Hospitals have a hard time to adapt their resource planning along the patient predictions. Historical experience is of little value. Calculation tools are missing and that's why we tried to develop one.
What it does
Our program simulates the spreading of the coronavirus for a given region or country. The past spreading can be extended to a prediction that would help hospitals planning their necessary resources and the effectiveness of a given measure (for example social distancing) could also be observed in our simulation. The simulation takes into account various parameters such as susceptibility of a given person, the number of beds available, the resources (medical staff, material, medicine) available in hospitals, the incubation time, the different stages of the disease,...
How I built it
The main program is written on Python, based on our own algorithm inspired by existing propagation (SIR) models. The model was then adapted to covid-19 and Switzerland based on the data found in various studies.
Challenges I ran into
Finding enough data on the covid-19 was not easy as the disease hasn't been around for a long time.
What I learned
We learned how to simulate the propagation of a disease, find and gather the relevant data.
What's next for Hospital resources simulation
Our simulation could now be improved and adapted to be used in other countries and regions or for different contagious diseases.