Impact de la pandémie de la COVID-19 sur l´utilisation des services de santé dans la ville de Niamey: une analyse dans 17 formations sanitaires de janvier à juin 2020
Bibliographic record
Abstract
COVID-19 pandemic has posed huge challenges for the health system in Africa; however they haven´t been well quantified. The purpose of this study was to assess the impact of COVID-19 pandemic on curative and preventive activities in health care facilities at 17 integrated health centers in Niamey by comparing the first half of 2020 and the first half of 2019. The differences were more pronounced in the second quarter of 2020, with a 34% reduction (95% CI: -47% to -21%) for curative care, 61% (95% CI: -74% to -48%) for pentavalent vaccines 1 and 3 and 36% (95% CI: -49% to -23%) for VAR 1. A nearly zero gain of 1% (95% IC: -2% to 4%) was reported for prenatal care attendance, thus reversing the gains of the first quarter. The COVID-19 pandemic has had negative effects on service deliveries to the most vulnerable groups, such as women and children. New strategies, such as community engagement, are essential.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".