ArticlePloS one2021
Fast and principled simulations of the SIR model on temporal networks.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- REPLAY: a GPU-accelerated tool for temporal contact network epidemiology.BMC medical informatics and decision making · 2025Article
- Epydemix: An open-source Python package for epidemic modeling with integrated approximate Bayesian calibration.PLoS computational biology · 2025Article
- Connecting mass-action models and network models for infectious diseases.PLoS computational biology · 2025Article
- Heterogeneous risk tolerance, in-groups, and epidemic waves.Frontiers in applied mathematics and statistics · 2024Article
- Article
- Assessing individual risk and the latent transmission of COVID-19 in a population with an interaction-driven temporal model.Scientific reports · 2023Article
- Active querying approach to epidemic source detection on contact networks.Scientific reports · 2023Article
- Identifying important nodes in complex networks based on extended degree and E-shell hierarchy decomposition.Scientific reports · 2023Article
- Determining the rate of infectious disease testing through contagion potential.PLOS global public health · 2023Article
- Outbreak detection for temporal contact data.Applied network science · 2021Article
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Susceptible-Infectious-Recovered (SIR) model is the canonical model of epidemics of infections that make people immune upon recovery. Many of the open questions in computational epidemiology concern the underlying contact structure's impact on models like the SIR model. Temporal networks constitute a theoretical framework capable of encoding structures both in the networks of who could infect whom and when these contacts happen. In this article, we discuss the detailed assumptions behind such simulations-how to make them comparable with analytically tractable formulations of the SIR model, and at the same time, as realistic as possible. We also present a highly optimized, open-source code for this purpose and discuss all steps needed to make the program as fast as possible.
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Registered trials
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