On Herd Immunity: or Not

Path of least resistance AND looking at new ways of getting information (mostly for me) out of my “second brain” of Roam Research (“networked tool for thought) and into a place that has at least a weak possibility of finding its way into other minds and unlikely conversation:

So I will, from time to time, post stuff in this fashion. In this instance, all “highlights” are pulled directly from the long article to help me better understand the content. In future, at times, I will add my own commentary. FWIW.

â–ºMost important info here: learn about Rt versus R0 (R Nought) and what they mean with regard to COVID rise and fall.

In Roam, I will further digest such a piece via “progressive summarization” so that I have some level of mastery of the details. But enough, already.

Article:: Dangerous misunderstandings by [[Dr. Felicia Keesing]]

Dangerous misunderstandings | Cary Institute of Ecosystem Studies

  • Tags:: #roam_highlighter #pandemic #prevention
  • See also graphs by state of Rt Rt: Effective Reproduction Number
    • 📌FBF: this is really worth a look!
  • See also Herd immunity | Cary Institute of Ecosystem Studies
  • Highlights::
    • def: Rt, the effective reproduction number
    • What does it mean to say that Rt is less than one?
      • It means that if 10 people were infected, they’d infect only 9 others (in the case of Rt = 0.9) or 8 others (in the case of Rt = 0.8). Whenever Rt is less than one, there will be fewer and fewer infected people over time. The further Rt is below one, the faster this decline will happen.
      • Right now in the United States, most states have an estimated Rt of between 0.75 and 0.98. A handful of states have Rt above 1, but even the highest — Minnesota this week — is only at 1.05.
    • In most places, if we kept doing what we’ve been doing for long enough, the disease would slowly, slowly decline, potentially to zero
      • The three important points about this are these:
        1. The decline to zero would take a long time. Months and months. And months.
        1. Along the way, more and more people would be getting infected, and some of them would die. The total number of people infected at any one moment would be declining, but the actual people suffering would keep changing.
        1. As soon as we change what we’re doing about social distancing, hygiene, and quarantining, Rt will change as well, almost certainly by going up.
      • A problem for many of the reopening scenarios is that they assume that there is a threshold density below which students (or workers) returning to campuses (or offices) will be “safe” and above which they won’t be. But at least for now, there isn’t. For now, the less contact infected people have with others, the safer it will be[3]. It’s not a threshold. It’s a continuum.
    • If we want to reach the thresholds of *safe* or *normal*, we will need better solutions
      • For example, we could reopen higher-density settings, including campuses, (fairly) safely if we could test everyone daily, trace their contacts, and quarantine anyone who tests positive. But we can’t [4]. We could reach a threshold of something like normal if we had a safe, effective, and widely available vaccine. But we don’t.
    • As we plan the details of when and how to reopen more spaces and activities going forward, we face two critical issues.
      • How to lower the risks as much as possible
        • This involves
          • finding ways to maximize both hygiene (think masks, hand sanitizer, and extra cleanings) and distancing (think single-occupancy spaces, and socially-distant cafeterias).
          • We must also have a workable plan for what to do when people inevitably become sick. How do we detect infected people quickly, and how do we responsibly and efficiently identify their contacts? For colleges and universities, how do we quarantine sick students?
          • And how do we protect the most vulnerable?
      • Determining what level of risk is acceptable
        • With the tools we currently have, it’s not a question of whether creating lower-density campuses or businesses is safe. It’s a question of whether it’s safe enough. That’s not a scientific question, and it doesn’t have a scientific answer.
      • ❗R t versus R nought ❗
        • The effective reproduction number Rt is different from Ro (R-nought), though they’re related. Ro is the number of cases that would arise if an infected person was in a population in which everyone else was susceptible to infection. In theory at least, it’s an immutable property of a pathogen. In contrast, when some people are immune, through prior exposure or vaccination, or when people take active steps to reduce transmission (like washing hands or social-distancing or wearing masks), we need a different number. That’s Rt. It’s a measure of the number of new cases that are actually arising from each infected person, and it can change based on our behavior.

4 Replies to “On Herd Immunity: or Not”

  1. Thanks for this Fred. I had been confused about the “spreadability” (R-Naught) could keep changing. it doesn’t. Rt keeps changing based on our behavior. I don’t think I’ve seen the term Rt anywhere in the press. They either call it R-Naught or just the R factor.

  2. OmmaGerd! Somebody READ this and paid attention!

    I looking for a place to publish such material (and if found, I’d invest more time into synthesis and summarization.) There is a resurrected environmental newspaper coming back to our area (https://www.newrivervoice.com/?page_id=2) and I hope to find a landing place for stuff that finds no readership or interest at Fragments or FB.

    I’m also working w a regional small press to get book #3 between covers in a year, no more than two.

    So lack of visible words-to-print does not mean I’ve given up the fight. Thanks for reading.

  3. Hi, Fred! I just read it for the second time. Does that count? This is very clear, even just reading from your notes. I’ve been generally annoyed and confused reading anything from the popular press about viral spread, but have resisted really getting into the weeds of it in the scientific literature. I have a general sense of things from the (ancient) epidemiology course I had in school but not enough remnants of specifics remain for me to explain anything to anyone else with any credibility. People really don’t understand the complexity of the decision-making involved. Hope you and yours are well!
    Peg

  4. Greetings MargarEd, good to hear from you, and yes you have advanced credits for reading more than once. I do think the Rt graph over time can be very useful–for going back in time to see state patterns that reflect governmental policy/public compliance with policy. I wish it were more granular (by county, by community even.)

    Now that doors are “opening” we should probably expect to see more states rising above the 1.0 Rt line, with some crazy peaks and troughs over the coming year(s).

    We would certainly have stayed put where we are (for another week or two) where at least some things are certain and within our control (wood heat, artesian pressure, known good neighbors with skill sets). But the die is cast, we will forge on!

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