Skeeter Buster: A Stochastic, Spatially Explicit Modeling Tool for Studying Aedes aegypti Population Replacement and Population Suppression Strategies

Krisztian Magori,Thomas W Scott,Mathieu Legros,Alun L Lloyd,Dana A Focks,Molly E Puente,Fred Gould,Pattamaporn Kittayapong

doi:10.1371/journal.pntd.0000508

Abstract

BackgroundDengue is the most important mosquito-borne viral disease affecting humans. The only prevention measure currently available is the control of its vectors, primarily Aedes aegypti. Recent advances in genetic engineering have opened the possibility for a new range of control strategies based on genetically modified mosquitoes. Assessing the potential efficacy of genetic (and conventional) strategies requires the availability of modeling tools that accurately describe the dynamics and genetics of Ae. aegypti populations.Methodology/Principal findingsWe describe in this paper a new modeling tool of Ae. aegypti population dynamics and genetics named Skeeter Buster. This model operates at the scale of individual water-filled containers for immature stages and individual properties (houses) for adults. The biology of cohorts of mosquitoes is modeled based on the algorithms used in the non-spatial Container Inhabiting Mosquitoes Simulation Model (CIMSiM). Additional features incorporated into Skeeter Buster include stochasticity, spatial structure and detailed population genetics. We observe that the stochastic modeling of individual containers in Skeeter Buster is associated with a strongly reduced temporal variation in stage-specific population densities. We show that heterogeneity in container composition of individual properties has a major impact on spatial heterogeneity in population density between properties. We detail how adult dispersal reduces this spatial heterogeneity. Finally, we present the predicted genetic structure of the population by calculating FST values and isolation by distance patterns, and examine the effects of adult dispersal and container movement between properties.Conclusions/SignificanceWe demonstrate that the incorporated stochasticity and level of spatial detail have major impacts on the simulated population dynamics, which could potentially impact predictions in terms of control measures. The capacity to describe population genetics confers the ability to model the outcome of genetic control methods. Skeeter Buster is therefore an important tool to model Ae. aegypti populations and the outcome of vector control measures.

Highlights

Mosquito-borne dengue virus serotypes cause approximately 50 million cases of dengue fever per year, 500,000 cases of dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS), and result in approximately 12,500 fatalities annually [1,2]
Dengue viruses are vectored by mosquitoes, predominantly by the species Aedes aegypti
This can be achieved by traditional approaches such as insecticides, or by recently developed genetic methods that propose the release of mosquitoes genetically engineered to be unable to transmit dengue viruses

Summary

Introduction

Mosquito-borne dengue virus serotypes cause approximately 50 million cases of dengue fever per year, 500,000 cases of dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS), and result in approximately 12,500 fatalities annually [1,2]. The major vector for dengue is the mosquito Aedes aegypti which thrives in households with open, water-filled containers in which larvae develop. Several practices are used to control dengue vector populations, including reduction or elimination of larval development sites and insecticides targeting immatures or adults. In the case of Ae. aegypti, the Container Inhabiting Mosquito Simulation Model (CIMSiM) [6,7] is the most detailed tool available for understanding population dynamics and the expected effects of different intervention strategies on adult female densities. Recent advances in genetic engineering have opened the possibility for a new range of control strategies based on genetically modified mosquitoes. Assessing the potential efficacy of genetic (and conventional) strategies requires the availability of modeling tools that accurately describe the dynamics and genetics of Ae. aegypti populations

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Conclusion