Spatial-temporal analysis of malaria and the effect of environmental factors on its incidence in Yongcheng, China, 2006–2010

BMC Public Health

Zhi-Fang Li⁵  Hong-Sheng Li³  Jing-Yi Jiang³  Guang-Chao Zhou³  Xiao-Bo Liu⁵  Rong-Sheng Luan¹  Qi-Yong Liu²  Yan Zhang⁴ 

[1]Department of Epidemiology, West China School of Public Health, Sichuan University, Chengdu, People’s Republic of China

[2]Shandong University Climate Change and Health Center, Jinan, People’s Republic of China

[3]Yongcheng Center for Disease Control and Prevention, Yongcheng prefecture, People’s Republic of China

[4]Fengtai Center for Disease Control and Prevention, Beijing, People’s Republic of China

[5]State Key Laboratory for Infectious Diseases Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People’s Republic of China

关键词: Modeling;    Geographic information system;    Weather;    Anopheles;    Malaria;   

Others  :  1163431
DOI  :  10.1186/1471-2458-12-544

 received in 2011-12-13, accepted in 2012-06-30,  发布年份 2012

【 摘 要 】

Background

In 2003, Plasmodium vivax malaria has re-emerged in central eastern China including Yongcheng prefecture, Henan Province, where no case has been reported for eleven years. Our goals were to detect the space-time distribution pattern of malaria and to determine significant environmental variables contributing to malaria incidence in Yongcheng from 2006 to 2010, thus providing scientific basis for further optimizing current malaria surveillance and control programs.

Methods

This study examined the spatial and temporal heterogeneities in the risk of malaria and the influencing factors on malaria incidence using geographical information system (GIS) and time series analysis. Univariate analysis was conducted to estimate the crude correlations between malaria incidence and environmental variables, such as mosquito abundance and climatic factors. Multivariate analysis was implemented to construct predictive models to explore the principal environmental determinants on malaria epidemic using a Generalized Estimating Equation (GEE) approach.

Results

Annual malaria incidence at town-level decreased from the north to south, and monthly incidence at prefecture-level demonstrated a strong seasonal pattern with a peak from July to November. Yearly malaria incidence had a visual spatial association with yearly average temperature. Moreover, the best-fit temporal model (model 2) (QIC = 16.934, P<0.001, R² = 0.818) indicated that significant factors contributing to malaria incidence were maximum temperature at one month lag, average humidity at one month lag, and malaria incidence of the previous month.

Conclusions

Findings supported the effects of environment factors on malaria incidence and indicated that malaria control targets should vary with intensity of malaria incidence, with more public resource allocated to control the source of infections instead of large scale An. sinensis control when malaria incidence was at a low level, which would benefit for optimizing the malaria surveillance project in China and some other countries with unstable or low malaria transmission.

【 授权许可】

   
2012 Zhang et al.; licensee BioMed Central Ltd.

【 图 表 】

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