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In dengue-endemic areas such as Thailand, there is clear seasonality in the number of reported cases of dengue virus disease. However, the roles of different entomological and biological variables in determining this pattern have not been ascertained. To investigate this, seasonally-varying parameters were introduced in a step-wise fashion into a mathematical model of the transmission dynamics of dengue viruses. The predicted prevalence of infection was then compared to observed seasonal patterns of disease. The strongest influences on the pattern of infection and its seasonal variation were duration of infectiousness of the host, vector mortality, and biting rate. However, seasonally-varying parameters such as the latent period of infection in the vector had to be incorporated into the model to generate the correct timing of peak infection prevalence. A few limiting variables usually control the prevalence of an infectious disease because small changes in their values can carry the infection beyond the threshold at which its basic reproductive number is one. It was changes in such parameters (vector biting and mortality rate) which caused seasonal prevalence, but the timing of peak prevalence was a result of time delays within the system.
Hartley et al. (2002) studied this question.