New and out from the GenderSci Lab this week in the journal Social Science and Medicine is a comprehensive paper characterizing extensive heterogeneity in COVID-19 sex disparities over time and across states in the U.S. The paper is the first longitudinal study to quantify variation in COVID-19 gender/sex disparities across U.S. states.

Through what methods would we know whether COVID-19 deadlier for men than for women? In a new commentary just out in Women’s Health Issues, the GenderSci Lab examines the limitations of case fatality rate (CFR) as a metric for studying sex disparities in COVID-19 outcomes.

Below we explore how the authors of the 2020 Nature paper helped frame this small COVID-19 sex difference study as an unsubstatiated “Battle of the Sexes” in the popular press.

In our Matters Arising piece, we aren’t just arguing that there are some small issues with the original paper. We argue that its core claim is completely unsubstantiated: that the Takahashi et al. study does not, in fact, demonstrate that biological sex explains differences in COVID-19 patient outcomes.

The GenderSci Lab has decided to update our report card parameters, so that we now track states’ reporting of gender/sex interactions for three outcome variables (age, race/ethnicity, and comorbidities), plus nonbinary gender. Here we unveil our first report card in this new iteration, from April 2021.

Here, we will summarise our general reflections from our 8 months of tracking data collection and reporting through the current iteration of our Report Card. First, we'll describe the challenges of data collection, then we will explore changes we observed in the reporting of socially relevant variables by each state.

We recap the process of creating our COVID-19 State Report Card, which tracks the comprehensiveness of state reporting of socially relevant variables for COVID-19 cases and fatalities. Here we also provide the grades and results from our February 2021 report card.

In a collaboration with the Harvard SOGIE Health Equity Research Collaborative, today the Harvard GenderSci Lab has a new post up on the Health Affairs blog about gaps in COVID-19 public health data collection on trans, non-binary, and gender-expansive people.

This piece takes a more in-depth look at the current reporting of individuals who identify as non-binary or who are unclassified by sex. The take-home, summarized in Tables 1 and 2 below, is that there are few states explictly collecting data on trans and nonbinary people, and that the ways in which states report “unknown” gender/sex lack transparency and are highly discordant across states.

Our findings are stark. Black men are far more likely to die than any other group; but Black women have over 3 times higher mortality rates than white or Asian/Pacific Islander men (Figure 1). Further, the sex disparity within race varies widely.

The GenderSci Lab is looking for two undergraduate research assistants to assist with the lab’s current project analyzing sex & gender disparities in COVID-19 outcomes.

Highlights from December’s Report Card

From September to December, the average state score increased from 6.65 (D grade) to 6.78 (D grade) on a scale of 0-10.

Both Montana and New Mexico saw score increases of 3. This takes Montana’s score to a B grade, and New Mexico’s score to a D grade.

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Following the initial release of the GenderSci Lab’s Health Affairs Blog, Socially Relevant Variables in US State COVID-19 Surveillance Reporting: A Report Card, at the end of June, the lab has continued to track changes in state reporting of socially relevant variables for COVID-19 cases and fatalities. Data availability is becoming increasingly critical as many states experience a second wave of infections.

The “Gender/Sex Disparities in COVID-19 Outcomes” guide and toolkit is an open-access Google Slides presentation offered by the Harvard GenderSci Lab for adoption in introductory-level gender studies, feminist science studies, and health sciences courses. The presentation helps students develop a critical and intersectional understanding of sex disparities in COVID-19 outcomes.

Following the initial release of the GenderSci Lab’s Health Affairs Blog, Socially Relevant Variables in US State COVID-19 Surveillance Reporting: A Report Card, at the end of June, the lab has continued to track changes in state reporting of socially relevant variables for COVID-19 cases and fatalities. Data availability is becoming increasingly critical as many states experience a second wave of infections.

This is the July update to the US State COVID-19 Report Card. The Report Card tracks how US States are reporting socially relevant variables including race/ethnicity, sex, age, and interactions between these variables in COVID cases and outcomes. Our goal is to provide a source of transparent data accountability. The increased reporting of socially relevant variables is critical to understanding health inequities in the COVID-19 pandemic.

How well is your state reporting on socially relevant COVID data? At the most basic level, to understand the nature and extent of COVID outcome disparities, we must have data on gender/sex, age, race/ethnicity, and comorbidity status, and the interactions between them. Here, the GenderSci Lab releases a US State COVID-19 Report Card.

In most places, men are dying at higher rates than women of COVID-19. In this post, accompanying our Op-Ed in the NYT and the launch of our US Gender/Sex in COVID-19 Data Tracker, we explain how the explanation for this trend is not all biology. In fact, our findings strongly suggests that gender/sex differences in COVID-19 vulnerabilities mediated by social context.

As a part of its COVID Project, the GenderSci Lab began collecting weekly data on cases and deaths for the fifty U.S. States, Washington, DC, Puerto Rico, and the U.S. Virgin Islands on April 13, 2020, with data published today on our website. Here, we offer key take-aways from this first data roll-out. Stay tuned in future weeks for more insights!