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Our take —

This study presented the prevalence of antibodies for SARS-CoV-2 at a tertiary care hospital in New York City, and found one third to have antibodies. The study collected minimal sociodemographic or clinical data from participants, and found no association between age or sex and seroprevalence. Participation was voluntary, and workers concerned about infection may have been more likely to get tested, which would inflate the prevalence.

Study design

Cross-Sectional

Study population and setting

The goal of this study was to understand the serological prevalence of SARS-CoV-2 among healthcare workers in a tertiary care hospital in New York City, where there is a large amount of community transmission. Healthcare workers (n=285) volunteered to undergo serological (antibody) testing after at least 3 days with no COVID-19 symptoms. Participants who had experienced symptoms prior to enrollment did not undergo testing until at least 2 weeks symptoms onset, and 3 days without any symptoms. The study was conducted from March 24 to April 4, 2020, and collected age and sex demographic variables.

Summary of Main Findings

The average participant age was about 38 years (SD=10.8 years), and the majority of participants were men (n=111, 54%). Overall, 33% (n=93) of participants had positive antibody titers (defined as antibodies detected at dilutions greater than 1:320), and 3% (n=9) had weakly positive SARS-CoV-2 titers (defined as antibodies detected at dilutions of 1:50 to 1:160). Neither age nor sex showed any association with seroprevalence.

Study Strengths

The study had a reasonable sample size to conduct the analyses. The study used a 14-day delay since symptom onset for participants to be tested in order to allow for antibodies to build in the system and be detectable.

Limitations

The study was voluntary, which may be subject to selection bias among participants who were interested in learning their infection status, but who likely experienced minimal or mild symptoms that allowed them to present for testing. Healthcare workers who did not expect themselves to be exposed or infected were potentially less likely to self-refer for testing, potentially overestimating prevalence. The study also did not collect any other demographic or exposure-related variables, such as the department or specific occupation (e.g., physician, nurse, etc.) of their participants, or clinical variables such as symptoms experienced earlier.

Value added

This study demonstrated the prevalence of SARS-CoV-2 antibodies among healthcare workers in a tertiary care hospital across a number of departments.

Our take —

This retrospective cross-sectional study examined the correlation between SARS-CoV-2 RT-PCR results (RNA testing) from Canada, and time since symptom onset with virus culture in vitro. While they used the largest sample size to date of non-epidemiologically linked samples to assess these associations, they do not assess actual infectivity in vivo, and the sample size per day since symptom onset is very limited. They also do not assess the relationship between RNA testing and infectiousness in asymptomatic or pre-symptomatic individuals, who may be contributing a significant amount to viral spread in the real-world. Given the limited sample size, we recommend caution when interpreting the peak infectivity.

Study design

Cross-Sectional; Other

Study population and setting

Nasopharangeal (NP) and endotracheal (ETT) samples collected as part of routine care and surveillance in Manitoba, Canada, were tested for SARS-CoV-2 RNA using RT-PCR targeting the viral envelope at the provincial public health laboratory (n=90 total samples). Samples were linked with epidemiological data including time from symptom onset to test (STT). Researchers assessed the relationship between RT-PCR cycle threshold (Ct), which has an inverse relationship with viral concentration, STT, and infectivity of Vero cells in vitro.

Summary of Main Findings

Overall, 26/90 (28.9%) of the samples were deemed infectious, though none past day 8 STT. Infectious samples were more likely to have a lower Ct (<24) and a lower STT (<8 days) than non-infectious samples. Ct was found to be statistically associated with positive culture (infectivity) (OR 0.64 [95% CI: 0.49 – 0.84])—which can be interpreted as for each 1 unit increase in Ct value the odds of infectivity decreased by 32%. Similarly, STT was associated with culture as well (OR 0.63 [95% CI: 0.42 – 0.94]). The peak probability of infectivity was on day 3 STT and decreased thereafter.

Study Strengths

The study used the largest sample size to date collected from epidemiologically unrelated individuals to examine the relationship between test result and infectivity. They integrated PCR results, with epidemiological data and in-vitro infectivity data.

Limitations

Although the largest sample to date, 26 infectious cases remains limited and it is not clear how many samples were available by day, potentially leading to a misinterpretation of results that infectiousness is highest at Day 3 STT given limited sample sizes. In vitro culture is not directly equivalent to in vivo infectivity, especially with respect to actual factors related to transmission events. All individuals were symptomatic, part of the criteria for testing in Manitoba, so the relationship between PCR results and infectivity remains unknown in asymptomatic individuals who have been shown to be infectious. Ct values can vary by assay and lab even when using the same assay. Ct values can be converted into a viral load with a properly run standard curve, which may be more useful in drawing hypotheses across platforms and laboratories about viral PCR results and infectiousness.

Value added

This study links epidemiologic, laboratory, and diagnostic data using a large and epidemiologically unrelated sample set to examine the relationship between RNA testing, time since symptom onset, and potential infectiousness (in vitro).

Our take —

This study was conducted at Singapore General Hospital, and assessed community-acquired coinfections for SARS-CoV-2 and other viral respiratory infections. Out of 3807 patients hospitalized, 19.3% were infected with SARS-CoV-2, and only 6 of those cases also had a viral respiratory coinfection. These data suggest co-infection among COVID-19 patients is limited, however SARS-CoV-2 coinfections may not be representative of cases not requiring hospitalization or of areas with greater seasonal viruses circulating.

Study design

Cross-Sectional

Study population and setting

This study sought to estimate the prevalence and etiology of viral respiratory infections requiring hospitalization at a large, public, tertiary hospital (Singapore General Hospital). All patients presenting with respiratory symptoms or radiology of likely pneumonia from February 5 to April 15, 2020 were included in the study. Oropharyngeal or other respiratory swabs were collected within 24 hours of patient admission.

Summary of Main Findings

The rate of admission doubled over the study period, from 316 in week 1 to 659 in week 10, and for SARS-CoV-2 respiratory infections, it increased from 5 cases in week 1 to 210 cases in week 10. Among the 3807 respiratory-related admissions, 19.3% (n=736) had a viral respiratory infection from PCR analysis; 58.5% of these (n=431) were positive for SARS-CoV-2. Only 6 (1.4%) SARS-CoV-2 infected patients had coinfections. SARS-CoV-2 infected patients had lower odds of respiratory coinfection (0.27, 95% CI: 0.11 – 0.72), compared to patients with other respiratory virus. Rhinovirus was most correlated with SARS-CoV-2 infection, followed by parainfluenza.

Study Strengths

The study had multiple weeks of cross-sectional data to use for a time series for SARS-CoV-2, as well as other respiratory viruses to show the trends in SARS-CoV-2 infection compared to other viral infections. By also measuring coinfection rates, these data offer important information about the risk of coinfection in a community sample with severe illness that requires hospitalization. The study also had detailed case histories about those with SARS-CoV-2 who were infected.

Limitations

This study examined infections requiring hospitalization, which may lead to selection bias for those with higher severity of disease than would exist in the population prevalence. Many of the other respiratory viruses examined have seasonal trends which could not be observed due to Singapore’s climate, so there may be reduced generalizability to other settings. Finally, SARS-CoV-2 coinfections were uncommon (n=6), and so it was not possible to test for risk factors for coinfection among those with COVID-19, and only a descriptive case history could be given.

Value added

This study is one of the few that looks at coinfection, and has a wide range of respiratory infections included with one of the largest sample sizes.

Our take —

Correctional/detention facilities are at greater risk of COVID-19 outbreaks due to the confined physical spaces, high contacts between inmates, and logistical and security issues that make it difficult to implement recommended distancing measures. This study does not report details of testing and screening policies; cases may be severely undercounted. The CMAR tool helps public health officials systematically assess risks and provide tailored strategies for infection control within correctional and detention facilities.

Study design

Cross-Sectional

Study population and setting

This paper describes: 1) the prevalence of COVID-19 in correctional and detention facilities across 144 facilities in Louisiana, USA, with an incarcerated or detained population of 45,400, based on active daily surveillance between March 22 to April 22, 2020; and 2) the benefits of using the COVID-19 Management Assessment and Response (CMAR) tool to help public health officials provide tailored and specific guidance to 24 correctional and detention facilities. The Centers for Disease Control and the Louisiana Department of Health collaborated to develop the CMAR, a phone-based assessment tool. CMAR systematically records the characteristics of correctional facilities so that technical advisors can recommend strategies to address identified weaknesses, evaluate management protocols, and guide conversations between public health practitioners and correctional facilities staff.

Summary of Main Findings

There were 489 laboratory-confirmed cases of COVID-19 in the incarcerated or detained population and 253 cases among staff across 46 facilities. The CMAR tool was used in 24 facilities, 13 of which had confirmed cases. All facilities implemented hand-washing recommendations, screened new inmates for symptoms, and stopped visitation to facilities. However, there was variation in uptake of interventions such as wearing masks, quarantine of close contacts, and allocating specific staff to each unit. The CMAR tool highlighted how structural, physical, and logistical facility-specific barriers such as limited space, close contact between inmates, low staffing numbers, and deterrents to reporting cases probably contributed to the spread of COVID-19 in correctional and detention facilities.

Study Strengths

Surveillance data were collected from 144 correctional and detention facilities across Louisiana.

Limitations

No information is presented on either statewide or facility-specific testing and screening protocols, making it difficult to interpret case counts and prevalence estimates. There were no data available on the overall number of staff members. The number of COVID-19 cases among staff is underreported, as not all facilities provided case numbers. Case numbers were detected through surveillance systems specific to each facility, and these systems may have varied in quality and coverage. Facilities that chose to use the CMAR tool (24/144) may be different from other facilities. Implementation and uptake of interventions could not be directly observed, as this was a phone-based tool.

Value added

As one of the first studies to focus on COVID-19 in correctional/detention facilities in the US, the study highlights the challenges in controlling an outbreak in these settings. The CMAR tool provides a way for public health officials to communicate with facility administration and provide recommendations for infection control.

Our take —

Among 18,401 users of a symptom-tracking app in the UK and US, the loss of smell and taste (as well as cough, fatigue, and skipped meals) was strongly associated with a positive SARS-CoV-2 test result. Although a symptom-based predictive model of infection performed reasonably well, caution is warranted because of possible bias arising from the sample of individuals studied, the self-reported nature of the data, and the lack of information on the timing of symptoms relative to testing.

Study design

Cross-Sectional, Other

Study population and setting

The study included 2,618,862 individuals in the UK and the US (65% female, 95% from the UK) who used a COVID-19 symptom tracking app (COVID Symptom Study, developed by Zoe Global) between March 24 and April 21, 2020. Analyses were conducted separately in the UK and US cohorts. Authors were focused on loss of smell and taste as specific symptoms of COVID-19. Patients used the app to report symptoms, whether they were tested for SARS-CoV-2 infection via PCR, and the outcome of the tests.

Summary of Main Findings

18,401 (0.7%) individuals reported being tested for SARS-CoV-2 infection, and of these, 7,178 (39%) reported a positive test. Among those tested, loss of smell and taste was strongly associated with a positive result in multivariable regression (UK:OR 6.40, 95% CI: 5.96-6.87; US: OR 10.01, 95% CI: 8.23-12.16). With data from the UK cohort, the authors used step-wise regression to develop a prognostic model for SARS-CoV-2 infection. The final model included age, sex, loss of smell and taste, cough, fatigue, and skipped meals; this model had an area under the curve (AUC) of 0.76 in 10-fold cross-validation, a sensitivity of 0.65, a specificity of 0.78, a positive predictive value of 0.69, and a negative predictive value of 0.75 in the UK cohort. The model performed similarly in the US cohort, with an AUC of 0.76. When applied to all 805,753 individuals who reported symptoms but were not tested, the model predicted that 17.42% (14.45–20.39%) were likely to be infected, representing 5.36% of all app users.

Study Strengths

The sample size was large, even when limited to those receiving tests. The US cohort allowed validation of the predictive model.

Limitations

Olfactory dysfunction (anosmia) and taste dysfunction (dysgeusia) were combined in the app questionnaire. Self-reporting of symptoms and of SARS-CoV-2 test results are subject to misclassification; for example, respondents with positive tests may be more likely to report symptoms that have received media attention, such as loss of smell. Furthermore, defining cases by a single PCR test may result in misclassification. The timing of symptoms relative to test results was not reported, limiting the interpretability of the prognostic tool. The population of all respondents may not be representative of the general population (there was a considerably higher proportion of females, for example). Moreover, the subpopulation of respondents receiving SARS-CoV-2 tests are not a random sample of all respondents; they may have been more likely to have known exposures or to have experienced severe symptoms. Associations between reported symptoms and infection status may differ in this selected population.

Value added

This study is the largest published to date of self-reported symptoms as they relate to the likelihood of SARS-CoV-2 infection.

Our take —

Most children admitted to intensive care for COVID-19 had significant underlying health conditions, and many had complex developmental and/or congenital disorders.  2 of 18 children requiring mechanical ventilation died by the end of follow-up, though 7 remained hospitalized.  This proportion is much smaller than that observed among adults.  Reinforcing existing evidence from North America and beyond, this study suggests a less severe clinical course for COVID-19 in children than in adults.

Study design

Case Series; Cross-Sectional

Study population and setting

This study included 48 children (median age 13 years, 52% male) with laboratory-confirmed COVID-19 admitted to pediatric intensive care units (PICUs) in 14 U.S. hospitals (out of 46 collaborating PICUs in North America) between March 14 and April 3, 2020.  Outcomes were ascertained through April 10, 2020.

Summary of Main Findings

35 children (73%) presented with respiratory symptoms.  40 children (83%) had at least one significant underlying medical condition. At admission, 69% of the pediatric patients were determined to have severe or critical illness. 18 patients (38%) required mechanical ventilation, and 21 (44%) required non-invasive respiratory support. Of the 18 patients who required mechanical ventilation, by the end of follow-up, 2 died (4.2% of all patients), 3 remained on mechanical ventilation, 7 others remained hospitalized, and 6 were discharged alive.  Among all patients who died or were discharged, the median hospital stay was 7 days, and the median ICU stay was 5 days.

Study Strengths

The study drew from a large group of institutions throughout North America.

Limitations

Few patients were included in the study, a reflection of the apparently lower likelihood of severe disease in pediatric COVID-19.  Follow-up duration was short; the fatality ratio may change with time.  Inadequate testing in North America may have resulted in missed COVID-19 diagnoses among hospitalized children.

Value added

This is the largest study to date of severe pediatric COVID-19 in the North America.

Our take —

An online survey published as a preprint and thus not yet peer-reviewed, found that US adults expressed a high willingness to test for COVID-19 at home, at drive-through test sites, and at clinics if they developed illness symptoms, with a majority expressing preference for home-based testing. Additional evidence is needed to corroborate expressed testing preferences with actual testing uptake among symptomatic adults in the US.

Study design

Cross-Sectional

Study population and setting

The study included 1,435 adults 18 years and older in the United States who were recruited via social media advertisements between March 27 and April 1, 2020 and who completed an online survey measuring willingness to complete four different modalities of COVID-19 testing: home-based saliva, home-based swab, drive-through, and clinic-based. Testing willingness was compared across participant socio-demographic characteristics, levels of COVID-19 disease knowledge, and self-reported COVID-19 symptoms.

Summary of Main Findings

Respondents indicated the highest degree of willingness to test for COVID-19 with home-based testing, with 92% of participants endorsing (agreeing or strongly agreeing) willingness to test with home-based saliva tests and 88% with throat swabs. Fewer expressed interest in COVID-19 testing through drive-through (71%) and clinic-based (60%) specimen collection. All differences in mean willingness scores between modalities were statistically significant (p<0.001). Two-thirds (68%) expressed more willingness to test for COVID-19 if home-based testing were available. No differences in testing willingness or testing modality preferences were observed across socio-demographic categories, levels of COVID-19 knowledge, or self-reported COVID-19 symptoms.

Study Strengths

The study disaggregated results by different factors of interest (e.g., demographics, COVID-19 knowledge) and testing objectives (i.e., diagnosis or follow-up care).

Limitations

Given the survey’s online recruitment and implementation, individuals who willingly participated in the survey could be substantially different from non-participating individuals, suggesting the study is susceptible to selection bias. Study inclusion criteria were adjusted on the final day of survey recruitment to exclude non-Hispanic White individuals, resulting in 1,123 exclusions, indicating authors were concerned about a non-representative sample. Lastly, expressed testing preferences may not align with actual testing behavior if testing modalities were made widely available for symptomatic individuals.

Value added

This is among the first studies to describe and compare COVID-19 testing preferences and willingness to seek COVID-19 testing in a large online sample of US adults.

Our take —

Early evidence from a large online survey conducted in four European countries and the United States suggests a high willingness to install or keep a digital contact tracing application on a mobile device, with few differences across sub-populations (i.e., age, gender) and countries. Additional corroboration of these results, through end-user pilot tests and other demonstration activities, is required to determine actual acceptability of a digital contact tracing app. This manuscript was a preprint at the time of review, and was not yet subjected to the peer review process.

Study design

Cross-Sectional

Study population and setting

The objective of the study was to determine the acceptability and willingness to use a mobile phone application (“app”) facilitating digital contact tracing for COVID-19. The investigators implemented an online survey with a socio-demographically representative sample of adults (N = 5,995) in four European countries (France, Germany, Italy, and the United Kingdom) and the United States. The surveys evaluated user acceptance of the app under different installation methods (voluntary installation or automatic installation), comparing across participant socio-demographic characteristics, political affiliations/beliefs, and COVID-19 epidemic properties in participants’ country of residence.

Summary of Main Findings

Across countries, three-fourths (75%) of respondents expressed willingness to download the app onto their mobile phones, and over two-thirds (68%) reported desire to keep the app installed on their devices if automatically downloaded. Self-reported reasons for supporting the app included a desire to protect friends/family, obligations towards community, and perceived effectiveness of stopping the spread of COVID-19. Other factors associated with app support included carrying a cellphone regularly, having a chronic health condition, and higher self-reported trust in the government. Sources of opposition for using the app revolved around concerns regarding government surveillance and phone security. Support for both voluntary and automatic installation was higher among participants in the United Kingdom, Italy, and France compared to Germany and the United States, respectively. No differences in app support across socio-demographic characteristics (i.e., age, gender) or among participants in countries with different COVID-19 mortality profiles were observed.

Study Strengths

The investigators included questions gauging support for digital contact tracing applications under different installation scenarios. Participant recruitment in multiple countries also helps generalize the findings to populations in different epidemic contexts, and understand user preferences in different settings. The investigators also reproduced their analyses using different statistical models (with different parameters and underlying assumptions) in order to corroborate the quantitative findings.

Limitations

Fewer than two-thirds (59%) of sampled individuals were included following the online comprehension check prior to survey administration, which is highly suggestive of response and selection biases that may reduce the representativeness of survey participants. The survey did not include additional behavioral questions that may influence user acceptance of and willingness to use a digital contact tracing app, including self-reported adherence to physical distancing ordinances and perceived risk of COVID-19 infection. Lastly, the authors measured interest in a hypothetical digital contact tracing app, which may not align with actual user behavior towards the mobile app (particularly since the details and characteristics of an app were not available to participants at the time of survey administration).

Value added

This is among the first studies to measure willingness to use digital contact tracing apps in a large population-based sample recruited from various high-income countries.

Our take —

This serologic validation study showed that the commercially-available Abbott SARS-CoV-2 IgG assay had optimal sensitivity 17 days post-symptom onset in a mostly hospitalized patient population, but the sensitivity of the assay remains unknown in other populations such as mild or asymptomatic cases of infection. The assay had optimal specificity in pre-COVID-19 pandemic specimens, but further validation is needed to assess whether the assay cross-reacts with other coronaviruses.  The study also demonstrates the feasibility of using the Abbott SARS-CoV-2 IgG assay to perform a community serosurvey.

Study design

Cross-Sectional; Retrospective Cohort; Other

Study population and setting

This study evaluated the test performance of the Abbott SARS-CoV-2 IgG assay, which is a chemiluminescent microparticle immunoassay for the qualitative detection of IgG antibody against the SARS-CoV-2 nucleoprotein in plasma or serum. To assess assay sensitivity, 689 excess serum samples from 125 patients in Seattle who were PCR-positive for SARS-CoV-2 infection were tested. To assess assay specificity, 1,020 de-identified serum samples from unique individuals that had excess serum originally obtained for herpes simplex serology in 2018-2019 (i.e., pre-COVID-19) were tested. In addition, the study evaluated the seroprevalence of anti-SARS-CoV-2 among 4,856 individuals who were sampled in April 2020 via the Crush the Curve program in Boise, Idaho.

Summary of Main Findings

Sensitivity of the Abbott SARS-CoV-2 IgG assay increased with time since symptom onset and from the date of PCR positivity among mostly hospitalized COVID-19 patients. For this group, the assay had 100% sensitivity at 17 days post symptom onset and 14 days from the date of PCR positivity. In pre-COVID-19 serum samples (n=1,020), assay specificity was 99.0%; only one false-positive result was observed. Specificity of the assay could be improved to 100% while maintaining sensitivity at 100% by increasing the manufacturer’s cut-off value for seropositivity. Assay results were also shown to be reproducible. Among the participants in Boise, Idaho, anti-SARS-CoV-2 seroprevalence was 1.8% overall, 2.1% in males, and 1.6% in females.

Study Strengths

The study used longitudinal sera to describe increases in antibody detection over time and assess the impact of infection duration on assay sensitivity. The sample sizes used to assess both assay sensitivity and specificity were large.

Limitations

The specimens used to evaluate test performance characteristics of the Abbott SARS-CoV-2 IgG assay were not well characterized. Most of the sera used to assess assay sensitivity were from mostly hospitalized patients who were recently infected with SARS-CoV-2. It is unclear whether the Abbott SARS-CoV-2 IgG assay would have optimal sensitivity in mild or asymptomatic cases of SARS-CoV-2 infection or recovered COVID-19 patients who are no longer PCR-positive. Additionally, the study did not include specimens from patients known to be infected with other coronaviruses, so it is unclear whether the Abbott SARS-CoV-2 IgG assay produces false-positive results due to cross-reactivity. Finally, the Crush the Curve participants were a self-selected sample and are not representative of all Boise, Idaho residents, so the seroprevalence estimates may not be reflective of the general Boise population.

Value added

This study provides key test performance characteristics for a commercially-available SARS-CoV-2 IgG antibody assay and demonstrates its utility in community serosurveys.

Our take —

Preliminary results from this study of real-time COVID-19 symptom data collected through an app suggests that app-based symptom tracking may be useful for predicting spikes and drops in new cases several days in advance of other more traditional measures (e.g. confirmed positive tests).

Study design

Cross-Sectional; Modeling/Simulation; Other

Study population and setting

The authors developed an app-based symptom tracker, “COVID Symptom Study” (referred to previously as COVID Symptom Tracker), and demonstrated proof-of-concept for real-time tracking of symptoms through mobile phones. App data can be used to immediately inform public health responses to COVID-19 by detecting outbreaks, disparities in testing, and emerging symptoms. The app was tested in the United Kingdom and United States of America. Recruitment for the app relied on downloads, but also recruitment through existing large cohort studies that often have higher under-represented populations.

Summary of Main Findings

Initial findings were reported based on 1.6 million users in the UK, including 265,851 who experienced COVID-19 symptoms, of whom 0.4% received testing. Those that reported fatigue and/or cough along with another symptoms were more likely to test positive, but 20% of individuals that reported this combination of symptoms did not receive testing. Among those who tested positive, loss of smell was more common than fever, suggesting that anosmia may be a good predictor for testing positive for COVID-19. Based on modeling using existing data, the authors were able to predict increases and decreases in COVID-19 cases in geographic areas across the UK several days in advance of confirmed case data.

Study Strengths

The app provides a useful tool to collect longitudinal data on COVID-19 symptoms and testing on the scale needed for meaningful analysis. Recruitment for app use included leveraging existing large cohort studies, thereby improving diversity and the potential to link existing cohort data with COVID Symptom Study data. Software updates allow questions to be modified as knowledge of the outbreak develops and new hypotheses emerge. As the app collected data on symptoms and testing over time, authors were able to assess which symptoms were more likely to result in a positive test and predict where hotspots may emerge.

Limitations

As the authors acknowledge, the population contributing data to the COVID Symptom Study may not be representative of the broader population. App users must be over the age of 18 years, and app use requires daily access to a smartphone as well as English language skills. The vast majority (75%) of the first 1.6 million users in the UK were female which may bias study findings, especially as male sex is associated with COVID-19 disease severity. The app does not currently meet accessibility standards for those with limited sight.

Value added

This app demonstrates proof-of-concept for large scale real-time mobile data collection on symptoms, testing, and mobility data of potential cases that can be used to predict potential outbreaks.