Sex, Gender, and the Problem with COVID-19 Open Data
So, what is the big deal if patients are incorrectly categorized by sex and gender?
Searching for your state’s COVID-19 data will most likely take you to a dashboard, displaying data in graphs and tables. But if you compare the dashboards from one state to another, you will notice the labels that are used differ. Some states use “black” while other states use “African-American non-Hispanic” to describe the same person. Even health conditions are described differently. To illustrate the differences between labels, here are three states that classify a patients’ pre-existing health conditions in vastly different ways.
This graphic from Arizona classifies people as either having a chronic medical condition, being high-risk, or not. While there is a small list at the bottom of what a chronic medical condition counts as, we do not know if this is a full, exhaustive list.
The state of Wyoming classifies people as either having underlying medical conditions or not. A category is provided for those whose underlying health conditions are unknown.
Lastly, Louisiana classifies those who have underlying conditions by which specific condition they have. These conditions include, but are not limited to, asthma, diabetes, obesity, and cancer.
While labels can differ in describing housing conditions, current health state, and job sector, my interest in COVID-19 data is the labels applied to people to describe their body identity.
The term “body identity,” coined by Dr. Anne Washington, professor of data policy at NYU, is used to describe the relationship between one’s identity and their family heritage, color, reproductive organs, chromosomes, hormones, and outward presentation.
When analyzing COVID-19 data, our research group looked at what labels are utilized to describe body identity in publicized state data. The graph below reports findings from NYU’s Digital Interest Lab.
“Sex and Gender Demographics” chart by Hope Muller, @Digital Interests Lab.
While the use of sex and gender was fairly even, an overwhelming amount of states included only two options. Very few included options for non-binary individuals, such as neither, or other.
The problem here is that states are using labels for body identity incorrectly. Sex refers to the way one’s body functions and is typically reliant on reproductive organs and chromosomes. Gender refers to how one identities and usually depends on self description. Gender can include many labels, not just two. And while sex tends to encompass males and females only, intersex people can also be included, since they have biologically diverse hormones, reproductive organs, and chromosomes.
So, what is the big deal? Why does it matter if labels are being used incorrectly?
In this case, an entire demographic of people is erased. Just recently, the Trevor Project conducted a study and found that 25% of LGBTQ+ youth used they/them pronouns. While not all of these individuals identify as a different gender than their sex, some do. When states include only two categories of body identity, states are erasing non-binary, genderfluid, transgender, and agender people.
This erasure particularly impacts younger people, who are using new, diverse labels each day to describe their gender. During a global pandemic in particular, ensuring that all people are included in data, and are included in data correctly, is key.
Healthcare providers may be unaware that they have to consider a different level of risk than what the “M” or “F” marker on their patient’s form tells them.
It was found recently that men and women may have differences in COVID-19 outcomes due to hormones. Women experience COVID-19 less intensely than men. As a result, some doctors are testing whether estrogen and progesterone can help men battle COVID-19 symptoms. This can pose a problem for transgender people who were born female and now take testosterone to develop more male characteristics. Their chart may read “F,” but their body reads “M” or “N.” These people, on the basis of their chart, may be passed up for the opportunity to use this treatment that could mean the difference between survival or death.
Lastly, consider what it says that even when we know that COVID-19 affects marginalized populations more, including the transgender community, governments choose to label the data in a way that makes it seem as if COVID-19 is affecting everyone equally. If governments today fudge data to serve specific political agendas, this will impact the trust between the government and the people for years to come.
The LGBTQ+ community is no stranger to distrusting the government. When the Department of Health and Human Services said it was going to roll back protections from discrimination for transgender people, while heartbreaking, it was nothing new to us. Today, many of us are still mourning the loss of our loved ones from HIV and AIDS. They died because our healthcare system did not see them nor treat them as patients deserving care.
Now that the world has to fight against a contagious pandemic, we cannot let any community go unseen or unheard. Not only should we value people for who they are, but allowing groups to feel dispensable, causing them to avoid healthcare, can spread COVID-19 even more.
The benefits of jotting down one’s body identity correctly, or recording gender AND sex, are invaluable. We establish trust, give respect, and are able to track, treat, and make accurate assessments using data.
As a transgender person myself, I have experienced doctors telling me they cannot help me prior to my visit, because they assumed I was born female and still identify as such. I have had counselors misgender me during some of the most volatile times of my life. I have had anxiety attacks wondering how I would correct people who used wrong data about me to draw conclusions.
The numbers in the data are there to tell a story for people living through events and for those who will never live through it. My data, and the data of thousands of transgender Americans, tells a story and we do not want that story to be told wrong.
