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Geospatial mapping of malaria risk in flood-prone zones of Sub-Saharan Africa

  • Jeremy Eudaric
  • , Marleen C. de Ruiter
  • , Nivedita Sairam
  • , Andrés Camero
  • , Kasra Rafiezadeh Shahi
  • , Mark W. Smith
  • , Xiao Xiang Zhu
  • , Heidi Kreibich
  • Technical University of Munich
  • Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR)
  • Vrije Universiteit Amsterdam Instituut voor Milieuvraagstukken
  • German Research Centre for Geosciences
  • Potsdam Institute for Climate Impact Research (PIK)–Member of the Leibniz Association
  • University of Leeds
  • Munich Center for Machine Learning

Research output: Contribution to journalArticlepeer-review

Abstract

The World Health Organisation (WHO) aims to eliminate malaria by 2030; yet, the disease remains endemic in Sub-Saharan Africa. Stagnant floodwaters provide ideal breeding grounds for mosquitoes. Previous estimates of potential malaria risk in flood zones have been limited due to insufficient large-scale geospatial data. Here, we integrate high-resolution flood maps (2000–2018) from the Global Flood Database, malaria incidence data from the Malaria Atlas Project, and geospatial population data across 492 flood-prone zones in 38 countries. We used a geospatial statistical models to assess malaria relative risk and drivers. We found that in East and West Africa, malaria relative risk is elevated in flood-prone regions compared to national baselines. We estimate that 12 million individuals diagnosed with Plasmodium falciparum (Pf)were exposed to flooding events, representing one-third of the population affected by floods. Our analyses find that flood exposure is one of the main drivers of the malaria burden in flood zones. These findings identify critical malaria hotspots and key drivers in flood-prone zones, and can help inform WHO’s malaria eradication strategies by guiding policymakers on the geographic distribution of vulnerable areas.

Original languageEnglish
Article number18002
JournalScientific Reports
Volume16
Issue number1
DOIs
StatePublished - Dec 2026

Keywords

  • Flooding
  • Geospatial
  • Malaria
  • Sub-Saharan Africa

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