Better safe than sorry: why AI may be the answer to tomorrow’s pandemic

For once, the COVID-19 dashboard does not spell doom and gloom. According to data analyzed this week by CNBC, infections are down 90% compared to five weeks ago. What’s more, hospitalizations have also halved since the peak of 159,000 patients were recorded in January.

These encouraging data have meant that even the states that adopted the most aggressive stances on containing the virus, such as New York and California, recently announced that they would let their indoor mask mandates expire at the end of the month.

As the pandemic draws towards its final stages, US lawmakers are getting a head start on learning lessons from how the country - under two different administrations - dealt with the challenges posed by COVID-19.

Last month, this process began in earnest when the Senate’s Health, Education, Labor and Pensions committee announcing a bipartisan bill – the PREVENT Pandemics act. The ultimate aim of this exercise, as was made clear by ranking member Richard Burr (R-NC), is to ensure that America is “better prepared for the next threat we face”.

Lacking precision: the US COVID response

But what are the main lessons to be learned? Undoubtedly, an area that deserves serious scrutiny are the delays in protecting the people most vulnerable to suffer adverse consequences from being infected. The magnitude of these failings can be measured in the sobering death rate, which has been at times the highest among developed economies of the G7.

In many ways, however, COVID has already boosted innovation and progress on this front. For instance, the US has over the past year significantly increased its genome sequencing capabilities, which allow scientists to identify mutations in viruses.

But another lesson that must be learned - and that is equally as important - is how to make our economy resilient for when the next pandemic hits.

Throughout the COVID crisis, the public health approach to contain the number of cases has relied on blunt measures that had a great cost on livelihoods and the economy. This was especially true during the first peak in March 2020, when most States resorted to stay-at-home orders and economic shutdowns to limit the spread of the virus.

At the time, we were witnessing daily reports of around 20,000 infections and 2,000 deaths. The only way of responding, however, was to ground at least three quarters of the US workforce - no less than 120 million people. These numbers tell a clear story: because we lacked the tools to act in a precise way, we had to use a sledgehammer to crack a nut.

Innovation now: the opportunities of AI

While these blunt instruments may have been the best option at the time, it is key to prepare for the next pandemic by finding alternatives that ensure these measures are never needed again. The most likely avenue for doing so is to turn to the technological advances in Artificial Intelligence (AI), which increasingly offer opportunities to target containment measures and reduce disruption to everyday lives.

The merits of this approach have already been proven on US soil. For instance, last November, a co-working space club in New York adopted Biosafety Thermal Kits as a seamless screening measure against COVID-19. The kits – which were created by the NASDAQ-traded tech company Remark Holdings – have been used to conduct discrete temperature checks at pre-established points. Without creating long lines or disruption for customers, the computer vision technology is used as an efficient and seamless way of conducting COVID screening.

Such solutions have also proven to be scalable and applicable in a variety of industries. As well as being adopted by Wynn Resorts in Las Vegas, the same thermal scanners by Remark Holdings have been adopted in the healthcare sector by medical services provider in Oklahoma.

Another COVID-induced tech innovation that appears set to stay are QR codes in restaurants and bars. While initially used to consult a paperless menu via smartphone, companies such as Toast have continued innovating and now offer QR codes that direct customers to a platform where they can order and pay for their meal directly.

Fail to prepare, prepare to fail

The encouraging adoption of these smart solutions should not, however, hide the fact that the US is radically behind on AI investment compared to other countries. Japan, for instance, had already released a comprehensive National AI strategy in 2017, a full two years before the American initiative was published.

Another country that has not been shy about its ambitions is China, who has set the ambitious target of becoming the world’s main AI innovation center by 2030. Much more investment in AI-driven solutions is therefore needed if the US is to catch up and reap the benefits when the next crisis strikes.

The realization that neglecting AI and cutting-edge technologies would be a massive mistake for future pandemic preparedness has already dawned on the Senate health committee. In written evidence submitted last July, the Deputy Secretary for Washington State’s Department of Health emphasized the need for “structured innovation… through new public-private partnerships with healthcare providers, private sector, and other entities”.

Harnessing the opportunity of technology and AI for pandemic preparedness is essential, but must be done with two goals in mind. Not only must it save lives when the storm lands, but it must build resilience for the US economy to withstand the hit.

Much of the economic pain stemming from the COVID pandemic was evenly distributed. Most countries were caught wrongfooted, had to rely on heavily disruptive measures of containment and borrowed extensively to keep the economy afloat. This is unlikely to be the case next time.

Countries that invest now in tech-based systems that will enable a targeted approach will limit the disruption and pain experienced by their economies. Those who don’t will simply repeat the past two years. Learning the lesson now has never been so important for the future.

This article does not necessarily reflect the opinions of the editors or management of EconoTimes