A semi-quantitative framework for long-term thinking about the COVID-19 pandemic

I think the current rush to invoke extreme flatten-the-curve measures needs to be accompanied by careful thought about what we'll do once the measures have had the desired effect.  In particular, how long would restrictive measures need to remain in force, and how will we decide when they can be lifted?  And how can we mitigate the personal, social and economic harms of the measures while they remain in place?

So I've created a series of semi-quantitative graphs to help.  ('Semi-quantitative means that there are numbers on the axes and specific doubling times for periods of exponential growth, but the finer details are rough approximations.)

Here's the tl;dr for the first 6 months:

Points to note:  

• The Y-axis is log-scale, so small differences in height indicate big differences in numbers of infected people.
• Five different scenarios are considered, with plausible effects on doubling time of % infected.
• Restrictive measures are assumed to reduce peak % infected and eventual equilibrium.
• For all but the most extreme scenario, infection levels remain high (≥1%) even after 6 months.
• It will be very hard to justify lifting restrictions that have been effective.

Here's the tl;dr if the costly restrictions are lifted after 7 months of misery:

Points to note:

• In all cases, lifting restrictions makes % infected much worse (remember, log-scale...).
• The more effective the restrictions were in limiting total infections, the worse the second wave on infection is, and the longer it drags on.

Below are the individual graphs:

If no action were taken (doubling time 3 days):

Infections are assumed to peak at about 30% of the population at weeks 6-10, and then to decline to about 1% of the population since about half of the population will remain susceptible.

If we take actions that have no or low personal cost (doubling time 6 days):

• Reduce physical contact with other people
• Don’t touch your face
• Wash your hands
• Avoid large groups and crowded places
• Work from home if this is possible
• Reduce travel

The peak % infected is lower, maybe 20%,  occurs at weeks 11-16, and declines to about 0.3% provided the restrictions remain in place.

If we take actions that have moderate cost (doubling time 10 days):

• Cancel pro-sports, concerts, conferences and other large gatherings
• Close bars and restaurants
• Cancel university classes

The peak % infected is lower, maybe 15%, occurs at weeks 18-25, and declines to about 0.15% provided the restrictions remain in place.

If we take actions that have high cost (doubling time 20 days):

• Close all schools and universities
• Close close non-essential shops and workplaces
• Close all public buildings
• Ban all non-essential travel

The peak % infected is lower, about 10%%, occurs at weeks 35-40, and falls to about 1% by week 52 provided the restrictions remain in place.

If we take extreme actions (R0 <1 b="">

• Lock down the entire population
• Enforce by police or the National Guard

The % infected slows its increase and begins to decline by week 15.  It continues declining provided the restrictions remain in place.