Deutsche Welle (English edition)
COVID vaccine trials: Where are the women?
Worldwide, women are reporting worse side effects after COVID vaccinations than men. But the data is hard to find — most studies ignore gender and sex.
Serious side effects for the COVID vaccines remain extremely rare.
Most people have mild reactions that disappear after a few days, such as low-grade fevers or muscle aches. Health experts say these are a sign of our bodies mounting an immune response and that that signals we will likely be protected by the vaccine against future infections.
In the United States, health authorities say fewer than 0.001% of vaccinated people have had an extreme reaction, like an allergic response to a COVID vaccine.
But people do get side effects. And increasingly, data suggests that women are much more likely to experience side effects than men — and that reflects a trend throughout the history of vaccination.
Female immunity can be remarkably different
In June, the Swiss government released data showing 68.7% of reported side effects to COVID vaccines came from women. In the US, that percentage was 79.1% for the first 13.7 million doses given to people — 61.2% of which had been administered to women. And in Norway it was 83% of the 722,000 people vaccinated as of early April.
That's just a handful of samples. Data on women's side effects is scarce.
But Maria Teresa Ferretti, a neuroimmunologist at the Medical University of Vienna, says the data we have is unsurprising. Ferretti, who also founded a nonprofit called Women's Brain Project, says we already knew that men and women react differently to vaccination.
"From vaccines for other viruses, we knew that women tend to produce more antibodies when they are vaccinated, which means they also tend to have more side effects," she told DW.
One study, spanning 26 years from 1990 and 2016, found that women accounted for 80% of adult anaphylactic reactions to vaccines.
Women were also found to be four times as likely to report an allergic reaction to an H1N1 vaccine used during the 2009 swine flu pandemic.
Other research has suggested that sex hormones can influence the human immune system. A more robust immune response is also why more women tend to develop autoimmune diseases than men — the body goes into
overdrive, attacking things that are meant to be there.
Biological sex and gender 'intersect'
This difference is part of a bigger picture of how biological sex and gender both influence our health, says Rosemary Morgan, a gender and health researcher at the Johns Hopkins Bloomberg School of Public Health in the US.
While women are more likely to suffer worse side effects from
vaccines, men are more likely to be hospitalized for serious cases of COVID, and more men die of COVID.
Biological factors affect our immune systems — whether we are born biologically male, female or intersex.
Male immune systems, for example, have their own specific issues that apply less to female bodies. For instance, testosterone can be immunosuppressive.
But gender — considered a social construct; an idea in our heads — can also affects people's behavior and access to healthcare.
Men, for example, are often socialized to repress pain and, as a result, may be less likely to report adverse reactions.
"Studies show that men are less likely to wear masks and wash their hands. If you couple that with their biological risk, it's this complex intersection that plays into men's greater vulnerability to COVID-19," Morgan told DW.
Data on intersex, non-binary and transgender susceptibility to COVID is limited, but some research suggests that discrimination against gender and sexual minorities could mean they are disproportionately affected by COVID. And that's possible around the world. The research suggests certain groups of people are being excluded from vital healthcare.
Women, intersex, nonbinary, trans people excluded from research
Ferretti says researchers should consider the effects of exclusion and discrimination when they develop vaccines and drugs and trials to test them — whether it's for COVID or any other disease.
"You would think they would consider these [factors]. But it doesn't seem like they have," she says.
A study published in Nature Communications in July found that only 4% of a set of nearly 4500 clinical studies into treatments for COVID-19 had reported a plan to consider the role of sex and/or gender.
The studies ranged from clinical trials for vaccines and drugs to observational studies looking at the effects of lockdown on mental health and access to healthcare.
Only one study was found to specifically look at the impact of COVID on transgender people. Some studies only involved women, and they were mainly about COVID and pregnancy.
Out of 45 randomized and controlled trials, published up to December 2020, only eight referred to sex and/or gender.
Sabine Oertelt-Prigione, a gender and health researcher at Radboud University Medical Center in the Netherlands, says scientists can feel a lot of pressure to publish results quickly.
"Researchers are sometimes worried that analyzing sex differences in a study might mean more participants and longer recruitment times to reach their targets," said Oertelt-Prigione.
This sex and gender breakdown is also often overlooked in simple counts of infection cases and vaccinations.
The Sex, Gender & COVID-19 project, a global tracker of sexspecific research by a nonprofit called Global Health 50/50, shows only 37% of countries reported death data that specified the sex of the individual and 18% vaccination data that differentiated between sex in the month of June 2021.
Male body used as 'default human being'
"There has been a historical lack of sex and gender analysis within medical and clinical research," says Morgan. She says that it wasn't until 1993 in the United States that women were mandated to be included in clinical trials.
It's said that researchers were worried that women's hormones would skew the results. So, they used the male body as a "default human being" in medical research.
Apart from anything else, Morgan says, this has meant that a lot of medication is dosed with only men in mind. And that means doctors can't reliably prescribe the correct dose of drugs for female patients or those of other, non-male sexes.
It also means we can't say for sure whether any women are hesitant about getting a COVID vaccine because of the potential side effects. We just don't know for certain.
"We have a one-size-fits-all approach to dosing but that doesn't necessarily suit women," said Morgan.
Ferretti says it's "shallow medicine" — a phrase coined by American cardiologist Eric Topol. And Ferretti says it needs to change, that we need to go deeper: "We're assuming that all patients are more or less the same. But they aren't."
And we humans often feel like we can't control or even know what ML algorithms learn. But actually, we can ― because we write the original code. So you can afford to relax. A bit.
In summary, AIs and MLs are programs that let us process lots and lots of information, a lot of it "raw" data, very fast. They are not all evil monsters out to kill us or steal our jobs — not necessarily, anyway.
How AI is helping in the fight against COVID
With COVID-19, AI and ML may have helped save a few lives. They have been used in diagnostic tools that read vast numbers of chest X-rays faster than any radiologist. That's helped doctors identify and monitor COVID patients.
In Nigeria, the technology has been used at a very basic but practical level to help people assess their of risk of getting infected. People answer a series of questions online and depending on their answers, are offered remote medical advice or redirected to a hospital.
The makers, a company called Wellvis, say it has reduced the number of people calling disease control hotlines unnecessarily.
South Korea: Testing for COVID
One of the most important things we've had to handle is finding out who is infected — fast. And in South Korea, artificial intelligence gave doctors a head start.
Way back when the rest of the
world was still wondering whether it was time to go into the first lockdown, a company in Seoul used AI to develop a COVID-19 test — in mere weeks. It would have taken them months without AI.
It was "unheard of," said Youngsahng "Jerry" Suh, head of data science and AI development at the company, Seegene, in an interview with DW.
Seegene's scientists ordered raw materials for the kits on January 24 and by February 5, the first version of the test was ready.
It was only the third time the company had used its supercomputer and Big Data analysis to design a test.
But they must have done something right because by mid-March 2020, international reports suggested that South
Korea had tested 230,000 people.
And, at least for a while, the country was able to keep the number of new infections per day relatively flat.
"And we're constantly updating that as new variants and mutations come to light. So, that allows our machine learning algorithm to detect those new variants as well," says Suh.
South Africa: Detecting a third wave
One of the other major issues we've had to handle is tracking how the disease — especially new variants and their mutations — spread through a community and from country to country.
In South Africa, researchers used an AI-based algorithm to predict future daily confirmed cases of COVID-19.
It was based on historical data from South Africa's past
infection history and other information, such as the way people move from one community to another.
In May, they say they showed the country had a low risk of a third wave of the pandemic.
"People thought the beta variant was going to spread around the continent and overwhelm our health systems, but with AI we were able to control that," says Jude Kong, who leads the Africa-Canada Artificial Intelligence and Data Innovation Consortium.
The project is a collaboration between Wits University and the Provincial Government of Gauteng in South Africa and York University in Canada, where Kong, who comes from Cameroon, is an assistant professor.
Kong says "data is very sparse in Africa" and one of the problems is getting over the stigma attached to any kind of illness, whether it's COVID, HIV, Ebola or malaria.
But AI has helped them "reveal hidden realities" specific to each area, and that's informed local health policies, he says.
They have deployed their AI modelling in Botswana, Cameroon, Eswatini, Mozambique, Namibia, Nigeria, Rwanda, South Africa, and Zimbabwe.
"A lot of information is onedimensional," Kong says. "You know the number of people entering a hospital and those that get out. But hidden below that is their age, comorbidities, and the community where they live. We reveal that with AI to determine how vulnerable they are and inform policy makers."
A "hyped" potential?
Other types of AI, similar to facial recognition algorithms, can be used to detect infected people, or those with elevated temperatures, in crowds. And AIdriven robots can clean hospitals and other public spaces.
But, beyond that, there are experts who say AI's potential has been overstated.
They include Neil Lawrence, a professor of machine learning at the University of Cambridge who was quoted in April 2020, calling out AI as "hyped."
It was not surprising, he said, that in a pandemic, researchers fell back on tried and tested techniques, like simple mathematical modelling. But one day, he said, AI might be useful.
That was only 15 months ago. And look how far we've come.