Human Factors

The emergence and spread of infectious diseases, like COVID-19, are on the rise. Can you identify patterns between population density and COVID-19 cases and identify factors that could help predict hotspots of disease spread?

COVID19 spreading prediction by SolveIT!

Summary

This project can be developed and the prediction can be more exact if there will be used special upgrades in public transports.

How We Addressed This Challenge

These days the spreading of COVID19 is the biggest problem of modern society. Our group has created an app that will help to predict the COVID19 spreading through public transportation and decrease the number of infection cases.

How We Developed This Project

We were inspired by the idea of developing public transportations because they are the most common and popular way of traveling and we aimed to solve the problems that are connected by safety and COVID19. We created an app that allows us to predict the chance of being infected through a bus traveling by the number of people, days and bus cleaning. We used the C# to make a code to this project and the average number of people who use the bus from official info from the app "2GIS".So, we have created the math model of number growth of Covid-19  infected. That model is Y(x)= 1+1,25*x*n +x*m . So, Y is a number of infected people, x- time, n - the average number of people, who are in the bus, m - number of busses.

Project Demo

So, we have created the math model of number growth of Covid-19  infected. That model is Y(x)= 1+1,25*x*n +x*m . So, Y is a number of infected people, x- time, n - the average number of people, who are in the bus, m - number of busses

Data & Resources

https://habr.com/ru/post/338992/

https://en.wikipedia.org/wiki/Malthusian_growth_model

https://en.wikipedia.org/wiki/Mathematical_model

Tags
#bus#publictransport#transportation#COVID19
Global Judging
This project was submitted for consideration during the Space Apps Global Judging process.