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Home / Malaria Research / Can Slide Positivity Rates Predict Malaria Transmission?

Can Slide Positivity Rates Predict Malaria Transmission?

April 18, 2012 By Malaria.com Leave a Comment

Malaria is a significant threat to population health in the border areas of Yunnan Province, China. How to accurately measure malaria transmission is an important issue. This study aimed to examine the role of slide positivity rates (SPR) in malaria transmission in Mengla County, Yunnan Province, China.

Methods
Data on annual malaria cases, SPR and socio-economic factors for the period of 1993 to 2008 were obtained from the Center for Disease Control and Prevention (CDC) and the Bureau of Statistics, Mengla, China. Multiple linear regression models were conducted to evaluate the relationship between socio-ecologic factors and malaria incidence.

Results
The results show that SPR was significantly positively associated with the malaria incidence rates. The SPR (beta = 1.244, p = 0.000) alone and combination (SPR, beta = 1.326, p < 0.001) with other predictors can explain about 85% and 95% of variation in malaria transmission, respectively. Every 1% increase in SPR corresponded to an increase of 1.76/100,000 in malaria incidence rates.

Conclusion
SPR is a strong predictor of malaria transmission, and can be used to improve the planning and implementation of malaria elimination programmes in Mengla and other similar locations. SPR might also be a useful indicator of malaria early warning systems in China.

Reference: Malaria Journal 2012, 11:117 doi:10.1186/1475-2875-11-117

Copyyight © 2012 Yan Bi, Wenbiao Hu, Huaxin Liu, Yujiang Xiao, Yuming Guo, Shimei Chen, Laifa Zhao and Shilu Tong.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Full Article: Can Slide Positivity Rates Predict Malaria Transmission? (Provisional PDF)

Filed Under: Malaria Research Tagged With: ancient China, China, Huaxin Liu, Laifa Zhao, Malaria Journal, Shilu Tong, Shimei Chen, Wenbiao Hu, Yan Bi, Yujiang Xiao, Yuming Guo

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