COVID-19 Simulation

The Importance of Social Isolation

Coronavirus has got me shook. I’ve been staying up late for the past several days reading about the coronavirus. I’m trying to think of ways I can use my not-a-real-dr skills to help spread awareness.

Twitter is a great place to stay updated, and I found knowledge that only made it to mainstream media after 2-3 days – which by then is sometimes “old” news, and the reality then is much worse. For instance, as of this writing on March 14, 2020, we have about 10,000 to 20,000 cases in the United States. But the mainstream media is reporting the 2-3k numbers that are officially reported (perhaps they will try to correct for the underreported numbers soon).

This morning, I woke up to a really interesting tweet.

It inspired me to do something similar. I’m not an expert, but I wanted to see the general effects of social distancing.

Suppose there is a population of 100 people (represented in blue), and they all wear face masks. The CDC has suggested face masks are not effective but we can optimistically assume that it’s “harder” to get infected. For instance, we won’t be able to touch our mouths or nose (but still our eyes and ears). This is what it could look like, where the red color means a person is infected.

We can see that eventually, everyone gets infected. Assume the bottom x-axis represents some measure of time.

Now imagine if everyone interacted with each other with reckless abandon. Two people hug, shake hands, and immediately rub their eyes. We might see something like the following:

Here, the number of infected people increase much faster, and everyone still gets infected. Compared to the face mask version, everyone in reckless abandon is infected by the time things really start to ramp up for people wearing face masks.

Now let’s look at the effects of social isolation. Suppose that only 30% of a population practiced social distancing or social isolation, and were vigilant to always wash their hands. We don’t even have to quarantine people who are sick – just keep 30% of people working from home or socially isolated. This is what it could look like:

Unlike before, we see that some of the blue people still remain at the end – and it takes a longer time for most of the population to get infected.

Now let’s assume that a majority, say 60%, of the population practices social isolation or social distancing. Over the same amount of time as the previous simulations, not only will the entire population never become all red, but there are a lot of blue people around by the end! And this is still assuming that the red people infect others with reckless abandon!

In reality, we hope the results are more towards the last graph. Other things we don’t consider is that the red people will become better with time, and that those who are sick will self-quarantine. If we assume these two factors are true, we will have even more blue people.

So let’s do social distancing as much as we can, and we will not only flatten the curve, but we can smash it!

Special thanks to Ali Almossawi for showing me how to convert a sequence of image files to gif.

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