The Hollowing Out of America’s Advocates for Public Health

One of CDC’s key vaccine experts resigned this week, a direct consequence of HHS leadership failures that prioritize ideology over evidence.

Some folks are doers. They convert ideas into real things. They stand up when the moment demands it. These doers are the backbone of government function – they solve problems, convert experience into action, and have the wisdom to interpret signals amidst the fog of uncertainty. This week, we lost one such doer from government service. Hers is not a household name and she is not the only one, but she is one that I know – not through any personal connection but through the quality of her work and willingness to share insights in a crisis where experience and expertise matters. Her choice to resign is gaining national attention because her decision reflects a fundamental degradation in America’s capacity to leverage experts and expertise to support mission-driven agencies in health, human services, and beyond.

The hollowing out of what makes HHS work.

The Washington Post broke the story on Monday June 16^th, sharing a report that Fiona Havers, a medical epidemiologist and vaccine expert at the CDC, decided to resign from service because, in her words shared via email:

“I no longer have confidence that these data will be used objectively or evaluated with appropriate scientific rigor to make evidence-based vaccine policy decisions.”

The story immediately struck me for two reasons. First, Havers is not a household name. Second, I work in epidemic modeling areas adjacent to Havers’ specialization to know her work represents some of the best of the CDC. Her resignation means that HHS leadership decisions to undercut evidence-driven decision making has crossed a threshold: forcing experts within government to face the realistic chance that their work would be misused to advance ideological aims.

Havers has a long and distinguished career spanning multiple public health threats, including working on interventions to the 2014-2016 Ebola virus disease outbreak in W. Africa, managing antibiotic use in influenza infections, estimating the burden of RSV-associated hospitalizations, and responding to Covid from the pre- to post-vaccination phases of the public health emergency. Notably, Havers is the lead author of an early 2020 study on seroprevalence of antibodies to Covid, finding significant underdetection of infections, one of a series of studies providing a fuller picture of who was infected in light of mild/asymptomatic cases and limited testing.

This paper and the organization of a national serosurvey addressed an essential problem during the early stages of the pandemic – viral testing was too limited and too slow. Many individuals had mild or asymptomatic infections and never knew they had been infected. As a result, many of our early responses were shaped by significant uncertainty regarding how many people had been infected. If we could more accurately assess the number of infections then we could estimate how many remained immunologically naïve and improve estimates of the infection fatality rate.

Havers and her team’s work showed that (i) far more individuals had been infected than detected using PCR-based viral tests, initially at levels about 10x that eventually dropped to levels between of ~4x later in 2020, but that (ii) the vast majority of Americans remained immunologically naive in early 2020 and were susceptible to infection and (severe) disease; and finally that (iii) the infection fatality rate for COVID was lower than reported case fatality rates but still well above that of flu.

This is a long way to say that Havers and her team of collaborators narrowed down the uncertainty while also clarifying precisely the potential for large-scale infection, hospitalizations, and fatalities in mid-2020. Havers and colleagues are precisely the kind of scientists you want to have working at a federal agency – they know what questions to ask, how to address them, how to interpret the data, and how to communicate their findings to the broader public. Everything I just described was already available to scientists and policy makers in by June 2020 and published after peer review in JAMA Internal Medicine by July 2020 – eventually informing public-facing work on risk assessment, forecasts, and scenario evaluation, including assessing the public health impacts of vaccines from 2021 onwards.

Havers has resigned. Instead, the US is left with RFK Jr leading HHS and Jay Bhattacharya leading NIH. Although RFK Jr’s long-standing anti-vaccine activism is well known, the work of Bhattacharya is typically associated with the ‘Great Barrington Declaration’ that advocated for a rapid reopening amidst the near-term availability of life-saving vaccines. But interestingly, in early 2020 Bhattacharya also worked on a serosurvey in a way that reflects a wholly different approach to public health research in the midst of a global crisis.

In April 2020, Jay Bhattacharya and colleagues released a preprint focusing on a serosurvey they designed and implemented in Santa Clara County in which they concluded that “there were 50-85-fold more [undetected infections] than the number of confirmed cases.” If this were true, it would have been a game-changer. The preprint implied that far more people had been infected and we could see 'herd immunity' soon and that the true infection fatality rate of COVID was much much lower than reported, perhaps on par with seasonal influenza. The preprint drew national attention. But it wasn't true & we knew it was wrong at the time.

Revisiting the Santa Clara serological survey is vital to arguments in my book (‘Asymptomatic’) explaining that the misinterpretation of asymptomatic infections made COVID harder to stop and easier for some – including Bhattacharya and colleagues – to weave unobserved data to fit a particular viewpoint. Bhattacharya and colleagues' work had a number of flaws spanning the study design and participant recruitment such that the sample was likely unrepresentative of the public at large. Moreover, because of the imperfect nature of testing for antibodies in it was possible that many (if not most) of the positive antibody tests were actually false positives.

Bhattacharya’ claim that 50-85x more individuals had been infected as observed via serological surveys than detected using PCR-based tests became the basis for a recurrent theme: that COVID was no worse than the flu. There is a direct line from this flawed early work and the grievances that permeate a recurring effort to minimize COVID’s impacts. This direct line goes all the way to recent COVID revisionism, including the book “In Covid’s Wake” (to be discussed in an upcoming post), and decisions by RFK Jr to disband ACIP and by Bhattacharya to support devastating cuts to federally funded medical research.

There are many reasons to have substantive discussions about policy failures during the global health emergency. In doing so it is essential to remember that Covid killed more than 1.2M Americans, led to devastating impacts in the acute early phase, and would have killed far more if not for life-saving vaccines. We can and must do better. But how will we learn from successes and failures if the federal government intentionally abandons an evidence-based approach to decision making in favor of one governed by ideology?

Havers’ resignation suggests that data may be molded to fit preferred policy decisions rather than being used to design evidence-based responses to RSV, COVID, measles and more. Fiona Havers is precisely the kind of scientist the CDC should have on its team to sort out the signal from the noise. Moving forward, America’s ability to respond to public health threats will be diminished when we lose dedicated experts who would work in the nation’s service if only the administration lets them.