Can slide positivity rates predict malaria transmission?

Bi, Yan, Hu, Wenbiao, Liu, Huaxin, Xiao, Yujiang, Guo, Yuming, Chen, Shimei, Zhao, Laifa, & Tong, Shilu (2012) Can slide positivity rates predict malaria transmission? Malaria Journal, 11(117).

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Background: 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.

Impact and interest:

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ID Code: 54910
Item Type: Journal Article
Refereed: Yes
Keywords: Malaria transmission, Slide positivity rates, Malaria elimination, International border areas, China
DOI: 10.1186/1475-2875-11-117
ISSN: 1475-2875
Subjects: Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > PUBLIC HEALTH AND HEALTH SERVICES (111700) > Epidemiology (111706)
Divisions: Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Current > Schools > School of Public Health & Social Work
Copyright Owner: Copyright 2012 Bi et al.
Copyright Statement: 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.
Deposited On: 20 Nov 2012 22:56
Last Modified: 09 Apr 2014 12:21

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