Temporal trends in disparities in COVID-19 seropositivity among Canadian blood donors

被引:0
作者
Yu, Yuan [1 ]
Knight, Matthew J. [1 ]
Gibson, Diana [1 ]
OBrien, Sheila F. [2 ,3 ]
Buckeridge, David L. [1 ,4 ]
Russell, W. Alton [1 ]
机构
[1] McGill Univ, Sch Populat & Global Hlth, Suite 1200,2001 McGill Coll Ave, Montreal, PQ H3A 1G1, Canada
[2] Canadian Blood Serv, Ottawa, ON, Canada
[3] Univ Ottawa, Sch Epidemiol & Publ Hlth, Ottawa, ON, Canada
[4] COVID 19 Immun Task Force, Montreal, PQ, Canada
关键词
Serology; COVID-19; surveillance; Bayesian multi-level regression; health disparities; blood donors; SARS-COV-2; SEROPREVALENCE; MODELS;
D O I
10.1093/ije/dyae078
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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.
引用
收藏
页数:8
相关论文
共 38 条
[1]   Healthy donor effect: its magnitude in health research among blood donors [J].
Atsma, Femke ;
Veldhuizen, Ingrid ;
Verbeek, Andre ;
de Kort, Wim ;
de Vegt, Femmie .
TRANSFUSION, 2011, 51 (08) :1820-1828
[2]   Impact of social and demographic factors on the spread of the SARS-CoV-2 epidemic in the town of Nice [J].
Barjoan, Eugenia Marine ;
Chaarana, Amel ;
Festraets, Julie ;
Geloen, Carole ;
Prouvost-Keller, Bernard ;
Legueult, Kevin ;
Pradier, Christian .
BMC PUBLIC HEALTH, 2023, 23 (01)
[3]   Global SARS-CoV-2 seroprevalence from January 2020 to April 2022: A systematic review and meta-analysis of standardized population-based studies [J].
Bergeri, Isabel ;
Whelan, Mairead G. ;
Ware, Harriet ;
Subissi, Lorenzo ;
Nardone, Anthony ;
Lewis, Hannah C. ;
Li, Zihan ;
Ma, Xiaomeng ;
Valenciano, Marta ;
Cheng, Brianna ;
Al Ariqi, Lubna ;
Rashidian, Arash ;
Okeibunor, Joseph ;
Azim, Tasnim ;
Wijesinghe, Pushpa ;
Linh-Vi Le ;
Vaughan, Aisling ;
Pebody, Richard ;
Vicari, Andrea ;
Yan, Tingting ;
Yanes-Lane, Mercedes ;
Cao, Christian ;
Clifton, David A. ;
Cheng, Matthew P. ;
Papenburg, Jesse ;
Buckeridge, David ;
Bobrovitz, Niklas ;
Arora, Rahul K. ;
Van Kerkhove, Maria D. .
PLOS MEDICINE, 2022, 19 (11)
[4]   BAYESIAN IMAGE-RESTORATION, WITH 2 APPLICATIONS IN SPATIAL STATISTICS [J].
BESAG, J ;
YORK, J ;
MOLLIE, A .
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, 1991, 43 (01) :1-20
[5]   Global seroprevalence of SARS-CoV-2 antibodies: A systematic review and meta-analysis [J].
Bobrovitz, Niklas ;
Arora, Rahul Krishan ;
Cao, Christian ;
Boucher, Emily ;
Liu, Michael ;
Donnici, Claire ;
Yanes-Lane, Mercedes ;
Whelan, Mairead ;
Perlman-Arrow, Sara ;
Chen, Judy ;
Rahim, Hannah ;
Ilincic, Natasha ;
Segal, Mitchell ;
Duarte, Nathan ;
Van Wyk, Jordan ;
Yan, Tingting ;
Atmaja, Austin ;
Rocco, Simona ;
Joseph, Abel ;
Penny, Lucas ;
Clifton, David A. ;
Williamson, Tyler ;
Yansouni, Cedric P. ;
Evans, Timothy Grant ;
Chevrier, Jonathan ;
Papenburg, Jesse ;
Cheng, Matthew P. .
PLOS ONE, 2021, 16 (06)
[6]   Multilevel Modelling of Country Effects: A Cautionary Tale [J].
Bryan, Mark L. ;
Jenkins, Stephen P. .
EUROPEAN SOCIOLOGICAL REVIEW, 2016, 32 (01) :3-22
[7]   brms: An R Package for Bayesian Multilevel Models Using Stan [J].
Buerkner, Paul-Christian .
JOURNAL OF STATISTICAL SOFTWARE, 2017, 80 (01) :1-28
[8]  
Canadian Medical Association, 2023, Containing COVID-19: How a Calgary Health Team Helped Suppress an Outbreak at a Meat-Packing Plant
[9]   Pre-Vaccine Positivity of SARS-CoV-2 Antibodies in Alberta, Canada during the First Two Waves of the COVID-19 Pandemic [J].
Charlton, Carmen L. ;
Nguyen, Leonard T. ;
Bailey, Ashley ;
Fenton, Jayne ;
Plitt, Sabrina S. ;
Marohn, Carol ;
Lau, Cheryl ;
Hinshaw, Deena ;
Lutsiak, Christie ;
Simmonds, Kimberley ;
Kanji, Jamil N. ;
Zelyas, Nathan ;
Lee, Nelson ;
Mengel, Michael ;
Tipples, Graham .
MICROBIOLOGY SPECTRUM, 2021, 9 (01) :1-2
[10]  
Chen XH, 2021, LANCET GLOB HEALTH, V9, pE598, DOI [10.1101/2020.09.11.20192773, 10.1016/S2214-109X(21)00026-7]