Abstract

Complex interactions between physical landscapes and social factors increase vulnerability to emerging infections
and their sequelae. Relative vulnerability to severe illness and/or death (VSID) depends on risk and
extent of exposure to a virus and underlying health susceptibility. Identifying vulnerable communities and the
regions they inhabit in real time is essential for effective rapid response to a new pandemic, such as COVID-19. In
the period between first confirmed cases and the introduction of widespread community testing, ambulance
records of suspected severe illness from COVID-19 could be used to identify vulnerable communities and regions
and rapidly appraise factors that may explain VSID. We analyse the spatial distribution of more than 10,000
suspected severe COVID-19 cases using records of provisional diagnoses made by trained paramedics attending
medical emergencies. We identify 13 clusters of severe illness likely related to COVID-19 occurring in the East
Midlands of the UK and present an in-depth analysis of those clusters, including urban and rural dynamics, the
physical characteristics of landscapes, and socio-economic conditions. Our findings suggest that the dynamics of
VSID vary depending on wider geographic location. Vulnerable communities and regions occur in more deprived
urban centres as well as more affluent peri-urban and rural areas. This methodology could contribute to the
development of a rapid national response to support vulnerable communities during emerging pandemics in real
time to save lives.