Flatten the curve...or else

There's a lot of talk about "flattening the curve" this last week but not a lot of hard answers.  Here's a guess what might be in store in Nevada.

I have to start with a quick digression on epidemic (epi) curves.  Epi curves plot the number of new cases with time.  The total number of cases, mortality and other statistics can in turn be calculated from the epi curve.  Natural epidemics obey basic mathematical laws and tend to form bell shaped curves with long tails on the down side.  With no measures taken to stop them, highly infectious diseases can spread very quickly throughout a population but eventually the rate of new infection drops once a large proportion of the population gets infected.

Since medical resources are finite, an infectious disease outbreak can swamp the medical system, forcing medical practitioners to ration care and triage patients based on expected outcomes.   You can change this outcome by taking preventative measures to minimize the spread of the disease, thereby prolonging the outbreak but lowering the number of new cases the system has to deal with.  This is "flattening the curve" shown below:

  So - what's the story in Nevada?  In the absence of any guidance  from state authorities (at least that I can find), I decided to take a stab at estimating what might happen.   Below is an epi curve for Nevada cases of COVID-19 constructed from data collected by the Johns Hopkins University Center for Systems Science and Engineering, current to March 17.

 For the last seven days, the average daily rate of  increase in new cases is 29.8%.

The Nevada Current estimates there are 6,000 hospital beds in Nevada.   Statista estimates the average utilization rate of hospital beds in America is about 66%.  So that leaves about 2,000 beds in Nevada available to cope with the COVID-19 outbreak.  When might all those beds be filled?

In China, the World Health Organization documented that roughly 15% of COVID-19 patients required medical attention (oxygen and / or ventilation) and that the average patient required 3 to 6 weeks of care.  For comparison, the current COVID-19 hospitalization rate in New York is 19% (CNBC).  From the epi-curve we can estimate the number of patients who will require care and the number of beds required.    Assuming a 29.8% compound case growth rate, 15% hospitalization rate and 4 weeks care, you can calculate what demand an outbreak might place on our medical system:

The bottom line: by April 8, our hospital beds could be full and we could be turning away COVID-19 patients.

Now I get why there is panic in the air. 

The CDC has told us what to do: we'd better cooperate and flatten this curve.

-- Mike Power