ArticlePhysica A2021
A random walk Monte Carlo simulation study of COVID-19-like infection spread.
Article in Physica A, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- A coupled experimental and statistical approach for an assessment of SARS-CoV-2 infection risk at indoor event locations.BMC public health · 2023Article
- Attitudinal analysis of vaccination effects to lead endemic phases.Scientific reports · 2023Article
- Plausible explanation for the third COVID-19 wave in India and its implications.Infectious Disease Modelling · 2023Article
- COVID-19 modeling based on real geographic and population data.Turkish journal of medical sciences · 2023Article
- Using a latent Hawkes process for epidemiological modelling.PloS one · 2023Article
- COVID-19 ground-glass opacity segmentation based on fuzzy c-means clustering and improved random walk algorithm.Biomedical signal processing and control · 2023Article
- Airborne transmission of COVID-19 virus in enclosed spaces: An overview of research methods.Indoor air · 2022Review
- Population density impact on COVID-19 mortality rate: A multifractal analysis using French data.Physica A · 2022Article
- Towards predicting COVID-19 infection waves: A random-walk Monte Carlo simulation approach.Chaos, solitons, and fractals · 2022Article
- A stochastic process based modular tool-box for simulating COVID-19 infection spread.Informatics in medicine unlocked · 2022Article
- A new logistic growth model applied to COVID-19 fatality data.Epidemics · 2021Article
- Nonlinear Dynamics of the Introduction of a New SARS-CoV-2 Variant with Different Infectiousness.Mathematics (Basel, Switzerland) · 2021Article
- The effect of weekend curfews on epidemics: a Monte Carlo simulation.Turkish journal of biology = Turk biyoloji dergisi · 2021Article
- Piecewise quadratic growth during the 2019 novel coronavirus epidemic.Infectious Disease Modelling · 2020Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent analysis of early COVID-19 data from China showed that the number of confirmed cases followed a subexponential power-law increase, with a growth exponent of around 2.2 (Maier and Brockmann, 2020). The power-law behavior was attributed to a combination of effective containment and mitigation measures employed as well as behavioral changes by the population. In this work, we report a random walk Monte Carlo simulation study of proximity-based infection spread. Control interventions such as lockdown measures and mobility restrictions are incorporated in the simulations through a single parameter, the size of each step in the random walk process. The step size
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