How Asians Are Invisible in Data Analysis (Too)

The data for death rate by race published by New York City immediately prompted many to conclude that the reason blacks and Latinos are dying at higher rates must be because they are poorer, live in smaller apartments, commute longer, and have jobs with a higher risk of infection. Here is an example from The Intercept.

Now, if you are Asian, you will likely see that something is amiss here because the article does not mention Asians even though NYC’s chart includes them. There is nothing wrong with drawing those conclusions but not by ignoring one major racial group. If we are going to analyze the data and draw conclusions, we have to account for all the racial groups and see if our hypothesis holds up.

In New York City, Asians have the highest poverty rate at 24.1%, followed by Hispanic 23.9%, black 19.2%, and white 13.4%. See the data here.

For some, these numbers might be surprising, because many people think Asians are rich. Some are indeed rich, and if you are white, you likely know only these rich Asians, and the rest are invisible to you—hence the assumption.

If poverty were a significant cause of death from COVID-19, Asians should have the highest rate, but they have the lowest. How do we explain that?

Do poor Asians somehow avoid long commutes? Many Chinese workers in Chinatown commute from Flushing in cramped shuttle busses with even less space and ventilation. Many others take the subway from Brooklyn’s Chinatown and Flushing, just like blacks and Latinos. Many Chinese immigrants sleep on bunk beds with many others. Many of them work in restaurants serving and delivering food, as well as in retail and healthcare. So, none of those theories holds up if we examine Asians.

Perhaps these theories turn out to be correct in the end, but what is interesting to note is that people who propose these theories do not even try to take Asians into considerations. Asians are simply put aside as an anomaly or an “other” that does not need to be accounted for.