Evidence map›Paper›PMID 34007892›Full record

ArticleInternational journal of population data science2021

Mapping population vulnerability and community support during COVID-19: a case study from Wales.

Nina H Di Cara, Jiao Song, Valerio Maggio, Christopher Moreno-Stokoe, Alastair R Tanner, Benjamin Woolf, Oliver Sp Davis, Alisha Davies

Abstract read
In one paragraph

Article in International journal of population data science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

8 authors.

Nina H Di CaraMRC Integrative Epidemiology Unit, University of Bristol, UK.
Jiao SongResearch and Evaluation Division, Public Health Wales, UK.
Valerio MaggioMRC Integrative Epidemiology Unit, University of Bristol, UK.
Christopher Moreno-StokoeMRC Integrative Epidemiology Unit, University of Bristol, UK.
Alastair R TannerMRC Integrative Epidemiology Unit, University of Bristol, UK.
Benjamin WoolfMRC Integrative Epidemiology Unit, University of Bristol, UK.
Oliver Sp DavisMRC Integrative Epidemiology Unit, University of Bristol, UK.
Alisha DaviesResearch and Evaluation Division, Public Health Wales, UK.

Funding

Medical Research Council MC_PC_20029Medical Research Council MC_PC_20058
6 · The paper itself

Abstract

backgroundDisasters such as the COVID-19 pandemic pose an overwhelming demand on resources that cannot always be met by official organisations. Limited resources and human response to crises can lead members of local communities to turn to one another to fulfil immediate needs. This spontaneous citizen-led response can be crucial to a community's ability to cope in a crisis. It is thus essential to understand the scope of such initiatives so that support can be provided where it is most needed. Nevertheless, quickly developing situations and varying definitions can make the community response challenging to measure.

aimTo create an accessible interactive map of the citizen-led community response to need during the COVID-19 pandemic in Wales, UK that combines information gathered from multiple data providers to reflect different interpretations of need and support. APPROACH: We gathered data from a combination of official data providers and community-generated sources to create 14 variables representative of need and support. These variables are derived by a reproducible data pipeline that enables flexible integration of new data. The interactive tool is available online (www.covidresponsemap.wales) and can map available data at two geographic resolutions. Users choose their variables of interest, and interpretation of the map is aided by a linked bee-swarm plot. DISCUSSION: The novel approach we developed enables people at all levels of community response to explore and analyse the distribution of need and support across Wales. While there can be limitations to the accuracy of community-generated data, we demonstrate that they can be effectively used alongside traditional data sources to maximise the understanding of community action. This adds to our overall aim to measure community response and resilience, as well as to make complex population health data accessible to a range of audiences. Future developments include the integration of other factors such as well-being.

Indexed as

community resiliencecoronavirusdata visualisationgeospatialpublic health

Identifiers

PMID34007892
PMCPMC8104153

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.