ArticlePhysical review. E2016
Limitations of discrete-time approaches to continuous-time contagion dynamics.
Article in Physical review. E, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Efficient Gillespie algorithms for spreading phenomena in large and heterogeneous higher-order networks.Nature communications · 2026Article
- Flexible Bayesian inference on partially observed epidemics.Journal of complex networks · 2024Article
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- J-SPACE: a Julia package for the simulation of spatial models of cancer evolution and of sequencing experiments.BMC bioinformatics · 2022Article
- An epidemic model for COVID-19 transmission in Argentina: Exploration of the alternating quarantine and massive testing strategies.Mathematical biosciences · 2022Article
- COVID-19 epidemic under the K-quarantine model: Network approach.Chaos, solitons, and fractals · 2022Article
- Synchronising institutions and value systems: A model of opinion dynamics mediated by proportional representation.PloS one · 2021Article
- Effects of heterogeneous self-protection awareness on resource-epidemic coevolution dynamics.Applied mathematics and computation · 2020Article
- Efficient sampling of spreading processes on complex networks using a composition and rejection algorithm.Computer physics communications · 2019Article
- Hipsters on networks: How a minority group of individuals can lead to an antiestablishment majority.Physical review. E · 2019Article
- Epidemic Threshold in Continuous-Time Evolving Networks.Physical review letters · 2018Article
- Effect of risk perception on epidemic spreading in temporal networks.Physical review. E · 2018Article
- Mathematical models of SIR disease spread with combined non-sexual and sexual transmission routes.Infectious Disease Modelling · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Continuous-time Markov process models of contagions are widely studied, not least because of their utility in predicting the evolution of real-world contagions and in formulating control measures. It is often the case, however, that discrete-time approaches are employed to analyze such models or to simulate them numerically. In such cases, time is discretized into uniform steps and transition rates between states are replaced by transition probabilities. In this paper, we illustrate potential limitations to this approach. We show how discretizing time leads to a restriction on the values of the model parameters that can accurately be studied. We examine numerical simulation schemes employed in the literature, showing how synchronous-type updating schemes can bias discrete-time formalisms when compared against continuous-time formalisms. Event-based simulations, such as the Gillespie algorithm, are proposed as optimal simulation schemes both in terms of replicating the continuous-time process and computational speed. Finally, we show how discretizing time can affect the value of the epidemic threshold for large values of the infection rate and the recovery rate, even if the ratio between the former and the latter is small.
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Registered trials
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