Evidence map›Paper›PMID 35566527›Full record

ArticleJournal of clinical medicine2022

Analysis of COVID-19 Spread in Tokyo through an Agent-Based Model with Data Assimilation.

Chang Sun, Serge Richard, Takemasa Miyoshi, Naohiro Tsuzu

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Personalizing computational models to construct medical digital twins.Journal of the Royal Society, Interface · 2025
    Article
  2. Personalizing computational models to construct medical digital twins.bioRxiv : the preprint server for biology · 2024
    Article
  3. Article
  4. Article
  5. Analysis of COVID-19 in Japan with extended SEIR model and ensemble Kalman filter.Journal of computational and applied mathematics · 2023
    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.

Chang SunData Assimilation Research Team, RIKEN Center for Computational Science (R-CCS), Kobe 650-0047, Japan.
Serge RichardData Assimilation Research Team, RIKEN Center for Computational Science (R-CCS), Kobe 650-0047, Japan.
Takemasa MiyoshiData Assimilation Research Team, RIKEN Center for Computational Science (R-CCS), Kobe 650-0047, Japan.ORCID 0000-0003-3160-2525
Naohiro TsuzuData Assimilation Research Team, RIKEN Center for Computational Science (R-CCS), Kobe 650-0047, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we introduce an agent-based model together with a particle filter approach to study the spread of COVID-19. Investigations are mainly performed on the metropolis of Tokyo, but other prefectures of Japan are also briefly surveyed. A novel method for evaluating the effective reproduction number is one of the main outcomes of our approach. Other unknown parameters are also evaluated. Uncertain quantities, such as, for example, the probability that an infected agent develops symptoms, are tested and discussed, and the stability of our computations is examined. Detailed explanations are provided for the model and for the assimilation process.

Indexed as

agent-based modelCOVID-19data assimilationeffective reproduction number

Identifiers

PMID35566527
PMCPMC9103055

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.