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Linking mosquito surveillance to dengue fever through Bayesian mechanistic modeling

November 23, 2020

Our ability to effectively prevent the transmission of the dengue virus through targeted control of its vector, Aedes aegypti, depends critically on our understanding of the link between mosquito abundance and human disease risk. Mosquito and clinical surveillance data are widely collected, but linking them requires a modeling framework that accounts for the complex non-linear mechanisms involved in transmission. Most critical are the bottleneck in transmission imposed by mosquito lifespan relative to the virus’ extrinsic incubation period, and the dynamics of human immunity. We developed a differential equation model of dengue transmission and embedded it in a Bayesian hierarchical framework that allowed us to estimate latent time series of mosquito demographic rates from mosquito trap counts and dengue case reports from the city of Vitória, Brazil. We used the fitted model to explore how the timing of a pulse of adult mosquito control influences its effect on the human disease burden in the following year. We found that control was generally more effective when implemented in periods of relatively low mosquito mortality (when mosquito abundance was also generally low). In particular, control implemented in early September (week 34 of the year) produced the largest reduction in predicted human case reports over the following year. This highlights the potential long-term utility of broad, off-peak-season mosquito control in addition to existing, locally targeted within-season efforts. Further, uncertainty in the effectiveness of control interventions was driven largely by posterior variation in the average mosquito mortality rate (closely tied to total mosquito abundance) with lower mosquito mortality generating systems more vulnerable to control. Broadly, these correlations suggest that mosquito control is most effective in situations in which transmission is already limited by mosquito abundance.

Citation Information

Publication Year 2020
Title Linking mosquito surveillance to dengue fever through Bayesian mechanistic modeling
DOI 10.1371/journal.pntd.0008868
Authors Clinton B. Leach, Jennifer A. Hoeting, Kim M. Pepin, Alvaro E. Eiras, Mevin Hooten, Colleen T. Colleen T. Webb
Publication Type Article
Publication Subtype Journal Article
Series Title PLoS Neglected Tropical Diseases
Index ID 70227148
Record Source USGS Publications Warehouse
USGS Organization Colorado Cooperative Fish and Wildlife Research Unit

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