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Malaria Incidence from 2005-2013 and Its Associations with Meteorological Factors in Guangdong, China

Overview
Journal Malar J
Publisher Biomed Central
Specialty Tropical Medicine
Date 2015 Apr 17
PMID 25881185
Citations 29
Authors
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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.

Conclusion: 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.

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References
1.
Loevinsohn M . Climatic warming and increased malaria incidence in Rwanda. Lancet. 1994; 343(8899):714-8. DOI: 10.1016/s0140-6736(94)91586-5. View

2.
Ree H . Studies on Anopheles sinensis, the vector species of vivax malaria in Korea. Korean J Parasitol. 2005; 43(3):75-92. PMC: 2712014. DOI: 10.3347/kjp.2005.43.3.75. View

3.
Zhao X, Chen F, Feng Z, Li X, Zhou X . The temporal lagged association between meteorological factors and malaria in 30 counties in south-west China: a multilevel distributed lag non-linear analysis. Malar J. 2014; 13:57. PMC: 3932312. DOI: 10.1186/1475-2875-13-57. View

4.
Chatterjee C, Sarkar R . Multi-step polynomial regression method to model and forecast malaria incidence. PLoS One. 2009; 4(3):e4726. PMC: 2648889. DOI: 10.1371/journal.pone.0004726. View

5.
Bhaskaran K, Gasparrini A, Hajat S, Smeeth L, Armstrong B . Time series regression studies in environmental epidemiology. Int J Epidemiol. 2013; 42(4):1187-95. PMC: 3780998. DOI: 10.1093/ije/dyt092. View