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To inform public health policy, it is critical to monitor COVID-19 vaccine effectiveness (VE), including against acquiring infection. We estimated VE using a retrospective cohort study among repeat blood donors who donated during the first half of 2021, demonstrating a viable approach for monitoring of VE via serological surveillance. Using Poisson regression, we estimated overall VE was 88.8% (95% CI: 86.2-91.1), adjusted for demographic covariates and variable baseline risk. Time since first reporting vaccination, age, race-ethnicity, region, and calendar time were statistically significant predictors of incident infection. Studies of VE during periods of Delta and Omicron spread are underway.
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BackgroundBlood donors are increasingly being recognized as an informative resource for surveillance. We aimed to review and characterize SARS-CoV-2 seroprevalence studies conducted using blood donors to investigate methodology and provide guidance for future research. MethodsWe conducted a scoping review of peer-reviewed and preprint publications between January 2020 to January 2021. Two reviewers used standardized forms to extract seroprevalence estimates and data on methodology pertaining to population sampling, periodicity, assay characteristics and antibody kinetics. National data on cumulative incidence and social distancing policies were extracted from publicly available sources and summarized. ResultsThirty-three studies representing 1,323,307 blood donations from 20 countries worldwide were included (sample size per study ranged from 22 to 953,926 donations). Seroprevalence rates ranged from 0% to 76% (after adjusting for waning antibodies). Overall, less than 1 in 5 studies reported standardized seroprevalence rates to reflect the demographics of the general population. Stratification by age and sex were most common (64% of studies), followed by region (48%). 52% of studies reported seroprevalence at a single time point. Overall, 27 unique assay combinations were identified, 55% of studies used a single assay and only 39% adjusted seroprevalence rates for imperfect test characteristics. Among the eight nationally representative studies case detection was most underrepresented in Kenya (1:1264). ConclusionAs of December 11, 2020, 79% of studies reported seroprevalence rates <10%; thresholds far from reaching herd immunity. In addition to differences in community transmission and diverse public health policies, study designs and methodology were likely contributing factors to seroprevalence heterogeneity.
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BackgroundCOVID-19 Convalescent Plasma (CCP) is a promising treatment for COVID-19. Blood collectors have rapidly scaled up collection and distribution programs. MethodsWe developed a detailed simulation model of CCP donor recruitment, collection, production and distribution processes. Simulations based on epidemics in 11 U.S. states, in which key parameters were varied over wide ranges, allowed identification of the drivers of ability to calibrate collections capacity and ability to meet demand for CCP. ResultsChanges in collection capacity utilization lagged increases and decreases in COVID-19 hospital discharges, and never exceeded 75% in most simulations. Demand could be met for most of the simulation period in most simulations, but in states with early sharp increases in hospitalizations a substantial portion of demand went unmet during these early peaks. Modeled second wave demand could generally be met with stockpiles established during first epidemic peaks. Apheresis machine capacity (number of machines) and probability that COVID-19 recovered individuals are willing to donate were the most important supply-side drivers of ability to meet demand. Recruitment capacity was important in states with early peaks. ConclusionsEpidemic trajectory was the most important determinant of ability to meet demand for CCP, although our simulations revealed several contributing operational drivers of CCP program success.
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The herd immunity threshold is the proportion of a population that must be immune to an infectious disease, either by natural infection or vaccination such that, in the absence of additional preventative measures, new cases decline and the effective reproduction number falls below unity. This fundamental epidemiological parameter is still unknown for the recently-emerged COVID-19, and mathematical models have predicted very divergent results. Population studies using antibody testing to infer total cumulative infections can provide empirical evidence of the level of population immunity in severely affected areas. Here we show that the transmission of SARS-CoV-2 in Manaus, located in the Brazilian Amazon, increased quickly during March and April and declined more slowly from May to September. In June, one month following the epidemic peak, 44% of the population was seropositive for SARS-CoV-2, equating to a cumulative incidence of 52%, after correcting for the false-negative rate of the antibody test. The seroprevalence fell in July and August due to antibody waning. After correcting for this, we estimate a final epidemic size of 66%. Although non-pharmaceutical interventions, plus a change in population behavior, may have helped to limit SARS-CoV-2 transmission in Manaus, the unusually high infection rate suggests that herd immunity played a significant role in determining the size of the epidemic.
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We report very low SARS-CoV-2 seroprevalence in two San Francisco Bay Area populations. Seropositivity was 0.26% in 387 hospitalized patients admitted for non-respiratory indications and 0.1% in 1,000 blood donors. We additionally describe the longitudinal dynamics of immunoglobulin-G, immunoglobulin-M, and in vitro neutralizing antibody titers in COVID-19 patients. Neutralizing antibodies rise in tandem with immunoglobulin levels following symptom onset, exhibiting median time to seroconversion within one day of each other, and there is >93% positive percent agreement between detection of immunoglobulin-G and neutralizing titers.