crushthecurve
Existing contact tracing apps use Bluetooth which can't be used to determine proximity with any reliability - solid objects (particularly human bodies) absorb significant signal.
Unless all protestors were holding their phones up high for unimpeded line-of-site connections then even protestors next to each other could 'appear' 20-30m away.
In most cases (especially in a protest situation) all Bluetooth-based contact tracing apps can tell you is that two devices are in Bluetooth range (so accuracy of ~30m?).
However digital contact tracing has a fatal flaw: Bluetooth cannot be used to reliably estimate proximity in dynamic, real-world scenarios as objects (especially human bodies) absorb huge amounts of the signal.
In many scenarios this can make two people sitting next to each other look like they're 10-20 metres away compared to line-of-sight equivalents (just by having a phone in a pocket, handbag, or even next to a head taking a call). You can easily see this using, for instance, Apple's Bluetooth Explorer tool as part of Xcode developer tools [1] (or any of the bluetooth signal strength tools in the Play / App Stores).
You don't have to rely on DIY tests from the internet though. While they're extremely static tests, the Singapore TraceTogether team did some field studies highlighting the significant variability across hardware [2]. Their tests ended in a plea for factory calibration data from hardware manufacturers.
The Singapore team has talked about false positives in depth as a major issue (one was someone in a different apartment, because bluetooth goes through walls), which is why they set a hard, low RSSI value to reduce false positives - this means a lot of true positives will be missed too.
The key Australian dev revealing significant issues in Australia's COVIDSafe app also acknowledged the major limitations of BLE. [3]
The problem of course is you have a situation where you cannot determine if a contact is epidemiologically interesting, because accuracy in real-world situations is really down to the 20-30 metres of Bluetooth range, even over longer time-frames.
This means you either have a huge caseload for human tracers to sort the signal from the noise (and this relies on the memory of all participants) or you have some kind of automated system (such as amber alerts that the NHS talks about) and the challenge there is that no-one knows if they're really interesting epidemiologically, as no-one can tell where each party was in the context.
A recent series of talks by bluetooth experts is extremely informative.
In one, an expert discusses all the significant sources of error which creates the huge variability you can see in DIY tests at home. [4]
There are other great talks in that video, but Jen Watson - who leads a team at MIT engaged in advanced signal processing - delivers a good brief talk of the issues, hoping to use statistical analysis - using detection theory of fluctuating signals to estimate interesting contacts. [5]
The takeaway from all this though is that it's a hard problem, and in Watson's talk she quickly moves on to thinking about additional future capabilities (such as features in upcoming Bluetooth standards) that might help improve the resolution.
This does leave us with a large current problem though. Tracking apps have been thoroughly oversold with little evidence of usefulness, and in the case of the UK and Australia government authorities have refused to publish the algorithms they are using to determine proximity from an RSSI value and a phone model.
There is nothing sensitive about this apart from the fact it may reveal the system is not useful for the stated purposes.
[1] https://twitter.com/crushthecurve_/status/125911361479693926...
[2] https://github.com/opentrace-community/opentrace-calibration...
[3] https://twitter.com/jim_mussared/status/1255498092239036417
Due to all the hardware and environmental factors, it really works as a large spreadsheet of all devices in Bluetooth range over the last 21 days (in the case of the Australian COVIDSafe app).
All it can do to grasp at the environmental context is to record the phone model, and the RSSI over time.
In a dynamic, real-world environment that will vary hugely, especially on public transport, as human bodies could be in the exact same close spot, but due to phone position and rotation the RSSI will vary wildly (as mentioned in the video), making two people close to each other actually look 20 metres or more away.
The huge amount of contacts each have to be manually contacted and interviewed to determine whether they're epidemiologically relevant. That also relies on the recall of the infected and the false 'close contacts' who are at risk of having to isolate for up to 14 days regardless of test or symptoms (according to a reading of the Australian rules).
This reality is extremely divorced from the Oxford University paper, which imagined a system that could accurately determine proximity of users and instantly notify them to isolate. This rapid notification and isolation was, in fact, the central proof of the impact of a digital contact tracing system.
So we have a centralised system that:
* only 'works' in a 'mandatory install' context
* can't determine proximity in the real-world (too much variability)
* would introduce huge numbers of false positives into a system that has to manually follow-up every one
* normalises carrying a tracking device of all nearby people (which in future would be far more useful as a societal monitoring system than as an epidemiological tool)
Having to traverse two human bodies will create significant variation, and antenna angle will also add to that.
As mentioned in the video [1] this can make people look much further away, making it rather useless at estimating real distance.
[1] https://www.youtube.com/watch?v=KgKbllhgESc&feature=youtu.be...
A recent article [1] confirmed this in interviewing the inventors of Bluetooth.
The environmental factors were explored in a recent conference on contact tracing [2] with leading researchers.
So in a UK context, what is the plan in dealing with the huge number of false positives captured by this system, which in reality cannot estimate a 2 metre distance?
The Australian COVIDSafe app sends all contacts in Bluetooth distance, which obviously includes people in other rooms, and on entirely different levels of a building - because there's no directional information.
Separate to the issue of proximity is the issue that this system cannot really work unless it's mandatory, as others have outlined.
Does any purpoted health benefits have to be modelled, proved and measured against the issues of shifting Western society to one which requires mandatory install and carry of a mobile phone which records all nearby devices?
It gets us closer to a society where political actors will be tempted to provide a rationale which justifies permanent extreme surveillance of citizens.
The limited analysis of the particular client implementations appears to miss this wider geopolitical point, and responsible technologists might want to consider these more carefully.
In the Australian situation all we are currently told is that if the app registers you as a close contact then it is used for 'usual contact tracing' and that contact tracing involves determining whether you are a 'close contact' and have to self-isolate for 14 days - a huge cost in a re-opened society if it is an unnecessary false positive.
It's been quite strange to see leading technologists such as Mike Cannon Brookes of Atlassian and Troy Hunt of HaveIBeenPwned strongly urge Australians to download it as an 'unequivocally safe app' when the most important part - the server-side algorithm to 'guesstimate' proximity - has not been shared by the Australian Government [3].
How can a technologist give the thumbs up to a proximity app when there is no evidence of it reliably estimating proximity in the real-world scenarios it is meant to operate in?
[1] https://theintercept.com/2020/05/05/coronavirus-bluetooth-co...
[2] https://www.youtube.com/watch?v=KgKbllhgESc&feature=youtu.be...
[3] https://www.abc.net.au/news/science/2020-05-06/coronavirus-c...
One recent data point using the CovidSafe app is here: https://twitter.com/jim_mussared/status/1256199078314078210
Exploration around the defects in that app is ongoing here: https://docs.google.com/document/d/1u5a5ersKBH6eG362atALrzuX...
When you consider that close contacts include anyone you've spent more than 2 hours with in a room, it becomes clear that most life situations are not handled by estimates of proximity using bluetooth: home, family & friend visits, workplaces.
You can find a deep-dive into these issues here:
https://blog.crushthecurve.today/why-should-you-install-the-...
A determination around being a close contact results in 14-day isolation regardless of symptoms, presumably because you may initially test negative before moving into an infectious and asymptomatic or symptomatic phase.
https://blog.gds-gov.tech/automated-contact-tracing-is-not-a...
The policy there probably reflects the understanding that people in the early stages of infection won't test positive or exhibit symptoms.
A lot of voices have spoken out about this issue overseas (particularly in the US) while many local tech voices have skipped considering this at all.
See:
* Previous FTC CTO / Obama Whitehouse senior adviser: https://twitter.com/ashk4n/status/1248659875669798912
* Brookings Institute article: https://www.brookings.edu/techstream/inaccurate-and-insecure...
* Margolis Center for Health Policy at Duke University (pdf report): https://healthpolicy.duke.edu/sites/default/files/atoms/file...
* Bruce Schneier: https://www.schneier.com/blog/archives/2020/05/me_on_covad-1...
A contact is only registered after 15 minutes of time spent within an estimated proximity of 1.5 metres (itself a primitive model of infectious disease transmission based on a 1942 paper). Note other countries set the distance at 2 metres.
As outlined in other comments in this thread, close contact rules include anyone in a room for more than 2 hours, so even though all close contacts have to be manually interviewed (there is no instantaneous notification and isolation) for most social situations close contacts won't be registered through crude estimates of proximity: home, family / friends, work all require thinking about and providing contacts.
When you strip out all the situations that aren't beneficial, that starts to leave public transport in major metro situations where commutes are greater than 15 minutes.
Keep in mind that also implies the end of any social distancing (as otherwise no contacts are registered). That seems obvious, as public transport becomes overwhelmed if capacity is significantly reduced.
The reality is the entire 'human in the loop' contact tracing process is still manual. Health staff working in state contact tracing teams still need to call and interview every contact to determine whether they could be considered a close contact from an epidemiological perspective.
Also consider that close contacts include anyone you've spent more than 2 hours in an enclosed room with.
So that immediately limits the utility of any bluetooth proximity app: you still need an entirely manual process for home, work, social gatherings - any situation where you are in an enclosed room.
We've taken a deeper look at the assumptions and expert opinion, both from individuals and institutions, which appear to discount this kind of system from providing significant value.
Even the product lead of Singapore's TraceTogether app, as a natural advocate for this kind of initiative, admits the technology is oversold and is only an additional tool (due to the significant potential for false positives / negatives):
https://blog.gds-gov.tech/automated-contact-tracing-is-not-a...
One thing that's interesting to think about more deeply is how difficult it is to estimate proximity based on the combinatorial explosion of different hardware, individual device peculiarities, battery levels and environmental factors (walls, glass windows, partitions, ventilation).
The very limited data published appears like interesting preliminary field work which finds significant variability in signal strength across hardware, and rather than concluding proximity estimations are useful, ends in a plea for OEMs to release factory calibration data for their BLE implementations:
https://github.com/opentrace-community/opentrace-calibration...
It seems the sensible order of questions is:
1) Do we have a contact tracing problem?
2) Does digital contact tracing generally solve it?
3) Is the specific app / implementation useful / safe / privacy-respecting?
It appears the national conversation almost entirely skips thinking about 1) and 2) and gets lost in the limited analysis of 3).
We had a deeper look at 2) in this recent piece:
https://blog.crushthecurve.today/why-should-you-install-the-...