Evidence map›Paper›PMID 36462204›Full record

ArticleJournal of global health2022

Community vulnerability to the COVID-19 pandemic: A narrative synthesis from an ecological perspective.

Qiuyan Liao, Meihong Dong, Jiehu Yuan, Wendy Wing Tak Lam, Richard Fielding

Abstract read
In one paragraph

Article in Journal of global health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Qiuyan Liao
Meihong Dong
Jiehu Yuan
Wendy Wing Tak Lam
Richard Fielding

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: We aimed to conduct a narrative synthesis of components and indicators of community vulnerability to a pandemic and discuss their interrelationships from an ecological perspective. Methods: We searched from PubMed, Embase, Web of Science, PsycINFO, and Scopus (updated to November 2021) for studies focusing on community vulnerability to a pandemic caused by novel respiratory viruses on a geographic unit basis . Studies that reported the associations of community vulnerability levels with at least one disease morbidity or mortality outcome were included. Results: Forty-one studies were included. All were about the COVID-19 pandemic. Suitable temperature and humidity environments, advanced social and human development (including high population density and human mobility, connectivity, and occupations), and settings that intensified physical interactions are important indicators of vulnerability to viral exposure. However, the eventual pandemic health impacts are predominant in communities that faced environmental pollution, higher proportions of socioeconomically deprived people, health deprivation, higher proportions of poor-condition households, limited access to preventive health care and urban infrastructure, uneven social and human development, and racism. More stringent social distancing policies were associated with lower COVID-19 morbidity and mortality only in the early pandemic phases. Prolonged social distancing policies can disproportionately burden the socially disadvantaged and racially/ethnically marginalized groups. Conclusions: Community vulnerability to a pandemic is foremost the vulnerability of the ecological systems shaped by complex interactions between the human and environmental systems. Registration: PROSPERO (CRD42021266186).

Indexed as

COVID-19RacismHumansPandemicsPhysical DistancingPolicy

Identifiers

PMID36462204
PMCPMC9719409

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.