Arizona IS experiencing an increase in infection rate(s)

[thinkalot]

Originally Posted by KurtAZ

This is a good point...why would you go get tested and stand around a bunch of potentially sick people? Wouldn't those already feeling ill STILL be the ones getting tested or those that need to be tested to go back to work? I am not going out of my way to get tested...my company has us on indefinite WFH (not that it matters, I have been doing this for almost 5 years now) so I have no reason to go get tested.

Yep. I don't know one person that has been tested that wasn't having surgery.

Until they randomly test 10,000 people throughout the state instead of the people that have been getting tested those numbers don't mean much to me.

[Hoonose]

Originally Posted by belgirl

The RT factor for Arizona has been under 1 since June 23rd and currently sits at .89. Anything under 1 indicates slowing infection rates which if accurate essentially contradicts what you are saying. Arizona has had one of the lowest numbers for weeks now.

And as others have already stated, there is no reason for non-symptomatic people to go get tested. None. (unless they are having surgery and are required to have it etc.)

Or if they have been more potentially exposed.

[teddyearp]

Originally Posted by belgirl

The RT factor for Arizona has been under 1 since June 23rd and currently sits at .89. Anything under 1 indicates slowing infection rates which if accurate essentially contradicts what you are saying. Arizona has had one of the lowest numbers for weeks now.

And as others have already stated, there is no reason for non-symptomatic people to go get tested. None. (unless they are having surgery and are required to have it etc.)

Real quick as I am curious. What is this RT factor you speak of and how is it computed? What are the source numbers and the formula(s) to arrive at it.

[teddyearp]

Originally Posted by roodd279

I think positivity COULD mean something – but – in Ohio, for instance – until July, only “sick” people were tested in the first place. As a result, positivity was quite high.

6 weeks ago or so, the rules changed, now anyone can get tested. So – of course – the positivity is going down. Did the infection rate change? I don’t know – but you can’t tell from the positivity.

Your (reported) numbers may all be correct, but it doesn’t (necessarily) mean infections are at a higher rate. It could just mean fewer not-sick people are bothering with the test.

Are you looking at the numbers and dates I posted? Or maybe we need to understand the terminology each of us is using. When you say 'positivity' I interpret that as the rate of positive test result compared to amount of tests given, expressed as a percentage. Which is what I mean when I say 'infection rate'.


IIRC, back in June, the only way to get tested was if you were already showing symptoms. And on June 1, the infection (or positivity) rate was 8.82% And six weeks or so ago, as you said, anyone can get tested. But you say the positivity is going down??? June 18 it was at 11.44%. Last I checked, 11 is greater than 8, 11 is going up from 8. Then you go on to say, "Did the infection rate change? I don't know - but you can't tell them from the positivity"?


So, I now see that you see them as two different things. Please tell me what you mean by 'positivity', the source numbers you are using and your formula(s).

[belgirl]

Originally Posted by teddyearp

Real quick as I am curious. What is this RT factor you speak of and how is it computed? What are the source numbers and the formula(s) to arrive at it.

Here you go: https://rt.live/us/AZ

Explanation of how they arrive at the number is explained as well.

[teddyearp]

Originally Posted by fluffythewondercat

This is hilarious. You do not trust the "24/7 news cycle", yet you trot out a far-left source (The Atlantic).

Try getting the numbers directly from AZ DHS. AZCentral (aka The Arizona Republic) reported yesterday:

The state's positivity rate, or the number of tests coming back positive, was 11% of known tests last week. Arizona's positivity rate of more than 25% in July — pegged by Johns Hopkins University<snip>

You know what's really hilarious? I stumbled across something today while at the John's Hopkins site, this one:


https://coronavirus.jhu.edu/testing/individual-states


Right under the graph, it lists its data source with a link. Want to guess where that link goes?

[teddyearp]

Originally Posted by belgirl

Here you go: https://rt.live/us/AZ

Explanation of how they arrive at the number is explained as well.

Well thank you. It means Reproductive Rate for anyone who doesn't know. So I went to the site to see what numbers they use and the formulas. Here are some examples of what I found in that regard:

We adjust positive tests for the number of tests done. Then, we calculate an implied infection curve. This uses a known distribution of how much time passes between infection and a confirmed positive report.

Ok. Unless you are right there with a microscope or something else, how in the heck is anyone going to know for certain when someone gets infected?

Rt represents the effective reproduction rate of the virus calculated for each locale. It lets us estimate how many secondary infections are likely to occur from a single infection in a specific area. Values over 1.0 mean we should expect more cases in that area, values under 1.0 mean we should expect fewer.

Now here's some stuff from the FAQ:

I checked the site yesterday and it showed a different curve for my state, what’s going on? First, note that we changed the model significantly on June 19th.

To understand these regions, you need to understand that the model is searching for the best Rt curve of an infinite number of curves to explain the new case data that we are seeing. Of these infinitely many curves, there are some that are compatible with the data and others that are not. We show a single average curve, but the truth is that we’re not so confident that we can pick just one curve of all those curves. So, we show a range where we’re 80% sure the true curve lies. You'll notice this range is much larger in states with fewer cases. This happens because there are far more curves that can explain the small case counts than when case counts are large.

Finally, when trying to find the numbers and formulas, well they are just not there at all. You are more than welcome to go to their github (geeks know what this is) and see it, because it is admittedly that complicated:

In the simplest terms, it searches for the most likely curve of Rt that produced the new cases per day that we observe. It does this through some neat (and powerful!) math that is beyond the scope of this FAQ. In more complex terms: we assume a seed number of people and a curve of Rt over the history of the pandemic, we then distribute those cases into the future using a known delay distribution between infection and positive report. We then scale and add noise based on known testing volumes via a negative binomial with an exposure parameter for a given day to recover an observed series. We plan on publishing our code soon, so if you’re so inclined you’ll be able to run it, too.

So, to translate that to a layman's terms, "trust us, we're way smarter than you, don't believe the raw numbers, because our assumptions and 'code' are better." I am not going to hold much truck in someone's invented 'rating' from their invented code. I only put the plain numbers up and showed plainly my formula for all to see, not some 'code'.



Are the founders of Instagram Doctors?


In closing, the increase in infection rate might be from wearing masks, or it might be explained by the fact that I believe they're including the folks who test positive for anti-bodies into it. I believe that I read one of the numbers sites saying that they do not want those numbers included in positive tests.