Richard Baker, CEO of GeoSpock, explains why data is crucial to understanding our invisible enemy’s activity
Reopening the economy while avoiding a second wave of Covid-19 is one of the biggest challenges of our time. Maintaining a low rate of transmission while opening up places of work and leisure is a delicate balance to strike, and localised outbreaks must be kept under control before they spread more widely. To do this requires a rapid, joined-up approach between regions, one which technology can enable.
With a raft of issues leading to the recent scrapping of the NHS’s contact tracing app, the pressure is on tech giants Apple and Google to provide a better solution. The apps currently provided are Bluetooth-based.
This approach, which uses Bluetooth signals between mobile devices to ascertain which users are close to each other, has already been widely adopted in Asian countries. This is arguably more efficient than traditional contact tracing methods that require large staffs to interview patients about their whereabouts and those they have been in contact with. However, it also has several flaws, such as relying on uptake.
To keep low transmission rates under control and move back to normality, contact-tracing methods must shift from reactionary to proactive.
A fundamentally flawed approach
Bluetooth-only contact tracing is useful in alerting people when those infected cannot recall whom they have been in close proximity with for an extended period of time.
However, it can’t stop the virus in its tracks. If you are close enough to catch a Bluetooth signal, you are close enough to have already caught the virus.
The approach is reactive, rather than proactive, and also lacks accuracy. Bluetooth on its own only tells people the ‘who’, and not so much of the ‘where’ – a person travelling on a train could infect many people at opposite ends of the country in a single day.
In addition, signals could be received through the windows of an isolation booth and can propagate further than airborne viral spread, providing inaccurate data. Whilst helping reduce onward infections with post-exposure mitigation, it isn’t effective for pre-exposure prevention. This all suggests we should be looking for a better technology solution.
That’s where the prevalence of communications technology comes in. When harnessed fully, widespread mobile phone adoption can provide sophisticated environmental sensing. When combined with additional datasets and the ability to carry out rapid large-scale location data analytics, it would provide full-situational contextual intelligence. In turn, this can enable true data-driven decision making and a more coordinated response to the pandemic.
Understanding the invisible enemy
Data is crucial to understanding our invisible enemy’s activity. This can be in the form of close-contact data, such as Bluetooth signals, or fine-grained location data, such as GPS signals from mobile devices or social media check-ins.
Another category is coarse-grained location data, which includes government place-of-residency records and network-based location trilateration from telecoms providers using mobile phone towers. Meanwhile, supplementary contextual data can be in the form of COVID-19 testing outcomes, like crowd monitoring via CCTV or even weather conditions.
Location intelligence in particular has a lot of potential, enabling us to have real-time understanding of when and where the virus is progressing. This is vital for continuous situation management and provides governments with the data necessary to act safely, efficiently.
It can underpin everything from healthcare resource management and business continuity planning, to exposure-risk assessment for individuals and track-and-trace activity with granular containment, isolation and travel policies. In addition to this, it can enable low-risk, low-exposure areas and industries to safely reopen – crucial to minimising economic disruption in the short term and long term.
Controlling local outbreaks
Flexibility is paramount as the pandemic evolves and as new datasets become available or new outcomes are desired. In addition to the complex nature of the data ecosystem, some of the datasets will be machine generated, which means very large amounts of data will need to be stored and processed for insights and analytics.
A highly sophisticated and specialised database is required to cope with these large and complex datasets, while maintaining rapid speed of response. The ability to fuse different data together and extract new insights can guide the design of new policies and guidelines.
This could eliminate the need for a nationwide lockdown, with the contact tracing app not only alerting individuals who have encountered someone who has tested positive for COVID-19, but informing people if hyper-localised cases have occurred in their neighbourhood or at their place of work. This would enable them to stay at home or avoid visiting public places to minimise exposure to any risks, ultimately lowering transmission rates further.
Crucially, the solution could also prevent healthcare services from becoming overwhelmed. Healthcare managers could be alerted at an early stage to any regional growth in infection rates, enabling them to shift medical staff and resources to where they are needed most. Frontline workers could be supplied with the right equipment in good time to keep them safe.
Moreover, any nationwide analytics could enable the government to identify virus hotspots and react proactively and appropriately by locking down a town or city as opposed to the whole country. This kind of data-driven decision making, along with real-time monitoring and management of physical world systems, is critical when it comes to improving real-world outcomes.
For transmission of the virus to be brought fully under control, speed is critical. A Bluetooth approach isn’t enough. Real-time understanding of how the virus is progressing is required to keep up with its spread, and insights must be available for quick and effective decision making. With globalisation increasing the likelihood we will face future pandemics, data-driven technology holds the key to navigating the uncertainty ahead.