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Diferencialne enačbe 1. reda in modeliranje epidemije : magistrsko delo
ID Dimic, Anton (Author), ID Slapar, Marko (Mentor) More about this mentor... This link opens in a new window

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Abstract
V magistrskem delu je obravnavano matematično modeliranje širjenja nalezljivih bolezni z uporabo sistemov linearnih diferencialnih enačb prvega reda. Predstavljena je analiza osnovnega modela SIR, ki opisuje dinamiko prehoda posameznikov med razredi dovzetnih, okuženih in prebolelih v populaciji. Model je razširjen z uvedbo cepljenja, kar omogoča analizo vpliva različnih strategij cepljenja na zajezitev širjenja bolezni. Poleg tega je razširitev modela prilagojena za obravnavo več variant patogena, kar omogoča bolj kompleksno analizo epidemijskih scenarijev. Uporabljene so numerične metode za simulacijo modelov, ki omogočajo raziskovanje vpliva ključnih parametrov, kot so učinkovitost cepljenja, stopnja prenosa in precepljenost populacije. Cilj magistrskega dela je razviti matematično orodje, ki služi kot podpora pri načrtovanju strategij za obvladovanje epidemij.

Language:Slovenian
Keywords:Matematika, Diferencialne enačbe, diferencialne enačbe prvega reda, model Sir, modeliranje epidemije, razširitev osnovnega modela SIR
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:PEF - Faculty of Education
Place of publishing:Ljubljana
Publisher:A. Dimic
Year:2025
Number of pages:38 str.
PID:20.500.12556/RUL-170463 This link opens in a new window
UDC:517.91(043.2)
COBISS.SI-ID:246401283 This link opens in a new window
Publication date in RUL:06.07.2025
Views:217
Downloads:30
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Secondary language

Language:English
Title:First-order differential equations and epidemic modelling
Abstract:
In this master thesis, mathematical modeling of the spread of infectious diseases is addressed using systems of first-order linear differential equations. The thesis presents an analysis of the basic SIR model, which describes the dynamics of transitions between susceptible, infected, and recovered individuals within a population. The model is extended by incorporating vaccination, allowing for the analysis of the impact of different vaccination strategies on disease containment. Furthermore, the model is adapted to include multiple pathogen variants, enabling a more comprehensive examination of epidemic scenarios. Numerical methods are applied to simulate the models, facilitating the exploration of key parameters such as vaccine efficacy, transmission rate, and vaccination coverage. The objective of this master thesis is to develop a mathematical tool that supports the planning of strategies for epidemic management.

Keywords:First-order differential equations, model SIR, epidemic modeling, extension of the basic model SIR

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