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Allen JL, Amick BC, Williams ML, Kennedy JL, Boehme KW, Forrest JC, Primack B, Sides EA, Nembhard WN, Gardner SF, Snowden JN, James LP, Olgaard E, Gandy J. A longitudinal study of SARS-CoV-2 antibody seroprevalence and mitigation behaviors among college students at an Arkansas University. JOURNAL OF AMERICAN COLLEGE HEALTH : J OF ACH 2023:1-10. [PMID: 37289962 DOI: 10.1080/07448481.2023.2217456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 03/29/2023] [Accepted: 05/19/2023] [Indexed: 06/10/2023]
Abstract
Objective: Assess university students' SARS-CoV-2 antibody seroprevalence and mitigation behaviors over time. Participants: Randomly selected college students (N = 344) in a predominantly rural Southern state. Methods: Participants provided blood samples and completed self-administered questionnaires at three timepoints over the academic year. Adjusted odds ratios and 95% confidence intervals were estimated from logistic regression analyses. Results: SARS-CoV-2 antibody seroprevalence was 18.2% in September 2020, 13.1% in December, and 45.5% in March 2021 (21% for those with no vaccination history). SARS-CoV-2 antibody seroprevalence was associated with large social gatherings, staying local during the summer break, symptoms of fatigue or rhinitis, Greek affiliation, attending Greek events, employment, and using social media as the primary COVID-19 information source. In March 2021, seroprevalence was associated with receiving at least one dose of a COVID-19 vaccination. Conclusion: SARS-CoV-2 seroprevalence was higher in this population of college students than previous studies. Results can assist leaders in making informed decisions as new variants threaten college campuses.
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Affiliation(s)
- Jaimi L Allen
- Department of Epidemiology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Benjamin C Amick
- Department of Epidemiology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
- Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Mark L Williams
- Department of Health Behavior and Health Education, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Joshua L Kennedy
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
- Department of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
- Arkansas Children's Research Institute, Little Rock, Arkansas, USA
| | - Karl W Boehme
- Department of Microbiology & Immunology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
- Centre for Microbial Pathogenesis and Host Inflammatory Responses, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - J Craig Forrest
- Department of Microbiology & Immunology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Brian Primack
- Department of Public Health and Medicine, University of Arkansas, Fayetteville, Arkansas, USA
| | - Erica Ashley Sides
- Translational Research Institute, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Wendy N Nembhard
- Department of Epidemiology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Stephanie F Gardner
- College of Pharmacy, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Jessica N Snowden
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
- Arkansas Children's Research Institute, Little Rock, Arkansas, USA
| | - Laura P James
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
- Translational Research Institute, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Ericka Olgaard
- Department of Pathology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, USA
| | - Jay Gandy
- Department of Environmental Health, University of Arkansas for Medical Sciences, Fayetteville, Arkansas, USA
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Owusu-Boaitey N, Russell TW, Meyerowitz-Katz G, Levin AT, Herrera-Esposito D. Dynamics of SARS-CoV-2 seroassay sensitivity: a systematic review and modelling study. Euro Surveill 2023; 28:2200809. [PMID: 37227301 PMCID: PMC10283460 DOI: 10.2807/1560-7917.es.2023.28.21.2200809] [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: 10/10/2022] [Accepted: 03/10/2023] [Indexed: 05/26/2023] Open
Abstract
BackgroundSerological surveys have been the gold standard to estimate numbers of SARS-CoV-2 infections, the dynamics of the epidemic, and disease severity. Serological assays have decaying sensitivity with time that can bias their results, but there is a lack of guidelines to account for this phenomenon for SARS-CoV-2.AimOur goal was to assess the sensitivity decay of seroassays for detecting SARS-CoV-2 infections, the dependence of this decay on assay characteristics, and to provide a simple method to correct for this phenomenon.MethodsWe performed a systematic review and meta-analysis of SARS-CoV-2 serology studies. We included studies testing previously diagnosed, unvaccinated individuals, and excluded studies of cohorts highly unrepresentative of the general population (e.g. hospitalised patients).ResultsOf the 488 screened studies, 76 studies reporting on 50 different seroassays were included in the analysis. Sensitivity decay depended strongly on the antigen and the analytic technique used by the assay, with average sensitivities ranging between 26% and 98% at 6 months after infection, depending on assay characteristics. We found that a third of the included assays departed considerably from manufacturer specifications after 6 months.ConclusionsSeroassay sensitivity decay depends on assay characteristics, and for some types of assays, it can make manufacturer specifications highly unreliable. We provide a tool to correct for this phenomenon and to assess the risk of decay for a given assay. Our analysis can guide the design and interpretation of serosurveys for SARS-CoV-2 and other pathogens and quantify systematic biases in the existing serology literature.
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Affiliation(s)
- Nana Owusu-Boaitey
- Case Western Reserve University School of Medicine, Cleveland, United States
- These authors contributed equally to this work
| | - Timothy W Russell
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | | | - Andrew T Levin
- Dartmouth College, Hanover, United States
- National Bureau for Economic Research, Cambridge, United States
- Centre for Economic Policy Research, London, United Kingdom
| | - Daniel Herrera-Esposito
- These authors contributed equally to this work
- Department of Psychology, University of Pennsylvania, Philadelphia, United States
- Laboratorio de Neurociencias, Universidad de la República, Montevideo, Uruguay
- Centro Interdisciplinario en Ciencia de Datos y Aprendizaje Automático, Universidad de la República, Montevideo, Uruguay
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McElfish PA, Liston R, Smith V, Norris AK, Weaver J, Dickson SM, Macechko MD, Brimberry RK, Lemdja MR, Middleton TL, Nix MW, Irish-Clardy KA, Meredith-Neve SM, Kennedy JL, James LP. Rural Research Network to engage rural and minority community members in translational research. J Clin Transl Res 2023; 9:115-122. [PMID: 37179792 PMCID: PMC10171320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 01/30/2023] [Accepted: 03/02/2023] [Indexed: 05/15/2023] Open
Abstract
Background To address the high prevalence of health disparities and lack of research opportunities among rural and minority communities, the University of Arkansas for Medical Sciences (UAMS) developed the Rural Research Network in January 2020. Aim The aim of this report is to describe our process and progress in developing a rural research network. The Rural Research Network provides a platform to expand research participation opportunities to rural Arkansans, many of whom are older adults, low-income individuals, and underrepresented minority populations. Methods The Rural Research Network leverages existing UAMS Regional Programs family medicine residency clinics within an academic medical center. Results Since the inception of the Rural Research Network, research infrastructure and processes have been built within the regional sites. Twelve diverse studies have been implemented with recruitment and data collection from 9248 participants, and 32 manuscripts have been published with residents and faculty from the regional sites. Most studies were able to recruit Black/African American participants at or above a representative sample. Conclusions As the Rural Research Network matures, the types of research will expand in parallel with the health priorities of Arkansas. Relevance to Patients The Rural Research Network demonstrates how Cancer Institutes and sites funded by a Clinical and Translational Science Award can collaborate to expand research capacity and increase opportunities for research among rural and minority communities.
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Affiliation(s)
- Pearl A. McElfish
- University of Arkansas for Medical Sciences Northwest, Springdale, AR, United States of America
- Corresponding author: Pearl A. McElfish University of Arkansas for Medical Sciences Northwest, 2708 S. 48 St, Springdale, AR 72762, United States of America. Phone: +1 479 713 8680
| | - Robin Liston
- University of Arkansas for Medical Sciences, Little Rock, AR, United States of America
| | - Veronica Smith
- University of Arkansas for Medical Sciences, Little Rock, AR, United States of America
| | - Amber K. Norris
- University of Arkansas for Medical Sciences East, Helena-West Helena, AR, United States of America
| | - Jordan Weaver
- University of Arkansas for Medical Sciences North Central, Batesville, AR, United States of America
| | - Scott M. Dickson
- University of Arkansas for Medical Sciences Northeast, Jonesboro, AR, United States of America
| | - Michael D. Macechko
- University of Arkansas for Medical Sciences Northwest, Fayetteville, AR, United States of America
| | - Ronald K. Brimberry
- University of Arkansas for Medical Sciences Northwest, Fayetteville, AR, United States of America
| | - Mimo R. Lemdja
- University of Arkansas for Medical Sciences South, Magnolia, AR, United States of America
| | - Toni L. Middleton
- University of Arkansas for Medical Sciences South Central, Pine Bluff, AR, United States of America
| | - Matthew W. Nix
- University of Arkansas for Medical Sciences Southwest, Texarkana, AR, United States of America
| | | | | | - Joshua L. Kennedy
- University of Arkansas for Medical Sciences, Little Rock, AR, United States of America
| | - Laura P. James
- University of Arkansas for Medical Sciences, Little Rock, AR, United States of America
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Pan X, Kaminga AC, Chen Y, Liu H, Wen SW, Fang Y, Jia P, Liu A. Auxiliary Screening COVID-19 by Serology. Front Public Health 2022; 10:819841. [PMID: 35983367 PMCID: PMC9380738 DOI: 10.3389/fpubh.2022.819841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 06/21/2022] [Indexed: 11/13/2022] Open
Abstract
Background The 2019 novel coronavirus (COVID-19) pandemic remains rampant in many countries/regions. Improving the positive detection rate of COVID-19 infection is an important measure for control and prevention of this pandemic. This meta-analysis aims to systematically summarize the current characteristics of the auxiliary screening methods by serology for COVID-19 infection in real world. Methods Web of Science, Cochrane Library, Embase, PubMed, CNKI, and Wangfang databases were searched for relevant articles published prior to May 1st, 2022. Data on specificity, sensitivity, positive/negative likelihood ratio, area under curve (AUC), and diagnostic odds ratio (dOR) were calculated purposefully. Results Sixty-two studies were included with 35,775 participants in the meta-analysis. Among these studies, the pooled estimates for area under the summary receiver operator characteristic of IgG and IgM to predicting COVID-19 diagnosis were 0.974 and 0.928, respectively. The IgG dOR was 209.78 (95% CI: 106.12 to 414.67). The IgM dOR was 78.17 (95% CI: 36.76 to 166.25). Conclusion Our findings support serum-specific antibody detection may be the main auxiliary screening methods for COVID-19 infection in real world.
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Affiliation(s)
- Xiongfeng Pan
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Atipatsa C. Kaminga
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
- Department of Mathematics and Statistics, Mzuzu University, Mzuzu, Malawi
| | - Yuyao Chen
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Hongying Liu
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Shi Wu Wen
- OMNI Research Group, Ottawa Hospital Research Institute, Ottawa, ON, Canada
- Department of Obstetrics and Gynaecology, University of Ottawa Faculty of Medicine, Ottawa, ON, Canada
- School of Epidemiology and Public Health, University of Ottawa Faculty of Medicine, Ottawa, ON, Canada
| | - Yingjing Fang
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
| | - Peng Jia
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
- *Correspondence: Peng Jia
| | - Aizhong Liu
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China
- Aizhong Liu
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