Evidence map›Paper›PMID 40267106›Full record

ArticlePloS one2025

Effects of inbound attendees of a mass gathering event on the COVID-19 epidemic using individual-based simulations.

Masaya M Saito, Kotoe Katayama, Akira Naruse, Peiying Ruan, Michio Murakami, Tomoaki Okuda, Tetsuo Ysutaka, Wataru Naito, Masaharu Tsubokura, Seiya Imoto

Abstract read
In one paragraph

Article in PloS one, 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

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

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

10 authors.

Masaya M SaitoDepartment of Information Security, Faculty of Information Systems, University of Nagasaki, Siebold, Manabino, Nagayocho, Nishisonogigun, Nagasaki, Japan.ORCID 0000-0002-4840-6515
Kotoe KatayamaLaboratory of Sequence Analysis, Human Genome Center, The Institute of Medical Science, The University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan.
Akira NaruseNVIDA, Santa Clara, California, United States of America.
Peiying RuanNVIDIA AI Technology Center, Tokyo, Japan.
Michio MurakamiCenter for Infectious Disease Education and Research (CiDER), Osaka University, Yamadaoka, Suita, Osaka, Japan.ORCID 0000-0002-5557-9801
Tomoaki OkudaDepartment of Applied Chemistry, Faculty of Science and Technology, Keio University, Hiyoshi, Kohoku, Yokohama, Kanagawa, Japan.ORCID 0000-0002-5057-9044
Tetsuo YsutakaInstitute for Geo-Resources and Environment, National Institute of Advanced Industrial Science and Technology (AIST), Higashi, Tsukuba, Ibaraki, Japan.
Wataru NaitoResearch Institute of Science for Safety and Sustainability, National Institute of Advanced Industrial Science and Technology (AIST), Onogawa, Tsukuba, Ibaraki, Japan.ORCID 0000-0003-2064-7170
Masaharu TsubokuraDepartment of Radiation Health Management, Fukushima Medical University School of Medicine, Hikarigaoka, Fukushima, Fukushima, Japan.
Seiya ImotoLaboratory of Sequence Analysis, Human Genome Center, The Institute of Medical Science, The University of Tokyo, Shirokanedai, Minato-ku, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given that mass gathering events involve heterogeneous and time-varying contact between residents and visitors, we sought to identify possible measures to prevent the potential acceleration of the outbreak of an emerging infectious disease induced by such events. An individual-based simulator was built based on a description of the reproduction rate among people infected with the infectious disease in a hypothetical city. Three different scenarios were assessed using our simulator, in which controls aimed at reduced contact were assumed to be carried out only in the main event venue or at subsequent additional events, or in which behavior restrictions were carried out among the visitors to the main event. The simulation results indicated that the increase in the number of patients with COVID-19 could possibly be suppressed to a level equivalent to that if the event were not being held so long as the prevalence among visitors was only slightly higher than that among domestic residents and strict requirements were applied to the activities of visitors.

Indexed as

COVID-19Mass GatheringsComputer SimulationEpidemicsHumansSARS-CoV-2

Identifiers

PMID40267106
PMCPMC12017503

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.