Considering the major advancements made in AI, with 92,821 patents granted over the last 20 years, there is potential in applying this technology to identify the start of a Covid-like outbreak and then prevent the transition to a pandemic. This could have been done with Covid-19, through AI-driven algorithms like BlueDot’s, which alerted customers of the possible risk prior to China’s first official report.

Covid-19 has now killed over 4.6 million people, just under 20 months since the first death was reported. With a total of over 224 million confirmed cases, the world remains firmly in the grip of the Covid-19 pandemic. This underlines the need for improved tools to manage the risk of this and future pandemics. One promising area is the use of artificial intelligence (AI)-backed infectious-disease surveillance software.

Both the public and private sectors hold the resources necessary to create and purchase these algorithms, which may then be used on a national and international level. There is a clear social responsibility for both the public and private sectors to act to reduce the risks of a future pandemic.

AI-backed algorithms were already able to identify the initial outbreak in Wuhan

From China’s first report on a cluster of SARS-CoV-2 cases on 31 December, 2019, it took 23 days to lock down the city of Wuhan, and 30 days for the World Health Organization (WHO) to declare the outbreak a Public Health Emergency of International Concern. Meanwhile, the disease spread across continents, demonstrating a clear failing in efforts to measure the growth and movement of the outbreak, even within a country’s own borders.

As the pandemic slows across developed nations, through vaccination efforts, the question is what could have happened if initial outbreaks of SARS-CoV-2 had been identified sooner. Researchers from the University of Southampton predict that there could have been a reduction of up to 66% in infections in China if interventions such as early identification were employed only a week earlier.

Even with minimal information and resources, AI-backed algorithms were already able to identify the initial outbreak in Wuhan. The question therefore lies in how quickly governments could react in the future if further investment is made to develop new tools and processes.

Blue-chip companies are beginning to prioritize pandemic prevention but collaboration between the public, private and nonprofit sectors is key

There is a 22-28% probability that we will witness another pandemic in the coming decade, according to Metabiota. It is therefore fortunate that blue-chip companies are finally engaging in initiatives for improved pandemic prevention.

Microsoft, Tencent, Google and Facebook, are founders of The Trinity Challenge, an initiative which has awarded millions in dollars to researchers in this field. Several beneficiaries, including Participatory One Health Disease Detection, BloodCounts! and MedShr, are creating AI-backed infectious-disease surveillance software.

Over the past year, many other private-public-nonprofit collaborations have appeared on the scene alongside The Trinity Challenge, such as the Pandemic Action Network (including Johnson & Johnson, and the Wellcome Trust) and BARDA Ventures (US Department of Health and Human Services, and Global Health Investment Corporation). As more organizations understand their shared social responsibility to avoid another global pandemic, we can expect further financial incentives, regulatory efforts and international collaboration to help achieve this.