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MYC translocations, a hallmark of Burkitt lymphoma, occur in 5-15% of diffuse large B-cell lymphoma, and have a negative prognostic impact. Numerical aberrations of MYC have also been detected in these patients, but their incidence and prognostic role are still controversial. We analyzed the clinical impact of MYC increased copy number on 385 patients with diffuse large B-cell lymphoma screened at diagnosis for MYC, BCL2, and BCL6 rearrangements. We enumerated the number of MYC copies, defining as amplified those cases with an uncountable number of extra-copies. The prevalence of MYC translocation, increased copy number and amplification was 8.8%, 15%, and 1%, respectively. Patients with 3 or 4 gene copies, accounting for more than 60% of patients with MYC copy number changes, had a more favorable outcome compared to patients with >4 copies or translocation of MYC, and were not influenced by the type of treatment received as first-line. Stratification according to the number of MYC extra-copies showed a negative correlation between an increasing number of copies and survival. Patients with >7 copies or the amplification of MYC had the poorest prognosis. Patients with >4 copies of MYC showed a similar, trending towards worse prognosis compared to patients with MYC translocation. The survival of patients with >4 copies, translocation or amplification of MYC seemed to be superior if intensive treatments were used. Our study underlines the importance of fluorescence in situ hybridization testing at diagnosis of diffuse large B-cell lymphoma to detect the rather frequent and clinically significant numerical aberrations of MYC.

B-cell receptor (BCR) signaling pathway components represent promising treatment targets in multiple B-cell malignancies including diffuse large B-cell lymphoma (DLBCL). In in vitro and in vivo model systems, a subset of DLBCLs depend upon BCR survival signals and respond to proximal BCR/phosphoinositide 3 kinase (PI3K) blockade. However, single-agent BCR pathway inhibitors have had more limited activity in patients with DLBCL, underscoring the need for indicators of sensitivity to BCR blockade and insights into potential resistance mechanisms. Here, we report highly significant transcriptional upregulation of C-X-C chemokine receptor 4 (CXCR4) in BCR-dependent DLBCL cell lines and primary tumors following chemical spleen tyrosine kinase (SYK) inhibition, molecular SYK depletion or chemical PI3K blockade. SYK or PI3K inhibition also selectively upregulated cell surface CXCR4 protein expression in BCR-dependent DLBCLs. CXCR4 expression was directly modulated by fork-head box O1 via the PI3K/protein kinase B/forkhead box O1 signaling axis. Following chemical SYK inhibition, all BCR-dependent DLBCLs exhibited significantly increased stromal cell-derived factor-1α (SDF-1α) induced chemotaxis, consistent with the role of CXCR4 signaling in B-cell migration. Select PI3K isoform inhibitors also augmented SDF-1α induced chemotaxis. These data define CXCR4 upregulation as an indicator of sensitivity to BCR/PI3K blockade and identify CXCR4 signaling as a potential resistance mechanism in BCR-dependent DLBCLs.

BACKGROUND AND PURPOSE:

Diffuse intrinsic pontine glioma is a lethal childhood brain cancer with dismal prognosis and MR imaging is the primary methodology used for diagnosis and monitoring. Our aim was to determine whether advanced diffusion, perfusion, and permeability MR imaging metrics predict survival and pseudoprogression in children with newly diagnosed diffuse intrinsic pontine glioma.

MATERIALS AND METHODS:

A clinical trial using the poly (adenosine diphosphate ribose) polymerase (PARP) inhibitor veliparib concurrently with radiation therapy, followed by maintenance therapy with veliparib + temozolomide, in children with diffuse intrinsic pontine glioma was conducted by the Pediatric Brain Tumor Consortium. Standard MR imaging, DWI, dynamic contrast-enhanced perfusion, and DSC perfusion were performed at baseline and approximately every 2 months throughout treatment. ADC histogram metrics of T2-weighted FLAIR and enhancing tumor volume, dynamic contrast-enhanced permeability metrics for enhancing tumors, and tumor relative CBV from DSC perfusion MR imaging were calculated. Baseline values, post-radiation therapy changes, and longitudinal trends for all metrics were evaluated for associations with survival and pseudoprogression.

RESULTS:

Fifty children were evaluable for survival analyses. Higher baseline relative CBV was associated with shorter progression-free survival (P = .02, Q = 0.089) and overall survival (P = .006, Q = 0.055). Associations of higher baseline mean transfer constant from the blood plasma into the extravascular extracellular space with shorter progression-free survival (P = .03, Q = 0.105) and overall survival (P = .03, Q = 0.102) trended toward significance. An increase in relative CBV with time was associated with shorter progression-free survival (P < .001, Q < 0.001) and overall survival (P = .004, Q = 0.043). Associations of longitudinal mean extravascular extracellular volume fraction with progression-free survival (P = .03, Q = 0.104) and overall survival (P = .03, Q = 0.105) and maximum transfer constant from the blood plasma into the extravascular extracellular space with progression-free survival (P = .03, Q = 0.102) trended toward significance. Greater increases with time were associated with worse outcomes. True radiologic progression showed greater post-radiation therapy decreases in mode_ADC_FLAIR compared with pseudoprogression (means, –268.15 versus –26.11, P = .01.)

CONCLUSIONS:

ADC histogram, perfusion, and permeability MR imaging metrics in diffuse intrinsic pontine glioma are useful in predicting survival and pseudoprogression.

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Follow our live coronavirus updates HERE Coronavirus: the symptoms

Early in the morning on April 5, 2020, an article appeared on the website Medium with the title “Covid-19 had us all fooled, but now we might have finally found its secret.” The article claimed that the pathology of COVID-19 was completely different from what public health authorities, such as the World Health Organization, had previously described. According to the author, COVID-19 strips the body’s hemoglobin of iron, preventing red blood cells from delivering oxygen and damaging the lungs in the process. It also claimed to explain why hydroxychloroquine, an experimental treatment often hyped by President Trump, should be effective.

The article was published under a pseudonym—libertymavenstock—but the associated account was linked to a Chicagoland man working in finance, with no medical expertise. (His father is a retired M.D., and in a follow-up note posted on a blog called “Small Dead Animals,” the author claimed that the original article was a collaboration between the two of them.) Although it was not cited, the claims were apparently based on a single scientific article that has not yet undergone peer-review or been accepted for publication, along with “anecdotal evidence” scraped from social media.1

While Medium allows anyone to post on their site and does not attempt to fact-check content, this article remained up for less than 24 hours before it was removed for violating Medium’s COVID-19 content policy. Removing the article, though, has not stopped it from making a splash. The original text continues to circulate widely on social media, with users tweeting or sharing versions archived by the Wayback Machine and re-published by a right-wing blog. As of April 12, the article had been tweeted thousands of times.

There is a pandemic of misinformation about COVID-19 spreading on social media sites. Some of this misinformation takes well-understood forms: baseless rumors, intentional disinformation, and conspiracy theories. But much of it seems to have a different character. In recent months, claims with some scientific legitimacy have spread so far, so fast, that even if it later becomes clear they are false or unfounded, they cannot be laid to rest. Instead, they become information zombies, continuing to shamble on long after they should be dead.

POOR STANDARD: The antiviral drug hydroxychloroquine has been hyped as an effective treatment for COVID-19, notably by President Trump. The March journal article that kicked off the enthusiasm was later followed by a lesser-read news release from the board of its publisher, the International Society of Antimicrobial Chemotherapy, which states the “Board believes the article does not meet the Society’s expected standard.”Marc Bruxelle / Shutterstock

It is not uncommon for media sources like Medium to retract articles or claims that turn out to be false or misleading. Neither are retractions limited to the popular press. In fact, they are common in the sciences, including the medical sciences. Every year, hundreds of papers are retracted, sometimes because of fraud, but more often due to genuine errors that invalidate study findings.2 (The blog Retraction Watch does an admirable job of tracking these.)

Reversing mistakes is a key part of the scientific process. Science proceeds in stops and starts. Given the inherent uncertainty in creating new knowledge, errors will be made, and have to be corrected. Even in cases where findings are not officially retracted, they are sometimes reversed— definitively shown to be false, and thus no longer valid pieces of scientific information.3

Researchers have found, however, that the process of retraction or reversal does not always work the way it should. Retracted papers are often cited long after problems are identified,4 sometimes at a rate comparable to that before retraction. And in the vast majority of these cases, the authors citing retracted findings treat them as valid.5 (It seems that many of these authors pull information directly from colleagues’ papers, and trust that it is current without actually checking.) Likewise, medical researchers have bemoaned the fact that reversals in practice sometimes move at a glacial pace, with doctors continuing to use contraindicated therapies even though better practices are available.6

For example, in 2010, the anesthesiologist Scott Reuben was convicted of health care fraud for fabricating data and publishing it without having performed the reported research. Twenty-one of Reuben’s articles were ultimately retracted. And yet, an investigation four years later found half of these articles were still consistently cited, and that only one-fourth of these citations mentioned that the original work was fraudulent.7 Given that Reuben’s work focused on the use of anesthetics, this failure of retraction is seriously disturbing.

Claims with some scientific legitimacy continue to shamble on long after they should be dead.

But why don’t scientific retractions always work? At the heart of the matter lies the fact that information takes on a life of its own. Facts, beliefs, and ideas are transmitted socially, from person to person to person. This means that the originator of an idea soon loses control over it. In an age of instant reporting and social media, this can happen at lightning speed.

The first models of the social spread of information were actually epidemiological models, developed to track the spread of disease. (Yes, these are the very same models now being used to predict the spread of COVID-19.) These models treat individuals as nodes in a network and suppose that information (or disease) can propagate between connected nodes.

Recently, one of us, along with co-authors Travis LaCroix and Anders Geil, repurposed these models to think specifically about failures of retraction and reversal.8 A general feature of retracted information, understood broadly, is that it is less catchy than novel information in the following way. People tend to care about reversals or retractions only when they have already heard the original, false claim. And they tend to share retractions only when those around them are continuing to spread the false claim. This means that retractions actually depend on the spread of false information.

We built a contagion model where novel ideas and retractions can spread from person to person, but where retractions only “infect” those who have already heard something false. Across many versions of this model, we find that while a false belief spreads quickly and indiscriminately, its retraction can only follow in the path of its spread, and typically fails to reach many individuals. To quote Mark Twain, “A lie can travel halfway around the world while the truth is putting on its shoes.” In these cases it’s because the truth can’t go anywhere until the lie has gotten there first.

Another problem for retractions and reversals is that it can be embarrassing to admit one was wrong, especially where false claims can have life or death consequences. While scientists are expected to regularly update their views under normal circumstances, under the heat of media and political scrutiny during a pandemic they too may be less willing to publicize reversals of opinion.

The COVID-19 pandemic has changed lives around the world at a startling speed—and scientists have raced to keep up. Academic journals, accustomed to a comparatively glacial pace of operations, have faced a torrent of new papers to evaluate and process, threatening to overwhelm a peer-review system built largely on volunteer work and the honor system.9 Meanwhile, an army of journalists and amateur epidemiologists scour preprint archives and university press releases for any whiff of the next big development in our understanding of the virus. This has created a perfect storm for information zombies—and although it also means erroneous work is quickly scrutinized and refuted, this often makes little difference to how those ideas spread.

Many examples of COVID-19 information zombies look like standard cases of retraction in science, only on steroids. They originate with journal articles written by credentialed scientists that are later retracted, or withdrawn after being refuted by colleagues. For instance, in a now-retracted paper, a team of biologists based in New Delhi, India, suggested that novel coronavirus shared some features with HIV and was likely engineered.10 It appeared on an online preprint archive, where scientists post articles before they have undergone peer review, on January 31; it was withdrawn only two days later, following intense critique of the methods employed and the interpretation of the results by scientists from around the world. Days later, a detailed analysis refuting the article was published in the peer-reviewed journal Emerging Microbes & Infections.11 But a month afterward, the retracted paper was still so widely discussed on social media and elsewhere that it had that highest Altmetric score—a measure of general engagement with scientific research—of any scientific article published or written in the previous eight years. Despite a thorough rejection of the research by the scientific community, the dead information keeps walking.

Other cases are more subtle. One major question with far-reaching implications for the future development of the pandemic is to what extent asymptomatic carriers are able to transmit the virus. The first article reporting on asymptomatic transmission was a letter published in the prestigious New England Journal of Medicine claiming that a traveler from China to Germany transmitted the disease to four Germans before her symptoms appeared.12 Within four days, Science reported that the article was flawed because the authors of the letter had not actually spoken with the Chinese traveler, and a follow-up phone call by public health authorities confirmed that she had had mild symptoms while visiting Germany after all.13 Even so, the article has subsequently been cited nearly 500 times according to Google Scholar, and has been tweeted nearly 10,000 times, according to Altmetric.

Media reporting on COVID-19 should be linked to authoritative sources that are updated as information changes.

Despite the follow-up reporting on this article’s questionable methods, the New England Journal of Medicine did not officially retract it. Instead, a week after publishing the letter, the journal added a supplemental appendix describing the progression of the patient’s symptoms while in Germany, leaving it to the reader to determine whether the patient’s mild early symptoms should truly count. Meanwhile, subsequent research14, 15 involving different cases has suggested that asymptomatic transmission may be possible after all—though as of April 13, the World Health Organization considers the risk of infection from asymptomatic carriers to be “very low.” It may turn out that transmission of the virus can occur before any symptoms appear, or while only mild symptoms are present, or even in patients who will never go on to present symptoms. Even untangling these questions is difficult, and the jury is still out on their answers. But the original basis for claims of confirmed asymptomatic transmission was invalid, and those sharing them are not typically aware of the fact.

Another widely discussed article, which claims that the antiviral drug hydroxychloroquine and the antibiotic azithromycin, when administered together, are effective treatments for COVID-19 has drawn enormous amounts of attention to these particular treatments, fueled in part by President Trump.16 These claims, too, may or may not turn out to be true—but the article with which they apparently originated has since received a statement of concern from its publisher, noting that its methodology was problematic. Again, we have a claim that rests on shoddy footing, but which is spreading much farther than the objections can.17 And in the meantime, the increased demand for these medications has led to dangerous shortages for patients who have an established need for them.18

The fast-paced and highly uncertain nature of research on COVID-19 has also created the possibility for different kinds of information zombies, which follow a similar pattern as retracted or refuted articles, but with different origins. There have been a number of widely discussed arguments to the effect that the true fatality rate associated with COVID-19 may be ten or even a hundred times lower than early estimates from the World Health Organization, which pegged the so-called “case fatality rate” (CFR)—the number of fatalities per detected case of COVID-19—at 3.4 percent.19-21

Some of these arguments have noted that the case fatality rate in certain countries with extensive testing, such as Iceland, Germany, and Norway, is substantially lower. References to the low CFR in these countries have continued to circulate on social media, even though the CFR in all of these locations has crept up over time. In the academic realm, John Ioannidis, a Stanford professor and epidemiologist, noted in an editorial, “The harms of exaggerated information and non‐evidence‐based measures,” published on March 19 in the European Journal of Clinical Investigation, that Germany’s CFR in early March was only 0.2 percent.21 But by mid-April it had climbed to 2.45 percent, far closer to the original WHO estimate. (Ioannidis has not updated the editorial to reflect the changing numbers.) Even Iceland, which has tested more extensively than any other nation, had a CFR of 0.47 percent on April 13, more than 4 times higher than it was a month ago. None of this means that the WHO figure was correct—but it does mean some arguments that it is wildly incorrect must be revisited.

What do we do about false claims that refuse to die? Especially when these claims have serious implications for decision-making in light of a global pandemic? To some degree, we have to accept that in a world with rapid information sharing on social media, information zombies will appear. Still, we must combat them. Science journals and science journalists rightly recognize that there is intense interest in COVID-19 and that the science is evolving rapidly. But that does not obviate the risks of spreading information that is not properly vetted or failing to emphasize when arguments depend on data that is very much in flux.

Wherever possible, media reporting on COVID-19 developments should be linked to authoritative sources of information that are updated as the information changes. The Oxford-based Centre for Evidence-Based Medicine maintains several pages that review the current evidence on rapidly evolving questions connected to COVID-19—including whether current data supports the use of hydroxychloroquine and the current best estimates for COVID-19 fatality rates. Authors and platforms seeking to keep the record straight should not just remove or revise now-false information, but should clearly state what has changed and why. Platforms such as Twitter should provide authors, especially scientists and members of the media, the ability to explain why Tweets that may be referenced elsewhere have been deleted. Scientific preprint archives should encourage authors to provide an overview of major changes when articles are revised.

And we should all become more active sharers of retraction. It may be embarrassing to shout one’s errors from the rooftops, but that is what scientists, journals, and responsible individuals must do to slay the information zombies haunting our social networks.

Cailin O’Connor and James Owen Weatherall are an associate professor and professor of logic and philosophy at the University of California, Irvine. They are coauthors of The Misinformation Age: How False Beliefs Spread.

Lead image: nazareno / Shutterstock

References

1. Liu, W. & Li, H. COVID-19 attacks the 1-beta chain of hemoglobin and captures the porphyrin to inhibit human heme metabolism. ChemRxiv (2020).

2. Wager, E. & Williams, P. Why and how do journals retract articles? An analysis of Medline retractions 1988-2008. Journal of Medical Ethics 37, 567-570 (2011).

3. Prasad, V., Gall, V., & Cifu, A. The frequency of medical reversal. Archives of Internal Medicine 171, 1675-1676 (2011).

4. Budd, J.M., Sievert, M., & Schultz, T.R. Phenomena of retraction: Reasons for retraction and citations to the publications. The Journal of the American Medical Association 280, 296-297 (1998).

5. Madlock-Brown, C.R. & Eichmann, D. The (lack of) impact of retraction on citation networks. Science and Engineering Ethics 21, 127-137 (2015).

6. Prasad, V. & Cifu, A. Medical reversal: Why we must raise the bar before adopting new technologies. Yale Journal of Biology and Medicine 84, 471-478 (2011).

7. Bornemann-Cimenti, H., Szilagyi, I.S., & Sandner-Kiesling, A. Perpetuation of retracted publications using the example of the Scott S. Reuben case: Incidences, reasons and possible improvements. Science and Engineering Ethics 22, 1063-1072 (2016).

8. LaCroix, T., Geil, A., & O’Connor, C. The dynamics of retraction in epistemic networks. Preprint. (2019).

9. Jarvis, C. Journals, peer reviewers cope with surge in COVID-19 publications. The Scientist (2020).

10. Pradhan, P., et al. Uncanny similarity of unique inserts in the 2019-nCoV spike protein to HIV-1 gp120 and Gag. bioRxiv (2020).

11. Xiao, C. HIV-1 did not contribute to the 2019-nCoV genome. Journal of Emerging Microbes and Infections 9, 378-381 (2020).

12. Rothe, C., et al. Transmission of 2019-nCoV infection from an asymptomatic contact in Germany. New England Journal of Medicine 382, 970-971 (2020).

13. Kupferschmidt, K. Study claiming new coronavirus can be transmitted by people without symptoms was flawed. Science (2020).

14. Hu, Z., et al. Clinical characteristics of 24 asymptomatic infections with COVID-19 screened among close contacts in Nanjing, China. Science China Life Sciences (2020). Retrieved from doi: 10.1007/s11427-020-1661-4.

15. Bai, R., et al. Presumed asymptomatic carrier transmission of COVID-19. The Journal of the American Medical Association 323, 1406-1407 (2020).

16. Gautret, P., et al. Hydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open-label non-randomized clinical trial. International Journal of Antimicrobial Agents (2020).

17. Ferner, R.E. & Aronson, J.K. Hydroxychloroquine for COVID-19: What do the clinical trials tell us? The Centre for Evidence-Based Medicine (2020).

18. The Arthritis Foundation. Hydroxychloroquine (Plaquenil) shortage causing concern. Arthritis.org (2020).

19. Oke, J. & Heneghan, C. Global COVID-19 case fatality rates. The Centre for Evidence-Based Medicine (2020).

20. Bendavid, E. & Bhattacharya, J. Is the coronavirus as deadly as they say? The Wall Street Journal (2020).

21. Ionnidis, J.P.A. Coronavirus disease 2019: The harms of exaggerated information and non-evidence-based measures. European Journal of Clinical Investigation 50, e13222 (2020).

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The officials deciding what to open, and when, seldom offer thoughtful rationales. Clearly, risk communication about COVID-19 is failing with potentially dire consequences.Photograph by michael_swan / Flickr

When I worked as a TV reporter covering health and science, I would often be recognized in public places. For the most part, the interactions were brief hellos or compliments. Two periods of time stand out when significant numbers of those who approached me were seeking detailed information: the earliest days of the pandemic that became HIV/AIDS and during the anthrax attacks shortly following 9/11. Clearly people feared for their own safety and felt their usual sources of information were not offering them satisfaction. Citizens’ motivation to seek advice when they feel they aren’t getting it from official sources is a strong indication that risk communication is doing a substandard job. It’s significant that one occurred in the pre-Internet era and one after. We can’t blame a public feeling misinformed solely on the noise of the digital age.

America is now opening up from COVID-19 lockdown with different rules in different places. In many parts of the country, people have been demonstrating, even rioting, for restrictions to be lifted sooner. Others are terrified of loosening the restrictions because they see COVID-19 cases and deaths still rising daily. The officials deciding what to open, and when, seldom offer thoughtful rationales. Clearly, risk communication about COVID-19 is failing with potentially dire consequences.

A big part of maintaining credibility is to admit to uncertainty—something politicians are loath to do.

Peter Sandman is a foremost expert on risk communication. A former professor at Rutgers University, he was a top consultant with the Centers for Disease Control in designing crisis and emergency risk-communication, a field of study that combines public health with psychology. Sandman is known for the formula Risk = Hazard + Outrage. His goal is to create better communication about risk, allowing people to assess hazards and not get caught up in outrage at politicians, public health officials, or the media. Today, Sandman is a risk consultant, teamed with his wife, Jody Lanard, a pediatrician and psychiatrist. Lanard wrote the first draft of the World Health Organization’s Outbreak Communications Guidelines. “Jody and Peter are seen as the umpires to judge the gold standard of risk communications,” said Michael Osterholm of the Center for Infectious Disease Research and Policy at the University of Minnesota. Sandman and Lanard have posted a guide for effective COVID-19 communication on the center’s website.

I reached out to Sandman to expand on their advice. We communicated through email.

Sandman began by saying he understood the protests around the country about the lockdown. “It’s very hard to warn people to abide by social-distancing measures when they’re so outraged that they want to kill somebody and trust absolutely nothing people say,” he told me. “COVID-19 outrage taps into preexisting grievances and ideologies. It’s not just about COVID-19 policies. It’s about freedom, equality, too much or too little government. It’s about the arrogance of egghead experts, left versus right, globalism versus nationalism versus federalism. And it’s endlessly, pointlessly about Donald Trump.”

Since the crisis began, Sandman has isolated three categories of grievance. He spelled them out for me, assuming the voices of the outraged:

• “In parts of the country, the response to COVID-19 was delayed and weak; officials unwisely prioritized ‘allaying panic’ instead of allaying the spread of the virus; lockdown then became necessary, not because it was inevitable but because our leaders had screwed up; and now we’re very worried about coming out of lockdown prematurely or chaotically, mishandling the next phase of the pandemic as badly as we handled the first phase.”

• “In parts of the country, the response to COVID-19 was excessive—as if the big cities on the two coasts were the whole country and flyover America didn’t need or didn’t deserve a separate set of policies. There are countless rural counties with zero confirmed cases. Much of the U.S. public-health profession assumes and even asserts without building an evidence-based case that these places, too, needed to be locked down and now need to reopen carefully, cautiously, slowly, and not until they have lots of testing and contact-tracing capacity. How dare they destroy our economy (too) just because of their mishandled outbreak!”

• “Once again the powers-that-be have done more to protect other people’s health than to protect my health. And once again the powers-that-be have done more to protect other people’s economic welfare than to protect my economic welfare!” (These claims can be made with considerable truth by healthcare workers; essential workers in low-income, high-touch occupations; residents of nursing homes; African-Americans; renters who risk eviction; the retired whose savings are threatened; and others.)

In their article for the Center for Infectious Disease Research and Policy, Sandman and Lanard point out that coping with a pandemic requires a thorough plan of communication. This is particularly important as the crisis is likely to enter a second wave of infection, when it could be more devastating. The plan starts with six core principles: 1) Don’t over-reassure, 2) Proclaim uncertainty, 3) Validate emotions—your audience’s and your own, 4) Give people things to do, 5) Admit and apologize for errors, and 6) Share dilemmas. To achieve the first three core principles, officials must immediately share what they know, even if the information may be incomplete. If officials share good news, they must be careful not to make it too hopeful. Over-reassurance is one of the biggest dangers in crisis communication. Sandman and Lanard suggest officials say things like, “Even though the number of new confirmed cases went down yesterday, I don’t want to put too much faith in one day’s good news.” 

Sandman and Lanard say a big part of maintaining credibility is to admit to uncertainty—something politicians are loath to do. They caution against invoking “science” as a sole reason for action, as science in the midst of a crisis is “incremental, fallible, and still in its infancy.” Expressing empathy, provided it’s genuine, is important, Sandman and Lanard say. It makes the bearer more human and believable. A major tool of empathy is to acknowledge the public’s fear as well as your own. There is good reason to be terrified about this virus and its consequences on society. It’s not something to hide.

Sandman and Lanard say current grievances with politicians, health officials, and the media, about how the crisis has been portrayed, have indeed been contradictory. But that makes them no less valid. Denying the contradictions only amplifies divisions in the public and accelerates the outrage, possibly beyond control. They strongly emphasize one piece of advice. “Before we can share the dilemma of how best to manage any loosening of the lockdown, we must decisively—and apologetically—disabuse the public of the myth that, barring a miracle, the COVID-19 pandemic can possibly be nearing its end in the next few months.”

Robert Bazell is an adjunct professor of molecular, cellular, and developmental biology at Yale. For 38 years, he was chief science correspondent for NBC News.

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