Indirect effects of COVID-19 pandemic on reproductive, maternal, newborn and child health services in Pakistan
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
Background: COVID-19 is having many impacts on health, economy and social life; some due to the indirect effects of closure of health facilities to curb the spread. Closures were implemented in Pakistan from March 2020, affecting provision of reproductive, maternal, newborn and child health (RMNCH) services. Aims: To appraise the effects of containment and lockdown policies on RMNCH service utilization in order to develop an early response to avoid the catastrophic impact of COVID-19 on RMNCH in Pakistan. Methods: Routine monitoring data were analysed for indicators utilization of RMNCH care. The analysis was based on Period 1 (January-May 2020, first wave of COVID-19); Period 2 (June-September 2020, declining number of cases of COVID-19); and Period 3 (October-December 2020, second wave of COVID-19). We also compared data from May and December 2020 with corresponding months in 2019, to ascertain whether changes were due to COVID-19. Results: Reduced utilization was noted for all RMNCH indicators during Periods 1 and 3. There was a greater decline in service utilization during the first wave, and the highest reduction (~82%) was among children aged < 5 years, who were treated for pneumonia. The number of caesarean sections dropped by 57%, followed by institutional deliveries and first postnatal visit (37% each). Service utilization increased from June to September, but the second wave of COVID-19 led to another decrease. Conclusion: To reinstate routine services, priority actions and key areas include continued provision of family planning services along with uninterrupted immunization campaigns and routine maternal and child services.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it