Influence of climate and heatwaves on dengue transmission in Sao Paulo and Natal, Brazil

气候和热浪对巴西圣保罗和纳塔尔登革热传播的影响

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Abstract

Dengue fever, a mosquito-borne viral disease, poses a significant public health challenge whose transmission dynamics are highly sensitive to climatic conditions. However, the effects of extreme weather events like heatwaves remain poorly understood. This study investigated the influence of climatic factors and heatwaves on dengue incidence in two key Brazilian hotspots: the subtropical megacity of São Paulo (Sao Paulo State) and the tropical coastal city of Natal (Rio Grande do Norte State). We analyzed weekly confirmed dengue cases and meteorological data (temperature, precipitation, heatwaves) from 2014 to 2023. Distributed lag non-linear models and negative binomial regression were used to assess the complex, delayed associations between meteorological variables and dengue infections. Over the study period, 149,468 dengue cases were reported in São Paulo and 80,999 in Natal. Transmission patterns differed significantly, with Natal exhibiting more regular epidemic cycles. Our models revealed that higher minimum temperatures were associated with increased dengue risk in both cities. Conversely, and perhaps counter-intuitively, higher maximum temperatures and total precipitation showed negative associations with dengue cases. The impact of heatwaves was strikingly different between the locations. In São Paulo, the occurrence of a heatwave was associated with a 70% reduction in dengue risk in subsequent weeks (Relative Risk [RR]: 0.30, 95% Confidence Interval [CI]: 0.18-0.49). In contrast, no statistically significant association between heatwaves and dengue was observed in Natal. Our findings demonstrate that the relationship between extreme heat and dengue transmission is not uniform and can be inhibitory, challenging the assumption that warming consistently favors vector proliferation. These location-specific insights are critical for developing more accurate, tailored public health early-warning systems and caution against one-size-fits-all climate adaptation strategies for vector-borne diseases.

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