the lack of testing for people, due to the governments decision (failure) to continue/expand/rol out systems (despite offers from quite a few research labs that had large capacity systems ready to roll).
Instead, the assumption was that people would "self report" with symptoms (or diagnosed after a 111 call) - not only might these be unreliable, they might attract abuse (troll like behaviour is fairly common). Hence one goal was that the index case should be trackable and (presumably) potentially blocked /reported if multiple bogus attempts made to claim a) they were infected and therefore b) cause a lot of people in their contactee data to have to self isolate pointlessly for 7+ days.
I'll note here that tests on the contactees dont help set them free, because recently infected people don't typically test positive for virus until they have symptoms (pre-symptomatic) and note, a significant fraction won't ever get symptoms even if infected (asymptomatic, and are still potentially infectious even if apparently well. Indeed - there arre good public health reasons to measure the rate of asymptomatic infectious people as this is part of the risk level in an area.
Thus, as well as wishing to improve any diagnosis menus in an app, and as well as desiring to continuously improve the exposure notification algorithm used to turn BLE measurements into a likelihood of possible infection, we also have the wish to record who (non anonymously) claimed infection, and who (possibly anonymously, but re-linkably in a chain of infections) was a contactee without symptoms, for epidemiological reasons, as well as for notification.
As well as this, it would be useful to know the context (location, e.g. indoors, in vehicle, type of building versus out doors) and whether in only a pairwise encounter, or a group - all this data helps understand the modes that the virus spreads through, to help sharpen advice to the public, and also refine the algorithms.
There's some discussion about why one would combine these two functions in one app (contact notification and public health statistics). There are quite a few nice symptom reporting apps (notably in the UK joinzoe), which do a good job of learning new symptoms' importance, and can map hotspots over time as well) - but the point is that it is not a change to a centralised app to provide the contact graph of infected people - this is the same primary purpose - the "second" application is simply the use of the stored data and doesn't change the app at all. In fact, the notification service is also notably simpler if you don't need to build some magic decentralised rendezvous network.
I notify service I am diagnosed positive with list of contacts. service notifies each contact they may have been exposed (potentially with human in the loop to detoxify the bad news).
so what are the trust problems here? well by not having testing and not trusting the users to all only honestly report symptoms, the government/UK health service set a tone that the customer is not always right. But the decentralised systems send the message that the public don't trust the national health service in their country, and yet they have to trust that health service if they fall ill, so this is a hidden toxic message too.
don't be too surprised if both systems lead to a rise in distrust of health science, and potentially a boost to the anti-vaxxer movement, just at a time when we may really need to get vaccinated.
the good thing is that when we have a vaccine, unlike with smallpox or polio, we don't need to create (true) herd immunity immediately, but rather need only vaccinate the vulnerable, at least at first. Of course, there may be a novel novel corona virus around the corner which goes back to the mortality risk levels of SARS and MERS but has the incubation time of Covid-19, and then we'd really care that a lot of people were out of the infection loop proactively (not reactively).
For now, reacting as fast as possible is our best bet to get as close to zero cases as possible..
No comments:
Post a Comment