Evidence map›Paper›PMID 36596837›Full record

ArticleScientific reports2023

Novel indicator for the spread of new coronavirus disease 2019 and its association with human mobility in Japan.

Yuta Kawakami, Shuko Nojiri, Daisuke Nakamoto, Yoshiki Irie, Satoshi Miyazawa, Manabu Kuroki, Yuji Nishizaki

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. 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

7 authors.

Yuta KawakamiClinical Research and Trial Center, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan.
Shuko NojiriClinical Research and Trial Center, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan. s-nojiri@juntendo.ac.jp.
Daisuke NakamotoClinical Translational Science, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan.
Yoshiki IrieClinical Research and Trial Center, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan.
Satoshi MiyazawaLocationMind Inc, Tokyo, Japan.
Manabu KurokiFaculty of Engineering, Yokohama National University, 79-5 Tokiwadai, Hodogaya-Ku, Yokohama, Kanagawa, 240-8501, Japan.
Yuji NishizakiClinical Research and Trial Center, Juntendo University, 2-1-1 Hongo, Bunkyo-Ku, Tokyo, 113-8421, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Japanese government adopted policies to control human mobility in 2020 to prevent the spread of severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19). The present study examined the impact of human mobility on COVID-19 cases at the prefectural level in Japan by devising an indicator to have a relationship between the number of infected people and on human mobility. We calculated origin-destination travel mobility within prefectures in Japan from March 1st to December 31st, 2020, using mobile phone data. A cross-correlation function (CCF) was used to examine the relationship between human mobility and a COVID-19 infection acceleration indicator (IAI), which represents the rate of change in the speed of COVID-19 infection. The CCF of intraprefectural human mobility and the IAI in Tokyo showed a maximum value of 0.440 at lag day 12, and the IAI could be used as an indicator to predict COVID-19 cases. Therefore, the IAI and human mobility during the COVID-19 pandemic were useful for predicting infection status. The number of COVID-19 cases was associated with human mobility at the prefectural level in Japan in 2020. Controlling human mobility could help control infectious diseases in a pandemic, especially prior to starting vaccination.

Indexed as

COVID-19HumansJapanPandemicsSARS-CoV-2Tokyo

Identifiers

PMID36596837
PMCPMC9810243

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.