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Nash D, Rane MS, Robertson MM, Chang M, Gorrell SK, Zimba R, You W, Berry A, Mirzayi C, Kochhar S, Maroko A, Westmoreland DA, Parcesepe AM, Waldron L, Grov C. Severe Acute Respiratory Syndrome Coronavirus 2 Incidence and Risk Factors in a National, Community-Based Prospective Cohort of US Adults. Clin Infect Dis 2022; 76:e375-e384. [PMID: 35639911 PMCID: PMC9213857 DOI: 10.1093/cid/ciac423] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Revised: 04/01/2022] [Accepted: 05/24/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Prospective cohort studies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) incidence complement case-based surveillance and cross-sectional seroprevalence surveys. METHODS We estimated the incidence of SARS-CoV-2 infection in a national cohort of 6738 US adults, enrolled in March-August 2020. Using Poisson models, we examined the association of social distancing and a composite epidemiologic risk score with seroconversion. The risk score was created using least absolute shrinkage selection operator (LASSO) regression to identify factors predictive of seroconversion. The selected factors were household crowding, confirmed case in household, indoor dining, gathering with groups of ≥10, and no masking in gyms or salons. RESULTS Among 4510 individuals with ≥1 serologic test, 323 (7.3% [95% confidence interval (CI), 6.5%-8.1%]) seroconverted by January 2021. Among 3422 participants seronegative in May-September 2020 and retested from November 2020 to January 2021, 161 seroconverted over 1646 person-years of follow-up (9.8 per 100 person-years [95% CI, 8.3-11.5]). The seroincidence rate was lower among women compared with men (incidence rate ratio [IRR], 0.69 [95% CI, .50-.94]) and higher among Hispanic (2.09 [1.41-3.05]) than white non-Hispanic participants. In adjusted models, participants who reported social distancing with people they did not know (IRR for always vs never social distancing, 0.42 [95% CI, .20-1.0]) and with people they knew (IRR for always vs never, 0.64 [.39-1.06]; IRR for sometimes vs never, 0.60 [.38-.96]) had lower seroconversion risk. Seroconversion risk increased with epidemiologic risk score (IRR for medium vs low score, 1.68 [95% CI, 1.03-2.81]; IRR for high vs low score, 3.49 [2.26-5.58]). Only 29% of those who seroconverted reported isolating, and only 19% were asked about contacts. CONCLUSIONS Modifiable risk factors and poor reach of public health strategies drove SARS-CoV-2 transmission across the United States.
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Affiliation(s)
- Denis Nash
- CORRESPONDING AUTHOR: Denis Nash, Ph.D., MPH CUNY Graduate School of Public Health and Health Policy 55 W. 125th St., 6th Floor New York, NY USA 10027
| | - Madhura S. Rane
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - McKaylee M. Robertson
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Mindy Chang
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Sarah Kulkarni Gorrell
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Rebecca Zimba
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA,Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA
| | - William You
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Amanda Berry
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Chloe Mirzayi
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA,Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA
| | - Shivani Kochhar
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Andrew Maroko
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA,Department of Environmental, Occupational, and Geospatial Health Sciences, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA
| | - Drew A. Westmoreland
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Angela M. Parcesepe
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA,Department of Maternal and Child Health, Gillings School of Public Health, University of North Carolina, Chapel Hill, NC, USA,Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Levi Waldron
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA,Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA
| | - Christian Grov
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA,Department of Community Health and Social Sciences, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA
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Arnold CRK, Srinivasan S, Rodriguez S, Rydzak N, Herzog CM, Gontu A, Bharti N, Small M, Rogers CJ, Schade MM, Kuchipudi SV, Kapur V, Read AF, Ferrari MJ. A longitudinal study of the impact of university student return to campus on the SARS-CoV-2 seroprevalence among the community members. Sci Rep 2022; 12:8586. [PMID: 35597780 PMCID: PMC9124192 DOI: 10.1038/s41598-022-12499-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 05/04/2022] [Indexed: 12/02/2022] Open
Abstract
Returning university students represent large-scale, transient demographic shifts and a potential source of transmission to adjacent communities during the COVID-19 pandemic. In this prospective longitudinal cohort study, we tested for IgG antibodies against SARS-CoV-2 in a non-random cohort of residents living in Centre County prior to the Fall 2020 term at the Pennsylvania State University and following the conclusion of the Fall 2020 term. We also report the seroprevalence in a non-random cohort of students collected at the end of the Fall 2020 term. Of 1313 community participants, 42 (3.2%) were positive for SARS-CoV-2 IgG antibodies at their first visit between 07 August and 02 October 2020. Of 684 student participants who returned to campus for fall instruction, 208 (30.4%) were positive for SARS-CoV-2 antibodies between 26 October and 21 December. 96 (7.3%) community participants returned a positive IgG antibody result by 19 February. Only contact with known SARS-CoV-2-positive individuals and attendance at small gatherings (20-50 individuals) were significant predictors of detecting IgG antibodies among returning students (aOR, 95% CI 3.1, 2.07-4.64; 1.52, 1.03-2.24; respectively). Despite high seroprevalence observed within the student population, seroprevalence in a longitudinal cohort of community residents was low and stable from before student arrival for the Fall 2020 term to after student departure. The study implies that heterogeneity in SARS-CoV-2 transmission can occur in geographically coincident populations.
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Affiliation(s)
- Callum R K Arnold
- Department of Biology, Pennsylvania State University, University Park, PA, 16802, USA.
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, 16802, USA.
| | - Sreenidhi Srinivasan
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, 16802, USA
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, 16802, USA
| | - Sophie Rodriguez
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, 16802, USA
| | - Natalie Rydzak
- Department of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, PA, 16802, USA
| | - Catherine M Herzog
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, 16802, USA
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, 16802, USA
| | - Abhinay Gontu
- Department of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, PA, 16802, USA
| | - Nita Bharti
- Department of Biology, Pennsylvania State University, University Park, PA, 16802, USA
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, 16802, USA
| | - Meg Small
- College of Health and Human Development, Pennsylvania State University, University Park, PA, 16802, USA
- Social Science Research Institute, Pennsylvania State University, University Park, PA, 16802, USA
| | - Connie J Rogers
- Department of Nutritional Sciences, Pennsylvania State University, University Park, PA, 16802, USA
| | - Margeaux M Schade
- College of Health and Human Development, Pennsylvania State University, University Park, PA, 16802, USA
| | - Suresh V Kuchipudi
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, 16802, USA
- Department of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, PA, 16802, USA
| | - Vivek Kapur
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, 16802, USA
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, 16802, USA
- Department of Animal Science, Pennsylvania State University, University Park, PA, 16802, USA
| | - Andrew F Read
- Department of Biology, Pennsylvania State University, University Park, PA, 16802, USA
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, 16802, USA
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, 16802, USA
| | - Matthew J Ferrari
- Department of Biology, Pennsylvania State University, University Park, PA, 16802, USA.
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, 16802, USA.
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Heyming T, Bacon K, Lara B, Knudsen-Robbins C, Tongol A, Sanger T. SARS-CoV-2 Serology Testing in an Asymptomatic, At-Risk Population: Methods, Results, Pitfalls. Infect Dis Rep 2021; 13:910-916. [PMID: 34698190 PMCID: PMC8544562 DOI: 10.3390/idr13040082] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 10/05/2021] [Accepted: 10/14/2021] [Indexed: 11/30/2022] Open
Abstract
The primary aim of this study was to determine the seroprevalence of SARS-CoV-2 antibodies in a population of pediatric healthcare workers (HCWs). This study was conducted 14 May-13 July 2020. Study participants included pediatric HCWs at a pediatric hospital with either direct patient contact or close proximity to patient-care areas. SARS-CoV-2 antibodies were assessed via the Wytcote Superbio SARS-CoV-2 IgM/IgG Antibody Fast Detection Kit and the Abbott Architect SARS-CoV-2 IgG assay. Participants underwent RT-PCR testing upon entry to the study and following rapid IgM+/IgG+ results; respiratory panel PCR (RP-PCR) was performed following IgM+ results. A total of 57 of 289 (19.7%) of participants demonstrated positive serology as assessed by the Wytcote rapid kit (12 on Day 1 and 45 throughout the study). However, only one of these participants demonstrated IgG+ serology via the Abbott assay. Two participants tested SARS-CoV-2+ via RT-PCR testing. One individual was adenovirus+ and enterovirus/rhinovirus+. In our study population, we observed a seroprevalence of SARS-CoV-2 antibodies of 0.35%. The lack of concordance between antibody tests suggests that the Wytcote rapid test kit may not be of use as a screening tool. However, the feasibility of the overall process indicates that a similar methodology may have potential for future epidemiologic surveillance.
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Affiliation(s)
- Theodore Heyming
- Children’s Hospital of Orange County, Orange, CA 92868, USA; (T.H.); (K.B.); (B.L.); (A.T.)
- Department of Emergency Medicine, University of California, Irvine, CA 92868, USA
| | - Kellie Bacon
- Children’s Hospital of Orange County, Orange, CA 92868, USA; (T.H.); (K.B.); (B.L.); (A.T.)
| | - Bryan Lara
- Children’s Hospital of Orange County, Orange, CA 92868, USA; (T.H.); (K.B.); (B.L.); (A.T.)
| | | | - Aprille Tongol
- Children’s Hospital of Orange County, Orange, CA 92868, USA; (T.H.); (K.B.); (B.L.); (A.T.)
| | - Terence Sanger
- Children’s Hospital of Orange County, Orange, CA 92868, USA; (T.H.); (K.B.); (B.L.); (A.T.)
- Department of Electrical Engineering and Computer Science, University of California, Irvine, CA 92697, USA
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Nash D, Rane MS, Chang M, Kulkarni SG, Zimba R, You W, Berry A, Mirzayi C, Kochhar S, Maroko A, Robertson MM, Westmoreland DA, Parcesepe AM, Waldron L, Grov C. SARS-CoV-2 incidence and risk factors in a national, community-based prospective cohort of U.S. adults. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.02.12.21251659. [PMID: 33619505 PMCID: PMC7899475 DOI: 10.1101/2021.02.12.21251659] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
BACKGROUND Epidemiologic risk factors for incident SARS-CoV-2 infection as determined via prospective cohort studies greatly augment and complement information from case-based surveillance and cross-sectional seroprevalence surveys. METHODS We estimated the incidence of SARS-CoV-2 infection and risk factors in a well-characterized, national prospective cohort of 6,738 U.S. adults, enrolled March-August 2020, a subset of whom (n=4,510) underwent repeat serologic testing between May 2020 and January 2021. We examined the crude associations of sociodemographic factors, epidemiologic risk factors, and county-level community transmission with the incidence of seroconversion. In multivariable Poisson models we examined the association of social distancing and a composite score of several epidemiologic risk factors with the rate of seroconversion. FINDINGS Among the 4,510 individuals with at least one serologic test, 323 (7.3%, 95% confidence interval [CI] 6.5%-8.1%) seroconverted by January 2021. Among 3,422 participants seronegative in May-September 2020 and tested during November 2020-January 2021, we observed 161 seroconversions over 1,646 person-years of follow-up (incidence rate of 9.8 per 100 person-years [95%CI 8.3-11.5]). In adjusted models, participants who reported always or sometimes social distancing with people they knew (IRRalways vs. never 0.43, 95%CI 0.21-1.0; IRRsometimes vs. never 0.47, 95%CI 0.22-1.2) and people they did not know (IRRalways vs. never 0.64, 95%CI 0.39-1.1; IRRsometimes vs. never 0.60, 95%CI 0.38-0.97) had lower rates of seroconversion. The rate of seroconversion increased across tertiles of the composite score of epidemiologic risk (IRRmedium vs. low 1.5, 95%CI 0.92-2.4; IRRhigh vs. low 3.0, 95%CI 2.0-4.6). Among the 161 observed seroconversions, 28% reported no symptoms of COVID-like illness (i.e., were asymptomatic), and 27% reported a positive SARS-CoV-2 diagnostic test. Ultimately, only 29% reported isolating and 19% were asked about contacts. INTERPRETATION Modifiable epidemiologic risk factors and poor reach of public health strategies drove SARS-CoV-2 transmission across the U.S during May 2020-January 2021. FUNDING U.S. National Institutes of Allergy and Infectious Diseases (NIAID).
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Affiliation(s)
- Denis Nash
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
- Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA
| | - Madhura S. Rane
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Mindy Chang
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Sarah Gorrell Kulkarni
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Rebecca Zimba
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
- Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA
| | - William You
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Amanda Berry
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Chloe Mirzayi
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
- Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA
| | - Shivani Kochhar
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Andrew Maroko
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
- Department of Environmental, Occupational, and Geospatial Health Sciences, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA
| | - McKaylee M. Robertson
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Drew A. Westmoreland
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
| | - Angela M. Parcesepe
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
- Department of Maternal and Child Health, Gillings School of Public Health, University of North Carolina, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Levi Waldron
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
- Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA
| | - Christian Grov
- Institute for Implementation Science in Population Health (ISPH), City University of New York (CUNY); New York City, New York USA
- Department of Community Health and Social Sciences, Graduate School of Public Health and Health Policy, City University of New York (CUNY); New York City, New York USA
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Arnold CR, Srinivasan S, Rodriguez S, Rydzak N, Herzog CM, Gontu A, Bharti N, Small M, Rogers CJ, Schade MM, Kuchipudi SV, Kapur V, Read A, Ferrari MJ. SARS-CoV-2 Seroprevalence in a University Community: A Longitudinal Study of the Impact of Student Return to Campus on Infection Risk Among Community Members. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.02.17.21251942. [PMID: 33619497 PMCID: PMC7899462 DOI: 10.1101/2021.02.17.21251942] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
BACKGROUND Returning university students represent large-scale, transient demographic shifts and a potential source of transmission to adjacent communities during the COVID-19 pandemic. METHODS In this prospective longitudinal cohort study, we tested for IgG antibodies against SARS-CoV-2 in a non-random cohort of residents living in Centre County prior to the Fall 2020 term at the Pennsylvania State University and following the conclusion of the Fall 2020 term. We also report the seroprevalence in a non-random cohort of students collected at the end of the Fall 2020 term. RESULTS Of 1313 community participants, 42 (3.2%) were positive for SARS-CoV-2 IgG antibodies at their first visit between 07 August and 02 October 2020. Of 684 student participants who returned to campus for fall instruction, 208 (30.4%) were positive for SARS-CoV-2 antibodies between 26 October and 21 December. 96 (7.3%) community participants returned a positive IgG antibody result by 19 February. Only contact with known SARS-CoV-2-positive individuals and attendance at small gatherings (20-50 individuals) were significant predictors of detecting IgG antibodies among returning students (aOR, 95% CI: 3.1, 2.07-4.64; 1.52, 1.03-2.24; respectively). CONCLUSIONS Despite high seroprevalence observed within the student population, seroprevalence in a longitudinal cohort of community residents was low and stable from before student arrival for the Fall 2020 term to after student departure. The study implies that heterogeneity in SARS-CoV-2 transmission can occur in geographically coincident populations.
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Affiliation(s)
- Callum R.K. Arnold
- Department of Biology, Pennsylvania State University, University Park, PA, USA 16802
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
| | - Sreenidhi Srinivasan
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Sophie Rodriguez
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Natalie Rydzak
- Department of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Catherine M. Herzog
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Abhinay Gontu
- Department of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Nita Bharti
- Department of Biology, Pennsylvania State University, University Park, PA, USA 16802
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
| | - Meg Small
- College of Health and Human Development, Pennsylvania State University, University Park, PA, USA 16802
- Social Science Research Institute, Pennsylvania State University, University Park, PA, USA 16802
| | - Connie J. Rogers
- Department of Nutritional Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Margeaux M. Schade
- Social Science Research Institute, Pennsylvania State University, University Park, PA, USA 16802
| | - Suresh V Kuchipudi
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
- Department of Veterinary and Biomedical Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Vivek Kapur
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA 16802
- Department of Animal Science, Pennsylvania State University, University Park, PA, USA 16802
| | - Andrew Read
- Department of Biology, Pennsylvania State University, University Park, PA, USA 16802
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA, USA 16802
| | - Matthew J. Ferrari
- Department of Biology, Pennsylvania State University, University Park, PA, USA 16802
- Center for Infectious Disease Dynamics, Pennsylvania State University, University Park, PA, USA 16802
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Roxhed N, Bendes A, Dale M, Mattsson C, Hanke L, Dodig-Crnković T, Christian M, Meineke B, Elsässer S, Andréll J, Havervall S, Thålin C, Eklund C, Dillner J, Beck O, Thomas CE, McInerney G, Hong MG, Murrell B, Fredolini C, Schwenk JM. Multianalyte serology in home-sampled blood enables an unbiased assessment of the immune response against SARS-CoV-2. Nat Commun 2021; 12:3695. [PMID: 34140485 PMCID: PMC8211676 DOI: 10.1038/s41467-021-23893-4] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 05/21/2021] [Indexed: 12/18/2022] Open
Abstract
Serological testing is essential to curb the consequences of the COVID-19 pandemic. However, most assays are still limited to single analytes and samples collected within healthcare. Thus, we establish a multianalyte and multiplexed approach to reliably profile IgG and IgM levels against several versions of SARS-CoV-2 proteins (S, RBD, N) in home-sampled dried blood spots (DBS). We analyse DBS collected during spring of 2020 from 878 random and undiagnosed individuals from the population in Stockholm, Sweden, and use classification approaches to estimate an accumulated seroprevalence of 12.5% (95% CI: 10.3%-14.7%). This includes 5.4% of the samples being IgG+IgM+ against several SARS-CoV-2 proteins, as well as 2.1% being IgG-IgM+ and 5.0% being IgG+IgM- for the virus' S protein. Subjects classified as IgG+ for several SARS-CoV-2 proteins report influenza-like symptoms more frequently than those being IgG+ for only the S protein (OR = 6.1; p < 0.001). Among all seropositive cases, 30% are asymptomatic. Our strategy enables an accurate individual-level and multiplexed assessment of antibodies in home-sampled blood, assisting our understanding about the undiagnosed seroprevalence and diversity of the immune response against the coronavirus.
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Affiliation(s)
- Niclas Roxhed
- Micro and Nanosystems, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden.
- MedTechLabs, BioClinicum, Karolinska University Hospital, Solna, Sweden.
| | - Annika Bendes
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden
| | - Matilda Dale
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden
| | - Cecilia Mattsson
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden
| | - Leo Hanke
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solna, Sweden
| | - Tea Dodig-Crnković
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden
| | - Murray Christian
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solna, Sweden
| | - Birthe Meineke
- Science for Life Laboratory, Karolinska Institutet, Department of Medical Biochemistry and Biophysics, Division of Genome Biology, Solna, Sweden
- Ming Wai Lau Centre for Reparative Medicine, Stockholm node, Karolinska Institutet, Solna, Sweden
| | - Simon Elsässer
- Science for Life Laboratory, Karolinska Institutet, Department of Medical Biochemistry and Biophysics, Division of Genome Biology, Solna, Sweden
- Ming Wai Lau Centre for Reparative Medicine, Stockholm node, Karolinska Institutet, Solna, Sweden
| | - Juni Andréll
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden
| | - Sebastian Havervall
- Division of Internal Medicine, Department of Clinical Sciences, Karolinska Institutet, Danderyd Hospital, Danderyd, Sweden
| | - Charlotte Thålin
- Division of Internal Medicine, Department of Clinical Sciences, Karolinska Institutet, Danderyd Hospital, Danderyd, Sweden
| | - Carina Eklund
- Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Joakim Dillner
- Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Olof Beck
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Cecilia E Thomas
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden
| | - Gerald McInerney
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solna, Sweden
| | - Mun-Gwan Hong
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden
| | - Ben Murrell
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solna, Sweden
| | - Claudia Fredolini
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden
| | - Jochen M Schwenk
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden.
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Zurochka A, Dobrinina M, Zurochka V, Hu D, Solovyev A, Ryabova L, Kritsky I, Ibragimov R, Sarapultsev A. Seroprevalence of SARS-CoV-2 Antibodies in Symptomatic Individuals Is Higher than in Persons Who Are at Increased Risk Exposure: The Results of the Single-Center, Prospective, Cross-Sectional Study. Vaccines (Basel) 2021; 9:627. [PMID: 34207919 PMCID: PMC8229032 DOI: 10.3390/vaccines9060627] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 06/03/2021] [Accepted: 06/08/2021] [Indexed: 01/08/2023] Open
Abstract
The present study aimed to assess antibody seropositivity prevalence among symptomatic individuals and individuals with a high risk of occupational exposure to SARS-CoV-2. Participants from Chelyabinsk (Russian Federation) who were at an increased risk of exposure to SARS-CoV-2 (high-risk group, n = 1091) and participants who either had symptoms consistent with COVID-19 or were suspected to have experienced COVID-19 in the past (symptomatic group, n = 692) were enrolled between 28 September and 30 December 2020. Blood samples were tested by enzyme-linked immunosorbent assay D-5501 SARS-Cov-2-IgG-EIA-BEST and D-5502 SARS-Cov-2-IgM-EIA-BEST (AO Vector-Best, Novosibirsk, Russia). The overall seropositivity rate was 28.33-28.53%. SARS-CoV-2 antibodies were detected in 17.23% (adjusted prevalence of 17.17-17.29%) of participants in the high-risk and 45.95% (adjusted prevalence of 45.91-46.24%) in the symptomatic group. Higher IgG and IgM titers were observed in women compared to men, as well as in participants in the symptomatic group compared to those in the high-risk group. The results indicate that the seroprevalence among residents in several Russian regions is low (28.38%) and inadequate to provide herd immunity. The lower seroprevalence among participants in the high-risk group may be attributed to the enforcement of healthcare protocols and the use of adequate personal protective equipment.
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Affiliation(s)
- Alexandr Zurochka
- School of Medical Biology, South Ural State University, 454080 Chelyabinsk, Russia; (A.Z.); (V.Z.)
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
| | - Maria Dobrinina
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
| | - Vladimir Zurochka
- School of Medical Biology, South Ural State University, 454080 Chelyabinsk, Russia; (A.Z.); (V.Z.)
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
| | - Desheng Hu
- Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 200092, China;
| | - Alexandr Solovyev
- NPO National Medical Association for the Development of the Expert Activities in the Field of Laboratory Diagnostics “MedLabExpert”, 117042 Moscow, Russia;
- LCC GMK MEDMA, 620102 Ekaterinburg, Russia
| | - Liana Ryabova
- Department of Propedeutics of Internal Diseases, South Ural State Medical University, 454092 Chelyabinsk, Russia;
| | - Igor Kritsky
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
- Institute of Natural Sciences and Mathematics, Ural Federal University Named after the First President of Russia, 620026 Ekaterinburg, Russia
| | - Roman Ibragimov
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
- Institute of Natural Sciences and Mathematics, Ural Federal University Named after the First President of Russia, 620026 Ekaterinburg, Russia
| | - Alexey Sarapultsev
- School of Medical Biology, South Ural State University, 454080 Chelyabinsk, Russia; (A.Z.); (V.Z.)
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
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8
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Hicks J, Klumpp-Thomas C, Kalish H, Shunmugavel A, Mehalko J, Denson JP, Snead KR, Drew M, Corbett KS, Graham BS, Hall MD, Memoli MJ, Esposito D, Sadtler K. Serologic Cross-Reactivity of SARS-CoV-2 with Endemic and Seasonal Betacoronaviruses. J Clin Immunol 2021; 41:906-913. [PMID: 33725211 PMCID: PMC7962425 DOI: 10.1007/s10875-021-00997-6] [Citation(s) in RCA: 109] [Impact Index Per Article: 36.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 02/15/2021] [Indexed: 12/31/2022]
Abstract
In order to properly understand the spread of SARS-CoV-2 infection and development of humoral immunity, researchers have evaluated the presence of serum antibodies of people worldwide experiencing the pandemic. These studies rely on the use of recombinant proteins from the viral genome in order to identify serum antibodies that recognize SARS-CoV-2 epitopes. Here, we discuss the cross-reactivity potential of SARS-CoV-2 antibodies with the full spike proteins of four other betacoronaviruses that cause disease in humans, MERS-CoV, SARS-CoV, HCoV-OC43, and HCoV-HKU1. Using enzyme-linked immunosorbent assays (ELISAs), we detected the potential cross-reactivity of antibodies against SARS-CoV-2 towards the four other coronaviruses, with the strongest cross-recognition between SARS-CoV-2 and SARS /MERS-CoV antibodies, as expected based on sequence homology of their respective spike proteins. Further analysis of cross-reactivity could provide informative data that could lead to intelligently designed pan-coronavirus therapeutics or vaccines.
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Affiliation(s)
- Jennifer Hicks
- Trans-NIH Shared Resource on Biomedical Engineering and Physical Science, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, 20894, USA.,Section on Immuno-Engineering, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Carleen Klumpp-Thomas
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, 20850, USA
| | - Heather Kalish
- Trans-NIH Shared Resource on Biomedical Engineering and Physical Science, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, 20894, USA.,Section on Immuno-Engineering, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Anandakumar Shunmugavel
- Section on Immuno-Engineering, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Jennifer Mehalko
- Protein Expression Laboratory, NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA
| | - John-Paul Denson
- Protein Expression Laboratory, NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA
| | - Kelly R Snead
- Protein Expression Laboratory, NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA
| | - Matthew Drew
- Protein Expression Laboratory, NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA
| | - Kizzmekia S Corbett
- Vaccine Research Center, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Barney S Graham
- Vaccine Research Center, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Matthew D Hall
- National Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, 20850, USA
| | - Matthew J Memoli
- LID Clinical Studies Unit, Laboratory of Infectious Diseases, Division of Intramural Research, National Institute for Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, 20894, USA
| | - Dominic Esposito
- Protein Expression Laboratory, NCI RAS Initiative, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA
| | - Kaitlyn Sadtler
- Section on Immuno-Engineering, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, 20892, USA.
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9
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Polvere I, Parrella A, Casamassa G, D’Andrea S, Tizzano A, Cardinale G, Voccola S, Porcaro P, Stilo R, Vito P, Zotti T. Seroprevalence of Anti-SARS-CoV-2 IgG and IgM among Adults over 65 Years Old in the South of Italy. Diagnostics (Basel) 2021; 11:483. [PMID: 33803299 PMCID: PMC8001683 DOI: 10.3390/diagnostics11030483] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 03/02/2021] [Accepted: 03/05/2021] [Indexed: 12/19/2022] Open
Abstract
SARS-CoV-2 is a zoonotic betacoronavirus associated with worldwide transmission of COVID-19 disease. By the beginning of March, WHO reported about 113,820,000 confirmed cases including more than 2,527,000 deaths all over the world. However, the true extent of virus circulation or its real infection/fatality ratio is not well-estimated due to the huge portion of asymptomatic infections. In this observational study, we have estimated the prevalence of specific immunoglobulin M and G directed towards SARS-CoV-2 antigen in a cohort of 1383 adult volunteers aged over 65 years old, living in the district of Benevento, in the South of Italy. Serological screening was carried out on capillary blood in September 2020, seven months after pandemic outbreak in Italy, to evaluate virus circulation and antibody response among elderly adults, in which severe symptoms due to viral infection are more common. The overall seroprevalence of anti-SARS-CoV-2 antibodies was 4.70% (CI 3.70%-5.95%) with no statistically significant differences between sexes. Among these, 69.69% (CI 55.61%-77.80%) tested positive to IgM, 23.08% (CI 14.51%-34.64%) to IgG and 9.23% (CI 4.30%-18.71%) was positive for both. All patients that were positive to IgM underwent molecular testing through RT-qPCR on oral-rhino pharyngeal swabs and only one specimen was positive for SARS-CoV-2 RNA detection. Instead, the presence of IgG from screened volunteers was confirmed by re-testing serum samples using both an ELISA assay validated for in vitro diagnostic use (IVD) and a recently published synthetic peptide-based ELISA assay. In conclusion, our report suggests that (1) early restrictions were successful in limiting COVID-19 diffusion in the district of Benevento; (2) rapid serological analysis is an ideal testing for both determining real seroprevalence and massive screening, whereas detection of viral RNA remains a gold standard for identification of infected patients; (3) even among people without COVID-19 related symptoms, the antibody response against SARS-CoV-2 antigens has individual features.
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Affiliation(s)
- Immacolata Polvere
- Dipartimento di Scienze e Tecnologie, Università degli Studi del Sannio, 82100 Benevento, Italy; (I.P.); (S.D.); (A.T.); (R.S.)
- Genus Biotech, Università degli Studi del Sannio, 82100 Benevento, Italy;
| | - Alfredina Parrella
- Consorzio Sannio Tech, 82030 Apollosa, Italy; (A.P.); (G.C.); (G.C.); (P.P.)
| | - Giovanna Casamassa
- Consorzio Sannio Tech, 82030 Apollosa, Italy; (A.P.); (G.C.); (G.C.); (P.P.)
| | - Silvia D’Andrea
- Dipartimento di Scienze e Tecnologie, Università degli Studi del Sannio, 82100 Benevento, Italy; (I.P.); (S.D.); (A.T.); (R.S.)
| | - Annamaria Tizzano
- Dipartimento di Scienze e Tecnologie, Università degli Studi del Sannio, 82100 Benevento, Italy; (I.P.); (S.D.); (A.T.); (R.S.)
| | - Gaetano Cardinale
- Consorzio Sannio Tech, 82030 Apollosa, Italy; (A.P.); (G.C.); (G.C.); (P.P.)
| | - Serena Voccola
- Genus Biotech, Università degli Studi del Sannio, 82100 Benevento, Italy;
- Consorzio Sannio Tech, 82030 Apollosa, Italy; (A.P.); (G.C.); (G.C.); (P.P.)
| | - Piercarmine Porcaro
- Consorzio Sannio Tech, 82030 Apollosa, Italy; (A.P.); (G.C.); (G.C.); (P.P.)
| | - Romania Stilo
- Dipartimento di Scienze e Tecnologie, Università degli Studi del Sannio, 82100 Benevento, Italy; (I.P.); (S.D.); (A.T.); (R.S.)
| | - Pasquale Vito
- Dipartimento di Scienze e Tecnologie, Università degli Studi del Sannio, 82100 Benevento, Italy; (I.P.); (S.D.); (A.T.); (R.S.)
- Genus Biotech, Università degli Studi del Sannio, 82100 Benevento, Italy;
| | - Tiziana Zotti
- Dipartimento di Scienze e Tecnologie, Università degli Studi del Sannio, 82100 Benevento, Italy; (I.P.); (S.D.); (A.T.); (R.S.)
- Genus Biotech, Università degli Studi del Sannio, 82100 Benevento, Italy;
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10
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Laing ED, Sterling SL, Richard SA, Epsi NJ, Coggins S, Samuels EC, Phogat S, Yan L, Moreno N, Coles CL, Drew M, Mehalko J, English CE, Merritt S, Mende K, Munster VJ, de Wit E, Chung KK, Millar EV, Tribble DR, Simons MP, Pollett SD, Agan BK, Esposito D, Lanteri C, Clifton GT, Mitre E, Burgess TH, Broder CC. Antigen-based multiplex strategies to discriminate SARS-CoV-2 natural and vaccine induced immunity from seasonal human coronavirus humoral responses. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.02.10.21251518. [PMID: 33594376 PMCID: PMC7885935 DOI: 10.1101/2021.02.10.21251518] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Sensitive and specific SARS-CoV-2 antibody assays remain critical for community and hospital-based SARS-CoV-2 sero-surveillance. With the rollout of SARS-CoV-2 vaccines, such assays must be able to distinguish vaccine from natural immunity to SARS-CoV-2 and related human coronaviruses. Here, we developed and implemented multiplex microsphere-based immunoassay strategies for COVD-19 antibody studies that incorporates spike protein trimers of SARS-CoV-2 and the endemic seasonal human coronaviruses (HCoV), enabling high throughout measurement of pre-existing cross-reactive antibodies. We varied SARS-CoV-2 antigen compositions within the multiplex assay, allowing direct comparisons of the effects of spike protein, receptor-binding domain protein (RBD) and nucleocapsid protein (NP) based SARS-CoV-2 antibody detection. Multiplex immunoassay performance characteristics are antigen-dependent, and sensitivities and specificities range 92-99% and 94-100%, respectively, for human subject samples collected as early as 7-10 days from symptom onset. SARS-CoV-2 spike and RBD had a strong correlative relationship for the detection of IgG. Correlation between detectable IgG reactive with spike and NP also had strong relationship, however, several PCR-positive and spike IgG-positive serum samples were NP IgG-negative. This spike and NP multiplex immunoassay has the potential to be useful for differentiation between vaccination and natural infection induced antibody responses. We also assessed the induction of de novo SARS-CoV-2 IgG cross reactions with SARS-CoV and MERS-CoV spike proteins. Furthermore, multiplex immunoassays that incorporate spike proteins of SARS-CoV-2 and HCoVs will permit investigations into the influence of HCoV antibodies on COVID-19 clinical outcomes and SARS-CoV-2 antibody durability.
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Affiliation(s)
- Eric D. Laing
- Department of Microbiology and Immunology, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Spencer L. Sterling
- Department of Microbiology and Immunology, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
| | - Stephanie A. Richard
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Nusrat J. Epsi
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Si’Ana Coggins
- Department of Microbiology and Immunology, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
| | - Emily C. Samuels
- Department of Microbiology and Immunology, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
| | - Shreshta Phogat
- Department of Microbiology and Immunology, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
| | - Lianying Yan
- Department of Microbiology and Immunology, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
| | - Nicole Moreno
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Christian L. Coles
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Matthew Drew
- Protein Expression Laboratory, National Cancer Institute RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Jennifer Mehalko
- Protein Expression Laboratory, National Cancer Institute RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Caroline E. English
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Scott Merritt
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- Brooke Army Medical Center, JBSA Fort Sam Houston, TX, USA
| | - Katrin Mende
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- Brooke Army Medical Center, JBSA Fort Sam Houston, TX, USA
| | - Vincent J. Munster
- Laboratory of Virology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Emmie de Wit
- Laboratory of Virology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA
| | - Kevin K. Chung
- Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Eugene V. Millar
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - David R. Tribble
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Mark P. Simons
- Department of Microbiology and Immunology, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Simon D. Pollett
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Brian K. Agan
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Dominic Esposito
- Protein Expression Laboratory, National Cancer Institute RAS Initiative, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Charlotte Lanteri
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
| | | | - Edward Mitre
- Department of Microbiology and Immunology, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Timothy H. Burgess
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA
| | - Christopher C. Broder
- Department of Microbiology and Immunology, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
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