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Mapping and Modelling Malaria Risk Areas Using Climate, Socio-Demographic and Clinical Variables in Chimoio, Mozambique

Author

Listed:
  • Joao L. Ferrao

    (Faculdade de Engenharia, Universidade Católica de Moçambique, Chimoio 20106, Mozambique)

  • Sergio Niquisse

    (GIS Department, Faculdade de Economia e Gestão, Universidade Católica de Moçambique, Beira 2107, Mozambique)

  • Jorge M. Mendes

    (NOVA Information Management School, Universidade Nova de Lisboa, 1000-260 Lisboa, Portugal)

  • Marco Painho

    (NOVA Information Management School, Universidade Nova de Lisboa, 1000-260 Lisboa, Portugal)

Abstract

Background : Malaria continues to be a major public health concern in Africa. Approximately 3.2 billion people worldwide are still at risk of contracting malaria, and 80% of deaths caused by malaria are concentrated in only 15 countries, most of which are in Africa. These high-burden countries have achieved a lower than average reduction of malaria incidence and mortality, and Mozambique is among these countries. Malaria eradication is therefore one of Mozambique’s main priorities. Few studies on malaria have been carried out in Chimoio, and there is no malaria map risk of the area. This map is important to identify areas at risk for application of Public Precision Health approaches. By using GIS-based spatial modelling techniques, the research goal of this article was to map and model malaria risk areas using climate, socio-demographic and clinical variables in Chimoio, Mozambique. Methods : A 30 m × 30 m Landsat image, ArcGIS 10.2 and BioclimData were used. A conceptual model for spatial problems was used to create the final risk map. The risks factors used were: the mean temperature, precipitation, altitude, slope, distance to water bodies, distance to roads, NDVI, land use and land cover, malaria prevalence and population density. Layers were created in a raster dataset. For class value comparisons between layers, numeric values were assigned to classes within each map layer, giving them the same importance. The input dataset were ranked, with different weights according to their suitability. The reclassified outputs of the data were combined. Results : Chimoio presented 96% moderate risk and 4% high-risk areas. The map showed that the central and south-west “Residential areas”, namely, Centro Hipico, Trangapsso, Bairro 5 and 1° de Maio, had a high risk of malaria, while the rest of the residential areas had a moderate risk. Conclusions : The entire Chimoio population is at risk of contracting malaria, and the precise estimation of malaria risk, therefore, has important precision public health implications and for the planning of effective control measures, such as the proper time and place to spray to combat vectors, distribution of bed nets and other control measures.

Suggested Citation

  • Joao L. Ferrao & Sergio Niquisse & Jorge M. Mendes & Marco Painho, 2018. "Mapping and Modelling Malaria Risk Areas Using Climate, Socio-Demographic and Clinical Variables in Chimoio, Mozambique," IJERPH, MDPI, vol. 15(4), pages 1-15, April.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:4:p:795-:d:141951
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    References listed on IDEAS

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    1. United Nations UN, 2015. "Transforming our World: the 2030 Agenda for Sustainable Development," Working Papers id:7559, eSocialSciences.
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    1. Francesco Di Gennaro & Claudia Marotta & Damiano Pizzol & Kajal Chhaganlal & Laura Monno & Giovanni Putoto & Annalisa Saracino & Alessandra Casuccio & Walter Mazzucco, 2018. "Prevalence and Predictors of Malaria in Human Immunodeficiency Virus Infected Patients in Beira, Mozambique," IJERPH, MDPI, vol. 15(9), pages 1-8, September.
    2. Alice McGushin & Yassen Tcholakov & Shakoor Hajat, 2018. "Climate Change and Human Health: Health Impacts of Warming of 1.5 °C and 2 °C," IJERPH, MDPI, vol. 15(6), pages 1-4, May.
    3. João L. Ferrão & Dominique Earland & Anísio Novela & Roberto Mendes & Marcos F. Ballat & Alberto Tungaza & Kelly M. Searle, 2021. "Mapping Risk of Malaria as a Function of Anthropic and Environmental Conditions in Sussundenga Village, Mozambique," IJERPH, MDPI, vol. 18(5), pages 1-16, March.

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