Inspiration
Nobody is really sure how to best act in the fight against Covid19. To know which measures can most effectively reduce the spread of the virus would be extremely helpful. By now the virus is with us for a long time already and a lot of countries have taken different measures that influenced the spread. Our mission in this hackatum was to find out which measures worked how well.
What we did
Using data analysis techniques we extracted different findings that put in relation different measures to their effect. This could be used as a general guideline for deciding on which measures to take and which ones to drop.
How we built it
We used the following dataset for information about which country took which measures: Furthermore we took data about daily new Corona cases in all countries from the WHO website: We applied data analysis techniques to extract measure effects using the change in the new cases number from all countries where a specific measure was applied.
Challenges we ran into
The biggest challenge was to deal with noisy and incomplete data. As the crisis is still proceeding some effects could not yet show their full impact. Additionally the reporting of measures varies sometimes massively from country to country.
Accomplishments that we're proud of
We feel like we extracted some useful information.
What we learned
Even in a short amount of time, with relatively limited data and comparably simple techniques it is possible to distill way more information from given data than you can see by just looking at the raw numbers.
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