The COVID-19 vulnerability index combines multiple sources of (mostly) open data to identify vulnerable areas and groups within Local Authorities and neighbourhoods (wards).
The Index currently maps clinical vulnerability (underlying health conditions), demographic vulnerability (over-70s, people seeking asylum), social vulnerability (barriers to housing and services, poor living environment, living in “left-behind” areas, loneliness, digital exclusion), and health inequalities.
Other vulnerabilities being added include:
- Mental health
- Economic vulnerability
- Social isolation
- Physical isolation from supermarkets, pharmacies
There's more information about our approach, current indicators and data sources, and forthcoming vulnerabilities in this open document.
Map of vulnerability in Local Authorities: https://britishredcrosssociety.github.io/covid-19-vulnerability/lad.html
Map of vulnerabilty in wards: https://britishredcrosssociety.github.io/covid-19-vulnerability
If you don't want to grapple with the code, we've already produced several outputs (descriptions of the variables are available here):
- the overall COVID-19 Vulnerability Index in .csv format for wards and Local Authorities
- the Vulnerability index in .geojson format for wards and Local Authorities
- the underlying indicators:
- clinical vulnerability for wards and Local Authorities
- our bespoke COVID-19 Index of Multiple Deprivation for lower-layer super output areas, wards and Local Authorities
- population over 70 for Local Authorities
- asylum seekers receiving Government support for Local authorities
- digital exclusion for Local authorities
- healthy life expectancy at age 65 for Local authorities
- risk of loneliness for Local authorities
You'll need to install R and ideally RStudio. Run the following to install all necessary packages:
install.packages(c("tidyverse", "readxl", "janitor", "xml2", "Hmisc", "sf", "httr", "classInt"))
Run the code in create vulnerability index.r
to create the overall index. Set reproduce_data = TRUE
on line 10 if you want to recreate the underlying indicators. See the individual prep *indicator*.r
files for the code to produce the underlying vulnerability indicators.
Designed and developed by Matt Thomas and Ellen Gordon at the British Red Cross.
With contributions from
- Tom Russell (University of Oxford)