ArticleInfectious Disease Modelling2027
A new three-layer metapopulation networks model coupling online-offline social interactions with epidemic spread.
Article in Infectious Disease Modelling, 2027. 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The dissemination of epidemic-related information can effectively enhance public awareness of preventive measures and decrease infection risks. However, information dissemination through multiple channels, including both online and offline sources, and the dynamics of information dissemination across these channels are influenced by individual mobility. To address this gap, this study develops a three-layer metapopulation network coupled model that integrates online information dissemination, epidemic spreading, and offline information dissemination. The proposed model systematically investigates the patterns of information dissemination through both online and offline channels, as well as the epidemic reaction-diffusion process driven by individual migration. Furthermore, the social interactions dynamics of both information channels are influenced by migration, manifested as migrated individuals acquire offline information in destination patches and establish online connections with individuals residing there. Theoretical analysis using the Microscopic Markov Chain Approach (MMCA) derives epidemic thresholds, while Monte Carlo (MC) simulations validate the model and examine factors influencing propagation dynamics. Results indicate that migration enhances individuals' offline information acquisition, and accelerates cross-patch online information dissemination. Both online and offline information interactions exert inhibitory effects on epidemic spread, effectively increasing the infection threshold and reducing the outbreak scale. Furthermore, increasing the connectivity and dissemination rate of online information, particularly the information dissemination via weak relationships between patches, can effectively inhibit epidemic outbreaks. Notably, when the suppression effect of information on the epidemic is weak, population migration facilitates epidemic spread. In contrast, when the suppression effect is strong, migration-driven information dissemination significantly reduces the probability of infection, thereby further suppressing the outbreak.
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.