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Description

Background: Emerging surveillance data from the COVID 19 pandemic suggest better outcomes in women.

Objective: This analysis aims to determine the magnitude of sex differences in SARS-CoV-2 infection rates and survival at a country level.

Methods: Data was sourced from the Global Health 50/50 (GH 50/50) website https://globalhealth5050.org/covid19, housed at University College of London, which collects government reported national surveillance data on confirmed cases of COVID 19 and confirmed deaths. This analysis used data completely disaggregated by sex, cutoff date 5/8/2020.

Results: Of 78 countries, with 3,044,513 confirmed cases of COVID 19 and 181,742 deaths, data were completely disaggregated by sex in 36 countries, partially disaggregated in 26, and not disaggregated in 16. In countries, with completely disaggregated data, 1,240, 803 cases of COVID-19 were reported on May 3, 4, 5 or 6, 2020 in 31 countries, and between Feb 28 and April 28 in 5 countries. The average proportion of cases in women was 50.3%: range 22% (Pakistan) to 63% (Netherlands). Deaths were reported in 83,388 individuals. The mean proportion of deaths in women was 39.2% (range 20% to 53%). The mean ratio of deaths (men to women) was 1.62 (range 0.9 to 3.2).

Discussion: This analysis of surveillance data from 36 countries shows a sex difference in mortality from COVID-19, with men more likely to die than women. Possible explanations include sex differences in the immune system, gender differences in environmental exposures or access to healthcare, and differences in comorbidities. Additional research to assess potential causes, and collect and analyze data by age, race, and ethnicity as well as sex and gender would be of value. These observations highlight the importance of disaggregating data by sex and gender in order to understand disease susceptibility, prevalence, and outcomes.

Publication Date

9-2020

Keywords

sex and gender, COVID 19

A Lesson from COVID-19 in the Importance of Sex Disaggregated Data: Sex Differences in SARS-CoV-2 Infection and Mortality Rates

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