| Literature DB >> 27114294 |
Mufaro Kanyangarara1, Edmore Mamini2, Sungano Mharakurwa2, Shungu Munyati2, Lovemore Gwanzura3, Tamaki Kobayashi4, Timothy Shields4, Luke C Mullany5, Susan Mutambu6, Peter R Mason2, Frank C Curriero4, William J Moss.
Abstract
In Zimbabwe, more than half of malaria cases are concentrated in Manicaland Province, where seasonal malaria epidemics occur despite intensified control strategies. The objectives of this study were to develop a prediction model based on environmental risk factors and obtain seasonal malaria risk maps for Mutasa District, one of the worst affected districts in Manicaland Province. From October 2012 to September 2015, 483 households were surveyed, and 104 individuals residing within 69 households had positive rapid diagnostic test results. Logistic regression was used to model the probability of household positivity as a function of the environmental covariates extracted from high-resolution remote sensing data sources. Model predictions and prediction standard errors were generated for the rainy and dry seasons. The resulting maps predicted elevated risk during the rainy season, particularly in low-lying areas bordering Mozambique. In contrast, the risk of malaria was low across the study area during the dry season with foci of malaria risk scattered along the northern and western peripheries of the study area. These findings underscore the need for strong cross-border malaria control initiatives to complement country-specific interventions. © The American Society of Tropical Medicine and Hygiene.Entities:
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Year: 2016 PMID: 27114294 PMCID: PMC4944678 DOI: 10.4269/ajtmh.15-0865
Source DB: PubMed Journal: Am J Trop Med Hyg ISSN: 0002-9637 Impact factor: 2.345