Mapping Risk of Malaria as a Function of Anthropic and Environmental Conditions in Sussundenga Village, Mozambique

João L. Ferrão, Dominique Earland, Anísio Novela, Roberto Mendes, Marcos F. Ballat, Alberto Tungaza and Kelly M. Searle
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João L. Ferrão: Instituto Superior de Ciências e Educação a Distância, Beira 2102, Mozambique
Dominique Earland: School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA
Anísio Novela: Direcção Distrital de Saúde de Sussundenga, Sussundenga 2207, Mozambique
Roberto Mendes: Centro de Informação Geográfica-Faculdade de Economia da UCM, Beira 2102, Mozambique
Marcos F. Ballat: Faculdade de Ciência de Saúde da UCM, Beira 2102, Mozambique
Alberto Tungaza: Faculdade de Engenharia da UCM, Chimoio 2203, Mozambique
Kelly M. Searle: School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA

IJERPH, 2021, vol. 18, issue 5, 1-16

Abstract: Mozambique is a country in Southern Africa with around 30 million inhabitants. Malaria is the leading cause of mortality in the country. According to the WHO, Mozambique has the third highest number of malaria cases in the world, representing approximately 5% of the world total cases. Sussundenga District has the highest incidence in the Manica province and environmental conditions are the major contributor to malaria transmission. There is a lack of malaria risk maps to inform transmission dynamics in Sussundenga village. This study develops a malaria risk map for Sussundenga Village in Mozambique and identifies high risk areas to inform on appropriate malaria control and eradication efforts. One hundred houses were randomly sampled and tested for malaria in Sussundenga Rural Municipality. To construct the map, a spatial conceptual model was used to estimate risk areas using ten environmental and anthropic factors. Data from Worldclim, 30 × 30 Landsat images were used, and layers were produced in a raster data set. Layers between class values were compared by assigning numerical values to the classes within each layer of the map with equal rank. Data set input was classified, using diverse weights depending on their appropriateness. The reclassified data outputs were combined after reclassification. The map indicated a high risk for malaria in the northeast and southeast, that is, the neighborhoods of Nhamazara, Nhamarenza, and Unidade. The central eastern areas, that is, 25 de Junho, 1 and 2, 7 de Abril, and Chicueu presented a moderate risk. In Sussundenga village there was 92% moderate and 8% high risk. High malaria risk areas are most often located in densely populated areas and areas close to water bodies. The relevant findings of this study can inform on effective malaria interventions.

Keywords: mapping; risk; malaria; Sussundenga village (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
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