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

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          Abstract

          Background

          Dengue 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 findings

          We 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 F ST values and isolation by distance patterns, and examine the effects of adult dispersal and container movement between properties.

          Conclusions/Significance

          We 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.

          Author Summary

          Dengue is a viral disease that affects approximately 50 million people annually, and is estimated to result in 12,500 fatalities. Dengue viruses are vectored by mosquitoes, predominantly by the species Aedes aegypti. Because there is currently no vaccine or specific treatment, the only available strategy to reduce dengue transmission is to control the populations of these mosquitoes. 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. The expected outcome of different control strategies can be compared by simulating the population dynamics and genetics of mosquitoes at a given location. Development of optimal control strategies can then be guided by the modeling approach. To that end, we introduce a new modeling tool called Skeeter Buster. This model describes the dynamics and the genetics of Ae. aegypti populations at a very fine scale, simulating the contents of individual houses, and even the individual water-holding containers in which mosquito larvae reside. Skeeter Buster can be used to compare the predicted outcomes of multiple control strategies, traditional or genetic, making it an important tool in the fight against dengue.

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          Most cited references29

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          Global Spread and Persistence of Dengue

          Dengue is a spectrum of disease caused by four serotypes of the most prevalent arthropod-borne virus affecting humans today, and its incidence has increased dramatically in the past 50 years. Due in part to population growth and uncontrolled urbanization in tropical and subtropical countries, breeding sites for the mosquitoes that transmit dengue virus have proliferated, and successful vector control has proven problematic. Dengue viruses have evolved rapidly as they have spread worldwide, and genotypes associated with increased virulence have expanded from South and Southeast Asia into the Pacific and the Americas. This review explores the human, mosquito, and viral factors that contribute to the global spread and persistence of dengue, as well as the interaction between the three spheres, in the context of ecological and climate changes. What is known, as well as gaps in knowledge, is emphasized in light of future prospects for control and prevention of this pandemic disease.
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            Dispersal of the dengue vector Aedes aegypti within and between rural communities.

            Knowledge of mosquito dispersal is critical for vector-borne disease control and prevention strategies and for understanding population structure and pathogen dissemination. We determined Aedes aegypti flight range and dispersal patterns from 21 mark-release-recapture experiments conducted over 11 years (1991-2002) in Puerto Rico and Thailand. Dispersal was compared by release location, sex, age, season, and village. For all experiments, the majority of mosquitoes were collected from their release house or adjacent house. Inter-village movement was detected rarely, with a few mosquitoes moving a maximum of 512 meters from one Thai village to the next. Average dispersal distances were similar for males and females and females released indoors versus outdoors. The movement of Ae. aegypti was not influenced by season or age, but differed by village. Results demonstrate that adult Ae. aegypti disperse relatively short distances, suggesting that people rather than mosquitoes are the primary mode of dengue virus dissemination within and among communities.
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              Reaction kinetics of poikilotherm development.

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Negl Trop Dis
                plos
                plosntds
                PLoS Neglected Tropical Diseases
                Public Library of Science (San Francisco, USA )
                1935-2727
                1935-2735
                September 2009
                1 September 2009
                : 3
                : 9
                : e508
                Affiliations
                [1 ]Department of Entomology, North Carolina State University, Raleigh, North Carolina, United States of America
                [2 ]Infectious Disease Analysis, Gainesville, Florida, United States of America
                [3 ]Department of Entomology, University of California, Davis, California, United States of America
                [4 ]Department of Mathematics and Biomathematics Graduate Program, North Carolina State University, Raleigh, North Carolina, United States of America
                Mahidol University, Thailand
                Author notes
                [¤]

                Current address: Odum School of Ecology, University of Georgia, Athens GA 30602, USA

                Conceived and designed the experiments: KM TWS ALL FG. Analyzed the data: ML ALL FG. Contributed reagents/materials/analysis tools: DAF. Wrote the paper: KM ML. Built the model: KM ML MEP ALL. Revised the paper: MEP TWS ALL FG.

                Article
                09-PNTD-RA-0096R2
                10.1371/journal.pntd.0000508
                2728493
                19721700
                a0165ab8-9862-4b2b-a843-3da839a5965e
                Magori et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 6 March 2009
                : 27 July 2009
                Page count
                Pages: 18
                Categories
                Research Article
                Ecology/Population Ecology
                Genetics and Genomics/Population Genetics
                Infectious Diseases/Epidemiology and Control of Infectious Diseases

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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