Research

One-year delayed effect of fog on malaria transmission: a time-series analysis in the rain forest area of Mengla County, south-west China

Linwei Tian^1* , Yan Bi^2* , Suzanne C Ho^1,3 , Wenjie Liu⁴ , Song Liang⁵ , William B Goggins⁶ , Emily YY Chan³ , Shuisen Zhou⁷ and Joseph JY Sung¹

¹  Stanley Ho Center for Emerging Infectious Diseases, School of Public Health, Chinese University of Hong Kong, Hong Kong, PR China

²  Yunnan Province Center for Disease Control and Prevention, Kunming, PR China

³  Department of Community and Family Medicine, School of Public Health, Chinese University of Hong Kong, Hong Kong, PR China

⁴  Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming, PR China

⁵  College of Public Health, Ohio State University, Columbus, Ohio, USA

⁶  Division of Biostatistics, School of Public Health, Chinese University of Hong Kong, Hong Kong, PR China

⁷  National Malaria Office, National Institute for Parasitic Diseases, Shanghai, PR China

author email corresponding author email* Contributed equally

Malaria Journal 2008, 7:110doi:10.1186/1475-2875-7-110

Published:	19 June 2008

Abstract

Background

Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China.

Methods

Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence.

Results

At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria.

Conclusion

Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide.