Back

Health inequalities in SARS-CoV-2 infection during the second wave in England: REACT-1 study

Wang, H.; Ainslie, K. E. C.; Eales, O.; Walters, C. E.; Haw, D.; Atchinson, C.; Fronterre, C.; Diggle, P. J.; Ashby, D.; Cooke, G.; Barclay, W.; Ward, H.; Darzi, A.; Donnelly, C. A.; Elliott, P.; Riley, S.

2023-08-02 epidemiology
10.1101/2023.08.01.23293491 medRxiv
Show abstract

ObjectivesThe rapid spread of SARS-CoV-2 infection caused high levels of hospitalisation and deaths in late 2020 and early 2021 during the second wave in England. Severe disease during this period was associated with marked health inequalities across ethnic and sociodemographic subgroups. In this paper, we aimed to investigate how inequalities influence the risk of getting infected across ethnic and sociodemographic subgroups during a key period before widespread vaccination. DesignRepeated cross-sectional community-based study. MethodsWe analysed risk factors for test-positivity for SARS-CoV-2, based on self-administered throat and nose swabs in the community during rounds 5 to 10 of the REal-time Assessment of Community Transmission-1 (REACT-1) study between 18 September 2020 and 30 March 2021. ResultsCompared to white ethnicity, people of Asian and black ethnicity had a higher risk of infection during rounds 5 to 10, with odds of 1.46 (1.27, 1.69) and 1.35 (1.11, 1.64) respectively. Among ethnic subgroups, the highest and the second-highest odds were found in Bangladeshi and Pakistan participants at 3.29 (2.23, 4.86) and 2.15 (1.73, 2.68) respectively when compared to British whites. People in larger (compared to smaller) households had higher odds of infection. Health care workers with direct patient contact and care home workers showed higher odds of infection compared to other essential/key workers. Additionally, the odds of infection among participants in public-facing activities or settings were greater than among those not working in those activities or settings. ConclusionOur findings highlight the differences in the risk of SARS-CoV-2 infection in a global-north population during a period when the risk of infection was high, and there were substantial levels of social mixing. Planning for future severe waves of respiratory pathogens should include policies to reduce inequality in the risk of infection by ethnicity, household size, and occupational activity in order to reduce inequality in disease. Summary boxWhat is already known on this topic Extensive studies have described the relationship between socio-demographic factors and SARS-CoV-2 outcomes such as hospitalisations and deaths, rather than SARS-CoV-2 infection. Limited community-based studies investigated risk factors associated with SARS-CoV-2 infection, with the time frame of these studies has mainly focused on the period of the first wave of infection, or the beginning of the second wave, or the rollout of the first dose of the vaccine after the second wave period. We did not find studies that covered the critical period of the second wave in England when levels of social mixing were high, but no vaccine was available. What this study adds We show health inequalities across ethnic and sociodemographic subgroups during a key period: before widespread vaccination, but, largely, not during the period of stringent social distancing. We observed substantial ethnic and occupational differences in the risk of SARS-CoV-2 infection. Minority ethnic groups, including those of Bangladeshi and Pakistani ethnicity, had an excess risk of infection compared with the British white population. Healthcare workers, care home workers and people who work in public-facing activities or settings were associated with higher odds of infection. The risk of SARS-CoV-2 infection increased monotonically as household size increased, and more deprived neighbourhood areas were associated with a higher risk of infection. How this study might affect research, practice or policy Our findings highlight the differences in the risk of SARS-CoV-2 infection in a global-north population during a period when the risk of infection was high, and there were substantial levels of social mixing. Planning for future waves of severe respiratory infection should explicitly aim to reduce inequalities in infection in order to reduce inequality in disease.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.