Community-based maternal and perinatal death surveillance and response: a comparative case study of implementation realities from humanitarian contexts
Bibliographic record
Abstract
BACKGROUND: Implementation of community-based Maternal and Perinatal Death Surveillance and Response (CB-MPDSR) in crisis-affected settings offers an opportunity to adapt humanitarian programming and mount solutions to directly improve maternal and neonatal health among those most in need. This study aimed to understand factors that influence implementation of CB-MPDSR approaches across diverse humanitarian contexts. METHODS: A comparative qualitative case study was conducted in December 2021-July 2022 to assess CB-MPDSR implementation in 4 diverse humanitarian settings: Cox's Bazar (CXB) refugee camps, Ugandan refugee settlements, South Sudan, and Yemen. A scoping review and 39 individual or group semi-structured key informant interviews were conducted. Thematic content analysis was employed to understand the adoption, penetration, and fidelity of CB-MPDSR approaches and elucidate cross-setting learning. FINDINGS: Adoption of CB-MPDSR varied: refugee contexts in CXB and Uganda had well-established systems involving active pregnancy and mortality surveillance and verbal autopsy. In Yemen, implementation was reliant upon passive reporting mechanisms, while implementing partners in South Sudan employed a mix of strategies. Financial, human resources, and socio-cultural dynamics significantly limited implementation, especially the notification and review of perinatal deaths. Strategic engagement of community stakeholders was employed to improve participation and transparency between communities and health systems; however, community trust in the humanitarian health system remains an unresolved issue. CONCLUSIONS: CB-MPDSR offers insights into important systemic and cultural factors contributing to mortality within crisis-affected settings. Our results call for more research investment in understanding how to effectively adapt CB-MPDSR and development of operational guidance to assist humanitarian actors in introducing or bolstering CB-MPDSR approaches, so as to support a system reflective of complex realities faced by these diverse and mobile communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".