There are many approaches that are standard in Bluetooth protocols that are relevant for contact tracing protocols generally. These are summarised in the below list.
These are approaches used in many protocols
All Bluetooth protocols store some information in their adverts. All have service and characteristic information. Some use the extended space in their adverts to act as the sole means of payload transmission.
This approach is limited as many devices (16% of UK mobile devices) do not support advertising, only reading others’ adverts.
This is where one phone interacts with each phone nearby directly, not via another device. When someone becomes ill just their contact information is used to notify other potentially ill people. In this approach we do not immediately ask first degree contacts for their contact information too, unless they become ill or test positive. All current protocols support this approach.
See Second and Third degree methods below for enhancements.
This are further approaches that can be used to increase effectiveness that are not common place. We have implemented all of these in our own Protocol.
We have found that Android phones’ speed when reading characteristics is much slower than its support for ‘write and ackowledge’. Using write instead of read for distance estimation allows a much lower continuity error, increasing accuracy, and reducing mean window times from above 8 seconds (minutes for some phones) to 0.5 - 4 seconds, depending on handset and number of devices nearby.
We there use a write characteristic wherever possible in our own protocol.
Note: You have to use ‘write and acknowledge’ as iPhones do not support ‘write without acknoeldgement’ when they act as ‘peripherals’ (advertisers) themselves.
Once a device starts maintaining a list of recent contact events, distance estimations, and identifiers it can act as a notice board. Other devices can ask what nearby devices it has seen in the last few seconds and can log these contacts.
This is useful in two situations:-
By using a Calling Card approach, two such devices like those described above can communicate via an intermediary phone that does not exhibit these behaviours.
This leaves you with two distance estimations. One from phone A to phone B, and one from phone B to phone C. So long as the identifiers and distance estimation values for A-B and B-C are known by both phone A and C, they can still estimate each others’ minimum and maximum potential distances.
As an extension to this, the more phone B’s you have the more accurate you can be. You could use multiple calling card readings to triangulate distance. In fact this approach could also make distance estimation more generally accurate for all phones if done as routine, overcoming some of the issues in distance estimation calculations.
The background ‘wake after X seconds’ timer on Android sometimes becomes ‘stuck’ and does not awake for many minutes. Creating a custom timer based on OS events allows applications to more effectively perform regular timed actions from a main event loop. This in turn increases detection and greatly lowers continuity error in our testing.
Some older Android phones change their network identifiers so often that the airwaves become crowded with communication. We use the advert manufacturer’s data area to include an ephemeral pseudo device address that changes on the same period as the MAC address (15 minutes) to work around this issue. This is described in detail in the Herald Formal Protocol Specification.
There are several mathematical extensions to a centralised contact tracing protocol that could raise the control factor on the spread of a virus. These are briefly described below, but not quantified in this paper:-
Rapidly taking multiple RSSI readings per device will allow an estimation of RSSI modal value. A modal value will be more reliable than a single reading of a mean of a small number of values, but requires more readings to be accurate.
If RSSI values on Bluetooth, for example, are below a certain level, do not try to exchange IDs until it is nearer. There will be a normalised probability function that can predict for all phones the likelihood that a phone is within the 8 metre range of epidemiological interest. Filtering out some phones from information exchange can lead to higher throughput and less cross talk, improving continuity and minimising data that needs to be held. It also helps with privacy.
Rather than just asking those who themselves have had direct confirmed exposure to one or more people with COVID-19 to isolate for 14 days, these people’s contact data could be asked for from first degree contacts at the same time prior to them being tested for COVID-19 in order to accelerate the control effect of automated mobile app based contact tracing. This would be useful near the peak of an outbreak.
This mechanism and its additional effectiveness is described in the Fraser Group paper Effective Configurations of a Digital Contact Tracing App. Retrieved 31 August 2020. See Figure 4 and its accompanying text.
As above, but for one more degrees of contact. Would lead to a large number of people self isolating. Useful just before a national lockdown is required.
Rather than using QR codes in venues or other complex manual mechanisms, instead provide a companion app for phones and tablets in restaurants, cinemas, bars, workplaces and other venues where people gather. This would capture the presence of someone using a contact tracing app in a privacy preserving way (compared to handing over your personal details every place you visit) and allow for automated notification. It also minimises the cost to businesses of assisting with contact tracing, and is likely to increase the number of premises complying with assisting with contact tracing measures.