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.
      2. 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.
      3. 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.