I am reposting this Blog because I have an important update with data from May 26, 2020 at the end. I think it is crucial to examine this statistic given the reductions in stay at home orders and violations of social distancing observed over Memorial Day weekend.
“R.t” is a commonly used measure to describe the expansion of infections during the COVID-19 pandemic. It measures the average number of people who become infected from a single, infected person. The higher the R.t is the quicker the virus is spreading.
If R.t is above 1.0, the virus is spreading faster than the rate needed just to sustain the pandemic. If R.t falls below 1.0, the pandemic actually shrinks because less than one person is infected by each infected person. R.t therefore provides an easy measure to see if the pandemic is expanding or shrinking.
Instagram founders Kevin Systrom and Mike Krieger have launched a new website called Rt.Live. It provides daily information on the R.t numbers for COVID-19 broken down by state. On April 1, the pandemic was spreading quickly, with almost all states having R.t greater than 1.0.
Of interest, on April 21 the country was split with about half the states below and half above 1.0.
Most interesting is that some of the hardest hit areas, such as New York Connecticut and Michigan, now have some of the lowest Rt values. In contrast, a few states that were doing the best (Washington State) now have some of the highest R.t. Also, states without shelter in place orders were evenly split between sub 1.0 (Arkansas and South Dakota) and higher (Nebraska 1.8 and North Dakota 2.2) R.t numbers.
While these findings suggest there has been an overall decline in the expansion of the pandemic, the reasons are not clear. Shelter in place would seem to have an effect, but not consistently. It is possible that in NYC and Detroit so many people are infected that the R.t had to decrease. Let’s hope that the positive trends continue. At least this website gives a snapshot of how we are doing.
An update. The most recent Rt values show continued improvement despite reductions in stay at home orders and social distancing. It may be that the effects of those changes are not yet evident, but it may also be that changes in conditions after the initial wave of infection has made for smaller outbreaks (Rt) when they occur. I will discuss the “K” factor that may be responsible for this tomorrow.
Pandemic Pondering 
Does their model factor in the estimated 35% rate of asymptotic cases? They do seem to factor in an increase in tests.
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Dr David Katz at Columbia has an interesting theory eg that no more than 20-30% of most populations is the peak that will be infected and others escape eg no virus, no detectable antibody but no good explanation—possibly cross resistance from non-Covid-19 coronavirus eg “colds” or maybe intrinsic resistance eg low, abnormal or an absent ACE2 receptors in their mucosal lining cells.
Look at the data in a recent JAMA about low receptor density in kids’ nasal mucosa.
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Agree. These seems to be a level of “natural immunity “ not accounted for by antibody. The limited spread seen with clusters of infection also supports this concept.
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