Diagnostic approaches to malaria in Zambia, 2009-2014

Submitted: 16 February 2015
Accepted: 9 April 2015
Published: 3 June 2015
Abstract Views: 3160
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Malaria is an important health burden in Zambia with proper diagnosis remaining as one of the biggest challenges. The need for reliable diagnostics is being addressed through the introduction of rapid diagnostic tests (RDTs). However, without sufficient laboratory amenities in many parts of the country, diagnosis often still relies on non-specific, clinical symptoms. In this study, geographical information systems were used to both visualize and analyze the spatial distribution and the risk factors related to the diagnosis of malaria. The monthly reported, district-level number of malaria cases from January 2009 to December 2014 were collected from the National Malaria Control Center (NMCC). Spatial statistics were used to reveal cluster tendencies that were subsequently linked to possible risk factors, using a non-spatial regression model. Significant, spatio-temporal clusters of malaria were spotted while the introduction of RDTs made the number of clinically diagnosed malaria cases decrease by 33% from 2009 to 2014. The limited access to road network(s) was found to be associated with higher levels of malaria, which can be traced by the expansion of health promotion interventions by the NMCC, indicating enhanced diagnostic capability. The capacity of health facilities has been strengthened with the increased availability of proper diagnostic tools and through retraining of community health workers. To further enhance spatial decision support systems, a multifaceted approach is required to ensure mobilization and availability of human, infrastructural and technological resources. Surveillance based on standardized geospatial or other analytical methods should be used by program managers to design, target, monitor and assess the spatio-temporal dynamics of malaria diagnostic resources country-wide.

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Supporting Agencies

partly funded by the Emerging Pathogens Institute at the University of Florida and the College of Liberal Arts and Sciences, as part of the University of Florida Pre-eminence Initiative

How to Cite

Mukonka, V. M., Chanda, E., Kamuliwo, M., Elbadry, M. A., Wamulume, P. K., Mwanza-Ingwe, M., Lubinda, J., Laytner, L. A., Zhang, W., Mushinge, G., & Haque, U. (2015). Diagnostic approaches to malaria in Zambia, 2009-2014. Geospatial Health, 10(1). https://doi.org/10.4081/gh.2015.330

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