Based on googling “hospital occupancy rates”, about 66% of beds are already in use on any given day. Doctors I’ve talked to have said that extremely busy days result in near or over 100% capacity.
I expect that there is going to be gradual overload as COVID spreads through various communities, e.g. we’re starting to see Washington hospitals starting to be overloaded
A rough estimate: there are ~333k empty hospital beds, a doubling time of 4 days, 300 new cases today, 0.2 percent of patients hospitalized and 14 days per hospitalization. Thus we want to solve for k such that ∑k+14n=k0.2∗300∗2(k/4)>333,000, giving k > 34, so hospitals will be overloaded in 34 days. This estimate assumes that patients are distributed uniformly throughout all hospitals, so it’s more of an upper bound given unchecked exponential growth.
Edit: Rob Wiblin provides an estimate (on FB) of 15k new cases in the US every day, giving k > 11.5. I haven’t thought much about 15k new cases, but it seems far more correct than 300.
Based on googling “hospital occupancy rates”, about 66% of beds are already in use on any given day. Doctors I’ve talked to have said that extremely busy days result in near or over 100% capacity.
I expect that there is going to be gradual overload as COVID spreads through various communities, e.g. we’re starting to see Washington hospitals starting to be overloaded
A rough estimate: there are ~333k empty hospital beds, a doubling time of 4 days, 300 new cases today, 0.2 percent of patients hospitalized and 14 days per hospitalization. Thus we want to solve for k such that ∑k+14n=k0.2∗300∗2(k/4)>333,000, giving k > 34, so hospitals will be overloaded in 34 days. This estimate assumes that patients are distributed uniformly throughout all hospitals, so it’s more of an upper bound given unchecked exponential growth.
Edit: Rob Wiblin provides an estimate (on FB) of 15k new cases in the US every day, giving k > 11.5. I haven’t thought much about 15k new cases, but it seems far more correct than 300.