Population Point Prevalence of SARS-CoV-2 Infection Based on a Statewide Random Sample - Indiana, April 25-29, 2020

Bayesian hierarchical spatiotemporal models for prediction of (under)reporting rates and cases: COVID-19 infection among the older people in the United States during the 2020-2022 pandemic

The gap between the reported and actual COVID-19 infection cases has been an issue of concern. Here, we present Bayesian hierarchical spatiotemporal disease mapping models for state-level predictions of COVID-19 infection risks and (under)reporting rates among people aged 65 and above during the first two years of the pandemic in the United States. With prior elicitation based on recent prevalence studies, the study suggests that the median state-level reporting rate of COVID-19 infection was 90% (interquartile range: [78%, 96%]). Our study uncovers spatiotemporal variations and dynamics in state-level infection risks and (under)reporting rates, suggesting time-varying associations between higher population density, higher percentage of minorities, and higher percentage of vaccination and increased risks of COVID-19 infection, as well as an association between more easily accessible tests and higher reporting rates. With sensitivity analyses, we highlight the impact and importance of incorporating covariates information and objective prior references for evaluating the issue of underreporting.

Adaptive Time-Location Sampling for COMPASS: A SARS-CoV-2 Prevalence Study in Fifteen Diverse Communities in the United States

BACKGROUND

COVID-19 has placed a disproportionate burden on underserved racial and ethnic groups, community members working in essential industries, those living in areas of high population density, and those reliant on in-person services such as transportation. The goal of this study was to estimate the cross-sectional prevalence of SARS-CoV-2 (active SARS-CoV-2 or prior SARS-CoV-2 infection) in children and adults attending public venues in 15 sociodemographically diverse communities in the United States and to develop a statistical design that could be rigorously implemented amidst unpredictable stay-at-home COVID-19 guidelines.

METHODS

We used time-location sampling with complex sampling involving stratification, clustering of units, and unequal probabilities of selection to recruit individuals from selected communities. We safely conducted informed consent, specimen collection, and face-to-face interviews outside of public venues immediately following recruitment.

RESULTS

We developed an innovative sampling design that adapted to constraints such as closure of venues, changing infection hotspots, and uncertain policies. We updated both the sampling frame and the selection probabilities over time using information acquired from prior weeks. We created site-specific survey weights that adjusted sampling probabilities for nonresponse and calibrated to county-level margins on age and sex at birth.

CONCLUSIONS

Although the study itself was specific to COVID-19, the strategies presented in this article could serve as a case study that can be adapted for performing population-level inferences in similar settings and could help inform rapid and effective responses to future global public health challenges.

Characterizing participants who respond to text, email, phone calls, or postcards in a SARS-CoV-2 prevalence study

INTRODUCTION

Multiple modalities and frequencies of contact are needed to maximize recruitment in many public health surveys. The purpose of this analysis is to characterize respondents to a statewide SARS-CoV-2 testing study whose participation followed either postcard, phone outreach or electronic means of invitation. In addition, we examine how participant characteristics differ based upon the number of contacts needed to elicit participation.

METHODS

This is a cross-sectional analysis of survey data collected from participants who were randomly selected to represent Indiana residents and were invited to be tested for Covid-19 in April 2020. Participants received invitations via postcard, text/emails, and/or robocalls/texts based upon available contact information. The modality, and frequency of contacts, that prompted participation was determined by when the notification was sent and when the participant responded and subsequently registered to participate in the study. Chi square analyses were used to determine differences between groups and significant findings were analyzed using multinomial logistic regression.

RESULTS

Respondents included 3,658 individuals and were stratified by postcards (7.9%), text/emails (26.5%), and robocalls/text (65.7%) with 19.7% registering after 1 contact, 47.9% after 2 contacts, and 32.4% after 3 contacts encouraging participation. Females made up 54.6% of the sample and responded at a higher rate for postcards (8.2% vs. 7.5%) and text/emails (28.1 vs. 24.6%) as compared to males (χ2 = 7.43, p = 0.025). Compared to males, females responded at a higher percentage after 1 contact (21.4 vs. 17.9%, χ2 = 7.6, p = 0.023). Those over 60 years responded most often after 2 contacts (χ2 = 27.5, p < 0.001) when compared to others at younger age groups. In regression analysis, participant sex (p = 0.036) age (p = 0.005), educational attainment (p = < 0.0001), and being motivated by "free testing" (p = 0.036) were correlated with participation in the prevalence study.

DISCUSSION

Researchers should be aware that the modality of contact as well as the number of prompts used could influence differential participation in public health studies. Our findings can inform researchers developing studies that rely on selective participation by study subjects. We explore how to increase participation within targeted demographic groups using specific modalities and examining frequency of contact.

Generating synthetic population for simulating the spatiotemporal dynamics of epidemics

Agent-based models have gained traction in exploring the intricate processes governing the spread of infectious diseases, particularly due to their proficiency in capturing nonlinear interaction dynamics. The fidelity of agent-based models in replicating real-world epidemic scenarios hinges on the accurate portrayal of both population-wide and individual-level interactions. In situations where comprehensive population data are lacking, synthetic populations serve as a vital input to agent-based models, approximating real-world demographic structures. While some current population synthesizers consider the structural relationships among agents from the same household, there remains room for refinement in this domain, which could potentially introduce biases in subsequent disease transmission simulations. In response, this study unveils a novel methodology for generating synthetic populations tailored for infectious disease transmission simulations. By integrating insights from microsample-derived household structures, we employ a heuristic combinatorial optimizer to recalibrate these structures, subsequently yielding synthetic populations that faithfully represent agent structural relationships. Implementing this technique, we successfully generated a spatially-explicit synthetic population encompassing over 17 million agents for Shenzhen, China. The findings affirm the method's efficacy in delineating the inherent statistical structural relationship patterns, aligning well with demographic benchmarks at both city and subzone tiers. Moreover, when assessed against a stochastic agent-based Susceptible-Exposed-Infectious-Recovered model, our results pinpointed that variations in population synthesizers can notably alter epidemic projections, influencing both the peak incidence rate and its onset.

Disparities in SARS-CoV-2 Infection by Race, Ethnicity, Language, and Social Vulnerability: Evidence from a Citywide Seroprevalence Study in Massachusetts, USA

OBJECTIVES

Uncovering and addressing disparities in infectious disease outbreaks require a rapid, methodical understanding of local epidemiology. We conducted a seroprevalence study of SARS-CoV-2 infection in Holyoke, Massachusetts, a majority Hispanic city with high levels of socio-economic disadvantage to estimate seroprevalence and identify disparities in SARS-CoV-2 infection.

METHODS

We invited 2000 randomly sampled households between 11/5/2020 and 12/31/2020 to complete questionnaires and provide dried blood spots for SARS-CoV-2 antibody testing. We calculated seroprevalence based on the presence of IgG antibodies using a weighted Bayesian procedure that incorporated uncertainty in antibody test sensitivity and specificity and accounted for household clustering.

RESULTS

Two hundred eighty households including 472 individuals were enrolled. Three hundred twenty-eight individuals underwent antibody testing. Citywide seroprevalence of SARS-CoV-2 IgG was 13.1% (95% CI 6.9-22.3) compared to 9.8% of the population infected based on publicly reported cases. Seroprevalence was 16.1% (95% CI 6.2-31.8) among Hispanic individuals compared to 9.4% (95% CI 4.6-16.4) among non-Hispanic white individuals. Seroprevalence was higher among Spanish-speaking households (21.9%; 95% CI 8.3-43.9) compared to English-speaking households (10.2%; 95% CI 5.2-18.0) and among individuals in high social vulnerability index (SVI) areas based on the CDC SVI (14.4%; 95% CI 7.1-25.5) compared to low SVI areas (8.2%; 95% CI 3.1-16.9).

CONCLUSIONS

The SARS-CoV-2 IgG seroprevalence in a city with high levels of social vulnerability was 13.1% during the pre-vaccination period of the COVID-19 pandemic. Hispanic individuals and individuals in communities characterized by high SVI were at the highest risk of infection. Public health interventions should be designed to ensure that individuals in high social vulnerability communities have access to the tools to combat COVID-19.

Stratified Simple Random Sampling Versus Volunteer Community-Wide Sampling for Estimates of COVID-19 Prevalence

Objectives. To evaluate community-wide prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using stratified simple random sampling. Methods. We obtained data for the prevalence of SARS-CoV-2 in Jefferson County, Kentucky, from adult random (n = 7296) and volunteer (n = 7919) sampling over 8 waves from June 2020 through August 2021. We compared results with administratively reported rates of COVID-19. Results. Randomized and volunteer samples produced equivalent prevalence estimates (P < .001), which exceeded the administratively reported rates of prevalence. Differences between them decreased as time passed, likely because of seroprevalence temporal detection limitations. Conclusions. Structured targeted sampling for seropositivity against SARS-CoV-2, randomized or voluntary, provided better estimates of prevalence than administrative estimates based on incident disease. A low response rate to stratified simple random sampling may produce quantified disease prevalence estimates similar to a volunteer sample. Public Health Implications. Randomized targeted and invited sampling approaches provided better estimates of disease prevalence than administratively reported data. Cost and time permitting, targeted sampling is a superior modality for estimating community-wide prevalence of infectious disease, especially among Black individuals and those living in disadvantaged neighborhoods. (Am J Public Health. 2023;113(7):768-777. https://doi.org/10.2105/AJPH.2023.307303).

Spread of SARS-CoV-2 Infection in Adult Populations in Cameroon: A Repeated Cross-Sectional Study Among Blood Donors in the Cities of Yaoundé and Douala

Over a period of about 9 months, we conducted three serosurveys in the two major cities of Cameroon to determine the prevalence of SARS-COV-2 antibodies and to identify factors associated with seropositivity in each survey. We conducted three independent cross-sectional serosurveys of adult blood donors at the Central Hospital in Yaoundé (CHY), the Jamot Hospital in Yaoundé (JHY) and at the Laquintinie Hospital in Douala (LHD) who consented in writing to participate. Before blood sampling, a short questionnaire was administered to participants to collect their sociodemographic and clinical characteristics. We included a total of 743, 1202, and 1501 participants in the first (January 25-February 15, 2021), second (May 03-28, 2021), and third (November 29-December 31, 2021) surveys, respectively. The adjusted seroprevalence increased from 66.3% (95% CrI 61.1-71.3) in the first survey to 87.2% (95% CrI 84.0-90.0) in the second survey, and 98.4% (95% CrI 96.8-99.7) in the third survey. In the first survey, study site, participant occupation, and comorbid conditions were associated with SARS-CoV-2 seropositivity, whereas only study site remained associated in the second survey. None of the factors studied was significantly associated with seropositivity in the third survey. Together, the data suggest a rapid initial spread of SARS-CoV-2 in the study population, independent of the sociodemographic parameters assessed.

Seroprevalence and SARS-CoV-2 invasion in general populations: A scoping review over the first year of the pandemic

Since the beginning of the COVID-19 pandemic, counting infected people has underestimated asymptomatic cases. This literature scoping review assessed the seroprevalence progression in general populations worldwide over the first year of the pandemic. Seroprevalence studies were searched in PubMed, Web of Science and medRxiv databases up to early April 2021. Inclusion criteria were a general population of all ages or blood donors as a proxy. All articles were screened for the title and abstract by two readers, and data were extracted from selected articles. Discrepancies were resolved with a third reader. From 139 articles (including 6 reviews), the seroprevalence estimated in 41 countries ranged from 0 to 69%, with a heterogenous increase over time and continents, unevenly distributed among countries (differences up to 69%) and sometimes among regions within a country (up to 10%). The seroprevalence of asymptomatic cases ranged from 0% to 31.5%. Seropositivity risk factors included low income, low education, low smoking frequency, deprived area residency, high number of children, densely populated centres, and presence of a case in a household. This review of seroprevalence studies over the first year of the pandemic documented the progression of this virus across the world in time and space and the risk factors that influenced its spread.

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.

Estimating the Under-ascertainment of COVID-19 cases in Toronto, Ontario, March to May 2020

Background

Public health surveillance data do not always capture all cases, due in part to test availability and health care seeking behaviour. Our study aimed to estimate under-ascertainment multipliers for each step in the reporting chain for COVID-19 in Toronto, Canada.

Design and methods

We applied stochastic modeling to estimate these proportions for the period from March 2020 (the beginning of the pandemic) through to May 23, 2020, and for three distinct windows with different laboratory testing criteria within this period.

Results

For each laboratory-confirmed symptomatic case reported to Toronto Public Health during the entire period, the estimated number of COVID-19 infections in the community was 18 (5th and 95th percentile: 12, 29). The factor most associated with under-reporting was the proportion of those who sought care that received a test.

Conclusions

Public health officials should use improved estimates to better understand the burden of COVID-19 and other similar infections.

Leveraging CTSA hubs for rapid, large-scale, high-impact research: A case study during a global public health emergency

As the COVID-19 pandemic took hold in the USA in early 2020, it became clear that knowledge of the prevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among asymptomatic individuals could inform public health policy decisions and provide insight into the impact of the infection on vulnerable populations. Two Clinical and Translational Science Award (CTSA) Hubs and the National Institutes of Health (NIH) set forth to conduct a national seroprevalence survey to assess the infection's rate of spread. This partnership was able to quickly design and launch the project by leveraging established research capacities, prior experiences in large-scale, multisite studies and a highly skilled workforce of CTSA hubs and unique experimental capabilities at the NIH to conduct a diverse prospective, longitudinal observational cohort of 11,382 participants who provided biospecimens and participant-reported health and behavior data. The study was completed in 16 months and benefitted from transdisciplinary teamwork, information technology innovations, multimodal communication strategies, and scientific partnership for rigor in design and analytic methods. The lessons learned by the rapid implementation and dissemination of this national study is valuable in guiding future multisite projects as well as preparation for other public health emergencies and pandemics.

ADAPTIVE TIME LOCATION SAMPLING FOR COMPASS, A SARS-COV-2 PREVALENCE STUDY IN FIFTEEN DIVERSE COMMUNITIES IN THE UNITED STATES

The COVPN 5002 (COMPASS) study aimed to estimate the prevalence of SARS-CoV-2 (active SARS-CoV-2 or prior SARS-CoV-2 infection) in children and adults attending public venues in 15 socio-demographically diverse communities in the United States. To protect against potential challenges in implementing traditional sampling strategies, time-location sampling (TLS) using complex sampling involving stratification, clustering of units, and unequal probabilities of selection was used to recruit individuals from neighborhoods in selected communities. The innovative design adapted to constraints such as closure of venues; changing infection hotspots; and uncertain policies. Recruitment of children and the elderly raised additional challenges in sample selection and implementation. To address these challenges, the TLS design adaptively updated both the sampling frame and the selection probabilities over time using information acquired from prior weeks. Although the study itself was specific to COVID-19, the strategies presented in this paper could serve as a case study that can be adapted for performing rigorous population-level inferences in similar settings and could help inform rapid and effective responses to future global public health challenges.

Quantifying the relationship between sub-population wastewater samples and community-wide SARS-CoV-2 seroprevalence

Robust epidemiological models relating wastewater to community disease prevalence are lacking. Assessments of SARS-CoV-2 infection rates have relied primarily on convenience sampling, which does not provide reliable estimates of community disease prevalence due to inherent biases. This study conducted serial stratified randomized samplings to estimate the prevalence of SARS-CoV-2 antibodies in 3717 participants, and obtained weekly samples of community wastewater for SARS-CoV-2 concentrations in Jefferson County, KY (USA) from August 2020 to February 2021. Using an expanded Susceptible-Infected-Recovered model, the longitudinal estimates of the disease prevalence were obtained and compared with the wastewater concentrations using regression analysis. The model analysis revealed significant temporal differences in epidemic peaks. The results showed that in some areas, the average incidence rate, based on serological sampling, was 50 % higher than the health department rate, which was based on convenience sampling. The model-estimated average prevalence rates correlated well with the wastewater (correlation = 0.63, CI (0.31,0.83)). In the regression analysis, a one copy per ml-unit increase in weekly average wastewater concentration of SARS-CoV-2 corresponded to an average increase of 1-1.3 cases of SARS-CoV-2 infection per 100,000 residents. The analysis indicates that wastewater may provide robust estimates of community spread of infection, in line with the modeled prevalence estimates obtained from stratified randomized sampling, and is therefore superior to publicly available health data.

Population-based correlates of COVID-19 infection: An analysis from the DFW COVID-19 prevalence study

BACKGROUND

COVID-19 has resulted in over 1 million deaths in the U.S. as of June 2022, with continued surges after vaccine availability. Information on related attitudes and behaviors are needed to inform public health strategies. We aimed to estimate the prevalence of COVID-19, risk factors of infection, and related attitudes and behaviors in a racially, ethnically, and socioeconomically diverse urban population.

METHODS

The DFW COVID-19 Prevalence Study Protocol 1 was conducted from July 2020 to March 2021 on a randomly selected sample of adults aged 18-89 years, living in Dallas or Tarrant Counties, Texas. Participants were asked to complete a 15-minute questionnaire and COVID-19 PCR and antibody testing. COVID-19 prevalence estimates were calculated with survey-weighted data.

RESULTS

Of 2969 adults who completed the questionnaire (7.4% weighted response), 1772 (53.9% weighted) completed COVID-19 testing. Overall, 11.5% of adults had evidence of COVID-19 infection, with a higher prevalence among Hispanic and non-Hispanic Black persons, essential workers, those in low-income neighborhoods, and those with lower education attainment compared to their counterparts. We observed differences in attitudes and behaviors by race and ethnicity, with non-Hispanic White persons being less likely to believe in the importance of mask wearing, and racial and ethnic minorities more likely to attend social gatherings.

CONCLUSION

Over 10% of an urban population was infected with COVID-19 early during the pandemic. Differences in attitudes and behaviors likely contribute to sociodemographic disparities in COVID-19 prevalence.

COVID-19 SeroHub, an online repository of SARS-CoV-2 seroprevalence studies in the United States

Seroprevalence studies provide useful information about the proportion of the population either vaccinated against SARS-CoV-2, previously infected with the virus, or both. Numerous studies have been conducted in the United States, but differ substantially by dates of enrollment, target population, geographic location, age distribution, and assays used. This can make it challenging to identify and synthesize available seroprevalence data by geographic region or to compare infection-induced versus combined infection- and vaccination-induced seroprevalence. To facilitate public access and understanding, the National Institutes of Health and the Centers for Disease Control and Prevention developed the COVID-19 Seroprevalence Studies Hub (COVID-19 SeroHub, https://covid19serohub.nih.gov/), a data repository in which seroprevalence studies are systematically identified, extracted using a standard format, and summarized through an interactive interface. Within COVID-19 SeroHub, users can explore and download data from 178 studies as of September 1, 2022. Tools allow users to filter results and visualize trends over time, geography, population, age, and antigen target. Because COVID-19 remains an ongoing pandemic, we will continue to identify and include future studies.

Point prevalence of SARS-CoV-2 infection in Sweden at six time points during 2020

Background

In order to estimate the prevalence and understand the spread of SARS-CoV-2 in Sweden, the Public Health Agency of Sweden, with support from the Swedish Armed Forces, conducted a series of point prevalence surveys between March and December 2020.

Methods

Sampling material and instructions on how to perform self-sampling of the upper respiratory tract were delivered to the homes of the participants. Samples were analysed by real-time PCR, and the participants completed questionnaires regarding symptoms.

Findings

The first survey in the Stockholm region in March 2020 included 707 participants and showed a SARS-CoV-2 prevalence of 2.5%. The following five surveys, performed on a national level, with between 2461 and 2983 participants, showed SARS-CoV-2 prevalences of 0.9% (April), 0.3% (May), 0.0% (August), 0.0% (September), and 0.7% (December). All positive cases who responded to questionnaires reported experiencing symptoms that occurred from 2 weeks before the date of sampling up to and including the date of sampling.

Interpretation

None of the individuals shown to be PCR-positive were asymptomatic at the time of sampling or in the 14 days prior to sampling. This is in contrast to many other surveys in which a substantial proportion of positive cases have been reported to be asymptomatic. Our surveys demonstrate a decreasing ratio between notified cases and the observed prevalence throughout the year, in line with increasing testing capacity and the consecutive inclusion of all symptomatic individuals in the case definition for testing.

Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States

Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.

Mitigation of COVID-19 at the 2021 National Collegiate Athletic Association Men’s Basketball Tournament

Background

Data are lacking regarding the risk of viral SARS-CoV-2 transmission during a large indoor sporting event involving fans utilizing a controlled environment. We sought to describe case characteristics, mitigation protocols used, variants detected, and secondary infections detected during the 2021 National Collegiate Athletic Association (NCAA) Men’s Basketball Tournament involving collegiate athletes from across the U.S.

Methods

This retrospective cohort study used data collected from March 16 to April 3, 2021, as part of a closed environment which required daily reverse transcription-polymerase chain reaction (RT-PCR) testing, social distancing, universal masking, and limited contact between tiers of participants. Nearly 3000 players, staff, and vendors participated in indoor, unmasked activities that involved direct exposure between cases and noninfected individuals. The main outcome of interest was transmission of SARS-CoV-2 virus, as measured by the number of new infections and variant(s) detected among positive cases. Secondary infections were identified through contact tracing by public health officials.

Results

Out of 2660 participants, 15 individuals (0.56%) screened positive for SARS-CoV-2. Four cases involved players or officials, and all cases were detected before any individual played in or officiated a game. Secondary transmissions all occurred outside the controlled environment. Among those disqualified from the tournament (4 cases; 26.7%), all individuals tested positive for the Iota variant (B.1.526). All other cases involved the Alpha variant (B.1.1.7). Nearly all teams (N = 58; 85.3%) reported that some individuals had received at least one dose of a vaccine. Overall, 17.9% of participants either had at least one dose of the vaccine or possessed documented infection within 90 days of the tournament.

Conclusion

In this retrospective cohort study of the 2021 NCAA Men’s Basketball Tournament closed environment, only a few cases were detected, and they were discovered in advance of potential exposure. These findings support the U.S. Centers for Disease Control and Prevention (CDC) guidelines for large indoor sporting events during the COVID-19 pandemic.

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.

Impacts of timing, length, and intensity of behavioral interventions to COVID-19 dynamics: North Carolina county-level examples

We sought to examine how the impact of revocable behavioral interventions, e.g., shelter-in-place, varies throughout an epidemic, as well as the role that the proportion of susceptible individuals had on an intervention's impact. We estimated the theoretical impacts of start day, length, and intensity of interventions on disease transmission and illustrated them on COVID-19 dynamics in Wake County, North Carolina, to inform how interventions can be most effective. We used a Susceptible, Exposed, Infectious, and Recovered (SEIR) model to estimate epidemic curves with modifications to the disease transmission parameter (β). We designed modifications to simulate events likely to increase transmission (e.g., long weekends, holiday seasons) or behavioral interventions likely to decrease it (e.g., shelter-in-place, masking). We compared the resultant curves' shape, timing, and cumulative case count to baseline and across other modified curves. Interventions led to changes in COVID-19 dynamics, including moving the peak's location, height, and width. The proportion susceptible, at the start day, strongly influenced their impact. Early interventions shifted the curve, while interventions near the peak modified shape and case count. For some scenarios, in which the transmission parameter was decreased, the final cumulative count increased over baseline. We showed that the timing of revocable interventions has a strong impact on their effect. The same intervention applied at different time points, corresponding to different proportions of susceptibility, resulted in qualitatively differential effects. Accurate estimation of the proportion susceptible is critical for understanding an intervention's impact. The findings presented here provide evidence of the importance of estimating the proportion of the population that is susceptible when predicting the impact of behavioral infection control interventions. Greater emphasis should be placed on the estimation of this epidemic component in intervention design and decision-making. Our results are generic and are applicable to other infectious disease epidemics, as well as to future waves of the current COVID-19 epidemic. Developed into a publicly available tool that allows users to modify the parameters to estimate impacts of different interventions, these models could aid in evaluating behavioral intervention options prior to their use and in predicting case increases from specific events.

Anti-SARS-CoV-2 seroprevalence in King County, WA—Cross-sectional survey, August 2020

We conducted a seroprevalence survey to estimate the true number of infections with SARS-CoV-2, the virus that causes COVID-19, in King County as of August 2020 by measuring the proportion of residents from who had antibodies against the virus. Participants from 727 households took part in a cross-sectional address-based household survey with random and non-random samples and provided dried blood spots that were tested for total antibody against the viral nucleocapsid protein, with confirmatory testing for immunoglobulin G against the spike protein. The data were weighted to match King County’s population based on sex, age group, income, race, and Hispanic status. After weighting and accounting for the accuracy of the tests, our best overall estimate of anti-SARS-CoV-2 seroprevalence in King County as of August 2020 is 3.9% (95% confidence interval (CI) 2.4%-6.0%) with an effective sample size of 589. Comparing seroprevalence with positive test reports, our survey suggests that viral testing underestimated incidence by a factor of about five and suggests that the proportion of cases that were serious (based on hospitalization) or fatal was 2.4% and 0.8%, respectively. Prevalence varied by subgroup; households reporting incomes at or below $100,000 in 2019 had nearly five times higher estimated antibody prevalence than those with incomes above $100,000. Those reporting non-White/non-Asian race had roughly seven times higher estimated antibody prevalence than those reporting White race. This survey was noteworthy for including people of all ages; among all age groups, the weighted estimate of prevalence was highest in older teens and young adults and lowest in young children, although these differences were not statistically significant.

A longitudinal study of anti-SARS-CoV-2 antibody seroprevalence in a random sample of the general population in Hiroshima in 2020

BACKGROUND

This longitudinal study aimed to determine chronological changes in the seroprevalence of prior SARS-CoV-2 infection, including asymptomatic infections in Hiroshima Prefecture, Japan.

METHODS

A stratified random sample of 7,500 residents from five cities of Hiroshima Prefecture was selected to participate in a three-round survey from late 2020 to early 2021, before the introduction of the COVID-19 vaccine. The seroprevalence of anti-SARS-CoV-2 antibodies was calculated if at least two of four commercially available immunoassays were positive. Then, the ratio between seroprevalence and the prevalence of confirmed COVID-19 cases in Hiroshima was calculated and compared to the results from other prefectures where the Ministry of Health, Labour and Welfare conducted a survey by using the same reagents at almost the same period.

RESULTS

The numbers of participants in the first, second, and third rounds of the survey were 3025, 2396, and 2351, respectively and their anti-SARS-CoV-2 antibodies seroprevalences were 0.03% (95% confidence interval: 0.00-0.10%), 0.08% (0.00-0.20%), and 0.30% (0.08-0.52%), respectively. The ratio between the seroprevalence and the prevalence of confirmed COVID-19 cases in Hiroshima was 1.2, which was smaller than that in similar studies in other prefectures.

CONCLUSIONS

The seroprevalence of anti-SARS-CoV-2 antibodies in Hiroshima increased tenfold in a half year. The difference between seroprevalence and the prevalence of confirmed COVID-19 cases in Hiroshima was smaller than that in other prefectures, suggesting that asymptomatic patients were more actively detected in Hiroshima.

Successive Wave Analysis to Assess Nonresponse Bias in a Statewide Random Sample Testing Study for SARS-CoV-2

INTRODUCTION

Nonresponse bias occurs when participants in a study differ from eligible nonparticipants in ways that can distort study conclusions. The current study uses successive wave analysis, an established but underutilized approach, to assess nonresponse bias in a large-scale SARS-CoV-2 prevalence study. Such an approach makes use of reminders to induce participation among individuals. Based on the response continuum theory, those requiring several reminders to participate are more like nonrespondents than those who participate in a study upon first invitation, thus allowing for an examination of factors affecting participation.

METHODS

Study participants from the Indiana Population Prevalence SARS-CoV-2 Study were divided into 3 groups (eg, waves) based upon the number of reminders that were needed to induce participation. Independent variables were then used to determine whether key demographic characteristics as well as other variables hypothesized to influence study participation differed by wave using chi-square analyses. Specifically, we examined whether race, age, gender, education level, health status, tobacco behaviors, COVID-19-related symptoms, reasons for participating in the study, and SARS-CoV-2 positivity rates differed by wave.

RESULTS

Respondents included 3658 individuals, including 1495 in wave 1 (40.9%), 1246 in wave 2 (34.1%), and 917 in wave 3 (25%), for an overall participation rate of 23.6%. No significant differences in any examined variables were observed across waves, suggesting similar characteristics among those needing additional reminders compared with early participants.

CONCLUSIONS

Using established techniques, we found no evidence of nonresponse bias in a random sample with a relatively low response rate. A hypothetical additional wave of participants would be unlikely to change original study conclusions. Successive wave analysis is an effective and easy tool that can allow public health researchers to assess, and possibly adjust for, nonresponse in any epidemiological survey that uses reminders to encourage participation.

SARS-CoV-2 seroprevalence around the world: an updated systematic review and meta-analysis

BACKGROUND

Covid-19 has been one of the major concerns around the world in the last 2 years. One of the challenges of this disease has been to determine its prevalence. Conflicting results of the serology test in Covid explored the need for an updated meta-analysis on this issue. Thus, this systematic review aimed to estimate the prevalence of global SARS-CoV-2 serology in different populations and geographical areas.

METHODS

To identify studies evaluating the seroprevalence of SARS-CoV-2, a comprehensive literature search was performed from international databases, including Medline (PubMed), Web of Sciences, Scopus, EMBASE, and CINHAL.

RESULTS

In this meta-analysis, the results showed that SARS-CoV-2 seroprevalence is between 3 and 15% worldwide. In Eastern Mediterranean, the pooled estimate of seroprevalence SARS-CoV-2 was 15% (CI 95% 5-29%), and in Africa, the pooled estimate was 6% (CI 95% 1-13%). In America, the pooled estimate was 8% (CI 95% 6-11%), and in Europe, the pooled estimate was 5% (CI 95% 4-6%). Also the last region, Western Pacific, the pooled estimate was 3% (CI 95% 2-4%). Besides, we analyzed three of these areas separately. This analysis estimated the prevalence in subgroups such as study population, diagnostic methods, sampling methods, time, perspective, and type of the study.

CONCLUSION

The present meta-analysis showed that the seroprevalence of SARS-CoV-2 has been between 3 and 15% worldwide. Even considering the low estimate of this rate and the increasing vaccination in the world, many people are still susceptible to SARS-CoV-2.

Seroprevalence and characteristics of Coronavirus Disease (COVID-19) in workers with non-specific disease symptoms

Background

The population-based serosurveys are essential for estimating Coronavirus Disease-19 (COVID-19) burden and monitoring the progression of this pandemic. We aimed to assess the seroprevalence of SARS-CoV-2 antibodies and potential predictors of seropositivity in the Pakistani population.

Methodology

This population-based seroprevalence study includes consenting subjects from the workplaces (factories, corporates, restaurants, media houses, schools, banks, and hospitals) located in the urban areas of Karachi, Lahore, Multan, Peshawar, and Quetta. We analyzed each subject's serum sample for SARS-CoV-2-IgM and/or IgG antibodies using UNIPER IgG/IgM Rapid COVID-19 Testing Kit. The subject's demographics, exposure history, and symptoms experienced (in last 7 days) were also obtained. The collected data was analyzed using SPSS version 22.0.

Results

The overall seroprevalence of SARS-CoV-2 antibodies was 16.0% (2810/17,764). The total antibody seropositivity was higher in males than females (OR 1.22, 95% CI 1.110–1.340). The symptomatic subjects had 2.18 times higher odds of IgG seropositivity while 1.2 times for IgM seropositivity than the asymptomatic subjects. The multivariable logistic regression model showed that the odds of SARS-CoV-2 total antibody seroprevalence were affected by the number of dependents (OR = 1.077; 95% CI 1.054–1.099), apparent symptomology (OR = 1.288; 95% CI 1.011–1.643), close unprotected contact with a confirmed or probable case of COVID-19 (OR 2.470; 95% CI 2.164–2.819), traveling history (last 14 days) (OR = 1.537; 95% CI 1.234–1.914) and proximity with someone who traveled (OR = 1.534; 95% CI 1.241–1.896).

Conclusion

We found a reasonable seroprevalence of SARS-CoV-2 antibodies in the studied population. Several factors like the number of dependents, apparent symptoms, close unprotected contact with a confirmed or probable case of COVID-19, traveling history, and proximity with someone who traveled are associated with increased odds of SARS-CoV-2 antibody seropositivity.

SARS-CoV-2 Viral Incidence, Antibody Point Prevalence, Associated Population Characteristics, and Vaccine Attitudes, South Carolina, February 2021

The SARS-CoV-2 outbreak from October 2020 through February 2021 was the largest outbreak as of February 2021, and timely information on current representative prevalence, vaccination, and loss of prior antibody protection was unknown. In February 2021, the South Carolina Department of Health and Environmental Control conducted a random sampling point prevalence investigation consisting of viral and antibody testing and an associated health survey, after selecting participants aged ≥5 years using a population proportionate to size of South Carolina residents. A total of 1917 residents completed a viral test, 1803 completed an antibody test, and 1463 completed ≥1 test and a matched health survey. We found an incidence of 2.16 per 100 residents and seroprevalence of 16.4% among South Carolina residents aged ≥5 years. Undetectable immunoglobulin G and immunoglobulin M antibodies were noted in 28% of people with a previous positive test result, highlighting the need for targeted education among people who may be susceptible to reinfection. We also found a low rate of vaccine hesitancy in the state (13%). The results of this randomly selected surveillance and associated health survey have important implications for prospective COVID-19 public health response efforts. Most notably, this article provides a feasible framework for prompt rollout of a statewide evidence-based surveillance initiative.

Seroprevalence and factors associated with SARS-CoV-2 infection among education workers after the first wave: the first cross-sectional study in Brazil

BACKGROUND

The school community was heavily impacted by the Covid-19 pandemic, especially with the long time of school closures. This study aimed to analyze the seroprevalence of SARS-CoV-2 antibodies and possible factors associated with seropositivity for COVID-19 in teachers and other school staff, and to estimate the fraction of asymptomatic individuals by sex and age group.

METHODS

We conducted a serological survey of SARS-CoV-2 infections. An analytical cross-sectional study was conducted in Fortaleza, Brazil. Teachers and other staff members from pre-schools to universities of higher education to were investigated.

RESULTS

A total of 1,901 professionals participated in the study, of which 1,021 were staff and 880 were teachers. The seroprevalence of SARS-CoV-2 was 8.0% (152/1901). In the seropositive group, 48.3% were asymptomatic. There was a predominance of women (68.4%); and, 47.1% of the participants were between 31 and 45 years old. There was an increase in prevalence with increasing age. An inverse relationship was found for education level: more professionals with less education tested positive for COVID-19. The presence of an infected person living in the same household was significantly associated with positive results for COVID-19 among the professionals.

CONCLUSIONS

This is the first study to report the seroprevalence of IgG against SARS-CoV-2 in Brazilian educational staff after the first wave of the disease. In this study, the seroprevalence was much lower than that in the general population. During school reopening, a small fraction of school workers showed serologically detectable signs of SARS-CoV-2 exposure.

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.

Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Seroprevalence in Decedents Undergoing Forensic Postmortem Examination: Feasibility for &#x2028;Real-Time Pandemic Surveillance

Background

Population-based seroprevalence studies offer comprehensive characterization of coronavirus disease 2019 (COVID-19) spread, but barriers exist and marginalized populations may not be captured. We assessed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody seroprevalence among decedents in Maryland over 6 months in 2020.

Methods

Data were collected on decedents undergoing forensic postmortem examination in Maryland from 24 May through 30 November 2020 from whom a blood specimen could be collected. Those with available blood specimens were tested with the CoronaCHEK lateral flow antibody assay. We assessed monthly seroprevalence compared to the statewide estimated number of cases and proportion of positive test results (testing positivity). We used Poisson regression with robust variance to estimate adjusted prevalence ratios (aPRs) with 95% confidence intervals (CIs) for associations of demographic characteristics, homelessness, and manner of death with SARS-CoV-2 antibodies.

Results

Among 1906 decedents, 305 (16%) were positive for SARS-CoV-2 antibodies. Monthly seroprevalence increased from 11% to 22% over time and was consistently higher than state-level estimates of testing positivity. Hispanic ethnicity was associated with 2- to 3.2-fold higher seropositivity (P < .05) irrespective of sex. Deaths due to motor vehicle crash were associated with 62% increased seropositivity (aPR, 1.62 [95% CI, 1.15–2.28]) vs natural manner of death. Though seroprevalence was lower in decedents of illicit drug overdose vs nonoverdose in early months, this shifted, and seroprevalence was comparable by November 2020.

Conclusions

Decedents undergoing forensic postmortem examination, especially those dying due to motor vehicle trauma, may be a sentinel population for COVID-19 spread in the general population and merits exploration in other states/regions.

Severe Acute Respiratory Syndrome Coronavirus 2 Cumulative Incidence, United States, August 2020-December 2020

BACKGROUND

Reported coronavirus disease 2019 (COVID-19) cases underestimate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. We conducted a national probability survey of US households to estimate cumulative incidence adjusted for antibody waning.

METHODS

From August-December 2020 a random sample of US addresses were mailed a survey and self-collected nasal swabs and dried blood spot cards. One adult household member completed the survey and mail specimens for viral detection and total (immunoglobulin [Ig] A, IgM, IgG) nucleocapsid antibody by a commercial, emergency use authorization-approved antigen capture assay. We estimated cumulative incidence of SARS-CoV-2 adjusted for waning antibodies and calculated reported fraction (RF) and infection fatality ratio (IFR). Differences in seropositivity among demographic, geographic, and clinical subgroups were explored.

RESULTS

Among 39 500 sampled households, 4654 respondents provided responses. Cumulative incidence adjusted for waning was 11.9% (95% credible interval [CrI], 10.5%-13.5%) as of 30 October 2020. We estimated 30 332 842 (CrI, 26 703 753-34 335 338) total infections in the US adult population by 30 October 2020. RF was 22.3% and IFR was 0.85% among adults. Black non-Hispanics (Prevalence ratio (PR) 2.2) and Hispanics (PR, 3.1) were more likely than White non-Hispanics to be seropositive.

CONCLUSIONS

One in 8 US adults had been infected with SARS-CoV-2 by October 2020; however, few had been accounted for in public health reporting. The COVID-19 pandemic is likely substantially underestimated by reported cases. Disparities in COVID-19 by race observed among reported cases cannot be attributed to differential diagnosis or reporting of infections in population subgroups.

COVID-19 seroprevalence in Pakistan: a cross-sectional study

OBJECTIVES

This study adapted WHO's 'Unity Study' protocol to estimate the population prevalence of antibodies to SARS CoV-2 and risk factors for developing SARS-CoV-2 infection.

DESIGN

This population-based, age-stratified cross-sectional study was conducted at the level of households (HH).

PARTICIPANTS

All ages and genders were eligible for the study (exclusion criteria: contraindications to venipuncture- however, no such case was encountered). 4998 HH out of 6599 consented (1 individual per HH). The proportion of male and female study participants was similar.

PRIMARY AND SECONDARY OUTCOME MEASURES

Following were the measured outcome measures- these were different from the planned indicators (i.e. two out of the three planned indicators were measured) due to operational reasons and time constraints: -Primary indicators: Seroprevalence (population and age specific).Secondary indicators: Population groups most at risk for SARS-CoV-2-infection.

RESULTS

Overall seroprevalence of SARS-CoV-2 antibodies was 7.1%. 6.3% of individuals were IgG positive while IgM positivity was 1.9%. Seroprevalence in districts ranged from 0% (Ghotki) to 17% (Gilgit). The seroprevalence among different age groups ranged from 3.9% (0-9 years) to 10.1% (40-59 years). There were no significant differences in the overall seroprevalence for males and females. A history of contact with a confirmed COVID-19 case, urban residence and mask use were key risk factors for developing SARS-CoV-2 infection.

CONCLUSIONS

This survey provides useful estimates for seroprevalence in the general population and information on risk factors for developing SARS-CoV-2 infection in the country. It is premised that similar studies need to be replicated at the population level on a regular basis to monitor the disease and immunity patterns related to COVID-19.

Adjusting COVID-19 Seroprevalence Survey Results to Account for Test Sensitivity and Specificity

Population-based seroprevalence surveys can provide useful estimates of the number of individuals previously infected with serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and still susceptible, as well as contribute to better estimates of the case-fatality rate and other measures of coronavirus disease 2019 (COVID-19) severity. No serological test is 100% accurate, however, and the standard correction that epidemiologists use to adjust estimates relies on estimates of the test sensitivity and specificity often based on small validation studies. We have developed a fully Bayesian approach to adjust observed prevalence estimates for sensitivity and specificity. Application to a seroprevalence survey conducted in New York State in 2020 demonstrates that this approach results in more realistic-and narrower-credible intervals than the standard sensitivity analysis using confidence interval endpoints. In addition, the model permits incorporating data on the geographical distribution of reported case counts to create informative priors on the cumulative incidence to produce estimates and credible intervals for smaller geographic areas than often can be precisely estimated with seroprevalence surveys.

Prevalence of COVID-19 in West Gondar Zone, Northwest Ethiopia: A Population-Based Retrospective Study

OBJECTIVE

Coronavirus disease 2019 (COVID-19) has spread rapidly around the world, affecting every community directly or indirectly. Therefore, this study aims to investigate the prevalence of COVID-19 infection in the population of the West Gondar zone.

METHOD

A retrospective cross-sectional study was conducted from November 2020 to January 2021, in the West Gondar zone, Northwest Ethiopia. Records of study participants with required information like age, gender, travel history, type of specimen taken, and site of specimen taken were included. For analysis, the statistical package for social sciences (SPSS) version 20 software was used. Descriptive statistics were summarized as percentages and means ± standard deviation. The chi-squared test is used to compare categorical data.

RESULTS

A total of 1,166 participants were enrolled in this study. Of them, 16 individuals had positive results, giving a prevalence of 1.37% (95% CI: 0.66-2.08). Living in an urban area (P-value = 0.035) and being female (P-value = 0.045) was statistically associated with the positive rate for COVID-19.

CONCLUSIONS

This study revealed a low prevalence of COVID-19 infection in the study area despite the increasing and rapid dissemination of the disease. State-wide population prevalence study should be done to estimate the general prevalence of COVID-19 in Ethiopia.

Analysis of accumulated SARS-CoV-2 seroconversion in North Carolina: The COVID-19 Community Research Partnership

Introduction

The COVID-19 Community Research Partnership is a population-based longitudinal syndromic and sero-surveillance study. The study includes over 17,000 participants from six healthcare systems in North Carolina who submitted over 49,000 serology results. The purpose of this study is to use these serology data to estimate the cumulative proportion of the North Carolina population that has either been infected with SARS-CoV-2 or developed a measurable humoral response to vaccination.

Methods

Adult community residents were invited to participate in the study between April 2020 and February 2021. Demographic information was collected and daily symptom screen was completed using a secure, HIPAA-compliant, online portal. A portion of participants were mailed kits containing a lateral flow assay to be used in-home to test for presence of anti-SARS-CoV-2 IgM or IgG antibodies. The cumulative proportion of participants who tested positive at least once during the study was estimated. A standard Cox proportional hazards model was constructed to illustrate the probability of seroconversion over time up to December 20, 2020 (before vaccines available). A separate analysis was performed to describe the influence of vaccines through February 15, 2021.

Results

17,688 participants contributed at least one serology result. 68.7% of the population were female, and 72.2% were between 18 and 59 years of age. The average number of serology results submitted per participant was 3.0 (±1.9). By December 20, 2020, the overall probability of seropositivity in the CCRP population was 32.6%. By February 15, 2021 the probability among healthcare workers and non-healthcare workers was 83% and 49%, respectively. An inflection upward in the probability of seropositivity was demonstrated around the end of December, suggesting an influence of vaccinations, especially for healthcare workers. Among healthcare workers, those in the oldest age category (60+ years) were 38% less likely to have seroconverted by February 15, 2021.

Conclusions

Results of this study suggest more North Carolina residents may have been infected with SARS-CoV-2 than the number of documented cases as determined by positive RNA or antigen tests. The influence of vaccinations on seropositivity among North Carolina residents is also demonstrated. Additional research is needed to fully characterize the impact of seropositivity on immunity and the ultimate course of the pandemic.

Seroprevalence study of SARS-CoV-2 antibodies in community based on participants in the 2020 Korea National Health and Nutrition Examination Survey (KNHANES)

Objectives

The Korea National Health and Nutrition Examination Survey (KNHANES) is a nationwide cross-sectional surveillance system that assesses the health and nutritional status of the Korean population. To evaluate the occurrence of SARS-CoV-2 infection in the community, we investigated the presence of antibodies against SARS-CoV-2 using the sera of KNHANES participants.

Methods

The subjects were recruited between April 24, 2020, and December 12, 2020. A total of 5,284 subjects aged 10-90 years from 17 regions participated in the survey. SARS-CoV-2 antibodies were screened using the Elecsys Anti-SARS-CoV-2 assay. Positive samples were verified using four different SARS-CoV-2 antibody assays and the plaque reduction neutralizing test (PRNT). The final seropositivity criteria were defined as a positive screening test and at least one positive out of the five additional tests.

Results

The distribution of survey participants was as follows: 49.2% (2,600/5,284) were from a metropolitan area, 48.9% were middle-aged (in their 40s and 60s) and 19.3% were in their 20s or younger. The seropositivity rate among the participants was 0.09% (5/5,284). Out of the five antibody-positive subjects, three had a history of infection, of whom, two were infected abroad while one was infected through a local cluster outbreak.

Conclusion

The low seroprevalence of SARS-CoV-2 antibody in Korea indicates the fewer COVID-19 patients due to succeed of COVID-19 management measures. Moreover, asymptomatic infections were also detected fewer due to active PCR testing. However, hidden infections may still be prevalent in the community, thus requiring continuous quarantine and vaccination.

Towards an Accurate Estimation of COVID-19 Cases in Kazakhstan: Back-Casting and Capture–Recapture Approaches

Background and Objectives: Coronavirus disease 19 (COVID-19) has emerged as the most devastating syndemic of the 21st century, with worrisome and sustained consequences for the entire society. Despite the relative success of vaccination programs, the global threat of the novel coronavirus SARS-CoV-2 is still present and further efforts are needed for its containment and control. Essential for its control and containment is getting closer to understanding the actual extent of SARS-CoV-2 infections. Material and Methods: We present a model based on the mortality data of Kazakhstan for the estimation of the underlying epidemic dynamic—with both the lag time from infection to death and the infection fatality rate. For the estimation of the actual number of infected individuals in Kazakhstan, we used both back-casting and capture–recapture methods. Results: Our results suggest that despite the increased testing capabilities in Kazakhstan, official case reporting undercounts the number of infections by at least 60%. Even though our count of deaths may be either over or underestimated, our methodology could be a more accurate approach for the following: the estimation of the actual magnitude of the pandemic; aiding the identification of different epidemiological values; and reducing data bias. Conclusions: For optimal epidemiological surveillance and control efforts, our study may lead to an increased awareness of the effect of COVID-19 in this region and globally, and aid in the implementation of more effective screening and diagnostic measures.

The 1st year of the COVID-19 epidemic in Estonia: a population-based nationwide sequential/consecutive cross-sectional study

Objectives

The objective of this study was to assess the population prevalence of SARS-CoV-2 and changes in the prevalence in the adult general population in Estonia during the 1^st year of COVID-19 epidemic.

Study design

This was a population-based nationwide sequential/consecutive cross-sectional study.

Methods

Using standardised methodology (population-based, random stratified sampling), 11 cross-sectional studies were conducted from April 2020 to February 2021. Data from nasopharyngeal testing and questionnaires were used to estimate the SARS-CoV-2 RNA prevalence and factors associated with test positivity.

Results

Between April 23, 2020, and February 2, 2021, results were available from 34,915 individuals and 27,870 samples from 11 consecutive studies. The percentage of people testing positive for SARS-CoV-2 decreased from 0.27% (95% confidence interval [CI] = 0.10%–0.59%) in April to 0.04% (95% CI = 0.00%–0.22%) by the end of May and remained very low (0.01%, 95% CI = 0.00%–0.17%) until the end of August, followed by an increase since November (0.37%, 95% CI = 0.18%–0.68%) that escalated to 2.69% (95% CI = 2.08%–2.69%) in January 2021. In addition to substantial change in time, an increasing number of household members (for one additional odds ratio [OR] = 1.15, 95% CI = 1.02–1.29), reporting current symptoms of COVID-19 (OR = 2.21, 95% CI = 1.59–3.09) and completing questionnaire in the Russian language (OR 1.85, 95% CI 1.15–2.99) were associated with increased odds for SARS-CoV-2 RNA positivity.

Conclusions

SARS-CoV-2 population prevalence needs to be carefully monitored as vaccine programmes are rolled out to inform containment decisions.

Seroprevalence of anti-SARS-CoV-2 IgG antibodies, risk factors for infection and associated symptoms in Geneva, Switzerland: a population-based study

Aims: To assess SARS-CoV-2 seroprevalence over the first epidemic wave in the canton of Geneva, Switzerland, as well as risk factors for infection and symptoms associated with IgG seropositivity. Methods: Between April and June 2020, former participants of a representative survey of the 20-74-year-old population of canton Geneva were invited to participate in the study, along with household members aged over 5 years. Blood samples were tested for anti-SARS-CoV-2 immunoglobulin G. Questionnaires were self-administered. We estimated seroprevalence with a Bayesian model accounting for test performance and sampling design. Results: We included 8344 participants, with an overall adjusted seroprevalence of 7.8% (95% credible interval 6.8-8.9). Seroprevalence was highest among 18-49 year-olds (9.5%), and lowest in 5-9-year-old children (4.3%) and individuals >65 years (4.7-5.4%). Odds of seropositivity were significantly reduced for female retirees and unemployed men compared to employed individuals, and smokers compared to non-smokers. We found no significant association between occupation, level of education, neighborhood income and the risk of being seropositive. The symptom most strongly associated with seropositivity was anosmia/dysgeusia. Conclusions: Anti-SARS-CoV-2 population seroprevalence remained low after the first wave in Geneva. Socioeconomic factors were not associated with seropositivity in this sample. The elderly, young children and smokers were less frequently seropositive, although it is not clear how biology and behaviours shape these differences.

Prevalence of current and past COVID-19 in Ohio adults

PURPOSE

To estimate the prevalence of current and past COVID-19 in Ohio adults.

METHODS

We used stratified, probability-proportionate-to-size cluster sampling. During July 2020, we enrolled 727 randomly-sampled adult English- and Spanish-speaking participants through a household survey. Participants provided nasopharyngeal swabs and blood samples to detect current and past COVID-19. We used Bayesian latent class models with multilevel regression and poststratification to calculate the adjusted prevalence of current and past COVID-19. We accounted for the potential effects of non-ignorable non-response bias.

RESULTS

The estimated statewide prevalence of current COVID-19 was 0.9% (95% credible interval: 0.1-2.0%), corresponding to ∼85,000 prevalent infections (95% credible interval: 6,300-177,000) in Ohio adults during the study period. The estimated statewide prevalence of past COVID-19 was 1.3% (95% credible interval: 0.2-2.7%), corresponding to ∼118,000 Ohio adults (95% credible interval: 22,000-240,000). Estimates did not change meaningfully due to non-response bias.

CONCLUSIONS

Total COVID-19 cases in Ohio in July 2020 were approximately 3.5 times as high as diagnosed cases. The lack of broad COVID-19 screening in the United States early in the pandemic resulted in a paucity of population-representative prevalence data, limiting the ability to measure the effects of statewide control efforts.

Retrospective epidemiology of the SARS-CoV-2 (and COVID-19) epidemic among 27 Brazilian cities

Background

Most of the countries facing the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic are still trying to understand the dynamics of the behavior of the virus and dissemination of the new agent.

Objectives

A retrospective descriptive epidemiological study of the 26 state capitals of Brazil and its capital, Brasilia, was performed to investigate the behavior of the infection and disease caused by SARS-CoV-2.

Study design

The data presented were obtained from the State Health Departments and the Brazilian Ministry of Health. Seven epidemiological markers (including the incidence, mortality and case fatality rates and the growth of the epidemic measured by the ratios observed on days 30, 60 and 90) were compared for the initial 90 days of the epidemic for each city.

Results

The epidemic spread to the country within 25 days, and deaths occurred as early as nine days from initiation. The incidence and mortality rates ranged from 70 to almost 1,599/100,000 and less than 1 to 1,171/1,000,000, respectively, at the end of the 90-day period of observation. The CFR was less than two up to 12.31%. The magnitude of each marker clustered the cities in different groups. The epidemic was managed differently in each city, with differences in qualified medical services and medical preparedness to face the emergency situation.

Conclusions

Although modeling the epidemic has been a constant task, epidemiological data should be pursued to define actual information, such as the prevalence and incidence rates, to understand the unpredictable nature of this emerging infection, including the present policy of vaccination campaigns.

Update on SARS-CoV-2 seroprevalence: regional and worldwide

BACKGROUND

With limited vaccine supplies, an informed position on the status of SARS-CoV-2 infection in people can assist the prioritization of vaccine deployment.

OBJECTIVES

We performed a systematic review and meta-analysis to estimate the global and regional SARS-CoV-2 seroprevalences around the world.

DATA SOURCES

We systematically searched peer-reviewed databases (PubMed, Embase and Scopus), and preprint servers (medRxiv, bioRxiv and SSRN) for articles published between 1 January 2020 and 30 March 2021.

STUDY ELIGIBILITY CRITERIA

Population-based studies reporting the SARS-CoV-2 seroprevalence in the general population were included.

PARTICIPANTS

People of different age groups, occupations, educational levels, ethnic backgrounds and socio-economic status from the general population.

INTERVENTIONS

There were no interventions.

METHODS

We used the random-effects meta-analyses and empirical Bayesian method to estimate the pooled seroprevalence and conducted subgroup and meta-regression analyses to explore potential sources of heterogeneity as well as the relationship between seroprevalence and socio-demographics.

RESULTS

We identified 241 eligible studies involving 6.3 million individuals from 60 countries. The global pooled seroprevalence was 9.47% (95% CI 8.99-9.95%), although the heterogeneity among studies was significant (I² = 99.9%). We estimated that ∼738 million people had been infected with SARS-CoV-2 (as of December 2020). Highest and lowest seroprevalences were recorded in Central and Southern Asia (22.91%, 19.11-26.72%) and Eastern and South-eastern Asia (1.62%, 1.31-1.95%), respectively. Seroprevalence estimates were higher in males, persons aged 20-50 years, in minority ethnic groups living in countries or regions with low income and human development indices.

CONCLUSIONS

The present study indicates that the majority of the world's human population was still highly susceptible to SARS-CoV-2 infection in mid-2021, emphasizing the need for vaccine deployment to vulnerable groups of people, particularly in developing countries, and for the implementation of enhanced preventive measures until 'herd immunity' to SARS-CoV-2 has developed.

Design of a population-based longitudinal cohort study of SARS-CoV-2 incidence and prevalence among adults in the San Francisco Bay Area

Purpose

We describe the design of a longitudinal cohort study to determine SARS-CoV-2 incidence and prevalence among a population-based sample of adults living in six San Francisco Bay Area counties.

Methods

Using an address-based sample, we stratified households by county and by census-tract risk. Risk strata were determined by using regression models to predict infections by geographic area using census-level sociodemographic and health characteristics. We disproportionately sampled high and medium risk strata, which had smaller population sizes, to improve precision of estimates, and calculated a desired sample size of 3400. Participants were primarily recruited by mail and were followed monthly with PCR testing of nasopharyngeal swabs, testing of venous blood samples for antibodies to SARS-CoV-2 spike and nucleocapsid antigens, and testing of the presence of neutralizing antibodies, with completion of questionnaires about socio-demographics and behavior. Estimates of incidence and prevalence will be weighted by county, risk strata and sociodemographic characteristics of non-responders, and will take into account laboratory test performance.

Results

We enrolled 3842 adults from August to December 2020, and completed follow-up March 31, 2021. We reached target sample sizes within most strata.

Conclusions

Our stratified random sampling design will allow us to recruit a robust general population cohort of adults to determine the incidence of SARS-CoV-2 infection. Identifying risk strata was unique to the design and will help ensure precise estimates, and high-performance testing for presence of virus and antibodies will enable accurate ascertainment of infections.

Antibody status and cumulative incidence of SARS-CoV-2 infection among adults in three regions of France following the first lockdown and associated risk factors: a multicohort study

BACKGROUND

We aimed to estimate the seropositivity to anti-SARS-CoV-2 antibodies in May-June 2020 after the first lockdown period in adults living in three regions in France and to identify the associated risk factors.

METHODS

Between 4 May 2020 and 23 June 2020, 16 000 participants in a survey on COVID-19 from an existing consortium of three general adult population cohorts living in the Ile-de-France (IDF) or Grand Est (GE) (two regions with high rate of COVID-19) or in the Nouvelle-Aquitaine (NA) (with a low rate) were randomly selected to take a dried-blood spot for anti-SARS-CoV-2 antibodies assessment with three different serological methods (ClinicalTrial Identifier #NCT04392388). The primary outcome was a positive anti-SARS-CoV-2 ELISA IgG result against the spike protein of the virus (ELISA-S). Estimates were adjusted using sampling weights and post-stratification methods. Multiple imputation was used to infer the cumulative incidence of SARS-CoV-2 infection with adjustments for imperfect tests accuracies.

RESULTS

The analysis included 14 628 participants, 983 with a positive ELISA-S. The weighted estimates of seropositivity and cumulative incidence were 10.0% [95% confidence interval (CI): 9.1%, 10.9%] and 11.4% (95% CI: 10.1%, 12.8%) in IDF, 9.0% (95% CI: 7.7%, 10.2%) and 9.8% (95% CI: 8.1%, 11.8%) in GE and 3.1% (95% CI: 2.4%, 3.7%) and 2.9% (95% CI: 2.1%, 3.8%) in NA, respectively. Seropositivity was higher in younger participants [odds ratio (OR) = 1.84 (95% CI: 1.79, 6.09) in <40 vs 50-60 years old and OR = 0.56 (95% CI: 0.42, 0.74) in ≥70 vs 50-60 years old)] and when at least one child or adolescent lived in the same household [OR = 1.30 (95% CI: 1.11, 1.53)] and was lower in smokers compared with non-smokers [OR = 0.71 (95% CI: 0.57, 0.89)].

CONCLUSIONS

Seropositivity to anti-SARS-CoV-2 antibodies in the French adult population was ≤10% after the first wave. Modifiable and non-modifiable risk factors were identified.

Better public decisions on COVID-19: A thought experiment in metrics

Objectives

Poor decision-making is a hallmark of the COVID-19 pandemic. Better metrics would help improve decision-makers' understanding of the scope of the pandemic and allow for better public understanding/review of these decisions.

Study design

Two novel metrics of disease impact were compared with more commonly used standard metrics.

Methods

A multi-criteria decision analysis technique, used previously to support metric selection in solid waste planning, was adapted to compare number of deaths, hospitalisations, positive test results and positivity rates (standard COVID-19 impact metrics) with a simple model that estimates the total number of potentially infectious people in an area and an associated odds ratio for infectious people.

Results

The odds ratio and total infectious population estimate metrics scored better in a comparison analysis than number of deaths, hospitalisations, positive test results and positivity rates (in that order).

Conclusions

The novel metrics provide a more effective means of communication than other more common measures of the outbreak. These superior metrics should support decision-making processes and result in a more informed population.

Disparities in COVID-19 Outcomes by Race, Ethnicity, and Socioeconomic Status: A Systematic-Review and Meta-analysis

IMPORTANCE

COVID-19 has disproportionately affected racial and ethnic minority groups, and race and ethnicity have been associated with disease severity. However, the association of socioeconomic determinants with racial disparities in COVID-19 outcomes remains unclear.

OBJECTIVE

To evaluate the association of race and ethnicity with COVID-19 outcomes and to examine the association between race, ethnicity, COVID-19 outcomes, and socioeconomic determinants.

DATA SOURCES

A systematic search of PubMed, medRxiv, bioRxiv, Embase, and the World Health Organization COVID-19 databases was performed for studies published from January 1, 2020, to January 6, 2021.

STUDY SELECTION

Studies that reported data on associations between race and ethnicity and COVID-19 positivity, disease severity, and socioeconomic status were included and screened by 2 independent reviewers. Studies that did not have a satisfactory quality score were excluded. Overall, less than 1% (0.47%) of initially identified studies met selection criteria.

DATA EXTRACTION AND SYNTHESIS

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Associations were assessed using adjusted and unadjusted risk ratios (RRs) and odds ratios (ORs), combined prevalence, and metaregression. Data were pooled using a random-effects model.

MAIN OUTCOMES AND MEASURES

The main measures were RRs, ORs, and combined prevalence values.

RESULTS

A total of 4 318 929 patients from 68 studies were included in this meta-analysis. Overall, 370 933 patients (8.6%) were African American, 9082 (0.2%) were American Indian or Alaska Native, 101 793 (2.4%) were Asian American, 851 392 identified as Hispanic/Latino (19.7%), 7417 (0.2%) were Pacific Islander, 1 037 996 (24.0%) were White, and 269 040 (6.2%) identified as multiracial and another race or ethnicity. In age- and sex-adjusted analyses, African American individuals (RR, 3.54; 95% CI, 1.38-9.07; P = .008) and Hispanic individuals (RR, 4.68; 95% CI, 1.28-17.20; P = .02) were the most likely to test positive for COVID-19. Asian American individuals had the highest risk of intensive care unit admission (RR, 1.93; 95% CI, 1.60-2.34, P < .001). The area deprivation index was positively correlated with mortality rates in Asian American and Hispanic individuals (P < .001). Decreased access to clinical care was positively correlated with COVID-19 positivity in Hispanic individuals (P < .001) and African American individuals (P < .001).

CONCLUSIONS AND RELEVANCE

In this study, members of racial and ethnic minority groups had higher risks of COVID-19 positivity and disease severity. Furthermore, socioeconomic determinants were strongly associated with COVID-19 outcomes in racial and ethnic minority populations.

Reliably quantifying the evolving worldwide dynamic state of the COVID-19 outbreak from death records, clinical parametrization, and demographic data

The dynamic characterization of the COVID-19 outbreak is critical to implement effective actions for its control and eradication but the information available at a global scale is not sufficiently reliable to be used directly. Here, we develop a quantitative approach to reliably quantify its temporal evolution and controllability through the integration of multiple data sources, including death records, clinical parametrization of the disease, and demographic data, and we explicitly apply it to countries worldwide, covering 97.4% of the human population, and to states within the United States (US). The validation of the approach shows that it can accurately reproduce the available prevalence data and that it can precisely infer the timing of nonpharmaceutical interventions. The results of the analysis identified general patterns of recession, stabilization, and resurgence. The diversity of dynamic behaviors of the outbreak across countries is paralleled by those of states and territories in the US, converging to remarkably similar global states in both cases. Our results offer precise insights into the dynamics of the outbreak and an efficient avenue for the estimation of the prevalence rates over time.

SARS-CoV-2 antibody seroprevalence and associated risk factors in an urban district in Cameroon

The extent of SARS-CoV-2 circulation in many African countries remains unclear, underlining the need for antibody sero-surveys to assess the cumulative attack rate. Here, we present the results of a cross-sectional sero-survey of a random sample of residents of a health district in Yaounde, Cameroon, conducted from October 14 to November 26, 2020. Among the 971 participants, the test-adjusted seroprevalence of anti-SARS-CoV-2 IgG antibodies was 29·2% (95% CI 24·3-34·1). This is about 322 times greater than the 0.09% nationwide attack rate implied by COVID-19 case counts at the time. Men, obese individuals and those living in large households were significantly more likely to be seropositive, and the majority (64·2% [58·7-69·4]) of seropositive individuals reported no symptoms. Despite the high seroprevalence, most of the population had not been infected with SARS-CoV-2, highlighting the importance of continued measures to control viral spread and quick vaccine deployment to protect the vulnerable.

Association of Health Status and Nicotine Consumption with SARS-CoV-2 positivity rates

Background

Much of what is known about COVID-19 risk factors comes from patients with serious symptoms who test positive. While risk factors for hospitalization or death include chronic conditions and smoking; less is known about how health status or nicotine consumption is associated with risk of SARS-CoV-2 infection among individuals who do not present clinically.

Methods

Two community-based population samples (including individuals randomly and nonrandomly selected for statewide testing, n = 8214) underwent SARS-CoV-2 testing in nonclinical settings. Each participant was tested for current (viral PCR) and past (antibody) infection in either April or June of 2020. Before testing, participants provided demographic information and self-reported health status and nicotine and tobacco behaviors (smoking, chewing, vaping/e-cigarettes). Using descriptive statistics and a bivariate logistic regression model, we examined the association between health status and use of tobacco or nicotine with SARS-CoV-2 positivity on either PCR or antibody tests.

Results

Compared to people with self-identified “excellent” or very good health status, those reporting “good” or “fair” health status had a higher risk of past or current infections. Positive smoking status was inversely associated with SARS-CoV-2 infection. Chewing tobacco was associated with infection and the use of vaping/e-cigarettes was not associated with infection.

Conclusions

In a statewide, community-based population drawn for SARS-CoV-2 testing, we find that overall health status was associated with infection rates. Unlike in studies of COVID-19 patients, smoking status was inversely associated with SARS-CoV-2 positivity. More research is needed to further understand the nature of this relationship.

Supporting Health Equity Through Data-Driven Decision-Making: A Local Health Department Response to COVID-19

COVID-19 highlights preexisting inequities that affect health outcomes and access to care for Black and Brown Americans. The Marion County Public Health Department in Indiana sought to address inequities in COVID-19 testing by using surveillance data to place community testing sites in areas with the highest incidence of disease. Testing site demographic data indicated that targeted testing reached populations with the highest disease burden, suggesting that local health departments can effectively use surveillance data as a tool to address inequities. (Am J Public Health. 2021;111(S3):S197-S200. https://doi.org/10.2105/AJPH.2021.306421).

Cohort profile: a national, community-based prospective cohort study of SARS-CoV-2 pandemic outcomes in the USA-the CHASING COVID Cohort study

PURPOSE

The Communities, Households and SARS-CoV-2 Epidemiology (CHASING) COVID Cohort Study is a community-based prospective cohort study launched during the upswing of the USA COVID-19 epidemic. The objectives of the cohort study are to: (1) estimate and evaluate determinants of the incidence of SARS-CoV-2 infection, disease and deaths; (2) assess the impact of the pandemic on psychosocial and economic outcomes and (3) assess the uptake of pandemic mitigation strategies.

PARTICIPANTS

We began enrolling participants from 28 March 2020 using internet-based strategies. Adults≥18 years residing anywhere in the USA or US territories were eligible. 6740 people are enrolled in the cohort, including participants from all 50 US states, the District of Columbia, Puerto Rico and Guam. Participants are contacted regularly to complete study assessments, including interviews and dried blood spot specimen collection for serologic testing.

FINDINGS TO DATE

Participants are geographically and sociodemographically diverse and include essential workers (19%). 84.2% remain engaged in cohort follow-up activities after enrolment. Data have been used to assess SARS-CoV-2 cumulative incidence, seroincidence and related risk factors at different phases of the US pandemic; the role of household crowding and the presence of children in the household as potential risk factors for severe COVID-19 early in the US pandemic; to describe the prevalence of anxiety symptoms and its relationship to COVID-19 outcomes and other potential stressors; to identify preferences for SARS-CoV-2 diagnostic testing when community transmission is on the rise via a discrete choice experiment and to assess vaccine hesitancy over time and its relationship to vaccine uptake.

FUTURE PLANS

The CHASING COVID Cohort Study has outlined a research agenda that involves ongoing monitoring of the incidence and determinants of SARS-CoV-2 outcomes, mental health outcomes and economic outcomes. Additional priorities include assessing the incidence, prevalence and correlates of long-haul COVID-19.