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

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

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.