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Cox SN, Roychoudhury P, Frivold C, Acker Z, Babu TM, Boisvert CL, Carone M, Ehmen B, Englund JA, Feldstein LR, Gamboa L, Grindstaff S, Grioni HM, Han PD, Hoffman KL, Kim HG, Kuntz JL, Lo NK, Lockwood CM, McCaffrey K, Mularski RA, Hatchie TL, Reich SL, Schmidt MA, Smith N, Starita LM, Varga A, Yetz N, Naleway AL, Weil AA, Chu HY. Household Transmission and Genomic Diversity of Respiratory Syncytial Virus (RSV) in the United States, 2022-2023. Clin Infect Dis 2025:ciaf048. [PMID: 40084542 DOI: 10.1093/cid/ciaf048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2024] [Indexed: 03/16/2025] Open
Abstract
BACKGROUND Household transmission of respiratory viruses may drive community spread. Few recent studies have examined household respiratory syncytial virus (RSV) transmission in the United States. METHODS We conducted a prospective community-based cohort study from 1 June 2022 to 31 May 2023. Participants had blood samples collected and completed nasal swabs and surveys at least weekly, irrespective of symptoms. We tested serum for RSV antibody, nasal swabs by quantitative reverse transcription polymerase chain reaction (RT-qPCR), and performed whole genome sequencing. We evaluated secondary RSV transmission and associated risk factors based on a log-linear Poisson regression model. RESULTS RSV was detected among 310 (10%) participants within 200 (20%) households. Most (94%) index cases were symptomatic. We identified 37 cases of potential secondary transmission within 14 days of a distinct index case (10%, 95% confidence interval [CI]: 7%, 14%); median age of index and secondary cases were 6 (interquartile range [IQR]: 3-10) and 35 (7-41) years, respectively, with 89% (24/27) of index cases aged 6 months to 12 years. Factors associated with increased risk of RSV transmission included index case viral detection ≥1 week and contact age ≤12 years. Of 120 sequenced specimens, the main lineages represented were A.d.5.2 (n = 37) and A.d.1 (n = 30). Sequenced viruses from households with ≥2 RSV infections were similar when occurring within ≤14 days (mean pairwise difference 4 [range 0-13], n = 17 households), compared to those >14 days (137 [37-236], n = 2). CONCLUSIONS Most RSV household transmission occurs from infants and young children to adults. Viral genome sequencing demonstrated that multiple household infections within a 14-day period are likely due to within-household transmission.
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Affiliation(s)
- Sarah N Cox
- Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Pavitra Roychoudhury
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Collrane Frivold
- Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Zack Acker
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Tara M Babu
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | | | - Marco Carone
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Brenna Ehmen
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Janet A Englund
- Seattle Children's Research Institute, Seattle, Washington, USA
- Department of Pediatrics, University of Washington, Seattle, Washington, USA
| | - Leora R Feldstein
- Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Luis Gamboa
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Sally Grindstaff
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Hanna M Grioni
- Seattle Children's Research Institute, Seattle, Washington, USA
| | - Peter D Han
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Katherine L Hoffman
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Hyeong Geon Kim
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
| | - Jennifer L Kuntz
- Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Natalie K Lo
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Christina M Lockwood
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Kathryn McCaffrey
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | | | - Tara L Hatchie
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Sacha L Reich
- Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Mark A Schmidt
- Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Ning Smith
- Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Lea M Starita
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Genome Science, University of Washington, Seattle, Washington, USA
| | - Alexandra Varga
- Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Neil Yetz
- Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | | | - Ana A Weil
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Helen Y Chu
- Department of Medicine, University of Washington, Seattle, Washington, USA
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2
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Kim AE, Bennett JC, Luiten K, O'Hanlon JA, Wolf CR, Magedson A, Han PD, Acker Z, Regelbrugge L, McCaffrey KM, Stone J, Reinhart D, Capodanno BJ, Morse SS, Bedford T, Englund JA, Boeckh M, Starita LM, Uyeki TM, Carone M, Weil A, Chu HY. Comparative Diagnostic Utility of SARS-CoV-2 Rapid Antigen and Molecular Testing in a Community Setting. J Infect Dis 2024; 230:363-373. [PMID: 38531685 DOI: 10.1093/infdis/jiae150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 03/12/2024] [Accepted: 03/25/2024] [Indexed: 03/28/2024] Open
Abstract
BACKGROUND SARS-CoV-2 antigen-detection rapid diagnostic tests (Ag-RDTs) have become widely utilized but longitudinal characterization of their community-based performance remains incompletely understood. METHODS This prospective longitudinal study at a large public university in Seattle, WA utilized remote enrollment, online surveys, and self-collected nasal swab specimens to evaluate Ag-RDT performance against real-time reverse transcription polymerase chain reaction (rRT-PCR) in the context of SARS-CoV-2 Omicron. Ag-RDT sensitivity and specificity within 1 day of rRT-PCR were evaluated by symptom status throughout the illness episode and Orf1b cycle threshold (Ct). RESULTS From February to December 2022, 5757 participants reported 17 572 Ag-RDT results and completed 12 674 rRT-PCR tests, of which 995 (7.9%) were rRT-PCR positive. Overall sensitivity and specificity were 53.0% (95% confidence interval [CI], 49.6%-56.4%) and 98.8% (95% CI, 98.5%-99.0%), respectively. Sensitivity was comparatively higher for Ag-RDTs used 1 day after rRT-PCR (69.0%), 4-7 days after symptom onset (70.1%), and Orf1b Ct ≤20 (82.7%). Serial Ag-RDT sensitivity increased with repeat testing ≥2 (68.5%) and ≥4 (75.8%) days after an initial Ag-RDT-negative result. CONCLUSIONS Ag-RDT performance varied by clinical characteristics and temporal testing patterns. Our findings support recommendations for serial testing following an initial Ag-RDT-negative result, especially among recently symptomatic persons or those at high risk for SARS-CoV-2 infection.
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Affiliation(s)
- Ashley E Kim
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Julia C Bennett
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Kyle Luiten
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Jessica A O'Hanlon
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Caitlin R Wolf
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Ariana Magedson
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Peter D Han
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Zack Acker
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Lani Regelbrugge
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | | | - Jeremey Stone
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - David Reinhart
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Benjamin J Capodanno
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Stephen S Morse
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Trevor Bedford
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Howard Hughes Medical Institute, Seattle, Washington, USA
| | - Janet A Englund
- Seattle Children's Research Institute, Seattle, Washington, USA
| | - Michael Boeckh
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Lea M Starita
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Timothy M Uyeki
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Marco Carone
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Ana Weil
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Helen Y Chu
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
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3
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Bennett JC, O'Hanlon J, Acker Z, Han PD, McDonald D, Wright T, Luiten KG, Regelbrugge L, McCaffrey KM, Pfau B, Wolf CR, Gottlieb GS, Hughes JP, Carone M, Starita LM, Chu HY, Weil AA. Evaluation of a novel university-based testing platform to increase access to SARS-CoV-2 testing during the COVID-19 pandemic in a cohort study. BMJ Open 2024; 14:e081837. [PMID: 38834321 PMCID: PMC11163660 DOI: 10.1136/bmjopen-2023-081837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 05/15/2024] [Indexed: 06/06/2024] Open
Abstract
OBJECTIVE We aimed to evaluate the feasibility and utility of an unsupervised testing mechanism, in which participants pick up a swab kit, self-test (unsupervised) and return the kit to an on-campus drop box, as compared with supervised self-testing at staffed locations. DESIGN University SARS-CoV-2 testing cohort. SETTING Husky Coronavirus Testing provided voluntary SARS-CoV-2 testing at a university in Seattle, USA. OUTCOME MEASURES We computed descriptive statistics to describe the characteristics of the study sample. Adjusted logistic regression implemented via generalised estimating equations was used to estimate the odds of a self-swab being conducted through unsupervised versus supervised testing mechanisms by participant characteristics, including year of study enrolment, pre-Omicron versus post-Omicron time period, age, sex, race, ethnicity, affiliation and symptom status. RESULTS From September 2021 to July 2022, we received 92 499 supervised and 26 800 unsupervised self-swabs. Among swabs received by the laboratory, the overall error rate for supervised versus unsupervised swabs was 0.3% vs 4%, although this declined to 2% for unsupervised swabs by the spring of the academic year. Results were returned for 92 407 supervised (5% positive) and 25 836 unsupervised (4%) swabs from 26 359 participants. The majority were students (79%), 61% were female and most identified as white (49%) or Asian (34%). The use of unsupervised testing increased during the Omicron wave when testing demand was high and stayed constant in spring 2022 even when testing demand fell. We estimated the odds of using unsupervised versus supervised testing to be significantly greater among those <25 years of age (p<0.001), for Hispanic versus non-Hispanic individuals (OR 1.2, 95% CI 1.0 to 1.3, p=0.01) and lower among individuals symptomatic versus asymptomatic or presymptomatic (0.9, 95% CI 0.8 to 0.9, p<0.001). CONCLUSIONS Unsupervised swab collection permitted increased testing when demand was high, allowed for access to a broader proportion of the university community and was not associated with a substantial increase in testing errors.
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Affiliation(s)
| | - Jessica O'Hanlon
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | | | - Peter D Han
- Brotman Baty Institute, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Devon McDonald
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Tessa Wright
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Kyle G Luiten
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | | | | | - Brian Pfau
- Brotman Baty Institute, Seattle, Washington, USA
| | - Caitlin R Wolf
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Geoffrey S Gottlieb
- Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Global Health, University of Washington, Seattle, Washington, USA
- Environmental Health & Safety Department, University of Washington, Seattle, WA, USA
| | - James P Hughes
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Marco Carone
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Lea M Starita
- Brotman Baty Institute, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Helen Y Chu
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Ana A Weil
- Department of Medicine, University of Washington, Seattle, Washington, USA
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4
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Perofsky AC, Hansen CL, Burstein R, Boyle S, Prentice R, Marshall C, Reinhart D, Capodanno B, Truong M, Schwabe-Fry K, Kuchta K, Pfau B, Acker Z, Lee J, Sibley TR, McDermot E, Rodriguez-Salas L, Stone J, Gamboa L, Han PD, Adler A, Waghmare A, Jackson ML, Famulare M, Shendure J, Bedford T, Chu HY, Englund JA, Starita LM, Viboud C. Impacts of human mobility on the citywide transmission dynamics of 18 respiratory viruses in pre- and post-COVID-19 pandemic years. Nat Commun 2024; 15:4164. [PMID: 38755171 PMCID: PMC11098821 DOI: 10.1038/s41467-024-48528-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 05/02/2024] [Indexed: 05/18/2024] Open
Abstract
Many studies have used mobile device location data to model SARS-CoV-2 dynamics, yet relationships between mobility behavior and endemic respiratory pathogens are less understood. We studied the effects of population mobility on the transmission of 17 endemic viruses and SARS-CoV-2 in Seattle over a 4-year period, 2018-2022. Before 2020, visits to schools and daycares, within-city mixing, and visitor inflow preceded or coincided with seasonal outbreaks of endemic viruses. Pathogen circulation dropped substantially after the initiation of COVID-19 stay-at-home orders in March 2020. During this period, mobility was a positive, leading indicator of transmission of all endemic viruses and lagging and negatively correlated with SARS-CoV-2 activity. Mobility was briefly predictive of SARS-CoV-2 transmission when restrictions relaxed but associations weakened in subsequent waves. The rebound of endemic viruses was heterogeneously timed but exhibited stronger, longer-lasting relationships with mobility than SARS-CoV-2. Overall, mobility is most predictive of respiratory virus transmission during periods of dramatic behavioral change and at the beginning of epidemic waves.
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Affiliation(s)
- Amanda C Perofsky
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.
| | - Chelsea L Hansen
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
- PandemiX Center, Department of Science & Environment, Roskilde University, Roskilde, Denmark
| | - Roy Burstein
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Shanda Boyle
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Robin Prentice
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Cooper Marshall
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - David Reinhart
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Ben Capodanno
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Melissa Truong
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Kristen Schwabe-Fry
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Kayla Kuchta
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Brian Pfau
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Zack Acker
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Jover Lee
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Thomas R Sibley
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Evan McDermot
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Leslie Rodriguez-Salas
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Jeremy Stone
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Luis Gamboa
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
| | - Peter D Han
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Amanda Adler
- Seattle Children's Research Institute, Seattle, WA, USA
| | - Alpana Waghmare
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Seattle Children's Research Institute, Seattle, WA, USA
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | | | - Michael Famulare
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, WA, USA
| | - Jay Shendure
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
| | - Trevor Bedford
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
| | - Helen Y Chu
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Janet A Englund
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Seattle Children's Research Institute, Seattle, WA, USA
- Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Lea M Starita
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Cécile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
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5
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Bennett JC, Luiten KG, O'Hanlon J, Han PD, McDonald D, Wright T, Wolf CR, Lo NK, Acker Z, Regelbrugge L, McCaffrey KM, Pfau B, Stone J, Schwabe-Fry K, Lockwood CM, Guthrie BL, Gottlieb GS, Englund JA, Uyeki TM, Carone M, Starita LM, Weil AA, Chu HY. Utilizing a university testing program to estimate relative effectiveness of monovalent COVID-19 mRNA booster vaccine versus two-dose primary series against symptomatic SARS-CoV-2 infection. Vaccine 2024; 42:1332-1341. [PMID: 38307746 DOI: 10.1016/j.vaccine.2024.01.080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 01/23/2024] [Accepted: 01/24/2024] [Indexed: 02/04/2024]
Abstract
Vaccine effectiveness (VE) studies utilizing the test-negative design are typically conducted in clinical settings, rather than community populations, leading to bias in VE estimates against mild disease and limited information on VE in healthy young adults. In a community-based university population, we utilized data from a large SARS-CoV-2 testing program to estimate relative VE of COVID-19 mRNA vaccine primary series and monovalent booster dose versus primary series only against symptomatic SARS-CoV-2 infection from September 2021 to July 2022. We used the test-negative design and logistic regression implemented via generalized estimating equations adjusted for age, calendar time, prior SARS-CoV-2 infection, and testing frequency (proxy for test-seeking behavior) to estimate relative VE. Analyses included 2,218 test-positive cases (59 % received monovalent booster dose) and 9,615 test-negative controls (62 %) from 9,066 individuals, with median age of 21 years, mostly students (71 %), White (56 %) or Asian (28 %), and with few comorbidities (3 %). More cases (23 %) than controls (6 %) had COVID-19-like illness. Estimated adjusted relative VE of primary series and monovalent booster dose versus primary series only against symptomatic SARS-CoV-2 infection was 40 % (95 % CI: 33-47 %) during the overall analysis period and 46 % (39-52 %) during the period of Omicron circulation. Relative VE was greater for those without versus those with prior SARS-CoV-2 infection (41 %, 34-48 % versus 33 %, 9 %-52 %, P < 0.001). Relative VE was also greater in the six months after receiving a booster dose (41 %, 33-47 %) compared to more than six months (27 %, 8-42 %), but this difference was not statistically significant (P = 0.06). In this relatively young and healthy adult population, an mRNA monovalent booster dose provided increased protection against symptomatic SARS-CoV-2 infection, overall and with the Omicron variant. University testing programs may be utilized for estimating VE in healthy young adults, a population that is not well-represented by routine VE studies.
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Affiliation(s)
- Julia C Bennett
- Department of Medicine, University of Washington, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA.
| | - Kyle G Luiten
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jessica O'Hanlon
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Peter D Han
- Brotman Baty Institute, Seattle, WA, USA; Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Devon McDonald
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Tessa Wright
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Caitlin R Wolf
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Natalie K Lo
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Zack Acker
- Brotman Baty Institute, Seattle, WA, USA
| | | | | | - Brian Pfau
- Brotman Baty Institute, Seattle, WA, USA
| | - Jeremey Stone
- Brotman Baty Institute, Seattle, WA, USA; Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Christina M Lockwood
- Brotman Baty Institute, Seattle, WA, USA; Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA
| | - Brandon L Guthrie
- Department of Epidemiology, University of Washington, Seattle, WA, USA; Department of Global Health, University of Washington, Seattle, WA, USA
| | - Geoffrey S Gottlieb
- Department of Medicine, University of Washington, Seattle, WA, USA; Department of Global Health, University of Washington, Seattle, WA, USA; Center for Emerging and Re-Emerging Infectious Diseases, University of Washington, Seattle, WA, USA; Environmental Health & Safety Department, University of Washington, Seattle, WA, USA
| | - Janet A Englund
- Seattle Children's Research Institute, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Timothy M Uyeki
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Marco Carone
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Lea M Starita
- Brotman Baty Institute, Seattle, WA, USA; Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Ana A Weil
- Department of Medicine, University of Washington, Seattle, WA, USA; Department of Global Health, University of Washington, Seattle, WA, USA; Center for Emerging and Re-Emerging Infectious Diseases, University of Washington, Seattle, WA, USA
| | - Helen Y Chu
- Department of Medicine, University of Washington, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA; Center for Emerging and Re-Emerging Infectious Diseases, University of Washington, Seattle, WA, USA
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6
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Heimonen J, Chow EJ, Wang Y, Hughes JP, Rogers J, Emanuels A, O’Hanlon J, Han PD, Wolf CR, Logue JK, Ogokeh CE, Rolfes MA, Uyeki TM, Starita L, Englund JA, Chu HY. Risk of Subsequent Respiratory Virus Detection After Primary Virus Detection in a Community Household Study-King County, Washington, 2019-2021. J Infect Dis 2024; 229:422-431. [PMID: 37531658 PMCID: PMC10873185 DOI: 10.1093/infdis/jiad305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 07/19/2023] [Accepted: 07/31/2023] [Indexed: 08/04/2023] Open
Abstract
BACKGROUND The epidemiology of respiratory viral infections is complex. How infection with one respiratory virus affects risk of subsequent infection with the same or another respiratory virus is not well described. METHODS From October 2019 to June 2021, enrolled households completed active surveillance for acute respiratory illness (ARI), and participants with ARI self-collected nasal swab specimens; after April 2020, participants with ARI or laboratory-confirmed severe acute respiratory syndrome coronavirus 2 and their household members self-collected nasal swab specimens. Specimens were tested using multiplex reverse-transcription polymerase chain reaction for respiratory viruses. A Cox regression model with a time-dependent covariate examined risk of subsequent detections following a specific primary viral detection. RESULTS Rhinovirus was the most frequently detected pathogen in study specimens (406 [9.5%]). Among 51 participants with multiple viral detections, rhinovirus to seasonal coronavirus (8 [14.8%]) was the most common viral detection pairing. Relative to no primary detection, there was a 1.03-2.06-fold increase in risk of subsequent virus detection in the 90 days after primary detection; risk varied by primary virus: human parainfluenza virus, rhinovirus, and respiratory syncytial virus were statistically significant. CONCLUSIONS Primary virus detection was associated with higher risk of subsequent virus detection within the first 90 days after primary detection.
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Affiliation(s)
- Jessica Heimonen
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Eric J Chow
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
- Prevention Division, Public Health—Seattle & King County, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Yongzhe Wang
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - James P Hughes
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Julia Rogers
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Anne Emanuels
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Jessica O’Hanlon
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Peter D Han
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Caitlin R Wolf
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Jennifer K Logue
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Constance E Ogokeh
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- Military and Health Research Foundation, Laurel, Maryland, USA
| | - Melissa A Rolfes
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Timothy M Uyeki
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Lea Starita
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Janet A Englund
- Division of Pediatric Infectious Diseases, Seattle Children's Research Institute, Seattle, Washington, USA
- Department of Pediatrics, University of Washington, Seattle, Washington, USA
| | - Helen Y Chu
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
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7
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Pfau B, Opsahl J, Crew R, Best S, Han PD, Heidl S, McDermot E, Stone J, Schwabe-Fry K, MacMillan MP, O'Hanlon J, Sohlberg S, Acker Z, Ehmen B, Englund JA, Konnick EQ, Chu HY, Weil AA, Lockwood CM, Starita LM. Tiny swabs: nasal swabs integrated into tube caps facilitate large-scale self-collected SARS-CoV-2 testing. J Clin Microbiol 2024; 62:e0128523. [PMID: 38131692 PMCID: PMC10865831 DOI: 10.1128/jcm.01285-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 11/07/2023] [Indexed: 12/23/2023] Open
Abstract
The COVID-19 pandemic spurred the development of innovative solutions for specimen collection and molecular detection for large-scale community testing. Among these developments is the RHINOstic nasal swab, a plastic anterior nares swab built into the cap of a standard matrix tube that facilitates automated processing of up to 96 specimens at a time. In a study of unsupervised self-collection utilizing these swabs, we demonstrate comparable analytic performance and shipping stability compared to traditional anterior nares swabs, as well as significant improvements in laboratory processing efficiency. The use of these swabs may allow laboratories to accommodate large numbers of sample collections during periods of high testing demand. Automation-friendly nasal swabs are an important tool for high-throughput processing of samples that may be adopted in response to future respiratory viral pandemics.
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Affiliation(s)
- Brian Pfau
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Jordan Opsahl
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Ruben Crew
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Sabrina Best
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Peter D. Han
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Sarah Heidl
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Evan McDermot
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Jeremy Stone
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | | | | | - Jessica O'Hanlon
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Sarah Sohlberg
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Zack Acker
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Brenna Ehmen
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Janet A. Englund
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Pediatrics, University of Washington, Seattle, Washington, USA
- Seattle Children’s Research Institute, Seattle, Washington, USA
| | - Eric Q. Konnick
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
| | - Helen Y. Chu
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
- Center for Emerging and Re-Emerging Infectious Diseases, University of Washington, Seattle, Washington, USA
| | - Ana A. Weil
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
- Center for Emerging and Re-Emerging Infectious Diseases, University of Washington, Seattle, Washington, USA
- Department of Global Health, University of Washington, Seattle, Washington, USA
| | - Christina M. Lockwood
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Lea M. Starita
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - The Seattle Flu Alliance InvestigatorsBedfordTrevorBoeckhMichaelChuHelen Y.EnglundJanet A.LockwoodChristina M.LutzBarry R.PrenticeRobinShendureJayStaritaLea M.WaghmereAlpanaWeilAna A.
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Pediatrics, University of Washington, Seattle, Washington, USA
- Seattle Children’s Research Institute, Seattle, Washington, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
- Center for Emerging and Re-Emerging Infectious Diseases, University of Washington, Seattle, Washington, USA
- Department of Global Health, University of Washington, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
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8
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Soto R, Paul L, Porucznik CA, Xie H, Stinnett RC, Briggs B, Biggerstaff M, Stanford J, Schlaberg R. Effectiveness of Self-Collected, Ambient Temperature-Preserved Nasal Swabs Compared to Samples Collected by Trained Staff for Genotyping of Respiratory Viruses by Shotgun RNA Sequencing: Comparative Study. JMIR Form Res 2023; 7:e32848. [PMID: 37999952 DOI: 10.2196/32848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 02/16/2023] [Accepted: 08/09/2023] [Indexed: 11/25/2023] Open
Abstract
BACKGROUND The SARS-CoV-2 pandemic has underscored the need for field specimen collection and transport to diagnostic and public health laboratories. Self-collected nasal swabs transported without dependency on a cold chain have the potential to remove critical barriers to testing, expand testing capacity, and reduce opportunities for exposure of health professionals in the context of a pandemic. OBJECTIVE We compared nasal swab collection by study participants from themselves and their children at home to collection by trained research staff. METHODS Each adult participant collected 1 nasal swab, sampling both nares with the single swab, after which they collected 1 nasal swab from 1 child. After all the participant samples were collected for the household, the research staff member collected a separate single duplicate sample from each individual. Immediately after the sample collection, the adult participants completed a questionnaire about the acceptability of the sampling procedures. Swabs were placed in temperature-stable preservative and respiratory viruses were detected by shotgun RNA sequencing, enabling viral genome analysis. RESULTS In total, 21 households participated in the study, each with 1 adult and 1 child, yielding 42 individuals with paired samples. Study participants reported that self-collection was acceptable. Agreement between identified respiratory viruses in both swabs by RNA sequencing demonstrated that adequate collection technique was achieved by brief instructions. CONCLUSIONS Our results support the feasibility of a scalable and convenient means for the identification of respiratory viruses and implementation in pandemic preparedness for novel respiratory pathogens.
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Affiliation(s)
- Raymond Soto
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
| | - Litty Paul
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
| | - Christina A Porucznik
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
| | - Heng Xie
- IDbyDNA, Salt Lake City, UT, United States
| | | | | | - Matthew Biggerstaff
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Joseph Stanford
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
| | - Robert Schlaberg
- Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, United States
- IDbyDNA, Salt Lake City, UT, United States
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9
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Bennett JC, Emanuels A, Heimonen J, O'Hanlon J, Hughes JP, Han PD, Chow EJ, Ogokeh CE, Rolfes MA, Lockwood CM, Pfau B, Uyeki TM, Shendure J, Hoag S, Fay K, Lee J, Sibley TR, Rogers JH, Starita LM, Englund JA, Chu HY. Streptococcus pneumoniae nasal carriage patterns with and without common respiratory virus detections in households in Seattle, WA, USA before and during the COVID-19 pandemic. Front Pediatr 2023; 11:1198278. [PMID: 37484765 PMCID: PMC10361771 DOI: 10.3389/fped.2023.1198278] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 06/23/2023] [Indexed: 07/25/2023] Open
Abstract
Background Respiratory viruses might influence Streptococcus pneumoniae nasal carriage and subsequent disease risk. We estimated the association between common respiratory viruses and semiquantitative S. pneumoniae nasal carriage density in a household setting before and during the COVID-19 pandemic. Methods From November 2019-June 2021, we enrolled participants in a remote household surveillance study of respiratory pathogens. Participants submitted weekly reports of acute respiratory illness (ARI) symptoms. Mid-turbinate or anterior nasal swabs were self-collected at enrollment, when ARI occurred, and, in the second year of the study only, from household contacts after SARS-CoV-2 was detected in a household member. Specimens were tested using multiplex reverse-transcription PCR for respiratory pathogens, including S. pneumoniae, rhinovirus, adenovirus, common human coronavirus, influenza A/B virus, respiratory syncytial virus (RSV) A/B, human metapneumovirus, enterovirus, and human parainfluenza virus. We estimated differences in semiquantitative S. pneumoniae nasal carriage density, estimated by the inverse of S. pneumoniae relative cycle threshold (Crt) values, with and without viral detection for any virus and for specific respiratory viruses using linear generalized estimating equations of S. pneumoniae Crt values on virus detection adjusted for age and swab type and accounting for clustering of swabs within households. Results We collected 346 swabs from 239 individuals in 151 households that tested positive for S. pneumoniae (n = 157 with and 189 without ≥1 viruses co-detected). Difficulty breathing, cough, and runny nose were more commonly reported among individuals with specimens with viral co-detection compared to without (15%, 80% and 93% vs. 8%, 57%, and 51%, respectively) and ear pain and headache were less commonly reported (3% and 26% vs. 16% and 41%, respectively). For specific viruses among all ages, semiquantitative S. pneumoniae nasal carriage density was greater with viral co-detection for enterovirus, RSV A/B, adenovirus, rhinovirus, and common human coronavirus (P < 0.01 for each). When stratified by age, semiquantitative S. pneumoniae nasal carriage density was significantly greater with viral co-detection among children aged <5 (P = 0.002) and 5-17 years (P = 0.005), but not among adults aged 18-64 years (P = 0.29). Conclusion Detection of common respiratory viruses was associated with greater concurrent S. pneumoniae semiquantitative nasal carriage density in a household setting among children, but not adults.
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Affiliation(s)
- Julia C. Bennett
- Department of Medicine, University of Washington, Seattle, WA, United States
- Department of Epidemiology, University of Washington, Seattle, WA, United States
| | - Anne Emanuels
- Department of Medicine, University of Washington, Seattle, WA, United States
| | - Jessica Heimonen
- Department of Medicine, University of Washington, Seattle, WA, United States
| | - Jessica O'Hanlon
- Department of Medicine, University of Washington, Seattle, WA, United States
| | - James P. Hughes
- Department of Biostatistics, University of Washington, Seattle, WA, United States
| | - Peter D. Han
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, United States
- Military and Health Research Foundation, Laurel, MD, United States
| | - Eric J. Chow
- Department of Medicine, University of Washington, Seattle, WA, United States
- Department of Epidemiology, University of Washington, Seattle, WA, United States
- Communicable Disease Epidemiology and Immunizations Section, Prevention Division, Public Health – Seattle & King County, Seattle, WA, United States
| | - Constance E. Ogokeh
- Military and Health Research Foundation, Laurel, MD, United States
- Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Melissa A. Rolfes
- Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Christine M. Lockwood
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, United States
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, United States
| | - Brian Pfau
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, United States
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Timothy M. Uyeki
- Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Jay Shendure
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, United States
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Samara Hoag
- Student Health Services, Seattle Public Schools, Seattle, WA, United States
| | - Kairsten Fay
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, United States
| | - Jover Lee
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, United States
| | - Thomas R. Sibley
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, United States
| | - Julia H. Rogers
- Department of Medicine, University of Washington, Seattle, WA, United States
- Department of Epidemiology, University of Washington, Seattle, WA, United States
| | - Lea M. Starita
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, United States
- Department of Genome Sciences, University of Washington, Seattle, WA, United States
| | - Janet A. Englund
- Seattle Children’s Research Institute, Department of Pediatrics, University of Washington, Seattle, WA, United States
| | - Helen Y. Chu
- Department of Medicine, University of Washington, Seattle, WA, United States
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10
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Hansen C, Perofsky AC, Burstein R, Famulare M, Boyle S, Prentice R, Marshall C, McCormick BJJ, Reinhart D, Capodanno B, Truong M, Schwabe-Fry K, Kuchta K, Pfau B, Acker Z, Lee J, Sibley TR, McDermot E, Rodriguez-Salas L, Stone J, Gamboa L, Han PD, Duchin JS, Waghmare A, Englund JA, Shendure J, Bedford T, Chu HY, Starita LM, Viboud C. Trends in Risk Factors and Symptoms Associated With SARS-CoV-2 and Rhinovirus Test Positivity in King County, Washington, June 2020 to July 2022. JAMA Netw Open 2022; 5:e2245861. [PMID: 36484987 PMCID: PMC9856230 DOI: 10.1001/jamanetworkopen.2022.45861] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
IMPORTANCE Few US studies have reexamined risk factors for SARS-CoV-2 positivity in the context of widespread vaccination and new variants or considered risk factors for cocirculating endemic viruses, such as rhinovirus. OBJECTIVES To evaluate how risk factors and symptoms associated with SARS-CoV-2 test positivity changed over the course of the pandemic and to compare these with the risk factors associated with rhinovirus test positivity. DESIGN, SETTING, AND PARTICIPANTS This case-control study used a test-negative design with multivariable logistic regression to assess associations between SARS-CoV-2 and rhinovirus test positivity and self-reported demographic and symptom variables over a 25-month period. The study was conducted among symptomatic individuals of all ages enrolled in a cross-sectional community surveillance study in King County, Washington, from June 2020 to July 2022. EXPOSURES Self-reported data for 15 demographic and health behavior variables and 16 symptoms. MAIN OUTCOMES AND MEASURES Reverse transcription-polymerase chain reaction-confirmed SARS-CoV-2 or rhinovirus infection. RESULTS Analyses included data from 23 498 individuals. The median (IQR) age of participants was 34.33 (22.42-45.08) years, 13 878 (59.06%) were female, 4018 (17.10%) identified as Asian, 654 (2.78%) identified as Black, and 2193 (9.33%) identified as Hispanic. Close contact with an individual with SARS-CoV-2 (adjusted odds ratio [aOR], 3.89; 95% CI, 3.34-4.57) and loss of smell or taste (aOR, 3.49; 95% CI, 2.77-4.41) were the variables most associated with SARS-CoV-2 test positivity, but both attenuated during the Omicron period. Contact with a vaccinated individual with SARS-CoV-2 (aOR, 2.03; 95% CI, 1.56-2.79) was associated with lower odds of testing positive than contact with an unvaccinated individual with SARS-CoV-2 (aOR, 4.04; 95% CI, 2.39-7.23). Sore throat was associated with Omicron infection (aOR, 2.27; 95% CI, 1.68-3.20) but not Delta infection. Vaccine effectiveness for participants fully vaccinated with a booster dose was 93% (95% CI, 73%-100%) for Delta, but not significant for Omicron. Variables associated with rhinovirus test positivity included being younger than 12 years (aOR, 3.92; 95% CI, 3.42-4.51) and experiencing a runny or stuffy nose (aOR, 4.58; 95% CI, 4.07-5.21). Black race, residing in south King County, and households with 5 or more people were significantly associated with both SARS-CoV-2 and rhinovirus test positivity. CONCLUSIONS AND RELEVANCE In this case-control study of 23 498 symptomatic individuals, estimated risk factors and symptoms associated with SARS-CoV-2 infection changed over time. There was a shift in reported symptoms between the Delta and Omicron variants as well as reductions in the protection provided by vaccines. Racial and sociodemographic disparities persisted in the third year of SARS-CoV-2 circulation and were also present in rhinovirus infection. Trends in testing behavior and availability may influence these results.
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Affiliation(s)
- Chelsea Hansen
- Brotman Baty Institute, University of Washington, Seattle
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland
| | - Amanda C. Perofsky
- Brotman Baty Institute, University of Washington, Seattle
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland
| | - Roy Burstein
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, Washington
| | - Michael Famulare
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle, Washington
| | - Shanda Boyle
- Brotman Baty Institute, University of Washington, Seattle
| | - Robin Prentice
- Brotman Baty Institute, University of Washington, Seattle
| | | | | | - David Reinhart
- Brotman Baty Institute, University of Washington, Seattle
| | - Ben Capodanno
- Brotman Baty Institute, University of Washington, Seattle
| | - Melissa Truong
- Brotman Baty Institute, University of Washington, Seattle
| | | | - Kayla Kuchta
- Brotman Baty Institute, University of Washington, Seattle
| | - Brian Pfau
- Brotman Baty Institute, University of Washington, Seattle
| | - Zack Acker
- Brotman Baty Institute, University of Washington, Seattle
| | - Jover Lee
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Thomas R. Sibley
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington
| | - Evan McDermot
- Brotman Baty Institute, University of Washington, Seattle
| | | | - Jeremy Stone
- Brotman Baty Institute, University of Washington, Seattle
| | - Luis Gamboa
- Brotman Baty Institute, University of Washington, Seattle
| | - Peter D. Han
- Brotman Baty Institute, University of Washington, Seattle
- Department of Genome Sciences, University of Washington, Seattle
| | - Jeffery S. Duchin
- Public Health Seattle and King County, Seattle, Washington
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle
- School of Public Health, University of Washington, Seattle
| | - Alpana Waghmare
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington
- Seattle Children’s Research Institute, Seattle, Washington
- Department of Pediatrics, University of Washington, Seattle
| | - Janet A. Englund
- Brotman Baty Institute, University of Washington, Seattle
- Seattle Children’s Research Institute, Seattle, Washington
- Department of Pediatrics, University of Washington, Seattle
| | - Jay Shendure
- Brotman Baty Institute, University of Washington, Seattle
- Department of Genome Sciences, University of Washington, Seattle
- Howard Hughes Medical Institute, Seattle, Washington
| | - Trevor Bedford
- Brotman Baty Institute, University of Washington, Seattle
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington
- Department of Genome Sciences, University of Washington, Seattle
- Howard Hughes Medical Institute, Seattle, Washington
| | - Helen Y. Chu
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle
| | - Lea M. Starita
- Brotman Baty Institute, University of Washington, Seattle
- Department of Genome Sciences, University of Washington, Seattle
| | - Cécile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland
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11
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Weil AA, Luiten KG, Casto AM, Bennett JC, O'Hanlon J, Han PD, Gamboa LS, McDermot E, Truong M, Gottlieb GS, Acker Z, Wolf CR, Magedson A, Chow EJ, Lo NK, Pothan LC, McDonald D, Wright TC, McCaffrey KM, Figgins MD, Englund JA, Boeckh M, Lockwood CM, Nickerson DA, Shendure J, Bedford T, Hughes JP, Starita LM, Chu HY. Genomic surveillance of SARS-CoV-2 Omicron variants on a university campus. Nat Commun 2022; 13:5240. [PMID: 36068236 PMCID: PMC9446629 DOI: 10.1038/s41467-022-32786-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 08/15/2022] [Indexed: 01/14/2023] Open
Abstract
Novel variants continue to emerge in the SARS-CoV-2 pandemic. University testing programs may provide timely epidemiologic and genomic surveillance data to inform public health responses. We conducted testing from September 2021 to February 2022 in a university population under vaccination and indoor mask mandates. A total of 3,048 of 24,393 individuals tested positive for SARS-CoV-2 by RT-PCR; whole genome sequencing identified 209 Delta and 1,730 Omicron genomes of the 1,939 total sequenced. Compared to Delta, Omicron had a shorter median serial interval between genetically identical, symptomatic infections within households (2 versus 6 days, P = 0.021). Omicron also demonstrated a greater peak reproductive number (2.4 versus 1.8), and a 1.07 (95% confidence interval: 0.58, 1.57; P < 0.0001) higher mean cycle threshold value. Despite near universal vaccination and stringent mitigation measures, Omicron rapidly displaced the Delta variant to become the predominant viral strain and led to a surge in cases in a university population.
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Affiliation(s)
- Ana A Weil
- Department of Medicine, University of Washington, Seattle, WA, USA.
| | - Kyle G Luiten
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Amanda M Casto
- Department of Medicine, University of Washington, Seattle, WA, USA
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Julia C Bennett
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jessica O'Hanlon
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Peter D Han
- Brotman Baty Institute, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Luis S Gamboa
- Brotman Baty Institute, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | | | - Geoffrey S Gottlieb
- Department of Medicine, University of Washington, Seattle, WA, USA
- Environmental Health & Safety Department, University of Washington, Seattle, WA, USA
- Department of Global Health, University of Washington, Seattle, WA, USA
| | - Zack Acker
- Brotman Baty Institute, Seattle, WA, USA
| | - Caitlin R Wolf
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Ariana Magedson
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Eric J Chow
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Natalie K Lo
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Lincoln C Pothan
- Brotman Baty Institute, Seattle, WA, USA
- Department of Global Health, University of Washington, Seattle, WA, USA
| | - Devon McDonald
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Tessa C Wright
- Department of Medicine, University of Washington, Seattle, WA, USA
| | | | - Marlin D Figgins
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Janet A Englund
- Seattle Children's Research Institute, Department of Pediatrics, University of Washington, Seattle, WA, USA
| | - Michael Boeckh
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Christina M Lockwood
- Brotman Baty Institute, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | | | - Jay Shendure
- Brotman Baty Institute, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
| | - Trevor Bedford
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Brotman Baty Institute, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
| | - James P Hughes
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Lea M Starita
- Brotman Baty Institute, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Helen Y Chu
- Department of Medicine, University of Washington, Seattle, WA, USA
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12
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Thompson MJ, Drain PK, Gregor CE, Hassell LA, Ko LK, Lyon V, Ahmed S, Bishop S, Dupuis V, Garza L, Lambert AA, Rowe C, Warne T, Webber E, Westbroek W, Adams AK. A pragmatic randomized trial of home-based testing for COVID-19 in rural Native American and Latino communities: Protocol for the "Protecting our Communities" study. Contemp Clin Trials 2022; 119:106820. [PMID: 35691487 PMCID: PMC9181367 DOI: 10.1016/j.cct.2022.106820] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 05/14/2022] [Accepted: 06/06/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND Home-based testing for COVID-19 has potential to reduce existing health care disparities among underserved populations in the United States. However, implementation of home-based tests in these communities may face significant barriers. This study evaluates the acceptability, feasibility, and success of home-based testing and the potential added benefit of active support from trusted community health workers for Native Americans and Hispanic/Latino adults living in rural Montana and Washington states. METHODS/DESIGN The academic-community research team designed the trial to be responsive to community needs for understanding barriers and supports to home-based COVID-19 testing. The "Protecting Our Community" study is a two-arm pragmatic randomized controlled trial in which a total of 400 participants are randomized to active or passive arms. Participants of both study arms receive a commercially available home collection COVID-19 test kit, which is completed by mailing a self-collected nasal swab to a central laboratory. The primary study outcome is return of the kit to the central lab within 14 days. The cultural, social, behavioral, and economic barriers to home-based COVID-19 testing are also assessed by qualitative research methods. A survey and semi-structured interviews are conducted after the trial to evaluate perceptions and experience of home-based testing. DISCUSSION Implementing home-based testing in underserved populations, including among Native American and Hispanic/Latino communities, may require additional support to be successful. The Protecting Our Community trial examines the effect of trusted community health workers on use of home-based testing, which may be adaptable for community-driven models of home-based testing in other underserved populations.
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Affiliation(s)
- Matthew J Thompson
- Institute of Translational Health Sciences, University of Washington, 850 Republican Street, Box 358051, Seattle, WA 98109, USA; Department of Family Medicine, University of Washington, Box 354696, Seattle, WA 98195, USA
| | - Paul K Drain
- Department of Global Health, University of Washington, Box 351620, Seattle, WA 98195, USA; Department of Medicine, University of Washington, Box 356420, Seattle, WA 98195, USA; Department of Epidemiology, University of Washington, Box 351619, Seattle, WA 98195, USA
| | - Charlie E Gregor
- Institute of Translational Health Sciences, University of Washington, 850 Republican Street, Box 358051, Seattle, WA 98109, USA
| | - Laurie A Hassell
- Institute of Translational Health Sciences, University of Washington, 850 Republican Street, Box 358051, Seattle, WA 98109, USA
| | - Linda K Ko
- Institute of Translational Health Sciences, University of Washington, 850 Republican Street, Box 358051, Seattle, WA 98109, USA; Department of Health Systems and Population Health, University of Washington, Box 351621, Seattle, WA 98195, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue N, PO Box 19024, Seattle, WA 98109, USA
| | - Victoria Lyon
- Department of Family Medicine, University of Washington, Box 354696, Seattle, WA 98195, USA
| | - Selena Ahmed
- Center for American Indian and Rural Health Equity (CAIRHE), Montana State University, PO Box 173485, Bozeman, MT 59717, USA
| | - Sonia Bishop
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue N, PO Box 19024, Seattle, WA 98109, USA
| | - Virgil Dupuis
- Salish Kootenai College, 58138 US-93, Pablo, MT, USA
| | - Lorenzo Garza
- Sunnyside School District, 1110 S 6th St., Sunnyside, WA, USA
| | - Allison A Lambert
- Institute of Translational Health Sciences, University of Washington, 850 Republican Street, Box 358051, Seattle, WA 98109, USA; Department of Medicine, University of Washington, Box 356420, Seattle, WA 98195, USA; Providence Medical Research Center, Providence Health Care, 105 W 8th Ave, Suite 6050W, Spokane, WA, USA
| | - Carly Rowe
- Institute of Translational Health Sciences, University of Washington, 850 Republican Street, Box 358051, Seattle, WA 98109, USA
| | - Teresa Warne
- Center for American Indian and Rural Health Equity (CAIRHE), Montana State University, PO Box 173485, Bozeman, MT 59717, USA
| | - Eliza Webber
- Center for American Indian and Rural Health Equity (CAIRHE), Montana State University, PO Box 173485, Bozeman, MT 59717, USA
| | | | - Alexandra K Adams
- Center for American Indian and Rural Health Equity (CAIRHE), Montana State University, PO Box 173485, Bozeman, MT 59717, USA.
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13
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Burstein R, Althouse BM, Adler A, Akullian A, Brandstetter E, Cho S, Emanuels A, Fay K, Gamboa L, Han P, Huden K, Ilcisin M, Izzo M, Jackson ML, Kim AE, Kimball L, Lacombe K, Lee J, Logue JK, Rogers J, Chung E, Sibley TR, Van Raay K, Wenger E, Wolf CR, Boeckh M, Chu H, Duchin J, Rieder M, Shendure J, Starita LM, Viboud C, Bedford T, Englund JA, Famulare M. Interactions among 17 respiratory pathogens: a cross-sectional study using clinical and community surveillance data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.02.04.22270474. [PMID: 35169816 PMCID: PMC8845514 DOI: 10.1101/2022.02.04.22270474] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Background Co-circulating respiratory pathogens can interfere with or promote each other, leading to important effects on disease epidemiology. Estimating the magnitude of pathogen-pathogen interactions from clinical specimens is challenging because sampling from symptomatic individuals can create biased estimates. Methods We conducted an observational, cross-sectional study using samples collected by the Seattle Flu Study between 11 November 2018 and 20 August 2021. Samples that tested positive via RT-qPCR for at least one of 17 potential respiratory pathogens were included in this study. Semi-quantitative cycle threshold (Ct) values were used to measure pathogen load. Differences in pathogen load between monoinfected and coinfected samples were assessed using linear regression adjusting for age, season, and recruitment channel. Results 21,686 samples were positive for at least one potential pathogen. Most prevalent were rhinovirus (33·5%), Streptococcus pneumoniae (SPn, 29·0%), SARS-CoV-2 (13.8%) and influenza A/H1N1 (9·6%). 140 potential pathogen pairs were included for analysis, and 56 (40%) pairs yielded significant Ct differences (p < 0.01) between monoinfected and co-infected samples. We observed no virus-virus pairs showing evidence of significant facilitating interactions, and found significant viral load decrease among 37 of 108 (34%) assessed pairs. Samples positive with SPn and a virus were consistently associated with increased SPn load. Conclusions Viral load data can be used to overcome sampling bias in studies of pathogen-pathogen interactions. When applied to respiratory pathogens, we found evidence of viral-SPn facilitation and several examples of viral-viral interference. Multipathogen surveillance is a cost-efficient data collection approach, with added clinical and epidemiological informational value over single-pathogen testing, but requires careful analysis to mitigate selection bias.
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Affiliation(s)
- Roy Burstein
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| | - Benjamin M. Althouse
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
- Department of Biology, New Mexico State University, Las Cruces, NM
| | - Amanda Adler
- Seattle Children’s Research Institute, Seattle WA USA
| | - Adam Akullian
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| | | | - Shari Cho
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Anne Emanuels
- Department of Medicine, University of Washington, Seattle WA USA
| | - Kairsten Fay
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | - Luis Gamboa
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Peter Han
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Kristen Huden
- Department of Medicine, University of Washington, Seattle WA USA
| | - Misja Ilcisin
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | - Mandy Izzo
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| | | | - Ashley E. Kim
- Department of Medicine, University of Washington, Seattle WA USA
| | - Louise Kimball
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | | | - Jover Lee
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | | | - Julia Rogers
- Department of Medicine, University of Washington, Seattle WA USA
| | - Erin Chung
- Department of Pediatrics, University of Washington, Seattle Children’s Hospital, Seattle
| | - Thomas R. Sibley
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | | | - Edward Wenger
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| | - Caitlin R. Wolf
- Department of Medicine, University of Washington, Seattle WA USA
| | - Michael Boeckh
- Department of Medicine, University of Washington, Seattle WA USA
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | - Helen Chu
- Department of Medicine, University of Washington, Seattle WA USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | - Jeff Duchin
- Department of Medicine, University of Washington, Seattle WA USA
- Public Health Seattle & King County, Seattle WA USA
| | - Mark Rieder
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Jay Shendure
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
- Department of Genome Sciences, University of Washington, Seattle WA USA
- Howard Hughes Medical Institute, Seattle WA USA
| | - Lea M. Starita
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
- Department of Genome Sciences, University of Washington, Seattle WA USA
| | - Cecile Viboud
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| | - Trevor Bedford
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
- Howard Hughes Medical Institute, Seattle WA USA
| | - Janet A. Englund
- Seattle Children’s Research Institute, Seattle WA USA
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Michael Famulare
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
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14
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Flu@home: The comparative accuracy of an at-home influenza rapid diagnostic test, using a pre-positioned test kit, mobile app, mail-in reference sample, and symptom-based testing trigger. J Clin Microbiol 2022; 60:e0207021. [PMID: 35107302 PMCID: PMC8925896 DOI: 10.1128/jcm.02070-21] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
At-home testing with rapid diagnostic tests (RDTs) for respiratory viruses could facilitate early diagnosis, guide patient care, and prevent transmission. Such RDTs are best used near the onset of illness when viral load is highest and clinical action will be most impactful, which may be achieved by at-home testing. We evaluated the diagnostic accuracy of the QuickVue Influenza A + B RDT in an at-home setting. A convenience sample of 5,229 individuals who were engaged with an on-line health research platform were prospectively recruited throughout the United States. "flu@home" test kits containing a QuickVue RDT and reference sample collection and shipping materials were pre-positioned with participants at the beginning of the study. Participants responded to daily symptom surveys. If they reported experiencing cough along with aches, fever, chills, and/or sweats, they used their flu@home kit following instructions on a mobile app and indicated what lines they saw on the RDT. Of the 976 participants who met criteria to use their self-collection kit and completed study procedures, 202 (20.7%) were positive for influenza by qPCR. The RDT had a sensitivity of 28% (95% CI: 21-36) and specificity of 99% (98-99) for influenza A, and 32% (95% CI: 20-46) and 99% (95% CI: 98-99), for influenza B. Our results support the concept of app-supported, pre-positioned at-home RDT kits using symptom-based triggers, although it cannot be recommended with the RDT used in this study. Further research is needed to determine ways to improve the accuracy and utility of home-based testing for influenza.
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15
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Requirements and study designs for US regulatory approval of influenza home tests. J Clin Microbiol 2021; 60:e0188421. [PMID: 34911365 PMCID: PMC9116184 DOI: 10.1128/jcm.01884-21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Home testing for infectious disease has come to the forefront during the COVID-19 pandemic. There is now considerable commercial interest in developing complete home tests for a variety of viral and bacterial pathogens. However, the regulatory science around home infectious disease test approval, and procedures test manufacturers and laboratory professionals will need to follow, have not yet been formalized by US FDA, with the exception of EUA guidance for COVID-19 tests. We describe the state of home-based testing for influenza with a focus on sample-to-result home tests, discuss the various regulatory pathways by which these products can reach populations, and provide recommendations for study designs, patient samples, and other important features necessary to gain market access. These recommendations have potential application for home use tests being developed for other viral respiratory infections, such as COVID-19, as guidance moves from EUA designation into 510(k) requirements.
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16
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Chung E, Chow EJ, Wilcox NC, Burstein R, Brandstetter E, Han PD, Fay K, Pfau B, Adler A, Lacombe K, Lockwood CM, Uyeki TM, Shendure J, Duchin JS, Rieder MJ, Nickerson DA, Boeckh M, Famulare M, Hughes JP, Starita LM, Bedford T, Englund JA, Chu HY. Comparison of Symptoms and RNA Levels in Children and Adults With SARS-CoV-2 Infection in the Community Setting. JAMA Pediatr 2021; 175:e212025. [PMID: 34115094 PMCID: PMC8491103 DOI: 10.1001/jamapediatrics.2021.2025] [Citation(s) in RCA: 65] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 05/10/2021] [Indexed: 01/14/2023]
Abstract
Importance The association between COVID-19 symptoms and SARS-CoV-2 viral levels in children living in the community is not well understood. Objective To characterize symptoms of pediatric COVID-19 in the community and analyze the association between symptoms and SARS-CoV-2 RNA levels, as approximated by cycle threshold (Ct) values, in children and adults. Design, Setting, and Participants This cross-sectional study used a respiratory virus surveillance platform in persons of all ages to detect community COVID-19 cases from March 23 to November 9, 2020. A population-based convenience sample of children younger than 18 years and adults in King County, Washington, who enrolled online for home self-collection of upper respiratory samples for SARS-CoV-2 testing were included. Exposures Detection of SARS-CoV-2 RNA by reverse transcription-polymerase chain reaction (RT-PCR) from participant-collected samples. Main Outcomes and Measures RT-PCR-confirmed SARS-CoV-2 infection, with Ct values stratified by age and symptoms. Results Among 555 SARS-CoV-2-positive participants (mean [SD] age, 33.7 [20.1] years; 320 were female [57.7%]), 47 of 123 children (38.2%) were asymptomatic compared with 31 of 432 adults (7.2%). When symptomatic, fewer symptoms were reported in children compared with adults (mean [SD], 1.6 [2.0] vs 4.5 [3.1]). Symptomatic individuals had lower Ct values (which corresponded to higher viral RNA levels) than asymptomatic individuals (adjusted estimate for children, -3.0; 95% CI, -5.5 to -0.6; P = .02; adjusted estimate for adults, -2.9; 95% CI, -5.2 to -0.6; P = .01). The difference in mean Ct values was neither statistically significant between symptomatic children and symptomatic adults (adjusted estimate, -0.7; 95% CI, -2.2 to 0.9; P = .41) nor between asymptomatic children and asymptomatic adults (adjusted estimate, -0.6; 95% CI, -4.0 to 2.8; P = .74). Conclusions and Relevance In this community-based cross-sectional study, SARS-CoV-2 RNA levels, as determined by Ct values, were significantly higher in symptomatic individuals than in asymptomatic individuals and no significant age-related differences were found. Further research is needed to understand the role of SARS-CoV-2 RNA levels and viral transmission.
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Affiliation(s)
- Erin Chung
- Department of Pediatrics, University of Washington, Seattle Children’s Hospital, Seattle
| | - Eric J. Chow
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle
| | - Naomi C. Wilcox
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle
| | - Roy Burstein
- Institute for Disease Modeling, Seattle, Washington
| | - Elisabeth Brandstetter
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
| | - Peter D. Han
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Department of Genome Sciences, University of Washington, Seattle
| | - Kairsten Fay
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Brian Pfau
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Department of Genome Sciences, University of Washington, Seattle
| | - Amanda Adler
- Seattle Children’s Research Institute, Seattle, Washington
| | | | - Christina M. Lockwood
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle
| | - Timothy M. Uyeki
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jay Shendure
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Department of Genome Sciences, University of Washington, Seattle
- Howard Hughes Medical Institute, Seattle, Washington
| | - Jeffrey S. Duchin
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle
- Public Health—Seattle & King County, Seattle, Washington
| | - Mark J. Rieder
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Department of Genome Sciences, University of Washington, Seattle
| | - Deborah A. Nickerson
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Department of Genome Sciences, University of Washington, Seattle
| | - Michael Boeckh
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | | | - James P. Hughes
- Department of Biostatistics, University of Washington, Seattle
| | - Lea M. Starita
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Department of Genome Sciences, University of Washington, Seattle
| | - Trevor Bedford
- Brotman Baty Institute for Precision Medicine, Seattle, Washington
- Department of Genome Sciences, University of Washington, Seattle
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | | | - Helen Y. Chu
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle
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17
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Srivatsan S, Heidl S, Pfau B, Martin BK, Han PD, Zhong W, van Raay K, McDermot E, Opsahl J, Gamboa L, Smith N, Truong M, Cho S, Barrow KA, Rich LM, Stone J, Wolf CR, McCulloch DJ, Kim AE, Brandstetter E, Sohlberg SL, Ilcisin M, Geyer RE, Chen W, Gehring J, Kosuri S, Bedford T, Rieder MJ, Nickerson DA, Chu HY, Konnick EQ, Debley JS, Shendure J, Lockwood CM, Starita LM. SwabExpress: An end-to-end protocol for extraction-free covid-19 testing. Clin Chem 2021; 68:143-152. [PMID: 34286830 DOI: 10.1093/clinchem/hvab132] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Accepted: 06/28/2021] [Indexed: 11/13/2022]
Abstract
BACKGROUND The urgent need for massively scaled clinical testing for SARS-CoV-2, along with global shortages of critical reagents and supplies, has necessitated development of streamlined laboratory testing protocols. Conventional nucleic acid testing for SARS-CoV-2 involves collection of a clinical specimen with a nasopharyngeal swab in transport medium, nucleic acid extraction, and quantitative reverse transcription PCR (RT-qPCR) (1). As testing has scaled across the world, the global supply chain has buckled, rendering testing reagents and materials scarce (2). To address shortages, we developed SwabExpress, an end-to-end protocol developed to employ mass produced anterior nares swabs and bypass the requirement for transport media and nucleic acid extraction. METHODS We evaluated anterior nares swabs, transported dry and eluted in low-TE buffer as a direct-to-RT-qPCR alternative to extraction-dependent viral transport media. We validated our protocol of using heat treatment for viral inactivation and added a proteinase K digestion step to reduce amplification interference. We tested this protocol across archived and prospectively collected swab specimens to fine-tune test performance. RESULTS After optimization, SwabExpress has a low limit of detection at 2-4 molecules/uL, 100% sensitivity, and 99.4% specificity when compared side-by-side with a traditional RT-qPCR protocol employing extraction. On real-world specimens, SwabExpress outperforms an automated extraction system while simultaneously reducing cost and hands-on time. CONCLUSION SwabExpress is a simplified workflow that facilitates scaled testing for COVID-19 without sacrificing test performance. It may serve as a template for the simplification of PCR-based clinical laboratory tests, particularly in times of critical shortages during pandemics.
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Affiliation(s)
- Sanjay Srivatsan
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Sarah Heidl
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | - Brian Pfau
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | - Beth K Martin
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Peter D Han
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | - Weizhi Zhong
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | | | - Evan McDermot
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | - Jordan Opsahl
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | - Luis Gamboa
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | - Nahum Smith
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | - Melissa Truong
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | - Shari Cho
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | - Kaitlyn A Barrow
- Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, WA, USA
| | - Lucille M Rich
- Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, WA, USA
| | - Jeremy Stone
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | - Caitlin R Wolf
- Department of Allergy and Infectious Disease, University of Washington, Seattle, WA, USA
| | - Denise J McCulloch
- Department of Allergy and Infectious Disease, University of Washington, Seattle, WA, USA
| | - Ashley E Kim
- Department of Allergy and Infectious Disease, University of Washington, Seattle, WA, USA
| | | | - Sarah L Sohlberg
- Department of Allergy and Infectious Disease, University of Washington, Seattle, WA, USA
| | - Misja Ilcisin
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Rachel E Geyer
- Department of Family Medicine, University of Washington, Seattle, Washington, USA
| | - Wei Chen
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Jase Gehring
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Sriram Kosuri
- Octant, Inc. Emeryville CA, USA.,Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - Trevor Bedford
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.,Brotman Baty Institute For Precision Medicine, Seattle, WA, USA.,Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Mark J Rieder
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | - Deborah A Nickerson
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.,Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
| | - Helen Y Chu
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA.,Department of Allergy and Infectious Disease, University of Washington, Seattle, WA, USA
| | - Eric Q Konnick
- Brotman Baty Institute For Precision Medicine, Seattle, WA, USA.,Department of Laboratory Medicine and Pathology, Seattle, WA, USA
| | - Jason S Debley
- Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, WA, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.,Brotman Baty Institute For Precision Medicine, Seattle, WA, USA.,Howard Hughes Medical Institute. Seattle, WA, USA
| | - Christina M Lockwood
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.,Brotman Baty Institute For Precision Medicine, Seattle, WA, USA.,Department of Laboratory Medicine and Pathology, Seattle, WA, USA
| | - Lea M Starita
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.,Brotman Baty Institute For Precision Medicine, Seattle, WA, USA
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18
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Affiliation(s)
- Dana C. Crawford
- Departments of Population and Quantitative Health Sciences and Genetics and Genome Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Scott M. Williams
- Departments of Population and Quantitative Health Sciences and Genetics and Genome Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
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19
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Srivatsan S, Heidl S, Pfau B, Martin BK, Han PD, Zhong W, van Raay K, McDermot E, Opsahl J, Gamboa L, Smith N, Truong M, Cho S, Barrow KA, Rich LM, Stone J, Wolf CR, McCulloch DJ, Kim AE, Brandstetter E, Sohlberg SL, Ilcisin M, Geyer RE, Chen W, Gehring J, Kosuri S, Bedford T, Rieder MJ, Nickerson DA, Chu HY, Konnick EQ, Debley JS, Shendure J, Lockwood CM, Starita LM. SwabExpress: An end-to-end protocol for extraction-free COVID-19 testing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2020.04.22.056283. [PMID: 32511368 PMCID: PMC7263496 DOI: 10.1101/2020.04.22.056283] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND The urgent need for massively scaled clinical testing for SARS-CoV-2, along with global shortages of critical reagents and supplies, has necessitated development of streamlined laboratory testing protocols. Conventional nucleic acid testing for SARS-CoV-2 involves collection of a clinical specimen with a nasopharyngeal swab in transport medium, nucleic acid extraction, and quantitative reverse transcription PCR (RT-qPCR) (1). As testing has scaled across the world, the global supply chain has buckled, rendering testing reagents and materials scarce (2). To address shortages, we developed SwabExpress, an end-to-end protocol developed to employ mass produced anterior nares swabs and bypass the requirement for transport media and nucleic acid extraction. METHODS We evaluated anterior nares swabs, transported dry and eluted in low-TE buffer as a direct-to-RT-qPCR alternative to extraction-dependent viral transport media. We validated our protocol of using heat treatment for viral activation and added a proteinase K digestion step to reduce amplification interference. We tested this protocol across archived and prospectively collected swab specimens to fine-tune test performance. RESULTS After optimization, SwabExpress has a low limit of detection at 2-4 molecules/uL, 100% sensitivity, and 99.4% specificity when compared side-by-side with a traditional RT-qPCR protocol employing extraction. On real-world specimens, SwabExpress outperforms an automated extraction system while simultaneously reducing cost and hands-on time. CONCLUSION SwabExpress is a simplified workflow that facilitates scaled testing for COVID-19 without sacrificing test performance. It may serve as a template for the simplification of PCR-based clinical laboratory tests, particularly in times of critical shortages during pandemics.
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Affiliation(s)
- Sanjay Srivatsan
- Department of Genome Sciences, University of Washington, Seattle WA, USA
| | - Sarah Heidl
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | - Brian Pfau
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | - Beth K. Martin
- Department of Genome Sciences, University of Washington, Seattle WA, USA
| | - Peter D. Han
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | - Weizhi Zhong
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | | | - Evan McDermot
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | - Jordan Opsahl
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | - Luis Gamboa
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | - Nahum Smith
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | - Melissa Truong
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | - Shari Cho
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | - Kaitlyn A. Barrow
- Center for Immunity and Immunotherapies, Seattle Children’s Research Institute, Seattle WA, USA
| | - Lucille M. Rich
- Center for Immunity and Immunotherapies, Seattle Children’s Research Institute, Seattle WA, USA
| | - Jeremy Stone
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | - Caitlin R. Wolf
- Department of Allergy and Infectious Disease, University of Washington, Seattle WA, USA
| | - Denise J. McCulloch
- Department of Allergy and Infectious Disease, University of Washington, Seattle WA, USA
| | - Ashley E. Kim
- Department of Allergy and Infectious Disease, University of Washington, Seattle WA, USA
| | | | - Sarah L. Sohlberg
- Department of Allergy and Infectious Disease, University of Washington, Seattle WA, USA
| | - Misja Ilcisin
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Rachel E. Geyer
- Department of Family Medicine, University of Washington, Seattle, Washington, USA
| | - Wei Chen
- Department of Genome Sciences, University of Washington, Seattle WA, USA
| | - Jase Gehring
- Department of Genome Sciences, University of Washington, Seattle WA, USA
| | | | - Sriram Kosuri
- Octant, Inc. Emeryville CA, USA
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles CA, USA
| | - Trevor Bedford
- Department of Genome Sciences, University of Washington, Seattle WA, USA
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Mark J. Rieder
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | - Deborah A. Nickerson
- Department of Genome Sciences, University of Washington, Seattle WA, USA
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
| | - Helen Y. Chu
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
- Department of Allergy and Infectious Disease, University of Washington, Seattle WA, USA
| | - Eric Q. Konnick
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
- Department of Laboratory Medicine and Pathology, Seattle WA, USA
| | - Jason S. Debley
- Center for Immunity and Immunotherapies, Seattle Children’s Research Institute, Seattle WA, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle WA, USA
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
- Howard Hughes Medical Institute. Seattle WA, USA
| | - Christina M. Lockwood
- Department of Genome Sciences, University of Washington, Seattle WA, USA
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
- Department of Laboratory Medicine and Pathology, Seattle WA, USA
| | - Lea M. Starita
- Department of Genome Sciences, University of Washington, Seattle WA, USA
- Brotman Baty Institute For Precision Medicine, Seattle WA, USA
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