Good news for "Research Parasites": NEJM takes it back, 8 years later

After years of debate, the National Institutes of Health finally rolled out a data sharing policy early this year, one that should greatly increase the amount of data that biomedical researchers share with the public. This week, three prominent scientists from Yale described, in an op-ed in the New England Journal of Medicine, how “the potential effects of this shift ... toward data sharing are profound.”

For some of us, it’s deliciously ironic that this op-ed appeared in NEJM, which just a few years ago coined the term “research parasites” to describe anyone who wants to make discoveries from someone else’s data. That earlier piece, written in 2016 by the NEJM’s chief editors, was simply dripping with disdain. It caused a huge outcry, including a response from me in these pages and a sharply worded response from the Retraction Watch team, published in Statnews. The editor backed down (slightly) in a follow-up letter just a few days later, but the damage was done.

One interesting consequence was that a group of scientists created a Research Parasite Award, now awarded each year (entirely seriously, despite the tongue-in-cheek name) at a major biomedical conference, for “rigorous secondary data analysis.”

The 2016 op-ed in NEJM was itself a response to a call for greater data sharing published in the New York Times by cardiologists Eric Topol and Harlan Krumholz–and Krumholz, we should note, is a co-author of the latest piece in NEJM. Meanwhile, the former editor of NEJM retired years ago, and it appears that the journal is now ready to join the 21st century, even if it’s a few decades late.

What is all this fuss about? Well, many people outside of the scientific research community probably don’t realize that vast amounts of data generated by publicly-funded research–work that is paid for by government grants–are not usually released to the public or to any other scientists.

On the contrary: in much of biomedical research, data sets collected with government funding are zealously kept private, often forever. The usual reasons for this are simple (although rarely admitted openly): the scientists who collected the data want to keep mining it for more discoveries, so why share it? Sometimes, too, researchers package up the data and sell it, which is completely legal, even though the government paid for the work.

(It’s not just medical research data, either: once I tried to get some data from a paleontologist, only to learn that he treated every fossil he ever collected as his personal property. But that’s a blog for another day.)

Many scientists have been fighting this culture of secrecy for a long time. Our argument is that all data should be set free, at least if it’s the subject of a scientific publication. It’s not just scientists making this argument: since the early 2000s, patient groups began to realize they couldn’t even read the studies about their own diseases unless they paid a for-profit journal to access the paper. Those groups lobbied–successfully, after a years-long fight–that any publicly-funded research had to be published on a free website, not locked behind the doors of private publishers. Their effort led to an NIH database called PubMedCentral, which contains the full text of thousands of articles.

The new NIH data sharing policy is one consequence of the Open Science movement (which I’m a part of), which argues that science moves much faster when it’s done in the open. This means sharing data, software, methods, and everything else. There’s now a U.S. government website dedicated to Open Science, open.science.gov, which includes more than a dozen federal agencies including NIH, NSF, and the CDC.

A bit more history: as far as I can tell, the earliest voices for data sharing emerged during the Human Genome Project, an international effort beginning in 1989 that produced the first draft of the human genome in 2001. When a private company (Celera Genomics) emerged in 1998, a dramatic race ensued, and as one strategy for competing, the public groups announced that, in contrast to the private group, they would release all their data openly on a weekly basis, long before publication. That wasn’t how things had worked before.

Very soon after that, scientists in genomics (my own field) realized that all genome data, whether from bacteria, viruses, animals, or plants, ought to be released freely. The publicly-funded sequencing centers received millions of dollars to generate the data, but they weren’t the only places who could analyze it. NIH and NSF agreed, and pretty soon they required all sequencing data to be released promptly.

This same spirit didn’t touch most medical research, though. Even though far more money–billions of dollars a year in NIH funds–is spent on disease-focused research, data from those studies remained locked up in the labs that got the funds. This is now changing.

As the Yale scientists (Joseph Ross, Joanne Waldstreicher, and Harlan Krumholz) point out in their NEJM editorial, open data sharing has already yielded tremendous benefits. For example, they point out that hundreds of papers have been published using public data from the NIH’s National Heart, Lung, and Blood Institute, including studies that revealed new findings about the efficacy of digoxin, a common drug used to treat heart failure.

The new NIH policy covers all of NIH, not just one institute, and we can hope it will unlock new discoveries by allowing many more scientists to look at the valuable data currently kept behind closed firewalls.

But simply requiring scientists to have a “data management and sharing policy,” as the NIH is now doing, might not be enough. Many thousands of scientific papers already say they share data and materials–but as it turns out, the authors don’t always want to share.

A study published last year illustrated how toothless some current policies are. That study identified nearly 1800 recent papers in which the authors said they would share their data “upon request.” They wrote to all of them, only to find that 93% of the authors either didn’t respond at all, or else declined to share their data. That’s right: only 7% of authors shared their data, despite publishing a statement that they would.

The NEJM editorial proposes a different solution, one that could be far more effective: putting scientific data into a government repository. This is something the government itself can enforce (because they control the funding), and once the data is in a public repository, the authors won’t be able to sit on it as (some of them) now do.

It’s good to see NEJM joining the open science movement. Science that is shared openly will inevitably move faster, and everyone–except, perhaps a few data hoarders–will benefit.

Masks do work, but mask policies are another thing entirely.

The use of masks to prevent the spread of Covid-19 has been controversial almost since the beginning of the pandemic, two years ago.

The U.S. Surgeon General made a huge early blunder, in February of 2020, when he recommended against masks, tweeting that

“masks are NOT effective in preventing general public from catching #Coronavirus, but if healthcare providers can’t get them to care for sick patients, it puts them and our communities at risk!”

That self-contradictory tweet was later deleted, but it caused a tremendous amount of confusion. After all, if masks don’t work, then why is it so important that healthcare workers have them?

Masks do work. The evidence is overwhelming that masks, if properly worn, “substantially reduce exhaled respiratory droplets and aerosols from infected wearers and reduce exposure of uninfected wearers to these particles,” as described in a CDC publication last year.

The idea that masks should help prevent infections is intuitively obvious: Covid-19 spreads through the transmission of viral particles from an infected person. These particles travel through the air, as numerous studies have shown, just like many other infectious diseases. If you can stop the spread of the viral particles themselves, then (obviously) you stop the virus from infecting people.

However, evidence emerged early on in the pandemic that cloth masks and standard surgical masks were not very effective, because they allowed viral particles to leak out (and in). The SARS-CoV-2 virus is really tiny, and it can slip through the gaps in these masks.

In other words, some masks work better than others.

In June of 2020, a large study published in The Lancet reported that N95 masks were far superior at preventing transmission of Covid-19. That study found that “face mask use could result in a large reduction in risk of infection, with stronger associations with N95 or similar respirators compared with disposable surgical masks.” They reported an overall risk reduction of 85%, with N95 masks conferring a 96% reduction but surgical masks just 67%.

It’s easy to find studies showing how to make masks even more effective: make sure they fit very snugly, tightening them around the head or ears if necessary. Medical professionals who follow these guidelines have had very few infections, despite being exposed daily to sick patients. (Johns Hopkins Hospital, part of my own university, has reported almost no infections among its medical staff caused by exposure to patients.)

This all makes perfect sense. After all, if masks didn’t work, then doctors and nurses would have to be unbelievably self-sacrificing (even more than they are already) to treat Covid-19 patients. Fortunately, though, a properly worn N95 mask does an excellent job at protecting the wearer against infection.

One problem that often goes unmentioned, though, is that the better the mask, the harder it is to breathe. This too is pretty obvious: if you make it harder for tiny particles to get in or out, then of course it’s harder to breathe. Snug-fitting N95 masks are, simply put, uncomfortable.

Mask policies are the real problem. Even though masks work, getting millions of people to wear them, and wear them consistently and properly, is a far greater challenge. A casual stroll through any indoor space where masks are required–and we’ve all done this–will reveal many people whose masks don’t cover their noses, or whose masks are clearly very loose, or who might not be wearing masks at all, despite the rules.

Why don’t people wear their masks? This too shouldn’t be a mystery. Many people, young and old, simply don’t like being told what to do, so when a local government says they have to wear masks, they resent it. And governments (or large companies) have a habit of creating one-size-fits-all policies that are don’t make sense for some people. The simplest mask mandates (simplest to explain and enforce, that is) say that everyone should wear a mask all the time, or that everyone should wear a mask indoors.

For example, in Baltimore everyone has to wear a mask indoors, but restaurants are open. Thus diners must wear a mask from the entrance to their table, and then they can eat their dinner, mask-free, for as long as they wish. This doesn’t make much sense.

And what about people who are vaccinated and free from any Covid-19 symptoms? Nope, no exceptions, according to every mask mandate I’ve heard of. Naturally, that is frustrating to some people. No one should find this surprising.

In reaction to mask requirements, many people, particularly on the political right, have proclaimed that “masks don’t work.” While some of them might believe this–in which case they are just wrong–what they might really be talking about is masking policies, and in that sense they are right. If you can’t get nearly everyone to wear an N95 mask, then you can’t realistically control the spread of the virus.

We’ve seen how this works in the U.S.: despite widely varying mask policies, the Omicron variant has swept through every single state in the country, including those with strict mandates. Some places, like New York City, were hit earlier despite having fairly strict mask policies. States with no masking requirements and those that banned mask mandates (such as Florida, Georgia, South Carolina, and Tennessee), were hit later and just as hard.

One reason that masking policies don’t work–although masks themselves do work–is that it’s just really inconvenient to wear a mask all the time.

So people continue to wear masks badly, or to refuse to wear them at all. Does this mean we should give up? No, not exactly. But we might have to limit strict masking rules to places where truly vulnerable people are present, such as hospitals and senior care homes. Large-scale mask mandates are just not working, and there’s probably little we can do to change that in a free society.

A far, far more effective way to control the virus is through vaccination. As Eric Topol pointed out recently with an elegant graphic: “How to reduce your chance of dying from Covid by 99%? Get vaccinated and a booster.”