Research Articles Public Health Reports / January–February 2003 / Volume 118  65 Climatic Variables and Transmission of Malaria: A 12-Year Data Analysis in Shuchen County, China Peng Bi, MBBS, PhD a Shilu Tong, MBBS, PhD b Ken Donald, MBBS, PhD c Kevin A Parton, BCom, MSc, PhD d Jinfa Ni, MBBS e a Centre for Healthcare Related Infection Surveillance and Prevention, Princess Alexandra Hospital, Brisbane, Australia b Centre for Public Health Research, Queensland University of Technology, Brisbane, Australia c Graduate School of Medicine, University of Queensland, Brisbane, Australia d Faculty of Rural Management, University of Sydney, Orange, Australia e Department of Epidemiology, An Hui Medical University, Hefei, China Address correspondence to: Peng Bi, MBBS, PhD, Centre for Healthcare Related Infection Surveillance and Prevention, Princess Alexandra Hosp., Ipswich Rd., Brisbane, QLD 4102 Australia; tel. 61 7 3240 5799; fax 61 7 3240 5540; e-mail: <peng_bi@health.qld.gov.au>. ©2003 Association of Schools of Public Health SYNOPSIS Objective. The objective of this study was to explore the impact of climate variability on the transmission of malaria, a vector-borne disease, in a county of China and provide suggestions to similar regions for disease prevention. Methods. A time-series analysis was conducted using data on monthly climatic variables and monthly incidence of malaria in Shuchen County, China, for the period 1980–1991. Results. Spearman’s correlation analysis showed that monthly mean maximum and minimum temperatures, two measures of monthly mean relative humidity, and monthly amount of precipitation were positively correlated with the monthly incidence of malaria in the county. Regression analysis suggested that monthly mean minimum temperature and total monthly rainfall, with a one- month lagged effect, were significant climatic variables in the transmission of malaria in Shuchen County. Seaonality was also significant in the regression model and there was a declining secular trend in the incidence of malaria. Conclusion. The results indicate that climatic variables should be considered as possible predictors for regions with similar geographic, climatic, and socioeco- nomic conditions to those of Shuchen County.