Using sero-epidemiology to monitor disparities in vaccination and infection with SARS-CoV-2

Abstract

As SARS-CoV-2 continues to spread and vaccines are rolled-out, the "double burden" of disparities in exposure and vaccination intersect to determine patterns of infection, immunity, and mortality. Serology provides a unique opportunity to measure prior infection and vaccination simultaneously. Leveraging algorithmically-selected residual sera from two hospital networks in the city of San Francisco, cross-sectional samples from 1,014 individuals from February 4-17, 2021 were each tested on two assays (Ortho Clinical Diagnostics VITROS Anti-SARS-CoV-2 and Roche Elecsys Anti-SARS-CoV-2), capturing the first year of the epidemic and early roll-out of vaccination. We estimated, using Bayesian estimation of infection and vaccination, that infection risk of Hispanic/Latinx residents was five times greater than of White residents aged 18-64 (95% Credible Interval (CrI): 3.2-10.3), and that White residents over 65 were twice as likely to be vaccinated as Black/African American residents (95% CrI: 1.1-4.6). We found that socioeconomically-deprived zipcodes had higher infection probabilities and lower vaccination coverage than wealthier zipcodes. While vaccination has created a 'light at the end of the tunnel' for this pandemic, ongoing challenges in achieving and maintaining equity must also be considered.

Fig. 1. Sample characteristics.

a Age distribution by health network of sample collection within the University of California, San Francisco (UCSF) (N = 698 biologically independent samples) and San Francisco Department of Public Health (ZSFG) hospital networks (N = 316 biologically independent samples). Each point represents a sample and colors correspond to age bins used for analysis. The box plot whiskers show the maximum and minimum ages, the box shows the 25-75^th percentile values for age, and the central line within the boxplot represents the median age within each health network. b Proportion of samples from a given San Francisco zipcode plotted against the proportion of the San Francisco population within that zipcode. Colors show the percentage of residents below the poverty line within that zipcode, as determined by the American Community Survey 2019, using census bureau definitions of poverty thresholds.

Fig. 2. Schematic of parameters to be estimated using serosurveillance platform (shown in red, blue and gold).

Red represents the probability of vaccination given prior infection, Pr(vacc|inf), blue represents the probability of prior infection, Pr(inf), and gold represents the probability of vaccination given no prior history of infection, Pr(vacc|uninf).

Fig. 3. Maps showing geographic disparities in SARS-CoV-2 within San Francisco.

Maps show a estimated probability of prior infection and b probability of vaccination by zipcode in San Francisco, as of February 2021.

Fig. 4. Stratified seroprevalence by assay and by demographic group.

a Univariate Roche seropositivity estimates by age (elicited by prior infection). b Univariate Vitros estimates by age (elicited by either prior infection or vaccination). c Univariate Roche estimates by race/ethnicity. d Univariate Vitros estimates by race/ethnicity. For all panels, the center line of the box and whisker diagram represents the median posterior estimate, the box represents the 25-75^th percentile values of the posterior, and the whisker lines show the 95% Credible Interval.

Fig. 5. Relationship between probability of vaccination and probability of prior infection by race/ethnicity.

a Probability of infection vs. probability of vaccination by age and race/ethnicity. Error bars show the upper and lower limits of the 95% Credible Interval of the estimates, and points show the median of the estimates. (65+ and Black/African American, N = 33; 65+ and White, N = 160; 65+ and Hispanic/Latinx, N = 37; 18–64 and Black/African American, N = 82; 18–64 and White, N = 202; 18–64 and Hispanic/Latinx, N = 130). b Infographic showing the number of estimated people vaccinated for every one person previously naturally infected in San Francisco within each racial/demographic group.