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16 Trinity Challenge Finalists Hold Out Hope For Future Pandemic Management

We may all be suffering from media fatigue around Covid-19, but the fact remains that the last year and a half has exposed a drastic and widespread mismanagement of a crisis that is still not over. As of this writing, more than 3.5 million people are known to have died from the novel coronavirus, with more than 171 million cases worldwide. Almost no one has escaped some brush with the disease, whether losing a loved one or knowing someone whose world has been permanently shaken in some way, particularly psychologically, by it. Yet despite myriad past pandemics—from SARS to MERS, Ebola and Avian Flu—we as a global society are still sorely unprepared for future pandemics. We know that with increasing world population density and climate change we are in for more frequently occurring pandemics. The issue is not if but when, and how soon.

Last fall I wrote about The Trinity Challenge, a new collaborative effort to crowdsource data and science-driven solutions to address the current lack dearth of global pandemic preparedness. As I mentioned back when the Challenge was calling for submissions, my company has been involved on the level of financial support, as well as offering our data and analysis expertise and statistical, real-life actuarial experience in aging, mortality and morbidity.

Now I’d like to add some updates on this initiative, starting with the good news that the Challenge received 340 applications from 61 countries, and of those 16 submissions have been shortlisted as finalists. On June 25th the winning solutions will be announced, as well as how much prize money will be allocated to realizing those ideas. While I can’t divulge too much here, I can give you a sense of the types of entries the judges have been looking at, as well as provide an comparative overview a few specific solutions other innovators have already been taking, independent of the challenge.

Interestingly, many of the Trinity Challenge solutions come from experts who are tuned into the crucial role of government, and who look at the intersection of policy and technology in providing solutions to pandemics. Their innovations use modern data and advanced analytics to manage disease outbreaks in new ways that can be more effective, less expensive and benefit more people and communities throughout the world. To me, this is one of the broadest practical applications of inclusive capitalism that anyone could ask for—a technology-based investment in innovation that benefits the health of a worldwide swath of people.

Here are some of the approaches Challenge submissions have taken:

1. Crowdsourced scientific insights. These solutions provide digital tools to connect farmers, community health workers and doctors who are on the front lines of potential disease spread and spillover from animals, enabling them to crowdsource large sets of data in real time.

2. Addressing health response where it is most needed. Some solutions propose to close data and technology gaps in low- and middle-income countries, using new and innovative digital tools, point-of-care diagnostics and blockchain technology to track vaccine delivery.

3. Predictive power of sewage and other environmental data. These proposals deploy leading-edge IoT sensors to measure the presence of pathogens in sewage, in the air, or among disease-carrying insects.

4. Natural Language Processing. Addressing the communication shortfalls we saw through Covid, some solutions use technology to rapidly create up-to-the-minute knowledge summaries by analyzing text via natural language processing to predict patterns and respond faster. Analyzed sources may include news, disease surveillance reports, physicians’ clinical notes, and publications.

5. AI and Machine Learning. To sort through big data sets, some proposals look to embed artificial intelligence and machine learning to further our understanding of emerging data, such as unlocking routine blood tests, helping inform policy makers toward better informed decisions.

I’ve seen a few specific projects from outside The Trinity Challenge that seem to be heading in some similar directions. For example, a team from Broad Institute in Massachusetts has been tracking the genetic fingerprint of Covid-19 virus strains to identify where the virus spread. While contact-tracing individuals at massive numbers is nearly impossible – several U.S. states gave up the effort once infection numbers had gotten too high – tracing at this level becomes possible when you look at viral fingerprints rather than individuals’ interactions. The team at Broad was able to identify one person who carried a strain with a particular genetic mutation to a Biotech conference in February, which led to at least 245,000 infections of the same fingerprint across the U.S. and Europe.

In another example, in the early days of the pandemic scientists in Chicago used the pro-bono analytics work of Cambridge-based wastewater epidemiology company Biobot to investigate wastewater samples for traces of the novel coronavirus in city sewers, which can show up a week before cases become symptomatic. Their research enabled the city to track outbreaks on a larger scale than individual testing, and gave local governments several days’ extra lead time to act.

Also noteworthy is a new book by epidemiologist Adam Kucharski, an infectious disease expert at the London School of Hygiene & Tropical Medicine. The Rules of Contagion: Why Things Spread – and Why They Stop lays out a mathematical model of disease spread while addressing complex sociological issues surrounding disease control, from misinformation—which can spread like a disease—to gun violence.

Another promising research project comes from Dr. Paul Lantos of Duke University, who is studying the spatial epidemiology of infection: using geographic information software (GIS), his team found clusters of infection, noting that communities of color were more likely to test positive for the coronavirus; he addresses ways in which neighborhood density, household size, and socioeconomic status can predict risk.

Undoubtedly particants in The Trinity Challenge will draw upon some of the key lessons we have learned this past year: don’t underestimate the threat, focus on public education initiatives with centralized and coherent messaging, find the weakest link, and look to existing knowledge.

Looking at the obvious shortcomings in our management of the current pandemic, it’s clear we have our work cut out for us for the next one. When we have the technology and the resources, there’s simply no excuse to leave others out in the cold. This is the time to push for new solutions, backed by funding and data, to help the broadest possible swath of the global community. It’s an opportunity to push for the high-risk, but high yield types of

interventions that we are going to need to deal with longstanding threats to the health of global communities and new emerging pandemics. Which of the Trinity Challenge innovators will be chosen to actualize their winning solutions?

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