It’s a difficult moment in the global pandemic. As many cases were diagnosed in the past two weeks as in the pandemic’s first six months—led by Brazil and India, where more than half of those cases occurred. India, in particular, is recording more than 400,000 cases per day, and officials fear that’s a vast undercount. Even in the United States, where cases are subsiding, vaccination has slowed down too, pushing any decisive end out of reach.

That the pandemic is escalating, 16 months after it started, lends urgency to a handful of efforts to extract the lessons of this crisis in time to prevent the next one. Some are political, pointing out ways countries and the World Health Organization could perform better. Others are commercial, posing opportunities for tech firms. And some are big-ticket foundation-sponsored efforts. All aim to make this a moment of long-term change by enumerating the vulnerabilities this pandemic exposed—and confirming that this kind of opportunity has been squandered before.

“These are the same conversations we heard after the 2003 SARS outbreak, after the 2009 flu pandemic, after the 2014 Ebola and 2016 MERS and 2018 Ebola outbreaks,” says Rick Bright, the former director of the US government’s Biomedical Advanced Research and Development Authority (BARDA), who resigned from the federal government to protest how the Trump administration was handling Covid. “We keep having the same conversations—What lessons do we learn? What do we do better next time?—and we still keep missing it.”

In March, Bright became senior vice president of pandemic prevention and response at the Rockefeller Foundation, where he is tasked with building a “pandemic prevention institute” as part of a $1 billion investment toward recovery from Covid. Bright’s institute is one of the first highly funded efforts to try to make something new out of the detritus of Covid: an analytics hub that will sift through national repositories of genomic and social data to find global patterns.

But a different big-ticket effort seems likely to be the first to write some checks. Next month the Trinity Challenge, a competition based at Cambridge University in the UK, will make its first awards for novel approaches to harnessing public and privately held data: a top prize of £2 million, with several runner-up prizes of £1 million each. (That’s about $2,777,000 and $1,398,000, respectively.) The teams have been asked to aim for one or several goals: identifying new epidemics as early as possible; developing affordable, equitable measures to reduce transmission and spread; or addressing how outbreaks hit poor nations and disadvantaged groups hardest, while making health care systems more resilient to those shocks.

The challenge is the creation of Sally Davies, a physician and the former chief medical officer of the United Kingdom, who became the master (or head) of Trinity College in late 2019. “What we have been missing is not just health data—numbers infected and in the hospital and getting better—but behavioral data, economic data, mobility data,” Davies says. “They will all impact how we should make policy, how we should interpret our response, and how we could recover. Yet that data is not accessible to governments and public health agencies. It’s the big tech companies who hold it. So how do we tap into that? I thought: a collaboration—bringing together academics, who can ask the questions with rigor, with the people who hold the data and have the great engineers—to sponsor a public challenge asking people to come in with their solutions.”

To do that, she recruited sponsorship and technical support from major tech companies including Facebook, Google and Tencent—along with media companies, drug firms, and research universities. The partners contribute to the total prize pool of £10 million and also make their staffs’ expertise available to the small teams who apply. It’s a fast-moving effort: The first round of submissions opened in February and closed in April. The entries, which are public, include networked rapid diagnostic devices, algorithms that monitor social media to parse the mood of the public, models that track the global supply chain of needles, and mapping of the distribution networks in rural areas of women who sell health products.

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