How many hospital beds with ventilators are needed?


Mar 24, 2020
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(a) How many hospital beds with ventilators will be needed to handle US coronavirus pandemic over a 3 month period?
(b) How many months will be need to flatten/delay the infection rate for the current number of hospital beds of 800,000 (80,000 of which are ICU beds, and of those, 75,000 have ventilators)?

We know the percentage of the population 65 and older is - 16% of 327 million = 52.3 million Americans

Add 4% for those with pre-existing conditions (likely higher) and you get 20% of 327 million = 65.4 million Americans that will need hospital beds with ventilators.

Let's assume the average ventilator stay is 7 days (Italy has reported some stays as long as 20 days).
(a) (65.4*10^6/90)*7 = 5.1 million hospital beds with ventilators. =====> Conclusion: Not possible to get through pandemic in 3 months without huge loss of life
(b) (65.4*10^6/75*10^3)*7 = 6104 days to completely treat all COVID-19 affected people that are at risk. That is 16 .7 years =====> Conclusion: Not possible to sustain the economy for 16 years while people stay self-quarantined in an effort to "flatten" the infection rate curve.

Summary: We need testing kits, and we need contact tracing and quarantine of all infected. The approach used by S. Korea and China.
Nov 11, 2019
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Hey there,

The math on this is a little rough, but what you're laying out is the primary case for concern. Though it is worth noting that ventilators can be shifted from place to place depending on the surge needs they arise - not all areas experience the peak window at the same time, fortunately. is a great resource to see not only the estimated window for action to be taken, but also estimates on hospitalization rates expected. The United States is somewhat hamstrung on this factor due to government type - our states have broad latitude to conduct regional level responses, and these are not necessarily all up to par with the requirements of handling this pandemic.

Additionally, some states have much older populations (Florida, for example), and so the math in application elsewhere is likely to change based on a more vulnerable population.