  Dengue fever impacts populations across the tropics. Dengue is caused by a
mosquito transmitted flavivirus and its burden is projected to increase under
future climate and development scenarios. The transmission process of dengue
virus is strongly moderated by hydro-climatic conditions that impact the
vector's life cycle and behavior. Here, we study the impact of rainfall
seasonality and moisture availability on the monthly distribution of reported
dengue cases in Sri Lanka. Through cluster analysis, we find an association
between seasonal peaks of rainfall and dengue incidence with a two-month lag.
We show that a hydrologically driven epidemiological model (HYSIR), which takes
into account hydrologic memory in addition to the nonlinear dynamics of the
transmission process, captures the two-month lag between rainfall and dengue
cases seasonal peaks. Our analysis reveals a non-monotonic dependence of dengue
cases on moisture, whereby an increase of cases with increasing moisture is
followed by a reduction for very high levels of water availability. Improvement
in prediction of the seasonal peaks in dengue incidence results from a
seasonally varying dependence of transmission rate on water availability.
