Project COVID-19

Exploratory and predictive analysis over Covid-19 in Mexico

Links:-

• Tableau Public Link:- https://public.tableau.com/app/profile/malvika4793
• Google slides:- https://docs.google.com/presentation/d/1yWZlWuGSaTPao9K6TRlcCLMK5A-ppxela27NbQfRnsU/edit#slide=id.p
• Deployment Web application:- https://lperez-covid-deployment.herokuapp.com/register
• Deployment repository:- https://github.com/lindaperez/heroku_flask_app_covid

Overview

Corona Virus Infection Disease (COVID-19) is a virus which was discovered recently that causes severe resipratory illness in various individuals since the last two years. It was then termed as a pandemic as it started spreading rapidly around the world when the world was unprepared. This ended in affecting the humanity by overwhelming the healthcare systems and also causing a severe economic crisis. In order to avoid the crisis of a pandemic it is good to be prepared and to mitigate the effects. As a part of the measures to avoid the unpreparedness it is good to find high risk and low risk patients thereby allocating the necessary healthcare priorites helping to reduce the load on the healthcare workers and economic crisis.

Motivation

The spread and impact of the novel coronavirus pandemic has taken the world by storm with its rapid growth in infection cases, high mortality rate, affecting thousands of millions of families in the human community. Within all the countries, Mexico is in the top 5 countries with the most death cases.

It would be helpful to figure out the potential factors that are attributed to the high mortality rate, so patients with potential factors will be classified as high risk or low risk, by which precautions can be taken accordingly. Furthermore, predictions can be made based on the Machine Learning model, which can be deployed for prevention care. Identifying high and low risk patients helps the healthcare workers to plan and prioritize care and thereby organize themselves and provide the best possible help needed without overwhelming themselves.

Aim

To develop a machine learning model in Python to analyze what has been its impact so far and analyze the outbreak of COVID 19 across various regions in Mexico, visualize them using charts and tables, and to identify high and low risk patients to help the healthcare workers plan and prioritize care based on underlying conditions.

Questions to answer

• What are the top hit regions in Mexico based on mortality and number of confirmed cases?
• How COVID-19 affected people based on age, gender and race in Mexico?
• How significant are the medical conditions classification of high and low risk patients for death/hospitalization and can it be predicted using ML?
• Can we classify high and low risk patients based on their existing medical conditions and deploy the model using a questionnaire?

Dataset to use:

• Mexico Confirmed Case_Death https://cdmx.dash.covid19.geoint.mx/#DownZCSV
• Mexico Visualization Dataset: https://covid.ourworldindata.org/data/owid-covid-data.csv
• Mexico Demographic Data https://datosabiertos.salud.gob.mx/gobmx/salud/datos_abiertos/datos_abiertos_covid19.zip

Communication protocol

• Slack channel: created to share ideas, ask for status updates, look for information and ask questions about the project.

• Google Docs File: designed to share resources, datasets, links, facts and ideas.

• Recurring Zoom Meetings: designed to brainstorm ideas and conclusions about the project, every Wednesday at 3 p.m PDT based on group availability.

Technologies, languages, tools, and algorithms used throughout the project

Please refer to the following text file for the details

• Technology Used Details
• Requirements.txt

Machine Learning Analysis

Please refer to the following text file for the details.
Machine Learning Analysis Report
The report covers:

• Data Preprocessing
• Statistical Analysis
• Feature Engineering
• Machine Learning Analysis
• Others