TY - JOUR
T1 - Can slide positivity rates predict malaria transmission?
AU - Bi, Yan
AU - Hu, Wenbiao
AU - Liu, Huaxin
AU - Xiao, Yujiang
AU - Guo, Yuming
AU - Chen, Shimei
AU - Zhao, Laifa
AU - Tong, Shilu
PY - 2012
Y1 - 2012
N2 - 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 (=1.244, p=0.000) alone and combination (SPR, =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.
AB - 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 (=1.244, p=0.000) alone and combination (SPR, =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.
KW - China
KW - International border areas
KW - Malaria elimination
KW - Malaria transmission
KW - Slide positivity rates
UR - http://www.scopus.com/inward/record.url?scp=84862202617&partnerID=8YFLogxK
U2 - 10.1186/1475-2875-11-117
DO - 10.1186/1475-2875-11-117
M3 - Article
C2 - 22513123
AN - SCOPUS:84862202617
VL - 11
JO - Malaria Journal
JF - Malaria Journal
SN - 1475-2875
M1 - 117
ER -