Spatial and Climatic Analysis of the 2025 Chikungunya Re-emergence in Mauritius
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Background
Chikungunya re-emerged in Mauritius in 2025 after a 19-year period with no outbreak. As precipitation and temperature play a key role in mosquito proliferation, the climatic conditions prevailing in Mauritius in 2025 may have influenced the emergence and spread of the outbreak. Our aim in this study was to investigate the spatial distribution of the 2025 chikungunya outbreak in Mauritius, and to determine the association between chikungunya incidence and selected predictor variables using Geographic Information Systems (GIS).
Methods
The variables considered were mean altitude, mean air temperature and mean precipitation, population density, road density, number of houses near rivers and the relative deprivation index (RDI) per village council area (VCA) and municipal ward (MW). Rainfall and temperature data were obtained from the climate bulletins of the Mauritius Meteorological Services and were also extracted from the ERA5 Monthly Averaged Data on Single levels available from the platform of Copernicus Climate Data Store. The U.S. Geological Survey Earth Explorer platform was used to access elevation data for Mauritius. In the absence of official case data, reported chikungunya cases were reconstructed from multiple publicly accessible media sources. Information was collected contemporaneously as the outbreak evolved during 2025 and was supplemented by searches of archived material. Cases were georeferenced and aggregated to VCAs and MWs. All data was mapped using QGIS version 3.40.13.
Results
The main findings were that the 2025 chikungunya outbreak was significantly associated with elevation and precipitation. Temporal analysis demonstrated that rainfall in the preceding month was the strongest climatic predictor of monthly chikungunya cases. Spatial analysis, however, showed that mean precipitation had a significant ( p -value < 0.001) and negative association with chikungunya incidence, indicating lower disease occurrence in areas of high precipitation. Mean elevation was significantly ( p -value < 0.001) and negatively associated with chikungunya incidence, indicating lower disease occurrence in higher-altitude areas. Temperature did not have any significant relationship with chikungunya incidence.
Conclusions
Rainfall had opposite associations depending on the analytical scale: preceding-month rainfall was positively associated with temporal case variation, whereas spatially averaged precipitation was negatively associated with incidence. Thus, rainfall exerted distinct temporal and spatial influences on chikungunya transmission, while higher elevation was associated with lower chikungunya incidence. These findings highlight the importance of integrating climatic and spatial analyses to improve surveillance
