How Do We Know?

I recommend reading Dhruv Khullar’s musings in the New Yorker on COVID-19 statistics. Here’s a sample passage I found telling:

A coronavirus infection isn’t what it once was. Studies suggest that, compared with Delta, Omicron is a third to half as likely to send someone to the hospital; by some estimates, the chance that an older, vaccinated person will die of covid is now lower than the risk posed by the seasonal flu. And yet the variant is exacting a punishing toll—medical, social, economic. (Omicron still presents a major threat to people who are unvaccinated.) The United States is recording, on average, more than eight hundred thousand coronavirus cases a day, three times last winter’s peak. Given the growing use of at-home tests, this official count greatly underestimates the true number of infections. We don’t know how many rapid tests are used each day, or what proportion return positive, rendering unreliable traditional metrics, such as a community’s test-positivity rate, which is used to guide policy on everything from school closures to sporting events.

There are many other numbers we’d like to know. How likely is Omicron to deliver not an irritating cold but the worst flu of your life? How does that risk increase with the number and severity of medical conditions a person has? What are the chances of lingering symptoms following a mild illness? How long does immunity last after a booster shot or an infection? Americans aren’t waiting to find out. Last week, rates of social distancing and self-quarantining rose to their highest levels in nearly a year, and dining, shopping, and social gatherings fell to new lows. Half of Americans believe that it will be at least a year before they return to their pre-pandemic lives, if they ever do; three-quarters feel that they’re as likely, or more so, to contract the virus today—a year after vaccines became available—as they were when the pandemic began.

He concludes on, presumably, a hopeful note:

But this wave, too, shall pass—possibly soon. At the end of it, the vast majority of Americans could have some degree of immunity, resulting from vaccination, infection, or both. In all probability, we’d then approach the endemic phase of the virus, and be left with a complex set of questions about how to live with it. What level of disease are we willing to accept? What is the purpose of further restrictions? What do we owe one another? A clear-eyed view of the numbers will inform the answers. But it’s up to us to paint the targets.

He also draws a distinction between “hospitalized for COVID” and “hospitalized with COVID”.

My question about much of this is how do we know? How do we know how many people have “some degree of immunity”? How will we know? How do we know what proportion of those hospitalized are hospitalized for COVID or hospitalized with COVID?

This hearkens back to an earlier post. The risk of “thinking like physicians” rather than like public health professionals is already an issue.

7 comments… add one
  • Drew Link

    We don’t know. For the umpteenth time: the data are terrible. Incomplete, impossible to determine, disputed, suppressed, changing with the preferred narrative…… The real question to be asked is why there has not been an all hands drive to obtain good data to actually define the issues. And in the absence of that drive: what’s really going on here?

  • PD Shaw Link

    I think some states are keeping track of who is admitted for COVID and who is admitted for other reasons but tests positive. In New York I think at one point it was 49% of the former, 51% of the latter. From the physicians view, it doesn’t matter because they have to take precautions in either case, but I think the larger issue is that many of these people may not be contagious, so the precautions are unnecessary and possibly counterproductive.

    This week Dr. Daniel Griffin shared a recent story about a woman admitted for a finger infection who tested positive and was quarantined in a room with another patient that tested positive. She complained that she couldn’t have COVID, she contracted the virus over Thanksgiving and was treated with monoclonals. The PCR test was positive at over 38 CT, which Griffin believed was consistent with prior infection from months ago. So not only was she put at risk of catching COVID (she left the hospital a few days later with a sore throat), there is a false positive test result. There is overcounting going on now as well.

  • Jan Link

    I don’t think we will ever know for sure the actual parameters of this virus, via an honestly derived data base. From the get go there were too many medicinal errors committed, hysterics ginned up, definitions and testing arbitrarily changed to recalibrate COVID’s societal effects, dusted with political advantage-seeking. In a collusion-type fashion, a consortium of TV doctors, social/print media, politicians wanting power, this pandemic was run like a screenplay gone bad. Unfortunately this political concoction continues, unrestrained, to supplant our civil rights and freedoms with a do-this-for-your-own-good-or-else type of authoritarianism.

  • steve Link

    We track the admitted with vs admitted because numbers. I think most hospitals do that. In a way it doesnt matter since we are still holding about 100 pts in our Eda. It is milder but more contagious plus we have a lot of unvaccinated in our area.

    I have not seen a study looking at what percentage of pts are not admitted that are still pretty sick. Might exist in family practice literature.

    Steve

  • Zachriel Link

    Dave Schuler: How do we know how many people have “some degree of immunity”?

    Nearly everyone who is vaccinated or has had COVID has some degree of immunity. That doesn’t mean they can’t catch COVID, but their immune systems are primed to fight the infection, resulting in milder cases.

  • That’s articulating a belief. I accept that you believe it. It may or may not be true. Only empirical evidence will demonstrate its truth.

  • Zachriel Link

    Dave Schuler: It may or may not be true. Only empirical evidence will demonstrate its truth.

    Empirical evidence:
    https://covid.cdc.gov/covid-data-tracker/#rates-by-vaccine-status

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