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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.
- COVID-19
- public health
- statistics & research methods
Data availability statement
Data may be obtained from a third party and are not publicly available. This work uses non-identifiable data provided through use of the DoH NI app, COVIDCare NI (formerly known as ‘COVID-19 NI’). Data may be obtained from the data controllers and are not publicly available. The app was produced on behalf of the DoH by Digital Health and Care Northern Ireland (DHCNI), working partnership with commercial partners Civica and BigMotive). Data may be obtained from the data controllers and are not publicly available.This work also uses data provided by participants of the COVID-19 Symptoms Study, developed by ZOE Global Limited with scientific and clinical input from King’s College London. This study makes use of anonymised data held in the Secure Anonymised Information Linkage (SAIL) Databank. Data may be obtained from the data controllers by application through https://www.healthdatagateway.org.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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Data availability statement
Data may be obtained from a third party and are not publicly available. This work uses non-identifiable data provided through use of the DoH NI app, COVIDCare NI (formerly known as ‘COVID-19 NI’). Data may be obtained from the data controllers and are not publicly available. The app was produced on behalf of the DoH by Digital Health and Care Northern Ireland (DHCNI), working partnership with commercial partners Civica and BigMotive). Data may be obtained from the data controllers and are not publicly available.This work also uses data provided by participants of the COVID-19 Symptoms Study, developed by ZOE Global Limited with scientific and clinical input from King’s College London. This study makes use of anonymised data held in the Secure Anonymised Information Linkage (SAIL) Databank. Data may be obtained from the data controllers by application through https://www.healthdatagateway.org.
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Footnotes
Twitter @mckinley_geojen
Contributors JMM conducted the initial literature searches, conducted the analysis and completed the initial drafts of the manuscript with input from all authors. DC and NA extracted the data and BJ, JMM and CG formatted the data. UM, PMA and FK conducted literature searches. UM, PMA, HVW, DTB and FK reviewed the statistical methods. All authors (JMM, UM, PMA, DC, NA, BJ, CG, HVW, DTB and FK) read and approved the final manuscript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
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Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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