The direct and indirect impact of COVID-19 pandemic on maternal and child health services in Africa: a scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: The novel coronavirus disease 2019 (COVID-19) continues to disrupt the availability and utilization of routine and emergency health care services, with differing impacts in jurisdictions across the world. In this scoping review, we set out to synthesize documentation of the direct and indirect effect of the pandemic, and national responses to it, on maternal, newborn and child health (MNCH) in Africa. METHODS: A scoping review was conducted to provide an overview of the most significant impacts identified up to March 15, 2022. We searched MEDLINE, Embase, HealthSTAR, Web of Science, PubMed, and Scopus electronic databases. We included peer reviewed literature that discussed maternal and child health in Africa during the COVID-19 pandemic, published from January 2020 to March 2022, and written in English. Papers that did not focus on the African region or an African country were excluded. A data-charting form was developed by the two reviewers to determine which themes to extract, and narrative descriptions were written about the extracted thematic areas. RESULTS: Four-hundred and seventy-eight articles were identified through our literature search and 27 were deemed appropriate for analysis. We identified three overarching themes: delayed or decreased care, disruption in service provision and utilization and mitigation strategies or recommendations. Our results show that minor consideration was given to preserving and promoting health service access and utilization for mothers and children, especially in historically underserved areas in Africa. CONCLUSIONS: Reviewed literature illuminates the need for continued prioritization of maternity services, immunization, and reproductive health services. This prioritization was not given the much-needed attention during the COVID-19 pandemic yet is necessary to shield the continent's most vulnerable population segments from the shocks of current and future global health emergencies.
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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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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 it