Risk factors associated with successive waves of COVID-19 in North Kivu province, Democratic Republic of the Congo, March 2020–September 2023

Abstract

The North Kivu province, located in the eastern Democratic Republic of the Congo (DRC), had the second highest disease incidence of COVID-19 during the successive waves observed between March 2020 and September 2023. However, a comprehensive understanding of the geographical trends and underlying mechanisms influencing the epidemiology of COVD-19 at a fine administrative scale is required to guide public health strategies. This first sub-provincial risk-factor modeling framework integrating conflict, forced migrations, epidemiological, demographic, socio-economic, and health-system variables was implemented at the health zone level. Hierarchical Clustering on Principal Components (HCPC) analysis was employed on the independent variables to cluster the health zones. Furthermore, multivariable negative binomial regression models were performed to identify significant predictors of high numbers of cases of COVID-19 recorded across the health zones. Of the five waves observed, the number of COVID-19 cases increased substantially during the third and fourth waves, with outbreak peaks exceeding 200 and 900 cases per week, respectively. HCPC resulted in five major clusters for the 34 health zones, and the number of cases varied significantly across clusters. In the final multivariable model, the number of COVID-19 cases was found to be significantly higher in heath zones with a history of Ebola virus disease outbreak (Risk Ratio [RR] = 2.69; 95% Confidence Interval [95% CI]: 1.14–6.34), active conflict (RR = 3.14; 95% CI: 1.08–9.19), an airport connectivity (RR = 6.05; 95% CI: 1.78–20.49), and high number of physicians per 100,000 inhabitants (RR = 4.41; 95% CI: 1.60-12.11). Our findings highlight the cross-disease vulnerability of the health zones that have been particularly hard-hit by COVID-19. They also advocate for allocating resources to capacity building and health education, particularly during periods of low disease activity, within surveillance systems at points of entry and within local communities.