago França Melo de Lima
- Departamento de Computação e Sistemas (DECSI), Instituto de Ciências Exatas e Aplicadas (ICEA), Universidade Federal de Ouro Preto (UFOP) - Campus João Monlevade, João Monlevade, MG 35931-008, Brasil.
| | - Raquel Martins Lana
- Programa Pós-Graduação em Epidemiologia em Saúde Pública, Escola Nacional de Saúde Pública Sérgio Arouca (ENSP), Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, RJ 21045-900, Brasil.
| | - Tiago Garcia de Senna Carneiro
- Departamento de Computação (DECOM), Instituto de Ciências Exatas e Biológicas (ICEB), Universidade Federal de Ouro Preto (UFOP) - Campus Morro do Cruzeiro, Ouro Preto, MG 35400-000, Brasil.
| | - Cláudia Torres Codeço
- Programa de Computação Científica (PROCC), Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, RJ 21045-900, Brasil.
| | - Gabriel Souza Machado
- Departamento de Computação e Sistemas (DECSI), Instituto de Ciências Exatas e Aplicadas (ICEA), Universidade Federal de Ouro Preto (UFOP) - Campus João Monlevade, João Monlevade, MG 35931-008, Brasil.
| | - Lucas Saraiva Ferreira
- Departamento de Computação e Sistemas (DECSI), Instituto de Ciências Exatas e Aplicadas (ICEA), Universidade Federal de Ouro Preto (UFOP) - Campus João Monlevade, João Monlevade, MG 35931-008, Brasil.
| | - Líliam César de Castro Medeiros
- Instituto de Ciência e Tecnologia, Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP), São José dos Campos, SP 12247-004, Brasil.
| | - Clodoveu Augusto Davis Junior
- Departamento de Ciência da Computação (DCC), Instituto de Ciências Exatas (ICEx), Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG 31270-010, Brasil.
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83
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Phung D, Talukder MRR, Rutherford S, Chu C. A climate-based prediction model in the high-risk clusters of the Mekong Delta region, Vietnam: towards improving dengue prevention and control. Trop Med Int Health 2016; 21:1324-1333. [PMID: 27404323 DOI: 10.1111/tmi.12754] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To develop a prediction score scheme useful for prevention practitioners and authorities to implement dengue preparedness and controls in the Mekong Delta region (MDR). METHODS We applied a spatial scan statistic to identify high-risk dengue clusters in the MDR and used generalised linear-distributed lag models to examine climate-dengue associations using dengue case records and meteorological data from 2003 to 2013. The significant predictors were collapsed into categorical scales, and the β-coefficients of predictors were converted to prediction scores. The score scheme was validated for predicting dengue outbreaks using ROC analysis. RESULTS The north-eastern MDR was identified as the high-risk cluster. A 1 °C increase in temperature at lag 1-4 and 5-8 weeks increased the dengue risk 11% (95% CI, 9-13) and 7% (95% CI, 6-8), respectively. A 1% rise in humidity increased dengue risk 0.9% (95% CI, 0.2-1.4) at lag 1-4 and 0.8% (95% CI, 0.2-1.4) at lag 5-8 weeks. Similarly, a 1-mm increase in rainfall increased dengue risk 0.1% (95% CI, 0.05-0.16) at lag 1-4 and 0.11% (95% CI, 0.07-0.16) at lag 5-8 weeks. The predicted scores performed with high accuracy in diagnosing the dengue outbreaks (96.3%). CONCLUSION This study demonstrates the potential usefulness of a dengue prediction score scheme derived from complex statistical models for high-risk dengue clusters. We recommend a further study to examine the possibility of incorporating such a score scheme into the dengue early warning system in similar climate settings.
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Affiliation(s)
- Dung Phung
- Centre for Environment and Population Health, Griffith University, Nathan, Brisbane, Qld, Australia.
| | | | - Shannon Rutherford
- Centre for Environment and Population Health, Griffith University, Nathan, Brisbane, Qld, Australia
| | - Cordia Chu
- Centre for Environment and Population Health, Griffith University, Nathan, Brisbane, Qld, Australia
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84
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Lourenço J, Recker M. Dengue serotype immune-interactions and their consequences for vaccine impact predictions. Epidemics 2016; 16:40-8. [PMID: 27663790 PMCID: PMC5030310 DOI: 10.1016/j.epidem.2016.05.003] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2015] [Revised: 05/31/2016] [Accepted: 05/31/2016] [Indexed: 11/11/2022] Open
Abstract
The firstever dengue vaccine, Dengvaxia®, has recently been licensed for use in several countries. Mathematical models are valuable tools for assessing vaccination impact on dengue burden. Model assumptions regarding dengue serotype immune interactions are inconsistent. Our results demonstrate how model assumptions critically affect vaccine impact predictions.
Dengue is one of the most important and wide-spread viral infections affecting human populations. The last few decades have seen a dramatic increase in the global burden of dengue, with the virus now being endemic or near-endemic in over 100 countries world-wide. A recombinant tetravalent vaccine candidate (CYD-TDV) has recently completed Phase III clinical efficacy trials in South East Asia and Latin America and has been licensed for use in several countries. The trial results showed moderate-to-high efficacies in protection against clinical symptoms and hospitalisation but with so far unknown effects on transmission and infections per se. Model-based predictions about the vaccine's short- or long-term impact on the burden of dengue are therefore subject to a considerable degree of uncertainty. Furthermore, different immune interactions between dengue's serotypes have frequently been evoked by modelling studies to underlie dengue's oscillatory dynamics in disease incidence and serotype prevalence. Here we show how model assumptions regarding immune interactions in the form of antibody-dependent enhancement, temporary cross-immunity and the number of infections required to develop full immunity can significantly affect the predicted outcome of a dengue vaccination campaign. Our results thus re-emphasise the important gap in our current knowledge concerning the effects of previous exposure on subsequent dengue infections and further suggest that intervention impact studies should be critically evaluated by their underlying assumptions about serotype immune-interactions.
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Affiliation(s)
- José Lourenço
- Department of Zoology, University of Oxford, Oxford OX1 3PS, UK
| | - Mario Recker
- Centre for Mathematics and the Environment, University of Exeter, Penryn Campus, Penryn TR10 9EZ, UK.
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85
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The Role of Serotype Interactions and Seasonality in Dengue Model Selection and Control: Insights from a Pattern Matching Approach. PLoS Negl Trop Dis 2016; 10:e0004680. [PMID: 27159023 PMCID: PMC4861330 DOI: 10.1371/journal.pntd.0004680] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2015] [Accepted: 04/11/2016] [Indexed: 01/10/2023] Open
Abstract
The epidemiology of dengue fever is characterized by highly seasonal, multi-annual fluctuations, and the irregular circulation of its four serotypes. It is believed that this behaviour arises from the interplay between environmental drivers and serotype interactions. The exact mechanism, however, is uncertain. Constraining mathematical models to patterns characteristic to dengue epidemiology offers a means for detecting such mechanisms. Here, we used a pattern-oriented modelling (POM) strategy to fit and assess a range of dengue models, driven by combinations of temporary cross protective-immunity, cross-enhancement, and seasonal forcing, on their ability to capture the main characteristics of dengue dynamics. We show that all proposed models reproduce the observed dengue patterns across some part of the parameter space. Which model best supports the dengue dynamics is determined by the level of seasonal forcing. Further, when tertiary and quaternary infections are allowed, the inclusion of temporary cross-immunity alone is strongly supported, but the addition of cross-enhancement markedly reduces the parameter range at which dengue dynamics are produced, irrespective of the strength of seasonal forcing. The implication of these structural uncertainties on predicted vulnerability to control is also discussed. With ever expanding spread of dengue, greater understanding of dengue dynamics and control efforts (e.g. a near-future vaccine introduction) has become critically important. This study highlights the capacity of multi-level pattern-matching modelling approaches to offer an analytic tool for deeper insights into dengue epidemiology and control. The fluctuations of multi-serotype infectious diseases are often highly irregular and hard to predict. Previous theoretical approaches have attempted to disentangle the drivers that may underlie this behaviour in dengue dynamics with variable success. Here, we examine the role of such drivers using a pattern-oriented modelling (POM) approach. In POM, multiple patterns observed at different scales are used to test a model’s proficiency in capturing real-world dynamics. We examined dengue models with combinations of cross-immunity, cross-enhancement, seasonal fluctuations in the transmission rate, and with sensitivity analyses of asymmetric transmission rates between serotypes as well as the possibility for four subsequent heterologous infections. We demonstrate the ability of POM to model dynamical drivers that have gone unnoticed in single pattern or synthetic likelihood approaches. Further, our results present a determining role of seasonality in the selection and operation of these processes in governing dengue dynamics, in particular when full, heterologous immunity is assumed to occur after a secondary infection. We show that this structural model uncertainty can have important practical significance, as demonstrated by the differences in control efforts required to disrupt transmission. These results highlight the importance of localised model selection and calibration using multiple data-matching, as well as taking explicit account of model uncertainty in predicting and planning control efforts for multi-serotype diseases.
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86
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Adde A, Roucou P, Mangeas M, Ardillon V, Desenclos JC, Rousset D, Girod R, Briolant S, Quenel P, Flamand C. Predicting Dengue Fever Outbreaks in French Guiana Using Climate Indicators. PLoS Negl Trop Dis 2016; 10:e0004681. [PMID: 27128312 PMCID: PMC4851397 DOI: 10.1371/journal.pntd.0004681] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Accepted: 04/11/2016] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Dengue fever epidemic dynamics are driven by complex interactions between hosts, vectors and viruses. Associations between climate and dengue have been studied around the world, but the results have shown that the impact of the climate can vary widely from one study site to another. In French Guiana, climate-based models are not available to assist in developing an early warning system. This study aims to evaluate the potential of using oceanic and atmospheric conditions to help predict dengue fever outbreaks in French Guiana. METHODOLOGY/PRINCIPAL FINDINGS Lagged correlations and composite analyses were performed to identify the climatic conditions that characterized a typical epidemic year and to define the best indices for predicting dengue fever outbreaks during the period 1991-2013. A logistic regression was then performed to build a forecast model. We demonstrate that a model based on summer Equatorial Pacific Ocean sea surface temperatures and Azores High sea-level pressure had predictive value and was able to predict 80% of the outbreaks while incorrectly predicting only 15% of the non-epidemic years. Predictions for 2014-2015 were consistent with the observed non-epidemic conditions, and an outbreak in early 2016 was predicted. CONCLUSIONS/SIGNIFICANCE These findings indicate that outbreak resurgence can be modeled using a simple combination of climate indicators. This might be useful for anticipating public health actions to mitigate the effects of major outbreaks, particularly in areas where resources are limited and medical infrastructures are generally insufficient.
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Affiliation(s)
- Antoine Adde
- Unité d’épidémiologie, Institut Pasteur de la Guyane, Cayenne, Guyane
- Unité d’entomologie médicale, Institut Pasteur de la Guyane, Cayenne, Guyane
| | - Pascal Roucou
- Centre de Recherches de Climatologie, UMR6282 Biogéosciences, CNRS Université de Bourgogne Franche-Comté, Dijon, France
| | - Morgan Mangeas
- Maison de la Télédétection, UMR 228 ESPACE-DEV, Institut de Recherche pour le Développement, Montpellier, France
| | - Vanessa Ardillon
- Cellule de l’Institut de Veille Sanitaire en Régions Antilles - Guyane, Cayenne, Guyane
| | | | | | - Romain Girod
- Unité d’entomologie médicale, Institut Pasteur de la Guyane, Cayenne, Guyane
| | - Sébastien Briolant
- Unité d’entomologie médicale, Institut Pasteur de la Guyane, Cayenne, Guyane
- Direction Interarmées du Service de Santé en Guyane, Cayenne, Guyane
- Institut de Recherche Biomédicale des Armées, Brétigny sur Orge, France
| | - Philippe Quenel
- Laboratoire d’Etudes et de Recherche en Santé-Environnement, Ecole des Hautes Etudes en Santé Publique, Rennes, France
| | - Claude Flamand
- Unité d’épidémiologie, Institut Pasteur de la Guyane, Cayenne, Guyane
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87
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Forshey BM, Stoddard ST, Morrison AC. Dengue Viruses and Lifelong Immunity: Reevaluating the Conventional Wisdom. J Infect Dis 2016; 214:979-81. [PMID: 26984147 DOI: 10.1093/infdis/jiw102] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Accepted: 03/07/2016] [Indexed: 11/12/2022] Open
Affiliation(s)
- Brett M Forshey
- Global Emerging Infections Surveillance and Response Section, Armed Forces Health Surveillance Branch Cherokee Nation Technology Solutions, Silver Spring, Maryland
| | | | - Amy C Morrison
- Department of Entomology and Nematology, University of California, Davis
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88
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Expanding vaccine efficacy estimation with dynamic models fitted to cross-sectional prevalence data post-licensure. Epidemics 2016; 14:71-82. [DOI: 10.1016/j.epidem.2015.11.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2015] [Revised: 11/02/2015] [Accepted: 11/25/2015] [Indexed: 01/02/2023] Open
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89
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Padmanabha H, Correa F, Rubio C, Baeza A, Osorio S, Mendez J, Jones JH, Diuk-Wasser MA. Human Social Behavior and Demography Drive Patterns of Fine-Scale Dengue Transmission in Endemic Areas of Colombia. PLoS One 2015; 10:e0144451. [PMID: 26656072 PMCID: PMC4684369 DOI: 10.1371/journal.pone.0144451] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2015] [Accepted: 11/18/2015] [Indexed: 01/09/2023] Open
Abstract
Dengue is known to transmit between humans and A. aegypti mosquitoes living in neighboring houses. Although transmission is thought to be highly heterogeneous in both space and time, little is known about the patterns and drivers of transmission in groups of houses in endemic settings. We carried out surveys of PCR positivity in children residing in 2-block patches of highly endemic cities of Colombia. We found high levels of heterogeneity in PCR positivity, varying from less than 30% in 8 of the 10 patches to 56 and 96%, with the latter patch containing 22 children simultaneously PCR positive (PCR22) for DEN2. We then used an agent-based model to assess the likely eco-epidemiological context of this observation. Our model, simulating daily dengue dynamics over a 20 year period in a single two block patch, suggests that the observed heterogeneity most likely derived from variation in the density of susceptible people. Two aspects of human adaptive behavior were critical to determining this density: external social relationships favoring viral introduction (by susceptible residents or infectious visitors) and immigration of households from non-endemic areas. External social relationships generating frequent viral introduction constituted a particularly strong constraint on susceptible densities, thereby limiting the potential for explosive outbreaks and dampening the impact of heightened vectorial capacity. Dengue transmission can be highly explosive locally, even in neighborhoods with significant immunity in the human population. Variation among neighborhoods in the density of local social networks and rural-to-urban migration is likely to produce significant fine-scale heterogeneity in dengue dynamics, constraining or amplifying the impacts of changes in mosquito populations and cross immunity between serotypes.
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Affiliation(s)
- Harish Padmanabha
- Centro de Investigaciones en el Desarrollo Humano (CIDHUM), Universidad del Norte, Km 5 Via Puerto Colombia, Puerto Colombia, Colombia
- National Socio-Environmental Synthesis Center (SESYNC), University of Maryland, 1 Park Place, Suite 300, Annapolis, Maryland, 21401, United States of America
- * E-mail:
| | - Fabio Correa
- Instituto Nacional de Salud de Colombia, Avenida/calle 26 No. 51–20 - Zona 6 CAN, Bogotá, D.C., Colombia
| | - Camilo Rubio
- Instituto Nacional de Salud de Colombia, Avenida/calle 26 No. 51–20 - Zona 6 CAN, Bogotá, D.C., Colombia
| | - Andres Baeza
- National Socio-Environmental Synthesis Center (SESYNC), University of Maryland, 1 Park Place, Suite 300, Annapolis, Maryland, 21401, United States of America
| | - Salua Osorio
- Instituto Nacional de Salud de Colombia, Avenida/calle 26 No. 51–20 - Zona 6 CAN, Bogotá, D.C., Colombia
| | - Jairo Mendez
- Instituto Nacional de Salud de Colombia, Avenida/calle 26 No. 51–20 - Zona 6 CAN, Bogotá, D.C., Colombia
| | - James Holland Jones
- Department of Anthropology/Woods Institute of the Environment, Stanford University, 450 Serra Mall, Building 50, Stanford, California, 94305–2034, United States of America
| | - Maria A Diuk-Wasser
- Department of Ecology, Evolution and Environmental Biology, Columbia University, 1200 Amsterdam Ave, New York, New York, 10027, United States of America
- Department of Epidemiology of Microbial Diseases, Yale University, 60 College St, New Haven, Connecticut, 06520, United States of America
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90
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Rocha FP, Rodrigues HS, Monteiro MTT, Torres DF. Coexistence of two dengue virus serotypes and forecasting for Madeira Island. ACTA ACUST UNITED AC 2015. [DOI: 10.1016/j.orhc.2015.07.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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91
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Abdelrazec A, Bélair J, Shan C, Zhu H. Modeling the spread and control of dengue with limited public health resources. Math Biosci 2015; 271:136-45. [PMID: 26593704 DOI: 10.1016/j.mbs.2015.11.004] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2015] [Revised: 09/07/2015] [Accepted: 11/16/2015] [Indexed: 11/15/2022]
Abstract
A deterministic model for the transmission dynamics of dengue fever is formulated to study, with a nonlinear recovery rate, the impact of available resources of the health system on the spread and control of the disease. Model results indicate the existence of multiple endemic equilibria, as well as coexistence of an endemic equilibrium with a periodic solution. Additionally, our model exhibits the phenomenon of backward bifurcation. The results of this study could be helpful for public health authorities in their planning of a proper resource allocation for the control of dengue transmission.
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Affiliation(s)
- Ahmed Abdelrazec
- Department of Mathematics and Statistics, Arizona State University, USA
| | - Jacques Bélair
- Département de mathématiques et de statistique, Université de Montréal, Canada
| | - Chunhua Shan
- Department of Mathematical and Statistical Sciences, University of Alberta, Canada
| | - Huaiping Zhu
- LAMPS and Department of Mathematics and Statistics, York University, Canada.
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92
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Knipl D, Moghadas SM. The Potential Impact of Vaccination on the Dynamics of Dengue Infections. Bull Math Biol 2015; 77:2212-30. [PMID: 26585748 DOI: 10.1007/s11538-015-0120-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2015] [Accepted: 10/22/2015] [Indexed: 12/01/2022]
Abstract
Dengue, classified as a 'neglected topical disease', is currently regarded globally as the most important mosquito-borne viral disease, which inflicts substantial socioeconomic and health burden in many tropical and subtropical regions of the world. While efforts continue towards developing and improving the efficacy of a tetravalent vaccine to protect individuals against all dengue virus serotypes, the long-term epidemiological impact of vaccination remains elusive. We develop a serotype-specific, vector-host compartmental model to evaluate the effect of vaccination in the presence of antibody-dependent enhancement and cross-protection following recovery from primary infection. Reproducing the reported multi-annual patterns of dengue infection, our model projects that vaccination can dramatically reduce the overall incidence of the disease. However, if the duration of vaccine-induced protection is shorter than the average lifetime of the human population, vaccination can potentially increase the incidence of severe infection of dengue haemorrhagic fever due to the effects of antibody-dependent enhancement. The magnitude and timelines for this increase depend strongly on the efficacy and duration of the vaccine-induced protection. Corresponding to the current estimates of vaccine efficacy, we show that dengue eradication is infeasible using an imperfect vaccine. Furthermore, for a vaccine that induces lifetime protection, a nearly full coverage of infant vaccination is required for dengue elimination. Our findings suggest that other vector control measures may still play a significant role in dengue prevention even when a vaccine with high protection efficacy becomes available.
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Affiliation(s)
- Diána Knipl
- Agent-Based Modelling Laboratory, York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada. .,MTA-SZTE Analysis and Stochastic Research Group, University of Szeged, Aradi vértanúk tere 1, Szeged, 6720, Hungary.
| | - Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, 4700 Keele St., Toronto, ON, M3J 1P3, Canada.
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93
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Bhattacharyya S, Gesteland PH, Korgenski K, Bjørnstad ON, Adler FR. Cross-immunity between strains explains the dynamical pattern of paramyxoviruses. Proc Natl Acad Sci U S A 2015; 112:13396-400. [PMID: 26460003 PMCID: PMC4629340 DOI: 10.1073/pnas.1516698112] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Viral respiratory tract diseases pose serious public health problems. Our ability to predict and thus, be able to prepare for outbreaks is strained by the complex factors driving the prevalence and severity of these diseases. The abundance of diseases and transmission dynamics of strains are not only affected by external factors, such as weather, but also driven by interactions among viruses mediated by human behavior and immunity. To untangle the complex out-of-phase annual and biennial pattern of three common paramyxoviruses, Respiratory Syncytial Virus (RSV), Human Parainfluenza Virus (HPIV), and Human Metapneumovirus (hMPV), we adopt a theoretical approach that integrates ecological and immunological mechanisms of disease interactions. By estimating parameters from multiyear time series of laboratory-confirmed cases from the intermountain west region of the United States and using statistical inference, we show that models of immune-mediated interactions better explain the data than those based on ecological competition by convalescence. The strength of cross-protective immunity among viruses is correlated with their genetic distance in the phylogenetic tree of the paramyxovirus family.
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Affiliation(s)
- Samit Bhattacharyya
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA 16802; Department of Biology, University of Utah, Salt Lake City, UT 84112;
| | - Per H Gesteland
- Department of Pediatrics, School of Medicine, University of Utah, Salt Lake City, UT 84112; Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84112
| | - Kent Korgenski
- Department of Pediatrics, School of Medicine, University of Utah, Salt Lake City, UT 84112; Pediatric Clinical Program, Intermountain Healthcare, Salt Lake City, UT 84111
| | - Ottar N Bjørnstad
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA 16802; Fogarty International Center, National Institutes of Health, Bethesda, MD 20892
| | - Frederick R Adler
- Department of Biology, University of Utah, Salt Lake City, UT 84112; Department of Mathematics, University of Utah, Salt Lake City, UT 84112
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94
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A role for vector control in dengue vaccine programs. Vaccine 2015; 33:7069-74. [PMID: 26478199 DOI: 10.1016/j.vaccine.2015.09.114] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Revised: 09/22/2015] [Accepted: 09/23/2015] [Indexed: 01/22/2023]
Abstract
Development and deployment of a successful dengue virus (DENV) vaccine has confounded research and pharmaceutical entities owing to the complex nature of DENV immunity and concerns over exacerbating the risk of DENV hemorrhagic fever (DHF) as a consequence of vaccination. Thus, consensus is growing that a combination of mitigation strategies will be needed for DENV to be successfully controlled, likely involving some form of vector control to enhance a vaccine program. We present here a deterministic compartmental model to illustrate that vector control may enhance vaccination campaigns with imperfect coverage and efficacy. Though we recognize the costs and challenges associated with continuous control programs, simultaneous application of vector control methods coincident with vaccine roll out can have a positive effect by further reducing the number of human cases. The success of such an integrative strategy is predicated on closing gaps in our understanding of the DENV transmission cycle in hyperedemic locations.
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95
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A multiobjective optimization approach for combating Aedes aegypti using chemical and biological alternated step-size control. Math Biosci 2015; 269:37-47. [PMID: 26362231 DOI: 10.1016/j.mbs.2015.08.019] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2015] [Revised: 07/16/2015] [Accepted: 08/28/2015] [Indexed: 11/23/2022]
Abstract
Dengue epidemics, one of the most important viral disease worldwide, can be prevented by combating the transmission vector Aedes aegypti. In support of this aim, this article proposes to analyze the Dengue vector control problem in a multiobjective optimization approach, in which the intention is to minimize both social and economic costs, using a dynamic mathematical model representing the mosquitoes' population. It consists in finding optimal alternated step-size control policies combining chemical (via application of insecticides) and biological control (via insertion of sterile males produced by irradiation). All the optimal policies consists in apply insecticides just at the beginning of the season and, then, keep the mosquitoes in an acceptable level spreading into environment a few amount of sterile males. The optimization model analysis is driven by the use of genetic algorithms. Finally, it performs a statistic test showing that the multiobjective approach is effective in achieving the same effect of variations in the cost parameters. Then, using the proposed methodology, it is possible to find, in a single run, given a decision maker, the optimal number of days and the respective amounts in which each control strategy must be applied, according to the tradeoff between using more insecticide with less transmission mosquitoes or more sterile males with more transmission mosquitoes.
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96
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Poore KD, Bauch CT. The impact of aggregating serogroups in dynamic models of Neisseria meningitidis transmission. BMC Infect Dis 2015. [PMID: 26223223 PMCID: PMC4520071 DOI: 10.1186/s12879-015-1015-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
Background Neisseria meningitidis (Nm) is a pathogen of multiple serogroups that is highly prevalent in many populations. Serogroups associated with invasive meningococcal disease (IMD) in Canada, for example, include A, B, C, W-135, X and Y. IMD is a rare but serious outcome of Nm infection, and can be prevented with vaccines that target certain serogroups. This has stimulated the development of dynamic models to evaluate vaccine impact. However, these models typically aggregate the various Nm serogroups into a small number of combined groups, instead of modelling each serogroup individually. The impact of aggregation on dynamic Nm model predictions is poorly understood. Our objective was to explore the impact of aggregation on dynamic model predictions. Methods We developed two age-structured agent-based models--a 2-strain model and a 4-strain model--to simulate vaccination programs in the Canadian setting. The 2-strain model was used to explore two different groupings: C, versus all other serogroups combined; and B, versus all other serogroups combined. The 4-strain model used the four groupings: C, B, Neisseria lactamica, versus all other serogroups combined. We compared the predicted impact of monovalent C vaccine, quadrivalent ACWY vaccine (MCV-4), and monovalent B vaccine (4CMenB) on the prevalence of serogroup carriage under these different models. Results The 2-strain and 4-strain models predicted similar overall impacts of vaccines on carriage prevalence, especially with respect to the vaccine-targeted serogroups. However, there were some significant quantitative and qualitative differences. Declines in vaccine-targeted serogroups were more rapid in the 2-strain model than the 4-strain model, for both the C and the 4CMenB vaccines. Sustained oscillations, and evidence for multiple attractors (i.e., different types of dynamics for the same model parameters but different initial conditions), occurred in the 4-strain model but not the 2-strain model. Strain replacement was also more pronounced in the 4-strain model, on account of the 4-strain model spreading prevalence more thinly across groups and thus enhancing competitive interactions. Conclusions Simplifying assumptions like aggregation of serogroups can have significant impacts on dynamic model predictions. Modellers should carefully weigh the advantages and disadvantages of aggregation when formulating models for multi-strain pathogens. Electronic supplementary material The online version of this article (doi:10.1186/s12879-015-1015-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Keith D Poore
- Department of Mathematics and Statistics, University of Guelph, 50 Stone Road East, Guelph, ON, Canada.
| | - Chris T Bauch
- Department of Mathematics and Statistics, University of Guelph, 50 Stone Road East, Guelph, ON, Canada. .,Department of Applied Mathematics, University of Waterloo, 200 University Avenue West, Waterloo, ON, Canada.
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97
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Campbell KM, Haldeman K, Lehnig C, Munayco CV, Halsey ES, Laguna-Torres VA, Yagui M, Morrison AC, Lin CD, Scott TW. Weather Regulates Location, Timing, and Intensity of Dengue Virus Transmission between Humans and Mosquitoes. PLoS Negl Trop Dis 2015. [PMID: 26222979 PMCID: PMC4519153 DOI: 10.1371/journal.pntd.0003957] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Background Dengue is one of the most aggressively expanding mosquito-transmitted viruses. The human burden approaches 400 million infections annually. Complex transmission dynamics pose challenges for predicting location, timing, and magnitude of risk; thus, models are needed to guide prevention strategies and policy development locally and globally. Weather regulates transmission-potential via its effects on vector dynamics. An important gap in understanding risk and roadblock in model development is an empirical perspective clarifying how weather impacts transmission in diverse ecological settings. We sought to determine if location, timing, and potential-intensity of transmission are systematically defined by weather. Methodology/Principal Findings We developed a high-resolution empirical profile of the local weather-disease connection across Peru, a country with considerable ecological diversity. Applying 2-dimensional weather-space that pairs temperature versus humidity, we mapped local transmission-potential in weather-space by week during 1994-2012. A binary classification-tree was developed to test whether weather data could classify 1828 Peruvian districts as positive/negative for transmission and into ranks of transmission-potential with respect to observed disease. We show that transmission-potential is regulated by temperature-humidity coupling, enabling epidemics in a limited area of weather-space. Duration within a specific temperature range defines transmission-potential that is amplified exponentially in higher humidity. Dengue-positive districts were identified by mean temperature >22°C for 7+ weeks and minimum temperature >14°C for 33+ weeks annually with 95% sensitivity and specificity. In elevated-risk locations, seasonal peak-incidence occurred when mean temperature was 26-29°C, coincident with humidity at its local maximum; highest incidence when humidity >80%. We profile transmission-potential in weather-space for temperature-humidity ranging 0-38°C and 5-100% at 1°C x 2% resolution. Conclusions/Significance Local duration in limited areas of temperature-humidity weather-space identifies potential locations, timing, and magnitude of transmission. The weather-space profile of transmission-potential provides needed data that define a systematic and highly-sensitive weather-disease connection, demonstrating separate but coupled roles of temperature and humidity. New insights regarding natural regulation of human-mosquito transmission across diverse ecological settings advance our understanding of risk locally and globally for dengue and other mosquito-borne diseases and support advances in public health policy/operations, providing an evidence-base for modeling, predicting risk, and surveillance-prevention planning. Timing and spatial-extent of diseases such as dengue and malaria that result from transmission between humans and mosquitoes are regulated by weather in complicated ways. For Aedes aegypti mosquitoes, the primary vector of dengue, slight changes in different components of weather have important effects on population dynamics, lifespan, biting-frequency, virus incubation period and capacity to transmit the virus, thus inducing changes in transmission probability. These complicated dynamics produce a weather-disease connection that is not well-defined for different ecological settings. Understanding this connection is important to critical elements of policy development and operational control of dengue such as predicting risk, developing human-vector transmission models, and planning surveillance-intervention strategies locally and globally. The empirical profile of the weather-disease connection for dengue developed in this study provides a needed understanding of how temperature and humidity work together in regulating human-mosquito transmission. The observed likelihood of low to epidemic-level transmission was highly sensitive to local seasonal duration in limited areas of this two-dimensional weather-space. Data presented represent a resource for estimating where and when transmission-potential supports epidemics of varying magnitude. This high-resolution weather-disease profile for dengue reveals systematic relationships that are informative for mosquito-borne diseases in general and discussions of consequences of global warming.
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Affiliation(s)
- Karen M. Campbell
- Computational Science Research Center, San Diego State University, San Diego, California, United States of America
- * E-mail:
| | - Kristin Haldeman
- Computational Science Research Center, San Diego State University, San Diego, California, United States of America
| | - Chris Lehnig
- Computational Science Research Center, San Diego State University, San Diego, California, United States of America
| | - Cesar V. Munayco
- Department of Preventive Medicine and Biometrics, Uniformed Services University of Health Sciences, Bethesda, Maryland, United States of America
| | | | | | | | - Amy C. Morrison
- Department of Entomology, University of California, Davis, Davis, California, United States of America
| | - Chii-Dean Lin
- Department of Mathematics and Statistics, San Diego State University, San Diego, California, United States of America
| | - Thomas W. Scott
- Department of Entomology, University of California, Davis, Davis, California, United States of America
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
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98
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Imai N, Dorigatti I, Cauchemez S, Ferguson NM. Estimating dengue transmission intensity from sero-prevalence surveys in multiple countries. PLoS Negl Trop Dis 2015; 9:e0003719. [PMID: 25881272 PMCID: PMC4400108 DOI: 10.1371/journal.pntd.0003719] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2015] [Accepted: 03/24/2015] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Estimates of dengue transmission intensity remain ambiguous. Since the majority of infections are asymptomatic, surveillance systems substantially underestimate true rates of infection. With advances in the development of novel control measures, obtaining robust estimates of average dengue transmission intensity is key for assessing both the burden of disease from dengue and the likely impact of interventions. METHODOLOGY/PRINCIPAL FINDINGS The force of infection (λ) and corresponding basic reproduction numbers (R0) for dengue were estimated from non-serotype (IgG) and serotype-specific (PRNT) age-stratified seroprevalence surveys identified from the literature. The majority of R0 estimates ranged from 1-4. Assuming that two heterologous infections result in complete immunity produced up to two-fold higher estimates of R0 than when tertiary and quaternary infections were included. λ estimated from IgG data were comparable to the sum of serotype-specific forces of infection derived from PRNT data, particularly when inter-serotype interactions were allowed for. CONCLUSIONS/SIGNIFICANCE Our analysis highlights the highly heterogeneous nature of dengue transmission. How underlying assumptions about serotype interactions and immunity affect the relationship between the force of infection and R0 will have implications for control planning. While PRNT data provides the maximum information, our study shows that even the much cheaper ELISA-based assays would provide comparable baseline estimates of overall transmission intensity which will be an important consideration in resource-constrained settings.
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Affiliation(s)
- Natsuko Imai
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Ilaria Dorigatti
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Simon Cauchemez
- Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France
| | - Neil M. Ferguson
- MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
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99
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Brady OJ, Smith DL, Scott TW, Hay SI. Dengue disease outbreak definitions are implicitly variable. Epidemics 2015; 11:92-102. [PMID: 25979287 PMCID: PMC4429239 DOI: 10.1016/j.epidem.2015.03.002] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2014] [Revised: 03/12/2015] [Accepted: 03/13/2015] [Indexed: 12/13/2022] Open
Abstract
With appropriate and timely control, disease outbreak burden can be minimised. Many different case data-based statistical methods are used to trigger outbreak response. Here we show that these methods are inconsistent and incomparable. This may hinder the effectiveness of outbreak response. Clear quantitative definitions of an outbreak are a prerequisite for effective outbreak early warning and response.
Infectious diseases rarely exhibit simple dynamics. Outbreaks (defined as excess cases beyond response capabilities) have the potential to cause a disproportionately high burden due to overwhelming health care systems. The recommendations of international policy guidelines and research agendas are based on a perceived standardised definition of an outbreak characterised by a prolonged, high-caseload, extra-seasonal surge. In this analysis we apply multiple candidate outbreak definitions to reported dengue case data from Brazil to test this assumption. The methods identify highly heterogeneous outbreak characteristics in terms of frequency, duration and case burden. All definitions identify outbreaks with characteristics that vary over time and space. Further, definitions differ in their timeliness of outbreak onset, and thus may be more or less suitable for early intervention. This raises concerns about the application of current outbreak guidelines for early warning/identification systems. It is clear that quantitatively defining the characteristics of an outbreak is an essential prerequisite for effective reactive response. More work is needed so that definitions of disease outbreaks can take into account the baseline capacities of treatment, surveillance and control. This is essential if outbreak guidelines are to be effective and generalisable across a range of epidemiologically different settings.
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Affiliation(s)
- Oliver J Brady
- Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology, University of Oxford, South Parks Road, Oxford, UK.
| | - David L Smith
- Spatial Ecology and Epidemiology Group, Tinbergen Building, Department of Zoology, University of Oxford, South Parks Road, Oxford, UK; Fogarty International Center, National Institutes of Health, Bethesda, MD, USA; Sanaria Institute for Global Health and Tropical Medicine, Rockville, MD, USA.
| | - Thomas W Scott
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA; Department of Entomology and Nematology, University of California, Davis, CA, USA.
| | - Simon I Hay
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA; The Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford OX3 7BN, UK.
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100
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Poletto C, Meloni S, Van Metre A, Colizza V, Moreno Y, Vespignani A. Characterising two-pathogen competition in spatially structured environments. Sci Rep 2015; 5:7895. [PMID: 25600088 PMCID: PMC4298724 DOI: 10.1038/srep07895] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2014] [Accepted: 12/16/2014] [Indexed: 11/10/2022] Open
Abstract
Different pathogens spreading in the same host population often generate complex co-circulation dynamics because of the many possible interactions between the pathogens and the host immune system, the host life cycle, and the space structure of the population. Here we focus on the competition between two acute infections and we address the role of host mobility and cross-immunity in shaping possible dominance/co-dominance regimes. Host mobility is modelled as a network of traveling flows connecting nodes of a metapopulation, and the two-pathogen dynamics is simulated with a stochastic mechanistic approach. Results depict a complex scenario where, according to the relation among the epidemiological parameters of the two pathogens, mobility can either be non-influential for the competition dynamics or play a critical role in selecting the dominant pathogen. The characterisation of the parameter space can be explained in terms of the trade-off between pathogen's spreading velocity and its ability to diffuse in a sparse environment. Variations in the cross-immunity level induce a transition between presence and absence of competition. The present study disentangles the role of the relevant biological and ecological factors in the competition dynamics, and provides relevant insights into the spatial ecology of infectious diseases.
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Affiliation(s)
- Chiara Poletto
- 1] Sorbonne Universités, UPMC Univ Paris 06, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, F-75013, Paris, France [2] INSERM, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, F-75013, Paris, France
| | - Sandro Meloni
- 1] Institute for Biocomputation and Physics of Complex Systems, University of Zaragoza, Zaragoza, Spain [2] Department of Theoretical Physics, University of Zaragoza, Zaragoza, Spain
| | - Ashleigh Van Metre
- 1] Sorbonne Universités, UPMC Univ Paris 06, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, F-75013, Paris, France [2] INSERM, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, F-75013, Paris, France [3] Wofford College, South Carolina, USA
| | - Vittoria Colizza
- 1] Sorbonne Universités, UPMC Univ Paris 06, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, F-75013, Paris, France [2] INSERM, UMR-S 1136, Institut Pierre Louis d'Epidémiologie et de Santé Publique, F-75013, Paris, France [3] ISI Foundation, Torino, Italy
| | - Yamir Moreno
- 1] Institute for Biocomputation and Physics of Complex Systems, University of Zaragoza, Zaragoza, Spain [2] Department of Theoretical Physics, University of Zaragoza, Zaragoza, Spain [3] ISI Foundation, Torino, Italy
| | - Alessandro Vespignani
- 1] ISI Foundation, Torino, Italy [2] Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston MA, USA
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