Gender and sex bias in COVID-19 epidemiological data through the lens of causality

Autor: Natalia Díaz-Rodríguez, Rūta Binkytė, Wafae Bakkali, Sannidhi Bookseller, Paola Tubaro, Andrius Bacevičius, Sami Zhioua, Raja Chatila

Publikováno v: Information Processing and Management
Information Processing and Management, 2023, 60 (3), pp.103276. ⟨10.1016/j.ipm.2023.103276⟩

The COVID-19 pandemic has spurred a large amount of experimental and observational studies reporting clear correlation between the risk of developing severe COVID-19 (or dying from it) and whether the individual is male or female. This paper is an at

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c06044c6fb27efee241162094a75219
https://doi.org/10.1016/j.ipm.2023.103276