Protecting the Health of Our Most Vulnerable Populations Means Understanding Their Motivations

Coronavirus disease 2019 disparities persist in our most vulnerable communities because of the financial necessity to continue working, as well as the lack of employment opportunities that enable their residents to work remotely. They are more likely to be considered essential workers, and that increases their exposure to the virus, explained Blythe Adamson, PhD, MPH, principal quantitative scientist at Flatiron Health.

Transcript:

Lower-income communities and racial and ethnic minority populations have been especially hard hit by the coronavirus disease 2019 (COVID-19) pandemic: Is there a way to optimally study these populations to overcome these disparities if there is a second wave this year or if COVID-19 becomes a yearly infectious cycle?

It’s been terrible to watch these low-income communities and racial and ethnic minorities be so hard hit by COVID. Some of the ways that we are beginning to understand why this might be happening is 2-fold: One of the things that puts people at higher risk is the need to continue going to work. And so these lower-income communities and racial and ethnic minorities are much less likely to have jobs that are suitable for working from home and are still in positions and in pressure to continue going to work and putting themselves at risk; you know, more likely to be an essential worker.

So now they're more likely to get infected, and now once they're infected—this is the second part of what piles on this additional burden of disease—and that's that we're seeing patients who are lower income or racial and ethnic minorities are more likely to have diabetes. They're more likely to be overweight and obese. And these are 2 characteristics that we know make an infected person much more likely to become a severe case and have a higher risk of death from COVID compared to other patients. And so both the amount of risk of even getting infected, and then once you're infected, to be more likely to have adverse outcomes, those are 2 reasons that we see that burden.

And then the part of your question about how do we study this, how do we understand this more? It's been really interesting to watch so many researchers using mobility data. Many of these data sources are publicly available, either from cell phone tracking or transportation. And we can see that in communities that are lower income that are still having to go to work, we can see that when a lockdown policy begins, it's often the lower-income communities that still are not reducing their mobility as much as higher-income communities and primarily because they are still having to go to work. So we need to keep following this and understand more through surveillance data, as testing continues to scale and we understand more about these vulnerable communities, how we can best protect them.