How can health systems better prepare for the next pandemic? A qualitative study of lessons learned from the COVID-19 response in Nigeria
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
Fragile health systems can become overwhelmed during public health crises, further exacerbating the human, economic, and political toll. It is then necessary as a country, to assess, understand, document, and report the activities/measures that are considered nationally and sub-nationally significant, both in terms of COVID-19 responses and strengthening of the health system for the future. Data collection was through a scoping review of 198 publications that were comprised of official documents, journal articles, and media reports that were published from December 2019 to December 2020. Journal articles were sourced from online journals in PubMed, Google Scholar, and Scopus using search terms/queries. Published official documents were retrieved from relevant websites of government agencies and development partners and media searches were performed in FACTIVA. In addition, qualitative data using in-depth interviews of key informants were collected from 38 respondents in April 2022. The transcripts from the IDIs were coded, and thematic analysis and narrative synthesis of data were done using NVivo version 12 using Palagyi et al.’s framework. Our findings revealed the need to institutionalize some COVID-19 response activities and to efficiently prioritize financial and material resources during a pandemic response. Also, to introduce flexibility in financial response activities. Pooling and funds management was found useful but the integration of response activities into already existing epidemic response pillars must be prioritized. Research should be incorporated early in pandemic responses. The need to use evidence in decision-making and include all levels of government in planning response actions was found necessary to enhance trust and compliance. This study demonstrates the value of applying the Palagyi et al. framework on systems preparedness towards emerging infectious diseases to understand how the health systems can be better prepared for the next pandemic. It highlighted specific strengths and areas of potential growth for pandemic response in Nigeria.
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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 | 0.029 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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