A Comparison of Parametric Methods for Modeling Mosquito Survival Using Temperature and Age-Dependent Survival Data

Abstract

It is estimated that Malaria effects over 200million people every year, and accounts for about 750,000 deaths during the same period. The adult female Anopheles mosquito accounts for all transmissions of the human malaria pathogen, Plasmodium. The disease control measures often include interventions aimed at reducing the survival of the adult female Anopheles mosquitoes. Various factors such as temperature and age have been found to be associated with vector mortality. Whereas much effort has been paid to evaluate the effects on the vector survival, little research has been done on how temperature and time affect the vector adult life-history parameters. The objective of the present study is to compare the performance of four parametric models, namely, Gompertz, gamma, Weibull, and exponential models to determine the best model for analyzing the survival of the female Anopheles mosquito. Using experimental data from a mosquito survival experiment, the present study compares the performance of the models in tting mosquito mortality. The results show that temperature and age are signifcant predictors of vector mortality. In addition, the Gompertz model ts the data on the adult A. gambiae and A. stephensi better than the Weibull, Gamma, and the Exponential model. This implies that the mosquito data survival in the laboratory is age-dependent. The findings of the present study are also useful in parameterizing reliable mathematical models that examine the potential impact of temperature as well as global warming on the transmission of malaria.