Modelling approaches for epidemiological models
Malakhovskaia, Veronika (2017)
Diplomityö
2017
Julkaisun pysyvä osoite on
http://urn.fi/URN:NBN:fi-fe201707257786
http://urn.fi/URN:NBN:fi-fe201707257786
Tiivistelmä
Predicting the spread of diseases remains an important aspect of epidemiological problems. For these purposes, such areas as statistics, sociology, and biology are used. Nowadays, there is a large number of approaches for modelling epidemiological problems using compartmental models.
The aim of this paper is to obtain solutions for a mathematical model of dynamics of an influenza epidemic using various methods and compare them to identify the optimal method for solving this problem. A number of the algorithms such as Markov Chain Monte Carlo method (MCMC) for the deterministic modelling and Gillespie algorithm and a discrete approach for the agent-based modelling (ABM) were implemented with Matlab, a numerical computing environment. The data for implementing the algorithms is taken from the case of the influenza epidemic in British Boarding School in 1978.
The aim of this paper is to obtain solutions for a mathematical model of dynamics of an influenza epidemic using various methods and compare them to identify the optimal method for solving this problem. A number of the algorithms such as Markov Chain Monte Carlo method (MCMC) for the deterministic modelling and Gillespie algorithm and a discrete approach for the agent-based modelling (ABM) were implemented with Matlab, a numerical computing environment. The data for implementing the algorithms is taken from the case of the influenza epidemic in British Boarding School in 1978.