Resources

Some codes and notes that may be useful to others.

Coding

C

COVID-19 modelling: code for the baseline scenario from the paper Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19 and Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas.
SIR model on a network with Gillespie algorithm: quick and dirty code to perform simulations of the SIR model on a network using Gillespie algorithm. Use at your own risk!

R

ggplot2 scripts: R scripts used to make the plots of my Thesis. Check out the examples!

Python

Hospitalization dynamics: code used in the paper Unraveling the COVID-19 hospitalization dynamics in Spain using Bayesian inference

Data

Hospital networks: networks used in the paper Assessing the risk of spatial spreading of diseases in hospitals

Lecture notes

[In Spanish] Los malditos punteros: apuntes del curso de Física Computacional 2018/2019 de la Universidad de Zaragoza sobre el funcionamiento de los punteros en C.

Thesis

Here you can find my Thesis in bookdown format:
- If you are interested in the link between physics and networks, check out Chapters 1 and 2.
- In Chapter 3 I gave a brief overview of the history of epidemic modeling. It might be useful to introduce new students to this world.
- The last chapter contains my boldest works, Pokémon and Forocoches!