20-10-21, add close contact analysis

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Harvey Tindall 2021-10-20 13:08:32 +01:00
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1:
* Way too much text
* Just reading the presentation
* Monotone
* Speeding through it
* Limit use of lego in diagrams
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* Not explaining the diagram (which is confusing)
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* Maybe you're meant to discuss your references
* Also put them at the end
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* Waste of space
* Shit animations
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* No jokes
* No cats
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* Stealing slides
* Terrible formatting (Can't read text)
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* Can't answer any Qs
General notes:
* You'll be marked on the slides, so make sure to include all information (just don't make it too dense)
* End with key points of the presentation, don't just ask for questions
* Proofread/do a test presentation
* Eyecontact, or just keep your camera on
References:
* Put them on the relevant slide, or right at the end (after conclusion and Qs)
* Use Leeds Harvard, or Leeds numeric
Other useful stuff:
* Google Scholar

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[Relevant paper](https://covid19.nhs.uk/risk-scoring-algorithm.html), and [Summary article](https://faq.covid19.nhs.uk/article/KA-01159/en-us)
* "Close contact" is generally summarised as being within 2m of the subject for > 15 minutes, but is actually based on an algorithm
* Upon agreeing to share the contact data collected by the app, data is given to Google/Apple API
* The user provides a date when they first noticed COVID-19 symptoms (if this was not already given), which is used to estimate their level of infectiousness on each day from 2 days before onset to 10 days after. It is higher closer to the onset.
* Data includes the signal strength between each device, which is measured on average every 3.6 minutes, stored and then transmitted to the other device
* Signal strength can be affected by external factors (location of phone on body, rf environment, etc.), so distance cannot be calculated exactly
* Each device now has its own and the other's strength measurements, which it uses to estimate a distance
* Using this set of measurements over time, the device calculates a "risk score" using these distance estimates:
* ( (Total time spent within 1 metre) + Sum( (Time spent within 1 metre or further) / (Distance^2) ) ) * ( Est. level of infectiousness on the day of the encounter )
* The threshold "risk score" is defined to produce results similar to the 2 metre 15 minute rule
* If a contact crossed this threshold, they are notified
* The risk level was transmitted as "Low", "Standard" or "High", although in more recent versions of GAEN API, Low has changed to None.
* Later versions of GAEN (Google/Apple Exposure Notifications) (>=1.6) and subsequently newer versions of NHS app added a REVOKED close contact report type, which denotes that previous close contact reports related to a users key can be discarded, for example if a user self-reported positive but PCR'ed negative. ([source](https://developers.google.com/android/exposure-notifications/exposure-notifications-api#data-structures), see "reportType" atrribute in "TemporaryExposureKey" class)

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Subproject commit aa949bbf26dc15b169d4fe215a41160d29d945b0

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* Contact tracing data is only shared if one chooses to when they test positive
* The app's source code is publicly available ([github](https://github.com/nihp-public/covid19-app-system-public)), and a vulnerability exposure program has been set up ([here](https://hackerone.com/nhscovid19app?type=team))
* Source available doesn't mean app is secure, but can mean vulnerabilites are found more quickly

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--* A mean number of 4.2 notifications were sent per user who tested positive and accepted contact tracing--
* As of 6th October 2021, ~6.9 million contact tracing alerts have been sent ([from NHS](https://stats.app.covid19.nhs.uk/#contact-tracing-alerts), "Number of contact tracing alerts sent (England)") with ~2.1 million positive tests reported in app (same link, "Number of test results linked to the app (England)", "Total positive test results")
* Therefore, notifications were sent to, on average, roughly 3 people who came into 'close contact' with a person who tested positive and reported it.