title: Malaria incidence from 2005-2013 and its associations with meteorological factors in Guangdong, China.
abstract: BACKGROUND
  The temporal variation of malaria incidence has been linked to meteorological factors in many studies, but key factors observed and corresponding effect estimates were not consistent. Furthermore, the potential effect modification by individual characteristics is not well documented. This study intends to examine the delayed effects of meteorological factors and the sub-population's susceptibility in Guangdong, China.
  
  
  METHODS
  The Granger causality Wald test and Spearman correlation analysis were employed to select climatic variables influencing malaria. The distributed lag non-linear model (DLNM) was used to estimate the non-linear and delayed effects of weekly temperature, duration of sunshine, and precipitation on the weekly number of malaria cases after controlling for other confounders. Stratified analyses were conducted to identify the sub-population's susceptibility to meteorological effects by malaria type, gender, and age group.
  
  
  RESULTS
  An incidence rate of 1.1 cases per 1,000,000 people was detected in Guangdong from 2005-2013. High temperature was associated with an observed increase in malaria incidence, with the effect lasting for four weeks and a maximum relative risk (RR) of 1.57 (95% confidence interval (CI): 1.06-2.33) by comparing 30°C to the median temperature. The effect of sunshine duration peaked at lag five and the maximum RR was 1.36 (95% CI: 1.08-1.72) by comparing 24 hours/week to 0 hours/week. A J-shaped relationship was found between malaria incidence and precipitation with a threshold of 150 mm/week. Over the threshold, precipitation increased malaria incidence after four weeks with the effect lasting for 15 weeks, and the maximum RR of 1.55 (95% CI: 1.18-2.03) occurring at lag eight by comparing 225 mm/week to 0 mm/week. Plasmodium falciparum was more sensitive to temperature and precipitation than Plasmodium vivax. Females had a higher susceptibility to the effects of sunshine and precipitation, and children and the elderly were more sensitive to the change of temperature, sunshine duration, and precipitation.
  
  
  CONCLUSIONS
  Temperature, duration of sunshine and precipitation played important roles in malaria incidence with effects delayed and varied across lags. Climatic effects were distinct among sub-groups. This study provided helpful information for predicting malaria incidence and developing the future warning system.
authors.affiliation: State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China. guocui815@163.com.
authors.forename: Cui
authors.initials: C
authors.lastname: Guo
authors.affiliation: Department of Nursing, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University, Hong Kong, China. l.yang@polyu.edu.hk.
authors.forename: Lin
authors.initials: L
authors.lastname: Yang
authors.affiliation: State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China. ouchunquan@hotmail.com.
authors.forename: Chun-Quan
authors.initials: CQ
authors.lastname: Ou
authors.affiliation: State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China. lylygdsg@163.com.
authors.forename: Li
authors.initials: L
authors.lastname: Li
authors.affiliation: State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China. zhuangy178@126.com.
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhuang
authors.affiliation: State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. smart_yjun@163.com.
authors.forename: Jun
authors.initials: J
authors.lastname: Yang
authors.affiliation: State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China. ying2360@126.com.
authors.forename: Ying-Xue
authors.initials: YX
authors.lastname: Zhou
authors.affiliation: Department of Mathematics and Physics, School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China. qianjun_gz@126.com.
authors.forename: Jun
authors.initials: J
authors.lastname: Qian
authors.affiliation: State Key Laboratory of Organ Failure Research, Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, 510515, China. chenpy99@126.com.
authors.forename: Ping-Yan
authors.initials: PY
authors.lastname: Chen
authors.affiliation: State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China. liuqiyong@cdc.cn.
authors.forename: Qi-Yong
authors.initials: QY
authors.lastname: Liu
mesh_terms: D000293:Adolescent; D000328:Adult; D002648:Child; D002675:Child, Preschool; D002681:China / Q000453:epidemiology; D005260:Female; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D008288:Malaria / Q000453:epidemiology*; D008297:Male; D008685:Meteorological Concepts; D008875:Middle Aged; D017711:Nonlinear Dynamics; D012306:Risk; D055815:Young Adult