Pandemics breed more than a contagious disease. They spread fear, misinformation, pseudoscience, and exploitation. Unfortunately our society is proving to be fertile ground for such things, and no amount of physical distancing will slow the spread of contagion over social media. And like any contagion, we can track the spread of certain strains of misinformation, that replicate and mutate with the most infectious tending to spread the widest.

One such nugget of misinformation, spread by those who are motivated to minimize the severity of COVID-19, is the narrative that this pandemic is just a bad flu season. We don’t go to extreme measures every year to minimize deaths from the flu, so why are we freaking out now? This, however, is a false comparison in many ways and entirely misses the point of physical distancing.

Flu season

The flu is a serious illness, make no mistake, and we do tend to ignore it because we have been living with it for so long. So what is a typical flu season like? Between 2010 and 2019 the annual flu season (deaths over an entire year, but not a calendar year – from the fall of one year through the spring of the next) ranged between 12,000 and 61,000 deaths in the US alone. That is from 9.3-45 million illnesses and 140-810 thousand hospitalizations. That is a significant disease burden every year, although spread out over about 8 months.

This means that the case fatality rate from getting the flu is about 0.1%. But that one number is not the only way to measure disease burden. There is also morbidity – negative health outcomes other than death. There is also the economic burden from direct health care costs and lost productivity. We can also consider lost years of life – is the flu killing mostly old sick people or young healthy people? The CDC estimates that 71-85% of flu deaths occur in those >= 65 years old. The flu also affects very young children and infants – and is generally considered to be most dangerous to the very young and the very old.

New flu strains can also be the source of pandemics of their own, such as the bird flu or H1N1 pandemics. These are generally caused by new and particularly virulent strains, and may be superimposed upon the natural cycle of the flu season.

There are two main measures that we take to minimize the morbidity and mortality from the flu. The first is targeted physical distancing – if you are symptomatic, stay at home. Don’t go to work and minimize contact with other people until you are no longer contagious. The second critical measure is the flu vaccine. The efficacy of the vaccine varies each year, because we are guessing which strains are most likely to hit us each season and those guesses, as informed as they are, may not be accurate. Even still, some coverage is better than none and it is always a good idea to get the flu vaccine every year (unless you have a medical contraindication).

The CDC estimates that for children 6 months to 17 years old flu vaccine coverage was 62.6%, and for adults 18 and over it was 45.3%. These numbers are sadly low. We would like >90% coverage to get effective herd immunity to reduce the spread of the flu.

Looking at the numbers, saying that a pandemic is a “bad flu season” is not really accomplishing the goal of minimizing it. The flu is a serious infectious illness with a substantial disease burden. The experts don’t ignore the flu, it’s just that the approach to minimizing it is public education about personal physical distancing for those who are symptomatic, good hygiene like hand washing, coughing into your elbow, and keeping surfaces clean, and getting the flu vaccine. When an actual “bad flu season” hits in the form of a flu pandemic, extreme physical distancing may be necessary.

But perhaps what one might conclude is that we have become complacent about the flu and should be more aggressive in mitigating it, not that we should be complacent about COVID-19.

The COVID-19 pandemic

Now let’s look at COVID-19. As of April 21, according to the CDC there were 776,093 cases in the US with 41,758 deaths. That is a case fatality rate of 5.3%, much higher than the flu. But that number has become highly controversial, and that’s because it is genuinely not reliable. The reason you cannot look at these numbers and compare it to the flu is that we are still in the middle of this pandemic. We won’t know the true case fatality rate until it is all over and we can look back at the numbers.

Let me first point out that these numbers are over essentially the last two months, not the 6-8 months of a typical flu season. That is critical, because one of the primary risks of the COVID-19 pandemic is that it overwhelms our resources. And in fact that is already happening. We are having shortages of personal protective equipment (PPE) and ventilators. We are stretching our ICU capacity beyond its limits. In my own hospital neurologists are being recruited to cover medical services because there aren’t enough doctors to cover the wave of COVID-19 cases. In some hospitals in New York patients are sharing ventilators. We don’t have the testing capacity to shift to an individual isolation strategy.

This is the whole point of physical distancing to “flatten the curve”. We are trying to spread out cases over a longer period of time to keep from overwhelming our medical resources. It doesn’t take much of an imagination to figure out that there will be incredible downstream negative effects, even on non-COVID-19 patients, if our hospitals are overwhelmed.

This brings up the additional point that the numbers I quotes above are with physical distancing. What would the numbers look like if we were not in the middle of a lockdown? We will never know for sure, but the models predicted about 2 million deaths in the US, and 40 million worldwide. That is similar to the 1918 flu pandemic that killed 50 million (conservatively). These “worst case” models have been highly criticized so let’s explore that a bit.

Such models are inherently variable because exponential processes like a pandemic are extremely sensitive to small changes. There are many assumptions in the models about individual behavior, infection rates, how infection rates change over time, the effects of immunity, and other variables. So they generally produce a wide range of estimates, and picking the extreme end is unlikely to be very predictive.

But we can say this – right now we have >40 thousand deaths in the US and we are clearly somewhere in the middle of this pandemic. The number of cases perhaps are just starting to flatten, but not drop, and the mortality numbers lag about two weeks behind the case numbers. The figure, therefore, is certain to climb significantly higher. And this is with the lockdown we are currently experiencing. We can argue about the details of the models, but no expert would disagree with the conclusion that the numbers would be significantly higher without physical distancing. How high we can’t know – but higher.

Also, since even now we are overwhelming our hospital capacity in hot-spots, the strain on the medical system would be much worse. It is hard to predict the effects this would have. When systems start to break down, the negative effects tend to cascade.

Now let’s take a closer look at the case fatality rate. Some have argued that the true number of cases (the denominator) is much higher because there are many unrecognized asymptomatic or minimally symptomatic cases. This is true but misleading. First, this doesn’t really affect the “case fatality” rate, if we define cases as those diagnosed with COVID-19. It is still meaningful to say that if you are diagnosed with COVID-19, the mortality rate is about 5%.

However, that number is likely even higher because the true case fatality rate is underestimated if you look at current cases, rather than only completed cases. That’s because some current cases will not survive, but they are counted as survivors if you use them in the denominator. If you look only at completed cases worldwide, the case fatality rate is 20%. That should probably be considered the high end of the range of estimates based on various methods. The low end would consider all current cases, including estimates of asymptomatic cases, which produces a mortality rate as low as 0.2%, close to the flu. But this is just as misleading as quoting a 20% case fatality rate.

The bottom line is that – we don’t know the case fatality rate, because we are still in the middle of the pandemic. I would point out, however, that just diluting the denominator with asymptomatic cases doesn’t really tell us anything about the disease burden. It makes the case fatality rate lower – by making the number of cases much higher. In the end, the number of deaths and morbidity is what we care about. We also don’t know what the seasonality of the disease will be, and if there will be a second or third wave. Remember, in the 1918 flu pandemic it was the second wave that killed the most people.

We also don’t know how good immunity is from getting the virus. Are all those asymptomatic infected people now immune? We don’t know. If there are, that’s a good thing, but we don’t currently know.

In the end, trying to minimize the severity of the COVID-19 pandemic by comparing it to a typical flu season is misleading in many ways. We know that COVID-19 is a serious illness that causes hospitalization in many cases, requiring ICU beds and ventilator support in some. In hot spots this is overwhelming our resources. The numbers are already serious, and we are still in the middle of this pandemic – hopefully, we don’t know what the future brings. We also know that without physical distancing it would be much worse, although it is difficult to say exactly how much.

The best we can do at this point is listen to the experts, but also be realistic about the nature of predicting and modeling a pandemic while we are in the middle of it.


Posted by Steven Novella

Founder and currently Executive Editor of Science-Based Medicine Steven Novella, MD is an academic clinical neurologist at the Yale University School of Medicine. He is also the host and producer of the popular weekly science podcast, The Skeptics’ Guide to the Universe, and the author of the NeuroLogicaBlog, a daily blog that covers news and issues in neuroscience, but also general science, scientific skepticism, philosophy of science, critical thinking, and the intersection of science with the media and society. Dr. Novella also has produced two courses with The Great Courses, and published a book on critical thinking - also called The Skeptics Guide to the Universe.