Climatic factors drive global viral respiratory infections with regional heterogeneity: A systematic review and meta-analysis

Background

Climate change is altering global respiratory virus transmission, yet pathogen-specific climate sensitivities remain unclear across diverse geographical settings.

Methods

We searched six databases (inception–10 May 2024) for studies quantifying associations between climate factors and virus respiratory infections (VRIs). Random-effects models pooled relative risks (RRs) per unit increase in temperature, relative humidity, precipitation, and wind speed, with climate sensitivity assessed by Köppen-Geiger zones.

Results

From 108 studies comprising 9.22 million VRI cases, three climate patterns emerged. First, temperature was the dominant driver: each 1°C increase reduced respiratory syncytial virus (RSV; RR 0.13, 95% CI 0.08–0.22), influenza virus (IV; RR 0.37, 95% CI 0.23–0.58), human metapneumovirus (HMPV; RR 0.48, 95% CI 0.32–0.73), SARS-CoV-2 (RR 0.52, 95% CI 0.35–0.78), and human coronavirus (HCoV; RR 0.21, 95% CI 0.07–0.61) risks, but increased parainfluenza virus (PIV; RR 2.35, 95% CI 1.46–3.77) and human bocavirus (HBoV; RR 1.86, 95% CI 1.04–3.32) risks. Second, other climate factors showed selective effects: higher humidity decreased IVB risk (RR 0.61, 95% CI 0.40–0.94) but increased enterovirus risk (RR 2.21, 95% CI 1.08–4.51); precipitation decreased IV risk (RR 0.67, 95% CI 0.51–0.89) but increased PIV risk (RR 1.91, 95% CI 1.21–2.99); wind speed amplified IV (RR 1.51, 95% CI 1.01–2.27) and HCoV transmission (RR 5.36, 95% CI 3.43–8.38). Third, climate-zone analyses revealed substantial heterogeneity: in temperate regions, low temperature and humidity increased the risk of most infections (except PIV and HBoV); risks of SARS-CoV-2 and SARS-CoV risks decreased in temperate but increased in continental regions; RSV and HMPV showed greater sensitivity in tropical regions; while in arid regions, MERS-CoV risk increased with temperature but decreased with humidity and wind speed.

Conclusion

This analysis identified climate-sensitive VRIs with temperature as key predictor, pathogen-specific sensitivities, and distinct regional patterns, informing targeted climate-based intervention strategies.