If that turns out to be the norm then we are all pretty much screwed. That to me sounds like it's mutating and people can get it over and over as it changes. Almost sounds like one of the virus movies where terrorists make a deadly virus and release it upon the population.
I’ve searched and only find a very few articles on people “getting it a second time”. And almost all of them bring up the possibility that it was the same infection that reactivated somehow. That’s out of millions of confirmed cases worldwide. As much as the media seems to love negative and sensational stories I would think they’d jump all over people getting COVID a truly second time if it were happening in any documented, confirmed way.

My Doctor and I were discussing this the other day at my check up. He said we won't get herd immunity because they are seeing that the antibodies are only staying in the system 3-4 weeks. After that...you can be reinfected.

My Doctor and I were discussing this the other day at my check up. He said we won't get herd immunity because they are seeing that the antibodies are only staying in the system 3-4 weeks. After that...you can be reinfected.

Not remotely true. Numerous studies show that T-cell immunity is robust and lasts months, if not years. Tests done with people who survived SARS shows that people mounted a defense *more than 13 years later*. We are *supposed* to lose antibodies over time, otherwise our lymph nodes would be friggin gigantic.

Here's some peer reviewed and other articles that go into more detail about this:

https://www.nature.com/articles/s41586-020-2550-z

https://www.cell.com/cell/pdf/S0092-8674(20)30610-3.pdf

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2683413/

https://immunology.sciencemag.org/content/5/48/eabd2071

What are the odds that some of today’s cases belong to yesterday’s totals? Again, thats why a 7 day running average is useful...

My Doctor and I were discussing this the other day at my check up. He said we won't get herd immunity because they are seeing that the antibodies are only staying in the system 3-4 weeks. After that...you can be reinfected.
Mine have stayed high for four months. Yet another thing that can’t be taken as an absolute one way or the other.

What are the odds that some of today’s cases belong to yesterday’s totals? Again, thats why a 7 day running average is useful...

I suppose it could be possible that some of the cases reported today didn't make the cut for reporting time yesterday. Still, today's 965 is much closer to the 7 day average of 718 than yesterdays reported 314.

Here is a graph of the running 7 day average for cases and deaths as reported by State of OK since June 1st.

https://i.imgur.com/vhIUQdo.png

I suppose it could be possible that some of the cases reported today didn't make the cut for reporting time yesterday. Still, today's 965 is much closer to the 7 day average of 718 than yesterdays reported 314.

Here is a graph of the running 7 day average for cases and deaths as reported by State of OK since June 1st.

https://i.imgur.com/vhIUQdo.png

It does look like new cases are starting to plateau. There is definitely a slope change in there suggesting a decreasing rate of increase. Let’s hope masks improve it further.

+1204.

Highest ever (real) one-day increase, and a new high in the 7-day average (860).

+1204.

Highest ever (real) one-day increase.

Welp, that explains Friday's low number. This isn't going anywhere anytime soon.

https://twitter.com/KOCODillon/status/1287420281028595714


We knew the 7-day average would rise today almost no matter what because of reporting issues last Sunday. But this is not only a record increase overall, it's also a stunning increase for a Sunday.

The previous Sunday record was 478 on 6/21

1500 some time this week. We got this. 314 on Friday lol. Oklahoma's quickly becoming the new hotspot imagine that.

I think some of Friday's numbers have bleed into the last couple days though

+1204.

Highest ever (real) one-day increase, and a new high in the 7-day average (860).

https://techcrunch.com/wp-content/uploads/2019/02/nakedgun.gif?w=1390&crop=1

Guys, don’t panic on today’s numbers. When you think about the global trends of our covid numbers, Sunday has historically been on of the lowest days of the week for reported numbers. This data point is so out of the norm that it makes zero sense. You can say the same for the report a couple of days ago. It was so anomalously low, that we all discounted it.

If you take the totals from the past 3 days and average them, we’re looking at around 800 per day. That falls in line the the global trends that we are plateauing in our daily rates (hopefully).

My question is how did our reporting suddenly get so crappy??

I agree that it is anomalously high and counteracts the anomalously low report from Friday, but the 7-day average continues to rise. I guess we'll see this week if the slow down in increase is real or just some noise. Although really, plateauing at 800-900 and remaining there as we move toward re-opening schools is not really starting us off in any sort of acceptable place or what seems like an inevitable surge.

I agree that it is anomalously high and counteracts the anomalously low report from Friday, but the 7-day average continues to rise. I guess we'll see this week if the slow down in increase is real or just some noise. Although really, plateauing at 800-900 and remaining there as we move toward re-opening schools is not really starting us off in any sort of acceptable place or what seems like an inevitable surge.

I suggest that you look at our curve again. There has been a clear decrease in the rate of change. The curve is showing that we may soon peak on this deal if you use other analogous cities

Guys, don’t panic on today’s numbers. When you think about the global trends of our covid numbers, Sunday has historically been on of the lowest days of the week for reported numbers. This data point is so out of the norm that it makes zero sense. You can say the same for the report a couple of days ago. It was so anomalously low, that we all discounted it.

If you take the totals from the past 3 days and average them, we’re looking at around 800 per day. That falls in line the the global trends that we are plateauing in our daily rates (hopefully).

My question is how did our reporting suddenly get so crappy??

Probably due to scaling.

It was a lot easier to track when we had like 100 cases a day, which is now 10x that # now.

Yes, it's best to focus on the 7-day rolling average.

Which of course, is horrible.

So how are people getting the virus? According to OKC- County Health Dept, contact tracing during July, the 4 hot spots for the virus have been faith based venues, restaurants, office settings and daycare. It indicated that bars gyms, and warehouses are still among areas of spread.

Only the restaurant part concerns me. Not often, but sometimes I go to a restaurant for dinner but always go at a non-busy time such as no later than 5 pm. After being seated the waiter asks me to have my mask on when I leave the table, due to city ordinance. So on one occasion someone going to the restroom would walk past me without a mask on.

I think we're all suspense in coming months to see how well reopening of schools, universities and sports play will go. Whatever the outcome, it will surely be useful in gathering a better understanding of the virus.

It does look like new cases are starting to plateau.

Nope.

Nope.

Great commentary. Please, show on the chart above how daily cases are still skyrocketing out of control. Clearly, the seven day average is leveling out.

I suggest that you look at our curve again. There has been a clear decrease in the rate of change. The curve is showing that we may soon peak on this deal if you use other analogous cities

We never bent the curve. we only kind of flattened it sort of a little. Then we did stuff and didn’t do stuff that caused our numbers to shoot up for two straight months with no government response besides sundry mask ordinances.

There won’t be a bent curve until something is done to make it bend. Do you see Governor Stitt doing anything?

A flattened curve at an unsustainable number isn’t good either but we haven’t peaked.

Great commentary. Please, show on the chart above how daily cases are still skyrocketing out of control. Clearly, the seven day average is leveling out.

It isn’t always a straight line, and all data points increase every single week. Are they completely out of effing control or just totally out of control? Who cares? The situation is out of control.

Are you happy with these numbers? What do you think is going to happen when school starts?

I never said we peaked. I said that we’re probably getting close to peaking. We’re starting to plateau. Clearly we have bent the curve, but whatever you want to yourself. Go run a derivative function on the 7 day average and tell me what you see? It will show that your rate of change has slowed. Whether that’s real or not is impossible to know given our issues with reporting numbers lately. I will say that is likely real, as our curve is behaving very similarly to nearby states.

I never said we peaked. I said that we’re probably getting close to peaking. We’re starting to plateau. Clearly we have bent the curve, but whatever you want to yourself. Go run a derivative function on the 7 day average and tell me what you see? It will show that your rate of change has slowed. Whether that’s real or not is impossible to know given our issues with reporting numbers lately. I will say that is likely real, as our curve is behaving very similarly to nearby states.

Ok, I guess we have a different view of the word bent. I see what you are saying and I am impressed by your mathematical and science knowledge but I take little comfort from what you are saying. The situation in Oklahoma is spiraling out of control. New cases and hospitalizations rise weekly. And now, deaths are rising. Our health department continues to report bogus recovery statistics that the CDC does not recognize, and there are ill-timed gaps in reporting. In some cities it takes several days to schedule a test and several more days for results. And, our governor is in 24/7 Trump re-election mode and is completely abdicating his primary job, which is to protect the citizens of this state

I do not need to survey a complicated math equation to say any of the above.

From https://twitter.com/KassieMcClung:

http://www.okctalk.com/images/pete/covid072620a.png

This looks like it’s surging up at the same rate it was previously.


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I never said we peaked. I said that we’re probably getting close to peaking. We’re starting to plateau. Clearly we have bent the curve, but whatever you want to yourself. Go run a derivative function on the 7 day average and tell me what you see? It will show that your rate of change has slowed. Whether that’s real or not is impossible to know given our issues with reporting numbers lately. I will say that is likely real, as our curve is behaving very similarly to nearby states.

Certainly hope you're right, as the last time it looked like rate of change slowed (A), we saw a huge leg up until (B) happened.

Sheesh, I need a refresher on derivatives. Have you already calculated it? I believe I can add that to my spreadsheet and plot it over time to see how deaths & cases change.

https://i.imgur.com/E13HeSy.png

Certainly hope you're right, as the last time it looked like rate of change slowed (A), we saw a huge leg up until (B) happened.

Sheesh, I need a refresher on derivatives. Have you already calculated it? I believe I can add that to my spreadsheet and plot it over time to see how deaths & cases change.

https://i.imgur.com/E13HeSy.png

These large endpoints, like today’s numbers, can really negatively affect trend analysis. Any derivative you calculate including today’s numbers will have a very large affect. I know the common way to analyze this data has been to apply a 7 day running average which smoothes the curve; however, our tests are delayed up to 10 days in some cases. I wonder if a 10 day running average would be better.

Even better than running averages, I wonder what the data would look like if you binned it instead. My suggestion is to pick a day. Any day. Doesn’t matter. I propose Friday’s as the numbers decrease over the weekend and are captured in Tuesday’s. Take Friday, and sum all the numbers for the previous week. So you’ll bin the numbers by week. Week 1, week 2, etc. Plot that curve. I bet it will look nicer than the 7 day running average.

These large endpoints, like today’s numbers, can really negatively affect trend analysis. Any derivative you calculate including today’s numbers will have a very large affect. I know the common way to analyze this data has been to apply a 7 day running average which smoothes the curve; however, our tests are delayed up to 10 days in some cases. I wonder if a 10 day running average would be better.

Even better than running averages, I wonder what the data would look like if you binned it instead. My suggestion is to pick a day. Any day. Doesn’t matter. I propose Friday’s as the numbers decrease over the weekend and are captured in Tuesday’s. Take Friday, and sum all the numbers for the previous week. So you’ll bin the numbers by week. Week 1, week 2, etc. Plot that curve. I bet it will look nicer than the 7 day running average.

Is it your goal to make it “look nicer?” If so, why? Whose interest does that serve?

We already have elected officials asleep at the wheel and a huge volume of people wandering around, claiming this is a hoax. Do we really need to get all academic with graphs when it should be enough to state that our cases, hospitalizations, and now deaths, keep rising beyond a sustainable level?

Is it your goal to make it “look nicer?” If so, why? Whose interest does that serve?

Some people don’t understand that factors like demand and testing availability and data entry issues and many other things may affect the daily reports. So some people may look at a “messy” graph that sometimes jumps all over the place and decide “look at that mess, how can they claim anything that is that variable could be accurate” and dismiss it out of hand. By making the graph less volatile, it may make it look ‘more accurate’ to folks like that.

At least I interpreted the comment to mean “make the graph look better to look at” rather than “make the numbers appear better”.

These large endpoints, like today’s numbers, can really negatively affect trend analysis. Any derivative you calculate including today’s numbers will have a very large affect. I know the common way to analyze this data has been to apply a 7 day running average which smoothes the curve; however, our tests are delayed up to 10 days in some cases. I wonder if a 10 day running average would be better.

Even better than running averages, I wonder what the data would look like if you binned it instead. My suggestion is to pick a day. Any day. Doesn’t matter. I propose Friday’s as the numbers decrease over the weekend and are captured in Tuesday’s. Take Friday, and sum all the numbers for the previous week. So you’ll bin the numbers by week. Week 1, week 2, etc. Plot that curve. I bet it will look nicer than the 7 day running average.

You can affect trend lines with algorithms based on sensitivity of changes. People need to quit trying to create spin without complete knowledge of how the reporting is done. Anybody can clearly see we are in a state of emergency exacerbated by the head in the sand positions of a certain segment of our society and "leadership". Reality is a hard master. It doesn't care what you believe it only cares what is. Time to believe reality and not myths.

Did we really have a July 4th peak?

Is it your goal to make it “look nicer?” If so, why? Whose interest does that serve?

We already have elected officials asleep at the wheel and a huge volume of people wandering around, claiming this is a hoax. Do we really need to get all academic with graphs when it should be enough to state that our cases, hospitalizations, and now deaths, keep rising beyond a sustainable level?

No absolutely not. This data is messy. There are lag times, testing errors, and a host of other problems. Plotting these data as we have been can lead to misinterpretations of the data. This is common issue in data analysis for noisy data. Smoothing doesn’t necessarily help with this. It kinda helps, but you can still draw bad conclusions from these graphs.

What I’m asking is whether there are other ways to view the data that may help us better understand what’s really happening out there. I’m not trying to fit a narrative.

And yes, it’s absolutely necessary to get “academic” with graphs and stuff. That’s what we should be doing with this data. If people can’t understand the basics of trend analysis, scientific methods, etc, then that’s on the education system....which is probably part of the reason why we’re in this mess to begin with.

Again, you are ignoring the fact that your basic thesis does not change what is actually happening. We don’t need to look at a graph to see that. Regardless, two separate graphs were supplied that seem to undermine your claim.

Again, you are ignoring the fact that your basic thesis does not change what is actually happening. We don’t need to look at a graph to see that. Regardless, two separate graphs were supplied that seem to undermine your claim.

Ugh...again, you fail to see where I’m coming from. You’re taking the referenced graphs at face value. You’re taking them to be accurate which they’re not. It’s impossible to know what’s really going on with time-based data when the data is entered at incorrect times and/or values.

What I’m proposing is not a thesis. It’s a hypothesis. I have no clue what my suggested graph will show. It may look identical to what’s been published today. It might, however, be a smoother representation of long-term trends, and we may be able to better interpret what’s going on. This could help spur better conversation on these boards.

These numbers are important but don't forget that this is epidemiology and not statistics. You can't crunch the numbers and apply graph smoothing or directional analysis unless you understand what the numbers mean. Instead, just go back to the OSDH graphs which update cases based on the date of onset. That removes most of the errors in the data:
https://looker-dashboards.ok.gov/embed/dashboards/70

Again, you are ignoring the fact that your basic thesis does not change what is actually happening. We don’t need to look at a graph to see that. Regardless, two separate graphs were supplied that seem to undermine your claim.


Also, how can you even possibly know what’s going on without looking at the data? How do you look at data?...you look at data via graphs and charts which is what we’re talking about here.

Delete

These numbers are important but don't forget that this is epidemiology and not statistics. You can't crunch the numbers and apply graph smoothing or directional analysis unless you understand what the numbers mean. Instead, just go back to the OSDH graphs which update cases based on the date of onset. That removes most of the errors in the data:
https://looker-dashboards.ok.gov/embed/dashboards/70

This is an interesting graph. I noticed it last night but wasn’t sure that I could trust it. It actually shows our total cases have peaked and are actually dropping. Is that correct? Interesting if true.

Here are the weekly totals (defined as Monday-Sunday) since the start of this thing, up through and including today. Data is from CovidTracking, which seemed to be the most reliable data I could find (not sure how they're handling the weird multi-day report compared to other sites, though).

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Derivatives on data like this will be quite sensitive to how you define the width of the bin and I didn't want to bother with the assumptions involved with fitting polynomials to the data, but summing the data to be weekly should help negate the day-to-day biases. In this case, here is the change in weekly totals:

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So, there's some movement, but nothing I would call an obvious or substantial slowing down, yet.

Finally, here is our weekly change in cases normalized by the total number of cases (which is less meaningful than it appears given "recoveries", but I digress). Other than the large numbers early on due to the very low number of existing cases, our rate the last month or so has been remarkably steady at about 0.19 (that is, we're adding about 20% of our total cases week-over-week).

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Sorry for the poor graph quality. Blame Google Sheets, lol.

This is an interesting graph. I noticed it last night but wasn’t sure that I could trust it. It actually shows our total cases have peaked and are actually dropping. Is that correct? Interesting if true.

I find these charts highly misleading. Results frequently take 5-10 days to come in, and this plots things as a function of symptom onset. So, given a) the delay in getting and reporting test results and b) the fact that it takes symptoms a variable number of days to come on, it will always be the case that the peak in symptom onset was a number of days ago with much fewer cases of reported symptom onset within the recent past. That chart has always bent sharply downward no matter when you look at it, with the data for a recent date "filling in" as time goes on. Even the doctors at the OKC City Council meeting called it potentially misleading, although it has value for epidemiological reasons, of course.

^

For that graph to be valuable, you need to chop off at least the last two weeks given the lag in testing and other factors.

I find these charts highly misleading. Results frequently take 5-10 days to come in, and this plots things as a function of symptom onset. So, given a) the delay in getting and reporting test results and b) the fact that it takes symptoms a variable number of days to come on, it will always be the case that the peak in symptom onset was a number of days ago with much fewer cases of reported symptom onset within the recent past. That chart has always bent sharply downward no matter when you look at it, with the data for a recent date "filling in" as time goes on. Even the doctors at the OKC City Council meeting called it potentially misleading, although it has value for epidemiological reasons, of course.

The value of the chart is that it's accurate data that is updated and backdated as cases are reported. Politicians don't like it because they can't spin day by day variability to their benefit, but that's not the point of the data. We need to see accurate information to make decisions.

The value of the chart is that it's accurate data that is updated and backdated as cases are reported. Politicians don't like it because they can't spin day by day variability to their benefit, but that's not the point of the data. We need to see accurate information to make decisions.

I can assure you I've looked at this exact chart for weeks and months now and it has always been the case that it bends sharply downward in the last week or so because of the aforementioned reasons. This is not political bias, it's an accurate understanding of the data being presented.

But go off, I guess.

These large endpoints, like today’s numbers, can really negatively affect trend analysis. Any derivative you calculate including today’s numbers will have a very large affect. I know the common way to analyze this data has been to apply a 7 day running average which smoothes the curve; however, our tests are delayed up to 10 days in some cases. I wonder if a 10 day running average would be better.

Even better than running averages, I wonder what the data would look like if you binned it instead. My suggestion is to pick a day. Any day. Doesn’t matter. I propose Friday’s as the numbers decrease over the weekend and are captured in Tuesday’s. Take Friday, and sum all the numbers for the previous week. So you’ll bin the numbers by week. Week 1, week 2, etc. Plot that curve. I bet it will look nicer than the 7 day running average.

Didn't try binning, need to read instructions first. But... did a combined plot of 7 day, 14 day, and 21 day case averages. It does tend to iron out some of the lumpiness with recent volatility. I thought about doing a 10-day trend, but sticking with multiples of 7 allows equal # of variances due to the "weekly" nature of the data. (Low Sun/Mon, high Tues.)

https://i.imgur.com/kTRXsIo.png


If you look at the Day over Day (DoD)% Change of the 7-day case average, and fit to a logarithmic trend (Excel), it HAS trended downward. However... I don't really like this measure. I was just curious to see what it would look like over time.

It simply calculates New-Old / Old where New = Today and Old = Yesterday. While this could be a valid measure on a per-day basis, trending it over time simply tells us: "Today's cases changed X% from yesterday's cases". It is also sensitive to the irregularities in daily reporting.

Still, a consistent long term value of this measure below zero would be a very good sign.

https://i.imgur.com/05NXPoa.png

I can assure you I've looked at this exact chart for weeks and months now and it has always been the case that it bends sharply downward in the last week or so because of the aforementioned reasons. This is not political bias, it's an accurate understanding of the data being presented.

But go off, I guess.

I don't think you're understanding the graph. Of course there will be fewer people reporting that they have symptoms of Covid-19 starting yesterday than a week ago. As those cases are reported in the following week though, yesterday's number is changed to reflect the new cases. That's how it can show us accurate data and trends.

Edit:
I apologize if my comment about politicians offended you but people have been cherry picking low (and high) daily case reports to further their narrative and it's frustrating.

I don't think you're understanding the graph. Of course there will be fewer people reporting that they have symptoms of Covid-19 starting yesterday than a week ago. As those cases are reported in the follow week though, yesterday's number is changed to reflect the new cases. That's how it can show us accurate data and trends.

But not until at least two weeks have passed for every data point on that graph.

Which also means the last two weeks are always going to be way under-reported.

But not until at least two weeks have passed for every data point on that graph.

Which also means the last two weeks are always going to be way under-reported.

Excellent visual way to demonstrate this problem. The same problem occurs with deaths and death reporting. They very often do not occur the day they are reported by the state, making it always appear they are "going down":

Screenshot from:
https://www.docdroid.net/snNC3wY/covid-trends-usa-pdf#page=10

https://i.imgur.com/p4vF8os.png

Dang! You guys are stepping up your game. I’m now watching the winter soldier with my son, so I’m not going to comment much until I can take a deeper look. Great work and great conversation!!

But not until at least two weeks have passed for every data point on that graph.

Which also means the last two weeks are always going to be way under-reported.

The purpose of the graph is to report what day symptoms for known cases were reported, which can more accurately identify what day the person was infected (a week or so earlier) and understand the spread. If it helps though, yes you can just chop off the last week of data and pretend that number is the number from today's executive report. It will likely still give you a more accurate idea of what's going on than trying to manually account for reporting delays and other variability.

The purpose of the graph is to report what day symptoms for known cases were reported, which can more accurately identify what day the person was infected (a week or so earlier) and understand the spread. If it helps though, yes you can just chop off the last week of data and pretend that number is the number from today's executive report. It will likely still give you a more accurate idea of what's going on than trying to manually account for testing delays and other variability.

Fair enough!

But really, the last two weeks are always going to be incomplete because there are plenty of reports of testing taking 10 days or more.

Here are the weekly totals (defined as Monday-Sunday) since the start of this thing, up through and including today. Data is from CovidTracking, which seemed to be the most reliable data I could find (not sure how they're handling the weird multi-day report compared to other sites, though).

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Derivatives on data like this will be quite sensitive to how you define the width of the bin and I didn't want to bother with the assumptions involved with fitting polynomials to the data, but summing the data to be weekly should help negate the day-to-day biases. In this case, here is the change in weekly totals:

16282

So, there's some movement, but nothing I would call an obvious or substantial slowing down, yet.

Finally, here is our weekly change in cases normalized by the total number of cases (which is less meaningful than it appears given "recoveries", but I digress). Other than the large numbers early on due to the very low number of existing cases, our rate the last month or so has been remarkably steady at about 0.19 (that is, we're adding about 20% of our total cases week-over-week).

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Sorry for the poor graph quality. Blame Google Sheets, lol.

Great analysis. On that last plot, if you max out your y-axis to something about half of what it is, I bet we could see more variability in recent weeks. There’s so much noise in this data that it’s really hard to make any detailed analysis without fine tuning the bin size for the derivative calculations.

Dale Bratzler of OU weighs in:

https://m.facebook.com/story.php?story_fbid=3978673208827675&id=100000551045034

Didn't try binning, need to read instructions first. But... did a combined plot of 7 day, 14 day, and 21 day case averages. It does tend to iron out some of the lumpiness with recent volatility. I thought about doing a 10-day trend, but sticking with multiples of 7 allows equal # of variances due to the "weekly" nature of the data. (Low Sun/Mon, high Tues.)

https://i.imgur.com/kTRXsIo.png


If you look at the Day over Day (DoD)% Change of the 7-day case average, and fit to a logarithmic trend (Excel), it HAS trended downward. However... I don't really like this measure. I was just curious to see what it would look like over time.

It simply calculates New-Old / Old where New = Today and Old = Yesterday. While this could be a valid measure on a per-day basis, trending it over time simply tells us: "Today's cases changed X% from yesterday's cases". It is also sensitive to the irregularities in daily reporting.

Still, a consistent long term value of this measure below zero would be a very good sign.

https://i.imgur.com/05NXPoa.png

Really great plots. I would like to see this going back a couple of months to remove any bias from recent misreported data, but I understand if you don’t have the time. Btw, what software are you using?

Edit: I would be curious to see how the second graph looks in April/May when our cases were declining before ramping up. That may be a good place to ground truth the interpretation.

Lol at everyone ignoring Bratzler’s comments about the data. Says a lot.

Lol at everyone ignoring Bratzler’s comments about the data. Says a lot.

Sorry sooner, there was no exerpt and I usually don't click on links in this thread because there's no telling where you might end up! =P

Which part of Dr Bratzler's comments were you referring to? The following jumped out at me with all the efforts people are taking to "correct" the daily reports and my crusade to point out that it's already being done for us:

"I am often asked to comment on whether some event (Memorial Day, Rally, Protests, July 4) could be linked to the new spike in cases. Honestly, without knowing when the tests are being done, it is exceedingly difficult to correlate events with spikes. We know clearly now that there are often lengthy delays between when a test is done on a person, and when those results may be reported as negative or a new case by OSDH in their daily reports."

https://www.news9.com/story/5f1df58ea717d00d80c4a709/suicide-rates-in-oklahoma-spike-due-to-covid19. Sad situation all the way around.

How to stop Covid-19:


https://threadreaderapp.com/thread/1287524301499965441.html

It's really not that hard, with the right leadership.....



STAY SAFE WEAR MASKS

https://www.news9.com/story/5f1df58ea717d00d80c4a709/suicide-rates-in-oklahoma-spike-due-to-covid19. Sad situation all the way around.

The solution to any real or perceived mental health crisis is to control the spread of the virus. The solution to the very real economic and employment collapses is to control the virus. Controlling and largely eradicating the virus is the only way our country will return to a semblance of normality.



STAY SAFE WEAR MASKS

Lol at everyone ignoring Bratzler’s comments about the data. Says a lot.

You posted a facebook link at 9pm, and you're upset that people hadn't replied to your post by 2am. How many people do you think are reading this thread between those hours?