CBL - Campus del Baix Llobregat

Projecte llegit

Títol: Anàlisi dels efectes epidemiològics de la interacció entre virus respiratoris

Estudiant que ha llegit aquest projecte:

Tutor/Cotutor: LOPEZ CODINA, DANIEL

Departament: FIS

Títol: Anàlisi dels efectes epidemiològics de la interacció entre virus respiratoris

Data inici oferta: 15-12-2021      Data finalització oferta: 15-07-2022

Estudis d'assignació del projecte:
    GR ENG SIS BIOLÒGICS

Lloc de realització:
EEABB

Segon tutor (UPC): PERRAMON MALAVEZ, AIDA

Paraules clau:
epidemiologia, models matemàtics, virus, SARS-CoV2, grip, VRS

Descripció del contingut i pla d'activitats:
1. Recerca bibliogràfica sobre la interacció entre virus respiratoris
2. Recerca bibliogràfica sobre models matemàtics de la interacció entre virus
3. Disseny i implementació de models matemàtics
4. Anàlisi de dades epidemiològiques

Overview (resum en anglès):
Viral coinfection presented in humans has important value in clinical and epidemiological studies. The relationship between viruses determines the consequences of viral coinfection. These consequences could be inhibition of viral growth, increased viral load, or even more severe symptoms in the patient. This work aims to understand the relationship between different viruses and the dynamics of their viral load during coinfection. In this way, it is hoped to be able to make an accurate prediction of the evolution of coinfection between respiratory viruses and, therefore, improve the protocol for the prevention of infectious respiratory diseases.
On the other hand, mathematical and computational models are efficient in understanding the dynamics of viruses and predicting the trends of an epidemic. This has also been demonstrated during the SARS-CoV-2 pandemic. Therefore, in this work, a series of mathematical models are developed to study the relationship between viruses under coinfection and to understand how the infection changes in the presence of other pathogens. In addition, the results are expected to be useful for taking measures to control a pandemic or epidemic similar to those experienced in the future.
This study focuses on 4 respiratory viruses: SARS-CoV-2, respiratory syncytial virus (RSV), influenza (IV), and human metapneumovirus (hMPV). The models generated in this work are derived from the Pinky and Dobrovoly1 coinfection model, which evaluates the evolution of viral load during coinfection. Viral load is an important variable that indicates what kind of interaction viruses establish: the interaction is positive when the presence of one virus increases the viral load of another virus over time, otherwise the interaction is negative. And when the viral load does not vary in coinfection, this interaction is neutral.
The mathematical models developed in this work not only fit well with the experimental data of coinfection but also with those of simple infection. Apart from that, we have studied different scenarios. On the one hand, we have made a model to understand the effect of one virus on the delayed infection with another. Also, the initial viral load has been increased to assess its relationship with the inhibitory effect. Finally, we investigated viral evolution with continuous cell introduction, adding a recruitment parameter to the model.

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