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Data can save us from COVID-19

The ethical use of data is a force for good and never more so than in this pandemic. 

Indeed this is, in many ways, the first data driven public health emergency. Without data, we wouldn’t be able to understand how the virus is spreading, or the impact it is having on our communities and our hospitals. Without data, we will not be able to plot a way out of the current lockdown. 

Yet, perhaps because we can’t touch or feel it, I’ve also seen how easily, and in some cases wilfully, the use of this data can be misunderstood. In normal times, such misunderstanding is frustrating, but hardly consequential. But these are not normal times. Wilfully misunderstanding how data is being used to fight this virus poses a huge risk to people’s lives and livelihoods. 

My company, Faculty, was already working with the NHS when the crisis struck. We’ve continued helping alongside some of the world’s largest tech companies. Our role has focused on helping the NHS understand the epidemic and use its resources as effectively as possible (despite claims by some, we are not working on the contact tracing app).

The result of all our collaborative team’s work has been a real-time dashboard which gives senior decision makers the information they need about what is going on around the country. Every day, some of the NHS’s most senior clinicians meet to look at what it is saying, and make decisions about where to send all kinds of medical equipment, including vital ventilators. This has been a small, but important, part in making sure that the NHS capacity wasn’t breached across the country. 

Part of this work has involved aligning with the rest of government – to make sure that everyone is working on the same assumptions. SAGE, and the modelling sub-group SPI-M, are packed with incredibly smart people doing a tremendously hard job. They tend to focus on, amongst many other things, the national spread of the disease. Understandably, the NHS, who we work with, cares equally about what is going on in local hospitals. After all, each hospital is different, serving different demographics. So we have been helping the NHS teams that work with SPI-M (regularly) and SAGE (which I attended once), to make sure that all the models work together in harmony. This means that SPI-M can properly calibrate their national forecasts with real data, and the NHS can be maximally informed about how the SPI-M models work, to plan how to resource individual hospitals. 

All our work, including with SPI-M, uses non-identifiable data – in the jargon, anonymous and aggregated. In other words, no one – not SPI-M, not central Government, not us – can match data to an individual person. That’s important because if this project is to succeed, people need to understand, and have confidence in, what is being done.

So what’s next? This first phase has been difficult but, being thankful for small mercies, the pandemic has not yet breached NHS capacity. Clearly, though, no one is out of the woods yet. As we release lockdown, we’re going to have to monitor the different regions of the UK incredibly carefully. The NHS is also going to have to figure out how to turn back on regular medical services alongside COVID treatments, and make sure that hospitals don’t become hubs of infection. Although this will mostly be done in local areas, I hope our dashboards can be helpful there too. 

One of the proudest moments I have had recently is when someone from the NHS said we had helped them make ten years of progress in just two months. That is the transformative power of data. Let’s continue that progress as a country, and responsibly use all the tools at our disposal to save as many lives as possible.

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