Experience of the COVID-19 Pandemic in Rural Nigeria: A Scoping Review of the Literature Contextualized With Local Knowledge Using Fuzzy Cognitive Mapping
Bibliographic record
Abstract
AimCollate and summarise published evidence of the non-clinical effects of the COVID-19 pandemic in rural Nigeria and compare the findings with community stakeholder experiences.MethodsWe searched PubMed, Scopus, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) for peer-reviewed papers published up to January 2024. Included studies used quantitative, qualitative, or mixed methods to examine the influence of the COVID-19 pandemic on the lives of rural Nigerians. Two reviewers conducted title, abstract, and full-text screening independently. We used narrative descriptions and fuzzy cognitive maps to summarise the findings of the review and compared the maps with those previously created by stakeholders in rural communities in Bauchi State, rural Nigeria.ResultsPoverty, hunger and lack of food, and stress and mental health problems were leading themes in both the literature and stakeholder maps. Stakeholder maps highlighted job loss and household conflicts. These topics were rarely explored in the literature, which emphasized reduced health services.ConclusionThis review and stakeholder perspectives confirm the importance of non-clinical impacts of the COVID-19 pandemic in rural Nigeria. Some issues highlighted by local community stakeholders were absent in the literature. Contextualizing published research with local experience provides specific insights to inform recovery policies.
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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 | 0.019 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.000 | 0.005 |
| 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".