BACKGROUND: Ethnically diverse and socio-economically deprived communities have been differentially affected by the COVID-19 pandemic in the UK. METHOD: Using a multilevel regression model we assessed the time-varying association between SARS-CoV-2 infections and areal level deprivation and ethnicity from 1st of June 2020 to the 19th of September 2021. We separately considered weekly test positivity rate and estimated debiased prevalence at the Lower Tier Local Authority (LTLA) level, adjusting for confounders and spatio-temporal correlation structure. FINDINGS: Comparing the least deprived and predominantly White areas with most deprived and predominantly non-White areas over the whole study period, the weekly positivity rate increases from 2·977% (95% CrI 2.913%-3.029%) to 3·347% (95% CrI 3.300%-3.402%). Similarly, prevalence increases from 0·369% (95% CrI 0.361%-0.375%) to 0·405% (95% CrI 0.399%-0.412%). Deprivation has a stronger effect until October 2020, while the effect of ethnicity becomes more pronounced at the peak of the second wave and then again in May-June 2021. In the second wave of the pandemic, LTLAs with large South Asian populations were the most affected, whereas areas with large Black populations did not show increased values for either outcome during the entire period under analysis. INTERPRETATION: Deprivation and proportion of non-White populations are both associated with an increased COVID-19 burden in terms of disease spread and monitoring, but the strength of association varies over the course of the pandemic and for different ethnic subgroups. The consistency of results across the two outcomes suggests that deprivation and ethnicity have a differential impact on disease exposure or susceptibility rather than testing access and habits. FUNDINGS: EPSRC, MRC, The Alan Turing Institute, NIH, UKHSA, DHSC.
BACKGROUND: Ethnically diverse and socio-economically deprived communities have been differentially affected by the COVID-19 pandemic in the UK. METHOD: Using a multilevel regression model we assessed the time-varying association between SARS-CoV-2 infections and areal level deprivation and ethnicity from 1st of June 2020 to the 19th of September 2021. We separately considered weekly test positivity rate and estimated debiased prevalence at the Lower Tier Local Authority (LTLA) level, adjusting for confounders and spatio-temporal correlation structure. FINDINGS: Comparing the least deprived and predominantly White areas with most deprived and predominantly non-White areas over the whole study period, the weekly positivity rate increases from 2·977% (95% CrI 2.913%-3.029%) to 3·347% (95% CrI 3.300%-3.402%). Similarly, prevalence increases from 0·369% (95% CrI 0.361%-0.375%) to 0·405% (95% CrI 0.399%-0.412%). Deprivation has a stronger effect until October 2020, while the effect of ethnicity becomes more pronounced at the peak of the second wave and then again in May-June 2021. In the second wave of the pandemic, LTLAs with large South Asian populations were the most affected, whereas areas with large Black populations did not show increased values for either outcome during the entire period under analysis. INTERPRETATION: Deprivation and proportion of non-White populations are both associated with an increased COVID-19 burden in terms of disease spread and monitoring, but the strength of association varies over the course of the pandemic and for different ethnic subgroups. The consistency of results across the two outcomes suggests that deprivation and ethnicity have a differential impact on disease exposure or susceptibility rather than testing access and habits. FUNDINGS: EPSRC, MRC, The Alan Turing Institute, NIH, UKHSA, DHSC.
Authors: Amy R Cross; Peng Hua; Damien J Downes; Nigel Roberts; Ron Schwessinger; Antony J Cutler; Altar M Munis; Jill Brown; Olga Mielczarek; Carlos E de Andrea; Ignacio Melero; Deborah R Gill; Stephen C Hyde; Julian C Knight; John A Todd; Stephen N Sansom; Fadi Issa; James O J Davies; Jim R Hughes Journal: Nat Genet Date: 2021-11-04 Impact factor: 38.330
Authors: Rohini Mathur; Christopher T Rentsch; Caroline E Morton; William J Hulme; Anna Schultze; Brian MacKenna; Rosalind M Eggo; Krishnan Bhaskaran; Angel Y S Wong; Elizabeth J Williamson; Harriet Forbes; Kevin Wing; Helen I McDonald; Chris Bates; Seb Bacon; Alex J Walker; David Evans; Peter Inglesby; Amir Mehrkar; Helen J Curtis; Nicholas J DeVito; Richard Croker; Henry Drysdale; Jonathan Cockburn; John Parry; Frank Hester; Sam Harper; Ian J Douglas; Laurie Tomlinson; Stephen J W Evans; Richard Grieve; David Harrison; Kathy Rowan; Kamlesh Khunti; Nishi Chaturvedi; Liam Smeeth; Ben Goldacre Journal: Lancet Date: 2021-04-30 Impact factor: 202.731
Authors: Chun-Han Lo; Long H Nguyen; David A Drew; Erica T Warner; Amit D Joshi; Mark S Graham; Adjoa Anyane-Yeboa; Fatma M Shebl; Christina M Astley; Jane C Figueiredo; Chuan-Guo Guo; Wenjie Ma; Raaj S Mehta; Sohee Kwon; Mingyang Song; Richard Davies; Joan Capdevila; Carole H Sudre; Jonathan Wolf; Yvette C Cozier; Lynn Rosenberg; Lynne R Wilkens; Christopher A Haiman; Loïc Le Marchand; Julie R Palmer; Tim D Spector; Sebastien Ourselin; Claire J Steves; Andrew T Chan Journal: EClinicalMedicine Date: 2021-07-17
Authors: Chris Holmes; Sylvia Richardson; George Nicholson; Marta Blangiardo; Mark Briers; Peter J Diggle; Tor Erlend Fjelde; Hong Ge; Robert J B Goudie; Radka Jersakova; Ruairidh E King; Brieuc C L Lehmann; Ann-Marie Mallon; Tullia Padellini; Yee Whye Teh Journal: Stat Sci Date: 2022-05 Impact factor: 4.015
Authors: Daniel Pan; Shirley Sze; Joshua Nazareth; Christopher A Martin; Amani Al-Oraibi; Rebecca F Baggaley; Laura B Nellums; T Déirdre Hollingsworth; Julian W Tang; Manish Pareek Journal: Lancet Date: 2022-10-15 Impact factor: 202.731