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Serosurveys are a key resource for measuring SARS-CoV-2 population exposure. A growing body of evidence suggests that asymptomatic and mild infections (together making up over 95% of all infections) are associated with lower antibody titers than severe infections. Antibody levels also peak a few weeks after infection and decay gradually. We developed a statistical approach to produce estimates of cumulative incidence from raw seroprevalence survey results that account for these sources of spectrum bias. We incorporate data on antibody responses on multiple assays from a post-infection longitudinal cohort, along with epidemic time series to account for the timing of a serosurvey relative to how recently individuals may have been infected. We applied this method to produce estimates of cumulative incidence from five large-scale SARS-CoV-2 serosurveys across different settings and study designs. We identify substantial differences between raw seroprevalence and cumulative incidence of over two-fold in the results of some surveys, and provide a tool for practitioners to generate cumulative incidence estimates with pre-set or custom parameter values. While unprecedented efforts have been launched to generate SARS-CoV-2 seroprevalence estimates over this past year, interpretation of results from these studies requires properly accounting for both population-level epidemiologic context and individual-level immune dynamics.

Serosurveillance provides a unique opportunity to quantify the proportion of the population that has been exposed to pathogens. Here, we developed and piloted Serosurveillance for Continuous, ActionabLe Epidemiologic Intelligence of Transmission (SCALE-IT), a platform through which we systematically tested remnant samples from routine blood draws in two major hospital networks in San Francisco for SARS-CoV-2 antibodies during the early months of the pandemic. Importantly, SCALE-IT allows for algorithmic sample selection and rich data on covariates by leveraging electronic health record data. We estimated overall seroprevalence at 4.2%, corresponding to a case ascertainment rate of only 4.9%, and identified important heterogeneities by neighborhood, homelessness status, and race/ethnicity. Neighborhood seroprevalence estimates from SCALE-IT were comparable to local community-based surveys, while providing results encompassing the entire city that have been previously unavailable. Leveraging this hybrid serosurveillance approach has strong potential for application beyond this local context and for diseases other than SARS-CoV-2., Population-based surveys are the gold standard for estimating seroprevalence but are expensive and often only capture a small geographic area or window of time. This study describes a new platform, SCALE-IT, for serosurveillance based on algorithmic sampling of electronic health records, and uses it to estimate the seroprevalence of SARS-CoV-2 in San Francisco.

Serosurveys are a key resource for measuring SARS-CoV-2 cumulative incidence. A growing body of evidence suggests that asymptomatic and mild infections (together making up over 95% of all infections) are associated with lower antibody titers than severe infections. Antibody levels also peak a few weeks after infection and decay gradually. We developed a statistical approach to produce adjusted estimates of seroprevalence from raw serosurvey results that account for these sources of spectrum bias. We incorporate data on antibody responses on multiple assays from a post-infection longitudinal cohort, along with epidemic time series to account for the timing of a serosurvey relative to how recently individuals may have been infected. We applied this method to produce adjusted seroprevalence estimates from five large-scale SARS-CoV-2 serosurveys across different settings and study designs. We identify substantial differences between reported and adjusted estimates of over two-fold in the results of some surveys, and provide a tool for practitioners to generate adjusted estimates with pre-set or custom parameter values. While unprecedented efforts have been launched to generate SARS-CoV-2 seroprevalence estimates over this past year, interpretation of results from these studies requires properly accounting for both population-level epidemiologic context and individual-level immune dynamics.

Current serology tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies mainly take the form of enzyme-linked immunosorbent assays, chemiluminescent microparticle immunoassays or lateral flow assays, which are either laborious, expensive or lacking sufficient sensitivity and scalability. Here we present the development and validation of a rapid, low-cost, solution-based assay to detect antibodies in serum, plasma, whole blood and to a lesser extent saliva, using rationally designed split luciferase antibody biosensors. This new assay, which generates quantitative results in 30 min, substantially reduces the complexity and improves the scalability of coronavirus disease 2019 (COVID-19) antibody tests. This assay is well-suited for point-of-care, broad population testing, and applications in low-resource settings, for monitoring host humoral responses to vaccination or viral infection.

Antibody detection of prior SARS-CoV-2 infection depends on severity, assay, and timing with implications for serosurveillance., Interpretation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurveillance studies is limited by poorly defined performance of antibody assays over time in individuals with different clinical presentations. We measured antibody responses in plasma samples from 128 individuals over 160 days using 14 assays. We found a consistent and strong effect of disease severity on antibody magnitude, driven by fever, cough, hospitalization, and oxygen requirement. Responses to spike protein versus nucleocapsid had consistently higher correlation with neutralization. Assays varied substantially in sensitivity during early convalescence and time to seroreversion. Variability was dramatic for individuals with mild infection, who had consistently lower antibody titers, with sensitivities at 6 months ranging from 33 to 98% for commercial assays. Thus, the ability to detect previous infection by SARS-CoV-2 is highly dependent on infection severity, timing, and the assay used. These findings have important implications for the design and interpretation of SARS-CoV-2 serosurveillance studies.

A detailed understanding of long-term SARS-CoV-2-specific T cell responses and their relationship to humoral immunity and markers of inflammation in diverse groups of individuals representing the spectrum of COVID-19 illness and recovery is urgently needed. Data are also lacking as to whether and how adaptive immune and inflammatory responses differ in individuals that experience persistent symptomatic sequelae months following acute infection compared to those with complete, rapid recovery. We measured SARS-CoV-2-specific T cell responses, soluble markers of inflammation, and antibody levels and neutralization capacity longitudinally up to 9 months following infection in a diverse group of 70 individuals with PCR-confirmed SARS-CoV-2 infection. The participants had varying degrees of initial disease severity and were enrolled in the northern California Long-term Impact of Infection with Novel Coronavirus (LIINC) cohort. Adaptive T cell responses remained remarkably stable in all participants across disease severity during the entire study interval. Whereas the magnitude of the early CD4+ T cell immune response is determined by the severity of initial infection (participants requiring hospitalization or intensive care), pre-existing lung disease was significantly associated with higher long-term SARS-CoV2-specific CD8+ T cell responses, independent of initial disease severity or age. Neutralizing antibody levels were strongly correlated with SARS-CoV-2-specific CD4+ T but not CD8+ T cell responses. Importantly, we did not identify substantial differences in long-term virus-specific T cell or antibody responses between participants with and without COVID-19-related symptoms that persist months after initial infection.

Serosurveillance provides a unique opportunity to quantify the proportion of the population that has been exposed to pathogens. Here, we developed and piloted Serosurveillance for Continuous, ActionabLe Epidemiologic Intelligence of Transmission (SCALE-IT), a platform through which we systematically tested remnant samples from routine blood draws in two major hospital networks in San Francisco for SARS-CoV-2 antibodies during the early months of the pandemic. Importantly, SCALE-IT allows for algorithmic sample selection and rich data on covariates by leveraging electronic medical record data. We estimated overall seroprevalence at 4.2%, corresponding to a case ascertainment rate of only 4.9%, and identified important heterogeneities by neighborhood, homelessness status, and race/ethnicity. Neighborhood seroprevalence estimates from SCALE-IT were comparable to local community-based surveys, while providing results encompassing the entire city that have been previously unavailable. Leveraging this hybrid serosurveillance approach has strong potential for application beyond this local context and for diseases other than SARS-CoV-2.

Background and ObjectivesTesting strategies for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in school settings are needed to assess the efficacy of infection mitigation strategies and inform school reopening policies. We hypothesized that supervised serial self-collected non-nasopharyngeal testing in summer camp settings would be acceptable and feasible.MethodsWe performed a cohort study at two urban day camps for kindergarten-8th graders in June and July 2020. Eligible participants were campers, up to two adult household contacts, and camp staff. We assessed participation rates for providing, at two time points, supervised, self-collected anterior nares samples for reverse transcription polymerase chain reaction (RT-PCR) and saliva samples for antibody testing. We qualitatively assessed testing feasibility and adherence to stated camp infection mitigation strategies.Results76% (186/246) of eligible participants consented. The cohort completing both rounds of testing (n=163) comprised 67 campers, 76 household contacts, and 20 staff. Among those present, 100% of campers and staff completed test collection at both time points. Testing was feasible to implement, including staff participation supervising camper test collection. No virus was detected by RT-PCR; seven participants had antibodies. Observed adherence to stated camp mitigation policies for masking, physical distancing, and stable cohorting was generally high.ConclusionsSupervised, self-collected serial anterior nasal and saliva-based SARS-CoV-2 testing was acceptable, with successful repeated participation by children ages 5-14. This strategy for testing and the observed infection mitigation practices comprise potential core components for safe school reopening.

Author(s): Appa, Ayesha; Takahashi, Saki; Rodriguez-Barraquer, Isabel; Chamie, Gabriel; Sawyer, Aenor; Duarte, Elias; Hakim, Jill; Turcios, Keirstinne; Vinden, Joanna; Janson, Owen; Manglik, Aashish; Peluso, Michael J; Deeks, Steven G; Henrich, Timothy J; Torres, Leonel; Rodgers, Mary; Hackett, John; Chiu, Charles; Havlir, Diane; Greenhouse, Bryan | Abstract: BackgroundLimited systematic surveillance for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the early months of the US epidemic curtailed accurate appraisal of transmission intensity. Our objective was to perform case detection of an entire rural community to quantify SARS-CoV-2 transmission using polymerase chain reaction (PCR) and antibody testing.MethodsWe conducted a cross-sectional survey of SARS-CoV-2 infection in the rural town of Bolinas, California (population 1620), 4 weeks after shelter-in-place orders. Participants were tested between April 20 and 24, 2020. Prevalence by PCR and seroprevalence from 2 forms of antibody testing were performed in parallel (Abbott ARCHITECT immunoglobulin [Ig]G and in-house IgG enzyme-linked immunosorbent assay).ResultsOf 1891 participants, 1312 were confirmed Bolinas residents (g80% community ascertainment). Zero participants were PCR positive. Assuming 80% sensitivity, it would have been unlikely to observe these results (P l .05) if there were g3 active infections in the community. Based on antibody results, estimated prevalence of prior infection was 0.16% (95% credible interval [CrI], 0.02%-0.46%). The positive predictive value (PPV) of a positive result on both tests was 99.11% (95% CrI, 95.75%-99.94%), compared with PPV 44.19%-63.32% (95% CrI, 3.25%-98.64%) if 1 test was utilized.ConclusionsFour weeks after shelter-in-place, SARS-CoV-2 infection in a rural Northern California community was extremely rare. In this low-prevalence setting, use of 2 antibody tests increased seroprevalence estimate precision. This was one of the first community-wide studies to successfully implement synchronous PCR and antibody testing, particularly in a rural setting. Widespread testing remains an underpinning of effective disease control in conjunction with consistent uptake of public health measures.

We describe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific T cell responses, soluble markers of inflammation, and antibody levels and neutralization capacity longitudinally in 70 individuals with PCR-confirmed SARS-CoV-2 infection. Participants represent a spectrum of illness and recovery, including some with persistent viral shedding in saliva and many experiencing post-acute sequelae of SARS-CoV-2 infection (PASC). T cell responses remain stable for up to 9 months. Whereas the magnitude of early CD4+ T cell immune responses correlates with severity of initial infection, pre-existing lung disease is independently associated with higher long-term SARS-CoV-2-specific CD8+ T cell responses. Among participants with PASC 4 months following coronavirus disease 2019 (COVID-19) symptom onset, we observe a lower frequency of CD8+ T cells expressing CD107a, a marker of degranulation, in response to Nucleocapsid (N) peptide pool stimulation, and a more rapid decline in the frequency of N-specific interferon-γ-producing CD8+ T cells. Neutralizing antibody levels strongly correlate with SARS-CoV-2-specific CD4+ T cell responses., Graphical abstract, CD4+ and CD8+ T cell responses following natural infection with COVID-19 are stable over 8 months. Individuals with PASC demonstrate a lower frequency of CD8+ T cells expressing CD107a, a marker of degranulation, and a more rapid decline in the frequency of N-specific interferon-γ-producing CD8+ T cells.