Home visits by community health workers for pregnant mothers and newborns: coverage plateau in Malawi
Bibliographic record
Abstract
BACKGROUND: Home visits by community health workers (CHWs) during pregnancy and soon after delivery are recommended to improve newborn survival. However, as the roles of CHWs expand, there are concerns regarding the capacity of community health systems to deliver high effective coverage of home visits. The WHO's Rapid Access Expansion (RAcE) program supported the Malawi Ministry of Health to align their Community-Based Maternal and Newborn Care (CBMNC) package with the latest WHO guidelines and to implement and evaluate the feasibility and coverage of home visits in Ntcheu district. METHODS: A population-based survey of 150 households in Ntcheu district was conducted in July-August 2016 after approximately 10 months of CBMNC implementation. Thirty clusters were selected proportional-to-size using the most recent census. In selected clusters, five households with mothers of children under six months of age were randomly selected for interview. The Health Surveillance Assistants (HSAs) providing community-based services to the same clusters were purposively selected for a structured interview and register review. RESULTS: = 0.00). Most HSAs had the necessary equipment and supplies and were active in CBMNC: 83.9% (95% CI = 70.2%-97.6%) of HSAs had pregnancy home visits and 77.4% (95% CI = 61.8%-93.0%) had postnatal home visits documented in their registers for the previous three months. CONCLUSIONS: We found low coverage of home visits during pregnancy and soon after delivery in a well-supported program delivery environment. Most HSAs were conducting home visits, but not at the level needed to reach high coverage. These findings were similar to previous studies, calling into question the feasibility of the current visitation schedule. It is time to re-align the CBMNC package with what the existing platform can deliver and identify strategies to better support HSAs to implement home visits to those who would benefit most.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".