This simple project demonstrates the utility of data science. I chose personally to study the evolution of the Ebola outbreak that has been occurring in the north-east of the DRC since August 2018.
Unfortunately many people have lost their lives. I really encourage all those who are willing to provide their efforts day and night to stop this outbreak. And for all those who want to know whether or not the danger is growing up, this can be your quick reference.
Thanks to Dr. Oly Ilunga Kalenga, ex DRC's Minister of Health, for making available the data of this outbreak. The data I'm using here comes from this website https://data.humdata.org/dataset/ebola-cases-and-deaths-drc-north-kivu and the sources are added daily on https://mailchi.mp/sante.gouv.cd/
My last update here is 2019-11-04.
This source code is free of any improvements or even suggestions for improvement. For anyone who can contribute, I will be really happy.
I will try to answer four questions
Do you want to see what were the daily situation of health areas in terms of confirmed cases and confirmed death?
Do you want to see the number of people with Ebola per province per month, confirmed by the laboratory?
What is the proportion of confirmed deaths compared to confirmed cases?
Is there a way to customize the data?
You will need:
- Create a virtual environment, go to your project’s directory and run virtualenv.
python3 -m virtualenv envsource env/bin/activate
See my requirements.
The final result was deployed to Heroku Check the link: https://drc-ebola-outbreak.herokuapp.com/
👤 Guillain Bisimwa
- Github : @guillainbisimwa
- Twitter : @gullain_bisimwa
- Linkedin : guillain-bisimwa
Contributions, issues, and feature requests are welcome!
Feel free to check the issues page.
Give a ⭐️ if you like this project!
This project is MIT licensed.