COVID-19~ Is 9.75(r-1)^2+1 a good estimate for Ro?

In this post we consider if Ro = 9.75(r-1)^2+1 a good estimate for Ro.

We have already looked at worldwide estimates for Ro if Ro ~ exp(2.5r – 2.5), where r is a daily increase in case numbers early in an outbreak. Ro is the average number of people one person may infect when there is no immunity in the community over a ten-day infectious period, and “exp” means “e to the power of” where e ~ 2.718281828 is a mathematical constant. See:

We have already looked at these posts:

COVID-19~ Worldwide estimates if Ro ~ exp(2.5r – 2.5)

COVID-19 in 2020~ Extending using approximating polynomials for Ro

We look at these graphs:

Our simulations have indicated that when

r= 1.4, Re ~ 2.3

r= SQRT(3), Re ~ 6.2

Note: SQRT(3)~ 1.732

We have already looked at the green curve:

The graphs use this data:

We conclude that the red curve provides the good estimate up to r = 1.8 since when r = 1.4 we have estimated in our simulations that Re~ 2.3.

i.e. Ro = 9.75(r-1)^2+1 is the good estimate for Ro.

We could also use Ro = 0.7r^4 from r~ 1.5 (~1.1464 where the red and green curves intersect).

We have already seen that r^2.5 is also a good estimate for low values of r.

Update: We therefore require that our estimates for Ro are above the purple curve:

COVID-19~ Refining estimates for Ro~ May Ro be at least r^2.5?

In our next post we will combine these results by considering again r^2.5.

Shared Posts (Pingbacks)