Estimated seroprevalence of SARS-CoV-2 antibodies among adults in Orange County, California

Machine Learning Classification of Time since BNT162b2 COVID-19 Vaccination Based on Array-Measured Antibody Activity

Vaccines trigger an immunological response that includes B and T cells, with B cells producing antibodies. SARS-CoV-2 immunity weakens over time after vaccination. Discovering key changes in antigen-reactive antibodies over time after vaccination could help improve vaccine efficiency. In this study, we collected data on blood antibody levels in a cohort of healthcare workers vaccinated for COVID-19 and obtained 73 antigens in samples from four groups according to the duration after vaccination, including 104 unvaccinated healthcare workers, 534 healthcare workers within 60 days after vaccination, 594 healthcare workers between 60 and 180 days after vaccination, and 141 healthcare workers over 180 days after vaccination. Our work was a reanalysis of the data originally collected at Irvine University. This data was obtained in Orange County, California, USA, with the collection process commencing in December 2020. British variant (B.1.1.7), South African variant (B.1.351), and Brazilian/Japanese variant (P.1) were the most prevalent strains during the sampling period. An efficient machine learning based framework containing four feature selection methods (least absolute shrinkage and selection operator, light gradient boosting machine, Monte Carlo feature selection, and maximum relevance minimum redundancy) and four classification algorithms (decision tree, k-nearest neighbor, random forest, and support vector machine) was designed to select essential antibodies against specific antigens. Several efficient classifiers with a weighted F1 value around 0.75 were constructed. The antigen microarray used for identifying antibody levels in the coronavirus features ten distinct SARS-CoV-2 antigens, comprising various segments of both nucleocapsid protein (NP) and spike protein (S). This study revealed that S1 + S2, S1.mFcTag, S1.HisTag, S1, S2, Spike.RBD.His.Bac, Spike.RBD.rFc, and S1.RBD.mFc were most highly ranked among all features, where S1 and S2 are the subunits of Spike, and the suffixes represent the tagging information of different recombinant proteins. Meanwhile, the classification rules were obtained from the optimal decision tree to explain quantitatively the roles of antigens in the classification. This study identified antibodies associated with decreased clinical immunity based on populations with different time spans after vaccination. These antibodies have important implications for maintaining long-term immunity to SARS-CoV-2.

Risk factors for SARS-CoV-2 seropositivity in a health care worker population during the early pandemic

BACKGROUND

While others have reported severe acute respiratory syndrome-related coronavirus 2(SARS-CoV-2) seroprevalence studies in health care workers (HCWs), we leverage the use of a highly sensitive coronavirus antigen microarray to identify a group of seropositive health care workers who were missed by daily symptom screening that was instituted prior to any epidemiologically significant local outbreak. Given that most health care facilities rely on daily symptom screening as the primary method to identify SARS-CoV-2 among health care workers, here, we aim to determine how demographic, occupational, and clinical variables influence SARS-CoV-2 seropositivity among health care workers.

METHODS

We designed a cross-sectional survey of HCWs for SARS-CoV-2 seropositivity conducted from May 15th to June 30th 2020 at a 418-bed academic hospital in Orange County, California. From an eligible population of 5,349 HCWs, study participants were recruited in two ways: an open cohort, and a targeted cohort. The open cohort was open to anyone, whereas the targeted cohort that recruited HCWs previously screened for COVID-19 or work in high-risk units. A total of 1,557 HCWs completed the survey and provided specimens, including 1,044 in the open cohort and 513 in the targeted cohort. Demographic, occupational, and clinical variables were surveyed electronically. SARS-CoV-2 seropositivity was assessed using a coronavirus antigen microarray (CoVAM), which measures antibodies against eleven viral antigens to identify prior infection with 98% specificity and 93% sensitivity.

RESULTS

Among tested HCWs (n = 1,557), SARS-CoV-2 seropositivity was 10.8%, and risk factors included male gender (OR 1.48, 95% CI 1.05-2.06), exposure to COVID-19 outside of work (2.29, 1.14-4.29), working in food or environmental services (4.85, 1.51-14.85), and working in COVID-19 units (ICU: 2.28, 1.29-3.96; ward: 1.59, 1.01-2.48). Amongst 1,103 HCWs not previously screened, seropositivity was 8.0%, and additional risk factors included younger age (1.57, 1.00-2.45) and working in administration (2.69, 1.10-7.10).

CONCLUSION

SARS-CoV-2 seropositivity is significantly higher than reported case counts even among HCWs who are meticulously screened. Seropositive HCWs missed by screening were more likely to be younger, work outside direct patient care, or have exposure outside of work.

Accounting for assay performance when estimating the temporal dynamics in SARS-CoV-2 seroprevalence in the U.S

Reconstructing the incidence of SARS-CoV-2 infection is central to understanding the state of the pandemic. Seroprevalence studies are often used to assess cumulative infections as they can identify asymptomatic infection. Since July 2020, commercial laboratories have conducted nationwide serosurveys for the U.S. CDC. They employed three assays, with different sensitivities and specificities, potentially introducing biases in seroprevalence estimates. Using models, we show that accounting for assays explains some of the observed state-to-state variation in seroprevalence, and when integrating case and death surveillance data, we show that when using the Abbott assay, estimates of proportions infected can differ substantially from seroprevalence estimates. We also found that states with higher proportions infected (before or after vaccination) had lower vaccination coverages, a pattern corroborated using a separate dataset. Finally, to understand vaccination rates relative to the increase in cases, we estimated the proportions of the population that received a vaccine prior to infection.

Semi-parametric modeling of SARS-CoV-2 transmission using tests, cases, deaths, and seroprevalence data

Mechanistic models fit to streaming surveillance data are critical to understanding the transmission dynamics of an outbreak as it unfolds in real-time. However, transmission model parameter estimation can be imprecise, and sometimes even impossible, because surveillance data are noisy and not informative about all aspects of the mechanistic model. To partially overcome this obstacle, Bayesian models have been proposed to integrate multiple surveillance data streams. We devised a modeling framework for integrating SARS-CoV-2 diagnostics test and mortality time series data, as well as seroprevalence data from cross-sectional studies, and tested the importance of individual data streams for both inference and forecasting. Importantly, our model for incidence data accounts for changes in the total number of tests performed. We model the transmission rate, infection-to-fatality ratio, and a parameter controlling a functional relationship between the true case incidence and the fraction of positive tests as time-varying quantities and estimate changes of these parameters nonparametrically. We compare our base model against modified versions which do not use diagnostics test counts or seroprevalence data to demonstrate the utility of including these often unused data streams. We apply our Bayesian data integration method to COVID-19 surveillance data collected in Orange County, California between March 2020 and February 2021 and find that 32-72% of the Orange County residents experienced SARS-CoV-2 infection by mid-January, 2021. Despite this high number of infections, our results suggest that the abrupt end of the winter surge in January 2021 was due to both behavioral changes and a high level of accumulated natural immunity.

Ethnic inequalities in COVID-19 infection, hospitalisation, intensive care admission, and death: a global systematic review and meta-analysis of over 200 million study participants

Background

COVID-19 has exacerbated existing ethnic inequalities in health. Little is known about whether inequalities in severe disease and deaths, observed globally among minoritised ethnic groups, relates to greater infection risk, poorer prognosis, or both. We analysed global data on COVID-19 clinical outcomes examining inequalities between people from minoritised ethnic groups compared to the ethnic majority group.

Methods

Databases (MEDLINE, EMBASE, EMCARE, CINAHL, Cochrane Library) were searched from 1st December 2019 to 3rd October 2022, for studies reporting original clinical data for COVID-19 outcomes disaggregated by ethnicity: infection, hospitalisation, intensive care unit (ICU) admission, and mortality. We assessed inequalities in incidence and prognosis using random-effects meta-analyses, with Grading of Recommendations Assessment, Development, and Evaluation (GRADE) use to assess certainty of findings. Meta-regressions explored the impact of region and time-frame (vaccine roll-out) on heterogeneity. PROSPERO: CRD42021284981.

Findings

77 studies comprising over 200,000,000 participants were included. Compared with White majority populations, we observed an increased risk of testing positive for infection for people from Black (adjusted Risk Ratio [aRR]:1.78, 95% CI:1.59-1.99, I2 = 99.1), South Asian (aRR:3.00, 95% CI:1.59-5.66, I2 = 99.1), Mixed (aRR:1.64, 95% CI:1.02-1.67, I2 = 93.2) and Other ethnic groups (aRR:1.36, 95% CI:1.01-1.82, I2 = 85.6). Black, Hispanic, and South Asian people were more likely to be seropositive. Among population-based studies, Black and Hispanic ethnic groups and Indigenous peoples had an increased risk of hospitalisation; Black, Hispanic, South Asian, East Asian and Mixed ethnic groups and Indigenous peoples had an increased risk of ICU admission. Mortality risk was increased for Hispanic, Mixed, and Indigenous groups. Smaller differences were seen for prognosis following infection. Following hospitalisation, South Asian, East Asian, Black and Mixed ethnic groups had an increased risk of ICU admission, and mortality risk was greater in Mixed ethnic groups. Certainty of evidence ranged from very low to moderate.

Interpretation

Our study suggests that systematic ethnic inequalities in COVID-19 health outcomes exist, with large differences in exposure risk and some differences in prognosis following hospitalisation. Response and recovery interventions must focus on tackling drivers of ethnic inequalities which increase exposure risk and vulnerabilities to severe disease, including structural racism and racial discrimination.

Funding

ESRC:ES/W000849/1.

SARS-CoV-2 infection during pregnancy and preterm birth in Massachusetts from March 2020 through March 2021

BACKGROUND

SARS-CoV-2 infection during pregnancy has been linked to preterm birth, but this association is not well understood.

OBJECTIVES

To examine the association between SARS-CoV-2 infection and spontaneous and provider-initiated preterm birth (PTB), and how timing of infection, and race/ethnicity as a marker of structural inequality, may modify this association.

METHODS

We conducted a retrospective cohort study among pregnant people who delivered singleton, liveborn infants (22-44 weeks gestation) from 1 March 2020 to 31 March 2021 (n = 68,288). We used Cox proportional hazards models to compare the hazard of PTB between pregnant people with and without laboratory-confirmed SARS-CoV-2 infection during pregnancy. We evaluated this association according to the trimester of infection, timing from infection to birth, and timing of PTB. We also examined the joint associations of SARS-CoV-2 infection and race/ethnicity with PTB using the relative excess risk due to interaction (RERI).

RESULTS

Positive SARS-CoV-2 tests were identified for 2195 pregnant people (3.2%). The prevalence of PTB was 7.2% (3.8% spontaneous, 3.6% provider-initiated). SARS-CoV-2 infection during pregnancy was associated with an increased risk of PTB overall (adjusted hazard ratio [HR] 1.53, 95% confidence interval [CI] 1.34, 1.74), and provider-initiated PTB (HR 1.79, 95% CI 1.50, 2.12) but not spontaneous PTB (HR 1.09, 95% CI 0.89, 1.36). Second trimester infections were associated with an increased risk of provider-initiated PTB, and third trimester infections were associated with an increased risk of both PTB subtypes. A joint inverse association between White non-Hispanic race/ethnicity and SARS-CoV-2 infection and spontaneous PTB (HR 0.56, 95% CI 0.34, 0.94; RERI -0.6, 95% CI -1.0, -0.2) was also observed.

CONCLUSIONS

SARS-CoV-2 infections were primarily associated with an increased risk for provider-initiated PTB in this study. These findings highlight the importance of promoting infection-prevention strategies among pregnant people.

Missing science: A scoping study of COVID-19 epidemiological data in the United States

Systematic approaches to epidemiologic data collection are critical for informing pandemic responses, providing information for the targeting and timing of mitigations, for judging the efficacy and efficiency of alternative response strategies, and for conducting real-world impact assessments. Here, we report on a scoping study to assess the completeness of epidemiological data available for COVID-19 pandemic management in the United States, enumerating authoritative US government estimates of parameters of infectious transmission, infection severity, and disease burden and characterizing the extent and scope of US public health affiliated epidemiological investigations published through November 2021. While we found authoritative estimates for most expected transmission and disease severity parameters, some were lacking, and others had significant uncertainties. Moreover, most transmission parameters were not validated domestically or re-assessed over the course of the pandemic. Publicly available disease surveillance measures did grow appreciably in scope and resolution over time; however, their resolution with regards to specific populations and exposure settings remained limited. We identified 283 published epidemiological reports authored by investigators affiliated with U.S. governmental public health entities. Most reported on descriptive studies. Published analytic studies did not appear to fully respond to knowledge gaps or to provide systematic evidence to support, evaluate or tailor community mitigation strategies. The existence of epidemiological data gaps 18 months after the declaration of the COVID-19 pandemic underscores the need for more timely standardization of data collection practices and for anticipatory research priorities and protocols for emerging infectious disease epidemics.

THE DISTRIBUTIONAL EFFECTS OF COVID-19 AND OPTIMAL MITIGATION POLICIES

This paper develops a quantitative heterogeneous agent-life cycle-epidemiological model that is used to study the aggregate and distributional consequences of COVID-19 and mitigation policies. First, a stay-at-home subsidy is preferred to a lockdown because it reduces deaths by more and output by less. Second, Pareto-improving policies can reduce deaths by nearly 45 percent without any reduction in output relative to no public mitigation. Finally, it is possible to simultaneously improve public health and economic outcomes, suggesting that debates regarding a tradeoff between economic and health objectives may be misguided. This article is protected by copyright. All rights reserved.

Changes in the Relationship Between Income and Life Expectancy Before and During the COVID-19 Pandemic, California, 2015-2021

IMPORTANCE

The COVID-19 pandemic caused a large decrease in US life expectancy in 2020, but whether a similar decrease occurred in 2021 and whether the relationship between income and life expectancy intensified during the pandemic are unclear.

OBJECTIVE

To measure changes in life expectancy in 2020 and 2021 and the relationship between income and life expectancy by race and ethnicity.

DESIGN, SETTING, AND PARTICIPANTS

Retrospective ecological analysis of deaths in California in 2015 to 2021 to calculate state- and census tract-level life expectancy. Tracts were grouped by median household income (MHI), obtained from the American Community Survey, and the slope of the life expectancy-income gradient was compared by year and by racial and ethnic composition.

EXPOSURES

California in 2015 to 2019 (before the COVID-19 pandemic) and 2020 to 2021 (during the COVID-19 pandemic).

MAIN OUTCOMES AND MEASURES

Life expectancy at birth.

RESULTS

California experienced 1 988 606 deaths during 2015 to 2021, including 654 887 in 2020 to 2021. State life expectancy declined from 81.40 years in 2019 to 79.20 years in 2020 and 78.37 years in 2021. MHI data were available for 7962 of 8057 census tracts (98.8%; n = 1 899 065 deaths). Mean MHI ranged from $21 279 to $232 261 between the lowest and highest percentiles. The slope of the relationship between life expectancy and MHI increased significantly, from 0.075 (95% CI, 0.07-0.08) years per percentile in 2019 to 0.103 (95% CI, 0.098-0.108; P < .001) years per percentile in 2020 and 0.107 (95% CI, 0.102-0.112; P < .001) years per percentile in 2021. The gap in life expectancy between the richest and poorest percentiles increased from 11.52 years in 2019 to 14.67 years in 2020 and 15.51 years in 2021. Among Hispanic and non-Hispanic Asian, Black, and White populations, life expectancy declined 5.74 years among the Hispanic population, 3.04 years among the non-Hispanic Asian population, 3.84 years among the non-Hispanic Black population, and 1.90 years among the non-Hispanic White population between 2019 and 2021. The income-life expectancy gradient in these groups increased significantly between 2019 and 2020 (0.038 [95% CI, 0.030-0.045; P < .001] years per percentile among Hispanic individuals; 0.024 [95% CI: 0.005-0.044; P = .02] years per percentile among Asian individuals; 0.015 [95% CI, 0.010-0.020; P < .001] years per percentile among Black individuals; and 0.011 [95% CI, 0.007-0.015; P < .001] years per percentile among White individuals) and between 2019 and 2021 (0.033 [95% CI, 0.026-0.040; P < .001] years per percentile among Hispanic individuals; 0.024 [95% CI, 0.010-0.038; P = .002] years among Asian individuals; 0.024 [95% CI, 0.011-0.037; P = .003] years per percentile among Black individuals; and 0.013 [95% CI, 0.008-0.018; P < .001] years per percentile among White individuals). The increase in the gradient was significantly greater among Hispanic vs White populations in 2020 and 2021 (P < .001 in both years) and among Black vs White populations in 2021 (P = .04).

CONCLUSIONS AND RELEVANCE

This retrospective analysis of census tract-level income and mortality data in California from 2015 to 2021 demonstrated a decrease in life expectancy in both 2020 and 2021 and an increase in the life expectancy gap by income level relative to the prepandemic period that disproportionately affected some racial and ethnic minority populations. Inferences at the individual level are limited by the ecological nature of the study, and the generalizability of the findings outside of California are unknown.

Serology as a Tool to Assess Infectious Disease Landscapes and Guide Public Health Policy

Understanding the local burden and epidemiology of infectious diseases is crucial to guide public health policy and prioritize interventions. Typically, infectious disease surveillance relies on capturing clinical cases within a healthcare system, classifying cases by etiology and enumerating cases over a period of time. Disease burden is often then extrapolated to the general population. Serology (i.e., examining serum for the presence of pathogen-specific antibodies) has long been used to inform about individuals past exposure and immunity to specific pathogens. However, it has been underutilized as a tool to evaluate the infectious disease burden landscape at the population level and guide public health decisions. In this review, we outline how serology provides a powerful tool to complement case-based surveillance for determining disease burden and epidemiology of infectious diseases, highlighting its benefits and limitations. We describe the current serology-based technologies and illustrate their use with examples from both the pre- and post- COVID-19-pandemic context. In particular, we review the challenges to and opportunities in implementing serological surveillance in low- and middle-income countries (LMICs), which bear the brunt of the global infectious disease burden. Finally, we discuss the relevance of serology data for public health decision-making and describe scenarios in which this data could be used, either independently or in conjunction with case-based surveillance. We conclude that public health systems would greatly benefit from the inclusion of serology to supplement and strengthen existing case-based infectious disease surveillance strategies.

Effect of socioeconomic factors during the early COVID-19 pandemic: a spatial analysis

Background

Spatial variability of COVID-19 cases may suggest geographic disparities of social determinants of health. Spatial analyses of population-level data may provide insight on factors that may contribute to COVID-19 transmission, hospitalization, and death.

Methods

Generalized additive models were used to map COVID-19 risk from March 2020 to February 2021 in Orange County (OC), California. We geocoded and analyzed 221,843 cases to OC census tracts within a Poisson framework while smoothing over census tract centroids. Location was randomly permuted 1000 times to test for randomness. We also separated the analyses temporally to observe if risk changed over time. COVID-19 cases, hospitalizations, and deaths were mapped across OC while adjusting for population-level demographic data in crude and adjusted models.

Results

Risk for COVID-19 cases, hospitalizations, and deaths were statistically significant in northern OC. Adjustment for demographic data substantially decreased spatial risk, but areas remained statistically significant. Inclusion of location within our models considerably decreased the magnitude of risk compared to univariate models. However, percent minority (adjusted RR: 1.06, 95%CI: 1.06, 1.07), average household size (aRR: 1.06, 95%CI: 1.05, 1.07), and percent service industry (aRR: 1.05, 95%CI: 1.04, 1.06) remained significantly associated with COVID-19 risk in adjusted spatial models. In addition, areas of risk did not change between surges and risk ratios were similar for hospitalizations and deaths.

Conclusion

Significant risk factors and areas of increased risk were identified in OC in our adjusted models and suggests that social and environmental factors contribute to the spread of COVID-19 within communities. Areas in north OC remained significant despite adjustment, but risk substantially decreased. Additional investigation of risk factors may provide insight on how to protect vulnerable populations in future infectious disease outbreaks.

Risk factors for SARS-CoV-2 seroprevalence following the first pandemic wave in UK healthcare workers in a large NHS Foundation Trust

Background: We aimed to measure SARS-CoV-2 seroprevalence in a cohort of healthcare workers (HCWs) during the first UK wave of the COVID-19 pandemic, explore risk factors associated with infection, and investigate the impact of antibody titres on assay sensitivity. Methods: HCWs at Sheffield Teaching Hospitals NHS Foundation Trust were prospectively enrolled and sampled at two time points. We developed an in-house ELISA for testing participant serum for SARS-CoV-2 IgG and IgA reactivity against Spike and Nucleoprotein. Data were analysed using three statistical models: a seroprevalence model, an antibody kinetics model, and a heterogeneous sensitivity model. Results: Our in-house assay had a sensitivity of 99·47% and specificity of 99·56%. We found that 24·4% (n=311/1275) of HCWs were seropositive as of 12th June 2020. Of these, 39·2% (n=122/311) were asymptomatic. The highest adjusted seroprevalence was measured in HCWs on the Acute Medical Unit (41·1%, 95% CrI 30·0-52·9) and in Physiotherapists and Occupational Therapists (39·2%, 95% CrI 24·4-56·5). Older age groups showed overall higher median antibody titres. Further modelling suggests that, for a serological assay with an overall sensitivity of 80%, antibody titres may be markedly affected by differences in age, with sensitivity estimates of 89% in those over 60 years but 61% in those ≤30 years. Conclusions:  HCWs in acute medical units and those working closely with COVID-19 patients were at highest risk of infection, though whether these are infections acquired from patients or other staff is unknown. Current serological assays may underestimate seroprevalence in younger age groups if validated using sera from older and/or more severe COVID-19 cases.

State-wide random seroprevalence survey of SARS-CoV-2 past infection in a southern US State, 2020

The purpose of this cross-sectional study was to estimate the proportion of Arkansas residents who were infected with the SARS-CoV-2 virus between May and December 2020 and to assess the determinants of infection. To estimate seroprevalence, a state-wide population-based random-digit dial sample of non-institutionalized adults in Arkansas was surveyed. Exposures were age, sex, race/ethnicity, education, occupation, contact with infected persons, comorbidities, height, and weight. The outcome was past COVID-19 infection measured by serum antibody test. We found a prevalence of 15.1% (95% CI: 11.1%, 20.2%) by December 2020. Seropositivity was significantly elevated among participants who were non-Hispanic Black, Hispanic (prevalence ratio [PRs]:1.4 [95% CI: 0.8, 2.4] and 2.3 [95% CI: 1.3, 4.0], respectively), worked in high-demand essential services (PR: 2.5 [95% CI: 1.5, 4.1]), did not have a college degree (PR: 1.6 [95% CI: 1.0, 2.4]), had an infected household or extra-household contact (PRs: 4.7 [95% CI: 2.1, 10.1] and 2.6 [95% CI: 1.2, 5.7], respectively), and were contacted in November or December (PR: 3.6 [95% CI: 1.9, 6.9]). Our results indicate that by December 2020, one out six persons in Arkansas had a past SARS-CoV-2 infection.

Risk factors for SARS-CoV-2 seroprevalence following the first pandemic wave in UK healthcare workers in a large NHS Foundation Trust

Background: We aimed to measure SARS-CoV-2 seroprevalence in a cohort of healthcare workers (HCWs) during the first UK wave of the COVID-19 pandemic, explore risk factors associated with infection, and investigate the impact of antibody titres on assay sensitivity. Methods: HCWs at Sheffield Teaching Hospitals NHS Foundation Trust were prospectively enrolled and sampled at two time points. We developed an in-house ELISA for testing participant serum for SARS-CoV-2 IgG and IgA reactivity against Spike and Nucleoprotein. Data were analysed using three statistical models: a seroprevalence model, an antibody kinetics model, and a heterogeneous sensitivity model. Results: Our in-house assay had a sensitivity of 99·47% and specificity of 99·56%. We found that 24·4% (n=311/1275) of HCWs were seropositive as of 12th June 2020. Of these, 39·2% (n=122/311) were asymptomatic. The highest adjusted seroprevalence was measured in HCWs on the Acute Medical Unit (41·1%, 95% CrI 30·0-52·9) and in Physiotherapists and Occupational Therapists (39·2%, 95% CrI 24·4-56·5). Older age groups showed overall higher median antibody titres. Further modelling suggests that, for a serological assay with an overall sensitivity of 80%, antibody titres may be markedly affected by differences in age, with sensitivity estimates of 89% in those over 60 years but 61% in those ≤30 years. Conclusions:  HCWs in acute medical units and those working closely with COVID-19 patients were at highest risk of infection, though whether these are infections acquired from patients or other staff is unknown. Current serological assays may underestimate seroprevalence in younger age groups if validated using sera from older and/or more severe COVID-19 cases.

SARS-CoV-2 active infection prevalence and seroprevalence in the adult population of St. Louis County

BACKGROUND

The true prevalence of COVID-19 is difficult to estimate due to the absence of random population-based testing. To estimate current and past COVID-19 infection prevalence in a large urban area, we conducted a population-based survey in St. Louis County, Missouri.

METHODS

The population-based survey of active infection (PCR) and seroprevalence (IgG antibodies) of adults (≥ 18 years) was conducted through random-digit dialing and targeted sampling of St. Louis County residents with oversampling of Black residents. Infection prevalence of residents was estimated using design-based and raking weighting.

RESULTS

Between August 17 and October 24, 2020, 1,245 residents completed a survey and underwent PCR testing; 1,073 residents completed a survey and underwent PCR and IgG testing or self-reported results. Weighted prevalence estimates of residents with active infection was 1.9% (95% CI, 0.4% to 3.3%) and 5.6% were ever infected (95% CI, 3.3% to 8.0%). Overall infection hospitalization and fatality ratios were 4.9% and 1.4%, respectively.

CONCLUSIONS

Through October 2020, the percentage of residents that had ever been infected was relatively low. A markedly higher percentage of Black and other minorities compared to White residents were infected with COVID-19. The St. Louis region remained highly vulnerable to widespread infection in late 2020.

SARS-CoV-2 Period Seroprevalence and Related Factors, Hillsborough County, Florida, October 2020-March 2021

Estimating the actual extent of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is challenging because virus test positivity data undercount the actual number and proportion of persons infected. SARS-CoV-2 seroprevalence is a marker of past SARS-CoV-2 infection regardless of presence or severity of symptoms and therefore is a robust biomarker of infection period prevalence. We estimated SARS-CoV-2 seroprevalence among residents of Hillsborough County, Florida, USA, to determine factors independently associated with SARS-CoV-2 antibody status overall and among asymptomatic antibody-positive persons. Among 867 participants, SARS-CoV-2 period prevalence (October 2020–March 2021) was 19.5% (asymptomatic seroprevalence was 8%). Seroprevalence was 2-fold higher than reported SARS-CoV-2 virus test positivity. Factors related to social distancing (e.g., essential worker status, not practicing social distancing, contact with a virus-positive person, and length of contact exposure time) were consistently associated with seroprevalence but did not differ by time since suspected or known infection (<6 months vs. >6 months).

Orange County, California COVID-19 Vaccine Equity Best Practices Checklist: A Community-Centered Call to Action for Equitable Vaccination Practices

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has exacerbated longstanding inequities throughout the United States, disproportionately concentrating adverse social, economic, and health-related outcomes among low-income communities and communities of color. Inequitable distribution, prioritization, and uptake of COVID-19 vaccines due to systemic and organizational barriers add to these disproportionate impacts across the United States. Similar patterns have been observed within Orange County, California (OC). Methods: In response to COVID-19 vaccine inequities unfolding locally, the Orange County Health Equity COVID-19 community-academic partnership generated a tool to guide a more equitable vaccine approach. Contents of the OC vaccine equity best practices checklist emerged through synthesis of community-level knowledge about vaccine inequities, literature regarding equitable vaccination considerations, and practice-based health equity guides. We combined into a memo: the checklist, a written explanation of its goals and origins, and three specific action steps meant to further strengthen the focus on vaccine equity. The memo was endorsed by partnership members and distributed to county officials. Discussion: Since the initial composition of the checklist, the local vaccine distribution approach has shifted, suggesting that equitable pandemic responses require continual re-evaluation of local needs and adjustments to recommendations as new information emerges. To understand and address structural changes needed to reduce racial and socioeconomic inequities exacerbated by the pandemic, authentic partnerships between community, academic, and public health practice partners are necessary. Conclusion: As we face continued COVID-19 vaccine rollout, booster vaccination, and future pandemic challenges, community knowledge and public health literature should be integrated to inform similar equity-driven strategic actions.

Accuracy of Case-Based Seroprevalence of SARS-CoV-2 Antibodies in Maricopa County, Arizona

We conducted a community seroprevalence survey in Arizona, from September 12 to October 1, 2020, to determine the presence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We used the seroprevalence estimate to predict SARS-CoV-2 infections in the jurisdiction by applying the adjusted seroprevalence to the county's population. The estimated community seroprevalence of SARS-CoV-2 infections was 4.3 times greater (95% confidence interval = 2.2, 7.5) than the number of reported cases. Field surveys with representative sampling provide data that may help fill in gaps in traditional public health reporting. (Am J Public Health. 2022;112(1):38-42. https://doi.org/10.2105/AJPH.2021.306568).

SARS-CoV-2 Seroprevalence in Western Romania, March to June 2021

Background and Objectives: The extent of SARS-CoV-2 infection among a population may be assessed by the presence of serum SARS-CoV-2 antibodies, which indicates previous exposure. The aim of this study was to determine the seroprevalence of SARS-CoV-2 infection in the adult population from Western Romania. Materials and Methods: Samples of 2443 consecutive individuals, referred for routine laboratory investigations, were tested for SARS-CoV-2 antibodies using the Elecsys immunoassay that targets the nucleocapsid protein, for identifying the presence of the total antibodies against SARS-CoV-2. Results: The overall SARS-CoV-2 seroprevalence was 45.60%. SARS-CoV-2 seroprevalence was significantly higher in age group 30-49 years (53.94%) compared to age groups 50-69 years (43.53%) and 70-91 years (30.79%) (p < 0.001, p < 0.001, respectively). No significant difference in seroprevalence was observed between females (44.83%) and males (47.05%). Conclusions: Our data revealed a high seroprevalence of SARS-CoV-2 infection in the adult population from Western Romania and indicate the rapid and significant spread of the virus. The estimated prevalence of 45.60% was 6 times higher than the rate of confirmed COVID-19 cases reported in the study area. This indicates the magnitude of virus transmission in the community.

Seroprevalence of Anti-SARS-CoV-2 Antibodies among Municipal Staff in the Municipality of Prishtina

BACKGROUND

Some studies have assessed the seroprevalence of anti-SARS-CoV-2 antibodies in different populations. Very few studies have explored seroprevalence in municipal workers, an important and potentially high-risk population. This study aims to determine the prevalence of anti-SARS-CoV-2 antibodies in municipal workers, with the additional examination of the association of prevalence with various demographic, health-related, and epidemiological factors.

METHODS

We surveyed and tested for seroprevalence 418 public servants from the municipality of Prishtina, the capital of Kosovo. The primary prespecified outcome was the seroprevalence of anti-SARS-CoV-2 antibodies, IgG, and IgM. Additional outcomes were crude and adjusted odds ratios of seroprevalence by different factors.

RESULTS

21.1% of municipal workers tested positive for either IgM or IgG. Of these, 9.6% were positive for IgM and 19.4% for IgG. Data showed high levels of adherence to protective measures, e.g., social distancing in the office, but calculation of ORs did not show a significant difference between those reporting adherence to such measures and those reporting nonadherence. Of other examined factors, significantly lower odds were observed for smokers (0.52, 95% CI 0.28, 0.97), while municipal workers with infected family members had elevated odds of seropositivity according to both crude (2.19, 95% CI 1.34, 3.59) and adjusted (2.00, 95% CI 1.17, 3.41) ORs.

CONCLUSIONS

Most answers from public servants demonstrated compliance to social-distancing policies in the workplace, but analysis of crude and adjusted odds ratios did not suggest a significant effect between municipal workers who followed these guidelines and those who did not. Results from this study help Kosovo policy makers in understanding the level of prevalence of COVID-19 in municipal workers and the effect of different factors on such prevalence. Results from the study could inform future decisions on the design and application of protective measures for municipal workers. Our findings should encourage further research to assess the extent of the spread of COVID-19 to other essential workers in Kosovo, including retail workers.

The Pandemic Experience in Southeast Asia: Interface Between SARS-CoV-2, Malaria, and Dengue

Southeast Asia (SEA) emerged relatively unscathed from the first year of the global SARS-CoV-2 pandemic, but as of July 2021 the region is experiencing a surge in case numbers primarily driven by Alpha (B.1.1.7) and subsequently the more transmissible Delta (B.1.617.2) variants. While initial disease burden was mitigated by swift government responses, favorable cultural and societal factors, the more recent rise in cases suggests an under-appreciation of prior prevalence and over-appreciation of possible cross-protective immunity from exposure to endemic viruses, and highlights the effects of vaccine rollout at varying tempos and of variable efficacy. This burgeoning crisis is further complicated by co-existence of malaria and dengue in the region, with implications of serological cross-reactivity on interpretation of SARS-CoV-2 assays and competing resource demands impacting efforts to contain both endemic and pandemic disease.

Inferring the COVID-19 infection fatality rate in the community-dwelling population: a simple Bayesian evidence synthesis of seroprevalence study data and imprecise mortality data

Estimating the coronavirus disease-2019 (COVID-19) infection fatality rate (IFR) has proven to be particularly challenging –and rather controversial– due to the fact that both the data on deaths and the data on the number of individuals infected are subject to many different biases. We consider a Bayesian evidence synthesis approach which, while simple enough for researchers to understand and use, accounts for many important sources of uncertainty inherent in both the seroprevalence and mortality data. With the understanding that the results of one's evidence synthesis analysis may be largely driven by which studies are included and which are excluded, we conduct two separate parallel analyses based on two lists of eligible studies obtained from two different research teams. The results from both analyses are rather similar. With the first analysis, we estimate the COVID-19 IFR to be 0.31% [95% credible interval (CrI) of (0.16%, 0.53%)] for a typical community-dwelling population where 9% of the population is aged over 65 years and where the gross-domestic-product at purchasing-power-parity (GDP at PPP) per capita is $17.8k (the approximate worldwide average). With the second analysis, we obtain 0.32% [95% CrI of (0.19%, 0.47%)]. Our results suggest that, as one might expect, lower IFRs are associated with younger populations (and may also be associated with wealthier populations). For a typical community-dwelling population with the age and wealth of the United States we obtain IFR estimates of 0.43% and 0.41%; and with the age and wealth of the European Union, we obtain IFR estimates of 0.67% and 0.51%.

Distinct SARS-CoV-2 antibody reactivity patterns elicited by natural infection and mRNA vaccination

We analyzed data from two ongoing COVID-19 longitudinal serological surveys in Orange County, CA., between April 2020 and March 2021. A total of 8476 finger stick blood specimens were collected before and after a vaccination campaign. IgG levels were determined using a multiplex antigen microarray containing antigens from SARS-CoV-2, SARS, MERS, Common CoV, and Influenza. Twenty-six percent of specimens from unvaccinated Orange County residents in December 2020 were SARS-CoV-2 seropositive; out of 852 seropositive individuals 77 had symptoms and 9 sought medical care. The antibody response was predominantly against nucleocapsid (NP), full length, and S2 domain of spike. Anti-receptor binding domain (RBD) reactivity was low and not cross-reactive against SARS S1 or SARS RBD. A vaccination campaign at the University of California Irvine Medical Center (UCIMC) started on December, 2020 and 6724 healthcare workers were vaccinated within 3 weeks. Seroprevalence increased from 13% pre-vaccination to 79% post-vaccination in January, 93% in February, and 99% in March. mRNA vaccination induced higher antibody levels than natural exposure, especially against the RBD domain and cross-reactivity against SARS RBD and S1 was observed. Nucleocapsid protein antibodies can be used to distinguish vaccinees to classify pre-exposure to SARS-CoV-2 Previously infected individuals developed higher antibody titers to the vaccine than non pre-exposed individuals. Hospitalized patients in intensive care with severe disease reach significantly higher antibody levels than mild cases, but lower antibody levels compared to the vaccine. These results indicate that mRNA vaccination rapidly induces a much stronger and broader antibody response than SARS-CoV-2 infection.

SARS-CoV-2 acquisition and immune pathogenesis among school-aged learners in four diverse schools

BACKGROUND

Understanding SARS-CoV-2 infection in children is necessary to reopen schools safely.

METHODS

We measured SARS-CoV-2 infection in 320 learners [10.5 ± 2.1 (sd); 7-17 y.o.] at four diverse schools with either remote or on-site learning. Schools A and B served low-income Hispanic learners; school C served many special-needs learners, and all provided predominantly remote instruction. School D served middle- and upper-income learners, with predominantly on-site instruction. Testing occurred in the fall (2020), and 6-8 weeks later during the fall-winter surge (notable for a tenfold increase in COVID-19 cases). Immune responses and mitigation fidelity were also measured.

RESULTS

We found SARS-CoV-2 infections in 17 learners only during the surge. School A (97% remote learners) had the highest infection (10/70, 14.3%, p < 0.01) and IgG positivity rates (13/66, 19.7%). School D (93% on-site learners) had the lowest infection and IgG positivity rates (1/63, 1.6%). Mitigation compliance [physical distancing (mean 87.4%) and face-covering (91.3%)] was remarkably high at all schools. Documented SARS-CoV-2-infected learners had neutralizing antibodies (94.7%), robust IFN-γ + T cell responses, and reduced monocytes.

CONCLUSIONS

Schools can implement successful mitigation strategies across a wide range of student diversity. Despite asymptomatic to mild SARS-CoV-2 infection, children generate robust humoral and cellular immune responses.

IMPACT

Successful COVID-19 mitigation was implemented across a diverse range of schools. School-associated SARS-CoV-2 infections reflect regional rates rather than remote or on-site learning. Seropositive school-aged children with asymptomatic to mild SARS-CoV-2 infections generate robust humoral and cellular immunity.

SARS-CoV-2: An Empirical Investigation of Rose's Population-based Logic

BACKGROUND

Geoffrey Rose's paper "Sick Individuals, Sick Populations" highlights the counterintuitive finding that the largest share of morbidity arises from populations engaging in low- to moderate-risk behavior. Scholars refer to this finding as the prevention paradox. We examine whether this logic applies to SARS-CoV-2 infected persons considered low to moderate risk.

METHODS

We conducted a population-representative survey and sero-surveillance study for SARS-CoV-2 among adults in Orange County, California. Participants answered questions about health behaviors and provided a finger-pin-prick sample from 10 July to 16 August 2020.

RESULTS

Of the 2979 adults, those reporting low- and moderate-risk behavior accounted for between 78% and 92% of SARS-CoV-2 infections. Asymptomatic individuals, as well as persons with low and moderate scores for self-reported likelihood of having had SARS-CoV-2, accounted for the majority of infections.

CONCLUSIONS

Our findings support Rose's logic, which encourages public health measures among persons who self-identify as unlikely to have SARS-CoV-2. See video abstract at, http://links.lww.com/EDE/B860.

Predictors of Test Positivity, Mortality, and Seropositivity during the Early Coronavirus Disease Epidemic, Orange County, California, USA

We conducted a detailed analysis of coronavirus disease in a large population center in southern California, USA (Orange County, population 3.2 million), to determine heterogeneity in risks for infection, test positivity, and death. We used a combination of datasets, including a population-representative seroprevalence survey, to assess the actual burden of disease and testing intensity, test positivity, and mortality. In the first month of the local epidemic (March 2020), case incidence clustered in high-income areas. This pattern quickly shifted, and cases next clustered in much higher rates in the north-central area of the county, which has a lower socioeconomic status. Beginning in April 2020, a concentration of reported cases, test positivity, testing intensity, and seropositivity in a north-central area persisted. At the individual level, several factors (e.g., age, race or ethnicity, and ZIP codes with low educational attainment) strongly affected risk for seropositivity and death.

Risk factors for SARS-CoV-2 seroprevalence following the first pandemic wave in UK healthcare workers in a large NHS Foundation Trust

Background: We aimed to measure SARS-CoV-2 seroprevalence in a cohort of healthcare workers (HCWs) during the first UK wave of the COVID-19 pandemic, explore risk factors associated with infection, and investigate the impact of antibody titres on assay sensitivity. Methods: HCWs at Sheffield Teaching Hospitals NHS Foundation Trust were prospectively enrolled and sampled at two time points. SARS-CoV-2 antibodies were tested using an in-house assay for IgG and IgA reactivity against Spike and Nucleoprotein (sensitivity 99·47%, specificity 99·56%). Data were analysed using three statistical models: a seroprevalence model, an antibody kinetics model, and a heterogeneous sensitivity model. Results: As of 12th June 2020, 24·4% (n=311/1275) of HCWs were seropositive. Of these, 39·2% (n=122/311) were asymptomatic. The highest adjusted seroprevalence was measured in HCWs on the Acute Medical Unit (41·1%, 95% CrI 30·0-52·9) and in Physiotherapists and Occupational Therapists (39·2%, 95% CrI 24·4-56·5). Older age groups showed overall higher median antibody titres. Further modelling suggests that, for a serological assay with an overall sensitivity of 80%, antibody titres may be markedly affected by differences in age, with sensitivity estimates of 89% in those over 60 years but 61% in those ≤30 years. Conclusions:  HCWs in acute medical units working closely with COVID-19 patients were at highest risk of infection, though whether these are infections acquired from patients or other staff is unknown. Current serological assays may underestimate seroprevalence in younger age groups if validated using sera from older and/or more symptomatic individuals.

SARS-CoV-2 antibody seroprevalence among firefighters in Orange County, California

OBJECTIVES

We conducted serological SARS-CoV-2 antibody testing from October to November 2020 to estimate the SARS-CoV-2 seroprevalence among firefighters/paramedics in Orange County (OC), California.

METHODS

OC firefighters employed at the time of the surveillance activity were invited to participate in a voluntary survey that collected demographic, occupational and previous COVID-19 testing data, and a SARS-CoV-2 immunoglobulin (Ig)G antibody blood test. We collected venous blood samples using mobile phlebotomy teams that travelled to individual fire stations, in coordination with an annual tuberculosis testing campaign for firefighters employed by OC Fire Authority (OCFA), and independently for firefighters employed by cities. We estimated seroprevalence and assessed several potential predictors of seropositivity.

RESULTS

The seroprevalence was 5.3% among 923 OCFA personnel tested, with 92.2% participating. Among firefighters self-reporting a previous positive COVID-19 antibody or PCR test result, twenty-one (37%) did not have positive IgG tests in the current serosurvey. There were no statistically significant differences in demographic characteristics between cases and non-cases. Work city was a significant predictor of case status (p=0.015). Seroprevalence (4.8%) was similar when aggregated across seven city fire departments (42%-65% participation). In total, 1486°C fire personnel were tested.

CONCLUSION

Using a strong serosurvey design and large firefighter cohort, we observed a SARS-CoV-2 IgG seroprevalence of 5.3%. The seroprevalence among OC firefighters in October 2020 was lower than the general county population estimated seroprevalence (11.5%) in August. The difference may be due in part to safety measures taken by OC fire departments at the start of the pandemic, as well as differences in antibody test methods and/or duration of antibody response.

SARS-CoV-2 Cumulative Incidence and Period Seroprevalence: Results From a Statewide Population-Based Serosurvey in California

Background

California has reported the largest number of coronavirus disease 2019 (COVID-19) cases of any US state, with more than 3.5 million confirmed as of March 2021. However, the full breadth of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in California is unknown as reported cases only represent a fraction of all infections.

Methods

We conducted a population-based serosurvey, utilizing mailed, home-based SARS-CoV-2 antibody testing along with a demographic and behavioral survey. We weighted data from a random sample to represent the adult California population and estimated period seroprevalence overall and by participant characteristics. Seroprevalence estimates were adjusted for waning antibodies to produce statewide estimates of cumulative incidence, the infection fatality ratio (IFR), and the reported fraction.

Results

California's SARS-CoV-2 weighted seroprevalence during August-December 2020 was 4.6% (95% CI, 2.8%-7.4%). Estimated cumulative incidence as of November 2, 2020, was 8.7% (95% CrI, 6.4%-11.5%), indicating that 2 660 441 adults (95% CrI, 1 959 218-3 532 380) had been infected. The estimated IFR was 0.8% (95% CrI, 0.6%-1.0%), and the estimated percentage of infections reported to the California Department of Public Health was 31%. Disparately high risk for infection was observed among persons of Hispanic/Latinx ethnicity and people with no health insurance and who reported working outside the home.

Conclusions

We present the first statewide SARS-CoV-2 cumulative incidence estimate among adults in California. As of November 2020, ~1 in 3 SARS-CoV-2 infections in California adults had been identified by public health surveillance. When accounting for unreported SARS-CoV-2 infections, disparities by race/ethnicity seen in case-based surveillance persist.

Risk factors for SARS-CoV-2 seroprevalence following the first pandemic wave in UK healthcare workers in a large NHS Foundation Trust

BACKGROUND

We aimed to measure SARS-CoV-2 seroprevalence in a cohort of healthcare workers (HCWs) during the first UK wave of the COVID-19 pandemic, explore risk factors associated with infection, and investigate the impact of antibody titres on assay sensitivity.

METHODS

HCWs at Sheffield Teaching Hospitals NHS Foundation Trust (STH) were prospectively enrolled and sampled at two time points. SARS-CoV-2 antibodies were tested using an in-house assay for IgG and IgA reactivity against Spike and Nucleoprotein (sensitivity 99·47%, specificity 99·56%). Data were analysed using three statistical models: a seroprevalence model, an antibody kinetics model, and a heterogeneous sensitivity model.

FINDINGS

As of 12th June 2020, 24·4% (n=311/1275) HCWs were seropositive. Of these, 39·2% (n=122/311) were asymptomatic. The highest adjusted seroprevalence was measured in HCWs on the Acute Medical Unit (41·1%, 95% CrI 30·0-52·9) and in Physiotherapists and Occupational Therapists (39·2%, 95% CrI 24·4-56·5). Older age groups showed overall higher median antibody titres. Further modelling suggests that, for a serological assay with an overall sensitivity of 80%, antibody titres may be markedly affected by differences in age, with sensitivity estimates of 89% in those over 60 years but 61% in those ≤30 years.

INTERPRETATION

HCWs in acute medical units working closely with COVID-19 patients were at highest risk of infection, though whether these are infections acquired from patients or other staff is unknown. Current serological assays may underestimate seroprevalence in younger age groups if validated using sera from older and/or more symptomatic individuals.

RESEARCH IN CONTEXT

Evidence before this study: We searched PubMed for studies published up to March 6th 2021, using the terms "COVID", "SARS-CoV-2", "seroprevalence", and "healthcare workers", and in addition for articles of antibody titres in different age groups against coronaviruses using "coronavirus", "SARS-CoV-2, "antibody", "antibody tires", "COVID" and "age". We included studies that used serology to estimate prevalence in healthcare workers. SARS-CoV-2 seroprevalence has been shown to be greater in healthcare workers working on acute medical units or within domestic services. Antibody levels against seasonal coronaviruses, SARS-CoV and SARS-CoV-2 were found to be higher in older adults, and patients who were hospitalised.Added value of this study: In this healthcare worker seroprevalence modelling study at a large NHS foundation trust, we confirm that those working on acute medical units, COVID-19 "Red Zones" and within domestic services are most likely to be seropositive. Furthermore, we show that physiotherapists and occupational therapists have an increased risk of COVID-19 infection. We also confirm that antibody titres are greater in older individuals, even in the context of non-hospitalised cases. Importantly, we demonstrate that this can result in age-specific sensitivity in serological assays, where lower antibody titres in younger individuals results in lower assay sensitivity.Implications of all the available evidence: There are distinct occupational roles and locations in hospitals where the risk of COVID-19 infection to healthcare workers is greatest, and this knowledge should be used to prioritise infection prevention control and other measures to protect healthcare workers. Serological assays may have different sensitivity profiles across different age groups, especially if assay validation was undertaken using samples from older and/or hospitalised patients, who tend to have higher antibody titres. Future seroprevalence studies should consider adjusting for age-specific assay sensitivities to estimate true seroprevalence rates.

AUTHOR CONTRIBUTIONS

Understanding COVID-19 Epidemiology and Implications for Control: The Experience from a Greek Semi-Closed Community

BACKGROUND

We aimed to estimate the SARS-CoV-2 antigen and antibody seroprevalence in one of the worst-affected by the pandemic semi-closed communities in Greece, Deskati, and evaluate the sociodemographic and clinical correlations of functional antibody responses.

METHODS

The Ag2019n-CoV V1310/V1330 Rapid Test (Prognosis Biotech, Greece) was used for antigen detection. The Rapid Test 2019-nCoV Total Ig, V1210/V1230 (Prognosis Biotech, Greece), and the SARS-CoV-2 IgG II Quant method (Architect, Abbott, Illinois, USA) were used for antibody testing.

RESULTS

None of the participants had a positive antigen result. SARS-CoV-2 seropositivity ranged from 13% to 45% in the study population, depending on the method. One-third of the participants with known past infection had a positive antibody test result 77 ± 13 days after infection. Two-fifths of infections determined by serology were asymptomatic. The advancing age and hospitalization predicted seropositivity among patients with past infection. Half of the participants who tested positive for antibodies were not aware of past infection.

CONCLUSIONS

High-burden contexts in Greece, such as Deskati, are not so far from herd immunity thresholds. We highlighted the value of low-cost serosurveys targeting both symptomatic and asymptomatic populations to evaluate the natural immune response to SARS-CoV-2 in nonvaccinated susceptibles and design evidence-based policies for lifting lockdowns.

SARS-CoV-2 Acquisition and Immune Pathogenesis Among School-Aged Learners in Four Diverse Schools

Background

Understanding SARS-CoV-2 infection in children is necessary to reopen schools safely.

Methods

We measured SARS-CoV-2 infection in 320 learners [10.5 ± 2.1(sd); 7-17 y.o.] at four diverse schools with either remote or on-site learning. Schools A and B served low-income Hispanic learners; school C served many special-needs learners; and all provided predominantly remote instruction. School D served middle- and upper-income learners, with predominantly on-site instruction. Testing occurred in the fall (2020), and 6-8 weeks later during the fall-winter surge (notable for a tenfold increase in COVID-19 cases). Immune responses and mitigation fidelity were also measured.

Results

We found SARS-CoV-2 infections in 17 learners only during the surge. School A (97% remote learners) had the highest infection (10/70, 14.3%, p<0.01) and IgG positivity rates (13/66, 19.7%). School D (93% on-site learners) had the lowest infection and IgG positivity rates (1/63, 1.6%). Mitigation compliance [physical distancing (mean 87.4%) and face covering (91.3%)] was remarkably high at all schools. Documented SARS-CoV-2-infected learners had neutralizing antibodies (94.7%), robust IFN-γ+ T cell responses, and reduced monocytes.

Conclusion

Schools can implement successful mitigation strategies across a wide range of student diversity. Despite asymptomatic to mild SARS-CoV-2 infection, children generate robust humoral and cellular immune responses.

Key Points

Successful COVID-19 mitigation was implemented across a diverse range of schools.School-associated SARS-CoV-2 infections reflect regional rates rather than remote or on-site learning.Seropositive school-aged children with asymptomatic to mild SARS-CoV-2 infections generate robust humoral and cellular immunity.

Heterogeneity in SARS-CoV-2 Positivity by Ethnicity in Los Angeles

Recent studies have identified notable disparities in SARS-CoV-2 infection risk among ethnic minorities. We evaluated SARS-CoV-2 test results from individuals presenting for testing in Los Angeles between June and December, 2020. We calculated prevalence ratios for various employment categories. Among 518,914 test results, of which 295,295 (56.9%) were from individuals reporting Hispanic ethnicity, SARS-CoV-2 positivity was 16.5% among Hispanic individuals compared to 5.0% among non-Hispanic individuals (p-value <0.01). The prevalence ratios comparing Hispanic and non-Hispanic individuals were highest for members of the media (PR = 6.7; 95% CI 4.3-10.4), government employees (PR = 4.0; 95% CI 3.3-4.9), and agricultural workers (PR = 4.0; 95% CI 3.2-5.0). Such heterogeneity warrants further investigation in order to develop targeted public health interventions towards specific drivers of SARS-CoV-2 transmission.

Serological evidence of human infection with SARS-CoV-2: a systematic review and meta-analysis

BACKGROUND

A rapidly increasing number of serological surveys for antibodies to SARS-CoV-2 have been reported worldwide. We aimed to synthesise, combine, and assess this large corpus of data.

METHODS

In this systematic review and meta-analysis, we searched PubMed, Embase, Web of Science, and five preprint servers for articles published in English between Dec 1, 2019, and Dec 22, 2020. Studies evaluating SARS-CoV-2 seroprevalence in humans after the first identified case in the area were included. Studies that only reported serological responses among patients with COVID-19, those using known infection status samples, or any animal experiments were all excluded. All data used for analysis were extracted from included papers. Study quality was assessed using a standardised scale. We estimated age-specific, sex-specific, and race-specific seroprevalence by WHO regions and subpopulations with different levels of exposures, and the ratio of serology-identified infections to virologically confirmed cases. This study is registered with PROSPERO, CRD42020198253.

FINDINGS

16 506 studies were identified in the initial search, 2523 were assessed for eligibility after removal of duplicates and inappropriate titles and abstracts, and 404 serological studies (representing tests in 5 168 360 individuals) were included in the meta-analysis. In the 82 studies of higher quality, close contacts (18·0%, 95% CI 15·7-20·3) and high-risk health-care workers (17·1%, 9·9-24·4) had higher seroprevalence than did low-risk health-care workers (4·2%, 1·5-6·9) and the general population (8·0%, 6·8-9·2). The heterogeneity between included studies was high, with an overall I2 of 99·9% (p<0·0001). Seroprevalence varied greatly across WHO regions, with the lowest seroprevalence of general populations in the Western Pacific region (1·7%, 95% CI 0·0-5·0). The pooled infection-to-case ratio was similar between the region of the Americas (6·9, 95% CI 2·7-17·3) and the European region (8·4, 6·5-10·7), but higher in India (56·5, 28·5-112·0), the only country in the South-East Asia region with data.

INTERPRETATION

Antibody-mediated herd immunity is far from being reached in most settings. Estimates of the ratio of serologically detected infections per virologically confirmed cases across WHO regions can help provide insights into the true proportion of the population infected from routine confirmation data.

FUNDING

National Science Fund for Distinguished Young Scholars, Key Emergency Project of Shanghai Science and Technology Committee, Program of Shanghai Academic/Technology Research Leader, National Science and Technology Major project of China, the US National Institutes of Health.

TRANSLATION

For the Chinese translation of the abstract see Supplementary Materials section.

Antibody Responses in COVID-19: A Review

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to spread worldwide as a severe pandemic. Although its seroprevalence is highly variable among territories, it has been reported at around 10%, but higher in health workers. Evidence regarding cross-neutralizing response between SARS-CoV and SARS-CoV-2 is still controversial. However, other previous coronaviruses may interfere with SARS-CoV-2 infection, since they are phylogenetically related and share the same target receptor. Further, the seroconversion of IgM and IgG occurs at around 12 days post onset of symptoms and most patients have neutralizing titers on days 14-20, with great titer variability. Neutralizing antibodies correlate positively with age, male sex, and severity of the disease. Moreover, the use of convalescent plasma has shown controversial results in terms of safety and efficacy, and due to the variable immune response among individuals, measuring antibody titers before transfusion is mostly required. Similarly, cellular immunity seems to be crucial in the resolution of the infection, as SARS-CoV-2-specific CD4+ and CD8+ T cells circulate to some extent in recovered patients. Of note, the duration of the antibody response has not been well established yet.