Seropositivity and risk factors for SARS-CoV-2 infection in a South Asian community in Ontario: a cross-sectional analysis of a prospective cohort study

BACKGROUND: Early in the COVID-19 pandemic, the South Asian community in the Greater Toronto Area (GTA) was identified as having risk factors for exposure and specific barriers to accessing testing and reliable health information, rendering them particularly vulnerable to SARS-CoV-2 infection. We sought to investigate the burden of SARS-CoV-2 infection among South Asian people in the GTA, and to characterize the demographic characteristics, risk perceptions and trusted sources of health information in this group. METHODS: We conducted a cross-sectional analysis from the baseline assessment of participants in a prospective cohort study. Participants from the GTA were enrolled from Apr. 14 to July 28, 2021. Seropositivity for antispike and antinucleocapsid antibodies was determined from dried blood spots, and estimates of seropositivity were age and sex standardized to the South Asian population in Ontario. Demographic characteristics, risk perceptions and sources of COVID-19 information were collected via questionnaire and reported descriptively. RESULTS: Among the 916 South Asian participants enrolled (mean age 41 yr), the age- and sex-standardized seropositivity was 23.6% (95% confidence interval 20.8%–26.4%). Of the 693 respondents to the questionnaire, 228 (32.9%) identified as essential workers, and 125 (19.1%) reported living in a multigenerational household. A total of 288 (49.4%) perceived that they were at high COVID-19 risk owing to their geographic location, and 149 (34.3%) owing to their type of employment. The top 3 most trusted sources of information related to COVID-19 included health care providers and public health, traditional media sources and social media. INTERPRETATION: By the third wave of the COVID-19 pandemic, about one-quarter of a sample of South Asian individuals in Ontario had serologic evidence of prior SARS-CoV-2 infection. Insight into factors that put certain populations at risk can help future pandemic planning and disease control efforts.