Healthcare

How tech is being used to fight COVID-19

The coronavirus outbreak represents the most significant challenge this and several prior generations have faced. Its social, political and economic impact grow with each passing day, presenting us with dilemmas that demand solutions.

As history has shown on numerous occasions, though, mankind is more than capable of countering the difficulties it encounters. Persistence and adaptability are amongst our most identifiable traits and, just as the impact of coronavirus has been evident, so too has our collective will and effort.

More than a century has passed since the last pandemic that could reasonably be compared to COVID-19, the influenza outbreak of 1918. Technological developments we have witnessed following this – particularly those that have made our species more mobile – have contributed to the rapid circulation of coronavirus. In addition, though, they have played a prominent role in stymying its transit, to care for those affected and, vitally, the ongoing process of developing a vaccine. Here’s how advanced tech is being used to combat coronavirus.

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Author:

Chris Flynn
Chris Flynn Product Manager

Automation

Whilst we do not know precisely how coronavirus passes from one person to another, it is widely believed that it is circulated through respiratory droplets that are distributed when an infected individual coughs or sneezes. The spread of COVID-19 is, as a direct result, believed to be predominantly spread through close contact. It stands to reason, then, that reducing the need for people to be physically near one another will limit the opportunities the virus has to multiply. How, though, with the outbreak having inevitably brought about increased demand for supplies such as medicine, as well as patients requiring care, can this be facilitated?

In China – the country where the pandemic began – automation has provided a solution. Robots have been used to administer medication, to take the temperatures of and deliver meals to patients infected with COVID-19. This limits the amount of time physicians need to spend with confirmed carriers of coronavirus thus reducing the prospect of them contracting it.

Automatons are also being used to disinfect wards and other locations as required. Studies have revealed that the pathogens that can cause infection can survive on certain surfaces for up to three days.1 Any person that was required to clean an area that contained these pathogens would be likely to find themselves infected as a result. Assigning such tasks to robots negates such risks.

Finally, drones are being used to transport medical samples across cities. This, like the examples cited above, reduces the risk of the infection spreading by minimising peoples’ exposure to the virus.

AI

Determining where outbreaks will emerge with the greatest intensity allows authorities to allocate resources with the utmost efficiency. Doing so, however, is by no means a straightforward task. It is dependent on the collection and analysis of data from a multitude of sources. The majority of which are, in the modern era, unofficial and informal; chat rooms, blogs, social media and all potential avenues of information must be mined. The resultant ocean of data is simply too vast to be effectively analysed by a human element. Instead, artificial intelligence is used – and teamed with medical expertise – to develop understandings that lead to more informed strategies.

HealthMap, a piece of AI tech developed at Harvard Medical School, is currently being used to track the spread of coronavirus. It gathers and analyses online data in real time and has successfully tracked the emergence of COVID-19 across several American states. HealthMap’s researchers are also working closely with the World Health Organization and Centers for Disease Control and Prevention.2

As well as identifying where COVID-19 is gaining a foothold, AI is further able to ensure the most efficient allocation of resources by diagnosing the virus, thus freeing up medical professionals’ time. Chinese company Alibaba has developed a system capable of analysing patients’ CT scans and diagnosing coronavirus with 96% accuracy and within 20 seconds.3 In comparison, a physician typically takes between five and fifteen minutes to complete the same task.

Big data 

At the time of writing (19th March 2020), several companies are in the process of developing vaccines and treatments concerning the novel coronavirus. Progress has been remarkable, with the first human trials having already been conducted in the US. This has, in no small part, been possible due to decades worth of research having been centralised and made available for analysis. As January 2019’s British Society for Immunology stated:

“Where traditionally vaccine development has been dominated by trial and error, systems vaccinology is a tool that provides novel and comprehensive understanding if properly used. Data sets retrieved from systems‐based studies endorse rational design and effective development of safe and efficacious vaccines.”4

By teaming big data with AI, Google’s DeepMind has produced estimates of several of the proteins associated with COVID-19. This model – enabled by vast datasets concerning genomes of the virus, experimentally-determined and computationally-predicted representations of various viral proteins, and epidemiological information – was released prior to peer-review following the company having been encouraged to do so by structural biologists and virologists at the Francis Crick Institute. They have been made available via an open license and it is hoped they will help to develop our understanding of COVID-19 and aid the development of vaccinations and treatments.5

Blockchain

Blue Cross Insurance, part of the Bank of East Asia, has leveraged a blockchain-based claims app to both expedite the applications process and halt the spread of the virus.

In contrast to the laborious and bureaucratic processes typically associated with insurance claims, Blue Cross’s app removes the need for documents to be exchanged between various parties. In turn, this allows for claims to be fast-tracked meaning that patients can quickly access care whilst also eradicating the need for administrative staff to have face-to-face contact with claimants.6

Conclusion

In the face of considerable challenge, innovation is providing effective, tangible solutions. It is minimising the risk of cross infection, helping to assign resources effectively, aiding the creation of vaccines and treatments, and helping patients access the care they need.

Much of this technology has the potential to identify likely future outbreaks and possibly even develop contingencies or medication to counter them. BlueDot, an AI company based in Toronto, identified the beginnings of the COVID-19 outbreak on the 30th December 2019, nine days before the World Health Organization made the world aware of its existence.7 The company are using the same tech to track the spread of other viruses and, if teamed with vaccination development relying on likely protein structures determined by analysing similar strains, this could see immunisation take place in advance of circulation.

References:

  1. Forbes (2020) How Coronavirus Study Shows How Long It Survives On Different Surfaces, https://www.forbes.com/sites/ericmack/2020/03/15/new-coronavirus-study-shows-how-long-hcov-19-can-live-on-different-surfaces/#5beb072d412f
  2. The Harvard Crimson (2020), Harvard Medical School Professor’s Artifical Intelligence System Maps Coronavirus Outbreak, https://www.thecrimson.com/article/2020/3/3/hms-coronavirus-tracking-tool/
  3. Nikkei Asian Review (2020), Alibaba says AI can identify coronavirus infections with 96% accuracy, https://asia.nikkei.com/Spotlight/Coronavirus/Alibaba-says-AI-can-identify-coronavirus-infections-with-96-accuracy
  4. Raeven, R. van Riet, E. Meiring, H. Metz, B and Kersten, G. (2018) ‘Systems vaccinology and big data in the vaccine development chain’, Immunology vol. 156, no.1, pp. 33-46
  5. Deepmind (2020), Computational predictions of protein structures associated with COVID-19, https://deepmind.com/research/open-source/computational-predictions-of-protein-structures-associated-with-COVID-19
  6. Cointelegraph (2020), Chinese Insurance Firms Use Blockchain to Process Coronavirus Claims, https://cointelegraph.com/news/chinese-insurance-firms-use-blockchain-to-process-coronavirus-claims
  7. CNBC (2020), How this Canadian start-up spotted coronavirus before everyone else knew about it, https://www.cnbc.com/2020/03/03/bluedot-used-artificial-intelligence-to-predict-coronavirus-spread.html

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