Data in the fight against Covid-19
Could data prove to be one of our most valuable weapons in the fight against the Coronavirus?
On the night of Monday 23rd March an announcement was made requesting all residents of Great Britain and Northern Ireland to stay at home. A text was circulated to all UK phone numbers shortly afterwards containing important information and advice regarding the new rules. The prevalence of phones in 21st century life made this simple measure an effective method of distributing emergency news. Given the lack of an official UK government text broadcast system (something that I suspect will shortly change) this was only possible with collaboration from the major mobile network operators, showing just one of the important roles that tech companies can play in this crisis.
And this isn’t the only way that phones have been used to combat Covid-19: the government has set up a WhatsApp bot to provide information about the disease; simply text “Hi” to 07860 064422 to see for yourself!
Beyond texts, a new app has been set up by researchers from Guy’s, St Thomas’ and King’s College called Covid Symptom Tracker. By allowing users to self-report symptoms it will help provide data to scientists and the NHS about the spread of the virus, filling an information void left by a shortage of testing kits in the country. The app was downloaded over 650,000 times in the first 24 hours!
In Spain the Leitat Technology Centre have developed a medically approved ventilator capable of being produced by a 3D printer. Magí Galindo from the Centre said that the device has been designed such that anyone with access to a 3D printer can make them. The Leitat group estimated that they could produce 100 ventilators a day, however with companies like Airbus already agreeing to lend their printers to the project it is hoped that this figure could rise substantially.
This is only possible because of the sharing of data – given how catastrophic a lack of ventilators could prove it is a vital endeavour.
Companies like Kaspr Datahaus have been following the spread of Coronavirus by monitoring internet speeds. The change in speed of the internet across the world can be symptomatic of the disruption a country is suffering. More people staying at home during the day causes an increased strain on networks. Combine this with the vast increase in working from home and there could be serious productivity implications in countries with fragile internet networks (and even in those without!).
In the UK daytime downloads increased by 90% on the 23rd March – the first day of school closures. The increase in daytime uploads is even sharper, with rates seen to more than double largely based on the considerable spike in the use of video conference software. That said Virgin Media say the increase in traffic is still yet to match some of the spikes seen when multiple Premier League matches are streamed simultaneously.
AI and Coronavirus
The burgeoning field of AI seems to have applications to all aspects of modern life and the fighting of pandemics is no exception:
- Chinese tech giant Alibaba have developed an AI system for the diagnosis of Covid-19 from CT scans of patient’s chests with 96% accuracy. The process would take a human 15 minutes but can be performed in just 20 seconds by AI.
- Amazon, Microsoft and Palantir have teamed up with Faculty AI to produce a dashboard for the NHS aimed at optimising the distribution of ventilators. It considers the stocks and usage of ventilators, levels of staff sickness and hospital capacity (amongst other factors) and uses the data to identify areas of risk to ensure sufficient equipment is allocated correctly. The cloud computing facilities are provided by AWS whilst the data is being stored in a vast Azure data lake.
- An Oxford based firm, Exscientia, have been employing AI to generate candidate pharmaceutical drugs for years. Recently, they have gained access to a library of 15,000 existing drugs. These drugs have already been tested extensively for safety in humans and the aim is to assess if any can be repurposed to use against Coronavirus. Machine learning is employed to teach algorithms the qualities of a successful pharmaceutical, a process that can greatly speed up the process of drug development. Work has already begun, and it is hoped that a potential drug can be found within the next six to twelve months.
Looking ahead, AI could be used to predict the next epidemic before it has a chance to spread. BlueDot is a global AI database company that use powerful algorithms to track infectious diseases across the world. They were able to flag the dangerous situation in Wuhan nine days before it was recognised by the World Health Organization. The potential power of a system capable of sifting huge quantities of data and identifying potential outbreaks while still in their infancy cannot be overstated. With greater research and more sophisticated algorithms it is hoped that one day new diseases can be stopped before they have the chance to spread globally.
Although the highly connected, international world we live in may have given the Coronavirus the means to spread across the globe so quickly, that very connectedness could be our greatest weapon in fighting it. The distribution and sharing of data has applications ranging from tracking disruption to producing drugs and, if properly utilised, has the potential to not only stop this pandemic from having the devastating effect that it might, but even prevent the next one from occurring.