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?

Delayed Spike Reponse in Covid Cases After Intital Lockdown

Summary

The data used for our project originates from Google and Apple sources. We mapped the population mobility throughout the period where COVID-19 first spread in the U.S. Our plots show that there was an exponential growth in COVID-19 carriers in the states of New York and New Jersey. From the trend depicted in the two Positive COVID-19 Case graphs, the exponential growth only started when the lockdown started on March 15. Even though the average percentage of mobility has dropped, the trend grew e

How We Addressed This Challenge

Capture human mobility data and analyze geospatial correlation between Covid 19 cases and movement of general population. 

How We Developed This Project

Human movement and transportation is a key factor In human civilization. With the growing globalization and increasing transportation efficiency the rapid movement of people plays a key role in the exponential spread of disease, such as in the case of Covid 19. Our team seeks to explore the growth of the virus in some of the most densely populated regions in the United States and effectively displaying the growth of the virus in such regions. We were able to use Chart.js for displaying the data, Python backend to scrap raw data and find trends and important features pertaining to the data, and flask to package the project. 

Project Demo

https://docs.google.com/presentation/d/1lu4j9ou4xROjK7lHPvYLfOBpuFRXpeYbO6z_AU9HB9E/edit?usp=sharing

Data & Resources

Google/Apple Mobility Data :   State by State basis, updated daily

John Hopkins Covid Data  : Country wide and State wide, updated daily

Tags
#lockdown #pandemic #growth
Global Judging
This project was submitted for consideration during the Space Apps Global Judging process.