Hstepanalytics - Space Apps Challenge

Hstepanalytics| 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 Factors

Summary

For identification the tendencies of CODIVE-19 spread and the main principle of its containment we collected data and used Data Science and Machine learning to find solutions and draft the proposals to restrict the disease.Was used the below table of content:Data LoadingExploration of available dataVisualization of dependencies between variables(EU countries and characterizing them parameters)Intermediate findingsPre-processingSVM modellingGridSearchCVConclusion

How We Addressed This Challenge

We used the data collected and elaborated from 11 resources mentioned below. Afterward, we built a model to analyze which country has the tendency to overcome the consequence of CORONA-19 thanks to strict lockdown. What factors influence the spread of illness. What information could be required for future analysis.

How We Developed This Project

CODIVE-19 is one of the dangerous disasters that happened to humanity in this century and an obligation of every conscious member of society to help humanity cope with it. We used the maps indication NO2 before and after lockdown to analyze how different European countries kept the quarantine and find a correlation with case dynamics in different countries. Also, we reviewed multiple links of NASA and other space agencies to find info applicable to our project. I used the elements of Data Science and Machine Learning for these purposes. Mtoore information about usage applications is highly appreciated. Also, we applied the received info for analysis and defirenciated situation in North and South Europe thanks to it.