Using data science to identify climate change and health adverse impacts and solutions in Africa: a scoping review

Caradee Y. Wright; Anelisa Jaca; Thandi Kapwata; Natasha Naidoo; Babatunde Awokola; Engineer Bainomugisha; Kiros Berhane; Suzana Blesic; Anderson Gwanyebit Kehbila; Rajen N. Naidoo; Bono Nemukula; Benjamin Kofi Nyarko; Akinkunmi Paul Okekunle; Tolu Oni; Reginald Qunasah; Sokhna Thiam; Ibrahim Sidi Zakari; Negussie Beyene; Emile R. Chimusa; Candice Webster

doi:10.1038/s44401-025-00057-w

Using data science to identify climate change and health adverse impacts and solutions in Africa: a scoping review

Caradee Y. Wright^*, Anelisa Jaca, Thandi Kapwata, Natasha Naidoo, Babatunde Awokola, Engineer Bainomugisha, Kiros Berhane, Suzana Blesic, Anderson Gwanyebit Kehbila, Rajen N. Naidoo, Bono Nemukula, Benjamin Kofi Nyarko, Akinkunmi Paul Okekunle, Tolu Oni, Reginald Qunasah, Sokhna Thiam, Ibrahim Sidi Zakari, Negussie Beyene, Emile R. Chimusa, Candice Webster

^*Corresponding author for this work

School of Geography and Natural Sciences

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Abstract

Africa is experiencing the impacts of climate change. While global epidemiological studies using traditional analytical methods to study the relations between climate change and health exist, studies using data science to tackle these topics are increasing. The aim of this study was to identify how data science is being used to understand climate change impacts on health in Africa. We carried out a scoping review to synthesize the evidence of data science applied to understand health outcomes associated with climate change in Africa. Among 100 included articles, several temporal and spatial analytical tools and models were applied to determine the relationships between climate change factors and health outcomes for morbidity and mortality. For example, early warning systems for malaria were the most studied adaptation intervention. Africa has a wealth of evidence for addressing the health impacts of climate change to inform solutions for Africa and other countries around the world.

Original language	English
Article number	16
Pages (from-to)	1-14
Number of pages	14
Journal	npj Health Systems
Volume	3
Early online date	16 Feb 2026
DOIs	https://doi.org/10.1038/s44401-025-00057-w
Publication status	Published - 16 Feb 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 13 Climate Action

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Wright, C. Y., Jaca, A., Kapwata, T., Naidoo, N., Awokola, B., Bainomugisha, E., Berhane, K., Blesic, S., Kehbila, A. G., Naidoo, R. N., Nemukula, B., Nyarko, B. K., Okekunle, A. P., Oni, T., Qunasah, R., Thiam, S., Zakari, I. S., Beyene, N., Chimusa, E. R., & Webster, C. (2026). Using data science to identify climate change and health adverse impacts and solutions in Africa: a scoping review. npj Health Systems, 3, 1-14. Article 16. https://doi.org/10.1038/s44401-025-00057-w

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title = "Using data science to identify climate change and health adverse impacts and solutions in Africa: a scoping review",

abstract = "Africa is experiencing the impacts of climate change. While global epidemiological studies using traditional analytical methods to study the relations between climate change and health exist, studies using data science to tackle these topics are increasing. The aim of this study was to identify how data science is being used to understand climate change impacts on health in Africa. We carried out a scoping review to synthesize the evidence of data science applied to understand health outcomes associated with climate change in Africa. Among 100 included articles, several temporal and spatial analytical tools and models were applied to determine the relationships between climate change factors and health outcomes for morbidity and mortality. For example, early warning systems for malaria were the most studied adaptation intervention. Africa has a wealth of evidence for addressing the health impacts of climate change to inform solutions for Africa and other countries around the world.",

author = "Wright, \{Caradee Y.\} and Anelisa Jaca and Thandi Kapwata and Natasha Naidoo and Babatunde Awokola and Engineer Bainomugisha and Kiros Berhane and Suzana Blesic and Kehbila, \{Anderson Gwanyebit\} and Naidoo, \{Rajen N.\} and Bono Nemukula and Nyarko, \{Benjamin Kofi\} and Okekunle, \{Akinkunmi Paul\} and Tolu Oni and Reginald Qunasah and Sokhna Thiam and Zakari, \{Ibrahim Sidi\} and Negussie Beyene and Chimusa, \{Emile R.\} and Candice Webster",

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doi = "10.1038/s44401-025-00057-w",

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Wright, CY, Jaca, A, Kapwata, T, Naidoo, N, Awokola, B, Bainomugisha, E, Berhane, K, Blesic, S, Kehbila, AG, Naidoo, RN, Nemukula, B, Nyarko, BK, Okekunle, AP, Oni, T, Qunasah, R, Thiam, S, Zakari, IS, Beyene, N, Chimusa, ER & Webster, C 2026, 'Using data science to identify climate change and health adverse impacts and solutions in Africa: a scoping review', npj Health Systems, vol. 3, 16, pp. 1-14. https://doi.org/10.1038/s44401-025-00057-w

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T1 - Using data science to identify climate change and health adverse impacts and solutions in Africa: a scoping review

AU - Wright, Caradee Y.

AU - Jaca, Anelisa

AU - Kapwata, Thandi

AU - Naidoo, Natasha

AU - Awokola, Babatunde

AU - Bainomugisha, Engineer

AU - Berhane, Kiros

AU - Blesic, Suzana

AU - Kehbila, Anderson Gwanyebit

AU - Naidoo, Rajen N.

AU - Nemukula, Bono

AU - Nyarko, Benjamin Kofi

AU - Okekunle, Akinkunmi Paul

AU - Oni, Tolu

AU - Qunasah, Reginald

AU - Thiam, Sokhna

AU - Zakari, Ibrahim Sidi

AU - Beyene, Negussie

AU - Chimusa, Emile R.

AU - Webster, Candice

PY - 2026/2/16

Y1 - 2026/2/16

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AB - Africa is experiencing the impacts of climate change. While global epidemiological studies using traditional analytical methods to study the relations between climate change and health exist, studies using data science to tackle these topics are increasing. The aim of this study was to identify how data science is being used to understand climate change impacts on health in Africa. We carried out a scoping review to synthesize the evidence of data science applied to understand health outcomes associated with climate change in Africa. Among 100 included articles, several temporal and spatial analytical tools and models were applied to determine the relationships between climate change factors and health outcomes for morbidity and mortality. For example, early warning systems for malaria were the most studied adaptation intervention. Africa has a wealth of evidence for addressing the health impacts of climate change to inform solutions for Africa and other countries around the world.

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ER -

Using data science to identify climate change and health adverse impacts and solutions in Africa: a scoping review

Abstract

UN SDGs

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