We used available epidemiologic data such as infection rates, mobility, and transportation data as factors in developing our map indicating the level of seriousness of people in different countries which promotes the understanding and the generating of new insights regarding the effects of COVID-19.
Our project is a demonstration of how we could use available earth data in developing a new tool that inspires, teaches, and makes us reflect on the ways countries are dealing with the pandemic. Do their methods have a positive or negative impact on the numbers of cases and containing the situation? giving a chance for any person to better deal with it through learning from the policies and the behaviors of people from countries on the better side of the scale.
Our inspiration for choosing this challenge was that it aims for enhancing the impacts of Covid-19, a motive that made us develop a new tool through interpreting available data. We wanted to develop a tool that gathers and analyzes socio-economic and epidemiologic data into something new and useful which could become a way for people to observe how different parameters affect everything related to Covid-19 and how they could become more serious in dealing with it.
The data we used in our project includes Nasa datasets for NO2 cloud-screened from which we calculated the difference of NO2 emissions defined when the number of daily growth cases is more than 0.0012% of the population giving us the ability to estimate the ratio of number of vehicles in different countries which partially reflects the amount of people going out despite of the restrictions and lockdown policies. We also used the Google Trending API to factor terms that are searched and posted as an expression of disbelief regarding coronavirus such as “Corona is a scam” and others showing signs of not taking the subject seriously. We used another covid-19 API to factor the growth rate of the number of cases and deaths due to covid-19 around the world as it’s an indicator that provides evidence for the seriousness of the people.
We used python in developing this tool and many softwares: visual studio, visual studio code, notepad, scipy stack, paint.net, Xarray, pandas numpy and we used flask for developing the website.
The major problem that we encountered is not having access to a lot of global data concerning other parameters (e. g PPE sales ) that could have resulted in more accurate information and insights.
We have successfully managed to develop a website that shows the ranking of each country according to the chosen parameters.
https://youtu.be/4qB9LtFq3hk