Evidence map›Paper›PMID 39774000›Full record

ArticleScientific reports2025

Hotspot analysis of COVID-19 infection in Tokyo based on influx patterns.

Yu Kimura, Tatsunori Seki, Keisuke Chujo, Toshiki Murata, Tomoaki Sakurai, Satoshi Miyata, Hiroyasu Inoue, Nobuyasu Ito

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Yu KimuraSoftBank Corporation, Tokyo, Japan. yu.kimura@g.softbank.co.jp.
Tatsunori SekiSoftBank Corporation, Tokyo, Japan.
Keisuke ChujoSoftBank Corporation, Tokyo, Japan.
Toshiki MurataSoftBank Corporation, Tokyo, Japan. toshiki.murata@g.softbank.co.jp.
Tomoaki SakuraiSoftBank Corporation, Tokyo, Japan.
Satoshi MiyataSoftBank Corporation, Tokyo, Japan.
Hiroyasu InoueGraduate School of Information Science, University of Hyogo, Kobe, Japan.
Nobuyasu ItoRIKEN Center for Computational Science, Kobe, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We analyse the relationship between population influx and the effective reproduction number in the 23 wards of Tokyo during the COVID-19 pandemic to estimate hotspots of infection. We identify some patterns of population influx via factor analysis and estimate specific areas as infection-related hotspots by focusing on influx patterns that are highly correlated with the effective reproduction number. As a result, several influx patterns are assumed to be directly related to the subsequent spread of the infection. This analytical method has the potential to detect unknown hotspots related to pandemics in the future.

Indexed as

COVID-19SARS-CoV-2Basic Reproduction NumberDisease HotspotHumansPandemicsTokyo

Identifiers

PMID39774000
PMCPMC11707207

What OpenQuestion holds

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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.