Jen van der Meer

Straight Lines and S-Curves: Predicting COVID-19

Published: (Updated: ) in Business Model Narratives, Business Models, Systems Thinking by .

We’re all peeled to our digital screens right now checking in on the world, our families, our colleagues, and then trying to predict what all of that means for our selves.

What I’ve noticed are fights breaking out based on what comes down to math and mental models.

It’s curves vs. lines.

I know I’ve been guilty favoring curves versus lines. I love the sexy s-Curves of tech, mobile adoption, and disruptive innovation. I like to help organizations escape the boring flat lines of industrial-era businesses with their incremental shifts or even declining growth.

But now I’m seeing this favoritism for S-Curves blind the best thinkers from building useful scenarios and simulations. You’re a linear thinker who doesn’t “get” exponential curves. Or you’re a non-linear thinker that doesn’t “get” hospital capacity constraints. It’s time for us all to be bilingual in all kinds of curves.

Today I want to take a moment to deeply appreciate the installed base of things that don’t scale easily: respirators, oxygen tanks, HVAC systems, plastic tubing, buildings. I want to appreciate the people that can only scale in human terms: trained nurses and doctors and all of the facilities staff that keep the building functioning. 

I want to remind us that before we take sides in this debate, that it is not a debate. This pandemic requires us to be fluent in both exponential thinking AND linear thinking.

When you are told to stay home from school or from work, the math that is being conducted by your department of health factor in that S-Curves of diagnosis meeting constraints of hospital capacity.

So even if you think YOU are not at risk and you feel OK with your odds, when you are asked to stay home, please do so, so that you are not a carrier, so that WE do not overburden OUR healthcare system.

Source: Our World in Data

According to the American Hospital Association, 2018 hospital admissions were 36,353,946, but total staff beds were 924,107. In NYC, we have approximately 24,000 beds available within our 5 boroughs in acute care hospitals, which is enormous under normal circumstances and larger than the capacity of most states.

Source: True Cost of Healthcare, Referencing American Hospital Association

The declining admissions and census rates for hospitals stem from financial collapse of the weakest hospitals, and mergers of the remaining.

But when the growth in COVID-19 diagnoses started climbing the logarithmic curve seen in Wuhan and Northern Italy, it’s time to project how that curvy line will hit the very straight line capacity of available beds, respirators, oxygen tanks, and protective gear.

I won’t do the math for you. If you want to know what exponential COVID-19 cases look like hitting limited hospital capacity, then it’s time to read the first hand accounts of nurses in Wuhan and doctors in Milan.

If you want to brush up on your exponential thinking here is an excellent primer by 3Blue1Brown animated math.

Then, hunker down and cooperate with your local health authorities to flatten the S-Curve of the epidemic.

 

Update: it seems the hivemind is taking hold. An excellent primer on all of this math at: https://www.flattenthecurve.com/