The Food and Drug Administration’s cumbersome and ossified approval process for drugs and tests stands out as a major cause of the federal government’s failure to quickly and effectively respond when the the COVID-19 virus first attacked. And one thing upon which all policymakers agree is that abundant testing—both for the presence of active infection and for evidence of previous infection and possible immunity—is crucial to ending this crisis.

As I have written here, on February 29 the FDA began to loosen these regulations, particularly regarding approval of tests, and allowed academic and commercial labs more freedom to produce and distribute them without having to follow normal FDA approval protocols. Finally, on March 16, the FDA delegated authority to the states to approve COVID-19 tests that may be used within their borders. The FDA should have also granted states this same authority to approve drugs that may treat the infection.

While the FDA has approved only a few antibody tests (which provide evidence of previous infection), many have been approved by state governments and have already been deployed. For example, an antibody test manufactured by California-based Premier Biotech has been used by researchers at Stanford University and the University of Southern California to detect large segments of the populations of Santa Clara and Los Angeles counties who have already been infected by the virus.

In exercising the authority delegated to him by the FDA, Maryland Governor Larry Hogan announced yesterday that he purchased 500,000 tests from South Korea, a country that set an example of efficient and accurate testing when the virus attacked. The governor set the wheels in motion to purchase the tests from South Korea shortly after the FDA delegated authority to the states in mid-March. It culminated in a chartered Korean Airlines flight that carried the test kits to the Baltimore-Washington International Airport yesterday. The governor plans to deploy these kits to reach his state’s goal of testing 10,000 Marylanders per day.

Ironically, perhaps due to nationalist impulses, President Trump criticized Governor Hogan’s move. The president contended the governor should have used the tests available at federal laboratories—even though the governor was acting in accordance with administration policy. This was not the first time during this crisis that the president or his administration have transmitted mixed messages to the public.

One of the first questions that should have been asked in late February when it was discovered that the de facto CDC-monopoly on COVID-19 testing was a fiasco was: Why not use the tests already successfully in use in other countries? As I wrote last month, a good policy reform that should emerge when this crisis passes would be for the FDA to grant reciprocal approval to all drugs and tests that are already approved and in use by a list of similar countries—and not just in time of emergency. That way the people won’t get deprived of drugs and tests to which they have a right.

In the meantime, states should continue to exercise their newly-delegated power to decide on the tests that may be run within their borders and resist relinquishing this power once the crisis is over.

Did impeachment distract President Trump from the looming threat of the COVID-19 pandemic? That’s the story conservative pundits and pols have been trying to sell for over a month now. Presidential pal Sen. Lindsey Graham (R‑S.C.) joined the chorus last week, though in Graham’s version, it’s “Democrats and the media” who lost focus. (No doubt Graham didn’t want to get crosswise with Trump, who insists his pandemic response has been aces.)

The problem with the distraction narrative is the total lack of evidence for it. It’s a bad argument, and, in most cases, badly made.

Trump-friendly Washington Post columnist Henry Olsen was first out of the gate, with a March 23 piece titled, “Let’s be honest. Impeachment hurt Trump’s response to coronavirus.” In it, Olsen can’t seem to avoid stepping on his own points, sometimes in consecutive sentences. “Despite the near certainty that Republicans would not vote to convict the president,” he writes, the Democrats and the press forged ahead; “As a result, the White House was focused on addressing this threat to its survival.” Wait, what?

Anyway, Olsen continues, “it is extraordinarily difficult for politicians to foresee an event unprecedented in modern times,” and no Western democracy did much better than the United States. OK, but then why would we expect a distraction-free Donald Trump—if such a thing were possible—to have mounted a crack response?

The NY Post’s Miranda Devine offers a portentous timeline that’s supposed to illustrate the “dire distraction” impeachment represented. Things get a little disorienting by January 31st, when according to DeVine, “Trump closed the US border to China.”

Geographical oddities aside, that chronology should tell us something. The restrictions on travel from China, Trump’s boldest early move to stop the spread, came during the impeachment trial, about a week before acquittal. Porous though the limits were, they likely bought the U.S. valuable time to prepare.

How did the president spend that time? Ignoring warnings by his own staff, trying to jawbone the stock market, and—for a full month after impeachment was over—banging on about how COVID-19 was basically the flu.

What was it that was supposed to be stealing Trump’s “focus” from February to mid-March? Post-impeachment trauma?

You could make the case that Trump’s post-acquittal vendetta against everyone who crossed him has been the bigger diversion. The president embarked on a “payback tour” coming out of the Senate trial, and, by all appearances, it’s not over yet. Earlier this month, Trump fired Michael Atkinson, the Intelligence Community’s Inspector General, as retaliation for his role in the events that led to impeachment. Meanwhile, the Senate Homeland Security Committee is forging ahead with its investigation of Hunter Biden and Burisma. Is score-settling distracting them from Coronavirus response—or is it the other way around? Per the committee’s chairman, Trump loyalist Sen. Ron Johnson (R.-WI), “Coronavirus response has ‘hampered’ Hunter Biden investigation.” Priorities!

For what it’s worth, in a “fact check” published Friday, USA Today stresses that, during the key post-impeachment period from February to mid-March, President Trump had the time to play a whole lot of golf. I’ve never been a fan of this genre of presidential criticism, however, and it has its limits even here. Given this president’s penchant for larding the daily Coronavirus briefings with misinformation and autocratic threats, we might be better off if he tagged in Pence and Fauci and hit the links instead. 

President Trump announced last night that he would “temporarily suspend immigration into the United States” to stop the spread of COVID-19. While the details of this proposed executive order have yet to come out, we can say with confidence that the order will not help the pandemic response. Cato’s research over the last couple of months has shown why:

1. It’s based on a misconception: As my colleague Alex Nowrasteh explains in this post today, as seen in Figures 1 and 2, there is no correlation between immigrant share of a county’s population in the United States and its rate of cases or deaths from COVID-19 controlling for population density. Ultimately, viruses will spread faster where people are bunched together regardless of where they come from.

2. It’s not backed by research: As I have explained in this literature review, the epidemiological research shows that pandemic travel bans are ineffective at stopping the spread of disease. In particular, the “research also indicates that there is no benefit to international travel restrictions once an outbreak has already become an epidemic inside the destination country.” Table 1 below comes from a Proceedings of the National Academy of Sciences paper comparing the results of different interventions on different types of viruses (R₀ refers to how contagious the disease is) after an outbreak starts in the United States, finding that long-distance travel restrictions do nothing whatsoever to prevent the spread. The limited COVID-19 research so far shows much the same thing, as Alex has shown. A virus spreads among citizens just as fast.

3. It’ll harm first responders. As I explain in this post, immigrants are disproportionately involved in providing essential services during the pandemic. It makes no sense to keep out workers who are helping keep America running. Foreigners have already suspended nonessential travel here, but as Figures 1 and 2 show, the ones who are here are disproportionately involved in industries like health care and agriculture (the post has numerous other examples). Many are also working for companies developing vaccines and treatments for the virus.

4. It’s largely redundant. The Trump administration has already “suspended” nearly all immigration to the country by stopping almost all visas from being issued to noncitizens, as I explain in this post detailing all the actions that the government has taken on immigration. If immigrants cannot receive visas, they cannot travel here. But this is counterproductive if they are essential workers. So far, the government has carved out only a few narrow exceptions for health care and agricultural workers, as well as Canadian and Mexican essential workers, so it remains to be seen if this order will exacerbate this issue.

The United States needs no formal order for immigration to naturally contract. In 2008, at the onset of the last recession, more immigrants left than entered the country. The number of requests for temporary workers plummeted. This will certainly happen again if this recession persists, but the government shouldn’t intervene to stop employers from hiring people that they need to keep the essential economy going.

Late on Monday night, President Trump tweeted that he will temporarily suspend all immigration to the United States to protect from the “attack from the Invisible Enemy,” COVID-19. Implicit in his tweet is that immigrants are spreading COVID-19 in the United States. The first part of this post shows that there is no relationship between COVID-19 cases or deaths at the county level and the share of the population that is foreign-born in each county. The second part explains our data and methods for the regression. The last part discusses the implications.

No Relationships Between COVID-19 and Immigrant Populations

The rate of COVID-19 cases and deaths by county in the United States is not correlated with the share of the population that is foreign-born. We ran two cross-sectional regressions that are graphically described in each figure below. Figure 1 shows that there is no relationship between the rate of COVID-19 cases by county and the immigrant share of the population in those counties. Figure 2 also shows no statistical relationship between the rate of deaths from COVID-19 by county and the immigrant share of the population. The numbers in Figures 1 and 2 are corrected for population density and state fixed effects (explained in the Data and Methods section below).

In both regressions, the coefficients for the foreign-born population share at the county level are both small in magnitude and statistically indistinguishable from zero (Table 1). In other words, the results are statistically insignificant. Rather, the most predictive variable in each model is a county’s population density, which is statistically significant at the 0.1 percent level in each regression. Since there are dense counties with disproportionately native-born populations and dense counties with disproportionately foreign-born populations, it was important in each regression to control for that variable to specifically see how immigrants were related to COVID-19 and because population density is a risk factor for the disease.

Data and Methods

The data on the county-level COVID-19 cases and deaths comes from The New York Times. These data list the cumulative number of COVID-19 cases and deaths by county by day and are current as of April 19, 2020. The share of the foreign-born population by county comes from the American Community Survey (ACS). We use the most recent 2014–2018 ACS 5‑year pooled estimates, since the 5‑year estimates provide estimates of the foreign-born population for all counties in the United States (single year estimates are only available for counties with populations of 65,000 or greater). The resulting dataset is a cross-section of all U.S. counties in the 50 states and the District of Columbia with a total of 3,142 counties and county equivalents.

We run simple cross-sectional regressions that plot the immigrant share of a county’s population on the X‑axis and the COVID-19 death rate or case rate per 100,000 logged on the Y‑axis. We control for county population density, as measured by the number of residents per square mile per county, because it is a key risk factor in the spread of COVID-19. Data on land area by county come from the Census Bureau 2018 Gazetteer files.

In each regression, the response variable is the natural log of the COVID-19 incidence or death rate per 100,000 population (with 1 added to avoid zeroes) and the explanatory variables are the foreign-born share and the log county population density. Since many states implemented mandatory stay in place orders to curtail the spread of COVID-19, we include state fixed effects to capture state-specific factors and compute heteroskedasticity robust standard errors that are clustered at the state level.

Discussion

The cross-sectional results above are correlations and not causal in nature. They are simple and should be taken with a grain of salt, especially so early in the pandemic. However, the results suggest that the share of a county’s local immigrant population does not accelerate the spread of COVID-19 across U.S. counties. Of course, we regressed a measure of the stock of immigrants in the United States and not the flow. The flow of immigrants is what President Trump’s executive order will stop (if it does anything), but those immigrants will flow to counties of the United States where immigrants already live. Since they’ve been flowing there since COVID-19 jumped to humans and there is no relationship between the immigrant share in those counties and COVID-19, the above regressions do help peel back the fog of ignorance.

Patient Zero, the first known person to have COVID-19 in the United States, returned from visiting family in Wuhan, China on January 15, 2020. He came down with a fever on January 19^th and immediately went to a doctor’s office. Details about this person are not available, but since he “returned” to the United States it’s fair to say he probably didn’t get sick on his first trip here. According to the available evidence, a new immigrant didn’t bring COVID-19 to the United States.

The federal government has the legitimate power to restrict immigration or other travel across borders to limit the spread of serious contagious diseases and to protect public health. However, blanket bans like those imposed by the administration in recent months and those coming on April 21 are akin to closing the barn door after the horse has escaped. Most research on travel bans in response to pandemics finds that they don’t limit the spread of diseases, in part because they are always imposed after the disease has spread. At most, a reduction in travel from China might have delayed the onset of a pandemic for a few weeks after Trump imposed a virtual ban on travelers and immigrants from China on February 2, 2020. But further immigration bans now will have no effect.

The government should effectively use its power in cases where it can and should legitimately restrict immigration further. But Trump’s order is more for show as “the government has suspended nearly all legal immigration and travel to the United States” already, according to our colleague David J. Bier. Quarantines for new immigrants and travelers make sense. They could be carried out in either in their home countries or once they arrive here in many of the vacant hotels idling near airports. The immigrants or their sponsors could pay for the quarantines themselves and for a test when they want to enter the population. Additional health checks should be required for new immigrants in the short term.

Banning all immigration is not a serious response to the threat of COVID-19 at this stage of the pandemic. If Trump banned all immigration, travel with the rest of the world, and prevented U.S. citizens from returning except under strict quarantine in early January, he might have prevented or at least delayed the spread here, but that was long before the world knew of a serious pandemic. And remember that about 110,000 immigrants entered the United States during the more serious 1918 pandemic and the government didn’t cancel the temporary migrant worker program for Mexicans that year. During the greatest national emergency in the 20^th century, the United States let in 170,952 immigrants on green cards and 227,668 bracero guest workers to work in the essential economic sector of agriculture. At a very minimum, we can allow some legal immigrants and temporary guest workers to enter and work in essential sectors of the economy if they pass rigorous health screenings. Let’s make sure immigration doesn’t threaten public health rather than banning it altogether.

Beijing is trying to exploit the coronavirus pandemic at every opportunity. Although that strategy may advance some short-term objectives for Xi Jinping’s government, it is a myopic approach that is almost certain to backfire. Indeed, it is already breeding extensive resentment in the United States and around the world.

As I discuss in a new article in The Hill, Beijing launched a propaganda offensive to shift blame for the spread of the coronavirus onto the United States. Most evidence indicates that the virus originated in a market in the city of Wuhan, but there are recent indications that the pandemic may have begun when a contaminated employee of a virology research lab outside of Wuhan accidentally transmitted the disease to the broader population.

Yet early on, the Chinese government and state media began promoting the ugly assertion that Washington likely initiated the pandemic as the consequence of a bioweapons program. Stories appeared in China’s state-run media referring to the “American coronavirus” and emphasizing the participation of U.S. Army personnel at athletic games in Wuhan in October 2019, just before the first signs of the coronavirus began to appear. A furious Secretary of State Mike Pompeo denounced the Chinese government for making such allegations.

Beijing’s exploitation of the coronavirus tragedy goes far beyond attempts at blame-shifting, however. The attention of both the news media and general populations throughout the world is understandably focused on the pandemic, and Xi’s government is taking maximum advantage of that distraction. Chinese leaders chose this moment to pressure the Hong Kong government to crack down on the pro-democracy movement. On April 18, security forces arrested more than a dozen top leaders of that movement. The New York Times observed: “The arrests signaled a broader crackdown on the antigovernment movement that roiled the semiautonomous city last year, one of the most significant challenges to Communist Party rule in decades.” Beijing and its Hong Kong surrogates also are calling for lawmakers to pass national security laws that would enable the mainland authorities “to further encroach upon the territory’s civic freedoms.”

In addition to the crackdown in Hong Kong, Beijing is attempting to strengthen its vast territorial claims in the South China Sea. The government just established two new administrative districts as though the region is indisputably Chinese territory, despite competing claims from several neighboring countries. That move is the latest step in Beijing’s strategy to establish de facto control over the area, following programs to build artificial islands and establish military airfields and other facilities on those islands. The timing of the new initiative is hardly coincidental.

The PRC’s abrasive, cynical behavior on the coronavirus and other issues is having a noticeable impact on American public opinion. Citing a recent Harris poll, Washington Post columnist Josh Rogin concluded that “the coronavirus crisis is actually bringing Americans together on the China issue.” But the nature of that growing consensus should be a wake-up call for Beijing. “Republicans and Democrats now largely agree that the Chinese government bears responsibility for the spread of the pandemic, that it can’t be trusted on this or any other issue, and that the U.S. government should maintain a tough position” toward China on nearly all issues.

Chinese leaders have only themselves to blame for that development. Xi Jinping’s government may well pay a heavy price over the long-term because of its attempts to exploit the coronavirus outbreak for short-term strategic gains, and it deserves to do so.

During pandemics, what economic costs associated with regulation should society tolerate to reduce health risks? Economists usually argue that the answer should be guided by the decisions we observe in labor markets in which individuals accept additional morbidity and mortality risk in return for higher compensation. Coal miners and construction workers, for example, are paid more than others with similar skills because they face higher statistical risk of injury and death on the job. A recent estimate of the Value of a Statistical Life (VSL) is $9 million, which implies that policies that reduce mortality risk are acceptable if the cost per life saved is $9 million or less.

Regulatory economists routinely evaluate health and safety policies in this manner. Some interventions, such as rules mandating that lighters be childproof, only cost $100,000 per statistical life saved and are thus highly cost effective, while OSHA regulations regarding formaldehyde exposure in the workplace cost $78 billion per statistical life saved, more than 1,000 times greater than the VSL estimate.

So are lockdown regulations, such as mandating the closure of non-essential businesses and issuing stay-at-home orders, cost-effective means of reducing COVID-19 mortality risk, like the childproof lighter regulations, or absurd overkill, like the formaldehyde-exposure rules? Recent papers use epidemiological models to estimate the number of lives that can be saved through various isolation measures that are less severe than those currently in place for much of the country (7‑day isolation for anyone showing coronavirus symptoms, a 14-day voluntary quarantine for their entire household, and dramatically reduced social contact for those over 70 years of age). Greenstone and Nigam, for example, conclude that moderate social distancing can save 1.76 million lives through October 1. Using age-varying estimates of a statistical life (VSL for those under age 9 is $14.7 million while VSL for those over age 79 is $1.5 million), they estimate the benefits of such policies at slightly less than $8 trillion. A constant $9 million VSL, rather than age-varying estimates, implies benefits of $15.8 trillion.

In 2019 U.S. gross domestic product (GDP) was $21.4 trillion. The benefits from moderate social distancing are thus estimated to range from more than one-third to more than two-thirds of a year’s worth of national income.

The apparent implication of the analysis is that a policy-induced reduction of national income on the order of the Great Depression (between 1929 and 1933, real U.S. GDP fell around 30%) would be efficient if the estimate of lives saved (1.76 million) were correct. And thus the non-essential business closures mandated by states are cost-effective because they are unlikely to result in a loss of income as severe as the Great Depression: 8.5 percent of annual GDP if kept in place for just three months.

While we welcome attempts to estimate the relationship between the costs of forced reduction in human interaction and the mortality benefits that result, we believe that policies that deliberately reduce economic output have large costs beyond the lost income. In traditional analyses of health and safety regulation, such as the previously mentioned lighter and formaldehyde rules, the estimates of costs include only compliance costs: the extra material and labor costs involved in complying with the rule. The cost estimates do not include any other reasons that would cause consumers to oppose the regulation, or any broader costs more generally (such as long run, unintended effects of new government policies).

In most traditional health and safety regulatory contexts that omission is probably not empirically important: the airbag container makes the steering wheel less attractive for some people, perhaps, but the effect is tiny. In other traditional regulatory contexts, the omission is more important but ignored: childproof caps on OTC and prescription medicines are annoying for many people and especially difficult for the elderly, but most compliance cost analyses ignore such effects.

In the forced reduction of social interaction during the current pandemic, we think that many costs, beyond just lost income, are important: the cost of missing your last chance to see Grandad before he dies alone, the costs to mental and physical health of isolation, the cost of lost time for single people to meet a partner in the window of life where fertility is possible, the cost of missing travel opportunities, or the cost of acquiring new skills or talents that require exiting the home. In economic terms, these might be dubbed the broader costs of restrictions on our non-market liberties, or the decline in productivity of our leisure time. If they were monetized and added to any analysis assessing lockdowns, then the cost-effectiveness of restrictions would be much reduced.

To reiterate, we agree that, during a pandemic, comparing some estimate of the value of lives saved against the full costs of shutdowns is a fruitful analysis. Of course, this only tells us which broad policy is preferable, not “optimal.” It may be that lockdowns are more cost-effective than doing nothing, but that a range of safety protocols and isolation of vulnerable groups is even more cost-effective in minimizing the combined economic and health costs of the virus, for example. But our key point is this: a large component of the cost estimate of lockdowns should consist of the monetary value of the loss of freedom to move and interact as we normally do, in addition to the actual lost income from reduced market activity. Thus, the appropriate (cost-effective) policy-induced reduction in economic activity would likely be significantly smaller than currently estimated as cost effective by many economists.

In the April 16 White House briefing, President Trump again said, as he often has before, that “models predicted between 1.5 and 2.2 million deaths” if we had not endured the various economic shutdowns imposed by the Governors of 42 States. The severity and breadth of those statewide shutdowns was initially encouraged, and is now justified, by just one dramatic statistic. That number was the 2.2 million U.S. deaths supposedly at risk from COVID-19.

The famed 2.2 million estimate first reached viral status in the March 31 White House briefing by Doctors Anthony Fauci and Deborah Birx. They displayed a graph with two bell-shaped epidemic curves placed on top of each other. Both curves estimate deaths per day which rise to a peak and then fall.

The steeper of the two curves was painted black and marked “Pandemic Outbreak: No Interventions.” It showed an estimated total of 1.5 to 2.2 million deaths from COVID-19 in what appears to be a relatively short period. The White House graph showed no dates, but the source of that now-famous 2.2 million estimate (as explained later) predicted U.S. deaths would keep rising until June 20.

The second “flattened” curve rises more slowly but also peaks later (in, say, August) with a more prolonged period of deaths than the steep curve (where more deaths happen more quickly). The flatter curve is labeled “With Interventions” and also100,000 to 240,000 deaths. Contrary to the delayed timing shown in the lighter graph, the architects of that more-delayed or flattened curve believe COVID-19 deaths have already peaked.

Based on the two curves, President Trump repeatedly remarked that State government mitigation plans saved two million lives – the difference between one curve’s estimate of 2.2 million and the other’s very different estimate of roughly 200,000. The graphs certainly do create that impression, although White House briefings by Fauci and Birx never spelled it out. They instead emphasized that the goal of “flattening the curve” was merely to buy time and avoiding overwhelming the hospitals, saving some lives (but not two million) by not running out of hospital beds and ventilators.

Where did the two curves come from? At first, many thought the estimates came from the White House experts. CNBC reported, “Dr. Birx said the projections by Dr. Anthony Fauci that U.S. deaths could range from 1.6 million to 2.2 million deaths is a worst-case scenario if the country did ‘nothing’ to contain the outbreak, but said even ‘if we do things almost perfectly,’ she still predicts up to 200,000 U.S. deaths.”

The steep curve with 2.2 million deaths was not from Dr. Fauci, however, but from Neal Ferguson’s team at Imperial College London. As for the flatter curve, Dr. Birx later attributed it to Chris Murray’s team at the University of Washington Institute for Health Metrics and Evaluation (IHME). However, even the highest IHME death estimates never approached 200,000 (unlike death estimates on that graph) and their mid-range estimates have lately been reduced from 93,000 to 69,000. Like the Imperial College model and others, the IHME model greatly overestimated the need for hospital beds and ventilators. But because it incorporates new facts, such errors get corrected.

The March 16 Imperial College paper, unlike the IHME model, is a month old and cannot be undone without losing face. Even with “the most effective mitigation strategy examined,” that study predicted, “the surge limits for both general ward and ICU beds would be exceeded by at least 8‑fold under the more optimistic scenario.” Yet there are no signs the U.S. will ever need 8 times as many hospital beds, or that even New York City is critically short of beds or urgent care facilities.

If the point of comparing two graphs was to show estimated deaths with and without “interventions,” then there was no reason to use two models rather than one. The same Imperial College model that warned of 2.2 million U.S. deaths with no interventions also predicted 1.1 to 1.2 million deaths –not 100,000 to 240,000– even with “the most effective mitigation strategy.” The Imperial College recommendations for “most effective mitigation” focused on social distancing for those over 70 and isolation of only those infected and their contacts, rather than banning jobs or closing all restaurants and beaches. An effective strategy would be targeted and localized, consistent with the new federal guidelines for gradually easing restrictions on the least-risky counties, populations, activities and businesses.

For the White House science team to meld the Ferguson and Murray curves into a single graph was quite inappropriate, because they are quite different. The Murray/​IHME model continually monitors actual data on state and national deaths and hospitalization, and adjusts the projected epidemic curve to incorporate new information.

The Ferguson/​Imperial College estimates, by contrast, came from a month-old (March 16) simulation model for high-density areas which constructed hypothetical scenarios using inflexible parameters about infection rates and other variables culled from obsolete studies of the earliest phase of the outbreak in Wuhan, China. In my next blog, I will attempt to explain how and why the Imperial College report may have ended up with such extreme projections of hospital bed shortages and deaths.

Dr. Fauci and Dr. Birx have done an outstanding job of explaining how the new coronavirus spreads and what we can all do to reduce the risk of getting infected or infecting others. Federal advice about proper handwashing and alcohol-based hand sanitizers, and (belatedly) the value of masks, helped reinforce the natural incentive of people to protect themselves. Federal bans on travel from China and Europe clearly saved lives. Many of the broad statewide mitigation mandates, though not yet efficiently targeted, nonetheless saved lives.

But it was disingenuous for the White House team to imply–by wrongly comparing epidemic curves from two different models–that these mitigation strategies may have saved two million American lives. The British model that once postulated a scenario in which 2.2 million U.S. lives could be at risk was simply wrong, and references to it should stop.