Levitt's Measure Dasboard

Dashboard: Levitt's Measure Dashboard

Michael Levitt, a professor of structural biology in Stanford, also a Nobel laurette in Chemistry, defined a very simple measure, using which he predicted the progression and eventual end of the Covid 19 epidemic for many regions and countries, and (most of) his predictions turned out to be surprisingly accurate, given the simplicity of his metric.

Levitt's measure H(t) for day t for COVID-19 is a very simple measure, it is defined as:
H(t) = X(t) / X(t-1)
where X(t) is the cumulative number of COVID-19 cases on day t. When the value of H(t) approximately equals 1 (we have taken 1.0001), then the situation will be better and the number of new cases per day will become considerably low.
In the dashboard, one can see when Levitt's measure reaches a value of around 1.0001 for India or selected Indian State/UT/District, which will effectively mean when the situation will be under control. One can also adjust the start date to improve the fit of the regression line as the R-squared of the regression line is also shown.
More information on Levitt's measure can be found here: Conceptual basis of the Levitt measure

Setup Instructions

1. Make sure you have installed Python 3.6, pip3 and virtualenv.

2. Clone the repo - https://github.com/rajats/Levitt-Measure-Prediction-Dashboard.git and cd into the Levitt-Measure-Prediction-Dashboard directory.

3. Create a virtual environment with Python 3 and install dependencies:

   $ virtualenv venv --python=/path/to/python3
   $ source venv/bin/activate
   $ pip install -r requirements

4. Run python main.py to start the development server.

Setup Instructions (PyCharm)

1. Open Pycharm and click on VCS.
2. Click on Get from Version Control.
3. In the popup URL enter https://github.com/rajats/Levitt-Measure-Prediction-Dashboard.git
4. Press Ctrl+Alt+S to open the project Settings/Preferences.
5. Select Project | Python Interpreter. Click the settings icon and select Add.
6. In the left-hand pane of the Add Python Interpreter dialog, select Virtualenv Environment.
7. Specify the location of the new virtual environment in the text field.
8. Choose the base interpreter from the list as Python 3.x and click OK.
9. Click terminal and run pip install -r requirements.txt
10. Click on play button or run python main.py in the terminal to start the development server.
    More information on configuring virtual environment in PyCharm can be found here: Configure a virtual environment