Lotto Batista M et al. – J. Roy. Soc. Interface, 17 May 2023
This study demonstrates that hydrometeorological indicators, including El Niño, precipitation, and river height, are strong predictors of leptospirosis outbreaks in northeastern Argentina. By using a Bayesian modelling framework, the researchers found that climate-driven models accurately detected 89% of outbreaks, suggesting that such tools could effectively contribute to an early warning system for leptospirosis in the region.
DOI: 10.1098/rsif.2023.0069