journal article·2024-09-01Open access

On the use of reactive multiparticle collision dynamics to gather particulate level information from simulations of epidemic models

Zaib Un Nisa Memon, Katrin Rohlf

AIP Advances· Volume 14· Issue 9

Abstract

This paper discusses the application of reactive multiparticle collision (RMPC) dynamics, a particle-based method, to epidemic models. First, we consider a susceptible-infectious-recovered framework to obtain data on contacts of susceptibles with infectious people in a population. It is found that the number of contacts increases and the contact duration decreases with increases in the disease transmission rate and average population speed. Next, we obtain reinfection statistics for a general infectious disease from RMPC simulations of a susceptible-infectious-recovered-susceptible model. Finally, we simulate a susceptible-exposed-infectious-recovered model and gather the exposure, infection, and recovery time for the individuals in the population under consideration. It is worth mentioning that we can collect data in the form of average contact duration, average initial infection time, etc., from RMPC simulations of these models, which is not possible with population-based stochastic models, or deterministic systems. This study provides quantitative insights on the potential of RMPC to simulate epidemic models and motivates future efforts for its application in the field of mathematical epidemiology.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: COVID-19 epidemiological studies · Mathematical and Theoretical Epidemiology and Ecology Models · Diffusion and Search Dynamics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Mathematics, Toronto Metropolitan University , 350 Victoria St., Toronto ON M5B 2K3, Canada

Funding

Natural Sciences and Engineering Research Council of Canada · Ontario Graduate Scholarship · 2007 NSERC Research Tools and Infrastructure Grant

References (39)

Show source-provided references
1. An introduction to stochastic epidemic models10.1007/978-3-540-78911-6_4 ↗
2. Stochasticity in staged models of epidemics: Quantifying the dynamics of whooping cough10.1098/rsif.2009.0514 ↗
3. Generalized kinetic theory approach to modeling spread- and evolution of epidemics10.1016/s0895-7177(04)90501-8 ↗
4. Modeling and simulating the spatial spread of an epidemic through multiscale kinetic transport equations10.1142/s0218202521400017 ↗
5. Modelling epidemics and virus mutations by methods of the mathematical kinetic theory for active particles10.1142/s0218202509003838 ↗
6. A viral load-based model for epidemic spread on spatial networks10.3934/mbe.2021285 ↗
7. A kinetic model for epidemic spread10.2140/memocs.2020.8.249 ↗
8. Kinetic modeling of local epidemic spread and its simulation10.1007/s10915-017-0408-9 ↗
9. Understanding contagion dynamics through microscopic processes in active Brownian particles10.1038/s41598-020-77860-y ↗
10. Particle modeling of the spreading of coronavirus disease (COVID-19)10.1063/5.0020565 ↗
11. Modeling the epidemic dynamics of COVID-19: Agent-based approach including molecular dynamics simulation and SEIR type methods10.1142/s1793962321500574 ↗
12. The Direct simulation Monte Carlo method10.1063/1.168619 ↗
13. Direct Simulation Monte Carlo investigation of fluid characteristics and gas transport in porous microchannels10.1038/s41598-019-52707-3 ↗
14. Direct Simulation Monte Carlo for astrophysical flows – I. Motivation and methodology10.1093/mnras/stt2406 ↗
15. Direct simulation Monte Carlo: Novel application and new extensions
16. Direct simulation Monte Carlo for new regimes in aggregation-fragmentation kinetics10.1016/j.jcp.2022.111439 ↗
17. J. L. Pacheco , Z.Eckert, R.Hooper, M.Finley, and R. P.Manginell, “A novel use of Direct simulation Monte-Carlo to model dynamics of COVID-19 pandemic spread,” Report No. SAND2020-8172, Sandia National Laboratories, Albuquerque, New Mexico, 2020.10.2172/1648851 ↗
18. Classical dynamical density functional theory: From fundamentals to applications10.1080/00018732.2020.1854965 ↗
19. Effects of social distancing and isolation on epidemic spreading modeled via dynamical density functional theory10.1038/s41467-020-19024-0 ↗
20. Modeling epidemics by the lattice Boltzmann method10.1103/physreve.102.023301 ↗
21. Individual-based lattice model for spatial spread of epidemics10.1155/s1026022601000206 ↗
22. 2004
23. Modeling the evolution of COVID-19 via compartmental and particle-based approaches: Application to the Cyprus case10.1371/journal.pone.0250709 ↗
24. Simulation of pandemics in real cities: Enhanced and accurate digital laboratories10.1098/rspa.2020.0653 ↗
25. Scaling of the propagation of epidemics in a system of mobile agents10.1016/j.physa.2004.05.017 ↗
26. A particle-based COVID-19 simulator with contact tracing and testing10.1109/ojemb.2021.3064506 ↗
27. Epidemic thresholds and vaccination in a lattice model of disease spread10.1006/tpbi.1997.1323 ↗
28. Particle velocity controls phase transitions in contagion dynamics10.1038/s41598-019-42871-x ↗
29. Modelling SIR-type epidemics by ODEs, PDEs, difference equations and cellular automata – a comparative study10.1016/j.simpat.2008.05.015 ↗
30. Multi-agent system collision model to predict the transmission of seasonal influenza in Tokyo from 2014–2015 to 2018–2019 seasons10.1016/j.heliyon.2021.e07859 ↗
31. Reactive multiparticle collision dynamics10.1016/j.cpc.2008.01.027 ↗
32. Mesoscopic model for diffusion-influenced reaction dynamics10.1063/1.1690244 ↗
33. Active motion of synthetic nanomotors in filament networks10.1103/physrevresearch.2.033245 ↗
34. Stochastic simulations of the Schnakenberg model with spatial inhomogeneities using reactive multiparticle collision dynamics10.3934/math.2019.6.1805 ↗
35. A hybrid method for micro-mesoscopic stochastic simulation of reaction-diffusion systems10.1016/j.mbs.2019.04.001 ↗
36. Pair interaction of catalytical sphere dimers in chemically active media10.3390/mi9010035 ↗
37. Mesoscopic model for solvent dynamics10.1063/1.478857 ↗
38. Hydrodynamic fluctuations in thermostatted multiparticle collision dynamics10.1103/physreve.83.046708 ↗
39. The Maxwell-Boltzmann distribution