Evidence map›Paper›PMID 36463351›Full record

ArticleScientific reports2022

Agent-based model using GPS analysis for infection spread and inhibition mechanism of SARS-CoV-2 in Tokyo.

Taishu Murakami, Shunsuke Sakuragi, Hiroshi Deguchi, Masaru Nakata

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Taishu MurakamiMRI Research Associates, Inc., 2-10-3 Nagata-cho, Chiyoda-ku, Tokyo, 100-0014, Japan.
Shunsuke SakuragiMRI Research Associates, Inc., 2-10-3 Nagata-cho, Chiyoda-ku, Tokyo, 100-0014, Japan. shunsuke_sakuragi@mri-ra.co.jp.
Hiroshi DeguchiFaculty of Commerce and Economics, Chiba University of Commerce, 1-3-1 Konodai, Ichikawa-shi, Chiba, 272-8512, Japan.
Masaru NakataMRI Research Associates, Inc., 2-10-3 Nagata-cho, Chiyoda-ku, Tokyo, 100-0014, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analyzing the SARS-CoV-2 pandemic outbreak based on actual data while reflecting the characteristics of the real city provides beneficial information for taking reasonable infection control measures in the future. We demonstrate agent-based modeling for Tokyo based on GPS information and official national statistics and perform a spatiotemporal analysis of the infection situation in Tokyo. As a result of the simulation during the first wave of SARS-CoV-2 in Tokyo using real GPS data, the infection occurred in the service industry, such as restaurants, in the city center, and then the infected people brought back the virus to the residential area; the infection spread in each area in Tokyo. This phenomenon clarifies that the spread of infection can be curbed by suppressing going out or strengthening infection prevention measures in service facilities. It was shown that pandemic measures in Tokyo could be achieved not only by strong control, such as the lockdown of cities, but also by thorough infection prevention measures in service facilities, which explains the curb phenomena in real Tokyo.

Indexed as

COVID-19SARS-CoV-2CitiesHumansInfection ControlTokyo

Identifiers

PMID36463351
PMCPMC9719469

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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.