Abstract
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.
Highlights
The COVID-19 pandemic is a new disease and there is as yet not enough understanding on its future evolution
Our objective is to derive a model that is suitable for countries like Cyprus, where data typically used for modeling COVID-19, such as of hospitalizations, intubation, and deaths, are too small for a meaningful data-driven analysis
This study demonstrates the ability of these models to capture features of the pandemic, such as the infection rate, when relatively small numbers of cases are involved and for which statistical models yield results with very large uncertainties
Summary
The COVID-19 pandemic is a new disease and there is as yet not enough understanding on its future evolution. Since medical interventions, such as vaccines or antiviral treatments, are not available yet, non-medical interventions are being implemented to contain the disease. In a number of countries, including Cyprus, the imposed restrictions have helped slow down the spread of the disease. Cyprus, being an island country, managed to limit the spread of the disease, by imposing restrictions on air travel and shutting down large parts of the economy, achieving 2.2 deaths per 100,000 population, a death rate comparable to that of Greece and Malta [1, 2]. Reliable predictions will help policy-makers to formulate appropriate intervention strategies, while taking into account economic and social factors
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