ArticleInfectious Disease Modelling2026
Application of the type and target reproduction numbers to the evaluation of the influence of each prefecture in Japan on the disease spread.
Article in Infectious Disease Modelling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this study, by applying population mobility data in July, August and September of 2019-2023 in Japan to a multigroup epidemic model, we calculate the type and target reproduction numbers of each prefecture in Japan. Regarding these values as a kind of network centrality measure, we discuss which prefectures are influential on the disease spread in Japan. We show that the values of the type reproduction number are relatively high in 10 prefectures consisting of Hokkaido, Saitama, Chiba, Tokyo, Kanagawa, Aichi, Kyoto, Osaka, Hyogo and Fukuoka. In particular, by calculating the target reproduction number, we show that Tokyo and Kyoto could be the most influential on the disease spread, and the population mobility between the Kanto and Kansai regions could be the key factor for the nationwide epidemic in Japan.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.