Question: Follow-up question: But if the only people being tested are those that show up at testing facilities with symptoms, and legit estimates are that the actual infection rates are 4–10 times higher with many people asymptomatic or just refusing testing, then how can we believe our current numbers are a useful gauge for the spread and severity of this illness? Even without antibody tests, our denominators are still wrong.

Answer: Our numerators and denominators are both incorrect — we’re likely missing deaths and missing cases. I totally agree that we need widespread testing — testing that includes folks who are concerned that they may have been exposed, of folks who have only mild symptoms, of folks who are sick but do not require hospitalization, etc. Without such widespread testing, we won’t be able to accomplish our test, trace, isolate public health goals to constrain the spread of the virus. When it comes to understanding the spread and severity of the illness, while the data we have now are incomplete, they are nonetheless informative. For monitoring disease spread, we absolutely need widespread testing and contact tracing (Health Force!), but in their absence, we can make informed judgments based on a) hospitalization rates (daily admissions and overall bed use); b) percent of tests that are positive; c) number of daily cases. For more on these metrics, see Q&A of 4/16. When it comes to severity, what we’ve seen around the world — from Wuhan to New York to the US writ large — is that among cases that we do know about, approximately 20% are serious and require hospitalization. We also know that COVID is far more serious than the flu. I bring this up because early on in the spread of the virus, many people likened it to the flu to assuage concerns (this happened in 1918 too, when people likened the flu to “the old-fashioned grip”)! For more on the severity of COVID compared with the seasonal flu, this viewpoint published in JAMA Internal Medicine last week is a fantastic read that I highly recommend. Here’s one excerpt:

“The demand on hospital resources during the COVID-19 crisis has not occurred before in the US, even during the worst of influenza seasons. Yet public officials continue to draw comparisons between seasonal influenza and SARS-CoV-2 mortality, often in an attempt to minimize the effects of the unfolding pandemic. The root of such incorrect comparisons may be a knowledge gap regarding how seasonal influenza and COVID-19 data are publicly reported. The CDC, like many similar disease control agencies around the world, presents seasonal influenza morbidity and mortality not as raw counts but as calculated estimates based on submitted International Classification of Diseases codes.2 Between 2013–2014 and 2018–2019, the reported yearly estimated influenza deaths ranged from 23 000 to 61 000.3 Over that same time period, however, the number of counted influenza deaths was between 3448 and 15 620 yearly.4 On average, the CDC estimates of deaths attributed to influenza were nearly 6 times greater than its reported counted numbers. Conversely, COVID-19 fatalities are at present being counted and reported directly, not estimated. As a result, the more valid comparison would be to compare weekly counts of COVID-19 deaths to weekly counts of seasonal influenza deaths.

During the week ending April 21, 2020, 15 455 COVID-19 counted deaths were reported in the US.5 The reported number of counted deaths from the previous week, ending April 14, was 14 478. By contrast, according to the CDC, counted deaths during the peak week of the influenza seasons from 2013–2014 to 2019–2020 ranged from 351 (2015–2016, week 11 of 2016) to 1626 (2017–2018, week 3 of 2018).6 The mean number of counted deaths during the peak week of influenza seasons from 2013–2020 was 752.4 (95% CI, 558.8–946.1).7 These statistics on counted deaths suggest that the number of COVID-19 deaths for the week ending April 21 was 9.5-fold to 44.1-fold greater than the peak week of counted influenza deaths during the past 7 influenza seasons in the US, with a 20.5-fold mean increase (95% CI, 16.3–27.7).”