Covid-19 and scientific studies: a question (also) of gender

Antonietta Mira (r.) and Ilaria Capua (l.)
Antonietta Mira (r.) and Ilaria Capua (l.)

Institutional Communication Service

6 August 2021

What do Covid-19, big data and gender issues have in common? Quite a lot, according to Antonietta Mira, Full professor of Statistics at USI, and Ilaria Capua, virologist and Director of the One Health Center of Excellence at the University of Florida, who recently published their views in an exclusive interview for Ticino Scienza which focuses on the importance of the sex/gender dimension in the collection of data related to the novel coronavirus outbreak.

When affected by a given disease, women and men may present different symptoms and outcomes. Take for instance cardiovascular diseases: it has been recognized that women have different symptoms in heart attacks than men - an issue that can make the difference between surviving or dying. This recognition was achieved thanks in part to the systematic collection and analysis of gender-differentiated data. But what about the novel coronavirus?

"In two recent articles, one published in Nature Communications and the other in The Lancet, we point out that the majority of current clinical trials on SARS-CoV-2 make no mention of the sex/gender distinction, as well as the related disaggregated data analysis, which would be of great benefit for regulatory and public health decisions, for example for the design of mass vaccination programs", the two experts write.

The OECD and UN have guidelines to help assess whether a gender perspective is relevant to a scientific study and, if so, proceed to collect data with the gender dimension. "We believe that it is really time to take a different approach. Instead of putting more effort into clarifying whether the sex/gender dimension is relevant and therefore measured, collecting it should be done by principle, i.e., by default. We are thinking about the 'embedded' approach: post-pandemic data, not just health data but all person-related data in general, must include sex and gender dimensions, otherwise they would be considered incomplete", Mira and Capua explain.


The original article is available (in Italian) at: