Publication Date: 2016.
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<br />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<br />to environmental conditions (temperature and rainfall) and trace differences to specific model assumptions.<br />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<br />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.<br /><br />
Author affiliation: Legros, Mathieu. University of North Carolina; Estados Unidos
Author affiliation: Otero, Marcelo Javier. Universidad de Buenos Aires; Argentina
Author affiliation: Romeo Aznar, Victoria Teresa. Universidad de Buenos Aires; Argentina
Author affiliation: Solari, Hernan Gustavo. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Author affiliation: Gould, Fred. National Institutes of Health; Estados Unidos
Author affiliation: Lloyd, Alun L.. National Institutes of Health; Estados Unidos
Keywords: MODEL COMPARISON; MOSQUITO-BORNE DISEASES; POPULATION DYNAMICS; SPATIAL MODEL; VECTOR CONTROL; Otras Ciencias Biológicas; Ciencias Biológicas; CIENCIAS NATURALES Y EXACTAS; Otras Ciencias Biológicas; Ciencias Biológicas; CIENCIAS NATURALES Y EXACTAS; Astronomía; Ciencias Físicas; CIENCIAS NATURALES Y EXACTAS.
Repository: CONICET Digital (CONICET). Consejo Nacional de Investigaciones Científicas y Técnicas