Auxiliary Screening COVID-19 by Serology

Xiongfeng Pan; Atipatsa C. Kaminga; Atipatsa C. Kaminga; Yuyao Chen; Hongying Liu; Shi Wu Wen; Shi Wu Wen; Shi Wu Wen; Yingjing Fang; Peng Jia; Peng Jia; Aizhong Liu

doi:10.3389/fpubh.2022.819841

Frontiers in Public Health (Aug 2022)

Auxiliary Screening COVID-19 by Serology

Xiongfeng Pan,
Atipatsa C. Kaminga,
Atipatsa C. Kaminga,
Yuyao Chen,
Hongying Liu,
Shi Wu Wen,
Shi Wu Wen,
Shi Wu Wen,
Yingjing Fang,
Peng Jia,
Peng Jia,
Aizhong Liu

Affiliations

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
Atipatsa C. Kaminga: 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
Shi Wu Wen: Department of Obstetrics and Gynaecology, University of Ottawa Faculty of Medicine, Ottawa, ON, Canada
Shi Wu Wen: 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
Peng Jia: International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
Aizhong Liu: Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, China

DOI: https://doi.org/10.3389/fpubh.2022.819841
Journal volume & issue: Vol. 10

Abstract

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BackgroundThe 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.MethodsWeb 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.ResultsSixty-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).ConclusionOur findings support serum-specific antibody detection may be the main auxiliary screening methods for COVID-19 infection in real world.

Published in Frontiers in Public Health

ISSN: 2296-2565 (Online)
Publisher: Frontiers Media S.A.
Country of publisher: Switzerland
LCC subjects: Medicine: Public aspects of medicine
Website: https://www.frontiersin.org/journals/public-health

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