How Will Big Data Analytics Factor into the Next Phase of COVID-19?

May 07, 2020 - As COVID-19 has made its way across the US and around the world, healthcare stakeholders from all areas of the industry have prioritized containing the outbreak. Leaders at all levels have utilized advanced big data analytics tools and other technologies to reduce the impact of the virus, understand its nature, and protect those who are most vulnerable to severe illness.

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Phrases like flattening the curve and social distancing have become regular adages in the nation’s vocabulary, with the whole country seemingly holding its breath in anticipation of the end of the pandemic.

In the midst of the silence that has abruptly settled over the US, there are initial talks of reopening the country, reducing quarantine measures, and beginning to get closer to normal – the next phase of the coronavirus response.

But what exactly will the next phase of COVID-19 entail, and are states ready to make the leap? According to Julie Swann, PhD, professor and department head of the Fitts Department of Industrial and Systems Engineering at North Carolina State University, the answer is complex, and will largely depend on the country's ability to test and trace infected individuals.

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“People mean different things when they talk about the next phase of the pandemic,” she told HealthITAnalytics.

“Right now, in the US, we're only beginning to ramp up our testing and roll out testing for antibodies. We'll need to get to the point where we’re not only testing individuals, but also retesting people for their antibodies to get some sense of who has been exposed and who might have some level of immunity.”

Reaching that point may be easier said than done. While some coronavirus antibody tests are currently available in the US, these tests may lack appropriate standards or guidelines. A recent staff memo from the Subcommittee on Economic and Consumer Policy showed that federal agencies have failed to review the efficacy of antibody testing, allowing inaccurate and potentially fraudulent tests to spread unchecked.

To develop comprehensive, valuable antibody testing, and to speed vaccine development, organizations will need to leverage advanced big data analytics tools, Swann said.

“There's a lot of uncertainty about how much immunity is generated by having the virus a first time. Data and analytics technologies will help us better understand that level of immunity and what that means for the future,” she said.

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Several organizations have started to utilize these technologies to accelerate COVID-19 drug discovery and better comprehend how the immune system fights the virus. In early April, pharmaceutical companies GlaxoSmithKline (GSK) and Vir Biotechnology partnered to advance coronavirus treatment development using artificial intelligence and CRISPR.

And in the academic sector, the Harvard T. Chan School of Public Health recently joined forces with the Human Vaccines Project to launch the Human Immunomics Initiative, which utilizes artificial intelligence models to accelerate vaccines for a range of diseases, including COVID-19.

In addition to enhancing drug development, data analytics tools will play a major role in mitigating the spread of the virus going forward. As the US starts to consider reopening the economy, these tools will be essential for preventing a second wave of infections that could overwhelm hospitals and health systems.

“We’ll need to deploy data analytics tools in schools, hospitals, and workplaces to make sure that we are screening people appropriately as they come in the door of those settings,” Swann said.

“We will also need to have resources developed and allocated for contact tracing when someone tests positive, which will involve data on someone's social network and the interactions that they have had over a period of time. We’re likely to see more apps and data applications that aim to make contact tracing more efficient and effective.”

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Examples of such applications have sprung up from research entities and tech companies across the country. A team from Southern Illinois University (SIU) recently developed a data visualization tool that leverages GPS information to show users the locations of known COVID-19 cases. Industry giants Google and Apple have also partnered to develop a contact tracing app powered by Bluetooth technology.

However, as effective as these tools have the potential to be, they inevitably come with possible privacy risks. Two weeks after announcing their partnership, Google and Apple had to update their initial contact tracing app proposal to address feedback and privacy concerns from industry stakeholders.

Australia and the UK faced similar criticisms upon releasing their own coronavirus contact tracing apps.

In order for these technologies to play any role in the next phase of the pandemic, developers and policymakers will have to make data privacy a top priority.

“With these data and technology changes, we'll need to deal with potential privacy concerns – whether those concerns are specific to healthcare information or more general apprehensions,” Swann said.

With the nation’s attention starting to shift toward relaxed social distancing, the reopening of non-essential businesses, and the faint light at the end of the tunnel, it’s critical to consider what strategies and tools the industry needs to stay ahead of future health crises.

As Swann pointed out, these strategies will need to principally center around proactive data tracking at a granular level.

“We need to have better surveillance that goes down to a lower level of what we have had in the past. And this surveillance needs to be nearer to real time and at a local level. If you look at the US’s influenza-like illness surveillance, it's great at the national level, and it's pretty good at the state level. But it's not very good at community levels,” said Swann.

“We should be using technology and data to track potential infections – like fevers and influenza-like illnesses – which precede the confirmation of cases. By doing that, and then using corresponding analytics, we may be able to identify areas of a micro surge before that outbreak has gotten out of control.”

Going forward, improved methods of surveillance will have to extend to healthcare supplies and resources, and better ways of testing the population should also be top of mind.

“We need to have systems that allow us to stock and supply critical medical products and track the utilization of those critical medical products, including masks, ventilators, and pharmaceuticals,” Swann stated.

“We also need the ability to ramp up testing, which includes being able to produce the test in large numbers as well as process the samples in large numbers.”

Leaders at the national, state, and local levels should also utilize analytics tools to refine models that quantify the impact of non-clinical interventions.

“Numerous states have seen the value of models that can allow users to test out different social distancing and intervention scenarios. A lot of those got ramped up in a short amount of time, and that's something that's going to continue,” said Swann.

“Right now, a lot of the distancing policies are at the level of the state, or even a large city or county. But if we can get to a place where we're using data analytics more effectively, we may be able to target our distancing policies and interventions based on current conditions.”

Ultimately, moving into the next phase of the COVID-19 pandemic and beyond will require partnerships, data exchange, and advanced analytics techniques that will benefit the greater good.

“Organizations will need to agree to cooperate and share their data in a way that might not necessarily mean monetization of the results,” Swann said.