29. A two diffusions stochastic model for epidemic of the SARS-CoV-2 virus
Invited abstract in session TB-4: Modeling, Simulation and Optimization, stream Large scale optimization and applications.
Thursday, 10:00 - 11:30Room: C105
Authors (first author is the speaker)
| 1. | Ivan Papić
|
| School of Applied Mathematics and Informatics, J. J. Strossmayer University of Osijek | |
| 2. | Nenad Šuvak
|
| School of Applied Mathematics and Informatics, J.J. Strossmayer University of Osijek | |
| 3. | Jasmina Đorđević
|
| FACULTY OF SCIENCES AND MATHEMATICS, UNIVERSITY OF NIŠ |
Abstract
A refined version of the classical SEIR (susceptible-exposed-infected-recovered) model for the epidemic of the SARS-CoV-2 virus is proposed. The compartment of infected individuals is divided into four disjoint classes: symptomatic infected individuals (I), superspreaders (P), hospitalized infected individuals (H) and asymptomatic infected individuals (A). The model differentiates the spread of the virus via regular infected individuals and via superspreaders. This assumes two transmission coefficients each representing the spread via (normal) infected individuals and superspreaders. The model is defined through system of stochastic differential equations describing the dynamics of
epidemic, where uncertainty in the model is explained through perturbation of transmission coefficients of standard spreaders and superspreaders via two independent Brownian motions with different volatility. The results include proof of existence and uniqueness of the positive global solution of the corresponding system of SDEs as well as the conditions for the extinction of the virus and its persistence in population (persistence in mean). Theoretical results are illustrated via simulations, where the parameters of the model are adjusted based on the data from the early phase of the epidemic in Wuhan (January 4 to March 9, 2020).
Keywords
- Optimization under uncertainty and applications
Status: accepted
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