Mindblockers| Human Factors

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?

Human movement in the transmission of covid-19

Summary

How does the virus spread so fast?And how do we cant to prevent the propagation again?The answer lies in accurately identifying typical patterns between human activity and the possible spread of covid 19.We carefully analyzed relevant free to obtain data from the NASA Agency and other agencies at our proper disposal on the pandemic. The impact of human movement is significant for the spread of the virus.

How We Addressed This Challenge

Considering human movement, which represents a key pattern of natural activity and its relationship to the spread of COVID-19, statistical models and patterns of people's mobility when using certain means of transport are used to determine precisely the speed of the possible spread and the possible impact it has on major cities with high population density and the profound effect on the environment.

That is why we analyse the available information we have with the aim of providing ideas to avoid possible outbreaks or to control future pandemics.

How We Developed This Project

We chose this challenge because we believe in the important role of computer models in simulating infectious processes that affect humanity, as well as the analysis they allow to be made using the available data.

Our approach is that today we must use the tools we have at our disposal together with the knowledge we have to obtain patterns of this disease and be able to give a viable solution to avoid possible infections or future pandemics.

We have used the data from the space agency to see temporarily how this virus has been affecting the world's population, and how through analysis and visualization of satellite images, we have managed to obtain a series of patterns and conclusions to provide.

For the development of the project we have used Python as a language, Jupyter and Pandas for data analysis, Github for version control of the developed code and information storage and AWS for the deployment and visualization of our solution.

With respect to the problems, the most difficult thing has been to find publicly available data on transports, and nitrogen dioxide in raw format, not by means of images so that they can be analyzed in greater depth.

And the achievements we have made have been: communicating as a team from a distance and without knowing each other, having well combined the tasks and having developed a good project.

Tags
#human #factors #environment #density #population #transport #socialnetworks #data #analysis #NASA
Global Judging
This project was submitted for consideration during the Space Apps Global Judging process.