COVID-19 Exposure Probability and Mortality Rate Calculator

Our Website

Introduction

With our AI algorithm utilizing neural networks and full-scale simulation runs, you can analyze your risk of contracting COVID-19 if someone in your class was infected. We will be able to calculate a realistic chance of you contracting COVID-19 depending on risk factors such as class size and exposure time. Along with this comes a mortality rate calculator based on aspects such as race, gender, location, and age. This will assist with the safety protocols of in-person learning and will produce a better learning environment for all students.

Inspiration

Ever since the COVID-19 outbreak, many parents have been reluctant to send their children to school, especially due to concerns that students will spread the virus to more susceptible people. Contact tracing often requires invasive methods that many, in a modern age where personal privacy is dwindling, are beginning to shun. Students themselves may fear the uncertainty that is accompanied by the symptomless spread of COVID-19. When COVID-19 cases are identified, contact tracing, especially when specific to the school & classroom environment, is often unsuccessful.

What it does

Our program involves an AI algorithm utilizing neural networks & full-scale simulation runs. It can analyze your risk of contracting COVID-19 if someone in your class was infected. It is able to calculate a realistic chance of you contracting COVID-19 depending on risk factors such as class size, time since exposure, etc. It will assist with safety protocols of in-person learning & will produce a better learning environment for all students. Our website also features a program to utilize already present data & calculate one’s mortality rate, which can analyze one's risk of dying from COVID-19 if contracted. It is able to calculate a realistic preview of such a statistic depending on risk factors such as age, gender, ethnicity, location and will thus inform susceptible individuals to take health precautions.

How we built it

We decided to create a website to house our product with HTML frontend & Python backend. We used XML Javascript requests to call Python program given user inputs, successfully integrating all elements. Our website was styled & designed using CSS to create an aesthetically pleasing frontend. Furthermore, our Neural Network was greatly facilitated by Numpy module, a commonly used module that has many useful functions for matrices, which are used in neural networks. Python also orks well with Heroku, the server on which we are hosting our website.

What's next for COVID-19 Exposure Probability and Mortality Rate Calculator

Our project can be improved through connection to the Google Classroom API. We attempted to use OAuth 2.0 authentication to provide access to classroom rosters but were unable to successfully do so. Using rosters to pick specific class shuffling that better accurately targets community spread is an improvement that will allow us to predict superspreader events and community spread in a classroom environment. Furthermore, it will better suit the method of learning in the digital age.