Among the armchair epidemiologists there seems to be a misguided belief that the factor (1 – 1/R0) will set the asymptote for "herd immunity" of a population. Any value of R0 above unity is exponential contagion growth and below unity it is damped. So they apparently think that keeping R0 just above unity can keep the level of infection to a fraction of the population. See this blog post (by the well-known AGW skeptic Nic Lewis hosted on the well-known AGW skeptic Judith Curry's blog)

https://judithcurry.com/2020/05/10/why-herd-immunity-to-covid-19-is-reached-much-earlier-than-thought/

So if R0 is reduced to 1.1 instead of a highly contagious 5, they think that the fractional level of effective immunity can be reduced to 1-1/1.1 ~ 0.09. Apparently they believe that this provides a rationale for society to go back to BAU.

The issue is that new carriers of disease and relaxation of community standards will almost guarantee that everyone will become exposed to coronavirus at some point. IOW, I think the skeptics are playing mathematical games with this factor and in reality, the only solution is to maintain some type of lock-down approach until a vaccine is found.

I could be wrong about this interpretation, but in dealing with compartmental models for resource depletion over the years, I have found all that matters is the available pool to draw from. By slowing down extraction rates, this does not mean that we will extract less. For contagions, the available pool is the human population, and so by the same token, slowing the infection rate down will not change the asymptotic level.

The following document is what the contrarians need to be reading, and not analyses from armchair skeptics experienced at climate war polemics:

https://wwwnc.cdc.gov/eid/article/25/1/17-1901_article

> *Complexity of the Basic Reproduction Number (R0)*

> Abstract

> "The basic reproduction number (R0), also called the basic reproduction ratio or rate or the basic reproductive rate, is an epidemiologic metric used to describe the contagiousness or transmissibility of infectious agents. R0 is affected by numerous biological, sociobehavioral, and environmental factors that govern pathogen transmission and, therefore, is usually estimated with various types of complex mathematical models, which make R0 easily misrepresented, misinterpreted, and misapplied. R0 is not a biological constant for a pathogen, a rate over time, or a measure of disease severity, and R0 cannot be modified through vaccination campaigns. R0 is rarely measured directly, and modeled R0 values are dependent on model structures and assumptions. Some R0 values reported in the scientific literature are likely obsolete. R0 must be estimated, reported, and applied with great caution because this basic metric is far from simple."

this another the key point made in the conclusions

> "R0 values are nearly always estimated from mathematical models, and the estimated values are dependent on numerous decisions made in the modeling process. "