As our news feeds feature more shots of crowded events, we must remember the importance of keeping COVID transmission rates under control. As restrictions have eased, communities across the US are seeing a rise in cases and deaths.
By now, most of us are well acquainted with the concepts of mask use and social distancing to help slow the spread, but what does the impact of those measures really look like?
Here we visualize some of those concepts by simulating a few scenarios of virus transmission. But first, a few important caveats:
- One major difference between this simulation and the real world is that in these scenarios, no one dies. Our little dots move from healthy to infected to recovered until almost the entire population has been affected, but in reality that translates to thousands of people who never recover.
- We are also demonstrating these concepts on a tiny population in a closed system. When expanded outward, the situation becomes much more complex. People move between different areas with various rates of transmission, while some locations experience surges of infections that then ripple across surrounding areas.
Let’s start by introducing our three types of people:
Let’s assume the virus has a 5% probability of transmission when two people come into contact and see what happens with no precautionary measures. Infection takes off rapidly, and at its peak, up to 90% of the population is infected simultaneously.
What effect do masks have?
Now let’s compare that scenario with one where 95% of the population wears masks. The masked icon denotes masked individuals, while their color denotes infection status as above:
Here we assume that masks reduce the probability of virus transmission by 33% for both the infected person and the healthy person. See how the model changes for the case with no masks, despite the number of contacts being exactly the same.
By comparison, the 95% mask use scenario usually peaks with around half the population infected, or even lower. In other words, masks don’t totally prevent infections for any given individual; they lower the overall rate of transmission, resulting in fewer infections over time.
What about social distancing?
We can mimic partial social distancing by keeping some people in the simulation fixed, resulting in fewer contacts with others. Here are two scenarios where 50% of people are socially distant, one with masks and one without.
With the two social distancing scenarios, we see the curve flatten significantly, but when mask use is also implemented, the peak infection count drops to its lowest: around 25% of the population.
These simulations are random, and the exact numbers will change every time you run them. However, the trend remains clear: as more precautions are taken, the spread slows and the curve flattens.
What’s the big take-away?
As governments around the world grapple with the challenge of keeping economies afloat while minimizing the death toll, many base their policy decisions on peak infection rates. With those numbers steadily creeping back up, communities will be forced to take drastic action. By not adhering to recommended guidelines for mask use and social distancing, we not only hasten the return to a strict lockdown, but also reverse much of the progress made so far.
Thank you to Harry Stevens and his article Why outbreaks like coronavirus spread exponentially, and how to “flatten the curve” for inspiring this post.
