Mapping Population Vulnerability and Community Support during COVID-19: a case study from Wales

Nina Di Cara*, Jiao Song, Valerio Maggio, Chris Moreno-Stokoe, Alastair Tanner, Benjamin Woolf, Oliver S.P. Davis, Alisha Davies

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

4 Citations (Scopus)
302 Downloads (Pure)


Background: Disasters 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.

Aim: To 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 ( 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 including the integration of other factors such as well-being.
Original languageEnglish
Article number1409
Number of pages15
JournalInternational Journal of Population Data Science
Issue number4
Publication statusPublished - 19 Apr 2021

Bibliographical note

Funding Information:
This work was supported in part by the UK Medical Research Council Integrative Epidemiology Unit at the University of Bristol (Grant ref: MC UU 12013/1). NHD is supported by an MRC PhD studentship (Grant ref: MR/N013794/1), CMS is supported by an ESRC PhD studentship (Grant ref: ES/P000630/1), as is BW. OSPD and CMAH are funded by the Alan Turing Institute under the EPSRC grant EP/N510129/1. This study was also supported by the National Institute for Health Research Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol (BRC-1215-2011).

Publisher Copyright:
© The Authors. Open Access under CC BY 4.0 (

Structured keywords

  • Covid19


  • covid-19
  • coronavirus
  • community
  • resilience
  • community support
  • public health
  • data visualisation
  • gis
  • geospacial
  • vulnerability


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