How data could help predict COVID outbreaks

It’s an unfortunate but pervasive truth: The realities of COVID-19 are far from over. In fact, cases are actually picking up again — along with the easing of US restrictions, quarantine fatigue, the waning effectiveness of vaccines, and the growing (but misguided) belief that the pandemic is behind us. Now with current reports present rising infections and hospital admissions in Europe and renewed emphasis on new media reports Lock out In China, it is clear that as a society we must face a harsh reality in the fight against COVID-19: We are not over the hill yet.

If we hope to adjust to this new normal – one in which COVID cases have regularly fluctuated – we must be willing to change our perception of how we are keeping this virus in check. Gone are the days of the “COVID-free” future. On the contrary, it is no longer about how we defeat COVID-19, but how we learn to live with it. This starts with simple wisdom and data.

I believe that as a society, we need to rethink how we consolidate, analyze and distribute data related to COVID-19 infections, leveraging data science and technology – and providing more in-depth guidance for those struggling to control their exposure understand local, regional scale, and national scale. Fortunately, this type of infrastructure already exists and is easy to deploy. It just requires testing companies and population health managers to work together to usher in a new era of dealing with this virus, using predictive models to stay ahead of it. In this way, we could live in a world where COVID data allows us to predict and adapt to outbreaks, much like a weather forecast for a blizzard or hurricane. Here’s how:


Hypothetically, for a moment, imagine this: you open your phone, pull up your weather app, and search the National Oceanic and Atmospheric Association (NOAA) for a 10-day weather forecast. Instantly get a comprehensive overview of weather models for each relevant day, including risk profiles for UV exposure and other dangerous conditions. Why can’t our COVID-19 models – and our testing infrastructure – work the same way?

If we hope to adapt to the realities of a COVID-normative world, we must create predictive models that not only account for “clear and present” hazards, but also provide a risk exposure forecast for the days and weeks ahead. Armed with these real-time insights, we can indeed predict with varying degrees of certainty how COVID cases will rise and fall in the future. Similar to what scientists use sewage Analysis as a predictor of future COVID outbreaks, we can use the data collected from multiple sources to predict where we are going next.


With data spotlighting the way forward, prevention becomes less of a catching up game and more of a planning game. For example, if predictive measures indicate an impending surge, centralized data collection sources, such as For example, an app on a smartphone alerts you (or a healthcare manager) to the importance of taking preventive action before, not after, an outbreak occurs. Additionally, with appropriate data analysis infrastructure and highly targeted testing, these predictive models could analyze risk levels at the hyper-local scale and potentially change the way we regulate schools, communities and workplaces. Much like stocking up on supplies during a hurricane, tools like these could allow us to prepare for upcoming outbreaks before it’s too late and give us time to protect ourselves and our families every step of the way.

To protect

It’s worth noting that testing data and timely, targeted digital interventions not only benefit the healthy — they can also help protect infected individuals from worsening symptoms. Indeed, by employing state-of-the-art test-to-treat methods, we can now provide those who test positive with more effective and immediate access to potentially life-saving treatment. Indeed, by combining hyper-personalized interventions with community-based alerts and predictive guidance, we can pinpoint a potential hotspot down to the smallest detail—and implement personalized solutions to address it.

Make no mistake: we are at a crossroads in our fight against COVID-19. We can no longer sit idly by and assume that if we wait long enough, COVID will go away. On the contrary, if we hope to defeat this virus, we must be ready to find it and nip it in the bud by putting in place processes that holistically predict, prevent, and protect against infection. Luckily, through regular testing and data modeling, this is not just a possibility, it’s a probability. By being proactive, breaking down silos and collaborating across sectors, we can build a new-age COVID infrastructure – powered by data – that brings us one step closer to a post-quarantine future. Let the next phase in our fight against COVID begin.

Ron Gutman is the CoCEO of Intrivo, maker of the On/Go COVID-19 Rapid Tests. How data could help predict COVID outbreaks


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