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Identifier 000442828
Title Analysis and computational study of SIR-Type epidemiological models for the Covid-19 pandemic
Alternative Title Ανάλυση και υπολογιστική μελέτη επιδημιολογικών μοντέλων τύπου SIR για την πανδημία covid-19
Author Κλάγκου, Ευριδίκη
Thesis advisor Πλεξουσάκης, Μιχαήλ
Reviewer Λύκα, Κωνσταντία
Μακράκης, Γεώργιος
Abstract Epidemic outbreaks have been a major concern in public health throughout history. However from the 14th century till now there have been a lot of discoveries about them. Especially when mathematical methods were introduced to statistically support the data. In late 2019 SARS-CoV-2 virus, or Covid-19 started spreading around the world. Soon after the number of symptomatically infected and severely ill individuals overwhelmed the medical system in many countries. It also lead to more than 4 million deaths by July 2020. This pandemic also had severe consequences in the global economy due to disruption in manufacturing and services, income reductions and rize of unemployment. Public health officials use epidemiological models for disease surveilance and the investigation of outbreaks, along with observational studies, in order to identify risk factors and implement disease control measures. Although data are almost always available from occuring epidemics, they are often incomplete due to underreporting. In particluar, for the Covid-19 epidemic there is mounting evidence that some of the rapid spread of this virus has been driven by asymptomatic infections. Due to this lack of reliable data mathematical modeling and computer simulations have been used to perform theoretical experiments to estimate the parameters of the transmission mechanism and the spread of the disease. Moreover, such experiments may be useful in comparing the effects of preventive measures, such as social distancing or quarantine. A well known epidemical model is the SIR model, as it gives results that are similar with the real data. The aim of this thesis is the analytical and computational study of an extended SIR model which includes the class of asymptomatic individuals and compare its predictions with real Covid-19 data from Greece and elsewhere.
Language English, Greek
Issue date 2021-11-26
Collection   School/Department--School of Sciences and Engineering--Department of Mathematics and Applied Mathematics--Post-graduate theses
  Type of Work--Post-graduate theses
Permanent Link https://elocus.lib.uoc.gr//dlib/6/0/1/metadata-dlib-1634117491-696763-23760.tkl Bookmark and Share
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