Introduction
As of October 2020, the COVID-19 pandemic has claimed over 1 million lives across the world and over 41 million people have been infected. Understanding the factors and policies that influence the spread of the virus can help governments make informed decisions in order to control infections and deaths until a vaccine becomes widely available.
The goal of this article is to answer the following questions:
- What are the factors and policies that have the greatest impact on the number of cases and deaths across the world?
- How can we predict the number of COVID-19 cases, deaths, and recoveries in the future?
Datasets
In order to answer the questions above, I aggregated data from the following sources:
- COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University: https://github.com/CSSEGISandData/COVID-19
- **Policy Data From Oxford Coronavirus Government Response Tracker (OxCGRT): **https://ourworldindata.org/policy-responses-covid
I used data aggregated from both sources to train three neural networks that can** forecast the number of COVID-19 cases, deaths, and recoveries** in any nation months into the future based on a wide range of factors including:
- GDP
- Government response to the coronavirus, including stay-at-home and social distancing restrictions.
- The change in mobility of its population since the start of the pandemic.
- Demographic data about its population.
- Past data regarding the number of cases, deaths, and recoveries.
Source Code
All of the code that I used to build the models and visualizations described in this post are publicly available and can be accessed in the following GitHub repository: https://github.com/AmolMavuduru/COVID19FactorAnalysis.
A Detailed Look at the Data
The data used for this project can be divided into four different parts, each represented as separate data frames/tables in the code: policy data, mobility data, demographic data, and COVID-19 time-series statistics.
Policy Data
The policy data, extracted from the OxCGRT dataset, contains information about the policies implemented by the government in each country to control the spread of COVID-19. The policy data is available for each day after the start of the pandemic.
#deep-learning #covid19 #data-science #forecasting-models
