ArticleInfectious Disease Modelling2024
An application of small-world network on predicting the behavior of infectious disease on campus.
Article in Infectious Disease Modelling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- Data-driven network diagnostics for optimizing POCUS management: an actionable hospital analytical approach.BMC health services research · 2026Article
- A topic dissemination model based on hypernetwork.Scientific reports · 2025Article
- Descriptive epidemiology of Lassa fever, its trend, seasonality, and mortality predictors in Ebonyi State, South- East, Nigeria, 2018-2022.BMC public health · 2024Article
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Authors and funding
2 authors.
Funding
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Abstract
Networks haven been widely used to understand the spread of infectious disease. This study examines the properties of small-world networks in modeling infectious disease on campus. Two different small-world models are developed and the behaviors of infectious disease in the models are observed through numerical simulations. The results show that the behavior pattern of infectious disease in a small-world network is different from those in a regular network or a random network. The spread of the infectious disease increases as the proportion of long-distance connections
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Registered trials
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