Background: The influence of rising global temperatures on malaria dynamics and distribution remains controversial, especially in central highland regions. We aimed to address this subject by studying the spatiotempor...
Background: The influence of rising global temperatures on malaria dynamics and distribution remains controversial, especially in central highland regions. We aimed to address this subject by studying the spatiotemporal heterogeneity of malaria and the effect of climate change on malaria transmission over 27 years in Hainan, an island province in China. Methods: for this longitudinal cohort study, we used a decades-long dataset of malaria incidence reports from Hainan, China, to investigate the pattern of malaria transmission in Hainan relative to temperature and the incidence at increasing altitudes. Climatic data were obtained from the local meteorological stations in Hainan during 1984–2010 and the WorldClim dataset. A temperature-dependent R0 model and negative binomial generalised linear model were used to decipher the relationship between climate factors and malaria incidence in the tropical region. Findings: Over the past few decades, the annual peak incidence has appeared earlier in the central highland regions but later in low-altitude regions in Hainan, China. Results from the temperature-dependent model showed that these long-term changes of incidence peak timing are linked to rising temperatures (of about 1·5°C). Further, a 1°C increase corresponds to a change in cases of malaria from –5·6% (95% CI –4·5 to –6·6) to –9·2% (95% CI –7·6 to –10·9) from the northern plain regions to the central highland regions during the rainy season. In the dry season, the change in cases would be 4·6% (95% CI 3·7 to 5·5) to 11·9% (95% CI 9·8 to 14·2) from low-altitude areas to high-altitude areas. Interpretation: Our study empirically supports the idea that increasing temperatures can generate opposing effects on malaria dynamics for lowland and highland regions. This should be further investigated and incorporated into future modelling, disease burden calculations, and malaria control, with attention for central highland regions under climate change. Funding: S
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