COVID-19 Science Update released: November 17, 2020 Edition 65

COVID-19 Science Update

The COVID-19 Science Update summarizes new and emerging scientific data for public health professionals to meet the challenges of this fast-moving pandemic. Weekly, staff from the CDC COVID-19 Response and the CDC Library systematically review literature in the WHO COVID-19 databaseexternal icon, and select publications and preprints for public health priority topics in the CDC Science Agenda for COVID-19 and CDC COVID-19 Response Health Equity Strategy.


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***This week and next week the CDC COVID-19 Science Update will only be produced on Tuesday, 11/17 and Tuesday, 11/24. The CDC COVID-19 Science Update will not be produced on Friday, 11/20, or Friday, 11/27.***

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COVID-19 and Return to College

The increase in COVID-19 cases among younger persons points to a need to implement effective mitigation strategies to protect college students returning to campus, as well as the neighboring communities. Six out of 10 colleges and universities re-opened in the fall with in-person classesexternal icon, either full-time or combined with online classes. Safely bringing students and faculty back to campus will require testing and mitigation measures to prevent SARS-CoV-2 transmission. Optimal testing strategies for in-person classes and variables associated with likelihood of holding in-person classes at colleges and universities are discussed in the following papers.


A. Evaluation of COVID-19 testing strategies for repopulating college and university campuses: A decision tree analysis.external icon Van Pelt et al. Journal of Adolescent Health (November 3, 2020).

Key findings:

  • Strategies that included RT-PCR testing of in-coming students identified more cases than symptom-based screening alone; however, all strategies failed to detect a portion of the cases.
    • Using only symptom-based screening, less than 50% of true positive cases will be detected.
    • Testing all students on arrival, and again 7 days later, will detect the greatest number of cases.
  • At higher prevalence of infection, repeat testing will detect more true positives per test, but will cost more.

Methods: A decision tree analysis was used to evaluate testing strategies for safely repopulating a university with 20,000 students. The analysis evaluated five strategies: (1) classifying students with symptoms as having COVID-19 (no testing); 2) testing done on symptomatic students, (3) testing all students, (4) testing all students and retesting symptomatic students with a negative first test, and (5) testing all students and retesting all students with a negative first test. Costs estimates for given strategies were estimated. Limitations: Disease prevalence was based on national estimates; no analyses of testing strategies later in the semester.




B. Causal impacts of teaching modality on U.S. COVID-19 spread in fall 2020 semesterexternal icon. Badruddoza & Amin. MedRxiv. (November 3, 2020).

Key findings:

  • Reopening colleges was associated with increased COVID-19 cases and deaths.
  • Colleges with in-person classes are in counties with rapidly increasing COVID-19 cases (Figure).
    • Daily new COVID-19 cases increased in the fall 2020 semester by 1.87 cases per 100,000 population.
  • The variables most strongly associated (p <0.05) with adopting online teaching modes vs in-person enrollment were higher student enrollments, larger endowments per student, being a public (vs private) institution, individual mask policies, and prevalence of specific political party affiliation in the community.
  • There was a negative association between the percentage of county residents staying home and disease spread.

Methods: Use of metrics of new daily COVID-19 cases and COVID-19-related deaths in the county to describe the effects of college teaching modality on spread of disease for 745 US institutions and surrounding communities. The probability of choosing each teaching mode was calculated with multinomial logistic regression. Limitations: Student-specific infections are not addressed; method for classifying counties with multiple colleges with different teaching modes not explained.


Note: From Badruddoza et al. County-level growth of COVID-19 cases in counties by teaching modality for in-person, online, or hybrid classes. Opening date for colleges by teaching modality shown in bars from August 10 to September 19, 2020. Licensed under CC-BY-ND 4.0.

Implications for 2 studies (Van Pelt et al. and Badurddoza & Amin) These two articles highlight measures that colleges and universities can use to mitigate COVID-19. As discussed in Walke et al.,external icon institutional resources, cost of testing, and the possibility of distance learning need to be considered when re-opening schools. These articles show that decisions regarding type of teaching are also influenced by the surrounding communities, such as locally enacted preventative measures and the local political environment. Being aware of these influences may guide administrators in decision-making regarding re-opening campuses.


Antibodies to SARS-CoV-2, particularly neutralizing antibodies, appear to wane over time. Long-term protection against SARS-CoV-2 may rely on the maintenance of memory immune cells that quickly re-activate upon secondary infection, primarily B cells that produce antibodies and T cells that help B cells and kill virus-infected cells. The duration of SARS-CoV-2-specific cell-mediated immunity – i.e. immunity not mediated by antibody – is not well understood. Following are two recent pre-print studies examining the longevity of memory B and T cell responses against SARS-CoV-2.


A. Durable SARS-CoV-2 B cell immunity after mild or severe diseaseexternal icon. Ogega et al. MedRxiv (October 30, 2020).

Key findings:

  • B cells recognizing SARS-CoV-2 spike protein receptor binding domain (S-RBD) were detected in 13 of 14 participants with COVID-19 (Figure, A).
    • Four (57%) of seven patients with mild COVID-19 had S-RBD-specific immature B cells and antibody-secreting cells (ASC) and six (86%) had detectable memory B cells (MBC).
    • 100% of moderate-to-severe COVID-19 patients had S-RBD-specific B cells of all types (immature, ASC, and MBC).
  • The frequency of S-RBD specific MBC was significantly higher in patients with moderate-to-severe COVID-19 compared with mild COVID-19 (mean S-RBD+ frequency 0.85% vs. 0.20%, p = 0.004) (Figure, B).
    • The single individual with SARS-CoV-2 infection but without detectable S-RBD-specific MBC was asymptomatic.

Methods: S-RBD-specific B cells from seven ambulatory patients with mild COVID-19 and seven hospitalized patients with moderate-to-severe COVID-19, and cryopreserved cells from healthy blood donors collected prior to the COVID-19 pandemic were evaluated. Limitations: Maximum time from symptom onset to B cell sampling was 104 days (median 54 days); small sample size.


Note: Adapted from Ogega et al. The percent of S-RBD-specific memory B cells from healthy participants, participants with mild-COVID-19, or participants with severe COVID-19. A. Box and whiskers plots show summary of participants (whiskers are minimum to maximum). B. dot plot shows representative data from each group, with the population of B cells binding to S-RBD highlighted in the box. ** Indicates p ≤0.01. Licensed under CC-BY-ND 4.0.

B. Robust SARS-CoV-2-specific T cell immunity is maintained at 6 months following primary infection.external icon Zuo et al. BioRxiv (November 2, 2020).

Key findings:

  • Evidence of SARS-CoV-2-specific T cell responses was found in all donors at 6 months (Figure).
  • Median T cell responses were 50% higher in donors who had symptomatic infection compared with asymptomatic infection.
  • T cell responses at six months correlated with peak antibody levels against the SARS-CoV-2 nucleoprotein, receptor binding domain (RBD), and spike proteins.

Methods: Blood samples from 100 convalescent plasma donors were analyzed to characterize the cellular immune response measured by production of interferon-γ six months after SARS-CoV-2 infection, and to measure peak antibody levels against SARS-CoV-2 nucleoprotein, RBD, and spike proteins. Limitations: No assessment of immune responses beyond six months.


Note: Adapted from Zuo et al. Cellular response against SARS-CoV-2 proteins (spike, nucleoprotein/membrane proteins [N/M], and a pool of other SARS-CoV-2 peptides [accessory]) at six months following primary infection. Licensed under CC-BY-ND 4.0.

Implications for 2 studies (Ogega et al. & Zuo et al.): Memory B and T cells could provide durable immunity to SARS-CoV-2 even after serum antibodies decline, particularly in symptomatic individuals. A commentary from Wise, J.external icon highlights that durable T cell responses against a range of SARS-CoV-2 proteins might point to potential new vaccine targets.



Transmission of SARS-CoV-2 on mink farms between humans and mink and back to humans.external icon Munnink et al. Science (November 10, 2020).

Key findings:

  • Of 97 mink farm employees tested, 43/88 (49%) were positive by RT-PCR, 38/75 (51%) had detectable antibodies, and 66/97 (67%) had evidence of SARS-CoV-2 infection by RT-PCR or serology.
  • The mink and human strains clustered closely together (Figure).
    • There was greater phylogenetic relatedness between farm-related human and mink cases than between farm-related human and community cases within the same postal code.
  • Potential mink-to-human transmitted SARS-CoV-2 infections did not have differences in signs, duration, or severity compared with human-to-human transmitted infections.

Methods: Outbreak investigations were performed when respiratory signs and increased mortality for minks were reported to the Dutch Agriculture authorities. Investigations at 16 mink farms sought to identify the source of the outbreak, trace contacts and track movement of animals, vehicles, and people. SARS-CoV-2 diagnostic testing for mink and human samples was performed using RT-PCR and by antibody testing. Viral genomes were sequenced for PCR-positive samples with Ct values ≤32. Limitations: The investigation could not exclude the role that exposures from untested animals or humans might have played in transmission; temporary farm workers not tested.

Implications: SARS-CoV-2 outbreaks in mink farms are well-documented and resulted in recently-abandoned plans to cull Denmark’s 17 million minksexternal icon. This paper provides phylogenetic data suggestive of mink-to-human SARS-CoV-2 transmission; however, directionality of transmission is challenging to definitively demonstrate using phylogenetics. Concerns about potential mutations in SARS-CoV-2 from animal-to-human transmission that may lead to more rapid spread or jeopardize vaccine efficacyexternal icon may be premature.


Note: Adapted from Munnink et al. Phylogenetic tree of mink and human sequences found in a single farm (NB1) and the closest matching human sequences from the national SARS-CoV-2 database (NA 134 2020, and NA 376 2020). Numbers in black represent the bootstrapping values using all Dutch SARS-CoV-2 sequences. From Munnink et al., Transmission of SARS-CoV-2 on mink farms between humans and mink and back to humans, Science. Reprinted with permission from AAAS.

Repeated cross-sectional sero-monitoring of SARS-CoV-2 in New York Cityexternal icon. Stadlbauer et al. Nature (November 3, 2020).

Key findings:

  • A rapid rise in SARS-CoV-2 seroprevalence (6.2%) was detected in the urgent care (UC) group (Figure, A) compared with the routine care (RC) group, coinciding with the surge of new confirmed SARS-CoV-2 infections and related hospitalizations in New York City.
    • The uptick in seropositivity lagged approximately 1–2 weeks behind the increase in new cases (Figure A, C).
  • There was a longer delay between the increase in confirmed cases and the increase in seroprevalence in the RC group (Figure B, C).
  • Seroprevalence in the UC group declined to levels seen in the RC group coinciding with a drop in incidence of SARS-CoV-2 cases between May and July 2020 (Figures A, C).

Methods: Weekly cross-sectional analysis of anti-SARS-CoV-2 spike antibodies on 10,691 plasma samples randomly collected from patients at Mount Sinai Hospital in New York City from February 9 to July 5, 2020.  Seroprevalence was compared between an UC group (meant to capture seropositive individuals) and a RC group (meant to capture visits unrelated to COVID-19 and resemble the general population). Limitations: Non-random, non-representative sampling.

Implications: This will be the first of a series of repeated cross-sectional seroprevalence studies to understand the dynamics of SARS-CoV-2 transmission, seroconversion, and the stability of antibody responses over the course of a COVID-19 outbreak.


Note: Adapted from Stadlbauer et al. Serum antibody prevalence in the UC group (A) and in the RC group (B), and number of confirmed cases/day and number of deaths per day, February–July 2020 (C).) Reprinted by permission from Springer Nature Customer Service Centre GmbH: Springer [Nature] Repeated cross-sectional sero-monitoring of SARS-CoV-2 in New York City, Stadlbauer et al. COPYRIGHT 2020 ( icon).

Outcomes of contact tracing in San Francisco, California—test and trace during shelter-in-placeexternal icon.  Sachdev et al. JAMA Internal Medicine (November 2, 2020).

Key findings:

  • COVID-19 contact tracing program reached more than 85.4% of cases (Figure) and 83.8% of contacts.
  • The secondary attack rate was higher among household compared with non-household contacts (111 of 983 [11.3%] and 9 of 231 [3.9%], respectively; p <0.001).
  • Median time from symptom onset for a case to notifying and testing the contact was 6 days.
    • The median time from symptom onset to receipt of test results was 5 days.
    • Case interviews occurred on average 1 day after the test result and the first contact was notified on average 1 day after that.

Methods: Case investigation and contact tracing for 1,394 COVID-19 cases identified in San Francisco, California between April 13 and June 8, 2020. The study period included dates after which universal testing for COVID-19 contacts, regardless of symptoms, was recommended. The proportion of people who were interviewed and for whom close contacts were identified, with at least 1 contact being notified, was calculated. Median number of days (with IQR) taken to process each step was reported. Limitations: Underreporting of close contacts.

Implications: In order to maximize the impact of contact tracing on mitigating the spread of COVID-19, metrics such as these are needed, and efforts must be made to address testing delays and to improve contact identification.


Percentages for people with COVID-19 at selected stages of contact tracing implementation.

Note: Adapted from Sachdev et al. Percentages for people with COVID-19 at selected stages of contact tracing implementation. Reproduced with permission from JAMA Internal Medicine. Sachdev et al., Outcomes of contact tracing in San Francisco, California—test and trace during shelter-in-place. DOI:10.1001/jamainternmed.2020.5670. Copyright© 2020 American Medical Association. All rights reserved.

Proportion of asymptomatic infection among COVID-19 positive persons and their transmission potential: A systematic review and meta-analysisexternal icon. Yanes-Lane et al. PLOS One (November 7, 2020).

Key findings:

  • 24 studies report that the proportion of asymptomatic individuals among individuals testing positive for SARS-CoV-2 ranged from:
    • 20%–75% for the general population.
    • 2%–50% for contacts of known cases.
    • 45%–100% of obstetric patients presenting to hospitals.
    • 42%–66.7% of nursing home residents; 0%–50% of nursing home staff.
    • 50%–87.8% in congregate settings such as temporary homeless shelter.
    • 2% of retail workers (single study).
  • 8% (18/96) of contacts of asymptomatic index patients were SARS-CoV-2 positive in pooled analysis of 5 transmission studies.

Methods: Review of 28 moderate or high-quality studies systematically testing for COVID-19 through June 22, 2020, assessing the proportion of infections occurring in asymptomatic individuals and transmission. Limitations: Included mainly small studies of people with COVID-19 (n <100), limiting estimate precision; contact tracing in studies was limited which may bias the results; study heterogeneity limited ability to analyze by age group or sex.

Implications: The proportion of asymptomatic infections appears high in many groups. As asymptomatic individuals may have considerable transmission potential, symptom-based testing is insufficient to eliminate transmission. High quality studies in representative general population samples are needed to better understand the role of asymptomatic individuals in the transmission of SARS-CoV-2.


Antigen (Ag) tests may provide an easier point-of-care alternative to RT-PCR testing to detect infected individuals by detecting SARS-CoV-2 proteins rather than RNA. The Abbott BinaxNOW™ COVID-19 Ag Card (Binax-CoV2) is a 15-minute test that recently received an emergency use authorization by the US Food and Drug Administration for testing symptomatic individuals for SARS-CoV-2 infection. The US Department of Health and Human Services has ordered 150 million Binax-CoV2 rapid antigen tests, many of which are targeted for high-risk settings.


Performance characteristics of a rapid SARS-CoV-2 antigen detection assay at a public plaza testing site in San Francisco.external icon Pilarowski et al. MedRxiv (posted November 12, 2020).

Key findings:

  • Criteria for a positive test for the Binax-CoV2 rapid Ag test had to be adjusted when used to screen asymptomatic individuals.
    • When using the manufacturer’s recommendation to read any line as “positive,” 9 (64%) of 14 Binax-CoV2-positive tests were likely false positives.
  • Performance in asymptomatic subjects improved when a positive result was defined as a band extending the full width of the testing strip, regardless of intensity.
    • Sensitivity was 93.8% (95% CI 68.1%-99.8%, n = 16) and specificity was 100%, (95% CI 99.6%-100%, n = 855).
  • Samples with false negative Binax-CoV2 tests had low viral loads (high Ct values) (Figure).

Methods: In September 2020, 878 people participated in testing in San Francisco, CA. Binax-CoV2 cards were read by 2 independent observers with a third on hand to be a “tie-breaker.” Lab confirmation was done via RT-PCR testing. Limitations: The Binax-CoV2 Ag test currently is validated on symptomatic COVID-19 patients, full validation on asymptomatic individuals has not been done.

Implications: Since the Binax-CoV2 rapid test may be used to screen asymptomatic individuals, the data shown here will be critical in establishing guidance for validating this use case. Manabe et al.external icon outline the need for screening tests that can rapidly identify infectious individuals to prevent outbreaks.


Note: Adapted from Pilarowski et al. Average Ct from all 26 RT-PCR-positive participants for Binax-CoV2(+) and Binax-CoV2(-) participants with and without symptoms. Licensed under CC-BY-NC-ND 4.0.

In Brief


Note: From Trypsteen et al. Overview of body systems where SARS-CoV-2 has been found, with darker shading indicating the strength of the evidence for the virus in that system. Licensed under CC-BY 4.0.


Note: Adapted from Sims et al. A: Seropositivity to SARS-CoV-2 in healthcare workers with COVID-19 patient exposure or without COVID-19 patient exposure. B: Seropositivity to SARS-CoV-2 in healthcare workers based on job type with patient care or non-patient care. Reproduced by permission of Oxford University Press on behalf of the Infectious Diseases Society of America. Please visit:

Disclaimer: The purpose of the CDC COVID-19 Science Update is to share public health articles with public health agencies and departments for informational and educational purposes. Materials listed in this Science Update are selected to provide awareness of relevant public health literature. A material’s inclusion and the material itself provided here in full or in part, does not necessarily represent the views of the U.S. Department of Health and Human Services or the CDC, nor does it necessarily imply endorsement of methods or findings. While much of the COVID-19 literature is open access or otherwise freely available, it is the responsibility of the third-party user to determine whether any intellectual property rights govern the use of materials in this Science Update prior to use or distribution. Findings are based on research available at the time of this publication and may be subject to change.


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Page last reviewed: January 20, 2021
Content source: Office of the Chief Science Officer - COVID-19