Evidence map›Paper›PMID 34173599›Full record

ArticleThe Lancet regional health. Western Pacific2020

Large-scale epidemiological monitoring of the COVID-19 epidemic in Tokyo.

Daisuke Yoneoka, Yuta Tanoue, Takayuki Kawashima, Shuhei Nomura, Shoi Shi, Akifumi Eguchi, Keisuke Ejima, Toshibumi Taniguchi, Haruka Sakamoto, Hiroyuki Kunishima and 3 more

Abstract read
In one paragraph

Article in The Lancet regional health. Western Pacific, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

  1. Article
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  12. Global monitoring of the impact of the COVID-19 pandemic through online surveys sampled from the Facebook user base.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  13. The Willingness to Pay for a Hypothetical Vaccine for the Coronavirus Disease 2019 (COVID-19).International journal of environmental research and public health · 2021
    Article
  14. Article
  15. Review
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  20. COVID-19 and Heat Illness in Tokyo, Japan: Implications for the Summer Olympic and Paralympic Games in 2021.International journal of environmental research and public health · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Daisuke YoneokaDepartment of Health Policy and Management, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan.
Yuta TanoueInstitute for Business and Finance, Waseda University, Tokyo, Japan.
Takayuki KawashimaDepartment of Mathematical and Computing Science, Tokyo Institute of Technology, Tokyo, Japan.
Shuhei NomuraDepartment of Health Policy and Management, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan.
Shoi ShiDepartment of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Akifumi EguchiCenter for Preventive Medical Sciences, Chiba University, Chiba, Japan.
Keisuke EjimaDepartment of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, USA.
Toshibumi TaniguchiDepartment of Infectious Diseases, Chiba University, Chiba, Japan.
Haruka SakamotoDepartment of Health Policy and Management, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan.
Hiroyuki KunishimaDepartment of Infectious Diseases, School of Medicine, St. Marianna University, Kanagawa, Japan.
Stuart GilmourGraduate School of Public Health, St. Luke's International University, Tokyo, Japan.
Hiroshi NishiuraGraduate School of Medicine, Hokkaido University, Hokkaido, Japan.
Hiroaki MiyataDepartment of Health Policy and Management, School of Medicine, Keio University, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOn 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.

methodsA 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

findingsWe 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 (

interpretationWith 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.

fundingThe present work was supported in part by a grant from the Ministry of Health, Labour and Welfare of Japan (H29-Gantaisaku-ippan-009).

Identifiers

PMID34173599
PMCPMC7546969

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.