Coronavirus_prediction

Overview:

The Coronavirus Prediction Flask Web Application is a web application developed as a group midterm project for a class on Web Application Development. The aim of the project was to create a web application that provides information and predictions about the COVID-19 pandemic. The application is built using Flask, Bootstrap, Flask-SQLAlchemy, Pytorch, JavaScript, and AmCharts. It allows users to view landing page, sign up and sign in, monitor live data on COVID-19, cross-reference data worldwide, view historic data and plots, view information on specific countries, parse and display latest news on COVID, and download a simple PDF report of COVID data. The application also includes a page that displays predictions for COVID cases and deaths. It is currently deployed on Heroku, although the final version is not deployed due to size restrictions.

Features:

• View landing page describing the use of the application
• Sign up, sign in, and authorize via Google
• Monitor live data on COVID-19 from a source
• Cross-reference data worldwide in one table
• Watch historic data and plots
• View information on specific countries
• Parse and display latest news with source links on COVID
• Download a simple PDF report of COVID data
• View predictions for COVID cases and deaths

Summary:

The Coronavirus Prediction Flask Web Application is a web application developed as a group midterm project for a class on Web Application Development. It provides various features including live COVID-19 data monitoring, cross-referencing of data, historic data and plots, information on specific countries, latest news on COVID, and predictions for COVID cases and deaths. The application is built using Flask, Bootstrap, Flask-SQLAlchemy, Pytorch, JavaScript, and AmCharts. The installation process involves cloning the repository, setting up a virtual environment, installing the required packages, and running the application using the run.py file. Despite its limitations, such as lack of smoothness and stability, the application serves as a useful tool for accessing COVID-19 information and predictions. Future improvements could include integrating COVID data with economics data and market shifts, as well as creating additional Pytorch models.