What The R Number Where You Are?

[BiBottomBoy]

In France today they announced it's 1.17.

What numbers are you guys seeing?

[lookin]

Wish I knew.  

For some reason, the R0 number, despite its predictive importance, doesn't seem to be widely tracked in the U. S.

One thing that complicates matters is that the transmissibility of the virus varies by strain, and I don't think the U. S. has ever had a testing program robust enough to track individual strains very well.

From what I can tell, the vaccination rate in France is around 15%, and full immunization won't happen until August.  So France has a long way to go before getting to roughly 70% for "herd immunity".  That would make the R0 number more critical than for countries currently approaching that magic number.

The area where I live reports a hodgepodge of vaccination rates.  Roughly 40% of the total population have got at least one dose.  50% of the population over sixteen years old have got at least one dose.  And 25% of those over sixteen have completed a full course of vaccinations.

Add to that around 5% of the population who have already contracted the virus, and we have a little over half of the riskiest population with some level of immunity.

So, while we're a few months from "herd immunity", it's getting progressively harder for the virus to find someone vulnerable to infect.  I expect our R0 number is significantly less than one, and our case numbers are trending down.  Plus our area is pretty mask-friendly.  

All-in-all, it's been a while since I've felt highly vulnerable, knock on wood.  And that's especially true since I'm one of those who has completed my vaccinations.

[Riobard]

The reproduction metrics seem to be easily accessed in google search “Covid R Atlantis epiforecasts” (example), even by province in Canada, so likely states, etc as well as countries. 

R0, aka Rnaught is pretty much extinct for CoV as it is a basic reproduction number more applicable to early in an epidemic. So you will now see effective R or Rt (aka Rt current time) that I believe accounts for some of the variables already mentioned by @lookin , such as CoV19Classic having evolved to CoV21Variants, rising combined natural and artificial immunity, as well as other factors currently relevant to calculations.

I find that the current estimated confidence intervals for R, that is the range within which certainty is good the absolute value is contained by its bookend estimates, are so broad as to render the R metric meaningless, other than how it generally trends, up or down. So the forecasted doubling of incidence estimate for France varies from a week to 6 weeks according to the confidence interval margins. Additionally, the margins of a generation cycle, that is, the average time for the index case to transmit secondary infection, are so broad that it is hard to determine when the endpoint of, say, three cycles where R=1.2 ... 1-> 1.2 -> 1.44 -> 1.73 will have occurred. Then there is dispersion factor: a small percentage of carriers yielding a large percentage of secondary infection. 

Some epi folks think that R it is too heavily relied on for policy, that it has become a reasonably understood token of the pandemic but overly considered because the absolute value confidence margins are so distant from the number, and there are more complex algorithms that may be under-utilized.

A complex exposure risk algorithm is easy to calculate but, oddly, there has not to date been any chatter about arriving at a general consensus of contextual risk tolerability on a 0-100% scale. Such a metric could be held constant as numbers of acceptable community contacts (eg, classroom size, other events) are adjusted against rolling incidence. The accuracy confidence margins of those absolute numbers of people in a given event to maintain a constancy in exposure risk would be much closer to the absolute numbers than you see for R, doubling/halving, what have you.

A propos of mid-range ‘herd immunity’, combined natural and artificial, we see that Chile’s vaccination success story nevertheless illustrates the possible tension between growing vaxx uptake percentage and rolling case incidence. The surging case uptick is counterintuitive, even considering it is contemporaneous with Fall school resumption. So many variables ... guard too relaxed?, variant re-infection and contagion? waning natural immunity among recovered cases? a bottom line minimal threshold of community immunity to yield protection? squandering 10-15% of product vaccinating the 10-15% previously recovered when those doses could be steered to greater numbers of CoV virgins earlier to achieve threshold herd immunity faster?

 

[BiBottomBoy]

Here it's all about the R number. I'm surprised that isn't the case in America.

That's how you know if it's spreading or becoming contained.

[spoon]

Critical parameters for accurate R numbers are ample testing, hence, if the country is not testing enough of its citizen, R number can be deceiving

[BiBottomBoy]

How can they be deciving?

[Taikonaut]

Tanzania has a r of 0 because they don’t test at all for the virus for example. 

[spoon]

Given that the R number is based on number of infected cases against period of time, if a gov decided to reduce testing significantly due to overwhelmed by number of community spreading, the R number can go down instead of up, when in reality, the situation is worsening.

[BiBottomBoy]

Ah. Did not realize that.

[msclelovr]

In the UK (where I’m in lockdown) 0.6-0.9

In Spain 1.25 but in the Balearic Islands (where I have a house) 0.92

Both countries show the calculation based on the last 7 days.

[Riobard]

3 hours ago, BiBottomBoy said:

Ah. Did not realize that.

But it’s the within-region change in testing and tracing rates that poses the difficulty assessing reproduction. As @spoon says, for example, if a reduction occurs.

However, if those two metrics are consistent over time the scale of efforts at testing and tracing matters less and epidemiologists can estimate true infection rates, and changes in R, based on proportion of test positives in the context of reported case volume. 

Mexico is 17th globally in crude CoV mortality (deaths per capita) but the highest in case fatality, 9%. With that disconnect, we know case diagnosis is obviously hugely undercounted ... it’s 156th globally in testing rate. If that undercount bias is stable, changes in attack rate can nevertheless be detected.

All that said, the reproduction metric  is smoothed out and does not reflect regional case ascertainment differences or infection attack rate differences. As you indicated, Montpelier is not Paris. 

[BiBottomBoy]

yeah I don't know what's up with Paris.  They ignore the rules, their rates go up and the entire country suffers for it. it's bullshit.