ArticleChaos (Woodbury, N.Y.)2015
Interplay between the local information based behavioral responses and the epidemic spreading in complex networks.
Article in Chaos (Woodbury, N.Y.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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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
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Behavioural change models for infectious disease transmission: a systematic review (2010-2015).Journal of the Royal Society, Interface · 2016Pooled it
- Risk perception and subsidy policy-based voluntary vaccination driven by multiple information sources.PloS one · 2022Article
- The impact of dengue illness on social distancing and caregiving behavior.PLoS neglected tropical diseases · 2021Article
- Exploring Voluntary Vaccinating Behaviors using Evolutionary N-person Threshold Games.Scientific reports · 2017Article
- Voluntary Vaccination through Self-organizing Behaviors on Locally-mixed Social Networks.Scientific reports · 2017Article
- Interplay between epidemic spread and information propagation on metapopulation networks.Journal of theoretical biology · 2017Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The spreading of an infectious disease can trigger human behavior responses to the disease, which in turn plays a crucial role on the spreading of epidemic. In this study, to illustrate the impacts of the human behavioral responses, a new class of individuals, S(F), is introduced to the classical susceptible-infected-recovered model. In the model, S(F) state represents that susceptible individuals who take self-initiate protective measures to lower the probability of being infected, and a susceptible individual may go to S(F) state with a response rate when contacting an infectious neighbor. Via the percolation method, the theoretical formulas for the epidemic threshold as well as the prevalence of epidemic are derived. Our finding indicates that, with the increasing of the response rate, the epidemic threshold is enhanced and the prevalence of epidemic is reduced. The analytical results are also verified by the numerical simulations. In addition, we demonstrate that, because the mean field method neglects the dynamic correlations, a wrong result based on the mean field method is obtained-the epidemic threshold is not related to the response rate, i.e., the additional S(F) state has no impact on the epidemic threshold.
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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.