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High-Resolution Plasmodium falciparum Malaria Risk Mapping in Mutasa District, Zimbabwe: Implications for Regaining Control

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  • 1 Department of International Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland.
  • | 2 Biomedical Research and Training Institute, Harare, Zimbabwe.
  • | 3 Department of Medical Laboratory Sciences, College of Health Sciences, University of Zimbabwe, Harare, Zimbabwe.
  • | 4 Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland.
  • | 5 National Institute of Health Research, Harare, Zimbabwe.
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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.

Author Notes

* Address correspondence to Mufaro Kanyangarara, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, 615 North Wolfe Street, Baltimore, MD 21205. E-mail: mkanyan1@jhu.edu

Financial support: This work was supported by the Division of Microbiology and Infectious Diseases, National Institutes of Allergy and Infectious Diseases, National Institutes of Health as part of the International Centers of Excellence for Malaria Research (U19 AI089680).

Authors' addresses: Mufaro Kanyangarara and Luke C. Mullany, Department of International Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, E-mails: mkanyan1@jhu.edu and lmullany@jhu.edu. Edmore Mamini, Sungano Mharakurwa, Shungu Munyati, and Peter R. Mason, Biomedical Research and Training Institute, Harare, Zimbabwe, E-mails: edmoremamini@gmail.com, smharak1@jhu.edu, smunyati@brti.co.zw, and pmason@brti.co.zw. Lovemore Gwanzura, Department of Medical Laboratory Sciences, College of Health Sciences, University of Zimbabwe, Harare, Zimbabwe, E-mail: gwanzura@mweb.co.zw. Tamaki Kobayashi, Timothy Shields, Frank C. Curriero, and William J. Moss, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, E-mails: tkobaya2@jhu.edu, tshield2@jhu.edu, fcurriero@jhu.edu, and wmoss1@jhu.edu. Susan Mutambu, National Institute of Health Research, Harare, Zimbabwe, E-mail: mutambusl@gmail.com.

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