Original Research

Hydropower development and malaria transmission: A geospatial econometric study

Callum J. Thomas
Journal of Public Health in Africa | Vol 16, No 1 | a1397 | DOI: https://doi.org/10.4102/jphia.v16i1.1397 | © 2025 Callum J. Thomas | This work is licensed under CC Attribution 4.0
Submitted: 30 March 2025 | Published: 06 October 2025

About the author(s)

Callum J. Thomas, Department of International Relations, Peking University, Beijing, China; and Department of Finance for Sustainable Development, Organisation for Economic Cooperation and Development, Paris, France

Abstract

Background: In Western Africa, the causal relationship between hydropower project implementation and malaria transmission, remains understudied.
Aim: This study assesses whether a causal correlation exists between hydropower development and malaria transmission outcomes across locally affected communities, using malaria incidence and prevalence as key indicators. Malaria incidence is measured as the number of clinical Plasmodium falciparum cases per person, while prevalence is the parasite rate of P. falciparum in children aged 2–10 years. The analysis focuses on P. falciparum given its severity across West Africa, along with the availability of consistent geospatial data.
Setting: The study was conducted in Ghana, Côte d’Ivoire, and Gabon.
Methods: Utilising multivariate Difference-in-Differences (DiD) regression models and geospatial analysis across pre- and post-dam periods, this study evaluates malaria outcomes within 15 km of hydropower sites.
Results: The DiD estimator (Treatment_Post variable) suggests no statistically significant increase in malaria transmission following hydropower project implementation. Estimated effects are insignificant in Côte d’Ivoire (incidence: p = 0.210, prevalence: p = 0.200), Gabon (incidence: p = 0.990, prevalence: p = 0.990), and Ghana (incidence: p = 0.089, prevalence: p = 0.102), indicating no strong causal link at the 5% level. By contrast, environmental and socio-economic variables such as urbanisation, elevation, and climate factors consistently showed strong associations with malaria transmission (p < 0.01).
Conclusion: Hydropower presence alone is not a primary driver of malaria dynamics.
Contribution: This study provides the first large-scale geospatial analysis of malaria trends across hydropower projects in Western Africa, challenging traditional assumptions of a direct causal link and highlighting the need for interventions shaped by environmental and socio-economic factors.


Keywords

difference-in-differences; regression modelling; geographic information systems; GIS; malaria incidence; malaria prevalence; hydrodams

Sustainable Development Goal

Goal 3: Good health and well-being

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