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Our take —

The study, available as a preprint and thus not yet peer-reviewed, sought to describe the COVID-19-related mortality disparity among Native Americans in the US. The study found a standardized mortality ratio of 2.77 compared to white populations, and this was even higher in some states, with South Dakota having a mortality ratio of 9.7 as compared to the white population. They found that the standardized mortality ratio was highly correlated with cthe perent of Native Americans living on reservations. The study had many limitations due to its ecological study design, including use of data collected as far back as 2014, and potential underreporting of Native American race/ethnicity. Regardless, results show a high level of disparity in Native American mortality from COVID-19 compared to other racial/ethnic populations in the US.

Study design

Cross-Sectional, Ecological

Study population and setting

The study sought to describe risk factors for COVID-19 infection and related mortality among Native American/American Indian communities in the US. COVID-19-related death counts from the National Center for Health Statistics from January 1, 2020, through January 16, 2021 were used. Midyear population estimates of 2019 were drawn from the US Census Bureau data from 10 states: Arizona, California, Oklahoma, New Mexico, Washington, New York, South Dakota, Minnesota, Utah, and Mississippi. The American Community Survey (ACS) and the Behavioral Risk Factor Surveillance System (BRFSS) were used to estimate potential risk factors that may impact transmission and mortality. For the ACS, the analysis used 2014 – 2018 data to estimate the type of health insurance, income-poverty ratio, and household living arrangements. They also extracted data on frontline worker status using data from 2018. They used the BRFSS from 2011 to 2018 to estimate smoking status and health conditions including asthma, chronic obstructive pulmonary disease (COPD), kidney disease, cancer, heart disease, diabetes, and obesity. More recent ACS or BRFSS versions were not yet available. Finally, they utilized data from MultiState, which generates a rating of open-ness during the pandemic based on state policies and capacity/industry restrictions. They categorized race as non-Latino Native American (including American Indian and Alaskan Native), non-Latino white, non-Latino Black, and Latino, and using the My Tribal Area tool, integrated 2014 – 2018 ACS estimates of Native Americans living on- vs. off-reservation. They generated standardized mortality ratios compared to the 3 other racial categories overall and by state. They disaggregated this based on reservation living status, occupation, and chronic health conditions and behavioral risk factors, generating correlation estimates for each.

Summary of Main Findings

In this study, 2,789 COVID-19-related deaths were estimated from January 1, 2020 to January 16, 2021 among Native Americans. They estimated a crude death rate of 1.63 times that among the US white population, and a standardized mortality ratio of 2.77. This was greater than the standardized mortality ratio within the Black population (1.64) and the Latino population (1.81). Stratifying by state, they found geographic differences as well, with South Dakota having the highest standardized mortality ratio at 9.7 compared to the state’s White population, while California had the lowest at 1.6 times the mortality to the state’s White population. The standardized mortality ratios for the 10 states were correlated with increasing percentages of Native Americans living on reservations (correlation = 0.8). In their sociodemographic and behavioral correlations, they found the income-poverty ratio was highly negatively correlated with the standardized mortality ratio (-0.86).

Study Strengths

The study made use of a wide range of data to describe the health disparities impacting Native Americans, an often underreported population. They disaggregated by meaningful variables indicative of structural risks of disease, such as living on a reservation which may impact access to health services, and living in multigenerational or crowded households, and having insurance. They also examined individual-level factors, such as clinical risks through COPD and diabetes.

Limitations

The study’s primary limitation was that they used many different data sources which may have different reporting guidelines and criteria. Therefore, these results paint an overall picture of Native American health and health disparities, but do not generate individual-level estimates of risk factors and are limited to standardization by age and place alone.. They also limited their analysis to individuals reporting Native American as their only race, which likely underreports the true number of Native American people in the US. This standardization does not reflect differences in the underlying clinical health between white and Native American populations likely due to differences in access to health services and clinical care, and may be biased. They also used data from prior years going as far back as 2014 which may not reflect more recent trends in disease and social factors.

Value added

This is a large study of Native American people in the US, reflecting the health disparities they face compared to white and other racial/ethnic groups.

Our take —

This cross-sectional study examined the seroprevalence and symptom onset of SARS-CoV-2 infection among Orthodox Jewish communities in 5 US states. They found high prevalence of reported symptoms (61.0%) and high seroprevalence overall (30.1%) using antibody testing. Symptom onset was most frequent in March 2020, generally between March 9 and 31. The study’s primary limitation was the use of antibody testing which only reflects ever having been infected, and not whether onset of presumed COVID-19 symptoms actually corresponded to SARS-CoV-2 infection. Therefore, these estimates may not accurately reflect incident disease over the entire study period, but rather history of an illness and a SARS-CoV-2 infection. Further, estimates may under or overrepresent individuals based on infection severity or presumption, or community sub-group and thus should be interpreted with these caveats.

Study design

Cross Sectional

Study population and setting

The objective of this cross-sectional study was to understand the signs and symptoms, and seroprevalence, of SARS-CoV-2 in a cultural community with reported high rates of infection across 5 states in the US: New York, New Jersey, Connecticut, California, and Michigan. Participants were recruited in partnership with local non-profit and social service organizations serving Orthodox Jewish people 18 years and older. In the first stage of recruitment, which aimed to determine self-reported symptoms and infection, 12,626 individuals began the survey, 9,507 completed the it (75.3% completion) and 603 had obtained a positive PCR test (6.6%) during their illness. In the second stage of recruitment, a subset totaling 6,665 adults (70.1% response rate) had antibody testing following survey completion. Of the 6,665 in the antibody cohort, 422 (6.4%) obtained a positive PCR test during their illness and 2004 (30.1%) had a positive antibody test at the time of the study. The survey included patient demographics, symptoms of COVID-19, date of symptom onset, and whether they had been tested for SARS-CoV-2 by nasal swab.

Summary of Main Findings

In the full survey cohort, 61.0% (N=5803) of people in the survey cohort reported symptoms at any point in the study. The earliest date of symptom onset with a positive nasal swab test was on February 8, 2020 in Michigan. The median and mode dates of symptom onset occurred within the same 1-week period from March 13 to 20 across all sites. In the antibody cohort (N=6,665 individuals), 2004 individuals tested positive via antibody test (30.1%). The highest seroprevalence was in New Jersey (32.5%, N=1080), followed by New York (30.5%, N=671). As in the full cohort, most individuals within the antibody cohort reported symptom onset between March 9 and March 31, though the earliest reported date with an eventual positive antibody test was in New Jersey on December 18, 2019.

Study Strengths

The study’s main strength was the large number of Orthodox Jewish people who participated in the study, allowing the researchers to examine geographic differences and describe the temporal trends in symptom onset across multiple states. They additionally noted that the date of median and mode onset were approximately 7 to 10 days following a major Jewish festival (Purim) across all sites. They also were able to accurately describe prior infection using seroprevalence measures with their antibody testing.

Limitations

The primary limitation was that the researchers only had cross-sectional data available to them reflecting ever-infection through antibody testing, and then self-reported symptoms. For instance, for individuals reporting very early symptom onset in December and January, it was not possible to determine if this was SARS-CoV-2 infection or an unrelated respiratory illness and they later became infected with SARS-CoV-2 which was then captured by the antibody test. Additionally, the study only included cases of disease where participants could participate in the community, as opposed to hospital-based data collection. Therefore, it may not have reflected cases of severe disease. There also may have been volunteer bias, with individuals suspecting they had SARS-CoV-2 being more likely to participate than others, which would inflate their estimate of seroprevalence. Additionally, the population was largely Ashkenazi Jewish with limited racial diversity, thereby reflecting primarily white Orthodox Jewish people and not Orthodox Jewish people of color.

Value added

The study is the largest to date of a tight-knit religious and cultural community that experienced high prevalence of COVID-19 during the pandemic.

Our take —

In a survey of 742 non-remote employees working in a non-healthcare setting in the US between March and June 2020, about half (45.6%) reported occupational use of protective equipment for COVID-19 prevention (e.g., face shields, masks). Fewer than a third of participants (28.9%) reported voluntary use of protective equipment if their employers did not mandate nor prohibit it. These survey data were weighted to match the US population, however, the prevalence and effect estimates may have been biased. For example, the researchers depended on mail-based recruitment, which is most likely to reach people with stable addresses, and self-reported data, in which people may misrepresent themselves.

Study design

Cross-Sectional

Study population and setting

A sample of US adults (aged 18 and older) were recruited randomly by mail in June 2020 to participate in an online survey measuring COVID-19 precautions in the workplace. Analyses were restricted to participants who self-reported working in non-healthcare settings and in-person from March 2020 onwards. The relationship between employer provision of protective equipment for COVID-19 mitigation in the workplace (e.g., masks, face shields, other personal protective equipment) and voluntary use of protective equipment were investigated using risk differences, estimated from weighted regression models.

Summary of Main Findings

Among 742 participants retained in the analysis, half (45.6%) reported using protective equipment in the workplace—over half (55.5%) of whom were required by their employers to do so. Among those who did not use protective equipment in the workplace, a majority (77.2%) perceived not needing them in the workplace. Compared to higher-income adults, lower-income adults were less likely to report using protective equipment (22.3% vs. 48.9%) and that their employer mandated using protective equipment (22.3% vs. 27.7%), but were more likely to report being unable access protective equipment (12.6% vs. 4.5%) and were prohibited from using protective equipment (6.8% vs. 2.5%). Protective equipment was reported as being used by one quarter (28.9%) of participants whose workplaces had no policies mandating or prohibiting the use of protective equipment. Controlling for occupation type and self-reported proximity to others in the workplace, voluntary use of protective equipment was 22.3% higher among adults provided with protective equipment in the workplace relative to adults whose employers did not provide protective equipment.

Study Strengths

Investigators captured multiple response options (i.e., inability to obtain, prohibited from using, required use, provided but not required use) to measure workplace policies governing occupational provision and use of protective equipment.

Limitations

Mail-based recruitment may have oversampled adults whose experiences and behaviors are different from those who were unable to participate, potentially producing biased prevalence and effect estimates. Additionally, because the survey was fielded at a single point in time (June 2020), results may not be representative of employed adults at other points in time. Because these were self-reported data, investigators could not confirm personal protective equipment usage or workplace provision of protective equipment.

Value added

This is among the first studies to estimate the prevalence of provision and use of protective equipment for COVID-19 prevention in non-healthcare occupational settings in the United States.

Our take —

Among healthcare workers at the Panzi General Referral Hospital in Bukavu, Democratic Republic of Congo, the prevalence of SARS-CoV-2 antibodies was 41.2% (148/359). Less than a quarter of those with positive antibodies were able to recall any symptoms suggestive of symptomatic COVID-19 disease, and none had prior severe disease (i.e. hospitalization or death). Further research is needed to understand levels of community transmission in this setting and the extent to which asymptomatic infections among healthcare workers contribute to community spread via nosocomial and household transmission how the burden of disease may compare between healthcare workers and non-healthcare workers.

Study design

Cross-Sectional

Study population and setting

Between July 2 and August 19, 2020, healthcare workers at the Panzi General Referral Hospital in Bukavu, Democratic Republic of Congo were asked to participate in a voluntary study. The study involved collection of a brief survey regarding medical history and current or past symptoms and serological testing. Serological testing was performed using a QuickZen COVID-19 IgM/IgG rapid point-of-care test kit and confirmed using Euroimmun Anti-SARS-CoV-2 ELISA IgG assay.

Summary of Main Findings

A total of 359 healthcare workers, or 91.4% of all working staff members (n=393), participated in the study. 41.2% (n=148) tested positive for SARS-CoV-2 IgG antibodies by the Euroimmun assay. Based on findings from the questionnaire, 22.3% (33/148) of healthcare workers who tested positive for SARS-CoV-2 antibodies reported prior symptoms suggestive of COVID-19 illness, with none suffered from severe COVID-19 (i.e. hospitalization or death).

Study Strengths

The level of participation was high, and so the numbers reported here likely represent a fairly good picture of seroprevalence for this population of healthcare workers. Confirmation testing using ELISA reduced misclassification of antibody status.

Limitations

This was a cross-sectional study, and therefore recall of prior symptoms may have been poor. This study was not able to establish the relative burden of prior infection among healthcare workers compared with the general community, because measurement of SARS-CoV-2 antibodies was only done among healthcare workers.

Value added

Serological testing in sub-Saharan Africa to date has been limited, and this study provides valuable insight into the levels of exposure to SARS-CoV-2 in a healthcare setting in the Democratic Republic of Congo.

Our take —

This was a cross-sectional study, available as a preprint and thus not yet peer reviewed, conducted in November 2020, studying SARS-CoV-2 transmission among 24 randomly selected Berlin, Germany school classes and their connected households. Among students, infection prevalence was 2.7% (9/338). Among staff and household members, infection prevalence was 1.4% (2/140) and 2.3% (14/611), respectively. There were no secondary infections detected in school settings one week after initial testing; the attack rate among household contacts was 1.1%. This study is promising in that it shows that school-based transmission was low , even during a peak transmission period. Still, results should be interpreted with caution as they represent a single, very brief time period.

Study design

Cross-Sectional

Study population and setting

Between November 2 and 16, 2020, the initial peak of Germany’s second wave, SARS-CoV-2 transmission was studied among 24 randomly selected Berlin school classes (one class per 24 schools; classes were selected from grades 3-5 and 9-12) and their connected households. Both RT-PCR (SARS-CoV-2 infection) and ELISA tests (anti-SARS-CoV-2-IgG) were performed on oro-nasopharyngeal swabs and finger-prick blood samples from all students and staff. For all household contacts, self-swabs were collected, and they provided finger-prick samples at mobile clinics setup at school. A digital questionnaire was completed by all participants two days prior to the study visit day. Infection prevention and control measures happening in the schools were documented. In any classes with identified SARS-CoV-2 infection, school attendees and household members were re-tested one week later using self-swabs for data collection.

Summary of Main Findings

The study was made up of 1119 participants (352 students, 142 staff, and 625 household members). All schools had signs of hand hygiene, soap and water in restrooms, and air ventilation at least three times per day. 15 of the 24 schools (65%) did not have an obligatory facemask obligation within the classroom, but all had one for interaction outside of the classroom. Among students, infection prevalence was 2.7% (95% CI: 1.2-5.0%; n= 9/338). Among staff and household members, infection prevalence was 1.4% (0.2-5.1%; 2/140) and 2.3% (1.2-3.8%; n=14/611), respectively. Among students, IgG antibodies were detected in 2.0% (0.8-4.1%; n=7/347) of samples. Among staff and household members, IgG antibodies were detected in 1.4% (0.2-5.0%; n=2/141) and 1.4% (0.6-2.7%; n=8/576), respectively. In the one-week period following initial infections, no school-related secondary infections were detected, while the attack rate in households was 1.1% ([0.3-2.9]; n=4/352 persons with exposed index participant following the initial cross-sectional assessment.

Study Strengths

Classrooms were selected at random, indicating that in expectation, there should be no characteristics of the classrooms that would make them have a different infection prevalence than other classrooms in Berlin. The use of both PCR and antibody testing on all individuals regardless of symptoms is an additional strength.

Limitations

These data were cross-sectional and represented a small window of time (less than a month); less can be said using these data on trends in transmission over time, and it is unclear whether what was captured here was representative of a larger period or not. The total number of events (cases) was small, making it difficult to describe differences by the use of different infection prevention and control measures.

Value added

This study provides a snapshot of potential transmission of SARS-CoV-2 in 24 classrooms and their associated households in Berlin, Germany.

Our take —

This study, available as a preprint and thus not yet peer-reviewed, was conducted in September 2020 and assessed demographic and behavioral factors associated with history of SARS-CoV-2 infection among college students from Indiana University Bloomington (UIB). Overall, 1,239 randomly sampled students completed a behavioral survey, and 1,076 students were administered serological testing to assess for historical SARS-CoV-2 infection. Among study participants, 4.6% were confirmed to have a history of SARS-CoV-2 infection and 10.3% self-reported a history of SARS-CoV-2 infection. Among students who tested positive for SARS-CoV-2 antibodies and had complete self-reported testing data, 63% self-reported a history of SARS-CoV-2 infection. Sorority or fraternity membership, multiple romantic partners, knowing someone in one’s immediate environment with SARS-CoV-2 infection, drinking alcohol more than 1 day per week, and interacting with more than 4 people when drinking alcohol were associated with seropositivity and SARS-CoV-2 infection history. Data should be interpreted with caution however, as they were assessed in September 2020, around the time of return to college, and may largely reflect infection history predating return to college.

Study design

Cross-sectional

Study population and setting

This study assessed demographic and behavioral factors associated with laboratory based and self-reported SARS-CoV-2 infection among college students. A random sample of undergraduate students was recruited from Indiana University Bloomington (UIB). Eligible participants were age 18 years or older, a current IUB undergraduate student, and currently residing in Monroe County, Indiana in September 2020. Overall, 1,397 students consented to participate of whom 1,239 participated in the socio-behavioral questionnaire, and serological testing data were available for 1,076 students. The study included a self-reported socio-behavioral questionnaire covering age, biological sex, engagement in campus and social activities, alcohol use and relationship status, and a SARS-CoV-2 IgM/IgG rapid assay kit to assess the presence of antibodies as a measure for history of infection.

Summary of Main Findings

Among study participants, 4.6% (95% CI: 3.3%, 5.8%) were confirmed to have a history of SARS-CoV-2 infection, and the prevalence of self-reported SARS-CoV-2 infection history was 10.3% (95% CI: 8.6%, 12.0%). Among students who tested positive for SARS-CoV-2 antibodies and had complete self-reported testing data (N=46), 63% self-reported a history of SARS-CoV-2 infection (=29). Sorority or fraternity membership, multiple romantic partners, knowing someone in one’s immediate environment with SARS-CoV-2 infection, drinking alcohol more than 1 day per week, and hanging out with more than 4 people when drinking alcohol were associated with both seropositivity and self-reported SARS-CoV-2 infection history.

Study Strengths

This study included college students who were recruited through random sampling. This study leveraged a socio-behavioral questionnaire and serological testing to assess potential risk factors with history of SARS-CoV-2 infection.

Limitations

Temporality could not be established because the data were collected cross-sectionally, therefore the risk factors assessed could have occurred prior to SARS-CoV-2 infection. This analysis also reported descriptive measures of associations, and therefore, it cannot be assumed that any of these factors are causally associated with infection. Additionally, given that this study was conducted in September (beginning of the school year), infections may have been occurred during social activities unrelated to the college setting. Among 7,499 students recruited and 4,069 presumed eligible, 2,651 did not respond or did not sign the consent form and 21 explicitly refused. Selection bias may be present if enrolled individuals differed from those who refused or did not respond to the study invitation.

Value added

This study leveraged a random sample of college students to assess potential risk factors with history of SARS-CoV-2 infection using both serological testing and self-reported measures.

Our take —

In a large survey of over 300,000 US residents aged 13 and older between June 3 and July 27, 2020, 85% of respondents said they were “very likely” to wear a mask while grocery shopping, while only 40% were “very likely” to wear a mask while visiting family and friends. In an analysis conducted at the state level, the authors estimated that an increase of 10% in self-reported mask wearing by this measure was associated with a more than threefold increase in the odds of epidemic control, as defined by an estimated SARS-CoV-2 reproduction number below 1. Although these results support the consensus that mask use is an effective component of transmission control, they should be interpreted cautiously for multiple reasons including survey representativeness, crude measures of exposure and outcome, and likely unmeasured confounding.

Study design

Cross-sectional; Ecological

Study population and setting

This study related US state-level self-reported mask use to transmission control, as measured by an estimate of the reproduction number (Rt) of SARS-CoV-2. Mask use was assessed with a survey delivered by the SurveyMonkey.com online platform and answered by 378,207 individuals 13 years or older between June 3 and July 27, 2020. Results were analyzed as unweighted data and by weighting for age, race, sex, education, geography, and political affiliation to reflect the composition of the U.S. population. Respondents were asked how likely they were to wear a mask “while grocery shopping” or “while visiting with family or friends in their homes,” on a four-point scale ranging from “very likely to “not at all.” A binary classification of mask-wearing was created, defined as responding “very likely” to both questions. Individual mask use data were then aggregated at the state-level each week: this was the primary exposure measurement of mask community use used in subsequent models. Logistic regression models were fit to aggregated state-level weekly estimates of Rt that were dichotomized as either below or above 1 (epidemic slowing vs. epidemic growing). Models were adjusted for several possible confounding variables, including physical distancing (defined by state-level weekly time spent at home relative to a baseline period, measured with aggregated mobility data from Google), state population density, proportion of non-white respondents, and a linear time trend.

Summary of Main Findings

A high proportion (84.7%) of respondents reported that they would be very likely to wear masks at the grocery store, while only 40.2% reported they would be very likely to wear masks while visiting family and friends; 39.8% answered “very likely” to both questions. Self-reported mask use increased linearly with age and was higher among women, nonwhite people, and people with lower income. Mask use varied considerably by geographic region, and was highest on both coasts, along the southern border, and in urban areas. In multivariable logistic regression, self-reported mask use was associated with transmission control (defined as Rt <1): a 10% increase in mask use had an estimated odds ratio for epidemic control of 3.53 (95% CI: 2.03 to 6.43). Results were broadly similar, though attenuated in some instances, under other assumptions including alternative Rt estimates, an alternative definition of mask wearing, dichotomizing Rt at different thresholds, and using self-reported community contacts rather than mobility data. A separate analysis found no association between state-level mask mandates and changes in self-reported mask use.

Study Strengths

This study employed self-reported mask-wearing behavior, rather than mask policies, as the exposure of interest. The sample size was large and was weighted to match the distribution of some US demographic variables. The authors performed a range of sensitivity analyses.

Limitations

Self-reported mask-wearing behavior is subject to bias; for example, respondents may have provided answers in line with perceived social desirability, and this may have occurred differently across geographic regions. The survey was administered via a web platform, and thus respondents are more likely to have internet access than the broader U.S. population, and may have been non-representative in other ways. Moreover, those who responded to the survey may have systematically differed from those who did not respond, which is particularly concerning given that the response rate was only 11%. The measure of dichotomous mask-wearing was crude and may have ignored meaningful gradations in behavior. The outcome measure was similarly crude, and more problematic, since the time-varying reproduction number at the state level is determined by a heterogeneous array of factors, many of which relate to geographically specific transmission dynamics. It is unlikely that the potential confounding variables included in the model (including a linear time trend) adequately accounted for determinants of Rt that may also be related to self-reported mask use. Lastly, self-reported mask use may have been affected by characteristics of local epidemics that were not entirely accounted for by adjusting for prior peak Rt (e.g., test positivity rate, local hospital capacity, local social distancing policies).

Value added

Many prior ecological studies of mask-wearing effectiveness relied on mask mandates and policies; this is one of the few to measure self-reported mask use at a large scale.

Our take —

The study, available as a preprint and thus not yet peer reviewed, showed that Pfizer/BioNTech vaccine-induced antibodies are reactive against an important mutation in the two newly reported SARS-CoV-2 variants. While these results are encouraging, testing the efficacy against the whole set of mutations in these new variants is essential. In addition, continuous monitoring of vaccinated individuals will ultimately determine the degree and longevity of protection the vaccine provides against these variants.

Study design

Cross-Sectional

Study population and setting

The study included samples from 20 participants from the Pfizer/ BioNTech’s phase3 SARS-CoV-2 clinical trial. The sera were collected from participants at 2 and 4 weeks after the second standard dose of the vaccine. The authors tested the ability of these sera to prevent the infection of cultured cells with SARS-CoV-2 with and without a mutation at the amino acid 501, a common mutation in the receptor binding domain between the newly described UK and South-African variants.

Summary of Main Findings

The study found that there was no reduction in the neutralization activity of the sera from the previously vaccinated participants against a mutant virus.

Study Strengths

Recently, new SARS-CoV-2 genetic variants were reported initially in UK and South Africa and subsequently were detected in many other countries. These variants are of public health interest because they are associated with recent increases in cases. As these variants have mutations in the spike protein, the target of many vaccines including those developed by Pfizer/BioNTech and Moderna, they raised the concerns about the efficacy of the current vaccines against these variants. This study tested the ability of the vaccine-induced antibodies to neutralize SARS-CoV-2 viral particles carrying one of the mutations that changes the amino acid number 501 from asparagine to tyrosine. This mutation was found in both the UK and South African variants and was shown to increase the binding of the virus to its receptor. The study included 20 participants and the sera from these participants were simultaneously tested against both the mutant and wildtype viruses.

Limitations

The study is relatively small, and included only one mutation in the viral spike protein and not the full set of changes seen in the new variants. The sera tested was also taken soon after the second dose of the vaccine and may not reflect the neutralization potential later after vaccination.

Value added

This study suggests that the currently used Pfizer/BioNTech COVID19 vaccine is effective against one of the common mutations in two newly described SARS-CoV-2 variants.

Our take —

SARS-CoV-2 antigen-based testing using the Sofia SARS Antigen Fluorescent Immunoassay demonstrated good diagnostic accuracy in this study of 1,098 paired samples from two universities in Wisconsin, and thus may aid in serial testing in congregate settings such as universities. Confirmatory RT-PCR testing is recommended in certain instances in order to rule out false positive or false negative test results. The study population was predominantly white and under the age of 24 years, thus potentially limiting the generalizability of these findings.

Study design

Cross Sectional

Study population and setting

Performance data on an FDA-authorized antigen-based SARS-CoV-2 test (Sofia SARS Antigen Fluorescent Immunoassay, Quidel Corp.) relative to CDC RT-PCR test was obtained using 1,098 paired nasal swab samples from individuals at two universities in Wisconsin, from September to October 2020. Subjects included both sexes and were predominately white students under the age of 24 years, either with (20.7%), or without (79.3%) self-reported COVID-19-compatible symptoms at the time of sample collection.

Summary of Main Findings

Compared to the CDC RT-PCR test, in subjects reporting one or more symptoms at the time of sample collection, the antigen-based test had a sensitivity of 80.0%; a specificity of 98.9%; positive predictive value (PPV) of 94.1% and negative predictive value (NPV) of 95.9% in this population. For asymptomatic subjects, sensitivity was 41.2%; specificity was 98.4%; PPV was 33.3% and NPV was 98.8%. Negative predictive value is the probability of not having disease given a negative test, while positive predictive value is the probability of having disease given a positive test.

Study Strengths

The primary study strength was that these findings were based on real-world data collected from university-based testing programs. This study also directly compared assay performance of an FDA-approved antigen-based SARS-CoV-2 test to CDC RT-PCR test using paired, contemporaneously collected nasal swab samples. For a subset with positive RT-PCR or antigen test results, viral culture was performed to further validate findings.

Limitations

Test subjects were predominately white (84%), college-age students, from a single university (96%), thus potentially limiting the generalizability of these study results to other populations. The study population was already undergoing serial testing, thus the NPVs and PPVs obtained here would not necessarily apply to populations undergoing less intensive screening. Additionally, the study only evaluated the performance of the Sofia SARS Antigen FIA, thus these results cannot be generalized to other antigen-based tests.

Value added

This study supplied performance data for an antigen-based SARS-CoV-2 test. Compared to RT-PCR, antigen-based tests are faster and cheaper, and thus have potential advantages for use in serial testing of congregate populations. These results indicate that the Sofia SARS Antigen FIA test may have utility in serial testing of young adults in the university setting, but that confirmatory nucleic acid-based testing should be considered for negative test results in symptomatic individuals and for positive test results in asymptomatic individuals, in order to help rule out potential false negatives and false positives, respectively.

Our take —

In an online survey of 3,058 adults in three US states, general self-reported mask use consistency was not associated with SARS-CoV-2 PCR test positivity in the past two weeks; however, more frequent mask removal and higher activity participation were both associated with recent COVID-19 infection. These findings are subject to caution since respondents to this internet-based survey may systematically differ from non-respondents, and respondents who tested positive may have been more likely to recall social activities and instances of mask removal. Nonetheless, the study suggests that more nuanced measures of mask use behavior are needed to accurately capture risks of SARS-CoV-2 exposure in population-based surveys. The senior author of this scientific article is also a member of the Hopkins NCRC; therefore, this expert review was written by an NCRC member without current or past collaborations with Wesolowski.

Study design

Cross-Sectional

Study population and setting

Between September and October 2020, investigators administered an online survey to 3,058 adults in three US states (Florida, Maryland, and Illinois). Respondents were asked whether they wore a mask (always, sometimes, or never) when indoors, outdoors, and within 6 feet of others. They were also asked whether they had participated in one of six types of activities (visiting with friends, relatives, or neighbors [indoor/outdoor]; going to a bar or restaurant [indoor/outdoor]; going to a gym or fitness class [indoor/outdoor]). Finally, respondents were asked if they always, sometimes, or never removed their masks while participating in these activities. The investigators created summary scores reflecting respondents’ frequency of activity participation and mask removal, respectively. The investigators then measured associations between self-reported SARS-CoV-2 positivity in the past two weeks and mask use measures.

Summary of Main Findings

Self-reported consistent mask use in both indoor (73%) and outdoor (73%) settings was high and did not vary considerably across states. Among these respondents, a majority (78%) reported taking their mask off when outside their homes, either in indoor or outdoor spaces. Nearly one-fourth (23%) of respondents who self-reported SARS-CoV-2 PCR testing in the past two weeks had a positive test. SARS-CoV-2 test positivity was significantly associated with participation in more activities outside the home (OR per additional activity: 2.03, 95% CI: 1.68–2.59) and more frequent mask removal when participating in indoor and outdoor activities (OR for a one-unit increase in mask removal score: 9.92, 95% CI: 1.16–85.1). When not accounting for frequency of mask removal or activity participation, consistency of mask use indoors and outdoors was not significantly associated with SARS-CoV-2 test positivity.

Study Strengths

The study used novel measures of mask use behavior, including removal of masks when participating in specific indoor and outdoor activities. Additionally, investigators restricted reporting periods to the two weeks prior to survey participation to mitigate possible recall biases and strengthen temporal inferences in the observed associations between mask use behaviors, activity participation, and recent COVID-19 infection.

Limitations

Individuals may recall prior exposures differently depending on their SARS-CoV-2 infection status; for example, those testing positive within the past two weeks may be particularly apt to recall instances when they removed their masks. If this recall bias occurred systematically, the association between mask removal and SARS-CoV-2 test positivity would be overestimated. Reliance on self-reported SARS-CoV-2 test positivity is likely to result in underestimation of COVID-19 infection prevalence in the study population, as decisions to seek COVID-19 testing and access to testing are likely to be imbalanced among survey respondents across residence and symptomatology. Additionally, while measures of mask use behaviors used in the survey were nuanced, these measures did not include specific dimensions of mask use behavior (i.e., appropriate use, mask type, duration of mask removal) that are essential for exposure surrogacy measures. Internet-based recruitment and administration of the survey limits generalizability of results, as respondents are likely to be substantially different from those who chose not to participate or are excluded from participating. As with other cross-sectional online surveys, results from this study are limited by the simultaneous assessment of mask use and SARS-CoV-2 positivity (i.e., causation cannot be inferred in the mask behavior and SARS-CoV-2 positivity relationship). Responses may also be subject to social desirability bias (i.e., respondents may have been more likely to self-report behavior that they deemed to be desirable), which may bias measures of behavior and observed associations in analysis.

Value added

This study is among the first to find that more nuanced measures of mask use behaviors, specifically frequency of mask removal when participating in activities outside the household, explain SARS-CoV-2 test positivity more so than general self-reported adherence to mask use recommendations.