Just wanted to share a little chart showing the likely effect of the mass BLM protests over George floyd compared to the COVID-19 recorded new cases count.

To be clear, I think Floyd's death was an injustice and I support the idea of opposing it at every level. But it was the number one biggest factor that caused the COVID epidemic to resurge out of control and we never recovered from the surge seen during the protest and even now this new surge we are seeing is partially fueled by the effects of those protests.

The irony here is the left have been the most vocal about COVID and blamed Trump for not seeing enough success in battling it as a central point in their entire presidential debate... yet they are also the ones who caused more loss of life and a more prolific spread of the diseases than anyone else when it served their agenda, and had the gall to try to blame that on Trump or republicans.

After seeing months of liberals abusing old ladies grocery shopping without a mask on and the like it is pretty disgusting, though typical, to see they are also the ones who caused more a problem than anyone else.

#COVID #COVID19 #Corona #Coronavirus #BLM #Protest @Science

@freemo I think that you have a clever perspective a lot of the time and enjoy reading your posts, but this one seems in bad faith with very sloppy reasoning. Given the inflammatory nature of it, I have to ask, are you just trolling?

@sergiopantalone Well depends.. I did try to make it a point to state that I do support the need and intent of the Floyd protests... But I even said at the time that it was extremely reckless and irresponsible to have mass gatherings during the middle of the worst pandemic in history.. Seeing how many have died as a result of that choice has of course bothered me greatly when no one listened to the warnings that were said for months prior about public gatherings.

I also found it very insulting that no responsiblity was taken and that democrat politicians even supported the protests rather than decry it, with photos of AoC blowing bubbles in a little kids face with her mast off for example.

So is it inflamatory.. as in, people will be upset by it... yes... But when people do wreckless things that cost the lives of 57,000 people, and when they **knew** before doing it that it would cost many lives (it was what was said for many months prior).. then I think people need to be a bit upset, they did wrong, and when you do something wrong that hurts so many people it is natural to be upset, to be "inflamed", and my only hope is that people will learn from it in the future.

I dont like either extreme of the political spectrum, as you know, that includes most liberals and conservatives in america as many on each side are at the extremes of the spectrum. But what I particularly despise about the liberal half of america is the constant hypocrisy... Doing as much or more evil than the right, and then pretending like the right is the worst inarnation of said offense imaginable. In this case that took the form of them blaming Trump for the deaths and verbally or even physically abusing people for not wearing a mask (even when maintaining social distancing) and yet in the very same motion being the single biggest cause of viral proliferation we had seen to date...

I am sorry,a nd while I appreciate your kind tone... on this I feel that people being inflamed should be the least of my worries, especially when so few people recognize the death and suffering they caused

@sergiopantalone By the way not sure if you saw my other post where I linked to this one...

But as I pointed out I did a lot of number crunching to verify that the bump we are seeing is in fact due to the protests. While science is never 100% certain, and in this case not peer-reviewed or anything to that extent, I know personally the numbers look pretty solid given my conclusion.

To be specific the number of people infected due to the protests would be 6,087,567.. the number who died as a consequence of the protests are 56,982...

So yea im sorry but its hard for me to not highlight this situation when it resulted int he death of 57,000 people.

@sergiopantalone Also, understand if you didnt already know, I have worked professional for the government and some private sector stuff on disease proliferation models in the past. In fact I designed a particular equation used in some of those models still used today. So again while not peer-reviewed, and should not hold the weight peer-review would hold, I did do my due diligence and do have the needed expertise to ensure that if i make an assertion like this that I am reasonably sure that it is a fair one as well as accurate.

@freemo I guess I didn't see your other post about the numbers. I also didn't know where you got the data from for your chart. Is that national or a particular subset?

@freemo As a fellow student of statistics I'm sure you know how difficult it is to tie correlation to causation. And in your anger I worry you haven't misinterpreted those results.

@sergiopantalone That seems like a leap of an assumption since I didnt describe the process I took to come to the conslusion I did. I posted it higher in the thread but ill copy and paste it here and delete that higher up post so it is linked to this responsE:

The chart shown is national (USA) the chart itself is compiled from 15 different sources but I worked with the raw data in doing my analysis, I only used the chart to illustrate the final point.

My process for confirming the cause of the bump was the protest was by looking at the same numbers across different cities in the usa and correlating those numbers against an approximation of the magnitude of the numbers in each city. My hypothesis was that in cities where protests did not take place in significant numbers would show the smallest initial relative change with possibly having a secondary characteristic of a skewed peak tot he right as infections spread from other cities with higher protests, eventually affecting the entire population the more skewed to the right you go. Also keep in mind I had to normalize this against the testing rate in various cities to ensure i ruled out any cities which did not have reliable data to pull from as well.

In addition to this I checked specifically the expected propagation model given the generation time of COVID-19 (5.0 - 5.5) and R0 (2.0).. keeping in mind while we do have different values for R0 they correlate with numbers of Tau that would result in the same R, so the specific numbers give the same results as other studies. From this I was able to account for precisely the delayed effect from the beginning of protests until when you first expect to see a rise in cases, and to the point where you would expect to see a peak.. All of which matches closely the data observed.

Finally I further confirmed the data by looking at other countries to see if there was a similar bump which would invalidate my results as one would expect it to be local to the united states, and other countries did not show a similar spike.

@freemo Thank you for your response and your patience. I don't mean to make assumptive leaps. My alternate hypothesis that it coincides with national holidays would also account for the propagation curve and the fact that it's not mirrored in other countries. I don't have access to your methodology for the varying cities (it was the chart that caught my eye) but I would like to know more about it. Again, thanks.

@sergiopantalone

Since I am working off of some proprietary tools it would be hard to give a complete copy of my work (and i do understand why that would make you more critical, as it should).. but I think i can relate the state-by state findings in a less rigerous way to at least illustrate the connection.

First though let me point out that your pointing to memorial day is very easily ruled out due to the generation time of the virus. It simply does not line up with the curve. Bhile the very first protests of any kind did start around the same time as memorial day, they were not particularly significant in number. If you look at a time line of protests and as they developed it wasnt until june 14th that the bulk of the protests from a nationwide perspective began. The date of memorial day is simple too soon to match the date, due to the generational time if that were an instigating factor cases would be observed increasing earlier than we saw when in fact they continued to decrease. However the generational time does match the life of the protests almost exactly as expected.

So next ill try to pull some images for this conversation. Keep in mind I didnt generate these images nor did i check their specific numbers. But they are fairly in line with the data source I used and look close enough to accurate to be useful for illustrative purposes here.

So first look at the attached image. As you can see California, New York Pennsylvania, florida were the places that had the biggest (as well as the largest) number of protests. This roughly aligns with my own data set. Of those five all but oregon had acceptable testing programs to pull from.

As would confirm my hypothesis all of the top 5 states show significant peaks at the expected time period to conclude it was due to protests.

In fact even if you normalize the cases for the population density and overall population they correlate very closely with the states that had the most protests. but more importantly when looking at this is looking at the time shift on their peak cases once rising on the graph. One would expect (and the data agrees) that states where the first generational cases begin for the resurgence will have their peak time shifted to the left, states that see secondary effects will have the peak shifted to the right.

As to be expected this lines up with the data also. New york for example had a 34% increase in cases from baseline during its peak and had its peak shifted to the left significant with a very sharp rise time, indicative of a ground zero event. The onset for the rise to begin was june 19th, exactly the generational period from the beginning of major protest events in the city of june 14th/15th reaching its initial. From first generation on june 15th we saw an increase in case count in new york of 34% over the next 19 days, which is one of the earliest onsets we see among states.

California shows a similar pattern of early onset, quick rise to peak, and significant relative change. In this case the initial onset of the peak and first generational symptoms was June 16th reaching its maximal peak on July 8th. California showed a 509% increase in relative case count in only about 22 days.

Floridas peak was July 13, with an over baseline rise of 1200%. and so on

In all these cases the peak of the spike was at least 2 weeks **sooner** than the national average, bearing in mind these states make up the bulk of that average as they, along with the other top ranking states that show similar patterns, have the bulk of the cases contributing to the spike. This pattern that the earliest onset of peak is only seen in states with significant protests and in fact in states where there were no significant protests the peak was very minimal to the point of almost not being present.

It is important to note when looking at other states many didnt have noticable spikes at all, but more important, where spikes were present they were time shifted significantly to the right of the mean by 2 weeks or more int he other direction. This suggests that while they did have cases result from the protests they were likely improted from other states and thus had a much smaller generation-0 which would be described and manifested as a delayed peak, exactly as we see it.

Moreover many of the states where we see delayed peaks but where the peaks are still noticeable are states in close proximity to states that have heavy protests. suggesting this was likely people commuting across state lines to protest and then bringing the disease back with them to their home state.

@freemo Thank you for the insight into your process, and for taking the time to share it. The only other thing I'm curious about is the steps you took to rule out spurious relationships. You said you normalized for population, but what about population density? Also, how did you take into account the dates of states reopening bars, restaurants and gyms? Did you factor in weather or tourism? I know you're using proprietary software but methodology is really important when making such bold claims.

@sergiopantalone These are all excellent questions and before I answer them I want to point out one thing, and please dont take this personally…

Consider your biases for a minute and how overwhelmingly obvious the conclusion should be , even without a full statistical deep-dive, that the protests should be quite obvious to any casual observer that it is the obvious cause.. ignoring the technical arguments consider the following

1)Memorial day is easily ruled out for several reasons

• most notably cases continued to drop for 16 days after memorial day, if this were to blame, given it was a nationwide event, we would see Generation one in 5 days and the onset of the curve, which didnt happen until more than 3 times that period

• While the relative change % might not be consistent the onset of the curve would be consistent across states if the triggering event could be traced to a single day.

• There were no large public gatherings due to coronavirus, so that means at best smaller gatherings were to blame.. obviously small gatherings are far less likely to be an integrating factor than mass protests crowded shoulder to shoulder in many cases in the street.

2) 4th of july is easily ruled out as well, it doesnt even occur until the peak is well underway and the generational period of 5 days would put the first cases at the 9th of july. By this point the curve stopped increasing and it leveled off, thus clearly ruling this out. also the above points for memorial day apply.

3) But more importantly.. seriously… we know and have been told countless times that even small gatherings are a huge risk factor for viral spread, we were discouraged to even have friends over in our home, and even in the supermarket to not be anywhere near eachother… Can you honestly tell me you are adamant about looking for alternative explanations when we literally jam packed ourselves shoulder to shoulder in the streets in every major city for days on end, with no other obvious candidates for a cause, like is this even something that should need to be proven in this level of detail.

All that said let me get back to your more specific questions… how did I rule out spurious relationships…

The only other thing I’m curious about is the steps you took to rule out spurious relationships. You said you normalized for population, but what about population density?

Well I stated that already for all the spurious relationships you have so far been able to propose as possible alternatives. But more importantly and more generally, the methodology used to analyze peak shifts to identify ground zero is a particularly effective method that is naturally much more resistant to spurious causes than other forms of analysis (such as simply looking at relative size of peaks).. th reason for this is when we see all of the cities with significant protests have significant left hand shifts that would mean the only way we could see that pattern due to a different effect is if there was some other event that was unique to only those cities and occuring on the same date as the onset of the protests, and which did not occur in other cities or occured 4 weeks later. That is a very unlikely scenario indeed.

For example consider if we saw that all the cities that I mentioned as the top candidates all happened to be cities that had the least public use of facemasks… even that would not explain the data observed because the only way that would work is if everyone in the city had suddenly stopped using facemasks the day the protests started, and then for some odd reason started using them again 2 weeks later.

Long story short this particular type of analysis for diseases factors simply cant be explained away very easily by spurious events without a pretty big coincidence.

You said you normalized for population, but what about population density?

While I did check against normalized data for population density, this was more out of curiosity on my part than due it being a valid approach in this case. specifically because population density is already baked into the underlying numbers I used during my analysis (which is typical in this type of analysis). In each case I used local state R numbers, keep in mind generation time is not effected by population density, only the R numbers are. Since the R numbers are derived as a baseline, and do not fluctuate as a disease progresses without some other factor playing a role (like a sudden use of masks).

Also keep in mind R numbers are far more precise than normalizing direct to population density as we do not know how individuals will move around.. some people will be protesting in their home city and simply local to the area, but many others will travel from nearby areas to join the protest and then bring the disease back. In all cases we would expect the local R number to hold true and be the conservative value, since a protest would, if anything, cause the R number to increase due to having a much higher density of people than normal.

So yes population density is accounted for.

Also, how did you take into account the dates of states reopening bars, restaurants and gyms?

I checked as best I could find the covid reopening schedule in several states, in fact i even posted it as a list sometime back on an earlier covid analysis I did (I will have to find it).. In order for a reopening to explain the events seen it would have had to have happened across all the top states that showed a left hand shift, so basically there would have to be changes in covid policy across half a dozen or more states all within just a few days of eachother (remember the generational period is only 5 days) to be able to explain these events. That was not the case here.

Did you factor in weather or tourism

I did not factor in weather or tourism, nor do I see how I would or how this could effect it. Again there would need to be a sudden change in weather occuring within a window of only a few days for it to be able to explain the sudden onset, which of course is not the case here, a rainy day or something isnt going to cause something like this.

As for tourism, its possible, but do you know of any tourism events that simultaneously affected the 5 states i listed all on the same day and didn’t effect other states. Unless you want to count the protests itself as a tourism event that is significantly higher than baseline I cant imagine how anything like that could or would be considered.

I know you’re using proprietary software but methodology is really important when making such bold claims.

To me saying “hey mass gatherings on an order of magnitude we havent seen in many years, and on a scale we just havent really seen in a long time, is likely the cause”… .especially saying that when every top professional had told us for many months prior “Even small gatherings will make this virus unmanageable, dont do” is not by any measure a “bold claim”… to me the claim is obvious, not even questionable really given how viruses work.. there shouldnt even be a need for me to do the level of rigour I did… So you might ask why I did it… simple people, even news papers, were making excuses left and right as to why the protests werent a bad thing WRT coronavirus.. to me this was just silly and obviously untrue, but it is hard to fight against the lies people tell themselves. This was a good cause so people are very eager to lie to themselves to try to find an excuse for it. So I felt given the amount of public sentiment that that was the case, and always being willing to question my own bias, no matter how obvious it might be, I decided to do a deep dive on the numbers and see if the numbers agreed with my own common sense judgement, of the doubts of others… Obviously you know my conclusion.