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Large-scale epidemiological monitoring of the COVID-19 epidemic in Tokyo
BACKGROUND: On April 7, 2020, the Japanese government declared a state of emergency regarding the novel coronavirus (COVID-19). Given the nation-wide spread of the coronavirus in major Japanese cities and the rapid increase in the number of cases with untraceable infection routes, large-scale monito...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7546969/ https://www.ncbi.nlm.nih.gov/pubmed/34173599 http://dx.doi.org/10.1016/j.lanwpc.2020.100016 |
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author | Yoneoka, Daisuke Tanoue, Yuta Kawashima, Takayuki Nomura, Shuhei Shi, Shoi Eguchi, Akifumi Ejima, Keisuke Taniguchi, Toshibumi Sakamoto, Haruka Kunishima, Hiroyuki Gilmour, Stuart Nishiura, Hiroshi Miyata, Hiroaki |
author_facet | Yoneoka, Daisuke Tanoue, Yuta Kawashima, Takayuki Nomura, Shuhei Shi, Shoi Eguchi, Akifumi Ejima, Keisuke Taniguchi, Toshibumi Sakamoto, Haruka Kunishima, Hiroyuki Gilmour, Stuart Nishiura, Hiroshi Miyata, Hiroaki |
author_sort | Yoneoka, Daisuke |
collection | PubMed |
description | BACKGROUND: On April 7, 2020, the Japanese government declared a state of emergency regarding the novel coronavirus (COVID-19). Given the nation-wide spread of the coronavirus in major Japanese cities and the rapid increase in the number of cases with untraceable infection routes, large-scale monitoring for capturing the current epidemiological situation of COVID-19 in Japan is urgently required. METHODS: A chatbot-based healthcare system named COOPERA (COvid-19: Operation for Personalized Empowerment to Render smart prevention And AN care seeking) was developed to surveil the Japanese epidemiological situation in real-time. COOPERA asked questions regarding personal information, location, preventive actions, COVID-19 related symptoms and their residence. Empirical Bayes estimates of the age-sex-standardized incidence rate and disease mapping approach using scan statistics were utilized to identify the geographical distribution of the symptoms in Tokyo and their spatial correlation r with the identified COVID-19 cases. FINDINGS: We analyzed 353,010 participants from Tokyo recruited from 27th March to 6th April 2020. The mean (SD) age of participants was 42.7 (12.3), and 63.4%, 36.4% or 0.2% were female, male, or others, respectively. 95.6% of participants had no subjective symptoms. We identified several geographical clusters with high spatial correlation (r = 0.9), especially in downtown areas in central Tokyo such as Shibuya and Shinjuku. INTERPRETATION: With the global spread of COVID-19, medical resources are being depleted. A new system to monitor the epidemiological situation, COOPERA, can provide insights to assist political decision to tackle the epidemic. In addition, given that Japan has not had a strong lockdown policy to weaken the spread of the infection, our result would be useful for preparing for the second wave in other countries during the next flu season without a strong lockdown. FUNDING: The present work was supported in part by a grant from the Ministry of Health, Labour and Welfare of Japan (H29-Gantaisaku-ippan-009). |
format | Online Article Text |
id | pubmed-7546969 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-75469692020-10-13 Large-scale epidemiological monitoring of the COVID-19 epidemic in Tokyo Yoneoka, Daisuke Tanoue, Yuta Kawashima, Takayuki Nomura, Shuhei Shi, Shoi Eguchi, Akifumi Ejima, Keisuke Taniguchi, Toshibumi Sakamoto, Haruka Kunishima, Hiroyuki Gilmour, Stuart Nishiura, Hiroshi Miyata, Hiroaki Lancet Reg Health West Pac Research Paper BACKGROUND: On April 7, 2020, the Japanese government declared a state of emergency regarding the novel coronavirus (COVID-19). Given the nation-wide spread of the coronavirus in major Japanese cities and the rapid increase in the number of cases with untraceable infection routes, large-scale monitoring for capturing the current epidemiological situation of COVID-19 in Japan is urgently required. METHODS: A chatbot-based healthcare system named COOPERA (COvid-19: Operation for Personalized Empowerment to Render smart prevention And AN care seeking) was developed to surveil the Japanese epidemiological situation in real-time. COOPERA asked questions regarding personal information, location, preventive actions, COVID-19 related symptoms and their residence. Empirical Bayes estimates of the age-sex-standardized incidence rate and disease mapping approach using scan statistics were utilized to identify the geographical distribution of the symptoms in Tokyo and their spatial correlation r with the identified COVID-19 cases. FINDINGS: We analyzed 353,010 participants from Tokyo recruited from 27th March to 6th April 2020. The mean (SD) age of participants was 42.7 (12.3), and 63.4%, 36.4% or 0.2% were female, male, or others, respectively. 95.6% of participants had no subjective symptoms. We identified several geographical clusters with high spatial correlation (r = 0.9), especially in downtown areas in central Tokyo such as Shibuya and Shinjuku. INTERPRETATION: With the global spread of COVID-19, medical resources are being depleted. A new system to monitor the epidemiological situation, COOPERA, can provide insights to assist political decision to tackle the epidemic. In addition, given that Japan has not had a strong lockdown policy to weaken the spread of the infection, our result would be useful for preparing for the second wave in other countries during the next flu season without a strong lockdown. FUNDING: The present work was supported in part by a grant from the Ministry of Health, Labour and Welfare of Japan (H29-Gantaisaku-ippan-009). Elsevier 2020-10-10 /pmc/articles/PMC7546969/ /pubmed/34173599 http://dx.doi.org/10.1016/j.lanwpc.2020.100016 Text en © 2020 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Paper Yoneoka, Daisuke Tanoue, Yuta Kawashima, Takayuki Nomura, Shuhei Shi, Shoi Eguchi, Akifumi Ejima, Keisuke Taniguchi, Toshibumi Sakamoto, Haruka Kunishima, Hiroyuki Gilmour, Stuart Nishiura, Hiroshi Miyata, Hiroaki Large-scale epidemiological monitoring of the COVID-19 epidemic in Tokyo |
title | Large-scale epidemiological monitoring of the COVID-19 epidemic in Tokyo |
title_full | Large-scale epidemiological monitoring of the COVID-19 epidemic in Tokyo |
title_fullStr | Large-scale epidemiological monitoring of the COVID-19 epidemic in Tokyo |
title_full_unstemmed | Large-scale epidemiological monitoring of the COVID-19 epidemic in Tokyo |
title_short | Large-scale epidemiological monitoring of the COVID-19 epidemic in Tokyo |
title_sort | large-scale epidemiological monitoring of the covid-19 epidemic in tokyo |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7546969/ https://www.ncbi.nlm.nih.gov/pubmed/34173599 http://dx.doi.org/10.1016/j.lanwpc.2020.100016 |
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