Dataset Information

Evaluation of location-specific predictions by a detailed simulation model of Aedes aegypti populations.

ABSTRACT:

Background

Skeeter Buster is a stochastic, spatially explicit simulation model of Aedes aegypti populations, designed to predict the outcome of vector population control methods. In this study, we apply the model to two specific locations, the cities of Iquitos, Peru, and Buenos Aires, Argentina. These two sites differ in the amount of field data that is available for location-specific customization. By comparing output from Skeeter Buster to field observations in these two cases we evaluate population dynamics predictions by Skeeter Buster with varying degrees of customization.

Methodology/principal findings

Skeeter Buster was customized to the Iquitos location by simulating the layout of houses and the associated distribution of water-holding containers, based on extensive surveys of Ae. aegypti populations and larval habitats that have been conducted in Iquitos for over 10 years. The model is calibrated by adjusting the food input into various types of containers to match their observed pupal productivity in the field. We contrast the output of this customized model to the data collected from the natural population, comparing pupal numbers and spatial distribution of pupae in the population. Our results show that Skeeter Buster replicates specific population dynamics and spatial structure of Ae. aegypti in Iquitos. We then show how Skeeter Buster can be customized for Buenos Aires, where we only had Ae. aegypti abundance data that was averaged across all locations. In the Argentina case Skeeter Buster provides a satisfactory simulation of temporal population dynamics across seasons.

Conclusions

This model can provide a faithful description of Ae. aegypti populations, through a process of location-specific customization that is contingent on the amount of data available from field collections. We discuss limitations presented by some specific components of the model such as the description of food dynamics and challenges that these limitations bring to model evaluation.

SUBMITTER: Legros M

PROVIDER: S-EPMC3143176 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Publications

Evaluation of location-specific predictions by a detailed simulation model of Aedes aegypti populations.

Legros Mathieu M Magori Krisztian K Morrison Amy C AC Xu Chonggang C Scott Thomas W TW Lloyd Alun L AL Gould Fred F

PloS one 20110725 7

<h4>Background</h4>Skeeter Buster is a stochastic, spatially explicit simulation model of Aedes aegypti populations, designed to predict the outcome of vector population control methods. In this study, we apply the model to two specific locations, the cities of Iquitos, Peru, and Buenos Aires, Argentina. These two sites differ in the amount of field data that is available for location-specific customization. By comparing output from Skeeter Buster to field observations in these two cases we eval ...[more]

PMID: 21799936

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Project description:BackgroundAedes aegypti is one of the most important mosquito vectors of human disease. The development of spatial models for Ae. aegypti provides a promising start toward model-guided vector control and risk assessment, but this will only be possible if models make reliable predictions. The reliability of model predictions is affected by specific sources of uncertainty in the model.Methodology/principal findingsThis study quantifies uncertainties in the predicted mosquito population dynamics at the community level (a cluster of 612 houses) and the individual-house level based on Skeeter Buster, a spatial model of Ae. aegypti, for the city of Iquitos, Peru. The study considers two types of uncertainty: 1) uncertainty in the estimates of 67 parameters that describe mosquito biology and life history, and 2) uncertainty due to environmental and demographic stochasticity. Our results show that for pupal density and for female adult density at the community level, respectively, the 95% prediction confidence interval ranges from 1000 to 3000 and from 700 to 5,000 individuals. The two parameters contributing most to the uncertainties in predicted population densities at both individual-house and community levels are the female adult survival rate and a coefficient determining weight loss due to energy used in metabolism at the larval stage (i.e. metabolic weight loss). Compared to parametric uncertainty, stochastic uncertainty is relatively low for population density predictions at the community level (less than 5% of the overall uncertainty) but is substantially higher for predictions at the individual-house level (larger than 40% of the overall uncertainty). Uncertainty in mosquito spatial dispersal has little effect on population density predictions at the community level but is important for the prediction of spatial clustering at the individual-house level.Conclusion/significanceThis is the first systematic uncertainty analysis of a detailed Ae. aegypti population dynamics model and provides an approach for identifying those parameters for which more accurate estimates would improve model predictions.

Project description:The success of control programs for mosquito borne diseases can be enhanced by crucial information provided by models of the mosquito populations. Models, however, can differ in their structure, complexity and biological assumptions, and these differences impact their predictions. Unfortunately, it is typically difficult to determine why two complex models make different predictions because we lack structured side-by-side comparisons of models using comparable parameterization. Here we present a detailed comparison of two complex, spatially-explicit, stochastic models of the population dynamics of Aedes aegypti, the main vector of dengue, yellow fever, chikungunya and Zika viruses. Both models describe the mosquito's biological and ecological characteristics, but differ in complexity and specific assumptions. We compare the predictions of these models in two selected climatic settings, a tropical and weakly seasonal climate in Iquitos, Peru, and a temperate and strongly seasonal climate in Buenos Aires, Argentina. Both models were calibrated to operate at identical average densities in unperturbed conditions in both settings, by adjusting parameters regulating densities in each model (number of larval development sites and amount of nutritional resources). We show that the models differ in their sensitivity to environmental conditions (temperature and rainfall), and trace differences to specific model assumptions. Temporal dynamics of the Ae. aegypti populations predicted by the two models differ more markedly under strongly seasonal Buenos Aires conditions. We use both models to simulate killing of larvae and/or adults with insecticides in selected areas. We show that predictions of population recovery by the models differ substantially, an effect likely related to model assumptions regarding larval development and (direct or delayed) density dependence. Our methodical comparison provides important guidance for model improvement by identifying key areas of Ae. aegypti ecology that substantially affect model predictions, and revealing the impact of model assumptions on population dynamics predictions in unperturbed and perturbed conditions.

Dataset Information

Evaluation of location-specific predictions by a detailed simulation model of Aedes aegypti populations.

Background

Methodology/principal findings

Conclusions

Publications

Evaluation of location-specific predictions by a detailed simulation model of Aedes aegypti populations.

Similar Datasets

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