The effects of seasonal human mobility and Aedes aegypti habitat suitability on Zika virus epidemic severity in Colombia.

The Zika virus epidemic of 2015–16, which caused over 1 million confirmed or suspected human cases in the Caribbean and Latin America, was driven by a combination of movement of infected humans and availability of suitable habitat for mosquito species that are key disease vectors. Both human mobility and mosquito vector abundances vary seasonally, and the goal of our research was to analyze the interacting effects of disease vector densities and human movement across metapopulations on disease transmission intensity and the probability of super-spreader events. Our research uses the novel approach of combining geographical modeling of mosquito presence with network modeling of human mobility to offer a comprehensive simulation environment for Zika virus epidemics that considers a substantial number of spatial and temporal factors compared to the literature. Specifically, we tested the hypotheses that 1) regions with the highest probability of mosquito presence will have more super-spreader events during dry months, when mosquitoes are predicted to be more abundant, 2) regions reliant on tourism industries will have more super-spreader events during wet months, when they are more likely to contribute to network-level pathogen spread due to increased travel. We used the case study of Colombia, a country with a population of about 50 million people, with an annual calendar that can be partitioned into overlapping cycles of wet and dry seasons and peak tourism and off tourism seasons that drive distinct cyclical patterns of mosquito abundance and human movement. Our results show that whether the first infected human was introduced to the network during the wet versus dry season and during the tourism versus off tourism season profoundly affects the severity and trajectory of the epidemic. For example, Zika virus was first detected in Colombia in October of 2015. Had it originated in January, a dry season month with high rates of tourism, it likely could have infected up to 60% more individuals and up to 40% more super-spreader events may have occurred. In addition, popular tourism destinations such as Barranquilla and Cartagena have the highest risk of super-spreader events during the winter, whereas densely populated areas such as Medellín and Bogotá are at higher risk of sustained transmission during dry months in the summer. Our research demonstrates that public health planning and response to vector-borne disease outbreaks requires a thorough understanding of how vector and host patterns vary due to seasonality in environmental conditions and human mobility dynamics. This research also has strong implications for tourism policy and the potential response strategies in case of an emergent epidemic. Author summary: The Zika virus pandemic of 2015–16, which caused over 1 million human cases in the Caribbean and Latin America, was driven by a combination of movement of infected humans and presence of mosquito species, such as Aedes aegypti, that carry the disease. Both human mobility and mosquito vector densities vary seasonally, and the goal of our research was to analyze the interacting effects of disease vector presence and human movement across metapopulations on disease transmission intensity and the probability of super-spreader events. Specifically, we tested the hypotheses that 1) regions with the highest probability of mosquito presence will have more super-spreader events during dry months, when mosquitoes are predicted to be more abundant, 2) regions reliant on tourism industries will have more super-spreader events during wet months, as they are more likely to contribute to network-level pathogen spread due to increased travel. We used the case study of Colombia, a nation with a population of about 50 million people, whose annual calendar can be partitioned into overlapping cycles of wet and dry seasons and tourism and off-tourism seasons that drive distinct cyclical patterns of mosquito occurrence and human movement. Our approach combined spatial modeling of mosquito presence with network modeling of human mobility. We used a Maximum Entropy model to estimate the spatially and temporally varying habitat suitability for Aedes aegypti, the primary mosquito vector of Zika virus in Colombia, in terms of environmental factors such as temperature, precipitation, and vegetation coverage and human factors indicating land use and development, socioeconomic status, and prevalence of standing water that provides key habitat for juvenile mosquitoes. We also used airline travel data to develop metapopulation patch network models of the 1,123 municipalities of Colombia for each month of 2015 and 2016. We combined our vector habitat suitability and human mobility network models to simulate the Zika virus epidemic if it had begun in each month of 2015. Our results show that whether the first human case was introduced to the network during the wet vs. dry season and during the tourism vs. off-tourism season profoundly affects the severity and trajectory of the epidemic. For example, Zika virus was first detected in Colombia in October of 2015. Had it originated in January, a dry season month with high rates of tourism, it likely could have infected up to 30% more individuals and up to 40% more super-spreader events may have occurred. In addition, popular vacation spots such as Barranquilla and Cartageña have the highest risk of super-spreader events during the winter, whereas densely populated areas such as Medellín and Bogotá are at higher risk of sustained transmission during dry months in the summer. Our research demonstrates that public health planning and response to vector-borne disease outbreaks requires a thorough understanding of how vector and host patterns vary due to seasonality in environmental conditions and human mobility dynamics. [ABSTRACT FROM AUTHOR]