Disentangling the human vector relationship to disrupt dengue and chikungunya virus outbreaks in Kenya

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In sub-Saharan Africa, routine passive surveillance for dengue (DENV) and chikungunya (CHIKV) viruses detects only a fraction of their impact, given the high probability of misdiagnosis and unstudied levels of transmission across different landscapes and within different susceptible populations. Known and unknown entomologic, environmental, and behavioral factors differentially drive transmission in different habitats. The lack of systematic surveillance and accurate diagnostics coupled with low levels of clinical suspicion all lead to under-diagnosis in the African setting and the inability to prevent outbreaks. In this renewal proposal, our hypothesis is that ongoing endemic transmission leads to potential for outbreaks that is modified by measurable factors (human movement and behavior patterns, weather/climate, and viral importations/introductions), and that this transition is predictable and preventable. The objective of these studies is to detail the dominant factors that facilitate epidemic transmission at the human-vector interface and to identify opportunities to blockade them. In order to define key drivers of outbreaks, we plan to: 1) Measure mosquito abundance in space and time; 2) Better define human-vector exposure using novel technology; 3) Identify human attributes such as movement and behavior that contribute to increased exposure; 4) Understand if outbreaks are due to new viral introductions or endemic viral strains and; 5) Identify the most influential drivers of ongoing human transmission and outbreak initiation and then use modeling to compare the potential impact of intervention strategies. Using novel approaches, we address the following aims: 1) Define time periods of increased vector abundance and increased risk for human transmission to delineate thresholds for dengue and chikungunya epidemic transition; 2) Detail locations with increased vector abundance and increased risk for human transmission; 3) Identify whether documented infection clusters occur due to importation/introduction vs. endemic transmission; and 4) Model outbreaks for predictive impact to inform policy. This research is based on 15 years of collaborative longitudinal studies and involves cohorts in Mombasa (coastal) and Kisumu (western), Kenya, where there is year-round transmission and documented recent outbreaks of DENV and CHIKV. These studies will fill knowledge gaps about the persistence of CHIKV and DENV in local habitats and the factors that contribute to outbreak transmission in varied settings. The data will also answer fundamental questions about arboviral etiologies in fever syndromes, while providing best estimates of related disease burden and long-term sequelae.