Assessment of Maternal and Child Health Care Services Performance in The Context of COVID-19 Pandemic in Addis Ababa, Ethiopia: Evidence From Routine Service Data
Bibliographic record
Abstract
Abstract Background In many settings, health care service provision has been modified to managing COVID-19 cases, and this has been affecting the provision of maternal and child health services. The aim of this study was to assess trends in selected maternal and child health services performance in the context of COVID-19 pandemic. Methods A cross-sectional data review was conducted in Addis Ababa, Ethiopia from April to May 2021. Routine health management information system database was reviewed from Addis Ababa Health Bureau for the period from July 2019 to March 2021 across all quarters. Proportions and mean with standard deviations were computed. T-test was used to assess statistically significant differences in services mean performance. Results PNC visit, new contraceptives accepters, safe abortion care and number of under-five years old children treated for pneumonia significantly decreased by 9.3% (p-value 0.04), 20.3% (p-value 0.004), 23.7% (p-value 0.01) and 77.2% (P-value < 0.001), respectively during the first eight months of the COVID-19 pandemic compared to the previous eight months’ average performance. The trends in ANC first visit, new contraceptive accepters, pentavalent-3 vaccination and under-five children treated for pneumonia began to decline between January-March 2020 when the COVID-19 pandemic began; with accelerated declines between April-June 2020 following national lockdown. The trends for the stated services began to increase during July-September 2020, during the last quarter of national lockdown. Contraceptive accepters and pentavalent-1 vaccination continued to decline and showed no recovery until January-March 2021when this study was completed. Conclusions Most of the maternal and child health services performance declined following the onset of COVID-19 pandemic and national lockdown, and most of the services began recovering during July-September 2020, the last quarter of national lockdown. However, new and repeat contraceptive accepters and pentavalent-1 recipients continue to decline and show no recovery during end of the study period. Implementing COVID-19 prevention measures and assuring the community about the safety of service delivery is imperative to ensure continuity of the maternal and child health services. Regular monitoring and evaluation of services performance is required to identify slowly recovering services and respond to potentially volatile changes during the COVID-19 pandemic.
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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 | 0.003 | 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 | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| 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".