(Pandemic) COVID-19 a year later: What have we learned? (Dario Gil, WEF)

On 31 December 2019, the world welcomed a new year unaware that several cases of viral pneumonia of an unknown cause had emerged in the Chinese city of Wuhan. Forty-four people were ill, 11 – severely – and those cases were reported to World Health Organization’s Country Office.

Those few cases of COVID-19 grew to a few hundred and then to a few thousand until that trickle became a flood, spilling out of mainland China and spreading across the globe. Just one year later, we’ve amassed 85 million cases and counting.

We’ve learned a lot during the past year about how to address global crises, but in my mind, one lesson cannot be ignored: The need for more strategic collaborations across institutions and sectors.

The power of collaboration was proven again and again. Shortly after the virus got its name, Chinese researchers published the first sequence of its genome. To widen its use, IBM scientists later processed all sequenced SARS-CoV-2 genomes, resulting in more than three million sequences – genomes, genes, proteins and other molecules. They added this data to IBM’s Functional Genomics Platform – a repository for researchers working to identify molecular targets for drug design, test development and treatment.

That platform now sports more than 300 million biological sequences extracted from various microbial genomes, with the coronavirus’s genome the newest kid on the block. It’s all open source – another key ingredient for success, along with collaborations.

Updating this platform happened at a crazy speed, just like many other COVID-19 related projects. I’m certain IBM isn’t unique in this – still, having seen my colleagues’ efforts firsthand, I was amazed at how everyone had a shared sense of urgency and a willingness to work together to speed the search for solutions. For me, IBM’s COVID-19 Technology Task Force put together to address the crisis has been the most naturally collaborative project I’ve ever led.

As we worked, the coronavirus remained ever-present, seemingly inescapable. I, myself, was deeply affected when I learned in March, that my cousin in Madrid, a medical doctor, had also contracted the virus. Moments like that drove home the fact that no person or organization could conquer COVID-19 alone. That thought led to a critical moment of inspiration, however. I called the White House – and in just over a week of discussions, established a global partnership I’m especially proud of – the COVID-19 High Performance Computing Consortium.

This public-private collaboration now has 43 members – national labs, universities and tech companies, many typically industry rivals, including Google, Amazon Web Services, Dell, Microsoft and others. Together, we’ve given researchers worldwide free access to powerful computing resources they normally wouldn’t have. The Consortium has sped up and enabled dozens of COVID-19-related projects around the world – from drug design to analyzing the propagation of the virus to splitting ventilators between multiple patients, and more.

Alongside establishing the Consortium, we’ve also adapted our cloud-based AI platform Deep Search, to aid in drug design. Knowing whether there have been attempts to design a molecule with specific properties and identifying knowledge gaps is crucial. The AI has been trained to do exactly that, combing through and ingesting thousands of scientific papers on the COVID-19 Open Research Dataset and databases at DrugBank, Clinicaltrials.gov and GenBank, turning the data into easy-to-read open access graphs.

When the truth really matters

While therapeutics and vaccines are critical to halt a pandemic, so is information. There has been a deluge of disinformation and fake news about COVID-19, from conspiracy theories claiming that the coronavirus is a bioweapon created in a Chinese lab to websites declaring the virus doesn’t even exist. Fake news has prompted people to hit the streets in anti-lockdown protests, potentially exposing themselves to the virus in a crowd, or refusing to wear masks and respect social distancing.

This is once again where collaborating has worked wonders. Working with The Weather Company, we created a smartphone app for mapping the spread of the virus across the U.S. The Weather Company App and weather.com now display a color-coded map with county and state-wide trend graphs and statistics on the increase or decrease of cases. The app pulls data from trusted sources including the World Health Organization and Johns Hopkins University, as well as sources at the state and county level.

Typically, an app like that could take months to build. Together, IBM and the Weather Company did it in just over a week. Everything changes when it’s a race against time.

There were many other examples of new and effective collaborations. Collaboration is, after all, how three of the leading vaccines were created: Oxford University and AstraZeneca exemplify the power of academia and industry coming together, while start-ups combined with industry leaders and the government led to the BioNTech/Pfizer and the Modern vaccines, respectively.

But more global crises are inevitable, be it another pandemic, a particularly devastating earthquake, a mega drought or even a meteor strike over a city. And this is when the lessons we’ve learned during the rather surreal 2020 will come in handy: The lessons in accelerating drug design; The lessons in tackling misinformation; The lessons in developing technology essential to save lives fast; And most of all, the lessons in creating more global public-private collaborations – because they work.

I have a way to kick-start this process. We need to create the Science Readiness Reserves (SRR), a partnership on a truly global and multi-disciplinary scale, with industry, academia, and government scientists working side by side. Researchers from different fields would assess the risks of a specific disaster in advance and develop an action plan to deal with it when it strikes.

The SRR’s core team would then put them in touch with the necessary facilities to speed up the process – from supercomputing resources to genomic sequencing to asteroid tracking systems, and more. And the SRR would also liaise with policymakers to put the proposed plan into action as soon as needed and as efficiently as possible.

Eventually, this pandemic will end. We will travel again. Many of us will return to the office and our kids will swap home learning for an actual school. We’ll finally chill at that concert we were dying to go to last year before it got cancelled, gasp at amazing art at that exhibit that’s had a ‘temporarily closed’ sign for months, or throw a proper birthday party with friends laughing next to us and not on a video call.

Those are everyday moments that the crisis took away. The Science Readiness Reserves can help us protect those everyday moments, and help ensure they aren’t halted or disrupted and that the world is not caught unaware again.

We can outsmart the next crisis. But we have to act now to make it happen. We must make sure that next time we’re prepared.