Decision support

Lotto Batista M et al. – J. Roy. Soc. Interface

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

The Lancet Regional Health – Europe
This article discusses the complexities of tracking the links between climate, health, and justice across regions and time. It calls for better, standardized data systems to address disparities and guide equitable policy interventions globally.

DOI: 10.1016/S2468-2667(23)00051-8

Claudia Di Napoli et al. – Meteorological Applications

This article highlights the need for climate-smart decisions in public health due to extreme weather events. The Lancet Countdown system uses reanalysis datasets like ERA5 to track global climate-related health impacts, such as heatwaves and disease transmission, and provides indicators to measure these effects. Public health professionals should collaborate to refine these datasets for better health outcomes.

DOI: 10.1002/met.2122