Told ‘ya:
Testing of the small devices, which can be worn on the end of a lanyard or carried in a handbag, follows limited take-up of an earlier smartphone-based system and has further fueled privacy concerns about contact tracing technology.
Source: Singapore plans wearable virus-tracing device for all – Reuters
Source: Calculated Risk: Comments on May Employment Report
Economists had forecast an additional loss of 8.3 million jobs in May, and an increase in the official unemployment estimate to 19.5%.
Actual for May: an increase of 2.5 million jobs and unemployment falling to 13.3%. Same for Canada too.
Economists and their computer models were off in space.
Since much of the country had not yet “re-opened” after public health sociopaths flattened the economy, this is a good number. By June, many more areas are re-opening – will be interesting to see the unemployment figures for June.
Continue reading Economics: Employment forecasts for May were in a different planetary system
Over 1,200 public health sociopaths signed on to this petition as of a day ago. Some say that not everyone who signed the petition is a legitimate public health person. However, there are social media posts like this one from an epidemiologist who clearly is in the field:
Today was the final straw for me. I no longer believe a word uttered by public health officials, epidemiologists and infectious disease specialists.
Not. One. Word.
I unsubscribed from my County’s daily public health newsletter, and when they asked for a reason, I told them: I no longer trust them.
Yes, over 1,000 public health sociopaths (some for sure) actually said that.
Public health no longer has any credibility and we are now ignoring them.
Continue reading I no longer believe anything from public health officials – or policeI updated my page of charts for tracking Covid-19 in Oregon. I have no expertise – but I prefer to use raw data rather than news reports which are heavy on fear, hysteria, assertions and speculation. When I started this, our state’s public health office was months away from providing public data and charts so that I could see the real picture.
This page is for “Entertainment purposes only” –> Oregon Covid-19 Situation in Charts (Unofficial)
During all of March, the state’s OHA was highly secretive and released little information. By April they began releasing some useful data (but not charts). By May they began to use Tableau to create online charts, and by June, they were finally producing sufficient charts that my DIY tracking page may no longer be needed. OHA public health has been consistently behind on everything – from their incomplete pandemic response plan to being late with public information to having no plan for unwinding their lock down.
Last month, I privately wrote some predictions for the rest of this year. One of those predictions was that these continued lock downs, well past the “Flatten the curve” milestone and which have led to mass unemployment, would lead to mass riots in the streets this summer. My timing and the ignition source was off a bit – but public health created a tinderbox that needed only a single match to explode. Minnesota police lit the match.
I feared the inconsistent, contradictory, incoherent and confusing messaging coming out of public health would lead to fiascoes, which did occur with regard to wearing face masks. People were shamed for wearing a mask, then shamed for wearing the wrong kind of mask, and finally, shamed for not wearing a mask. People have been verbally and physically assaulted, knifed and shot over mask wearing. “Karens” of the world have posted photos in online social groups to shame people in regards to their mask wearing. Everyone is becoming enraged over something.
Now the police blame the mandatory wearing of masks for mistakenly targeting, assaulting and arresting journalists. At least half a dozen were targeted with rubber bullets, point blank tear gas or arrested – for legally doing their jobs.
Continue reading Police blame the mandatory wearing of masks for assaulting the media
I’ve had a broken foot for months but the reason I could not get care was because our Democratic Authoritarian Supreme Leader, Kate Brown, banned non-emergency health care. I was not “skipping medical appointments” – our Supreme Leader had banned medical appointments.
I did not know I had a broken foot – only that it hurt a lot – walking caused immense pain. It was not life threatening so I did not get to a podiatrist until Dear Leader allowed doctors to practice medicine again, which meant May 13th . The diagnosis was “evidence of a stress fracture of the navicular”, “partial tear of the tendon”, and tendinitis.
Nearly half (48%) of those polled said someone in their family has skipped or delayed getting medical care during the coronavirus pandemic.
Source: Nearly half of Americans stressing and skipping medical appointments, survey finds – CNN
If this were treated early, I would be back to doing things. But it will now be many more weeks of healing. At least I know what the problem is and now know to stay off my foot as much as I can.
Continue reading Nearly half of Americans skipping medical appointments
The linked report is a very thorough analysis of what is being done in countries throughout the world in regards to cell phone data for Covid-19 tracking, and looks at a number of issues, particularly with regards to privacy.
Source: Mobile Location Data and Covid-19: Q&A | Human Rights Watch
I see so many problems – technology – both software and RF issues – usage scenarios, laws, privacy issues, and practical issues such as unenforceable quarantines via phone, false positives and insufficient participation and so on – that phone-based tracking apps will not provide meaningful benefits during the current calendar year.
At some point in the future, after much real world experimentation and a better understanding of how they work or do not work – and once issues have been fixed (if possible) – phone based tracking apps might be useful. Perhaps for a future pandemic or epidemic.
Right now this is an early software-focused project in Alpha test – using entire populations for a health experiment – without necessarily having informed consent about high false positive rates requiring unnecessary 14-day quarantines. The initial roll out to real world users will be an Alpha test phase. The apps that are officially rolled out in production about June 2020 will be Beta test – where we learn how these work in real world scenarios.
Related: Utah’s contact tracing app is about 8 weeks late to start testing, amid numerous problems. Sounds like a far too typical software project: over promised, under delivered, late, missing features, and will probably need more cash to get it done.
And
Public health officials might be losing interest in contact tracing apps as
the pandemic response has become a bitter lesson in everything technology can’t do and an example of Silicon Valley’s legendary myopia. States like New York, California, and Massachusetts, and cities like Baltimore and San Francisco, have looked carefully at cutting-edge contact-tracing solutions and largely said, “No thanks,” or “Not now.”
….
But public health officers are typically MDs and PhDs who aren’t dazzled by cool-looking software, especially if the pitch comes from people without public health backgrounds. They’re uncomfortable deploying untested technology during a pandemic, when glitches can cost lives.
https://www.wired.com/story/health-officials-no-thanks-contact-tracing-tech/
That story describes how the technologies used in China and Korea will not fly in the United States. This story points out exactly what I have said – that people pointing to Asian countries as a success of contact tracing apps have no understanding of what they are talking about – those scenarios are so different as to have no relevancy to the U.S.
In the end, the only place contact tracing apps might have a role to play is inside certain kinds of work places where groups of workers may share common areas for an extended period of time. And that’s it.
First:
Contact Tracing of Surfaces Across Time
Another problem with contact tracing apps is they cannot detect contacts across time. Some one sits on a bus seat or commuter light rail seat, coughs. Then gets up and leaves. Another person boards and sits in that seat and touches it with their hands. The BLE model is unable to detect this contact. Considering that the NYC subway is now thought to have been a major vector for diseases transmission, this is a serious short coming.
Another example – some one sits at a table at Starbucks, coughs on the table a few times and then leaves. 3 minutes later, someone else sits at that table and touches their hands on the table and later scratches their nose. The contact tracing app cannot detect surface contamination scenarios across time. While Starbucks might clean tables frequently, there is no guarantee.
There is no way to solve this problem using a BLE contact algorithm that does not store actual location data – the BLE tracking app only detects instantaneous “moment in time” contacts.
This week the CDC said that may be surface contamination is not a big source of infections so perhaps this is no longer a big factor.
Does it Matter? May be not?
And then perhaps none of this matters. In Utah, where they have traced the source of most Covid-19 patients’ contacts, about 60% were traced to close family contacts that had the disease and about 25% to close social contacts. That’s 85% of all traced contacts. There were not many random connection contacts leading to becoming infected. Originally, China thought about 60% were due to random contacts – but it might be appropriate to extrapolate that – from congested cities where much of the population travels via public transit – to many U.S. states (like Utah) where public transit use may be just 1-2% of the population.
Moving Further Apart Can Increase Signal Strength!
Another interesting problem with BLE-based tracking apps. They rely on the BLE 1 mw discovery process which can send a signal out to about 10 meters. They combine this with the Received Signal Strength Indicator to estimate that a contact is within about 6-7 feet. In a pure “free space” environment, signal strength can approximate distance. But the real world is not a “free space” environment.
First, if the phone is in your left pocket and you stand several feet from another person on your right, whose phone is in their right pocket, the direct path may have lost 20 db of signal strength due to your body blockage. The software thinks the two of you are far apart when you are actually standing next to each other.
Second, in the real world, radio signals do not travel in a straight line from transmitter direct to receiver. Instead, signals reflect off of objects in the environment. Some times the reflected signals arrive at the receiver in a way that increases their apparent strength and in other cases they arrive in a way that decreases their apparent strength. This is known as “multi-path”.
Think of a pond of calm water. Toss in a rock and see how the waves move across the surface. What happens when the waves strike the shore or another rock – they typically reflect or bounce back creating a new wave front. In a complex environment, there are many wave fronts traversing that water. In some places, wave heights may combine momentarily to create a higher wave, while in others they may combine to create a deeper trough.
The effect of this in the Bluetooth contact tracing app scenario is that – and this has been tested in the real world – there are real scenarios where people moving further apart see a stronger received signal strength!
The software erroneously thinks these two people have increased their risk when they are moving further apart!.
The opposite can also occur – as people move closer together, due to multipath, the devices may sense a drop in signal strength and erroneously think there is less risk.
The Need for Controlled Trials
This is why this technology must be tested in the real world before it is rolled out to entire populations. The bottom line assessment is: Does it detect actual contacts we need to worry about – without missing contacts we do need to worry about?
The Gold Standard: Does it result in an actual, measured decrease in the spread of Covid-19 and a reduction in mortality?
To answer those questions requires controlled trials, just as controlled trials are required for the use of hydroxchloroquinine in the treatment of Covid-19.
Some will argue no controlled trial is necessary as the use of the app is harmless. However, if you are periodically placed in 14-day quarantines – unnecessarily – harming your income and mental health, is that truly harmless?
If not tested, deploying smart phone contact tracing apps is a mass population medical experiment without informed consent – which is illegal in the United States. But given we are dealing with public health, laws no longer matter, of course.
I previously wrote about covid tracking apps and that what a “tracking app” is varies tremendously by country. Please read that first.
There is another issue that crops up – and that’s the effect of conditional probability (or Bayes’ Theorem). I am still reviewing this to see if I did something wrong (I think I did do some things wrong – see Afterword – the idea is probably sound but the calculations may be wrong) – but so far with reasonable assumptions, phone-based covid-19 contact detection apps seem unlikely to provide a benefit.
Singapore is the only country to have used a Bluetooth-based contact app so far. At the time of this writing, the U.K. is running a trial of BLE-based tracking apps.
Singapore achieved only a 12% participation rate. (Update: as of end of May it is up to 25%, which is still too small).
The probability that a person has the app on their phone is then p=0.12. The probability that a 2nd person has the app on their phone is also p=0.12. The probability that two strangers coming within close range both have the app installed is just .0144 or 1.44% – almost zero. (Update: at the 25% participation rate, this works out to 6.25%, which is still nearly zero).
There is another problem with tracking apps due to Bayes’ Theorem and that the true incidence of Covid-19 in the sample population may be very low.
Out of 500 potential contacts, 10% or 50 might be flagged as false positives and 1 person might be flagged as a true positive. We have now flagged 51 people in the population. (But see Afterword for the problem with this calculation.)
But we know we expect only 1 true positive out of all those sampled – but we now have 51 positive results. We do not know which one of those 51 is the true positive. For any individual in that set, the odds that they are the actual true positive is 1/51 or just 1.96%.
Continue reading Why “Covid-Tracking Apps” will probably not work