Shame in the Time of Covid-19

Almost immediately, I noticed some disturbing patterns on social media when the U.S. began directly responding to the Covid-19 pandemic several weeks ago.

The “Covid-19 is a hoax” and “Covid-19 is no worse than the flu” posts on Facebook immediately appeared (and have mostly disappeared), but what is more concerning is that very garbled and oversimplified posts also appeared and continue to flourish.

Ground Zero of garbled and oversimplified social media posts, I think, was arguments over the danger of Covid-19 that focused on death rates (percentage of deaths among those testing positive for the virus). Focusing on this one stat (a complicated data point because it is skewed by if and when people are tested, a serious failure of this pandemic event) greatly misrepresented the why of the unique danger Covid-19 presents.

Most people missed the “novel” terminology (many corona viruses exist, but a “novel,” thus new, version distinguishes Covid-19) and subsequently rushed past the very complex set of reasons this pandemic is not like the flu or other reasons people die daily in the U.S. and throughout the world.

The real threats posed by Covid-19 include the unknown (death rates, who is at-risk, etc.), but also some very significant knowns—likelihood that medical facilities will be overwhelmed, creating greater death rates for Covid-19, the flu, and other situations that normally could be addressed; the complicated and difficult to manage spread of the virus (by asymptomatic people); strategies that work such as “flattening the curve.”

As the U.S. moves into a second month of social distancing, there is more known each day about the virus, and subsequently, there are also more data on how we are managing the virus as well.

Changing information has always been a feature of science and of being evidence-driven. Changing information has always deterred many people from listening to science and evidence-driven policy.

This is a deadly paradox for dealing with a pandemic.

It seems reasonable to acknowledge that science/evidence-denial is incredibly dangerous and inexcusable in a well-informed and so-called advanced society (recognizing that the idealism about the U.S. is not well supported by evidence on lingering inequities).

But a potentially as harmful dynamic is science/evidence evangelism, which is quickly becoming forms of shaming. Two of the most recent forms of shaming concern social distancing and wearing face masks.

As with Covid-19 broadly, the science/evidence on social distancing and face masks is complicated, but slightly different.

Data drawn from cell phones has created a state-by-state and city-by-city ranking of who is practicing social distancing and who isn’t. However, that data exist doesn’t mean that any data set proves what people immediately assume.

Raw movement data by cell phone use doesn’t control for rural versus urban settings, doesn’t control for socioeconomic status of the users (who can and cannot “choose” not to work), and doesn’t control for essential versus nonessential movement.

A common problem in science/evidence is that data can be less valid and credible depending on how that data are interpreted and displayed; also, when messages are made public is incredibly important.

Cell data were immediately used to rank and shame states and cities (thus, this message will likely endure), but once the data and messages gained traction, a more nuanced and less shaming message has emerged:

In cities across America, many lower-income workers continue to move around, while those who make more money are staying home and limiting their exposure to the coronavirus, according to smartphone location data analyzed by The New York Times.

Although people in all income groups are moving less than they did before the crisis, wealthier people are staying home the most, especially during the workweek. Not only that, but in nearly every state, they began doing so days before the poor, giving them a head start on social distancing as the virus spread, according to aggregated data from the location analysis company Cuebiq, which tracks about 15 million cellphone users nationwide daily.

Jennifer Valentino-DeVriesDenise Lu and 

The data offers [sic] real-time evidence of a divide laid bare by the coronavirus pandemic — one in which wealthier people not only have more job security and benefits but also may be better able to avoid becoming sick. The outbreak is so new that the relationship between socioeconomic status and infection rates cannot be determined, but other data, including recent statistics released by public health officials in New York City, suggests [sic] that the coronavirus is hitting low-income neighborhoods the hardest.

The data are less about compliance and more about socioeconomic inequity and the false (idealized) myth of “choice” in the U.S. That choice is less about inherent character in people and more about privilege and anyone’s birth lottery.

Soon, we will have to confront that race/racism also pervades nearly every aspect of this pandemic, as Michael Harriot outlines on Twitter.

Social distance shaming is rooted in misunderstanding and oversimplifying data as well as careless data displays, such as charts and graphs.

More recently, since WHO and the CDC have begun to re-address guidelines on wearing masks, there is more mask shaming, which demonstrates once again that science and evidence are often complicated, but the media and lay people are apt to rush to oversimplifications, especially those who are science/evidence evangelists.

Similar to the initial message about the dangers of Covid-19 examined in the opening, what I understood about wearing face masks as the pandemic spread in the U.S. was not what most people said then or now; whether or not healthy or asymptomatic people (no evidence of exposure) should wear surgical masks or N95 masks was based on supply (low) and ranking who needed those most (medical workers), not about the effectiveness of wearing the masks.

People who interpreted the initial message as “masks do not protect healthy people” (an oversimplification grounded in truth) eventually recognized the contradiction as that sat against “healthcare workers need masks.”

The shift is now occurring whereby officials appear to be suggesting that everyone wear surgical masks, even prompting guides for making them at home. But the original science/evidence is not being honored in this either, especially as people begin to mask shame in the same ways that they are social distance shaming.

Seeking out the evidence on wearing masks is walking into a topic that may be even more complicated than a pandemic itself, but there is one really sobering fact that gets glossed over time and again:

Surgical Masks

Surgical masks (see Image 1) are loose, single use cloth masks designed to provide protection against large droplets, splashes or sprays of bodily or other hazardous fluids. These types of masks experience leakage around the edges when the user inhales, and do not provide a reliable level of respiratory protection against smaller airborne particles. The primary recommended medical function of these types of disposable masks is for infected individuals who want to decrease the risk of transmitting the disease to others in their vicinity, and they are not a substitute for a respirator mask and their primary function is not to protect the wearer of the mask [emphasis added].

Surgical Mask

Since the U.S. has made no effort to address the supply/need element in access to masks, and since the evidence on wearing basic masks is complicated (above), the move to mask shaming may have very negative consequences such as a false sense of security (prompting more socializing and working against social distancing) and stimulating unhealthy behavior (more face touching, reusing unsanitary masks).

Science and evidence are powerful and essential parts of creating public policy and especially of mandated and voluntary human behavior during a health crisis.

Yet, once again, we have ample evidence that neither the fatalism of denial nor the evangelism of shaming is the proper way to navigate science and evidence because science/evidence is more often than not very complicated and always in a state of evolution.

See Also

No need for healthy to wear face masks, says WHO after review

Heymann said masks could create a false sense of security that could end up putting people at greater risk. Even with the mouth and nose fully covered, the virus can still enter through the eyes.

“People think they are protected when they are not,” he said. “Healthcare workers, in addition to the masks, wear visors too, to protect the eyes.”

Another concern is that people may contaminate themselves when they adjust, remove and dispose of their masks.

COMMENTARY: Masks-for-all for COVID-19 not based on sound data