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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.
  • Yoneoka D; Department of Health Policy and Management, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan.
  • Tanoue Y; Graduate School of Public Health, St. Luke's International University, Tokyo, Japan.
  • Kawashima T; Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Nomura S; Institute for Business and Finance, Waseda University, Tokyo, Japan.
  • Shi S; Department of Mathematical and Computing Science, Tokyo Institute of Technology, Tokyo, Japan.
  • Eguchi A; Department of Health Policy and Management, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan.
  • Ejima K; Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Taniguchi T; Department of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Sakamoto H; Laboratory for Synthetic Biology, RIKEN Center for Biosystems Dynamics Research, Osaka, Japan.
  • Kunishima H; Center for Preventive Medical Sciences, Chiba University, Chiba, Japan.
  • Gilmour S; Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, USA.
  • Nishiura H; Department of Infectious Diseases, Chiba University, Chiba, Japan.
  • Miyata H; Department of Health Policy and Management, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan.
Lancet Reg Health West Pac ; 3: 100016, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-2287920
ABSTRACT

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).

Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: Lancet Reg Health West Pac Year: 2020 Document Type: Article Affiliation country: J.lanwpc.2020.100016

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Language: English Journal: Lancet Reg Health West Pac Year: 2020 Document Type: Article Affiliation country: J.lanwpc.2020.100016