Open AccessModeling the evolution of COVID-19 via compartmental and particle-based approaches: Application to the Cyprus case
Author(s) -
Constantia Alexandrou,
Vagelis Harmandaris,
Anastasios Irakleous,
Giannis Koutsou,
Nikos Savva
Publication year - 2021
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0250709
Subject(s) - covid-19 , ordinary differential equation , population , pandemic , set (abstract data type) , epidemic model , particle (ecology) , statistical physics , statistics , infectious disease (medical specialty) , mathematics , econometrics , computer science , differential equation , biology , physics , virology , outbreak , demography , ecology , disease , medicine , mathematical analysis , pathology , programming language , sociology
We present two different approaches for modeling the spread of the COVID-19 pandemic. Both approaches are based on the population classes susceptible, exposed, infectious, quarantined, and recovered and allow for an arbitrary number of subgroups with different infection rates and different levels of testing. The first model is derived from a set of ordinary differential equations that incorporates the rates at which population transitions take place among classes. The other is a particle model, which is a specific case of crowd simulation model, in which the disease is transmitted through particle collisions and infection rates are varied by adjusting the particle velocities. The parameters of these two models are tuned using information on COVID-19 from the literature and country-specific data, including the effect of restrictions as they were imposed and lifted. We demonstrate the applicability of both models using data from Cyprus, for which we find that both models yield very similar results, giving confidence in the predictions.