Simplistic (and therefore probably stupid) curve fit to USA COVID-19 cases and deaths.
If you want to be an optimist, then the USA may be near the peak of its new cases, and the first wave could even be mostly over by May.
If you want to be an optimist, then the USA may be near the peak of its new cases, and the first wave could even be mostly over by May.
To be clear the above plot is just a dumb curve-fitting exercise, but that simple model does fit the observations pretty closely.
The IHME modeling group is also doing curve-fitting with error functions, but they go state-by-state and ultimately predict ~82,000 deaths.
The IHME modeling group is also doing curve-fitting with error functions, but they go state-by-state and ultimately predict ~82,000 deaths.
A second problem with such simple modeling is that it can't really answer the question of what comes next.
If you fit an error function (or similar curve) then you are explicitly assuming that COVID-19 will just go away after the peak. That's pretty unlikely.
If you fit an error function (or similar curve) then you are explicitly assuming that COVID-19 will just go away after the peak. That's pretty unlikely.
The example of South Korea is helpful. They are well passed their peak in COVID-19 cases, but they still have had ~100 new cases per day.
Though the first wave of the COVID-19 epidemic appears likely to hit its peak soon in the USA, what comes after is very important.
There is likely to be a continuing trickle of new cases, and if social distancing is relaxed, further epidemic waves are likely.
There is likely to be a continuing trickle of new cases, and if social distancing is relaxed, further epidemic waves are likely.
After the initial wave, many people will want life to quickly get back to normal, but with millions of lives still at risk that will be unrealistic unless a plan can be developed to control the post-peak spread of COVID-19 and prevent further outbreak waves.
