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Background <p>This work investigated the future (2021–2050) impact of Climate Change on Malaria Prevalence in the Upper River Region of The Gambia under two representative concentration pathways, RCP4.5 and RCP8.5, comparing it with the observed evaluation period of 2011–2022.</p> Methods <p>The observed climatic variable data used was obtained from the Department of Water Resources and the corresponding malaria cases from the archive of the primary Health database, Banjul, The Gambia. Projected monthly temperature, precipitation, and relative humidity were downloaded from the coordinated Regional downscaling experiment (CORDEX) stimulation of the&#xa0;Rossby Centre Regional Atmospheric regional climate (RCA4). The dataset spans the decades from 2021 to 2050, providing insight into future climatic and epidemiological trends. Gradient Boost Machine Learning algorithm was utilized for the malaria projection both in the population below 5 and above five years.</p> Results <p>The result revealed an increase in malaria incidence under RCP4.5 and RCP8.5 climatic scenarios for both age categories with a clear indication in the population above five years.</p> Discussion and conclusion <p>The result pictures how climate change will impact malaria under RCP4.5 and RCP8.5 emission scenarios in the region and also clearly reveals that the upper river region of the Gambia population is at risk of malaria infection, thus, a strategic and robust intervention scheme is highly solicited.</p>

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Projection of future malaria prevalence in the upper river region of The Gambia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月3日

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  • Ugochinyere Agatha Okafor,
  • Pierre-Claver Konin Kakou,
  • Umberto D’Alessandro,
  • Vincent Nduka Ojeh,
  • Sidat Yaffa

摘要

Background

This work investigated the future (2021–2050) impact of Climate Change on Malaria Prevalence in the Upper River Region of The Gambia under two representative concentration pathways, RCP4.5 and RCP8.5, comparing it with the observed evaluation period of 2011–2022.

Methods

The observed climatic variable data used was obtained from the Department of Water Resources and the corresponding malaria cases from the archive of the primary Health database, Banjul, The Gambia. Projected monthly temperature, precipitation, and relative humidity were downloaded from the coordinated Regional downscaling experiment (CORDEX) stimulation of the Rossby Centre Regional Atmospheric regional climate (RCA4). The dataset spans the decades from 2021 to 2050, providing insight into future climatic and epidemiological trends. Gradient Boost Machine Learning algorithm was utilized for the malaria projection both in the population below 5 and above five years.

Results

The result revealed an increase in malaria incidence under RCP4.5 and RCP8.5 climatic scenarios for both age categories with a clear indication in the population above five years.

Discussion and conclusion

The result pictures how climate change will impact malaria under RCP4.5 and RCP8.5 emission scenarios in the region and also clearly reveals that the upper river region of the Gambia population is at risk of malaria infection, thus, a strategic and robust intervention scheme is highly solicited.