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Projecte llegit

Títol: Desenvolupament de models matemàtics tipus SEIR per estudiar les epidèmies de grip a Catalunya

Estudiant que ha llegit aquest projecte:

Tutor/Cotutor: LOPEZ CODINA, DANIEL

Departament: FIS

Títol: Desenvolupament de models matemàtics tipus SEIR per estudiar les epidèmies de grip a Catalunya

Data inici oferta: 20-07-2021      Data finalització oferta: 20-03-2022

Estudis d'assignació del projecte:
    GR ENG SIS BIOLÒGICS

Lloc de realització:

UPC      Departament/centre: Departament de Física

Segon tutor (UPC): PERRAMON MALAVEZ, AIDA

Paraules clau:
grip, models de compartiments, meteorologia

Descripció del contingut i pla d'activitats:
El treball pretén avançar en el desenvolupament d'eines per preveure l'inici d'epidèmies de malalties infeccioses. Per fer-ho es seguiran les següents etapes:
1) Revisió de models matemàtics epidemiològics de grip i de bronquiolitis causada pel virus de resistència sincitial.
2) Implementació dels models seleccionats en un programa de simulació.
3) Parametrització dels models amb dades epidemiològiques catalanes.
4) Discussió d'estratègies per donar utilitat als models implementats.

Overview (resum en anglès):
The flu is a contagious respiratory infectious disease caused by the influenza viruses. Annually in Catalonia there is a flu season within the months of autumn and winter, that can create a lot of stress to the healthcare system. The main goal of this study is to understand the dynamics of the flu and to be able to make predictions that allow anticipation, with enough time to respond to an increase of infected individuals that requires active action from the healthcare system managers.
Computational and mathematical models are a powerful tool that help understand and predict systems behaviours. In this study different models are adapted, developed and implemented to achieve the pursued objective.
Therefore, the interaction between meteorological factors and the flu seasonality and transmissivity has been studied, due to the known effects of these factors upon biological systems.
The mathematical models developed in this study fit correctly the epidemiological data, they allow the explanation of flu seasonality and perform predictions at short and long term. The base model that has been used proved to be a good fit to the previous seasons and has been applied to produce weakly reports of flu evolution this season 2021-2022. From the base model new models have been created, these include meteorological factors and have been called meteomodels. They have revealed the effect of temperature and absolute humidity upon the epidemic behavior of the flu. This is one of the main results of this study, there is no knowledge of any other published model that describes flu epidemics through meteorological factors as the models in this study do, with the added value that these meteorological models have the potential to predict two weeks ahead.
To sum up, predictive mathematical models have been developed, each one with a precision above 95%, for the flu epidemic in Catalonia and incorporating, for the first time, meteorological factors. Further work includes new and different combinations of meteorological factors, the incorporation of social factors, effects of viral interference and statistical analyses to determine the probable load of infected individuals for each center of primary attention in Catalonia.

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