As math students, we wanted to apply the knowledge we had acquired so far in helping others understand the spread of a virus better. Particularly, on how effective government measures such as confinement or testing are.
Indeed, faced with a general lack of awareness from the public and an abundance of fake news, we aim to provide a practical and fun tool to inform.

What it does

Our goal is to present data in a pedagogical way, making it as interactive and appealing as possible. Currently lacking the necessary data for specific COVID19 virus simulations, we studied different epidemics models hoping it would give insight into the more specific case of COVID19.

How we built it

We used different mathematical models to simulate the virus spread using Matlab. Then we displayed the datasets in JavaScript interactive graphs, allowing the user to modify certain parameters, compare the different outcomes and get a better overall understanding.

Challenges we ran into

The first challenge we ran into was finding mathematical models for an epidemic with explicit or easily approximable solutions. There are models that may have been more representative or that deal with different interesting aspects of the spread: the existence of a vaccine or a non constant population size where we could see the deadliness of a virus, for example. But we were faced with systems of nonlinear differential equations and we do not currently have enough mathematical knowledge to solve them.

Once we had chosen our model, another difficulty we ran into was finding realistic parameter values to represent the spread. Furthermore, since our simulations on MATLAB already took a long time to run for a total population of a million, it wouldn't be optimal to represented a worldwide pandemic.

Last of all, we learned the basics of javascript, HTML5/CSS in just three days and managed to get the wanted results.

Accomplishments that we're proud of

We are proud of ourselves for being able to implement all we set out to do for this project: the simulations on Matlab, interactivity using JavaScript and the web page. We are also very happy we managed to make our website interactive, since our main goal was to make the visualisation of pandemic spreads easy to understand for people from all different backgrounds.

It was a really good project to have and even though the SIR and SIS models used here simplified an actual spread, it was a good first approach.We were able to apply concepts we'd learnt in class so far, in particular we used the Galton-Watson process to model our generations of infection spread.

What we learned

First of all, we now have a better understanding on pandemics spread and how to model them. We also familiarized ourselves with different simulation models, even though only three were implemented, and did a lot of reading and research that could be applied to future projects. And once again, we also added to our skillsets the basics of javascript, HTML5/CSS.

What's next for PandemicAnalytics

Since our models simplified reality a lot, we would like to improve it by taking into consideration more parameters and larger scales. We would also like to improve the website interface.

Share this project: