A New Dynamic Model to Predict the Effects of Governmental Decisions on the Progress of the CoViD-19 Epidemic
Kamran Soltani (1), Ghader Rezazadeh (1, 2) ((1) Mechanical, Engineering Department, Urmia, Iran, (2) South Ural State University,, Chelyabinsk, Russian Federation)

TL;DR
This paper introduces a comprehensive dynamic mathematical model for COVID-19 that incorporates various transmission factors and government policies, validated with data from Iran and Italy, highlighting the impact of measures and healthcare capacity on epidemic progression.
Contribution
The paper presents a novel compartmental model with eight sub-populations and step-function coefficients, enhancing accuracy and flexibility in predicting COVID-19 epidemic dynamics.
Findings
Reopening plans significantly influence active case numbers.
Small population releases can trigger multiple waves.
Healthcare capacity impacts epidemic severity.
Abstract
We have established a novel mathematical model that considers various aspects of the spreading of the virus, including, the transmission based on being in the latent period, environment to human transmission, governmental decisions, and control measures. To accomplish this, a compartmental model with eight batches (sub-population groups) has been proposed and the simulation of the set of differential equations has been conducted to show the effects of the various involved parameters. Also, to achieve more accurate results and closer to reality, the coefficients of a system of differential equations containing transmission rates, death rates, recovery rates and etc. have been proposed by some new step-functions viewpoint. Results: First of all, the efficiency of the proposed model has been shown for Iran and Italy, which completely denoted the flexibility of our model for predicting the…
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Taxonomy
TopicsCOVID-19 epidemiological studies · Mathematical and Theoretical Epidemiology and Ecology Models
