Climate-driven models of leptospirosis dynamics in tropical islands from three oceanic basins

Background Leptospirosis is a neglected zoonosis which remains poorly known despite its epidemic potential, especially in tropical islands where outdoor lifestyle, vulnerability to invasive reservoir species and hot and rainy climate constitute higher risks for infections. Burden remains poorly documented while outbreaks can easily overflow health systems of these isolated and poorly populated areas. Identification of generic patterns driving leptospirosis dynamics across tropical islands would help understand its epidemiology for better preparedness of communities. In this study, we aim to model leptospirosis seasonality and outbreaks in tropical islands based on precipitation and temperature indicators.Methodology/Principal findings We adjusted machine learning models on leptospirosis surveillance data from seven tropical islands (Guadeloupe, Reunion Island, Fiji, Futuna, New Caledonia, and Tahiti) to investigate 1) the effect of climate on the disease's seasonal dynamic, i.e., the centered seasonal profile and 2) inter-annual anomalies, i.e., the incidence deviations from the seasonal profile. The model was then used to estimate seasonal dynamics of leptospirosis in Vanuatu and Puerto Rico where disease incidence data were not available. A robust model, validated across different islands with leave-island-out cross-validation and based on current and 2-month lagged precipitation and current and 1-month lagged temperature, can be constructed to estimate the seasonal dynamic of leptospirosis. In opposition, climate determinants and their importance in estimating inter-annual anomalies highly differed across islands.Conclusions/Significance Climate appears as a strong determinant of leptospirosis seasonality in tropical islands regardless of the diversity of the considered environments and the different lifestyles across the islands. However, predictive and expandable abilities from climate indicators weaken when estimating inter-annual outbreaks and emphasize the importance of these local characteristics in the occurrence of outbreaks. Tropical islands are particularly vulnerable to leptospirosis outbreaks. Hot and rainy climate, abundance of reservoir species and outdoor lifestyle contribute to the high risk for human infection. These isolated areas also deal with difficulties associated with diagnosis because of low awareness of the medical staff, non-specific symptoms of leptospirosis and limited availability of laboratory testing. Leptospirosis remains poorly documented, and a better understanding of its dynamics and its climate drivers would help improve awareness and preparedness of the public health services. In this study, we provide a climate-based model of leptospirosis seasonal dynamics in 7 tropical islands. The use of climate variables from publicly available satellite data makes the model expandable to predict leptospirosis seasonal dynamics in other tropical islands where the disease is not routinely monitored. This study emphasizes the importance of rainfall and temperature in driving the seasonality of leptospirosis in tropical islands. However, climate alone did not appear to not be a sufficient indicator to predict interannual variations, suggesting that the risk of leptospirosis outbreaks must be refined, considering local specificities as the lifestyle and the very local environment.