Adaptive Mechanisms of Health Zones to Chronic Traumatic Events in Eastern DRC: A Multiple Case Study.

BACKGROUND: The Eastern part of the Democratic Republic of Congo (DRC) has been affected by armed conflict for several years. Despite the growing interest in the impact of these conflicts on health service utilisation, few studies have addressed the coping mechanisms of the health system. The purpose of this study is to describe the traumatic events and coping mechanisms used by the health zones (HZs) in conflict settings to maintain good performance. METHODS: This multiple case study took place from July to October 2022 in four HZs in the South Kivu Province of DRC. HZs were classified into "cases" according to their conflict profile: accessible and stable (Case 1), accessible but remote (Case 2), unstable (Case 3), and intermediate (Case 4). Eight performance indicators and the amount of funding provided to the HZs by non-governmental organizations (NGOs) were recorded. A graph was created to compare their evolution from 2013 to 2018. A thematic analysis of qualitative data from individual interviews with selected health workers was conducted. RESULTS: Both battle-related events (war and its effects) and non-battle-related events (epidemics, disasters, strikes) were recorded according to the case conflict-profile. Although the cases (3 and 4) most affected by armed conflicts occasionally performed better than the stable ones (1 and 2), their operational action plan was poorly carried out. The coping mechanisms developed in cases 3 and 4 were the deployment of military nurses in preventive and supervisory activities, the solicitations of subsidies from NGOs, the relocation of health care facilities and the implementation of negotiation strategies with the belligerents. CONCLUSION: Armed conflict results in traumatic events that disrupt the execution of the operational action plan of HZs. The HZs' management team expertise, its strong leadership, and substantial financial support would enable this system to develop reliable and sustainable adaptive mechanisms.

The use of health facility data to assess the effects of armed conflicts on maternal and child health: experience from the Kivu, DR Congo.

BACKGROUND: In conflict-affected settings, data on reproductive, maternal, newborn and child health (RMNCH) are often lacking for priority setting and timely decision-making. We aimed to describe the levels and trends in RMNCH indicators within Kivu provinces between 2015 and 2018, by linking conflict data with health facility (HF) data from the District Health Information System 2 (DHIS2). METHODS: We used data from the DHIS2 for the period 2015-2018, the 2014 Demographic and Health Survey, the 2018 Multiple Indicators Cluster Survey and the Uppsala Conflict Data Program. Health zones were categorised in low, moderate and high conflict intensity level, based on an annual conflict death rate. We additionally defined a monthly conflict death rate and a conflict event-days rate as measures of conflict intensity and insecurity. Outcomes were completion of four antenatal care visits, health facility deliveries, caesarean sections and pentavalent vaccine coverage. We assessed data quality and analyzed coverage and trends in RMNCH indicators graphically, by conflict categories and using HF data aggregated annually. We used a series of fixed-effect regression models to examine the potential dose-response effect of varying conflict intensity and insecurity on RMNCH. RESULTS: The overall HF reporting was good, ranging between 83.3 and 93.2% and tending to be lower in health zones with high conflict intensity in 2016 and 2017 before converging in 2018. Despite the increasing number of conflict-affected health zones over time, more in North-Kivu than in South-Kivu, we could not identify any clear pattern of variation in RMNCH coverage both by conflict intensity and insecurity. North-Kivu province had consistently reported better RMNCH indicators than South-Kivu, despite being more affected by conflict. The Kivu as a whole recorded higher coverage than the national level. Coverage of RMNCH services calculated from HF data was consistent with population-based surveys, despite year-to-year fluctuation among health zones and across conflict-intensity categories. CONCLUSIONS: Although good in general, the HF reporting rate in the Kivu was negatively impacted by conflict intensity especially at the beginning of the DHIS2's rolling-up. Routine HF data appeared useful for assessing and monitoring trends in RMNCH service coverage, including in areas with high-intensity conflict.