The Francis Crick have successfully built a process for Covid PCR testing for patients and NHS Staff. The Crick have also validated a reverse transcription loop-mediated thermal amplification (RT-LAMP) method for 25-minute coronavirus testing. The best way to realise Operation Moonshot is to bring the two processes together and deliver across 200+ NHS trusts.
The following is a costed break-down of all of the necessary components within a solution architecture. I try to provide costed reasoning for all of my assumptions and to use fixed cost points and recent precedent. The costs are broken down into 5 areas: equipment, self-swabbing (as drive thru won’t scale), RT-LAMP testing, IT & processes and rollout. I believe that Operation Moonshot could be delivered for half the UK Government’s initial assessment.
Testing Equipment: The UK Government has already invested in the novel RT-LAMP test capability. The highest throughput machine is the Oxford Nanopore PromethION 48 which can process 15000 RT-LAMP tests a day. Each machine costs just under half a million pounds meaning that handling 10million tests a day would require 667 machines at a non-discounted prices of a third of a billion pounds.
machine list price
£476,145
tests per machine
15,000
tests a day
10,000,000
nhs trusts
220
number of machines
666.67
cost of machines
£317,430,000
cost per trust
£1,442,864
cost per trust for RT-LAMPore machines
Testing Capacity Increase & Self-Swabbing Costs: The UK already has an appointment booking process for the national pillar 2 swab testing. These tests are carried out in car and involve bagging the swabs with pre-registered barcodes. There are 50 test sites in the UK which provide the majority of the UK’s capacity of 350k a day. Increasing the testing capacity to 10m a day would require nearly 1500 sites and tens of thousands of more testers.
current test capacity
350,000
number of test sites
50
site processing capacity
7000
number of sites required
1,429
Drive through testing capacity
The other testing approaches would be either localised testing making use of any medically trained personnel or through self-testing through posted self-test kits. We will examine the self-test model: Based on 10m test a day the whole UK population will be tested each week meaning that everybody in the UK should be receiving a number of tests through the post. Self-testing would have a lower rate of accuracy but this would be mitigated by the sheer size of the testing quorum. The collection of self-tests will need to be within 24-48 hours for the test to be valid and testing centres will be reliant on the immediate return of tests.
tests a day
10,000,000
unit cost per kit
£0.50
daily cost
£5,000,000
kit test cost for 1 year
£1,825,000,000
courier costs per kit
£2.50
daily courier costs
£25,000,000
courier cost for 1 year
£9,125,000,000
total
£10,950,000,000
Self-testing costs
The kit and courier costs of 10m tests a day would be in excess of a £10bn a year even with the lower possible unit prices for kits and couriers. To be cost effective the self-test model would need a local drop-off and collection area to lower the total courier costs. Based on a drop-off model of £10 per 100 tests the yearly cost would decrease to 2bn a year.
tests a day
10,000,000
unit cost per kit
£0.50
daily cost
£5,000,000
kit test cost for 1 year
£1,825,000,000
drop-off courier costs per 100
£10.00
daily courier costs
£1,000,000
courier cost for 1 year
£365,000,000
total
£2,190,000,000
Self-test drop-off costs
RT-LAMP Testing & Results Process: RT-LAMP testing will unpack all self-swab packs and run each sample through the testing lifecycle producing a result within 25 minutes. Test results will need to be validated by medical professionals and positive tests need to be recorded against the summary care record and notified to the relevant Public Health Authority. If each NHS trust would have between 3-6 RT-LAMP machines handling tests and each machine would require a minimum staff of 6 people to continually operate and validate the test results. At an average cost of £40k per FTE this would cost more than £200m per year.
tests a day
10,000,000
nhs trusts
220
RT-LAMP machines per trust
4
trust daily throughput
45,455
daily FTE requirement
24
extra staff requirement
5280
staff costs
£211,200,000
Assessment of staffing costs for handing RT-LAMP process
Central IT Costs, Notifications and Mobile App: The national roll-out of a 10 million a day testing service would be vastly complex, far more complex than mere rocket science! Achieving such a service would require both centralised common processes and local variations to succeed. A good example of local variances would be the designing of the self-swap collection locations. A successful would also need the IT and process functions to be right first time, including the mobile app launch. The IT functions could be realised within a multi-tenanted ITIL compliant solution (e.g. ServiceNow) which would allow centralisation and local variances. Such a solution would also allow for stock and asset management. All test records could be centralised from the RT-LAMP machines and then fed to the relevant PHA’s by integration with the final notifications going to the public via a mobile app. Staffing would manage the end to end processes and the criticality of the data demands a security overhead. It is not unreasonable to include a 30% contingency on the total.
centralised IT process
£5,000,000
localisations budget
£10,000,000
staffing
£2,500,000
mobile app
£2,000,000
PHA integrations
£2,000,000
security
£3,000,000
contingency
£7,350,000
total
£31,850,000
Assessment of IT and process costs
Rollout Process: Rollout costs should be viewed separately as deployments would take time to bed in and would need a degree of local stock and asset management. Precedent suggests that getting to 100k daily tests would have more easily achieved with a lot of small ships rather than following a centralised model. It is therefore not unreasonable to suggest a £10m budget per trust for rollout processes. If the rollout were to include many more smaller GPs then that budget would have to be increased, for this reason I’ve included a 30% contingency.
number of trusts
220
cost per roll-out
£10,000,000
contingency 30%
£660,000,000
total
£2,860,000,000
Roll out costs
Total: The total cost assessment is for one year only but is approximately half of the UK Government’s assessment of £10bn. The most accurate costs are for the Testing Equipment based on the capacity and list prices of the Oxford Nanopore equipment. The self-swabbing approach is based on a collective drop-off solution as otherwise another £8bn could be spent on individual collection of swabs. The RT-LAMP costs as predominantly staff costs for 5000 new staff. The IT costs include a 30% contingency and are based on the UK Government getting its IT right first time. The rollout costs are the the highest individual costs but should be a year one only cost and do not include any economy of scale across multiple NHS trusts who may be able to work together.
Testing Equipment
£317,430,000
Testing Capacity Increase & Self-Swabbing Costs
£2,190,000,000
RT-LAMP testing
£211,200,000
Central IT Costs, Notifications and Mobile App
£31,850,000
Rollout
£2,860,000,000
Total
£5,610,480,000
Total cost assessment
Operation Moonshot has not published any assumptions, cost validation or time period for its £10 billion total cost. The above costs are all based on my recent previous experience of Covid-19 PCR testing. It is not unfeasible that Operation Moonshot could be achieved for half the costs currently being claimed.
I really enjoy working at the Francis Crick Institute and I am really proud to have worked on the SARS-CoV-2 Testing Service. It’s all quite different from mobile networks
Find out how @TheCrick worked with @uclh NHS Foundation Trust and Health Services Laboratories to set up a SARS-CoV-2 testing service in just two weeks that has now carried out over 30,000 tests.
The UK is trialling its Covid-19 contact tracing application which tracks human interactions. The app uses Bluetooth Low Energy (BLE) communications between smartphones for registering handshakes’ duration and distance. This data is then uploaded to a centralised database so that if a user self-registers as Covid-19 positive, the centralised service can push notifications to all ‘contacts’. This is a highly centralised model based around relaying all users ‘Contact Events’ together with user self-assessments of Covid-19 symptoms.
A user can self-report having the symptoms of Coronavirus. They cannot report a positive test for Coronavirus as there is no way of entering either an NHS_ID or a Test_ID. Technically the UK mobile app does not match the mobile App ID against the user’s NHS ID and there is no mapping between the app and NHS England’s Epic system. This approach allows for greater anonymity as the centralised database will not be recording a user’s NHS identifier. The downside of this approach will be a higher percentage of false positives and contact notifications .
NHSX’s Covid-19 App requires GDPR Consent as the legal basis to enable permissions
NHSX and Pivotal, the software development firm, have published the App’s source code and the App’s Data Protection Impact Assessment. The latter is a mandatory document within the EU-GDPR framework. The user provides ‘Consent’ as the legal basis for data processing of the first three characters on their postcode and the enabling of permissions. The NHS Covid-19 app captures the first part of the user’s postcode as personal data. It then requests permissions for Bluetooth connectivity necessary for handshakes and Push notifications necessary for file transfer.
The UK NHS app captures ‘Contact Events’ between enabled devices using Bluetooth. The app records and uploads Bluetooth Low Energy handshakes based on the Bluetooth Received Signal Strength Indication (RSSI) measure for determining proximity. Not all RSSI values are the same as chip manufacturers and firmware are different. The RSSI value differs between different radio circuits. Two different models of iPhones will have similar internal bluetooth components whereas on Android devices there will be a large variation of devices and chipsets. For Android devices it will be harder to absolutely measure a consistent RSSI across millions of handshakes. A Covid-19 proximity virus transfer predictor should take into account the variances between BLE chipsets.
All of the ‘Contact Events’ are stored in the centralised NHSX database. This datastore will most likely hold simple document records for each event, its duration, the average proximity, the postcode (first three characters) only where that occurred and which devices were involved. It will then run queries against that database whenever a user self-registers their Covid-19 symptoms. The centralised server will push notification messages to all registered app users returned in that query. The logic in the server will most likely take a positive / inclusive approach to notification so that anybody within a 2 metre RSSI range for more than 1 second of a person with Covid-19 symptoms will be notified.
All EU countries must comply with EU-GDPR and all are currently launching their Covid-19 tracking applications. These applications because they require user downloading can only use ‘Consent’ as the legal basis for data capture and require a register of the user’s consent. The user must also be able to revoke ‘Consent’ through the simple step of deleting the app on their device. A more pertinent challenge is within a corporate or public work environment where there can be a ‘Legitimate Interest’ legal basis for capturing user’s symptoms. For example a care home could have legitimate interest in knowing the Covid-19 symptoms of its employees. It is likely we may see the growth in the use of private apps encouraged by employers if the national centralised government apps do not reach a critical mass. Either way we live in a smartphone world and bluetooth’s ubiquity is now certain.
The Francis Crick Institute has repurposed its laboratories as an emergency Covid-19 testing facility. The Crick is helping combat the spread of infection and allow key workers to perform lifesaving duties and remain safe.
Crick repurposed PCR testing lab
One of the main technologies the Crick is using in this effort are Polymerase Chain Reaction machines. PCR machines test for the presence of a specific nucleic acid. The end to end process involves capturing molecules on a swab that are then broken down into genetic code, using special chemicals and liquid handling robots. The PCR (polymerase chain reaction) machine can then make billions of copies of DNA strands from the original swab. The PCR machine tests for the presence for the Covid-19 RNA. This is done on a series of 94 Wells (each containing an individual swab) on a Plate within the ThermoFisher PCR machines. The final step involves specialist clinicians making the decision on whether the sample contains sufficient RNA to justify the presence of Coronavirus.
The qPCR test produces a graph showing the exponential progress (or not) of the Cq (Ct) value as it traverses the threshold. The Cq value is the cycle quantification value of the PCR cycle number at which the sample’s reaction curve intersects the threshold line. This value tells how many cycles it took to detect a real signal from your samples. Real-Time PCR runs will have a reaction curve for each sample, and therefore many Cq values. Your cycler’s software calculates and charts the Cq value for each of your sample
Normal Fluorescence Graph in a PCR test
To help support the clinician diagnostic phase we have written a series of complementary tests. These seven tests (github) test each Well, each Plate and a series of Plates. The test data comes from the the ThermoFisher PCR machines and QuantStudio software.
Log score per Well between 90% & 110% Across multiple Plates a value of Rsquared greater than >0.99
Per Well & Multiple Plates
Per Well: Column R in Results Sheet provides efficiency score per WellMultiple Plates: Slope: ~ –3.3R2 >0.99
Seven logical tests implemented in code
The outcome of these tests can then be used in conjunction by the clinician reviewing 94 individual wells (each representing a unique swab). The intent is that this helps reduce human error and can improve the clinical throughput.