Modeling the spread of a pandemic!

How do scientists model an epidemic? How does the government come up with lockdown plans? How do we know if we flattened the curve already?

Note from the editors:Towards Data Science_ is a Medium publication primarily based on the study of data science and machine learning. We are not health professionals or epidemiologists, and the opinions of this article should not be interpreted as professional advice. To learn more about the coronavirus pandemic, you can click [here_](https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports).

We are living in the most unprecedented times that we have never imagined in our lifetimes. Our lives have long departed from what used to be normal and unfortunately, the world will never be the same again. Instead of stressing a lot about what has changed, it would be a wise idea to accept the new normal and move on, up and running again.

The 19th century has seen the three powerful things that changed the world for ever— Industrialization, the Internet, and the Infectious diseases!

Alright, let's address the elephant in the room — Coronavirus which originated from China infected nearly 22 million worldwide and claimed 770K deaths. Here is the current situation in the world as of August 17th, 2020.

Screenshot, as captured from https://www.worldometers.info/coronavirus/ on 17th August 2020

Here is the agenda for this article. You may choose to jump to any of the following section you may like:

• COVID-19 Data Visualizations
• Exponential growth, Logistic growth? what the hell are they talking anyway?
• Understanding the Basic SIR model and building blocks of a pandemic
• How various governments come up with different strategies?

All the code used in this article can be downloaded from this GitHub repository

COVID-19 Data Visualizations

Data Visualization #1: Total cases by country

The below data visualization runs through the timeline from Feb 2020 until the end of July 2020 and shows how the top 20 countries shifted places in terms of the total number of reported cases.

Data Visualization #2: Total deaths by country

Another data visualization shows hows the top 20 countries shifted places in terms of the total number of reported deaths due to COVID-19.

Data Visualization #3: World Heatmap showing the number of days until the first reported case

The following data visualization shows how quickly it spread to the entire world.

Days until the first reported case. For the interactive version, click here

From the above interactive data visualization, we can see that:

• Thailand is the first one to be hit (within the first 13 days) and then Japan (by 15 days) and South Korea (by 20 days).
• Within a month, the virus spread to India, Southeast Asian countries, Australia, most of Western Europe, United States, and Canada.
• Relatively it took longer for the spread to hit South American and African continents.

Data Visualization #4: World Heatmap showing the number of days until the first 1000 cases

Now, let us see how fast it took to reach the first 1000 cases within each country:

Days until first 1000 cases, For the interactive version, click here

From the above interactive data visualization, we can see that to reach the first thousand cases:

• Turkey, Iran, and Tajikistan took just 2 weeks. This tells a lot about how fast it spread in their societies.
• South Korea took a little over a month.
• Japan took more than 2 months.
• Most of Europe took nearly a month.
• United States, India, and Australia took nearly 2 months.
• Brazil and most of the South American countries took less than a month.
• South Africa took less than a month.

We have seen how fast the virus spreads in some of these countries. This is called exponential growth. In the next section, we will be covering the different growth models used to model the virus, and also we will be discussing how governments come up with various mitigation strategies.

covid19 modeling pandemic coronavirus data-science

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