ABSTRACT
BackgroundEstimating the cumulative incidence of SARS-CoV-2 is essential for setting public health policies. We leveraged de-identified Massachusetts newborn screening specimens to generate an accessible, retrospective source of maternal antibodies for estimating statewide SARS-CoV-2 seroprevalence in a non-test-seeking population. MethodsWe analyzed 72,117 newborn dried blood spots collected from November 2019 through December 2020, representing 337 towns and cities across Massachusetts. Seroprevalence was estimated for the general Massachusetts population after correcting for imperfect test specificity and nonrepresentative sampling using Bayesian multilevel regression and poststratification. ResultsStatewide seroprevalence was estimated to be 0.03% (90% credible interval (CI) [0.00, 0.11]) in November 2019 and rose to 1.47% (90% CI [1.00, 2.13]) by May 2020, following sustained SARS-CoV-2 transmission in the spring. Seroprevalence plateaued from May onwards, reaching 2.15% (90% CI [1.56, 2.98]) in December 2020. Seroprevalence varied substantially by community and was particularly associated with community percent non-Hispanic Black ({beta} = 0.024, 90% CI [0.004, 0.044]); i.e., a 10% increase in community percent non-Hispanic Black was associated with a 27% higher odds of seropositivity. Seroprevalence estimates had good concordance with reported case counts and wastewater surveillance for most of 2020, prior to the resurgence of transmission in winter. ConclusionsCumulative incidence of SARS-CoV-2 protective antibody in Massachusetts was low as of December 2020, indicating that a substantial fraction of the population was still susceptible. Maternal seroprevalence data from newborn screening can inform longitudinal trends and identify cities and towns at highest risk, particularly in settings where widespread diagnostic testing is unavailable. SummaryThe measurement of maternal antibodies in dried blood spots collected for newborn screening offers a statewide source of SARS-CoV-2 seroprevalence data independent of case testing limitations. We analyzed 72,117 Massachusetts spots collected November 2019 - December 2020 and estimated longitudinal trends.
ABSTRACT
The impact of variable infection risk by race and ethnicity on the dynamics of SARS-CoV-2 spread is largely unknown. Here, we fit structured compartmental models to seroprevalence data from New York State and analyze how herd immunity thresholds (HITs), final sizes, and epidemic risk changes across groups. A simple model where interactions occur proportionally to contact rates reduced the HIT, but more realistic models of preferential mixing within groups increased the threshold toward the value observed in homogeneous populations. Across all models, the burden of infection fell disproportionately on minority populations: in a model fit to Long Island serosurvey and census data, 81% of Hispanics or Latinos were infected when the HIT was reached compared to 34% of non-Hispanic whites. Our findings, which are meant to be illustrative and not best estimates, demonstrate how racial and ethnic disparities can impact epidemic trajectories and result in unequal distributions of SARS-CoV-2 infection.
