Contribute Try STAT+ Today

Much of the current discourse on — and dismissal of — the Covid-19 outbreak focuses on comparisons of the total case load and total deaths with those caused by seasonal influenza. But these comparisons can be deceiving, especially in the early stages of an exponential curve as a novel virus tears through an immunologically naïve population.

Perhaps more important is the disproportionate number of severe Covid-19 cases, many requiring hospitalization or weekslong ICU stays. What does an avalanche of uncharacteristically severe respiratory viral illness cases mean for our health care system? How much excess capacity currently exists, and how quickly could Covid-19 cases saturate and overwhelm the number of available hospital beds, face masks, and other resources?

This threat to the health care system as a whole poses the greatest challenge.


As I initially described in a Twitter thread, simple mathematics can derive rough estimates for how this might play out.

This exercise can inform our level of urgency and equip us to anticipate non-obvious, second-order effects, some of which can be mitigated with proper preparation.


As of March 8, about 500 cases of Covid-19 had been diagnosed in the U.S. Given the substantial underdiagnosis at present due to limitations in testing for the coronavirus, let’s say there are 2,000 current cases, a conservative starting bet.

We can expect a doubling of cases every six days, according to several epidemiological studies. Confirmed cases may appear to rise faster (or slower) in the short term as diagnostic capabilities are ramped up (or not), but this is how fast we can expect actual new cases to rise in the absence of substantial mitigation measures.

That means we are looking at about 1 million U.S. cases by the end of April; 2 million by May 7; 4 million by May 13; and so on.

As the health care system becomes saturated with cases, it will become increasingly difficult to detect, track, and contain new transmission chains. In the absence of extreme interventions like those implemented in China, this trend likely won’t slow significantly until hitting at least 1% of the population, or about 3.3 million Americans.

What does a case load of this size mean for health care system? That’s a big question, but just two facets — hospital beds and masks — can gauge how Covid-19 will affect resources.

The U.S. has about 2.8 hospital beds per 1,000 people (South Korea and Japan, two countries that have seemingly thwarted the exponential case growth trajectory, have more than 12 hospital beds per 1,000 people; even China has 4.3 per 1,000). With a population of 330 million, this is about 1 million hospital beds. At any given time, about 68% of them are occupied. That leaves about 300,000 beds available nationwide.

The majority of people with Covid-19 can be managed at home. But among 44,000 cases in China, about 15% required hospitalization and 5% ended up in critical care. In Italy, the statistics so far are even more dismal: More than half of infected individuals require hospitalization and about 10% need treatment in the ICU.

For this exercise, I’m conservatively assuming that only 10% of cases warrant hospitalization, in part because the U.S. population is younger than Italy’s, and has lower rates of smoking — which may compromise lung health and contribute to poorer prognosis — than both Italy and China. Yet the U.S. also has high rates of chronic conditions like cardiovascular disease and diabetes, which are also associated with the severity of Covid-19.

Support STAT: If you value our coronavirus coverage, please consider making a one-time contribution to support our journalism.

At a 10% hospitalization rate, all hospital beds in the U.S. will be filled by about May 10. And with many patients requiring weeks of care, turnover will slow to a crawl as beds fill with Covid-19 patients.

If I’m wrong by a factor of two regarding the fraction of severe cases, that only changes the timeline of bed saturation by six days (one doubling time) in either direction. If 20% of cases require hospitalization, we run out of beds by about May 4. If only 5% of cases require it, we can make it until about May 16, and a 2.5% rate gets us to May 22.

But this presumes there is no uptick in demand for beds from non-Covid-19 causes, a dubious presumption. As the health care system becomes increasingly burdened and prescription medication shortages kick in, people with chronic conditions that are normally well-managed may find themselves slipping into states of medical distress requiring hospitalization and even intensive care. For the sake of this exercise, though, let’s assume that all other causes of hospitalization remain constant.

Let me now turn to masks. The U.S. has a national stockpile of 12 million N95 masks and 30 million surgical masks for a health care workforce of about 18 million. As Covid-19 cases saturate nearly every state and county, virtually all health care workers will be expected to wear masks. If only 6 million of them are working on any given day (certainly an underestimate) they would burn through the national N95 stockpile in two days if each worker only got one mask per day, which is neither sanitary nor pragmatic.

It’s unlikely we’d be able to ramp up domestic production or importation of new masks to keep pace with this level of demand, especially since most countries will be simultaneously experiencing the same crises and shortages.

Shortages of these two resources — beds and masks — don’t stand in isolation but compound each other’s severity. Even with full personal protective equipment, health care workers are becoming infected while treating patients with Covid-19. As masks become a scarce resource, doctors and nurses will start dropping from the workforce for weeks at a time, leading to profound staffing shortages that further compound the challenges.

The same analysis applied to thousands of medical devices, supplies, and services — from complex equipment like ventilators or extracorporeal membrane oxygenation devices to hospital staples like saline drip bags — shows how these limitations compound one another while reducing the number of options available to clinicians.

Importantly — and I cannot stress this enough — even if some of the core assumptions I’m making, like the fraction of severe cases or the number of current cases, are off even by several-fold, it changes the overall timeline only by days or weeks.

Unwarranted panic does no one any good, but neither does ill-informed complacency. It’s inappropriate to assuage the public with misleading comparisons to the seasonal flu or by assuring people that there’s “only” a 2% fatality rate. The fraction of cases that are severe really sets Covid-19 apart from more familiar respiratory illnesses, compounded by the fact that it’s whipping through a population without natural immune protection at lightning speed.

Individuals and governments seem not to be fully grasping the magnitude and near-inevitability of the national and global systemic burden we’re facing. We’re witnessing the abject refusal of many countries to adequately respond or prepare. Even if the risk of death for healthy individuals is very low, it’s insensible to mock decisions like canceling events, closing workplaces, or stocking up on prescription medications as panicked overreaction. These measures are the bare minimum we should be doing to try to shift the peak — to slow the rise in cases so health care systems are less overwhelmed.

The doubling time will naturally start to slow once a sizable fraction of the population has been infected due to the emergence of herd immunity and a dwindling susceptible population. And yes, societal measures like closing schools, implementing work-from-home policies, and canceling events may start to slow the spread before reaching infection saturation.

But considering that the scenarios described earlier — overflowing hospitals, mask shortages, infected health care workers — manifest when infections reach a mere 1% of the U.S. population, these interventions can only marginally slow the rate at which our health care system becomes swamped. They are unlikely to prevent overload altogether, at least in the absence of exceedingly swift and austere measures.

Each passing day is a missed opportunity to mitigate the wave of severe cases that we know is coming, and the lack of widespread surveillance testing is simply unacceptable. The best time to act is already in the past. The second-best time is right now.

Liz Specht is the associate director of science and technology at The Good Food Institute.

  • Excellent article Liz – I ran some similar numbers (with much less detail) comparing Italy to the US. The biggest assumption I’d question above is the total number till overwhelm. Italy hit overwhelm on 10,000 cases (population 60m, 3.4 beds/1000) which seems MUCH earlier – applying same rational to US (pop 328m 2.4 beds/1000) would suggest overwhelm at 38k cases. Someone suggested that was because the Italian case was one region (pop 16m), that still would suggest US would hit overwhelm at around 228k cases, but that assumes the US impact is evenly distributed, and in an exponential that won’t be the case – its more likely to be city by city, once it gets hold in one place it will expand fast there. Those differences in assumption come down to about 6 doublings.

    More importantly, Italy also saw doubling times (over last 12 or 7 days) of 3 days (Australia and US are 4.4 and 3.4, but on smaller numbers and both AU & US numbers are probably deflated by unavailability of tests). With the exponential curve that’s a crucial difference. If its closer to 3.4 than 6 days, with your other assumptions unchanged that would change it from May 10 to Apr 15.

    I am *not* an epidemiologist so I have zero reason to assume my assumptions are more accurate than yours, I’m just interested in any enlightenment about the differences to help predict roughly when we hit overwhelm (especially in Australia) in order that people can be prepared.

  • Too bad R-0 is about six, and doubling occurs in 4.23 days, and not 6, as you assume.

    Your napkin-math is wildly optimistic. Unfortunately.

  • Amateur move to clump hospital beds together as if we can suites patients around the US easily. Number of available beds compared to population varies widely between cities especially in higher density cities with undeserved communities.

    • This is a back of the envelope calculation. More sophisticated models require large computer codes. Some medical schools Hopkins, Harvard, U Cal have these. The point is that because of the Trump induced foot dragging, the US is in for a world of hurt in the next 1-3 months. We will be like Italy, not South Korea.

  • The numbers in this article don’t make sense. China has 1.3 billion people but only But only 80,000 cases. How does the US get to

    That means we are looking at about 1 million U.S. cases by the end of April; 2 million by May 7; 4 million by May 13; and so on.

    Doesn’t add up.

  • I see below the estimate of this hitting up to 198 million US Citizens. The Swine Flu as a Pandemic hit about 60 Million US Citizens over 2009-2010. What in our very early models suggest this will hit a much higher percentage of citizens?

    • Researcher publicized that they found infected persons shed copious amounts of virus before they show any symptoms. This contributes greatly to the community spread and infection rates. The American Hospital Association guestimated that 40% of the population will be infected.

      Research is not yet available about how many virus are needed to be ingested to result in an infection. Your body has immunity. Some better than others. It takes more than one single virus or bacteria to cause an infection. If that was not the case, we would be extinct by now….

      They are also researching if persons that were infected with an earlier strain of chronavirus have some immunological resistance to this virus. Like the CDC says, ‘there is a lot we don’t know about this strain.’

    • I don’t think the modeling can accurately take into account behavioral changes. No measurable behavioral changes were made during the H1N1/09 pandemic (lasted about 12 months). But, I think it is very safe to say that the COVID-19 human host species, as a whole, has made measurable behavioral changes in the early onset of this COVID-19 pandemic. The R0 factor and behavior go hand in hand, although some do not seem to get that concept. If an infected individual that had not yet begun to shed the virus were placed on a deserted island for a month, the number of people they COULD have theoretically given it to if they’d of gone about their ordinary doings in civilization doesn’t change, but the number that they do give it to = zero.

  • I posted this in a different reply, but here it is, Hospital beds per country as per OCDE. I’ve highlighted the most infected countries for easy read.

    Also here,
    you can compare Regional Health Care systems. In Italy, which has a current CFR of 8%, the region Lombardie is hit the heaviest: it ranks 9.9/10, in the top 5% of OCDE’s regions. Ile de France where I live ranks 10/10 and also in top 5%, California 7.1/10, top 38%.

    In any case, you’re missing her point : exponential infection in an immunologically naive population make beds availability and even severe ICU % rate negligible : you only end-up with days or weeks delay before you are overrun.

    How is it so difficult for some to realize it?
    Haven’t you heard of controlled nuclear chain reaction? Haven’t you heard of what happens when the Neuton R0 is no longer kept mechanically below 1 ?

    If a top 5% region in OCDE like Lombary Italy is overrun…chances are we’ll all be and that only stric NPI actions are efficient at this rate.

    To not act, is akin to killing people today, we do not have Chinese excuse of not knowing!

  • I think nature will win this one. Community spread is a fact. Researchers say infected individuals shed copious amounts of virus BEFORE they develop symptoms. That is one reason why it is so contagious and it defeats measures like masks and negates taking people’s temperature moving from one zone to another or a port of entry.

    “Stay at home if you are sick.” What about your parent, spouse, and kids that work and go to school? Not a word from our health officials how to quarantine a person from others living in the same household. Break out the camper………?

    Infection rate is linear? Not if it doubles the number of cases every 4 days.

  • What “complex healthcare primary service area strategies and coverage ” is there, currently being deployed, that has any chance of lowering the current R0 rate of between 4-7?

    It’s not just journalists making these predictions. If it were there would be very little credibility to them for obvious reasons. However, you have incredibly well-respected specialists, such as Michael Osterholm (He is Regents Professor, McKnight Presidential Endowed Chair in Public Health, the director of the Center for Infectious Disease Research and Policy (CIDRAP), Distinguished Teaching Professor in the Division of Environmental Health Sciences, School of Public Health, a professor in the Technological Leadership Institute, College of Science and Engineering, and an adjunct professor in the Medical School, all at the University of Minnesota.) making the same predictions as the author of this article.

    Go over to and work your way through their peer-reviewed articles on the subject.

    It’s not about creating panic it’s about taking this thing seriously. The worst thing we can do is underreact, or wait until things worsen before taking the proper measures.

Comments are closed.

Your daily dose of news in health and medicine

Privacy Policy