Analysis and comparison of SARS-CoV-2 variant antibodies and neutralizing activity for 6 months after a booster mRNA vaccine in a healthcare worker population (preprint)

In the context of recurrent surges of SARS-CoV-2 infections, a detailed characterization of antibody persistence over a 6-month period following vaccine booster dose is necessary to crafting effective public health policies on repeat vaccination. To characterize the SARS-CoV-2 antibody profile of a healthcare worker population over a 6-month period following mRNA vaccination and booster dose. 323 healthcare workers at an academic medical center in Orange County, California who had completed primary vaccination and booster dose against SARS-CoV-2 were recruited for the study. A total of 690 blood specimens over a 6-month period were collected via finger-stick blood and analyzed for the presence of antibodies against 9 SARS-CoV-2 antigens using a coronavirus antigen microarray. The primary outcome of this study was the average SARS-CoV-2 antibody level as measured using a novel coronavirus antigen microarray. Additional outcomes measured include levels of antibodies specific to SARS-CoV-2 variants including Delta, Omicron BA.1, and BA.2. We also measured SARS-CoV-2 neutralization capacity for a subset of the population to confirm correlation with antibody levels. Although antibodies against SARS-CoV-2 wane throughout the 6-month period following a booster dose, antibody levels remain higher than pre-boost levels. However, a booster dose of vaccine generates approximately 3-fold lower antibody reactivity against Omicron variants BA.1 and BA.2 as compared to the original Wuhan strain.  Despite waning antibody levels, neutralization activity against the original Wuhan strain is maintained throughout the 6-month period. In the context of recurrent surges of SARS-CoV-2 infections despite vaccination with booster doses, our data indicate that breakthrough infections are likely driven by novel variants with different antibody specificity and not by time since last dose of vaccination, indicating that development of vaccinations specific to these novel variants is necessary to prevent future surges of SARS-CoV-2 infections.

A More Accurate Measurement of the Burden of COVID-19 Hospitalizations (preprint)

COVID-19 hospitalizations are a key indicator of the SARS-CoV-2 pandemic. The US Centers for Disease Prevention and Control describes oxygen supplementation as a measure of severe disease. SARS-CoV-2 PCR positive patients hospitalized without hypoxia or requiring oxygen may have been identified incidentally due to routine screening practices. We describe the application of a revised case definition for COVID-19 hospitalization based on the case-patient oxygen requirement on admission. Using data collected from consecutive SARS-CoV-2 PCR positive hospital admissions in December 2021 and January 2022 at a large safety net hospital in Los Angeles County, we highlight differences between patients hospitalized with COVID-19 (i.e., no oxygen requirement on admission or `incidental` infection) and those hospitalized for COVID-19 (i.e., oxygen requirement on admission). We conducted multivariable modeling to determine the effect of age as a positive predictor of COVID-19 hospitalization and vaccination or prior infection as a negative predictor. The revised case-definition resulted in a substantial decrease in the number of COVID-19 hospitalizations during the study period: 67.5% of SARS-CoV-2 PCR positive hospital admissions were not for COVID-19 but with COVID-19. A revised case-definition for COVID-19 hospitalization that includes the oxygen requirement on admission is needed to more accurately monitor the pandemic and inform public health policy.

Infection Prevention Strategies in COVID-19 Units Highly Protective While Primary Risks to Healthcare Professionals Come From Coworkers and the Community (preprint)

Background: Early evaluations of healthcare professional (HCP) COVID-19 risk occurred during insufficient personal protective equipment and disproportionate testing, contributing to perceptions of high patient-care related HCP risk. We evaluated HCP COVID-19 seropositivity after accounting for community factors and coworker outbreaks.Methods: Prior to universal masking, we conducted a single-center retrospective cohort plus cross-sectional study. All HCP 1) seen by Occupational Health for COVID-like symptoms (regardless of test result) or assigned to 2) dedicated COVID-19 units, 3) units with a COVID-19 HCP outbreak, or 4) control units from 01/01/2020-04/15/2020 were offered serologic testing by an FDA-authorized assay plus a research assay against 67 respiratory viruses, including 11 SARS-CoV-2 antigens. Multivariable models assessed the association of demographics, job role, comorbidities, care of a COVID-19 patient, and geocoded socioeconomic status with positive serology.Results: Of 654 participants, 87 (13.3%) were seropositive; among these 60.8% (N=52) had never cared for a COVID-19 patient. Being male (OR 1.79, CI 1.05-3.04, p=0.03), working in a HCP-outbreak unit (OR 2.21, CI 1.28-3.81, p<0.01), living in a community with low owner-occupied housing (OR=1.63, CI=1.00-2.64, p=0.05), and ethnically Latino (OR 2.10, CI 1.12-3.96, p=0.02) were positively-associated with COVID-19 seropositivity, while working in dedicated COVID-19 units was negatively-associated (OR 0.53, CI=0.30-0.94, p=0.03). The research assay identified 25 additional seropositive individuals (78 [12%] vs. 53 [8%], p<0.01).Conclusions: Prior to universal masking, HCP COVID-19 risk was dominated by workplace and community exposures while working in a dedicated COVID-19 unit was protective, suggesting that infection prevention protocols prevent patient-to-HCP transmission.

Substantial Differences in SARS-CoV-2 Antibody Responses Elicited by Natural Infection and mRNA Vaccination (preprint)

We analyzed data from two ongoing serologic surveys, a longitudinal cohort of health care workers (HCW) from the University of California Irvine Medical Center (Orange County, CA, USA), collected from May and December 2020 through March 2021, and a cross sectional county-wide study in July 2020 (actOC; Orange County, CA) and a more focused community study in the city of Santa Ana (Santa Ana Cares; Orange County, CA, USA), collected in December 2020 - in order to compare the antibody responses to SARS-CoV-2 natural infection and vaccination. In addition, we serially tested 9 volunteers at multiple time points to analyze the time course of vaccine-induced antibody response in more detail. In May 2020, 1060 HCW were enrolled and had finger stick samples collected. Finger stick samples were again collected in December 2020, before vaccination, as well as January, February and March 2021 during vaccination campaign. A total of 8,729 finger stick blood specimens were probed and analyzed for IgG and IgM antibodies using a coronavirus antigen microarray (COVAM). The microarray contained 10 SARS-CoV-2 antigens including nucleocapid protein (NP) and several varying fragments of the spike protein, as well as 4 SARS, 3 MERS, 12 Common CoV, and 8 Influenza antigens.Based on a random forest based prediction algorithm, between May and December, prior to vaccine rollout, we observed that seropositivity in the HCW cohort increased from 4.5% to 13%. An intensive vaccination campaign with mRNA vaccines was initiated on December 16, 2020 and 6,724 healthcare workers were vaccinated within 3 weeks. The observed seropositivity of the HCW specimens taken in the last week of January 2021 jumped to 78%, and by the last week in February it reached 93%, and peaked at 98% seropositive in March. The antibody profile induced by natural exposure differed from the profile induced after mRNA vaccination. Messenger RNA vaccines induced elevated antibody (Ab) reactivity levels against the Receptor Binding Domain (RBD) domain of SARS-CoV-2 spike, and cross-reactive responses against SARS and MERS RBD domains. Nucleocapsid protein (NP), which is an immunodominant antigen induced after natural exposure, is not present in the vaccine and can be used as a biomarker of past exposure. The results show that naturally-exposed individuals mount a stronger anti-spike response upon vaccination than individuals that were not previously exposed. Longitudinal specimens taken at approximately weekly intervals from 9 individuals show variation in the response to the mRNA vaccine, with some showing a vigorous response to the first dose (prime) and others requiring a subsequent dose (boost) to reach high anti-SARS-CoV-2 levels. Antibody titers determined by serial dilution of the specimens were used to accurately compare antibody levels in these samples. mRNA vaccinees after the boost have higher Ab titers (up to 10 times higher) than convalescent plasmas from donors who recovered from natural infection. The results of this study exemplify the time course and outcomes expected from similar mRNA mass vaccination campaigns conducted in other institutions.

Risk Factors for SARS-CoV-2 Seropositivity in a Health Care Worker Population (preprint)

Background Protecting health care workers (HCWs) during the coronavirus disease 2019 (COVID-19) pandemic is essential. Serologic testing can identify HCWs who had minimally symptomatic severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infections that were missed by occupational screening based on daily symptom and temperature checks. Recent studies report conflicting results regarding the impact of occupational factors on SARS-CoV-2 seropositivity amongst HCWs. Methods The study population included all hospital workers at an academic medical center in Orange County, California. SARS-CoV-2 seropositivity was assessed from a fingerstick blood specimen using a coronavirus antigen microarray, which compares IgM and IgG antibodies against a panel of SARS-CoV-2 antigens with positive and negative controls to identify prior SARS-CoV-2 infection with 98% specificity and 93% sensitivity. Demographic, occupational, and clinical factors were surveyed and their effect on seropositivity estimated using multivariable logistic regression analysis. Results Amongst 1,557 HCWs with complete data, SARS-CoV-2 seropositivity was 10.8%. Risk factors for increased seropositivity included male gender, exposure to COVID-19 outside of work, working in food or environmental services, and working in COVID-19 units. Amongst the 1,103 HCW who were seropositive but missed by occupational screening, additional risk factors included younger age and working in administration. Conclusions SARS-CoV-2 seropositivity is significantly higher than reported case counts even amongst HCWs who are meticulously screened. Seropositive HCWs missed by occupational screening were more likely to be younger, work roles without direct patient care, or have COVID-19 exposure outside of work. Key Points SARS-CoV-2 seropositivity risk factors amongst health care workers included male gender, nonoccupational exposure, food or environmental services role, and COVID-19 unit location. Those missed by occupational screening were younger, in roles without direct patient care, or exposed outside of work.

Estimated Seroprevalence of SARS-CoV-2 Antibodies Among Adults in Orange County, California (preprint)

BackgroundClinic-based estimates of SARS-CoV-2 may considerably underestimate the total number of infections. Access to testing in the US has been heterogeneous and symptoms vary widely in infected persons. Public health surveillance efforts and metrics are therefore hampered by underreporting. We set out to provide a minimally biased estimate of SARS-CoV-2 seroprevalence among adults for a large and diverse county (Orange County, CA, population 3.2 million). MethodsWe implemented a surveillance study that minimizes response bias by recruiting adults to answer a survey without knowledge of later being offered a SARS-CoV-2 test. Several methodologies were used to retrieve a population-representative sample. Participants (n=2,979) visited one of 11 drive-thru test sites from July 10th to August 16th, 2020 (or received an in-home visit) to provide a finger pin-prick sample. We applied a robust SARS-CoV-2 Antigen Microarray technology, which has superior measurement validity relative to FDA-approved tests. FindingsParticipants include a broad age, gender, racial/ethnic, and income representation. Adjusted seroprevalence of SARS-CoV-2 infection was 11.5% (95% CI: 10.5% to 12.4%). Formal bias analyses produced similar results. Prevalence was elevated among Hispanics (vs. other non-Hispanic: prevalence ratio [PR]= 1.47, 95% CI: 1.22 to 1.78) and household income $100,000: PR= 1.42, 95% CI: 1.14 to 1.79). InterpretationResults from a diverse population using a highly specific and sensitive microarray indicate a SARS-CoV-2 seroprevalence of [~]12 percent. This population-based seroprevalence is seven-fold greater than that using official County statistics. In this region, SARS-CoV-2 also disproportionately affects Hispanic and low-income adults. FundingOrange County Healthcare Agency

Distinct SARS-CoV-2 Antibody Reactivity Patterns in Coronavirus Convalescent Plasma Revealed by a Coronavirus Antigen Microarray (preprint)

A coronavirus antigen microarray (COVAM) was constructed containing 11 SARS-CoV-2, 5 SARS-1, 5 MERS, and 12 seasonal coronavirus recombinant proteins. The array is designed to measure immunoglobulin isotype and subtype levels in serum or plasma samples against each of the individual antigens printed on the array. We probed the COVAM with COVID-19 convalescent plasma (CCP) collected from 99 donors who recovered from a PCR+ confirmed SARS-CoV-2 infection. The results were analyzed using two computational approaches, a generalized linear model (glm) and Random Forest (RF) prediction model, to classify individual specimens as either Reactive or Non-Reactive against the SARS-CoV-2 antigens. A training set of 88 pre-COVID-19 specimens (PreCoV) collected in August 2019 and102 positive specimens from SARS-CoV-2 PCR+ confirmed COVID-19 cases was used for these analyses. Results compared with an FDA emergency use authorized (EUA) SARS-CoV2 S1-based total Ig chemiluminescence immunoassay (Ortho Clinical Diagnostics VITROS(R) Anti-SARS-CoV-2 Total, CoV2T) and with a SARS-CoV-2 S1-S2 spike-based pseudovirus micro neutralization assay (SARS-CoV-2 reporter viral particle neutralization titration (RVPNT) showed high concordance between the 3 assays. Three CCP specimens that were negative by the VITROS CoV2T immunoassay were also negative by both COVAM and the RVPNT assay. Concordance between VITROS CoV2T and COVAM was 96%, VITROS CoV2T and RVPNT 93%, and RVPNT and COVAM 95%. The discordances were all weakly reactive samples near the cutoff threshold of the VITROS CoV2T immunoassay. The multiplex COVAM allows CCP to be grouped according to antibody reactivity patterns against 11 SARS-CoV-2 antigens. Unsupervised K-means analysis, via the gap statistics, as well as hierarchical clustering analysis revealed 3 main clusters with distinct reactivity intensities and patterns. These patterns were not recapitulated by adjusting the VITROS CoV2T or RVPNT assay thresholds. Plasma classified according to these reactivity patterns may be better associated with CCP treatment efficacy than antibody levels alone. The use of a SARS-CoV-2 antigen array may be useful to qualify CCP for administration as a treatment for acute COVID-19 and to interrogate vaccine immunogenicity and performance in preclinical and clinical studies to understand and recapitulate antibody responses associated with protection from infection and disease.

A Modular Microarray Imaging System for Highly Specific COVID-19 Antibody Testing (preprint)

To detect the presence of antibodies in blood against SARS-CoV-2 in a highly sensitive and specific manner, here we describe a robust, inexpensive ($200), 3D-printable portable imaging platform (TinyArray imager) that can be deployed immediately in areas with minimal infrastructure to read coronavirus antigen microarrays (CoVAMs) that contain a panel of antigens from SARS-CoV-2, SARS-1, MERS, and other respiratory viruses. Application includes basic laboratories and makeshift field clinics where a few drops of blood from a finger prick could be rapidly tested in parallel for the presence of antibodies to SARS-CoV-2 with a test turnaround time of only 2-4 h. To evaluate our imaging device, we probed and imaged coronavirus microarrays with COVID-19-positive and negative sera and achieved a performance on par with a commercial microarray reader 100x more expensive than our imaging device. This work will enable large scale serosurveillance, which can play an important role in the months and years to come to implement efficient containment and mitigation measures, as well as help develop therapeutics and vaccines to treat and prevent the spread of COVID-19.

Development and External Validation of a Prognostic Tool for COVID-19 Critical Disease (preprint)

Background: The rapid spread of coronavirus disease 2019 (COVID-19) revealed significant constraints in critical care capacity. In anticipation of subsequent waves, reliable prediction of disease severity is essential for critical care capacity management and may enable earlier targeted interventions to improve patient outcomes. The purpose of this study is to develop and externally validate a prognostic model/clinical tool for predicting COVID-19 critical disease at presentation to medical care. Methods: This is a retrospective study of a prognostic model for the prediction of COVID-19 critical disease where critical disease was defined as ICU admission, ventilation, and/or death. The derivation cohort was used to develop a multivariable logistic regression model. Covariates included patient comorbidities, presenting vital signs, and laboratory values. Model performance was assessed on the validation cohort by concordance statistics. The model was developed with consecutive patients with COVID-19 who presented to University of California Irvine Medical Center in Orange County, California. External validation was performed with a random sample of patients with COVID-19 at Emory Healthcare in Atlanta, Georgia. Results: Of a total 3208 patients tested in the derivation cohort, 9% (299/3028) were positive for COVID-19. Clinical data including past medical history and presenting laboratory values were available for 29% (87/299) of patients (median age, 48 years [range, 21-88 years]; 64% [36/55] male). The most common comorbidities included obesity (37%, 31/87), hypertension (37%, 32/87), and diabetes (24%, 24/87). Critical disease was present in 24% (21/87). After backward stepwise selection, the following factors were associated with greatest increased risk of critical disease: number of comorbidities, body mass index, respiratory rate, white blood cell count, % lymphocytes, serum creatinine, lactate dehydrogenase, high sensitivity troponin I, ferritin, procalcitonin, and C-reactive protein. Of a total of 40 patients in the validation cohort (median age, 60 years [range, 27-88 years]; 55% [22/40] male), critical disease was present in 65% (26/40). Model discrimination in the validation cohort was high (concordance statistic: 0.94, 95% confidence interval 0.87-1.01). A web-based tool was developed to enable clinicians to input patient data and view likelihood of critical disease. Conclusions and Relevance: We present a model which accurately predicted COVID-19 critical disease risk using comorbidities and presenting vital signs and laboratory values, on derivation and validation cohorts from two different institutions. If further validated on additional cohorts of patients, this model/clinical tool may provide useful prognostication of critical care needs.

The disproportionate rise in COVID-19 cases among Hispanic/Latinx in disadvantaged communities of Orange County, California: A socioeconomic case-series (preprint)

Background: Recent epidemiological evidence has demonstrated a higher rate of COVID-19 hospitalizations and deaths among minorities. This pattern of race-ethnic disparities emerging throughout the United States raises the question of what social factors may influence spread of a highly transmissible novel coronavirus. The purpose of this study is to describe race-ethnic and socioeconomic disparities associated with COVID-19 in patients in our community in Orange County, California and understand the role of individual-level factors, neighborhood-level factors, and access to care on outcomes. Methods: This is a case-series of COVID-19 patients from the University of California, Irvine (UCI) across six-weeks between 3/12/2020 and 4/22/2020. Note, California's shelter-in-place order began on 3/19/2020. Individual-level factors included race-ethnicity status were recorded. Neighborhood-level factors from census tracts included median household income, mean household size, proportion without a college degree, proportion working from home, and proportion without health insurance were also recorded. Results: A total of 210-patients tested were COVID-19 positive, of which 73.3% (154/210) resided in Orange County. Hispanic/Latinx patients residing in census tracts below the median income demonstrated exponential growth (rate = 55.9%, R2 = 0.9742) during the study period. In addition, there was a significant difference for both race-ethnic (p < 0.001) and income bracket (p = 0.001) distributions prior to and after California's shelter-in-place. In addition, the percentage of individuals residing in neighborhoods with denser households (p = 0.046), lower levels of college graduation (p < 0.001), health insurance coverage (p = 0.01), and ability to work from home (p < 0.001) significantly increased over the same timeframe. Conclusions and Relevance: Our study examines the race-ethnic disparities in Orange County, CA, and highlights vulnerable populations that are at increased risk for contracting COVID-19. Our descriptive case series illustrates that we also need to consider socioeconomic factors, which ultimately set the stage for biological and social disparities.

Analysis of SARS-CoV-2 Antibodies in COVID-19 Convalescent Plasma using a Coronavirus Antigen Microarray (preprint)

The current practice for diagnosis of COVID-19, based on SARS-CoV-2 PCR testing of pharyngeal or respiratory specimens in a symptomatic patient at high epidemiologic risk, likely underestimates the true prevalence of infection. Serologic methods can more accurately estimate the disease burden by detecting infections missed by the limited testing performed to date. Here, we describe the validation of a coronavirus antigen microarray containing immunologically significant antigens from SARS-CoV-2, in addition to SARS-CoV, MERS-CoV, common human coronavirus strains, and other common respiratory viruses. A comparison of antibody profiles detected on the array from control sera collected prior to the SARS-CoV-2 pandemic versus convalescent blood specimens from virologically confirmed COVID-19 cases demonstrates near complete discrimination of these two groups, with improved performance from use of antigen combinations that include both spike protein and nucleoprotein. This array can be used as a diagnostic tool, as an epidemiologic tool to more accurately estimate the disease burden of COVID-19, and as a research tool to correlate antibody responses with clinical outcomes.

Analysis of Serologic Cross-Reactivity Between Common Human Coronaviruses and SARS-CoV-2 Using Coronavirus Antigen Microarray (preprint)

The current practice for diagnosis of SARS-CoV-2 infection relies on PCR testing of nasopharyngeal or respiratory specimens in a symptomatic patient at high epidemiologic risk. This testing strategy likely underestimates the true prevalence of infection, creating the need for serologic methods to detect infections missed by the limited testing to date. Here, we describe the development of a coronavirus antigen microarray containing immunologically significant antigens from SARS-CoV-2, in addition to SARS-CoV, MERS-CoV, common human coronavirus strains, and other common respiratory viruses. A preliminary study of human sera collected prior to the SARS-CoV-2 pandemic demonstrates overall high IgG reactivity to common human coronaviruses and low IgG reactivity to epidemic coronaviruses including SARS-CoV-2, with some cross-reactivity of conserved antigenic domains including S2 domain of spike protein and nucleocapsid protein. This array can be used to answer outstanding questions regarding SARS-CoV-2 infection, including whether baseline serology for other coronaviruses impacts disease course, how the antibody response to infection develops over time, and what antigens would be optimal for vaccine development.