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Gigot C, Pisanic N, Spicer K, Davis MF, Kruczynski K, Rivera MG, Koehler K, Hall DJ, Hall DJ, Heaney CD. SARS-CoV-2 antibody prevalence by industry, workplace characteristics, and workplace infection prevention and control measures, North Carolina, 2021 to 2022. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.06.24303821. [PMID: 38496588 PMCID: PMC10942491 DOI: 10.1101/2024.03.06.24303821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Background The COVID-19 pandemic has disproportionately affected workers in certain industries and occupations, and the workplace can be a high risk setting for SARS-CoV-2 transmission. In this study, we measured SARS-CoV-2 antibody prevalence and identified work-related risk factors in a population primarily working at industrial livestock operations. Methods We used a multiplex salivary SARS-CoV-2 IgG antibody assay to determine infection-induced antibody prevalence among 236 adult (≥18 years) North Carolina residents between February 2021 and August 2022. We used the National Institute for Occupational Safety and Health Industry and Occupation Computerized Coding System (NIOCCS) to classify employed participants' industry and compared infection-induced IgG prevalence by participant industry and with the North Carolina general population. We also combined antibody results with reported SARS-CoV-2 molecular test positivity and vaccination history to identify evidence of prior infection. We used logistic regression to estimate odds ratios of prior infection by potential work-related risk factors, adjusting for industry and date. Results Most participants (55%) were infection-induced IgG positive, including 71% of animal slaughtering and processing industry workers, which is 1.5 to 4.3 times higher compared to the North Carolina general population, as well as higher than molecularly-confirmed cases and the only other serology study we identified of animal slaughtering and processing workers. Considering questionnaire results in addition to antibodies, the proportion of participants with evidence of prior infection increased slightly, to 61%, including 75% of animal slaughtering and processing workers. Participants with more than 1000 compared to 10 or fewer coworkers at their jobsite had higher odds of prior infection (adjusted odds ratio [aOR] 4.5, 95% confidence interval [CI] 1.0 to 21.0). Conclusions This study contributes evidence of the severe and disproportionate impacts of COVID-19 on animal processing and essential workers and workers in large congregate settings. We also demonstrate the utility of combining non-invasive biomarker and questionnaire data for the study of workplace exposures.
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Affiliation(s)
- Carolyn Gigot
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Nora Pisanic
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Kristoffer Spicer
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Meghan F. Davis
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Johns Hopkins P.O.E. Total Worker Health(R) Center in Mental Health, Baltimore, Maryland, USA
- Division of Infectious Diseases and Department of Molecular and Comparative Pathobiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Kate Kruczynski
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Magdielis Gregory Rivera
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Kirsten Koehler
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - D. J. Hall
- Rural Empowerment Association for Community Help, Warsaw, North Carolina, USA
| | - Devon J. Hall
- Rural Empowerment Association for Community Help, Warsaw, North Carolina, USA
| | - Christopher D. Heaney
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of International Health Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Community Science and Innovation for Environmental Justice Initiative, Center for a Livable Future, Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
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Ciccone EJ, Zhu DR, Gunderson AK, Hawke S, Ajeen R, Lodge EK, Shook-Sa BE, Abernathy H, Garrett HE, King E, Alavian N, Reyes R, Taylor JL, Beatty C, Chung C, Mendoza CE, Weber DJ, Markmann AJ, Premkumar L, Juliano JJ, Boyce RM, Aiello AE. Magnitude and Durability of the Antibody Response to mRNA-Based Vaccination Among SARS-CoV-2 Seronegative and Seropositive Health Care Personnel. Open Forum Infect Dis 2024; 11:ofae009. [PMID: 38293246 PMCID: PMC10826795 DOI: 10.1093/ofid/ofae009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 01/04/2024] [Indexed: 02/01/2024] Open
Abstract
Few studies have described changes in SARS-CoV-2 antibody levels in response to infection and vaccination at frequent intervals and over extended follow-up periods. The purpose of this study was to assess changes in SARS-CoV-2-specific antibody responses among a prospective cohort of health care personnel over 18 months with up to 22 samples per person. Antibody levels and live virus neutralization were measured before and after mRNA-based vaccination with results stratified by (1) SARS-CoV-2 infection status prior to initial vaccination and (2) SARS-CoV-2 infection at any point during follow-up. We found that the antibody response to the first dose was almost 2-fold higher in individuals who were seropositive prior to vaccination, although neutralization titers were more variable. The antibody response induced by vaccination appeared to wane over time but generally persisted for 8 to 9 months, and those who were infected at any point during the study had slightly higher antibody levels over time vs those who remained uninfected. These findings underscore the need to account for SARS-CoV-2 natural infection as a modifier of vaccine responses, and they highlight the importance of frequent testing of longitudinal antibody titers over time. Together, our results provide a clearer understanding of the trajectories of antibody response among vaccinated individuals with and without prior SARS-CoV-2 infection.
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Affiliation(s)
| | - Deanna R Zhu
- Department of Epidemiology, Gillings School of Global Public Health
| | | | - Sam Hawke
- Department of Biostatistics, Gillings School of Global Public Health
| | - Rawan Ajeen
- Institute for Global Health and Infectious Diseases
| | - Evans K Lodge
- Department of Epidemiology, Gillings School of Global Public Health
| | - Bonnie E Shook-Sa
- Department of Biostatistics, Gillings School of Global Public Health
| | | | - Haley E Garrett
- Department of Epidemiology, Gillings School of Global Public Health
| | - Elise King
- Institute for Global Health and Infectious Diseases
| | - Naseem Alavian
- Division of Hospital Medicine, School of Medicine, University of North Carolina, Chapel Hill, North Carolina
| | - Raquel Reyes
- Division of Hospital Medicine, School of Medicine, University of North Carolina, Chapel Hill, North Carolina
| | | | - Cherese Beatty
- Department of Epidemiology and Robert N. Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, New York
| | | | - Carmen E Mendoza
- Department of Epidemiology, Gillings School of Global Public Health
| | - David J Weber
- Division of Infectious Diseases, School of Medicine
- Department of Epidemiology, Gillings School of Global Public Health
| | | | - Lakshmanane Premkumar
- Department of Microbiology and Immunology, School of Medicine, University of North Carolina, Chapel Hill, North Carolina
| | - Jonathan J Juliano
- Division of Infectious Diseases, School of Medicine
- Department of Epidemiology, Gillings School of Global Public Health
| | - Ross M Boyce
- Division of Infectious Diseases, School of Medicine
- Department of Epidemiology, Gillings School of Global Public Health
| | - Allison E Aiello
- Department of Epidemiology and Robert N. Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, New York
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3
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Vias NP, Cassidy CA, Edwards JK, Xiong K, Parker CB, Aiello AE, Boyce RM, Shook-Sa BE. Estimation of SARS-CoV-2 Seroprevalence in Central North Carolina: Accounting for Outcome Misclassification in Complex Sample Designs. Epidemiology 2023; 34:721-731. [PMID: 37527450 PMCID: PMC10403265 DOI: 10.1097/ede.0000000000001625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/03/2023]
Abstract
BACKGROUND Population-based seroprevalence studies are crucial to understand community transmission of COVID-19 and guide responses to the pandemic. Seroprevalence is typically measured from diagnostic tests with imperfect sensitivity and specificity. Failing to account for measurement error can lead to biased estimates of seroprevalence. Methods to adjust seroprevalence estimates for the sensitivity and specificity of the diagnostic test have largely focused on estimation in the context of convenience sampling. Many existing methods are inappropriate when data are collected using a complex sample design. METHODS We present methods for seroprevalence point estimation and confidence interval construction that account for imperfect test performance for use with complex sample data. We apply these methods to data from the Chatham County COVID-19 Cohort (C4), a longitudinal seroprevalence study conducted in central North Carolina. Using simulations, we evaluate bias and confidence interval coverage for the proposed estimator compared with a standard estimator under a stratified, three-stage cluster sample design. RESULTS We obtained estimates of seroprevalence and corresponding confidence intervals for the C4 study. SARS-CoV-2 seroprevalence increased rapidly from 10.4% in January to 95.6% in July 2021 in Chatham County, North Carolina. In simulation, the proposed estimator demonstrates desirable confidence interval coverage and minimal bias under a wide range of scenarios. CONCLUSION We propose a straightforward method for producing valid estimates and confidence intervals when data are based on a complex sample design. The method can be applied to estimate the prevalence of other infections when estimates of test sensitivity and specificity are available.
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Affiliation(s)
- Nishma P. Vias
- Adams School of Dentistry, University of North Carolina at Chapel Hill, NC, USA
| | - Caitlin A. Cassidy
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC, USA
| | - Jessie K. Edwards
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC, USA
| | - Khou Xiong
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC, USA
| | - Cherese Beatty Parker
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY
| | - Allison E. Aiello
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY
- Robert N Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, NY
| | - Ross M. Boyce
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, NC, USA
- Division of Infectious Diseases, School of Medicine, University of North Carolina at Chapel Hill, NC, USA
| | - Bonnie E. Shook-Sa
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC, USA
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Sciaudone M, Cutshaw MK, McClean CM, Lacayo R, Kharabora O, Murray K, Strohminger S, Zivanovich MM, Gurnett R, Markmann AJ, Salgado EM, Bhowmik DR, Castro-Arroyo E, Boyce RM, Aiello AE, Richardson D, Juliano JJ, Bowman NM. Seroepidemiology and risk factors for SARS-CoV-2 infection among household members of food processing and farm workers in North Carolina. IJID REGIONS 2023; 7:164-169. [PMID: 37034427 PMCID: PMC10032047 DOI: 10.1016/j.ijregi.2023.03.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/15/2023] [Accepted: 03/17/2023] [Indexed: 03/24/2023]
Abstract
Background Racial and ethnic minorities have borne a disproportionate burden from coronavirus disease 2019 (COVID-19). Certain essential occupations, including food processing and farm work, employ large numbers of Hispanic migrant workers and have been shown to carry an especially high risk of infection. Methods This observational cohort study measured the seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and assessed the risk factors for seropositivity among food processing and farm workers, and members of their households, in North Carolina, USA. Participants completed questionnaires, blood samples were collected, and an enzyme-linked immunosorbent assay was used to assess SARS-CoV-2 seropositivity. Univariate and multi-variate analyses were undertaken to identify risk factors associated with seropositivity, using generalized estimating equations to account for household clustering. Findings Among the 218 participants, 94.5% were Hispanic, and SARS-CoV-2 seropositivity was 50.0%. Most seropositive individuals did not report a history of illness compatible with COVID-19. Attending church, having a prior history of COVID-19, having a seropositive household member, and speaking Spanish as one's primary language were associated with SARS-CoV-2 seropositivity, while preventive behaviours were not. Interpretation These findings underscore the substantial burden of COVID-19 among a population of mostly Hispanic essential workers and their households in rural North Carolina. This study contributes to a large body of evidence showing that Hispanic Americans have suffered a disproportionate burden of COVID-19. This study also highlights the epidemiologic importance of viral transmission within the household.
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Affiliation(s)
- Michael Sciaudone
- Department of Medicine, Section of Infectious Diseases, Tulane University School of Medicine, New Orleans, Louisiana, USA
- Center for Intelligent Molecular Diagnostics, Tulane University School of Medicine, New Orleans, Louisiana, USA
| | | | | | - Roberto Lacayo
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Oksana Kharabora
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Katherine Murray
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Stephen Strohminger
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Miriana Moreno Zivanovich
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Rachel Gurnett
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Alena J. Markmann
- Department of Medicine, Division of Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Emperatriz Morales Salgado
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - D. Ryan Bhowmik
- Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Edwin Castro-Arroyo
- Infectious Disease Epidemiology and Ecology Laboratory, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Ross M. Boyce
- Institute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, North Carolina, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
- Carolina Population Center, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Allison E. Aiello
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
- Robert N Butler Columbia Aging Center, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - David Richardson
- Department of Environmental and Occupational Health, Program in Public Health, University of California – Irvine, Irvine, California, USA
| | - Jonathan J. Juliano
- Department of Medicine, Division of Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
- Curriculum in Genetics and Molecular Biology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Natalie M. Bowman
- Department of Medicine, Division of Infectious Diseases, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
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Gigot C, Pisanic N, Kruczynski K, Gregory Rivera M, Spicer K, Kurowski KM, Randad P, Koehler K, Clarke WA, Holmes P, Hall DJ, Hall DJ, Heaney CD. SARS-CoV-2 Antibody Prevalence among Industrial Livestock Operation Workers and Nearby Community Residents, North Carolina, 2021 to 2022. mSphere 2023; 8:e0052222. [PMID: 36656002 PMCID: PMC9942583 DOI: 10.1128/msphere.00522-22] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 12/06/2022] [Indexed: 01/20/2023] Open
Abstract
Industrial livestock operations (ILOs), particularly processing facilities, emerged as centers of coronavirus disease 2019 (COVID-19) outbreaks in spring 2020. Confirmed cases of COVID-19 underestimate true prevalence. To investigate the prevalence of antibodies against SARS-CoV-2, we enrolled 279 participants in North Carolina from February 2021 to July 2022: 90 from households with at least one ILO worker (ILO), 97 from high-ILO intensity areas (ILO neighbors [ILON]), and 92 from metropolitan areas (metro). More metro (55.4%) compared to ILO (51.6%) and ILON participants (48.4%) completed the COVID-19 primary vaccination series; the median completion date was more than 4 months later for ILO compared to ILON and metro participants, although neither difference was statistically significant. Participants provided a saliva swab we analyzed for SARS-CoV-2 IgG using a multiplex immunoassay. The prevalence of infection-induced IgG (positive for nucleocapsid and receptor binding domain) was higher among ILO (63%) than ILON (42.9%) and metro (48.7%) participants (prevalence ratio [PR], 1.38; 95% confidence interval [CI], 1.06 to 1.80; reference category ILON and metro combined). The prevalence of infection-induced IgG was also higher among ILO participants than among an Atlanta health care worker cohort (PR, 2.45; 95% CI, 1.80 to 3.33) and a general population cohort in North Carolina (PRs, 6.37 to 10.67). The infection-induced IgG prevalence increased over the study period. Participants reporting not masking in public in the past 2 weeks had higher infection-induced IgG prevalence (78.6%) than participants reporting masking (49.3%) (PR, 1.59; 95% CI, 1.19 to 2.13). Lower education, more people per bedroom, Hispanic/Latino ethnicity, and more contact with people outside the home were also associated with higher infection-induced IgG prevalence. IMPORTANCE Few studies have measured COVID-19 seroprevalence in North Carolina, especially among rural, Black, and Hispanic/Latino communities that have been heavily affected. Antibody results show high rates of COVID-19 among industrial livestock operation workers and their household members. Antibody results add to evidence of health disparities related to COVID-19 by socioeconomic status and ethnicity. Associations between masking and physical distancing with antibody results also add to evidence of the effectiveness of these prevention strategies. Delays in the timing of receipt of COVID-19 vaccination reinforce the importance of dismantling vaccination barriers, especially for industrial livestock operation workers and their household members.
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Affiliation(s)
- Carolyn Gigot
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Nora Pisanic
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Kate Kruczynski
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Magdielis Gregory Rivera
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Kristoffer Spicer
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Kathleen M. Kurowski
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Pranay Randad
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Kirsten Koehler
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - William A. Clarke
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Phyla Holmes
- Rural Empowerment Association for Community Help, Warsaw, North Carolina, USA
| | - D. J. Hall
- Rural Empowerment Association for Community Help, Warsaw, North Carolina, USA
| | - Devon J. Hall
- Rural Empowerment Association for Community Help, Warsaw, North Carolina, USA
| | - Christopher D. Heaney
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
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6
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Larremore DB, Fosdick BK, Zhang S, Grad YH. Optimizing prevalence estimates for a novel pathogen by reducing uncertainty in test characteristics. Epidemics 2022; 41:100634. [PMID: 36191537 PMCID: PMC11227734 DOI: 10.1016/j.epidem.2022.100634] [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: 02/09/2022] [Revised: 07/11/2022] [Accepted: 09/21/2022] [Indexed: 12/29/2022] Open
Abstract
Emergence of a novel pathogen drives the urgent need for diagnostic tests that can aid in defining disease prevalence. The limitations associated with rapid development and deployment of these tests result in a dilemma: In efforts to optimize prevalence estimates, would tests be better used in the lab to reduce uncertainty in test characteristics or to increase sample size in field studies? Here, we provide a framework to address this question through a joint Bayesian model that simultaneously analyzes lab validation and field survey data, and we define the impact of test allocation on inferences of sensitivity, specificity, and prevalence. In many scenarios, prevalence estimates can be most improved by apportioning additional effort towards validation rather than to the field. The joint model provides superior estimation of prevalence, sensitivity, and specificity, compared with typical analyses that model lab and field data separately, and it can be used to inform sample allocation when testing is limited.
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Affiliation(s)
- Daniel B Larremore
- Department of Computer Science, University of Colorado Boulder, Boulder, CO, 80309, USA; BioFrontiers Institute, University of Colorado at Boulder, Boulder, CO, 80303, USA.
| | - Bailey K Fosdick
- Department of Statistics, Colorado State University, Fort Collins, CO, 80523, USA.
| | - Sam Zhang
- Department of Applied Mathematics, University of Colorado Boulder, Boulder, CO, 80309, USA
| | - Yonatan H Grad
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
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Neighbors CE, Wu AE, Wixted DG, Heidenfelder BL, Kingsbury CA, Register HM, Louzao R, Sloane R, Eckstrand J, Pieper CC, Faldowski RA, Denny TN, Woods CW, Newby LK. The Cabarrus County COVID-19 Prevalence and Immunity (C3PI) Study: design, methods, and baseline characteristics. Am J Transl Res 2022; 14:5693-5711. [PMID: 36105067 PMCID: PMC9452347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 07/07/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVES Coronavirus Disease 2019 (COVID-19) is a viral illness with public health importance. The Cabarrus County COVID-19 Prevalence and Immunity (C3PI) Study is a prospective, longitudinal cohort study designed to contribute valuable information on community prevalence of active COVID-19 infection and SARS-CoV-2 antibodies as the pandemic and responses to it have and continue to evolve. We present the rationale, study design, and baseline characteristics of the C3PI Study. METHODS We recruited 1,426 participants between June 2020 and August 2020 from the Measurement to Understand the Reclassification of Disease of Cabarrus/Kannapolis (MURDOCK) Study Community Registry and Biorepository, a previously established, community-based, longitudinal cohort. Participants completed a baseline survey and follow-up surveys every two weeks. A nested weighted, random sub-cohort (n=300) was recruited to measure the incidence and prevalence of active COVID-19 infection and SARS-CoV-2 IgG antibodies. RESULTS The sub-cohort was younger (56 vs 61 years), had more men (39.0% vs 30.9%), and a higher proportion of Hispanic (11.0% vs 5.1%) and Black participants (17.0% vs 8.2%) compared with the overall cohort. They had similar anthropometrics and medical histories, but a greater proportion of the sub-cohort had a higher educational degree (36.1% vs 31.3%) and reported a pre-pandemic annual household income of >$90,000 (57.1% vs 47.9%). CONCLUSION This study is part of a multisite consortium that will provide critical data on the epidemiology of COVID-19 and community perspectives about the pandemic, behaviors and mitigation strategies, and individual and community burden in North Carolina.
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Affiliation(s)
| | - Angie E Wu
- Duke Clinical Research Institute, Duke UniversityDurham, North Carolina, USA
| | - Douglas G Wixted
- Duke Clinical and Translational Science Institute, Duke UniversityDurham, North Carolina, USA
| | - Brooke L Heidenfelder
- Duke Clinical and Translational Science Institute, Duke UniversityDurham, North Carolina, USA
| | - Carla A Kingsbury
- Duke Clinical and Translational Science Institute, Duke UniversityDurham, North Carolina, USA
| | - Heidi M Register
- Duke Human Vaccine Institute, Duke UniversityDurham, North Carolina, USA
| | - Raul Louzao
- Duke Human Vaccine Institute, Duke UniversityDurham, North Carolina, USA
| | - Richard Sloane
- Center for The Study of Aging and Human Development, Duke University Medical CenterDurham, North Carolina, USA
| | - Julie Eckstrand
- Duke Clinical and Translational Science Institute, Duke UniversityDurham, North Carolina, USA
| | - Carl C Pieper
- Department of Biostatistics and Bioinformatics, Duke University Medical CenterDurham, North Carolina, USA
| | - Richard A Faldowski
- Center for The Study of Aging and Human Development, Duke University Medical CenterDurham, North Carolina, USA
| | - Thomas N Denny
- Duke Human Vaccine Institute, Duke UniversityDurham, North Carolina, USA
- Department of Medicine, Duke University Medical CenterDurham, North Carolina, USA
| | - Christopher W Woods
- Duke Global Health Institute, Duke UniversityDurham, North Carolina, USA
- Department of Medicine and Pathology, Duke University Medical CenterDurham, North Carolina, USA
| | - L Kristin Newby
- Duke Clinical Research Institute, Duke UniversityDurham, North Carolina, USA
- Duke Clinical and Translational Science Institute, Duke UniversityDurham, North Carolina, USA
- Division of Cardiology, Department of Medicine, Duke University Medical CenterDurham, North Carolina, USA
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