Maternal and child health service delivery in conflict-affected settings: a case study example from Upper Nile and Unity states, South Sudan
Bibliographic record
Abstract
BACKGROUND: Decades of war left the Republic of South Sudan with a fragile health system that has remained deprived of resources since the country's independence. We describe the coverage of interventions for women's and children's health in Upper Nile and Unity states, and explore factors that affected service provision during a protracted conflict. METHODS: We conducted a case study using a desk review of publicly available literature since 2013 and a secondary analysis of intervention coverage and conflict-related events from 2010 to 2017. During June through September 2018, we conducted 26 qualitative interviews with technical leads and 9 focus groups among health workers working in women and children's health in Juba, Malakal, and Bentiu. RESULTS: Coverage for antenatal care, institutional delivery, and childhood vaccines were low prior to the escalation of conflict in 2013, and the limited data indicate that coverage remained low through 2017. Key factors that determined the delivery of services for women and children in our study sites were government leadership, coordination of development and humanitarian efforts, and human resource capacity. Participants felt that national and local health officials had a limited role in the delivery of services, and financial tracking data showed that funding stagnated or declined for humanitarian health and development programming during 2013-2014. Although health services were concentrated in camp settings, the availability of healthcare providers was negatively impacted by the protracted nature of the conflict and insecurity in the region. CONCLUSIONS: Health care for women and children should be prioritized during acute and protracted periods of conflict by strengthening surveillance systems, coordinating short and long term activities among humanitarian and development organizations, and building the capacity of national and local government officials to ensure sustainability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".