Evidence map›Paper›PMID 38625113›Full record

ArticleGeoJournal2023

A local government area based Covid-19 vulnerability analysis in Nigeria.

Olalekan Taiwo, Oluwaseun Addie, Kehinde Seun-Addie

Abstract read
In one paragraph

Article in GeoJournal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Olalekan TaiwoDepartment of Geography, University of Ibadan, Ibadan, Nigeria.ORCID 0000-0001-9290-379X
Oluwaseun AddieDepartment of Geography, University of Ibadan, Ibadan, Nigeria.
Kehinde Seun-AddieNational Population Commission's Headquarters, Abuja, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vulnerability to COVID-19 has been widely studied from varying perspectives, but susceptibility at the grassroots has not been adequately considered. The vulnerability of the 774 local government areas (LGAs) in Nigeria to COVID-19 and its predictors were determined using road distances from the two major entry airports in the country to each of the LGAs, socio-economic indices, quality of hygiene, and the level of exposure to mass media. LGA population data were obtained from the National Population Commission of Nigeria, while socio-economic and socio-demographic data were extracted from the 2018 NDHS report. Distances were determined with the aid of an online distance calculator,

Indexed as

COVID-19 pandemicCOVID-19 vulnerabilityLocal government areas in Nigeria

Identifiers

PMID38625113
PMCPMC10018617

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.