I knew the week ahead would present opportunities to put all the different elements of my plan in place, but I started the second week with one clear focus above all others: to use the best available data to demonstrate the way to move forward. To do this, I needed help.
I already had a clear sense of whom I needed for my small but essential data team: people whose tirelessness was a testament to their character. At first, I thought I would be able to find them on my own, but then Irum called me after she’d arrived from South Africa. She was coming voluntarily. She knew I would need support, and she was offering it. I needed her aboard immediately, and she was.
By Friday of the first week, I’d requested two others from the White House: Daniel Gastfriend from the Office of Management and Budget (OMB) and digital services expert Amy Gleason. Daniel had studied public administration and international development at the Harvard Kennedy School. He had also worked in South Africa, Uganda, and India. I hoped that having someone from within the White House Office of Management and Budget would help offset the “deep state” perceptions. Daniel was also young, very talented, and a tireless advocate for public health responses, possessing a wealth of knowledge about health security.
Amy Gleason had worked for years in the medical data field before joining the White House in the United States Digital Service team in 2018. Her previous experience with OMB and the White House would help in her management of services—and my management of perceptions.
Others I had worked with for years from the CDC volunteered to help me. Chuck Vitek was a CDC epidemiologist I knew and trusted. He was board certified in infectious diseases and had a strong public health background, having worked in the U.S. Public Health Service’s Commissioned Corps. Behind the scenes initially and out front later, Dr. Sean Cavanaugh was invaluable. With prior CDC and Department of Defense experience, he understood what frontline work was all about and the need to do it now and not wait. Bob Redfield said he’d be willing to release Steve Redd from his job in the CDC’s Emergency Operations Center in Atlanta. Steve served as an important conduit to CDC staff in Atlanta, aiding us greatly in aligning our mission with theirs.
I was glad to have CDCers in-house to interface with the agency’s data people. Steve was senior, smart, and a critical influencer within the CDC. If I could convince him and Chuck of the depth and breadth of the silent spread, both would be helpful in convincing senior CDCers that their flu model of tracking symptoms was wrong for this virus. We were fortunate in that Steve knew the individuals as well as the groupthink that often characterized the CDC’s positions and policies.
They knew what I was up against and how the negative perception of working in this White House might affect their careers, but they volunteered anyway. I will never forget all of them or the commitment and sacrifice they displayed in taking on something so hard and never ending.
We set up a command suite in a large conference room in the Eisenhower Executive Office Building (EEOB). Though the team comprised just five people on-site plus Sean, they were all outside any political bubble. I could trust them to look at the numbers and provide an unvarnished analysis free from a hidden or political agenda. There would be no groupthink within my inner circle.
Doubt existed about the extent of the silent spread. In our first week working together, we’d wind up in spirited debate. The working group demonstrated what I had hoped to find when I first came into the task force: people working from the best available information, using their diverse knowledge, skills, and experience to arrive at the best approach to the problem at hand.
Right away, I started pressing Steve Redd on the CDC’s data streams, and he explained that the CDC didn’t have the demographic data I was looking for. Worse, the data it did have would never help paint an accurate picture of this pandemic outbreak. When it came to an outbreak like Covid-19, the CDC reporting system was riddled with problems. Hospitals weren’t required to report their data, and the voluntary data-reporting facilities that existed weren’t distributed evenly around the country. Models based on this geographically biased data would, therefore, always produce inaccurate projections. Reports the CDC did receive included symptoms but no confirmed diagnoses of an illness. These symptoms were used to cluster illnesses into less specific categories, like “influenza-like illness.” Without knowing for sure what was causing the symptoms, we faced a whole new kind of ambiguity in the data sets. Was it flu or Covid-19, or was it both? Without a laboratory test, it was impossible to separate the two.
The CDC also had no laboratory reporting to it outside its own Public Health Laboratories. There was no way, therefore, to see the total number of tests performed, the total number of positive tests. Test positivity rates were a way to understand whether we were finding most of the infections and the only way to define the level of asymptomatic spread.
There was also no comprehensive hospital reporting of even symptomatic respiratory diseases. The CDC should have demanded that 100 percent of U.S. hospitals report all their Covid-19 cases and pushed for definitive laboratory confirmation of all cases.
Instead, the CDC relied on another reporting system—the National Hospital Security Network for its hospital figures. The NHSN was used primarily to track hospital-acquired infections and community-acquired infections that required hospitalization. It was also used to produce projections about the depth and spread of flu outbreaks. Unfortunately, this voluntary CDC-funded system was in place in only 40 percent of hospitals across the country. It could never provide us with an accurate view of what was happening in the remaining hospitals, only in modeled assessment. Worse, these figures often took weeks to get to the CDC. With only 40 percent of the delayed hospital data available to project what was happening across the country, we’d have a less accurate geographic assessment of the depth and spread of the outbreak.
It was also only a window into those sick enough to be hospitalized. In parallel to utilizing global health security funding they were tracking a small subset of United States emergency rooms symptom-based illnesses including influenza-like illness. Again, only those sick enough to come to emergency rooms. It wouldn’t help us account for silent spread, and any projections based on this biased and delayed data when used to create a predictive model would be inaccurate.
Also, the NHSN was especially problematic for use with Covid-19 specifically. If, in early March 2020, two people with “flu-like” symptoms went to a reporting hospital, they would both have been recorded in the CDC database as experiencing “flu-like” illness. If those patients weren’t tested for Covid-19, then they would remain in that flu-like illness category until tests determined whether they had seasonal flu or Covid-19. Even worse than this incomplete and slow accounting of hospital cases, relying on symptoms as a diagnosis meant the system once again offered no visibility into how Covid could be spreading asymptomatically. The only time the system could be trusted to identify Covid-19 disease by symptoms was when the seasonal influenza and influenza-like illness (ILI) declined and one could clearly see the second peak in the spring of 2020 due to Covid-like illness (CLI). The public health labs could test samples for influenza (H1 and N1) strains, but their platforms weren’t easily adaptable to test samples of suspected SARS-CoV-2 infections. It took some time before those lab tests were available to identify definitive positive cases, further delaying the CDC’s ability to see and to communicate what was really going on.
Along with these delays, because this system was used mainly for infection control and analysis, it didn’t track the hospital PPE utilization or need. Consequently, there was no centralized built-in alarm to alert us when protection for frontline health care workers was running short. We needed to move to a proactive system. We couldn’t wait for the phone calls from hospitals notifying us that they were totally out and in crisis. I was told by CDC officials that tracking hospital supplies was not their mandate. They wouldn’t add the supply element module to their system. Their refusal would require us to create yet another reporting system for hospitals. Now they would need to submit data three times. First for clinical care based on codes, next to provide data to the NHSN, and now data to the federal teams to support supplies. This resulted in them triplicating their efforts when they needed to simplify their response due to the coming crush of patients. Without a federal level reporting system, requests would come in from the states and local officials in a far less organized manner than what was needed.
If 100 percent of hospitals, emergency rooms, urgent care clinics, and pediatric offices had been part of the CDC’s early warning system as well as definitive laboratory diagnosis of ILI, Covid-19 would have been spotted far sooner on our shores, and we could have reacted much more quickly. Without a doubt, there are Americans, particularly in New York City, who went to the doctor, hospital, or ER with Covid-19 in February 2020 and were sent home with a symptomatic diagnosis of the flu, without a flu test being performed. If they had been tested for flu (or for all viral respiratory diseases), a red flag would have gone up when the results came back negative. Medical personnel likely would have realized that this person was sick with the same mysterious respiratory disease reported in China, and that was not the flu. That’s how new viruses typically get discovered: doctors run normal laboratory tests and, through negative results, learn that it’s none of the usual infectious suspects. Through negative tests for the flu, this mysterious illness would likely have led local doctors and, eventually, the CDC to connect the dots to what was happening in China in February 2020.
Instead of those early Covid-19 patients being caught in our early warning system, no red flag was raised, and those cases began to spread in the United States. For weeks the U.S. would stay stalled in the “containment” phase rather than aggressively mitigating. The Plan A that had long been established and agreed upon was based on this symptomatic detection. There was no Plan B then, and to this day there still is no Plan B. We would work to resolve some of these issues, but at this critical juncture, while I was trying to formulate a case for shutdown by any other name, the existing CDC data wouldn’t be of much help to me.
When I first went to Africa twenty-two years ago, no comprehensive laboratory or health data system existed. It took several years to build one for HIV, and we added additional disease models over time, while also including laboratory information systems. These databases and programs integrated data from various sources, allowing us to account for different aspects of the infections and disease. This comprehensive data system and population-based surveys allowed us to track the quality of care and the outcomes and impact of the program. These systems were the backbone of our collective ability to begin to control the HIV pandemic in Africa. From 2014 on, we did all this efficiently and accurately, while also adapting the health data system flexibly, to meet our needs and the specifics of a disease. Shockingly, this wasn’t the case with the CDC’s system in 2020, and it still isn’t today.
If we could design and use these essential tools in resource-limited settings like Africa, why hadn’t it been done in the United States? My assumption had been that the CDC had a best-in-class system to gather baseline data from all the hospitals and nursing homes in the country. If you have a new infectious agent you’re worried about, a health data system is where it would show up first. But the CDC didn’t have data collection like this in place.
The United States needs a Plan B, one in which all community-acquired infectious diseases are reported and definitive laboratory diagnostics performed. We need to move into the twenty-first century, using our amazing technical capacity linked with existing coded electronic medical records to create a national database on current community infectious diseases, so we can spot the new ones as soon as they emerge. This integrated data system would also ensure widespread testing capacity and better antivirals for treatment. Not only will that help us begin interventions sooner, but it will give pharmaceutical and biotech firms an earlier start on developing viral specific therapeutics.
After I learned about the CDC’s data collection issues—the delays in reporting as well as the vastly incomplete data which was missing age, race, and ethnicity information—the CDC’s reluctance to accept my ideas around silent spread began to make more sense. While I had been poring over the more complete international data from Italy and other countries, data whose implications were obvious to the trained eye, the CDC had been focusing on more limited, domestic data. It wasn’t seeing the asymptomatic spread because its early warning system was designed to show the exact opposite: growth in the number of people with significant symptoms, and only those who sought treatment in a clinic or hospital—with luck, one of the 40 percent the CDC was monitoring. This was why it was so hard for CDC researchers and officials to see the role asymptomatic cases were playing in fueling that growth—the CDC was operating in a bubble it had itself created. It was almost as if it was working to formulate a response to a completely different virus than I was. At this point, in the second week of March 2020, Johns Hopkins was doing a better job of aggregating count and location data across the globe than the CDC was.
Making matters worse, the CDC had put this symptom-based, incomplete flu model data through the sophisticated predictive model it had developed to show how serious the novel coronavirus outbreak would become in the United States. It then used those results to determine what was happening in the country. This compounded the agency’s initial errors by making predictions based on the poor visibility of the original data.
Yet the CDC believed steadfastly in the accuracy of its predictive models. If it had been the National Oceanic and Atmospheric Administration doing the same thing to create a weather forecast, outdoor plans might have been disrupted. But when it is the premier public health agency in the United States looking at an emerging pandemic, the consequences are far greater. No one individual dropped the ball. The system had been designed this way, and its problems were deeply entangled with how the CDC had related to the states for years. While it might sound overly ambitious to imagine every hospital in the United States reporting data to the CDC every day, we made it happen by June 2020. So, it wasn’t that hard to envision every one of those six thousand hospitals reporting detailed data—if only the CDC had set up the infrastructure for this. The same held true for nursing homes: there was no mandatory reporting out of nursing homes, and yet there were only fifteen thousand of them in the country. Seema Verma took this on and made it happen by June 2020, proving that the problems with mandatory reporting weren’t intractable. What it took was finding the will to do it.
This lack of will was the root issue. The CDC has never required anyone, neither the states nor hospitals, to report data outside a specific list of required reportable diseases, and that reporting is often done weeks to months after the cases are diagnosed. Every year, the CDC disburses an enormous amount of taxpayer money in the form of block grants and cooperative agreements to all fifty states, local governments, nonprofits, educational institutions, and for-profit groups, but it has been historically unwilling to attach strings to those federal dollars in the form of mandated data reporting and accountability for the dollars spent. Work plans are often submitted and reviewed, but there was no required reporting of outcomes or impact. Had the rates of diabetes, hypertension, and obesity declined? Were the dollars linked to the reporting of respiratory diseases (including viral ones like Covid-19) and to improving their laboratory diagnosis in real time? Without mandatory reporting, we lacked the data to answer these questions.
Similarly, despite the federal funding going to the states, CDC personnel believed they had to be invited into individual states during an outbreak or other public health emergency. So, unless a state wants them there, the CDC lacks the power to do anything directly. Basically, data reporting became something of a states’ rights issue. Knowing they would need permission to come into these states, the CDC didn’t want to create any ill will through mandatory data reporting that might contribute to the states’ refusing them entry. The compromise that had been reached with the states came in the form of “voluntary” reporting, and the CDC lived in fear of having the states turn off this voluntary data spigot. At the CDC, the mantra appeared to be: Tread lightly, don’t press too hard, and be grateful for what little data you have access to, no matter the delay or incomplete nature of the data.
This jurisdictional tension would play out in many ways during this crisis, but at the start, it led to the CDC’s not pushing the states too hard for detailed data and relying heavily on its preexisting voluntary reporting systems, including those where the states used paper and fax machines to transmit data. Any remedy to this system would be tantamount to making what had been voluntary, mandatory, and getting to mandatory reporting would take changing legislation and guidelines. But these actions were too time consuming and too complex to take on in the immediate. (Eventually, after a great deal of lobbying on my part, I was able to get mandatory reporting of all laboratory PCR test results, both positive and negative, from the states to the CDC. This required getting the White House to weigh in and make sure that this change was included in the Coronavirus Aid, Relief, and Economic Security pandemic-relief bill known as CARES, passed weeks into the pandemic, after the situation had already grown dire.)
Before these systems were up and running, both Roche and Abbott, due to the great work by the private sector in developing and shipping tests by the end of March, were sending me their nightly equipment reports from their platforms, so I could see hospital and commercial laboratories’ test positivity rates. In many labs, that figure was between 30 and 50 percent. This gave us some insight into how bad the next few weeks would be. Night after night, month after month, this data arrived from laboratory after laboratory. Having all this data allowed us to triangulate it with other figures and use the findings to guide our actions. This contribution from these labs demonstrates the value of mandatory data reporting. We got there, but if we’d had that more complete data set earlier, we’d have had a greater sense of urgency sooner, urgency that could have been translated into more proactive measures being implemented sooner.
In the end, the flu bias in the CDC’s data system and the agency’s jurisdictional limitations exposed, once again, the rigidity in its thinking—only, now, instead of on masks and tests, it was on data collection. To work around this systemic inflexibility would require more than just a tweak. We would have to significantly modify the models used to produce accurate projections, something that would require between weeks and months of work. More time lost meant more lives lost. This was the reality we faced in early March 2020.
As is true for so much of this story, the failure here does not belong to any one institution or person. It’s bigger than that, broader than that. It defies easy explanation or reflexive answers. It’s easy to lay the blame at the feet of the Trump administration, saying things like Well, this all happened because the Trump administration gutted the CDC. But it’s crucial to understand that the CDC had been fully funded for global health security and domestic health security since 2009. It had received millions upon millions of dollars in global health security funds every year for precisely the situation we were now in. They made decisions that resulted in the absence of a comprehensive national clinical and laboratory data system. No one else is accountable for that.
In other words, this specific issue was not a Trump administration problem; it was a CDC problem. No one in any presidential administration had instructed the CDC to design their data system this way. This was a plan the CDC had devised and funded. It was a twentieth-century solution for a twenty-first-century world.
It’s convenient to solely blame President Trump, and while he certainly deserves his share of the blame and then some for his response, blaming only his failures and letting the CDC and other HHS agencies off the hook for poor institutional choices over the years would be a recipe for repeating the same mistakes in the future. From masks to tests to data collection to flu bias—the CDC made several very real and very consequential decisions that shaped the early months of the pandemic and are still shaping events today. To this day, the data is incomplete. It is collected and analyzed too slowly. Small convenience studies are done rather than comprehensive country-wide analyses of everything from testing to sequencing to the impact of differential mitigation. As I write this, there remains a lack of emphasis on active testing, and there is still no sense of urgency to find the silent community invasion that occurs days to weeks before symptoms. This is bigger than who the president is or which political party is in charge. In many ways, anti-Trump sentiment has prevented people from seeing the full spectrum of the breakdown at the CDC in the pandemic’s early months and that continues today and still needs to be addressed.
Ultimately, the CDC’s greatest sin was not recognizing and acknowledging that it had sinned. Instead of fixing the issues, it hardened its belief that its approach was the best because they were the best.
Simply put, I, along with many others, saw that the CDC’s numbers were incomplete. By plugging its flawed data into their models, the agency’s researchers were never going to produce an accurate forecast. Even much later, when more data was available, they clung to their initial projections. As difficult as it is for me to believe and to write this, it’s true that one of our nation’s finest medical/scientific institutions, one of the world’s leading public health entities, believed that the projections it had derived from its model of cases and hospitalizations were more accurate than the real, comprehensive data itself.
This really stunned me. I pushed back on this notion constantly, but they were immovable.
This resulted in consequences in that first year that carried into 2021. Each and every surge through 2020 and 2021 was visible early, with rising test positivity in the younger age groups appearing days to weeks prior to hospitalizations increasing. Early and expanded testing of community college students along with sequencing would have allowed us to “see” the virus in the community early and see the new variants much earlier. But each time, the alert came too late, sometimes because of incomplete or late data—or, maybe because each time, we believed it would be different. Reacting late each time and not testing broadly enough cost lives then and now. Later, when we were behind in finding new variants, we had to rely on other countries, where the data was available. The same was true for vaccines and the durability of vaccine protection: we had to rely on the well-collected data from other countries to make decisions in this country, the United States, the country with the most advanced IT and data collection capacity, which we could have tapped into from the private sector.
When it comes to bad data producing bad projections to guide actions, it’s hard to determine the specific long-term consequences. What I can say is this: real-time data allows you to understand the present and predict the future with a fair amount of accuracy. This is especially true when tracking relative rates of increase and not just an absolute number. The confusion around these two concepts—how fast an increase is occurring versus what the overall tally is—continues to distort perceptions and delay actions. If a wildfire is approaching, knowing how fast it is moving and not how many acres it has consumed so far will better guide your immediate action. The rate of rise determines the level of urgency more than an accumulated total does. The first of these helps predict what is to come; the latter characterizes what has already happened. Too often, the CDC relied on this “rearview mirror” approach instead of using data to determine a future course of action and make corrections.
The more information you have, the better able you are to show people, with a high degree of certainty, where they’re going. Incomplete data opens us up to inaccurate interpretations, mischaracterizations, and politicization.
Perhaps it’s not surprising, then, that all three of these happened next.
ON WEDNESDAY, MARCH 11, we gathered in the Oval Office for a face-to-face meeting with the president. The only item on the agenda was issuing another travel ban—this one to and from Continental Europe.
I wasn’t looking forward to this meeting. Two days earlier, the task force had moved in favor of the European travel ban over the strong objections of Trump’s economic team. Now we came together to debate it all over again—only, this time, we were playing to an audience of one. I immediately thought the ban made sense, but to convince others, I had to appeal to their primary interest: the economy. President Trump believed that his policies had been the prime mover of the economic engine, creating the “best economy in the history of the United States.” It was going to be difficult to engage him on public health without acknowledging the economic impact. Consequently, I had to tie the two interests together, and how I united those strands would be critical.
To that point, my interactions with the president had been very brief and limited mostly to the formal meetings. Once in the Oval Office with the entire task force and various members of the president’s team of advisors, I wasn’t sure what to expect. I looked around the room. Everyone seemed comfortable. I wasn’t. All the reservations I had had about accepting this job were seated, with a few exceptions, around the room. I didn’t feel I was surrounded by enemies; I felt surrounded mostly by unknowns.
One known was this: this president wouldn’t have much patience for lengthy explanations or rationales. I would have to be on point and concise. I couldn’t do anything that would reveal my true intention—to use the travel ban as one brick in the construction of a larger wall of protective measures we needed to enact very soon.
The vice president opened by stating that the task force had agreed that this European travel advisory was necessary. The president took this in and then immediately, and perhaps predictably, turned to Steve Mnuchin and asked him for his thoughts.
I had come to see Secretary Mnuchin, Trump’s secretary of the treasury, and Larry Kudlow, his director of the National Economic Council, as the frontline players on the administration’s economic team. In addition there were the most important backbenchers, Marc Short, Stephen Miller, and the communications team at the Office of the Vice President, who, prior to my arrival, had agreed that the imposition of flight restrictions on China was warranted; now they didn’t see this to be the case with Europe.
Their reason? Secretary Mnuchin spoke for those opposed to the European travel ban. It would have a much greater impact on the U.S. economy and—left unsaid but clear—on the stock markets than the China ban had. He listed the reasons: With many more multinational businesses with offices in the United States, Europe, and the United Kingdom, many more people flew back and forth from Continental Europe. This could further cripple the airlines. I also heard talk about the effect on the gross national product numbers. Not just people, but cargo flew on those passenger planes. What was this going to do to the world’s supply chains? What would that mean for retailers and others along the way?
When Secretary Mnuchin was done speaking, the president turned to Bob, Tony, and me. Bob spoke first and in slightly more detail, elaborating on the points the vice president had made. He kept his focus on public health matters, making the case for why the travel ban was the right course to protect people. I made the same argument and noted that European cases were higher than China’s had been when the ban on visitors from there was imposed. I had a somewhat simplistic, but nonetheless viable, argument to counter that of the economic team: I always believed that the cost to human lives with this illness would be far greater than other costs down the road. If we limited the number of cases, if we mitigated against the virus in the short term, we could stabilize our hospitals sooner, save more lives, and immediately reduce these other, longer-term economic effects.
Outwardly, I was calm, but inside, my emotions were churning. I had that new-kid feeling again. Not only was I aware of how important this travel ban was to my plan to help save American lives, but I was feeling the pressure of having to disagree with one of the president’s most trusted cabinet members. Steven Mnuchin was articulate, logical, and brilliant. Over the last three years, he had worked side by side with the White House to improve the economy. I wasn’t lacking the courage of my convictions or my expertise. Still, in a high-stakes situation such as this one, who was saying something mattered more than what was being said. Mnuchin didn’t have a more valid argument than mine, but he had established credibility with the president that I lacked.
Mnuchin cut me off several times to rebut some of my points, but I kept my composure and carried on. I got the sense that he wasn’t used to anyone challenging his perspective. I felt satisfied that I had clearly communicated the China-then, Italy-now formula for decision making.
Bob and Tony backed up my additional points, which was key. We needed to be as consistent in our position as the economic team was united in theirs. The president then consulted with his security people, including Ken Cuccinelli of Homeland Security, who spoke of the logistical matters inherent in such a ban and pointed out that we would need considerably more personnel to enact the proposed measures.
At that point, the president looked around the room and then at his watch. “I don’t see anything that looks like consensus. Go into the other room. Figure this out and get to a point you can all agree on.”
An aide got his attention; it was clear we’d been dismissed.
I was dismayed but not surprised. On the one hand, I saw this as standard operating procedure, a kind of “tell me what I want to hear so I can do what I want to do and have justification for it based on your recommendation” scenario. On the other, I saw it as an approach that might work to my advantage.
Given how entrenched both sides were, true consensus was unlikely. Instead, I figured that we’d get to something more like capitulation. Some would concede, going along with the majority point of view simply because they knew that was what was being asked of them. Others would feel like they didn’t have much skin in the game in terms of what would be asked of the departments they represented. Some truly were conflicted and could be swayed.
I looked at it this way: If their concern over the economic impacts of the European travel ban was this high, how were they going to respond to the more extreme messages I planned to deliver in a few days? I really believed that what I was advocating for—my impending gambit for big-picture mitigation measures that would have us enacting more Italy-like measures—was a higher ground worth dying on. The travel ban was among the first steps up that steep hill. Retreat here, and it would make the upcoming struggle even longer and more difficult. I had the stamina to hold that ground, and Bob and Tony were with me.
After we reconvened in the Cabinet Room, I reviewed with them the most up-to-date data I had collected from Europe, South Korea, and China. Predictably, the number of domestic cases and fatalities was rising, but more important, in the two days since I’d presented on Monday, the cases were now (even with the extremely limited data reporting we had to work with) rising faster. Cases were essentially doubling each day, exhibiting the characteristics of exponential growth, a rate of increase that could be explained only by the underlying vast silent community spread.
Whether because of the dark picture my words painted or a lack of understanding of what I was arguing, in those early task force meetings, I saw a lot of distanced looks when I talked numbers and mentioned things like linear-versus-exponential growth.
Once I’d presented the data, the economics team pushed back again. They said the U.S. case counts were low and would stay low. They firmly believed the economic risks to the American public were far greater than the risks to their health. What I was presenting was theoretical, they said, based on assumptions I was making from Europe. America was different: We could do what everyone else had failed to do. We were better.
The discussion took on the form of a debate team meet: I see your incidence and fatality rates, and I raise you the GDP. America’s wealth and its collective faith, the economics team seemed to believe, would protect us. (I was grateful to my high school and the debate team training I received there for helping me sharpen my discourse and responses.)
Seeing this line in the sand drawn so starkly between the economy and public health so early in my tenure was as concerning as it was illuminating. Seeing who was on each side of that line and what their position was, I found beneficial. In theory, weighing the cost in human lives versus economic costs, and the downward spiral that poverty and a loss of livelihoods might bring, was germane when crafting a pandemic plan. But when it came to the crisis we were all now facing, I saw the economic consequences as a “tomorrow issue,” while human life was a “today issue.”
Steve Mnuchin spoke again. Much as I had done, he reiterated his most salient points. What he was forecasting could be potentially catastrophic to the economy as a whole. He wrapped up fairly quickly, letting the authority he brought to the room do a lot of the talking for him. It was as if he were saying, Whom are you going to trust? Someone who’s helped navigate this country into such a strong economic position, or her?
When Steve was done, I took a moment.
As a woman, I was used to certain adjectives being used to describe my aggressive pushing for lifesaving policies—most not complimentary. Behavior in men that was described as “focused” or “driven,” became “bitchy” when I exhibited it. Why is that bitch so aggressive and so direct? Never: Why is she direct and authoritative regarding actions to save human lives? Again, a man in my current position would have been viewed as a visionary, “willing to take the hard line to save lives.” They would have been applauded. I was always disparaged. I had experienced this time and again over the decades—and to be honest, it hadn’t improved that much anywhere in the world.
As evenly as I could, I continued: “I showed you my data supporting my position. I showed you how this could overwhelm our hospitals.” I looked around the room. “I understand. I’ve painted a disturbing picture. But it’s a realistic one, built using the best data available, to make projections based on what’s happening in the real world right now.”
I paused, before adding, “Where is your data supporting your dire economic predictions?”
No one interrupted me. No one countered my last point. But no one looked very happy or relieved. An uncomfortable silence lingered; a line had been drawn. At that moment, I couldn’t see how deep and broad that line would become. Those early months would come to be defined by the medical professionals on one side of the divide and the economics team on the other. What on the surface looked like agreement was, for some in the room, a call to action.
That moment marked the last time the White House senior advisors or components of the economics team would show up to a meeting like this without data. From that day, they would begin, and continue, to bring forward “alternative” data, analyses, and projections. This was not Secretary Mnuchin or Larry Kudlow, but others on the economic teams. Much like the CDC, they’d find or create models to back up their previously drawn conclusions. Like the CDC, they were working backward from a premise. I was looking forward, using data to clarify what the future held.
I’d asked where their data was. I wouldn’t ever get it, but I would eventually receive a lot of analyses of the data I had presented—much of it distorted or inaccurate, but it had the appearance of being factual. These distortions would become part of their standard operating procedure: Find some way, any way, to use figures, no matter how inaccurate, to support their conclusion. Interpreting data would become the new battlefield. While making the right policy decisions mattered deeply to me, using the right data to arrive at the right conclusions mattered just as much. In my mind, the two were inextricable. I operated not on gut checks, but fact-checks.
At that meeting in the Cabinet Room, I watched as clusters of advisors from both sides formed huddles and then broke up, heads inclining toward and then away from one another. I don’t know if it was immediately after this meeting or later that Tony and I earned the nickname “Dr. Doom.” Left unanswered was how my doom regarding human lives was any different from theirs predicting dire economic consequences.
Ultimately, on the question of the European travel ban, we didn’t vote by secret ballot, we didn’t do a show of hands, we didn’t reveal our position by voice acclimation. We shuffled papers, clicked pens, and scooted back chairs. We were heading back into the Oval. We’d reached “consensus”: we were recommending the ban. I did a quick review as I made my way back to the Oval Office: Derek Kan, of OMB and the Council of Economic Advisers (CEA), was very much on the economic supremacy side of the argument, but I sensed that Mnuchin and Kudlow, despite the clear economic impacts, were listening to the health arguments. (They did this throughout the remainder of the pandemic response. I came to see them as distinctly different in this regard from the rest of the CEA members.) I had a good feeling that two other key influencers on the president’s team seemed to get the “seriousness” argument. Marc Short had the vice president’s ear, but Jared Kushner and Hope Hicks had that most elusive of things: the president’s attention.
Knowing who could best champion specific elements of the Covid-19 response would be key to navigating the White House. Even in those first few days, it was clear that the president was constantly soliciting opinions from his senior advisors, but also from his outside influencers and from random people who crossed his path. I was not, and would not, be present for the majority of these interactions, and as such, I needed to ensure that someone in the room was armed not just with the data, but with the correct interpretation of the data.
Jared was one of the key people I needed to sway. I hadn’t spent much time with him yet, but he was present in the Oval Office meeting and the one in the Cabinet Room. Based on his brief interactions with me, I suspected that the Italy scenario as a predictor of the United States’ future had registered with him on some level. I watched him from across the large table in the Cabinet Room, when I and others were talking. He was tracking the conversation and seemed concerned when I talked about the frightening scenario on the horizon.
As we filed back into the Oval Office again, Matt Pottinger waved me over, pointing to the seat he had placed immediately in front of the Resolute Desk. I took the seat, and he retreated to one of the yellow couches. He wanted me there, as visible as possible to the president, as a reminder that there were two sides to the argument and that public health, symbolically and practically, needed to be front and center.
In the end, there wasn’t much reason for me to be placed there now, because with very little fanfare, the vice president promptly informed the president that we’d reached consensus. The European travel ban would be announced.
The president nodded, and we all left the room.
GETTING THE TRAVEL BAN through was a crucial first test of my data-driven approach. That it worked would, I hoped, make the end-of-the-week pitch for our version of a flattening-the-curve-to-protect-hospitals “shutdown” easier. But as the travel ban debate had shown, we were going to have to overcome resistance, primarily from a specific wing of the economic team, especially the Council of Economic Advisers. If I read the room right, both Secretary Mnuchin and Larry Kudlow were concerned about the potential of SARS-CoV-2 wreaking economic and public health havoc across areas of the country. The travel ban would impact a relatively small portion of the population, along with, primarily, the airline industry and associated businesses. It was unclear how the economic team would respond to measures affecting a far greater portion of the population and the economy. For this, it wouldn’t be enough to point out the seriousness of the pandemic and the need for action; we would have to develop a specific set of steps to recommend.
On Monday and Tuesday, while sorting through the CDC data issues, we worked simultaneously to develop the flatten-the-curve guidance I hoped to present to the vice president at week’s end. Getting buy-in on the simple mitigation measures every American could take was just the first step leading to longer and more aggressive interventions. We had to make these palatable to the administration by avoiding the obvious appearance of a full Italian lockdown. At the same time, we needed the measures to be effective at slowing the spread, which meant matching as closely as possible what Italy had done—a tall order. We were playing a game of chess in which the success of each move was predicated on the one before it. We needed to ensure the virus didn’t spread across the country. We had neither the hospital personnel, ventilators, nor the supply capacity to endure that type of surge across the country in metro after metro. With our response so far behind the virus, with no therapeutics to save the sick, we would have to do something drastic.
By Tuesday, March 10, we had initial drafts of the guidance and easy-to-comprehend slides to share with the nonmedical members of the task force. Ultimately, based on the feedback we received, we’d either share them as is or revise them before I met with the vice president in advance of presenting them to the full task force on Sunday. For the rest of the week in our task force meetings, I slipped in oblique references to future recommendations. For example, I’d present a graph that read, “Encourage your employee to . . .” followed by suggestions about how to keep the workplace safe, ratcheting up the urgency of my language incrementally. Bit by bit, I moved the pieces on the board in advance of delivering the full flatten-the-curve message. I wasn’t making slashing attacks with bishops or rooks. I was subtly moving my pawns, not wanting to put anyone in a defensive posture too soon.
Knowing the objections to the flatten-the-curve measures that were sure to come from the economics side, we decided to take these on directly, highlighting “preemptive” and “low-cost” interventions. By emphasizing “preemptive,” we’d send an important signal: some states still had time to prevent community spread. The “low-cost” interventions would be social distancing and enhanced hygiene vigilance. The first cost nothing; the second would involve the purchase of sanitizing and disinfecting agents. If the cost to the public was low, and if the behaviors were ones they typically engaged in, the public would be more likely to respond positively. The sooner they adopted and stuck with these measures, the sooner businesses could fully reopen. It would be a win for the “consumer” and a win for business owners.
To that end, we also made the difficult and significant decision not to include a specific reference to wearing masks. Without the full support of the CDC on nonmedical-grade masks, and with the administration’s ongoing resistance to their use, I couldn’t afford to have the entire mitigation program meet with strong opposition because of one provision. I was okay with this omission because, if the public followed the rest of the guidance, they would be staying at home more, reducing viral transmission opportunities. In retrospect, in focusing on the needs of the many, this safer-at-home approach put essential workers at greater risk. Either when delivering to homes or still encountering customers in stores, they faced a greater risk of exposure and they weren’t protected. This still haunts me. Four weeks later we were able to put the importance of masking in the opening guidelines. But for that four weeks, we put Americans at substantial risk.
I organized the presentation around three key areas: work, school, and family. These didn’t necessarily represent all of my priorities. Opening with “work,” I felt, would appeal to the economic team. Getting them started off on the right foot would make the next two steps easier. We’d highlight how we could keep the economy running while ensuring the safety of those who got the pistons pumping. If business owners acted proactively and got positive results, then nothing would feel punitive.
School guidance was second on the list, for reasons both rhetorical and practical. I wasn’t sure how many in the room had school-age children or grandchildren, but it was likely many. Keeping students, and the teachers for whom school was a workplace, safe was essential. This would lessen the impact on parents, allow them to continue to work, and maintain that cherished economic momentum. The medical side of the task force had to do triage here as well. Stabilize the situation first so that, downstream, we wouldn’t find ourselves in a more devastating crisis resulting in enormous loss of life. Fortunately, the European data on the virus up to this point had shown that children and young adults did not seem to become as seriously ill as older adults.
The last of the three, and the one I personally prioritized, was family. Because data had shown that seniors and those with underlying medical conditions were particularly vulnerable to being more severely affected by the disease, and were dying from it at a greater rate than young people, I used more direct language in our guidance. I sensed that American seniors would recognize their vulnerability and would be more willing to mitigate and protect themselves than younger people. I was very concerned about multigenerational households, like the one I lived in. Millions more of them existed and housed more people than care facilities. Within such households, the interplay between the unknowingly infected and highly contagious and those most susceptible to severe disease and poor outcomes produced the greatest likelihood of the most dangerous consequence of silent spread: hospitalization and death.
While I was writing the mitigation guidelines to present to the task force, my daughter and I continued to enact the practices we’d established weeks ago in the home we shared with my parents, who were ninety-one and ninety-five years old, and my grandchildren, both toddlers. My daughter also had someone coming in to provide child care. The weekend I returned from Africa, everything had changed. Given my fears about asymptomatic spread and the potential for my grandchildren (the two-year-old was in preschool) to bring the virus home and infect their grandparents, the entire household went into full lockdown. No one in, and no one out. Both sets of grandparents stopped their visits with the grandchildren. My daughter canceled child care, and the two-year-old stopped going to preschool. Without any explicit instructions, my daughter researched how to support the family with food and supplies and set up the most comprehensive supply chain to the house I had ever witnessed, all while still working full time from home.
Toilet paper, paper towels, and disinfectants were delivered to the house; we were dependent on her supplies throughout the pandemic. The same alert went out to my brother, his children, and other family members. We had vulnerable adults at risk in every household.
The guidelines that came out of the task force were meant to address another audience: the CDC. To break free from the constraints the CDC had placed on itself with its myopic flu model response, which had minimized the notion of silent spread, we couldn’t just call them out. Despite our differences in approach, we needed them. To that end, many of the guidelines we incorporated were based on CDC best practices. Undercutting the CDC at this stage wouldn’t have done anyone any good. The agency was sticking to its guns, and so was I. Yes, silent asymptomatic spread was a significant contributor to the outbreak, and all the advice we were giving to the American public spoke to that point, but without mentioning the concept by name.
While the guidance was written to make it hard for anyone—the CDC or the economics wing of the task force—to object, we still had to anticipate future greater resistance. I was already thinking this: Because we were dealing with a large number of political figures on the task force (essentially, everyone except Tony and me), in the White House, and in the administration throughout the many agencies, we knew we couldn’t call any measure a “regulation.” The Trump White House had spent the last three years eliminating so many of them in so many areas where it believed regulations interfered with economic progress. While rules and regulations were absolutely what the present crisis called for, and would help force the states to adopt these measures, the presence of the word regulation in the guidance would immediately have ended all our shutdown efforts. The guidance would never have made it past the White House gatekeepers. We therefore constantly emphasized that we were making “recommendations,” not establishing rules. This principle would guide our approach and our messaging within the task force, with the administration, and with the public. At this stage, we used the word encourage in the heading for each of the three main areas of focus.
The key was to establish a serious tone and let the states use the guidelines to justify more aggressive action. The White House would “encourage,” but the states could “recommend” or, if needed, “mandate.” In short, we were handing governors and their public health officials a template, a state-level permission slip they could use to enact a specific response that was appropriate for the people under their jurisdiction. The fact that the guidelines would be coming from a Republican White House gave political cover to any Republican governors skeptical of federal overreach and would lead to most states’ implementing clear regulations themselves.
With the benefit of almost two years’ worth of behavioral data, it’s easy to look back now and read a certain amount of naïveté in our belief that people would prioritize the health of others over their own personal liberty. Of course, we anticipated that some people would resist, but we strongly believed that most people would want to keep others in their community safe by doing the right thing en masse. Early data from Europe showed widespread compliance, with interaction with mobility decreased across the continent by 75–95 percent. The tricky thing was finding agreement over precisely what the “right thing” was. Unfortunately, we knew that, at some point, we would have to account for how politicized and divided the country had become. At that early stage, though, we had to focus our energies on how politicized the White House bubble was.
MY NEXT MOVE IN the ongoing chess game was to quietly convene an ad hoc group at my home. On Saturday, March 14, Joe Grogan, Steve Redd, Tony Fauci, and Tom Frieden joined me. Olivia Troye showed up unannounced. At the time, I didn’t think much about this, but clearly, she had come under the direction of Marc Short to see what I was doing.
The objective of this meeting was twofold: The first was to refine and finalize the presentation I’d be making the next day at the task force meeting. The second was to position ourselves to block any of the president’s escape routes. If all our pieces were aligned properly, he’d have no choice but to agree to our flatten-the-curve measures. A few of our moves would be dictated by the schedule. On Sunday, I would meet with the vice president before the afternoon’s task force meeting. In that private session, I hoped to get him on board with the recommendations we were drafting. With Vice President Pence in position, the president’s options would be even more limited. Going against the man he himself had put in charge of the task force wouldn’t look good, and the media were sure to get wind of how things played out. If I could get all those pieces in place, we would get to step one of a “circuit breaker” to flatten the curve, prevent the virus from spreading across the United States, and save as many lives as possible.
I was fairly certain the vice president would go along with what the task force recommended, but the president was always going to be a wild card. For this reason, I had invited task force member Joe Grogan to join us at my home. A longtime member of the administration and an important conduit to the president, Joe was a former member of OMB and the current director of the Domestic Policy Council, a key group in determining whether our recommendations could be enacted. He was therefore a critical lynchpin in getting my strategic plan approved. If Bob, Tony, and I could present a unified phalanx of support for the measures, Joe and, to a lesser extent, Olivia Troye, would take this positive show of strength to the Oval Office, to Marc Short, and the vice president. I’d seen the president’s desire for consensus before. Demonstrating that we had it would go a long way toward convincing him to approve our recommendations.
I was also hoping to leverage Joe’s prior “We will own it” statement to my advantage. I counted on him telling the vice president and president that it was better to act now than endure the dire consequences of inaction, when the blame would rest squarely on the president and his advisors. Joe would be the key to these discussions.
The trick was getting the medical side in agreement on silent spread; I planned to have Tom Frieden help bring the CDC along. Like me, the CDC wanted to do everything to stop the virus, but the agency needed to align with us on aggressive testing and silent spread. Those in my camp had nuanced sensibilities regarding data and modeling; Tony’s preferences were very much on my mind. At that point, the president trusted Tony, and to put it bluntly, Tony didn’t put much faith in predictive models because they were too dependent on the initial assumptions made to create them. He was right. Baseline assumptions and, consequently, what they predict can be too open to subjective perception. Tony absolutely believed in data, but he had a strong preference for quality-controlled data from well-designed clinical trials. With no such trials in place, Tony had little faith in projections beyond what the data was saying about the present moment. As a scientist, Tony very much wants to see substantiated, validated facts first, so I planned on leaning hard once again on the quality of the data I had from Italy.
During the course of the week, I’d continued to be in touch with Tom. If I could get him to agree that these shutdown-like measures were necessary, other CDCers would fall in line. While he still wasn’t fully committed to backing my 50 percent asymptomatic figure, he understood that the nation, with the administration leading the way, needed to take immediate action. What was most important was flattening the curve. With this virus, we were way past proactive mitigation, as was Europe. At this point, getting the doctors, including Tom and Tony, to be in complete agreement with me about asymptomatic spread was slightly less of a priority. As with masks, I knew I could return to that issue as soon as I got their buy-in on our recommendations. For now, I was focused on marshaling support from the public health side for this de facto shutdown.
The setting for this meeting, my home, was far less formal than the conference rooms at the EEOB or the White House. Though the tone was different, informal and interactive, the intent was similar: to exchange information with Tom and Tony and make sure I included their insights in the final guidelines. As with the travel ban discussions, I was prepared with data and graphics. I went through our guidance recommendations, beginning with the workplace category.
I expected some pushback from Joe, given that this was the most sensitive area for the administration. There were a few chuckles at the bullet point that read “Consider adjusting or postponing large meetings or gatherings.” At one point, I saw Joe nod his head and heard him say, “Seems very commonsense.”
“That’s the point,” I said. “Commonsense. Actionable. Letting every American know what part they should play.”
As I expected, Joe asked Tony, the White House medical advisor, to share his perspective. Essentially, Tony said the projections we’d based on the European data were likely to be true: We were past the point of containment. We had to limit people’s exposure to the virus and do exactly what flattening the curve is intended to do.
One of the key decisions made at the meeting was on the fifteen-day time frame during which we’d ask all Americans to do their part. Instead of just asking people to be vigilant during the flu season and to cough and sneeze into their elbows instead of their hands, we’d ask for other behavioral changes more in line with silent spread mitigation. To arrive at “fifteen days,” we had relied on the CDC’s estimates of this virus’s full transmission cycle (from inhalation of droplets or airborne particles to viral shedding to infectivity), a maximum of fourteen days. This was the justification for the exposure and quarantine times being used around the globe. Fifteen days was the minimum required to have any impact. I left the rest unstated: that this was just a starting point.
With the presentation finalized and the meeting ended, I tried to get as much rest as I could before my final presentation to the vice president. I had shown him an earlier version and planned to present the final one to him prior to the task force meeting the next day, Sunday.
When I met with Vice President Pence before the task force meeting I brought along all the final graphics I wanted him to present to the president. As in chess, it’s helpful to know your opponent’s tendencies, and the president liked visuals. I also factored in how Vice President Pence was likely to react. A former governor, he was predisposed to believe that it should be up to the states to take whatever measures they deemed necessary. They should decide whether to seek the support of the federal government. That’s where my “recommendations” and not “regulations” move came into play.
Knowing the vice president’s immense respect for governors and their leadership independent of political party, I had slightly altered my approach in my presentation to him. I knew that, when communicating our guidelines to the president, the vice president also would have to walk that fine line between nudging and pushing, making it seem as if our great idea had come from someone other than the task force. The psychology involved in this was maddeningly delicate.
At the conclusion of our meeting, I felt Vice President Pence understood the gravity of the situation and the urgency of what we were suggesting. Acting now was critical. The vice president and others needed to believe this was consistent with federalism and that the governors would “own” the final decision making. I believed in that moment that we had obscured the larger truth—that the White House was essentially recommending a flattening-the-curve “shutdown” to states with significant viral spread and extreme reductions in mobility and gatherings in other states to prevent surges there. After all, once the White House put out any serious recommendations, the governors and the American people would see it as open acknowledgment that what we were facing was serious and needed to be addressed immediately.
I wanted immediate confirmation that our plan was a go, but I wouldn’t be part of whatever meeting was held to inform the president. It was as if I had set up the chess board with a checkmate in three moves only to have another player edge me out of my chair to execute the final move, presidential approval.
I spent an anxious few hours trying to distract myself while the vice president met with the president—until I received an email from Jared Kushner that we were to proceed as planned. The vice president and Jared had gone to President Trump and gotten the green light. Somehow, it felt anticlimactic, but I told myself not to look a gift horse in the mouth: the White House would post “The President’s Coronavirus Guidelines for America” on its website, and the following day, President Trump would announce the campaign, which was eventually given the name “15 Days to Slow the Spread.”
It didn’t take long for the cost of the disconnect between the task force and the CDC over silent spread to be laid bare. Late in the evening on Sunday, March 15, I received an email from Olivia Troye. She forwarded a string of emails in which a member of the administration expressed concern that the CDC had independently issued directives regarding mass indoor gatherings: Their recommendation was that they be limited to no more than fifty people, while the recommendation in our presentation had capped the figure at ten people.
This was exactly what I didn’t need—neither the mistiming of the message nor the message itself. Ultimately, cross-household gatherings needed to be stopped entirely, households isolated from other households to prevent further spread. Limiting gatherings to ten had been a first step and was consistent with my spoonful-of-sugar approach. Starting at fifty, as the CDC was advising, would require many more moves to get to zero. All week in the task force meetings, with the CDC’s Bob Redfield present, we’d talked about that need and that number: ten. I’d even shared with Bob the proposed bullet points containing that figure. He hadn’t raised any objections, either in our meetings or privately with me, to using ten as the upper limit. This fifty figure must have emanated from the CDC rank and file, and Bob was probably caught off guard by it, too.
Of all things to suddenly drop through the roof, this discrepancy in numbers was the last thing I expected. By using fifty as the upper limit for gatherings, the CDC was giving those in the White House who already thought I was overreacting the exact ammunition they needed: See, even the CDC doesn’t see the virus as that serious a threat.
And that’s exactly what happened. Both behind the scenes and in direct emails, Marc Short of the Vice President’s Office pointed out the fifty-versus-ten conflict. He wondered why the White House plan was not aligned with the CDC recommendations. He also asked if there was a scientific basis for fifty versus ten, or even five? He was trying to flip the script on my travel ban message to the economics team: Show me the numbers. For people like Marc, the discrepancy was about how serious this viral outbreak was, and he was implying that I was exaggerating the seriousness by a factor of five. Was everything I was saying, every figure I was citing, similarly off by that factor? What if it were off by more?
The real problem with this fifty-versus-ten distinction, for me, was that it revealed that the CDC simply didn’t believe to the degree that I did that SARS-CoV-2 was being spread through the air silently and undetected from symptomless individuals. The numbers really did matter. As the years since have confirmed, in times of active viral community spread, as many as fifty people gathered together indoors (unmasked at this point, of course) was way too high a number. It increased the chances of someone among that number being infected exponentially. I had settled on ten knowing that even that was too many, but I figured that ten would at least be palatable for most Americans—high enough to allow for most gatherings of immediate family but not enough for large dinner parties and, critically, large weddings, birthday parties, and other mass social events.
The number mattered also because of this: When Americans heard “50,” I knew they would round up to 100. With the CDC guidance, large weddings, funerals, and birthday parties would proceed unchanged. If they were told “250,” they would hear “500.” Similarly, if I pushed for zero (which was actually what I wanted and what was required), this would have been interpreted as a “lockdown”—the perception we were all working so hard to avoid.
In response to the White House query about the “correct” number, Tony couldn’t commit. Privately, he wrote to tell me that he didn’t want to publicly contradict the CDC, but that he also believed fifty was too high. As he told me, he couldn’t give Marc Short an answer about the scientific basis for any number the CDC put out; that wasn’t the task force’s call to make. He wondered whether a call to Bob or Anne Schuchat at the CDC was in order.
This wasn’t a case of passing the buck; it was a function of Tony’s political sensibilities. He didn’t want to undercut Bob’s or the CDC’s already shaky authority. As scientists in a task force outnumbered by politicians, economists, and bureaucrats, we needed to present a more or less unified front—otherwise, a strategy of divide and conquer could have come into play. The CDC had erred in coming out with its announcement, but this fifty-versus-ten dispute was merely a microcosm of the fundamental disagreement among scientists over the nature of the virus’s transmission. We could agree neither on silent spread nor on how large a spread people could put out for friends and family. Surprising as it might seem in hindsight, this was a rare case of the White House taking the more cautious road than the CDC.
We were so consumed by the work we were putting in to develop the guidelines that became part of the 15 Days to Slow the Spread campaign that it was only after the president’s press conference on March 16 that something occurred to me: When we’d argued in favor of the European travel ban, we’d engaged in lengthy debate, with President Trump sending us away to achieve consensus the way a judge might instruct a hung jury to keep at its deliberations.
In contrast, for as much effort as we had put in and as much anxiety as I’d felt over 15 Days to Slow the Spread, we’d received little to no pushback that I could discern from the CEA or the other economics-minded factions in the White House. I thought again of Joe Grogan’s comments about “owning” this. It was possible that the president and his advisors saw the fifteen days as more of a cover-your-ass move than an effective means of combating what I and others saw as the most serious public health crisis of our lifetimes. The administration might have been worried about owning the potential failures, but its members, at that time, didn’t seem overly concerned about owning the responsibility for reducing the scope of the crisis.
I wondered if I’d oversold the notion that the guidelines would be low-cost, low-impact. Had we not made it clear enough that this was a serious matter? With whom had the president consulted before agreeing to announce the guidelines? If there was no infighting or debate, did that mean there had been complete agreement—or was it an indication of indifference? Did the president know that the practical effect of the guidelines would be that governors would begin to shut down their states?
Indeed, following President Trump’s announcement of the guidelines—almost on cue—the recommendations served as the basis for governors to mandate the flattening-the-curve shutdowns. The White House had handed down guidance, and the governors took that ball and ran with it. Based on the weekly governors’ call and my other interactions with them, I could tell they’d been looking for the White House to take the lead in letting the American public know how serious the situation was. With the White House’s “this is serious” message, governors now had “permission” to mount a proportionate response and, one by one, other states followed suit.
California was first, doing so on March 18. New York followed on March 20. Illinois, which had declared its own state of emergency on March 9, issued shelter-in-place orders on March 21. Louisiana did so on the twenty-second. In relatively short order by the end of March and the first week of April, there were few holdouts. The circuit-breaking, flattening-the-curve shutdown had begun.