3 ms·

Have you seen any attempts to actually put cause and effect together for stay-at-home orders and number of deaths? The only attempt I've seen to quantify it fou

Have you seen any attempts to actually put cause and effect together for stay-at-home orders and number of deaths? The only attempt I've seen to quantify it found no statistical connection between the two, but high connection between population density and deaths.

ashtonkem 7y ago
Any attempt to blame fatalities solely on population density is going to run into problems the moment they look at Southeast Asia.
- jtbayly 7y ago
  Please. That's not what I said. I said that there was a measurable connection between them. Any epidemiologist will acknowledge this. The point is that it could be seen and measured in this case. But when they attempted to find a connection between shutting down early or late (in the USA), no effect was found. The point being, the shocked horror that people already "forgot" the lessons learned last month is silly if that lesson wasn't learned and wasn't even true. The claim could do with some actual evidence. And I'm not even saying it's not true. I'm just saying this is the only attempt I've seen to actually analyze it, and it came up the opposite way. Can you point me to anything that shows the claim is true? https://www.wsj.com/articles/do-lockdowns-save-many-lives-is-most-places-the-data-say-no-11587930911 https://www.wsj.com/articles/do-lockdowns-save-many-lives-is...
  - stefan_ 7y ago
    New York City alone is #6 on the worldwide ranking for confirmed cases in countries.
    - jtbayly 7y ago
      And? How does that relate to my comment?
Grimm1 7y ago
Just a quick search on scholar shows me at least 5 studies into the impacts for a more rigorous analysis. Plus anecdotally I'm in NYC and since the stay at home order reached full strength the 3 day rolling average of infections has been decreasing. I can only see that being attributed to two things -- mask wearing and stay at home. Mask wearing came later in our lockdown so I'm going to say stay at home has been effective especially with what I've seen the infection number for COVID, I believe that's the R0 (Rt?) number, was something like 2.5 to much higher.
- jtbayly 7y ago
  I did a search but didn't find anything. Not sure exactly what to search for. Can you link to some of them?
  - Grimm1 7y ago
    https://arxiv.org/ftp/arxiv/papers/2004/2004.06098.pdf https://arxiv.org/ftp/arxiv/papers/2004/2004.06098.pdf https://arxiv.org/pdf/2004.14621.pdf https://arxiv.org/pdf/2004.14621.pdf That's two, I think the second one is better though as it uses more recent data and from more states and they raise a point that I think speaks to why the studies are not more prevalent and that is that many stay at home orders went into effect middle to end of March so the effects would only really be seen at the end of April. I imagine you'll see more of these popping up in the coming weeks.
- beerandt 7y ago
  >I can only see that being attributed to two things Two more things: 1) introducing (or the halting thereof) infections to at risk populations (the whole NY nursing/retirement home fiasco, or the Italy hospitals being points of transmission, or dorm style living in Wuhan) and 2) approaching ~50% of herd immunity. 1) When did NY state stop putting exposed/infected patients into those facilities? That's going to have a outsized result in the stats, given the segment vulnerability. Same for Italy hospitals being overwhelmed without PPE. 2) Not saying it's what is at play (yet) here, but infections will naturally decrease as a greater percentage of the population gains immunity. It's what has to happen as the population approaches herd immunity. (So about 30% if herd immunity is 60%, which is plausible, given the recent estimates of 20+% of the NYC population with antibody presence.) It's why exponential growth (for resource limited kinetics) ends up being an S curve and not a runaway exponential curve. The inflection point might not be at exactly 50% for a number of reasons, but it's good for a rough starting point. Additionally, it will be difficult to distinguish if the stay-at-home orders are effective due to the entire population participating, or if it's tied to specific population segments. Meaning the percent of the population active vs stay-at-home isn't independent of transmission numbers. The active sub-population might be closer to herd immunity than the stay-at-home crowd. This gets more complicated as you take into account the risk levels of particular patients. There's potentially a lot more going on. We need some scientific causation, not just correlation.

ashtonkem 7y ago

Any attempt to blame fatalities solely on population density is going to run into problems the moment they look at Southeast Asia.

jtbayly 7y ago
Please. That's not what I said. I said that there was a measurable connection between them. Any epidemiologist will acknowledge this. The point is that it could be seen and measured in this case. But when they attempted to find a connection between shutting down early or late (in the USA), no effect was found. The point being, the shocked horror that people already "forgot" the lessons learned last month is silly if that lesson wasn't learned and wasn't even true. The claim could do with some actual evidence. And I'm not even saying it's not true. I'm just saying this is the only attempt I've seen to actually analyze it, and it came up the opposite way. Can you point me to anything that shows the claim is true? https://www.wsj.com/articles/do-lockdowns-save-many-lives-is-most-places-the-data-say-no-11587930911 https://www.wsj.com/articles/do-lockdowns-save-many-lives-is...
- stefan_ 7y ago
  New York City alone is #6 on the worldwide ranking for confirmed cases in countries.
  - jtbayly 7y ago
    And? How does that relate to my comment?

Grimm1 7y ago

Just a quick search on scholar shows me at least 5 studies into the impacts for a more rigorous analysis. Plus anecdotally I'm in NYC and since the stay at home order reached full strength the 3 day rolling average of infections has been decreasing. I can only see that being attributed to two things -- mask wearing and stay at home. Mask wearing came later in our lockdown so I'm going to say stay at home has been effective especially with what I've seen the infection number for COVID, I believe that's the R0 (Rt?) number, was something like 2.5 to much higher.

jtbayly 7y ago
I did a search but didn't find anything. Not sure exactly what to search for. Can you link to some of them?
- Grimm1 7y ago
  https://arxiv.org/ftp/arxiv/papers/2004/2004.06098.pdf https://arxiv.org/ftp/arxiv/papers/2004/2004.06098.pdf https://arxiv.org/pdf/2004.14621.pdf https://arxiv.org/pdf/2004.14621.pdf That's two, I think the second one is better though as it uses more recent data and from more states and they raise a point that I think speaks to why the studies are not more prevalent and that is that many stay at home orders went into effect middle to end of March so the effects would only really be seen at the end of April. I imagine you'll see more of these popping up in the coming weeks.
beerandt 7y ago
>I can only see that being attributed to two things Two more things: 1) introducing (or the halting thereof) infections to at risk populations (the whole NY nursing/retirement home fiasco, or the Italy hospitals being points of transmission, or dorm style living in Wuhan) and 2) approaching ~50% of herd immunity. 1) When did NY state stop putting exposed/infected patients into those facilities? That's going to have a outsized result in the stats, given the segment vulnerability. Same for Italy hospitals being overwhelmed without PPE. 2) Not saying it's what is at play (yet) here, but infections will naturally decrease as a greater percentage of the population gains immunity. It's what has to happen as the population approaches herd immunity. (So about 30% if herd immunity is 60%, which is plausible, given the recent estimates of 20+% of the NYC population with antibody presence.) It's why exponential growth (for resource limited kinetics) ends up being an S curve and not a runaway exponential curve. The inflection point might not be at exactly 50% for a number of reasons, but it's good for a rough starting point. Additionally, it will be difficult to distinguish if the stay-at-home orders are effective due to the entire population participating, or if it's tied to specific population segments. Meaning the percent of the population active vs stay-at-home isn't independent of transmission numbers. The active sub-population might be closer to herd immunity than the stay-at-home crowd. This gets more complicated as you take into account the risk levels of particular patients. There's potentially a lot more going on. We need some scientific causation, not just correlation.