Evaluating the risk of conflict on recent Ebola outbreaks in Guinea and the Democratic Republic of the Congo

Gina E C Charnley; Nathan Green; Ilan Kelman; Espoir B Malembaka; Katy A M Gaythorpe

doi:10.1186/s12889-024-18300-8

Evaluating the risk of conflict on recent Ebola outbreaks in Guinea and the Democratic Republic of the Congo

BMC Public Health. 2024 Mar 20;24(1):860. doi: 10.1186/s12889-024-18300-8.

Authors

Gina E C Charnley^{1

2

3}, Nathan Green⁴, Ilan Kelman^{5

6

7}, Espoir B Malembaka^{8

9}, Katy A M Gaythorpe^{10

11}

Affiliations

¹ Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA. gcharnl1@jh.edu.
² School of Public Health, Imperial College London, London, UK. gcharnl1@jh.edu.
³ Institute for Global Health, University College London, London, UK. gcharnl1@jh.edu.
⁴ Department of Statistical Science, University College London, London, UK.
⁵ Institute for Global Health, University College London, London, UK.
⁶ Institute for Risk and Disaster Reduction, University College London, London, UK.
⁷ University of Agder, Kristiansand, Norway.
⁸ Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA.
⁹ Centre for Tropical Diseases and Global Health (CTDGH), Université Catholique de Bukavu, Bukavu, Democratic Republic of the Congo.
¹⁰ School of Public Health, Imperial College London, London, UK.
¹¹ MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.

Abstract

Background: Reducing Ebola virus transmission relies on the ability to identify cases and limit contact with infected bodily fluids through biosecurity, safe sex practices, safe burial and vaccination. Armed conflicts can complicate outbreak detection and interventions due to widespread disruption to governments and populations. Guinea and the Democratic Republic of the Congo (DRC) have historically reported the largest and the most recent Ebola virus outbreaks. Understanding if conflict played a role in these outbreaks may help in identifying key risks factors to improve disease control.

Methods: We used data from a range of publicly available data sources for both Ebola virus cases and conflict events from 2018 to 2021 in Guinea and the DRC. We fitted these data to conditional logistic regression models using the Self-Controlled Case Series methodology to evaluate the magnitude in which conflict increased the risk of reported Ebola virus cases in terms of incidence rate ratio. We re-ran the analysis sub-nationally, by conflict sub-event type and tested any lagged effects.

Results: Conflict was significantly associated with an increased risk of reported Ebola virus cases in both the DRC and Guinea in recent outbreaks. The effect was of a similar magnitude at 1.88- and 1.98-times increased risk for the DRC and Guinea, respectively. The greatest effects (often higher than the national values) were found in many conflict prone areas and during protest/riot-related conflict events. Conflict was influential in terms of Ebola virus risk from 1 week following the event and remained important by 10 weeks.

Conclusion: Extra vigilance is needed following protests and riot-related conflict events in terms of Ebola virus transmission. These events are highly disruptive, in terms of access to transportation and healthcare and are often in urban areas with high population densities. Additional public health messaging around these types of conflict events, relating to the risks and clinical symptoms may be helpful in reducing transmission. Future work should aim to further understand and quantify conflict severity and intensity, to evaluate dose-response relationships in terms of disease risk.

Keywords: Conflict; Democratic Republic of the Congo; Ebola virus; Guinea; Outbreaks.

MeSH terms

Democratic Republic of the Congo / epidemiology
Disease Outbreaks / prevention & control
Ebolavirus*
Guinea / epidemiology
Hemorrhagic Fever, Ebola* / epidemiology
Hemorrhagic Fever, Ebola* / prevention & control
Humans