ReviewGhana medical journal2022
An assessment of Nigeria's health systems response to COVID-19.
Review in Ghana medical journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Assessing the determinants of uptake and hesitancy in accessing COVID 19 vaccines in Nigeria: a scoping review.Frontiers in health services · 2025Pooled it
- "I didn't believe it was real": a qualitative exploration of COVID-19 vaccine hesitancy among key populations living with HIV/AIDS in Rivers State, Nigeria.BMC public health · 2026Article
- An account of health systems resilience to emergencies in Africa: a scoping review.Globalization and health · 2026Article
- Cost analysis of the management of end-stage renal disease patients in Abuja, Nigeria.Cost effectiveness and resource allocation : C/E · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: This study aims to understand and report on selected health system interventions considered nationally and sub-nationally of particular significance both in terms of COVID-19 responses and in strengthening the health system for the future. Design: A review of published and grey literature, including journals, news/ media and official documents, was conducted from 1st December 2019 to 31st December 2020. The reviewers read and extracted relevant data using FACTIVA in a uniform data extraction template. Responses that related to service delivery were captured. Setting: The assessment considered responses at the national and two state levels: Lagos and Enugu, representing the epicentre and a low COVID-19 burden centre. Inclusion criteria: Documents and news that mentioned COVID-19 response, particularly service delivery aspects, were included in this review. Results: The identified interventions were mostly technical support targeted at health workers: including training of about 17,000 health workers, supervising and engaging more health workers, upgrading laboratories and building new ones to improve screening and diagnosis, and motivation of health workforce with incentives. Furthermore, the influx of philanthropic contributions improved the data and information systems supply of medicines, medical products and non-pharmaceutical protective materials through local production. The presence of political will and the government's efforts in health system's response to COVID-19 facilitated these interventions. Conclusions: Interventions of state and non-state actors have strengthened the health systems to some extent. However, more needs to be done to sustain these gains and make the health system resilient to absorb unprecedented shocks. Funding: IDRC Canada Grant # 109479-001.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.