Prioritization of maternal and newborn health policies and their implementation in the eastern conflict affected areas of the Democratic Republic of Congo: a political economy analysis.

BACKGROUND: Maternal and neonatal mortality remains a major concern in the Democratic Republic of Congo (DRC), and the country's protracted crisis context exacerbates the problem. This political economy analysis examines the maternal and newborn health (MNH) prioritization in the DRC, focussing specifically on the conflict-affected regions of North and South Kivu. The aim is to understand the factors that facilitate or hinder the prioritization of MNH policy development and implementation by the Congolese government and other key actors at national level and in the provinces of North and South Kivu. METHODS: Using a health policy triangle framework, data collection consisted of in-depth interviews with key actors at different levels of the health system, combined with a desk review. Qualitative data were analysed using inductive and then deductive approaches, exploring the content, process, actor dynamics, contextual factors and gender-related factors influencing MNH policy development and implementation. RESULTS: The study highlighted the challenges of prioritizing policies in the face of competing health and security emergencies, limited resources and governance issues. The universal health coverage policy seems to offer hope for improving access to MNH services. Results also revealed the importance of international partnerships and global financial mechanisms in the development of MNH strategies. They reveal huge gender disparities in the MNH sector at all levels, and the need to consider cultural factors that can positively or negatively impact the success of MNH policies in crisis zones. CONCLUSIONS: MNH is a high priority in DRC, yet implementation faces hurdles due to financial constraints, political influences, conflicts and gender disparities. Addressing these challenges requires tailored community-based strategies, political engagement, support for health personnel and empowerment of women in crisis areas for better MNH outcomes.

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.