Propensity Matrix Method for Age Dependent Stochastic Infectious Disease Models

Mathematical modeling is one of the key factors of the effective control of newly found infectious diseases, such as COVID-19. Our knowledge about the parameters and the course of the infection is highly limited in the beginning of the epidemic, hence computer implementation of the models have to be...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Boldog Péter Tamás
Bogya Norbert
Vizi Zsolt
Dokumentumtípus: Könyv része
Megjelent: Springer International Publishing Cham 2022
Sorozat:Trends in Biomathematics: Stability and Oscillations in Environmental, Social, and Biological Models
Tárgyszavak:
doi:10.1007/978-3-031-12515-7_17

mtmt:33553275
Online Access:http://publicatio.bibl.u-szeged.hu/37707
Leíró adatok
Tartalmi kivonat:Mathematical modeling is one of the key factors of the effective control of newly found infectious diseases, such as COVID-19. Our knowledge about the parameters and the course of the infection is highly limited in the beginning of the epidemic, hence computer implementation of the models have to be quick and flexible. The propensity matrix method we discuss in this paper serves as a convenient approach to implement age structured stochastic epidemic models. The code base we implemented for our forecasting work is also included in the attached GitHub repository (Vizi, GitHub repository (2021). https://github.com/zsvizi/propensity-matrix-epidemics).
Terjedelem/Fizikai jellemzők:15
311-325
ISBN:3031125142; 9783031125140; 9783031125157