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According to the World Health Organization, dengue fever is the mostimportant mosquito-borne disease of humans, and it is currently estimated thatthere may be 50 - 100 million yearly dengue infections worldwide. For thepurpose to provide new techniques to public health policies in course, weintroduce a predictive non-linear population dynamics model to describe thepopulation size of four stages of the development of \emph{Aedes aegypti},having the coefficients set to be dependent on the rainfall index data. Inspite of the population dynamics of the \emph{Ae. aegypti} be mainly ruled bythe rainfall regime, most models are dedicated exclusively to effects oftemperature and only few models are dedicated to influence of rainfall. Vectorcontrol actions are also implemented in many periods of the year in order tocompare relative efficiency of public health policies. The analysis ofequilibrium and stability was performed. Field rainfall time series data fromthe City of Lavras (Minas Gerais, Brazil) was used for the model evaluation.The model was validated in a comparison with experimental mosquito abundancedata acquired by field health agents. We evaluated and validated anentomological conjecture that claims that control actions should be performedduring the dry season, instead of the common procedure adopted by vectorcontrol programs, in which those are mainly applied in the rainy season.

A model to predict the population size of the dengue fever vector based on rainfall data