Résumé
IntroductionLeptospirosis is a neglected disease of growing concern worldwide and rarely monitored by health systems. In Southeast Asia, only Thailand has evidenced its heavy burden on population thank to an efficient national surveillance system.ObjectivesBecause leptospirosis outbreaks are closely associated with climatic and environmental dynamics, this study aimed to model the current and future spatial distribution of Leptospirosis at provincial scale in mainland Southeast Asia, based on climate and environmental determinants.Material and methodWe first adjusted machine-learning models by analyzing the monthly reported cases of leptospirosis from 2003 to 2019 per province in Thailand. We only included the climatic and environmental data available over the whole study area. We selected the best model to estimate the actual distribution before forecasting its evolution under future climate projections over four 20-year periods from 2021 to 2100. We used six global models (CMIP6) and 4 Shared Socio-economics Pathways ranging from the most optimistic to the no-climate policy outcomes (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5).ResultsWe identified 10 environmental variables (four landscape-, four rainfall-, two temperature-related variables) that, taken together in our model, could predict leptospirosis burden in Thailand. Applying this model to Myanmar, Cambodia, Vietnam and Laos revealed the importance of this disease in territories where it is not diagnosed. We showed that Leptospirosis burden is likely to decline in the region as climate scenario worsen.The greatest decline, mainly driven by increasing temperatures, is observed under the worst-case climate scenario (SSP5-8.5). These global patterns are however contrasted regionally with some regions showing increased incidence in the future.ConclusionThese new results will help to raise awareness on leptospirosis by clarifying its extent and its associated climate and environmental factors.