Association between community-based self-reported COVID-19 symptoms and social deprivation explored using symptom tracker apps: a repeated cross-sectional study in Northern Ireland

Jennifer M Mckinley, David Cutting, Neil Anderson, Conor Graham, Brian Johnston, Ute Mueller, Peter M Atkinson, Hugo Van Woerden, Declan T Bradley, Frank Kee

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
57 Downloads (Pure)

Abstract

Abstract Objectives The aim of the study was to investigate the spatial and temporal relationships between the prevalence of COVID-19 symptoms in the community-level and area-level social deprivation. Design Spatial mapping, generalised linear models, using time as a factor and spatial-lag models were used to explore the relationship between self-reported COVID-19 symptom prevalence as recorded through two smartphone symptom tracker apps and a range of socioeconomic factors using a repeated cross-sectional study design. Setting In the community in Northern Ireland, UK. The analysis period included the earliest stages of non-pharmaceutical interventions and societal restrictions or ‘lockdown’ in 2020. Participants Users of two smartphone symptom tracker apps recording self-reported health information who recorded their location as Northern Ireland, UK. Primary outcome measures Population standardised self-reported COVID-19 symptoms and correlation between population standardised self-reported COVID-19 symptoms and area-level characteristics from measures of multiple deprivation including employment levels and population housing density, derived as the mean number of residents per household for each census super output area. Results Higher self-reported prevalence of COVID-19 symptoms was associated with the most deprived areas (p<0.001) and with those areas with the lowest employment levels (p<0.001). Higher rates of self-reported COVID-19 symptoms within the age groups, 18–24 and 25–34 years were found within the most deprived areas during the earliest stages of non-pharmaceutical interventions and societal restrictions (‘lockdown’). Conclusions Through spatial regression of self-reporting COVID-19 smartphone data in the community, this research shows how a lens of social deprivation can deepen our understanding of COVID-19 transmission and prevention. Our findings indicate that social inequality, as measured by area-level deprivation, is associated with disparities in potential COVID-19 infection, with higher prevalence of self-reported COVID-19 symptoms in urban areas associated with area-level social deprivation, housing density and age.
Original languageEnglish
Article numbere048333
Pages (from-to)1-9
Number of pages9
JournalBMJ open
Volume11
Issue number6
DOIs
Publication statusPublished - 22 Jun 2021

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