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Cumulative and undiagnosed SARS-CoV-2 infection among the staff of a medical research centre in Tokyo after the emergence of variants

Published online by Cambridge University Press:  08 March 2023

Tetsuya Mizoue*
Affiliation:
Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan
Shohei Yamamoto
Affiliation:
Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan
Yusuke Oshiro
Affiliation:
Department of Laboratory Testing, Center Hospital of the National Center for the Global Health and Medicine, Tokyo, Japan
Natsumi Inamura
Affiliation:
Department of Laboratory Testing, Center Hospital of the National Center for the Global Health and Medicine, Tokyo, Japan
Takashi Nemoto
Affiliation:
Department of Laboratory Testing, Center Hospital of the National Center for the Global Health and Medicine, Tokyo, Japan
Kumi Horii
Affiliation:
Infection Control Office, Center Hospital of the National Center for the Global Health and Medicine, Tokyo, Japan
Kaori Okudera
Affiliation:
Infection Control Office, Kohnodai Hospital of the National Center for the Global Health and Medicine, Chiba, Japan
Maki Konishi
Affiliation:
Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan
Mitsuru Ozeki
Affiliation:
Department of Laboratory Testing, Center Hospital of the National Center for the Global Health and Medicine, Tokyo, Japan
Haruhito Sugiyama
Affiliation:
Center Hospital of the National Center for the Global Health and Medicine, Tokyo, Japan
Nobuyoshi Aoyanagi
Affiliation:
Kohnodai Hospital of the National Center for the Global Health and Medicine, Chiba, Japan
Wataru Sugiura
Affiliation:
Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan
Norio Ohmagari
Affiliation:
Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo, Japan
*
Author for correspondence: Tetsuya Mizoue, E-mail: mizoue@hosp.ncgm.go.jp
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Abstract

To describe the trend of cumulative incidence of coronavirus disease 19 (COVID-19) and undiagnosed cases over the pandemic through the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants among healthcare workers in Tokyo, we analysed data of repeated serological surveys and in-house COVID-19 registry among the staff of National Center for Global Health and Medicine. Participants were asked to donate venous blood and complete a survey questionnaire about COVID-19 diagnosis and vaccine. Positive serology was defined as being positive on Roche or Abbott assay against SARS-CoV-2 nucleocapsid protein, and cumulative infection was defined as either being seropositive or having a history of COVID-19. Cumulative infection has increased from 2.0% in June 2021 (pre-Delta) to 5.3% in December 2021 (post-Delta). After the emergence of the Omicron, it has increased substantially during 2022 (16.9% in June and 39.0% in December). As of December 2022, 30% of those who were infected in the past were not aware of their infection. Results indicate that SARS-CoV-2 infection has rapidly expanded during the Omicron-variant epidemic among healthcare workers in Tokyo and that a sizable number of infections were undiagnosed.

Information

Type
Original Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press
Figure 0

Table 1. Chronological change of COVID-19 indicators among the staff of NCGM

Figure 1

Fig. 1. Expansion of SARS-CoV-2 infection among the staff of the NCGM during the pandemic.

Figure 2

Table 2. Chronological change of COVID-19 cumulative incidence according to background factors

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