Youyang Gu

Data Scientist

Highlighting Role of Inequality in Covid and Beyond

October 1st, 2021

I work with a lot of numbers, but sometimes I see a statistic that’s so shocking that I have to stop what I’m doing and learn more. I had such a moment earlier this year: During the pandemic, while disadvantaged neighborhoods were ravaged by the virus, millions of people lost their jobs, and thousands of people died every day, the world’s billionaires actually got 39% richer.

On the surface, this may not seem all that concerning. But it turns out that income inequality is the single biggest predictor of Covid deaths in the US. I spent some time looking building a model for Covid mortaility using over 40 variables, ranging from population density to obesity rates. After numerous model iterations, income inequality, not income, shows up time and time again as the best single predictor of Covid mortality in US states. I show my findings in the Twitter thread below (or click here to read the complete 13-part thread).

Don’t just take my word for it. In their July 31, 2021 issue, The Economist explores this topic. In addition to my citing my findings, they also cite a recent study by Frank Elgar of McGill University and colleagues which found that a 1% increase in the Gini coefficient is associated with a 0.67% increase in the mortality rate from Covid-19. A separate county-level study of US counties out of Stanford University also concluded that higher inequality tends to lead to more suffering.

In a capitalist society, inequality is not intrinsically a bad thing. The more important question is how much inequality we are willing to tolerate. By most measures, a society where 40% of the workforce applied for unemployment during the pandemic while America’s billionaires saw their wealth grow by $1.1 trillion is certainly a problematic one. High income and wealth inequality is not something we can change overnight. It takes a conscious, deliberate effort and years of patience to even begin to reverse the current troubling trends. But the first step to a solution is acknowledging the problem. Often times, there’s so much data and numbers flying around that we end up being distracted from the core issues. I hope to use my skillsets and platform to cut out the noise and focus on the root of the problem.

One of the downsides of being a “data guy” is that I’m rarely exposed to the front line problems facing our society. By the time these issues manifest themselves as data in spreadsheets, they have already become so densensitized that I begin treating everything as raw numbers, rather than individuals that these numbers represent. These past 2 years have showed me that I must consciously work harder to make sure that the data I’m working with can lead to change and not become just another statistic.

That’s why I’m honored to be part of the Technical Advisory Group for the World Health Organization (WHO) on COVID-19 mortality, with a focus on inequality between and within countries. I feel especially grateful to be in a position where there exists a platform to amplify the work of myself and other researchers and spur meaningful change. I will do my best to contribute to the highest of my abilities. In the meantime, let me know if you have any advice, suggestions, or new data that you think may be helpful. Stay tuned!

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