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COVID-19 affects people differently, in terms of infection with the virus SARS-CoV-2 and mortality rates. In this Special Feature, we focus on some of the sex differences that characterize this pandemic. Share on Pinterest The data that are available so far indicate that there are significant differences between how the sexes respond to the new coronavirus.

All data and statistics are based on publicly available data at the time of publication. Some information may be out of date. Visit our coronavirus hub for the most recent information on the COVID-19 pandemic.Was this helpful?

There are many ways in which the pandemic itself affects peoples day-to-day lives, and gender understood as the ensemble of social expectations, norms, and roles we associate with being a man, woman, trans- or nonbinary person plays a massive part.

On a societal level, COVID-19 has affected cis- and transwomen, for example, differently to how it has cismen, transmen, and nonbinary people. Reproductive rights, decision making around the pandemic, and domestic violence are just some key areas where the pandemic has negatively impacted women.

However, sex differences understood as the biological characteristics we associate with the sex that one is assigned at birth also play an undeniable role in an epidemic or pandemic.

While sex and gender are, arguably, inextricably linked in healthcare, as in every other area of our lives, in this Special Feature, we will focus primarily on the infection rates of SARS-CoV-2 and the mortality rates that COVID-19 causes, broken down by sex.

In specialized literature, these effects fall under the umbrella term of primary effects of the pandemic, while the secondary impact of the pandemic has deeper social and political implications.

Throughout this feature, we use the binary terms man and woman to accurately reflect the studies and the data they use. Sex-disaggregated data lacking

Before delving deeper into the subject of sex differences in COVID-19, it is worth noting that the picture is bound to be incomplete, as not all countries have released their sex-disaggregated data.

A report appearing on the blog of the journal BMJ Global Health on March 24, 2020, reviewed data from 20 countries that had the highest number of confirmed cases of COVID-19 at the time.

Of these 20 countries, Belgium, Malaysia, Netherlands, Portugal, Spain, United Kingdom, and the United States of America did not provide data that was disaggregated, or broken down, by sex.

At the time, the authors of the BMJ report appealed to these countries and others to provide sex specific data.

Anna Purdie, from the University College London, United Kingdom, and her colleagues, noted: We applaud the decision by the Italian government to publish data that are fully sex- and age-disaggregated. Other countries [] are still not publishing national data in this way. We understand but regret this oversight.
At a minimum, we urgently call on countries to publicly report the numbers of diagnosed infections and deaths by sex. Ideally, countries would also disaggregate their data on testing by sex.

Anna Purdie et al.

Since then, countries that include Belgium, the Netherlands, Portugal, and Spain have made their data available.

The U.K. have made only a part of the sex-disaggregated data available for England and Wales, without covering Scotland and Northern Ireland while Malaysia and the U.S. have not made their sex-disaggregated data available at all.

At the time of writing this article, the U.S. still have not released their sex-disaggregated data despite the country having the highest number of COVID-19 cases in the world.

For more research-backed information and resources for mens health, please visit our dedicated hub.Was this helpful? Men more than twice as likely to die

Global Health 5050, an organization that promotes gender equality in healthcare, has rounded up the total and partial data that is available from the countries with the highest numbers of confirmed COVID-19 cases.

According to their data gathering, the highest ratio of male to female deaths, as a result of COVID-19, is in Denmark and Greece: 2.1 to 1.

In these countries, men are more than twice as likely to die from COVID-19 as women. In Denmark, 5.7% of the total number of cases confirmed among men have resulted in death, whereas 2.7% of women with confirmed COVID-19 have died.

In the Republic of Ireland, the male to female mortality ratio is 2 to 1, while Italy and Switzerland have a 1.9 to 1 ratio each.

The greatest parity between the genders from countries that have submitted a full set of data are Iran, with 1.1 to 1, and Norway, with 1.2 to 1.

In Iran, 5.4% of the women patients have died, compared with 5.9% of the men. In Norway, these numbers stand at 1.3% and 1.1%, respectively.

China has a ratio of 1.7, with 2.8% of women having died, compared with 4.7% of men.
Infection rates in womenand men

A side-by-side comparison of infection rates between the sexes does not explain the higher death rates in men, nor is there enough data available to draw a conclusion about infection rates broken down by sexes.

However, it is worth noting that in Denmark, where men are more than twice as likely to die of COVID-19 as women, the proportion of women who contracted the virus was 54%, while that of men was 46%.

By contrast, in Iran, where the ratio of deaths between men and women is less different (1.1 to 1), just 43% of cases are female compared with 57% cases in men.

Until we know the proportion of people from each sex that healthcare professionals are testing, it will be difficult to fully interpret these figures.

What we do know so far is that, overall, nine of the 18 countries that have provided complete sex-disaggregated data have more COVID-19 cases among women than they do among men. Six of the 18 countries have more cases among men than they do among women.

Norway, Sweden, and Germany have a 5050% case ratio.

Other countries where more women have developed COVID-19 include:
Switzerland (53% of women to 47% of men)Spain (51% to 49%)The Netherlands (53% to 47%)Belgium (55% to 45%)South Korea (60% to 40%)Portugal (57% to 43%)Canada (52% to 48%)Republic of Ireland (52% to 45%)

Greece, Italy, Peru, China, and Australia all have a higher number of confirmed cases among men than women.Why are men more likely to die?

Part of the explanation for why the new coronavirus seems to cause more severe illness in men is down to biological sex differences.

Womens innate immune response plays a role. Experts agree that there are sex differences, such as sex chromosomes and sex hormones, that influence how a persons immunity responds to a pathogen.

As a result, women are in general able to mount a more vigorous immune response to infections [and] vaccinations. With previous coronaviruses, specifically, some studies in mice have suggested that the hormone estrogen may have a protective role.

For instance, in the study above, the authors note that in male mice there was an exuberant but ineffective cytokine response. Cytokines are responsible for tissue damage within the lungs and leakage from pulmonary blood vessels.

Estrogens suppress the escalation phase of the immune response that leads to increased cytokine release. The authors showed that female mice treated with an estrogen receptor antagonist died at close to the same rate as the male mice.

As some researchers have noted, lifestyle factors, such as smoking and alcohol consumption, which tend to occur more among men, may also explain the overall higher mortality rates among men.

Science has long linked such behaviors with conditions that we now know are likely to negatively influence the outcome of patients with COVID-19 cardiovascular disease, hypertension, and chronic lung conditions. Why women might be more at risk

On the other hand, the fact that societies have traditionally placed women in the role of caregivers a role which they continue to fulfill predominantly and the fact that the vast majority of healthcare workers are women cold place them at a higher risk of contracting the virus and might explain the higher infection rates in some countries.

An analysis of 104 countries by the World Health Organization (WHO) found that Women represent around 70% of the health workforce. In China, women make up more than 90% of healthcare workers in Hubei province.

These data emphasize the gendered nature of the health workforce and the risk that predominantly female health workers incur, write the authors of a report on the gendered impacts of the pandemic that appears in The Lancet.

Although we cannot yet draw definitive conclusions because sex-disaggregated data is not yet available from all the countries affected, The Lancet report looks at previous epidemics for clues.

During the 201416 west African outbreak of Ebola virus disease, the authors write, gendered norms meant that women were more likely to be infected by the virus, given their predominant roles as caregivers within families and as frontline healthcare workers.

The authors also call out for governments and health institutions to offer and analyze data on sex and gender differences in the pandemic.
Why sex-disaggregated data are urgent

The report in The Lancet reads, Recognising the extent to which disease outbreaks affect women and men differently is a fundamental step to understanding the primary and secondary effects of a health emergency on different individuals and communities, and for creating effective, equitable policies and interventions.

For instance, identifying the key difference that makes women more resilient to the infection could help create drugs that also strengthen mens immune response to the virus.

Devising policies and intervention strategies that consider the needs of women who work as frontline healthcare workers could help prevent the higher infection rates that we see among women.

Finally, men and women tend to react differently to potential vaccines and treatments, so having access to sex-disaggregated data is crucial for conducting safe clinical trials.

As Anna Purdie who also works for Global Health 5050 and her colleagues summarize in their article, Sex-disaggregated data are essential for understanding the distributions of risk, infection, and disease in the population, and the extent to which sex and gender affect clinical outcomes.
Understanding sex and gender in relation to global health should not be seen as an optional add-on but as a core component of ensuring effective and equitable national and global health systems that work for everyone. National governments and global health organizations must urgently face up to this reality.

Anna Purdie et al

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Indiana topples No. 3 Oregon to stay unbeaten

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Indiana topples No. 3 Oregon to stay unbeaten

EUGENE, Ore. — Fernando Mendoza threw for 215 yards and a key fourth-quarter touchdown and No. 7 Indiana remained undefeated with a 30-20 victory over No. 3 Oregon on Saturday.

Roman Hemby added a pair of scoring runs for the Hoosiers (6-0, 3-0 Big Ten), who frustrated the Ducks (5-1, 2-1) with stout defensive play.

The victory was Indiana’s second against an AP top-five opponent in program history. The Hoosiers entered Saturday having lost 46 consecutive games vs. AP top-five opponents, tied with Wake Forest for the longest streak in the AP poll era, according to ESPN Research.

Dante Moore threw for 186 yards and a touchdown for Oregon. He had two interceptions and was sacked six times.

With Oregon down 20-13 going into the fourth quarter, Brandon Finney Jr. intercepted Mendoza’s pass and ran it back 35 yards to tie the game with 12:42 left.

Mendoza answered with an 8-yard scoring pass to Elijah Sarratt with 6:23 to go. On Oregon’s next series, Dante Moore’s pass was intercepted by Louis Moore.

Brendan Franke added a 22-yard field goal for the Hoosiers with 2:06 left.

Both teams were coming off weeks off. In their last game, the Ducks beat Penn State 30-24 in double overtime on the road in the annual White Out game. The Hoosiers beat Iowa 20-15 on the road.

On the first series of the game, the Ducks failed at a fourth-and-1 attempt, giving the Hoosiers good field position for their opening drive. It ended with Nico Radicic‘s 42-yard field goal.

Oregon pulled ahead with Dante Moore’s 44-yard touchdown pass to Malik Benson, but Hemby rushed for a 3-yard touchdown before the end of the first quarter to make it 10-7.

Atticus Sappington‘s 40-yard field goal tied it up for the Ducks, but a later 36-yard attempt that would have given Oregon the lead went wide left.

Franke kicked a 58-yard field goal as time ran out to give Indiana a 13-10 advantage at the break.

Sappington’s 33-yard field goal in the third quarter tied it again for Oregon, but Hemby added his second touchdown for the Hoosiers, a 2-yard dash late in the period.

The Associated Press contributed to this story.

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Allar injured, out for year as PSU loses again

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Allar injured, out for year as PSU loses again

STATE COLLEGE, Pa. — Penn State quarterback Drew Allar, who left the Nittany Lions’ stunning 22-21 loss to Northwestern on Saturday, is out for the season, coach James Franklin said in his postgame media availability.

Allar hobbled off the field after a third-down play in the fourth quarter, and was eventually carted off to the locker room. He was replaced by Ethan Grunkemeyer.

“Drew will be done for the year,” Franklin said.

Penn State (3-3) has now lost three straight games, with two of those coming in Happy Valley. The reeling Nittany Lions will take on Iowa next Saturday.

It’s a different story for the Wildcats. They surged to 4-2 as Caleb Komolafe ran for 72 yards and a touchdown to stun the Beaver Stadium crowd. Preston Stone threw for 163 yards with a touchdown pass to Griffin Wilde, and Jack Olsen kicked three field goals for the Wildcats, who won their third straight and moved to 2-1 in the Big Ten.

The Wildcats, who hadn’t won in Beaver Stadium since 2014, took the lead for good with 4:51 remaining when Komolafe bulled his way through Penn State’s defense to cap a 75-yard drive.

The Nittany Lions, who fell to 0-3 in the league, got the ball back, but that’s when Allar suffered his injury. Grunkemeyer was immediately stopped on a fourth-down run, and the Wildcats ran the clock out from there.

“It’s 100 percent on me,” Franklin said of the loss. “And we got to get it fixed. And I will get it fixed.”

Allar, Nicholas Singleton and Kaytron Allen ran for touchdowns for the Nittany Lions. It was the fifth time a Franklin-coached Penn State team has lost at least three consecutive games in a season.

The Nittany Lions, who committed six penalties for 71 yards in the first half, could never get out of their way. Meanwhile, the Wildcats played steady, almost mistake-free football in front of a flat Penn State crowd that chanted “Fire James Franklin!” early.

Allar was intercepted on Penn State’s opening drive when he threw the ball right to defensive back Ore Adeyi in the end zone. Adeyi returned it to the Northwestern 33, and the Wildcats turned it into three points 12 plays later with Jack Olsen’s 27-yard field goal with 2:51 left in the first quarter.

The Nittany Lions finally got their offense moving with Allen. He carried five times on Penn State’s next possession and gave his team a 7-3 lead when he muscled in from 11 yards out early in the second.

Northwestern marched into Penn State’s territory on its next possession, and Stone found a wide-open Wilde for a go-ahead 28-yard touchdown pass.

The Wildcats appeared to get a stop on defense but fumbled away the ensuing punt. The Nittany Lions needed nine plays from Northwestern’s 26 but finally broke through on a fourth-and-goal when Singleton slashed around the Wildcats’ left flank for a 2-yard touchdown.

Olsen made a 34-yarder with three seconds left to cut Penn State’s lead to 14-13 at halftime.

The Associated Press contributed to this report.

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Manning powers Texas to upset win over No. 6 OU

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Manning powers Texas to upset win over No. 6 OU

DALLAS — Ryan Niblett returned a punt 75 yards for a decisive touchdown in the fourth quarter and Texas got a much-needed 23-6 win over sixth-ranked Oklahoma in their annual Red River Rivalry game on Saturday.

Arch Manning completed 21 of 27 passes for 166 yards and the go-ahead 12-yard TD to DeAndre Moore Jr. on the opening drive of the second half for the Longhorns (4-2, 1-1 Southeastern Conference), who were coming off a loss at Florida that knocked the preseason No. 1 team out of the AP Top 25.

Texas retained the Golden Hat trophy and should get back into the next poll on Sunday. More importantly, the Longhorns avoided a loss that likely would have ended any realistic chance of getting into the College Football Playoff for the third year in a row.

John Mateer was 20-of-38 passing with three interceptions in his return to the lineup for Oklahoma (5-1, 1-1) only 17 days after surgery on his throwing (right) hand.

Niblett worked up the sideline in front of the Texas bench, and after making a cut inside near midfield bounced off a teammate and continued his sprint to the end zone for a 20-6 lead with 9:59 left.

When the Sooners gained 38 yards on three plays to the Texas 27 on the ensuing drive, Mateer had an incompletion before being sacked on consecutive plays and then had another incompletion on fourth-and-22. They finished with only 258 total yards.

Mason Shipley kicked field goals of 22, 48 and 39 yards for the Longhorns. He had two long misses, the first a 55-yard attempt that ricocheted off the right upright, and was later short on a 56-yard attempt.

Tate Sandell kicked a 42-yard field goal on the game’s opening drive for the Sooners. He made it 6-0 with a 41-yarder in the second quarter, but they didn’t score again.

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