This project aims to simulate the spread of an infectious disease such as Covid-19, caused by the SARS-CoV2 virus. This is done by means of the SIRD (Susceptible Infected Recovered Deceased) epidemiological model. People are represented by sites in a lattice, and the virus is allowed to transmit from infected to susceptible individuals. See the presentation slides in Presentation.pdf for more information.
- Nearest neighbours get infected with a certain probability.
- Infected people get healed after a recovery period.
- Mobility models people moving around and having more conmtacts and spreading of the virus beyond the nearest neighbours.
- The healthcare capacity is limited and when the current active cases are beyond the healthcare capacity, the risk of passing away increases without proper care.
- Imposing and lifting lockdowns based on respective thresholds for currrent active cases. Premature lifting of thresholds causes subsequent secondary waves of infections.
- Vaccination of the population starts after certain number of days that it takes to develop a vaccine.
library.py: Code that simulates SIRD model and its extensions on a 2D lattice.config.py: Contains global default hyperparameters that can be overwritten if needed.main.py: Serves as a template to obtain data and plots for various parameter regimes.plots.py: Allows the creation of GIF files, if one first saves the necessary plots.journal.md: Contains our progress throughout the duration of the project.
- Python 3
- numpy
- scipy
- matplotlib
- random
- Smit Chaudhary
- Ignacio Fernández Graña
- Georgios Sotiropoulos