ArticleChaos, solitons, and fractals2020
Quantifying the effects of quarantine using an IBM SEIR model on scalefree networks.
Article in Chaos, solitons, and fractals, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Research on adaptive transmission and controls of COVID-19 on the basis of a complex network.Computers & industrial engineering · 2021Article
- Dynamics of SIR model with vaccination and heterogeneous behavioral response of individuals modeled by the Preisach operator.Journal of mathematical biology · 2021Article
- Behavioral response of population on transmissibility and saturation incidence of deadly pandemic through fractional order dynamical system.Results in physics · 2021Article
- Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 pandemic led several countries to resort to social distancing, the only known way to slow down the spread of the virus and keep the health system under control. Here we use an individual based model (IBM) to study how the duration, start date and intensity of quarantine affect the height and position of the peak of the infection curve. We show that stochastic effects, inherent to the model dynamics, lead to variable outcomes for the same set of parameters, making it crucial to compute the probability of each result. To simplify the analysis we divide the outcomes in only two categories, that we call
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