Can slide positivity rates predict malaria transmission?

17Citations
Citations of this article
57Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

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. © 2012 Bi et al; licensee BioMed Central Ltd.

Figures

  • Figure 1 The location of Mengla County, Yunnan Province, China.
  • Figure 2 Malaria incidence and slide positivity rates (SPR) in Mengla C
  • Figure 3 The relationship between slide positivity rates and crude malaria incidence in Mengla.
  • Table 1 Spearman correlations between malaria incidence and social and climatic variables, 1993-2008
  • Table 2 Association between malaria incidence and SPR in Mengla, China 1993-2008
  • Table 3 Regression coefficients of the best model
  • Figure 4 Regressive forecasts of annual malaria incidence in Mengla, China, 1993–2008, including SPR (A); and not including SPR (B).

References Powered by Scopus

Get full text
Get full text

Climate change and mosquito-borne disease

637Citations
639Readers
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Bi, Y., Hu, W., Liu, H., Xiao, Y., Guo, Y., Chen, S., … Tong, S. (2012). Can slide positivity rates predict malaria transmission? Malaria Journal, 11. https://doi.org/10.1186/1475-2875-11-117

Readers over time

‘12‘13‘14‘15‘16‘17‘18‘19‘20‘21‘22‘23‘240481216

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 20

53%

Researcher 8

21%

Lecturer / Post doc 6

16%

Professor / Associate Prof. 4

11%

Readers' Discipline

Tooltip

Medicine and Dentistry 13

46%

Agricultural and Biological Sciences 10

36%

Nursing and Health Professions 3

11%

Social Sciences 2

7%

Save time finding and organizing research with Mendeley

Sign up for free
0