Sufficient flattening would be extremely difficult to achieve
The range for effective R0 in which the virus spreads to the point of herd immunity in a reasonable time, without blowing out the hospital system and without infection rates collapsing, is extremely narrow.If you want to be very sure to avoid a blowout you have to basically be quite likely to produce a collapse in # cases. Maybe you could turn the isolation on and off but that is also very tricky.
Even if achieved, flattening would be a protracted process, lasting 1-2 years, with all that implies in terms of the economy.
As OP mentioned, the cost in lives lost would also be high for a flattening where 60+% of the community is infected. People argue that “only” old people/boomers are killed but… 1) the average years of life lost seems to be substantial (~11 years). This is not people dying a couple of months early 2)
Finally, daily reminder that Taiwan has very few cases, one death so far in April, without shutting down their economy. This idea that you have a dilemma of health versus economy is quite false. The dilemma is competence versus stupidity.
On the masks issue, OP’s proposal seems plausible, reducing effective R0. I am working on a program to model this and I will add this option and see what happens. It is a pity the authorities lied to us about masks, in order to preserve them for those with greater need when they were in very short supply.
Fraction of people compliant with the masks policy(asymmetric-distancing-fraction-compliant-fv) 0.7 Fraction of infection that still gets through from mask wearer to other person (asymmetric-distancing-outbound-ineffectiveness) 0.3 Fraction of infection that still gets through from non-mask-wearer to mask-wearing person (asymmetric-distancing-inbound-ineffectiveness) 0.8
Given this, and numerous other assumptions including no other measures taken, the death rate falls from 0.65% to 0.48% of the population. This is a good benefit but not a total solution.
If you have better numbers for mask effectiveness than the ones I guesstimated above please let me know.
The other main dubious assumption in my model (other than no other measures taken) is uniformity of people. I am adding some options on that tomorrow.
The range for effective R0 in which the virus spreads to the point of herd immunity in a reasonable time, without blowing out the hospital system and without infection rates collapsing, is extremely narrow.If you want to be very sure to avoid a blowout you have to basically be quite likely to produce a collapse in # cases. Maybe you could turn the isolation on and off but that is also very tricky.
Even if achieved, flattening would be a protracted process, lasting 1-2 years, with all that implies in terms of the economy.
As OP mentioned, the cost in lives lost would also be high for a flattening where 60+% of the community is infected. People argue that “only” old people/boomers are killed but… 1) the average years of life lost seems to be substantial (~11 years). This is not people dying a couple of months early 2)
See the modeling done for the Australian government here https://www.health.gov.au/news/modelling-how-covid-19-could-affect-australia—if you read between the lines you can see this confirms the above points, which originally came from a simple spreadsheet I did.
Finally, daily reminder that Taiwan has very few cases, one death so far in April, without shutting down their economy. This idea that you have a dilemma of health versus economy is quite false. The dilemma is competence versus stupidity.
On the masks issue, OP’s proposal seems plausible, reducing effective R0. I am working on a program to model this and I will add this option and see what happens. It is a pity the authorities lied to us about masks, in order to preserve them for those with greater need when they were in very short supply.
In my program I assume
Fraction of people compliant with the masks policy(asymmetric-distancing-fraction-compliant-fv) 0.7
Fraction of infection that still gets through from mask wearer to other person (asymmetric-distancing-outbound-ineffectiveness) 0.3
Fraction of infection that still gets through from non-mask-wearer to mask-wearing person (asymmetric-distancing-inbound-ineffectiveness) 0.8
Given this, and numerous other assumptions including no other measures taken, the death rate falls from 0.65% to 0.48% of the population. This is a good benefit but not a total solution.
If you have better numbers for mask effectiveness than the ones I guesstimated above please let me know.
The other main dubious assumption in my model (other than no other measures taken) is uniformity of people. I am adding some options on that tomorrow.