ArticlePLoS computational biology2015
Temporal Gillespie Algorithm: Fast Simulation of Contagion Processes on Time-Varying Networks.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- Gillespie-based simulation and inference for non-Markovian stochastic reaction networks.Briefings in bioinformatics · 2026Article
- MEmilio: a high performance Modular EpideMIcs simuLatIOn software for multi-scale and comparative simulations of infectious disease dynamics.Scientific reports · 2026Article
- Zooplankton feeding behavioral signatures in the morphology of macroscale prey spatial distribution.PLoS computational biology · 2026Article
- Unifying non-Markovian dynamics and agent heterogeneity in scalable stochastic networks.Nature communications · 2026Article
- Fast Actin Disassembly and Fimbrin Mechanosensitivity Support Rapid Turnover in a Model of Clathrin-Mediated Endocytosis.Cytoskeleton (Hoboken, N.J.) · 2025Article
- Hybrid metapopulation agent-based epidemiological models for efficient insight on the individual scale: A contribution to green computing.Infectious Disease Modelling · 2025Article
- Integrating Human Mobility Models with Epidemic Modeling: A Framework for Generating Synthetic Temporal Contact Networks.Entropy (Basel, Switzerland) · 2025Article
- Structural inequalities exacerbate infection disparities.Scientific reports · 2025Article
- Dynamic Contact Networks in Confined Spaces: Synthesizing Micro-Level Encounter Patterns through Human Mobility Models from Real-World Data.Entropy (Basel, Switzerland) · 2024Article
- The effect of temperature on the boundary conditions of West Nile virus circulation in Europe.PLoS neglected tropical diseases · 2024Article
- Simulating real-life scenarios to better understand the spread of diseases under different contexts.Scientific reports · 2024Article
- Criticality in probabilistic models of spreading dynamics in brain networks: Epileptic seizures.PLoS computational biology · 2023Article
- Article
- COVID-19 epidemic under the K-quarantine model: Network approach.Chaos, solitons, and fractals · 2022Article
- Reconstructing contact network structure and cross-immunity patterns from multiple infection histories.PLoS computational biology · 2021Article
- Mathematical modeling of spatio-temporal population dynamics and application to epidemic spreading.Mathematical biosciences · 2021Article
- Evaluating the contributions of strategies to prevent SARS-CoV-2 transmission in the healthcare setting: a modelling study.BMJ open · 2021Article
- Social distancing and epidemic resurgence in agent-based susceptible-infectious-recovered models.Scientific reports · 2021Article
- Modelling digital and manual contact tracing for COVID-19. Are low uptakes and missed contacts deal-breakers?PloS one · 2021Article
- Impact of temporal correlations on high risk outbreaks of independent and cooperative SIR dynamics.PloS one · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stochastic simulations are one of the cornerstones of the analysis of dynamical processes on complex networks, and are often the only accessible way to explore their behavior. The development of fast algorithms is paramount to allow large-scale simulations. The Gillespie algorithm can be used for fast simulation of stochastic processes, and variants of it have been applied to simulate dynamical processes on static networks. However, its adaptation to temporal networks remains non-trivial. We here present a temporal Gillespie algorithm that solves this problem. Our method is applicable to general Poisson (constant-rate) processes on temporal networks, stochastically exact, and up to multiple orders of magnitude faster than traditional simulation schemes based on rejection sampling. We also show how it can be extended to simulate non-Markovian processes. The algorithm is easily applicable in practice, and as an illustration we detail how to simulate both Poissonian and non-Markovian models of epidemic spreading. Namely, we provide pseudocode and its implementation in C++ for simulating the paradigmatic Susceptible-Infected-Susceptible and Susceptible-Infected-Recovered models and a Susceptible-Infected-Recovered model with non-constant recovery rates. For empirical networks, the temporal Gillespie algorithm is here typically from 10 to 100 times faster than rejection sampling.
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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.