tetano
Editor, Senior Moderator
Int J Epidemiol
. 2024 Apr 11;53(3):dyae078.
doi: 10.1093/ije/dyae078. Temporal trends in disparities in COVID-19 seropositivity among Canadian blood donors
Yuan Yu[SUP] 1 [/SUP], Matthew J Knight[SUP] 1 [/SUP], Diana Gibson[SUP] 1 [/SUP], Sheila F O'Brien[SUP] 2 3 [/SUP], David L Buckeridge[SUP] 1 4 [/SUP], W Alton Russell[SUP] 1 4 [/SUP]
Affiliations
Background: In Canada's largest COVID-19 serological study, SARS-CoV-2 antibodies in blood donors have been monitored since 2020. No study has analysed changes in the association between anti-N seropositivity (a marker of recent infection) and geographic and sociodemographic characteristics over the pandemic.
Methods: Using Bayesian multi-level models with spatial effects at the census division level, we analysed changes in correlates of SARS-CoV-2 anti-N seropositivity across three periods in which different variants predominated (pre-Delta, Delta and Omicron). We analysed disparities by geographic area, individual traits (age, sex, race) and neighbourhood factors (urbanicity, material deprivation and social deprivation). Data were from 420 319 blood donations across four regions (Ontario, British Columbia [BC], the Prairies and the Atlantic region) from December 2020 to November 2022.
Results: Seropositivity was higher for racialized minorities, males and individuals in more materially deprived neighbourhoods in the pre-Delta and Delta waves. These subgroup differences dissipated in the Omicron wave as large swaths of the population became infected. Across all waves, seropositivity was higher in younger individuals and those with lower neighbourhood social deprivation. Rural residents had high seropositivity in the Prairies, but not other regions. Compared to generalized linear models, multi-level models with spatial effects had better fit and lower error when predicting SARS-CoV-2 anti-N seropositivity by geographic region.
Conclusions: Correlates of recent COVID-19 infection have evolved over the pandemic. Many disparities lessened during the Omicron wave, but public health intervention may be warranted to address persistently higher burden among young people and those with less social deprivation.
Keywords: Bayesian multi-level regression; COVID-19; Serology; blood donors; health disparities; surveillance.
. 2024 Apr 11;53(3):dyae078.
doi: 10.1093/ije/dyae078. Temporal trends in disparities in COVID-19 seropositivity among Canadian blood donors
Yuan Yu[SUP] 1 [/SUP], Matthew J Knight[SUP] 1 [/SUP], Diana Gibson[SUP] 1 [/SUP], Sheila F O'Brien[SUP] 2 3 [/SUP], David L Buckeridge[SUP] 1 4 [/SUP], W Alton Russell[SUP] 1 4 [/SUP]
Affiliations
- PMID: 38840559
- DOI: 10.1093/ije/dyae078
Background: In Canada's largest COVID-19 serological study, SARS-CoV-2 antibodies in blood donors have been monitored since 2020. No study has analysed changes in the association between anti-N seropositivity (a marker of recent infection) and geographic and sociodemographic characteristics over the pandemic.
Methods: Using Bayesian multi-level models with spatial effects at the census division level, we analysed changes in correlates of SARS-CoV-2 anti-N seropositivity across three periods in which different variants predominated (pre-Delta, Delta and Omicron). We analysed disparities by geographic area, individual traits (age, sex, race) and neighbourhood factors (urbanicity, material deprivation and social deprivation). Data were from 420 319 blood donations across four regions (Ontario, British Columbia [BC], the Prairies and the Atlantic region) from December 2020 to November 2022.
Results: Seropositivity was higher for racialized minorities, males and individuals in more materially deprived neighbourhoods in the pre-Delta and Delta waves. These subgroup differences dissipated in the Omicron wave as large swaths of the population became infected. Across all waves, seropositivity was higher in younger individuals and those with lower neighbourhood social deprivation. Rural residents had high seropositivity in the Prairies, but not other regions. Compared to generalized linear models, multi-level models with spatial effects had better fit and lower error when predicting SARS-CoV-2 anti-N seropositivity by geographic region.
Conclusions: Correlates of recent COVID-19 infection have evolved over the pandemic. Many disparities lessened during the Omicron wave, but public health intervention may be warranted to address persistently higher burden among young people and those with less social deprivation.
Keywords: Bayesian multi-level regression; COVID-19; Serology; blood donors; health disparities; surveillance.