Mapping the COVID-19 pandemic in Burkina Faso: spatial patterns, socioeconomic factors, and public health implications

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Authors: Abdoul Azize Millogo, Aboubacar Karabinta, Emmanuel Kiendrebeogo, Bry Sylla, Abdoulaye Diabaté, Lassane Yaméogo
Cited by: 0
References: 37

Abstract

The first case of COVID-19 in Burkina Faso was reported in March 2020. As of June 8, 2025, Burkina Faso reported 22,114 confirmed cases and 400 deaths. However, few studies have investigated the spatiotemporal dynamics of pandemics within the national boundaries. This study provides a retrospective spatial analysis of COVID-19 transmission in Burkina Faso and identifies the key geographic drivers. Case statistics from March 2020 to December 2021 were sourced from the Directorate of Health Information Systems of the Ministry of Health. Covariates were identified through a literature review and retrieved from local and online resources. Spatial and temporal patterns were analyzed using ArcGIS Pro® 3.4.3. Hotspots and directional trends were mapped using Getis-Ord Gi* statistics and standard deviation ellipses, and district-level spatial associations were evaluated. Multiscale Geographically Weighted Regression (MGWR) was used to model the relationships between disease incidence and geographic features. Five major transmission phases were observed. Specifically, 20 Health Districts were affected between March and April 2020, 38 in September 2020, 62 in April 2021, and 67 in December 2021. Initially, a single hotspot centered in Ouagadougou was identified. A second hotspot emerged in Bobo Dioulasso in September 2020, considerable heterogeneity in case distribution was noted across the districts. The MGWR results highlight population density, poverty rate, relative wealth index, and distance to testing centers as the main spatial drivers, collectively explaining 70% of the variance in incidence. The findings revealed a fast-evolving outbreak with significant spatial variation, revealed the need for adaptive, geography-informed responses. This multiphase framework can inform real-time risk forecasting and improve epidemic preparednessin in low-resource settings.

Fields of Study & Subjects

COVID-19 epidemiological studies Data-Driven Disease Surveillance Viral Infections and Outbreaks Research

Publication details

Journal / source
International Journal of Health Geographics
Volume
25
Issue
1
Pages
11–11
Publication date
3 January 2026
Language
EN