LAUSR

SUMMARY This study aims to investigate the climate–malaria associations in nine cities selected from malaria high-risk areas in China. Daily reports of malaria cases in Anhui, Henan, and Yunnan Provinces for 2005–2012 were obtained from the Chinese Center for Disease Control and Prevention. Generalized estimating equation models were used to quantify the city-specific climate–malaria associations. Multivariate random-effects meta-regression analyses were used to pool the city-specific effects. An inverted-U-shaped curve relationship was observed between temperatures, average relative humidity, and malaria. A 1 °C increase of maximum temperature (T max) resulted in 6·7% (95% CI 4·6–8·8%) to 15·8% (95% CI 14·1–17·4%) increase of malaria, with corresponding lags ranging from 7 to 45 days. For minimum temperature (T min), the effect estimates peaked at lag 0 to 40 days, ranging from 5·3% (95% CI 4·4–6·2%) to 17·9% (95% CI 15·6–20·1%). Malaria is more sensitive to T min in cool climates and T max in warm climates. The duration of lag effect in a cool climate zone is longer than that in a warm climate zone. Lagged effects did not vanish after an epidemic season but waned gradually in the following 2–3 warm seasons. A warming climate may potentially increase the risk of malaria resurgence in China.