12 ms·

A curve was trending exponential, and flattened with lockdown. What's the alternate scenario for what caused the curve to flatten?

pbhjpbhj 6y ago
A possible alternative - and I'm categorically not saying this is true, not even likely - is that Covid19 is more infectious, and more widely infected people. But, that fewer people were susceptible, so there would be more asymptomatic carriers but fewer people hospitalised. If a virus runs out of people to infect then it will peak. You can prove that scenario wrong by testing (if number of 'already infected' is relatively low then this hypothesis would be wrong and the risk of further peaks is higher; I don't have enough data to attempt to disprove such a hypothesis.
- lbeltrame 6y ago
  This is what (reliable, and I repeat reliable) serological testing might tell us.
deathgrips 6y ago
We raised testing capacity exponentially, but weren't accurately tracking the spread until recently.
deleted 6y ago
[deleted]
downshun 6y ago
Wrong assumptions/data/conclusions from the epidemic model Misattribution of cause
- ceejayoz 6y ago
  Seems like it should be fairly trivial to test. Different countries went into lockdown at different times. When did each one's curve start to flatten in relation to their lockdowns?
  - downshun 6y ago
    'the curve' is based on a model. All models are wrong. No matter how much it is broadcasted.
    - ceejayoz 6y ago
      I'm not referring to the future models, I'm referring to the "how many cases have we confirmed per day" charts. (You could also do it with the excess death charts, given enough time for that data to settle out.) Stuff like https://91-divoc.com/pages/covid-visualization/ https://91-divoc.com/pages/covid-visualization/ and https://www.nytimes.com/interactive/2020/04/21/world/coronavirus-missing-deaths.html https://www.nytimes.com/interactive/2020/04/21/world/coronav....
  - mattkrause 6y ago
    Data from Italy makes for a good head-to-head comparison. Five regions locked down much sooner than their neighbors, and fared, at least initially, much better. Preprint: https://t.co/JYf1F5GnYu?amp=1 https://t.co/JYf1F5GnYu?amp=1 Figure S3 is probably the most relevant.
  - afterburner 6y ago
    We don't know when each country really got their first COVID-19 infections. That will always complicate analysis, and it will never be trivial. Never mind that we don't fully understand the virus itself, it's new.
    - ceejayoz 6y ago
      Use the spikes in excess death rates, then. https://www.nytimes.com/interactive/2020/04/21/world/coronavirus-missing-deaths.html https://www.nytimes.com/interactive/2020/04/21/world/coronav...
      - afterburner 6y ago
        The relationship between the spike and the beginning of spread is changed by the effectiveness of lockdown/other measures. Not to mention other variables like population density, population activity, etc.
djsumdog 6y ago
That SARS-CoV-2 was in our environment for months longer than thought, that 20% or more of Americans may already have antibodies, that tons of people suffered from not being able to get essential heart, dental and other surgery in preparation for some mythical surge that wouldn't have even happened anyway. That there's no evidence social distancing did anything at all? There are tons of other possibilities here. There simply isn't enough data, and won't be until Feb 2021 where we can retroactively look back at data that is cleaned, pruned and properly averaged.
- pbhjpbhj 6y ago
  What data do you think will exist by next year that we don't have now? Doctors have recorded those who died with respiratory distress and other Covid19 symptoms, and that tested positive, as being victims -- that data is here now and shows increased deaths haven't been just to co-morbidities not being treated. Test results are available to those in power. The data is around, it's just not public because - I warrant - politicians can't manipulate the story if the public has the full data.
  - djsumdog 6y ago
    We have never had time series data for any other illness, to this granularity. The data is also terribly dirty. The CDC doesn't track flu. It tracks pneumonia deaths, and then retroactively uses surveillance data to estimate the number of deaths from different infections. U Washington also seems to be using entirely different data sets than Johns Hopkins and the metrics for international data is not the same at all. I did a post on some of the issues I found: https://battlepenguin.com/tech/fighting-with-the-data/ https://battlepenguin.com/tech/fighting-with-the-data/
- esoterica 6y ago
  > That SARS-CoV-2 was in our environment for months longer than thought, that 20% or more of Americans may already have antibodies It's generally a good habit to do a little bit of simple arithmetic to see if the claims you are making pass a basic sanity check. If 20% of Americans already have antibodies, then how come NYC has 10x as many deaths per capita as the rest of the country? Did 200% of New Yorkers get infected?
JackFr 6y ago
The curve will always flatten lockdown or no. It can't be exponential forever.
- deleted 6y ago
  [deleted]
deleted 6y ago
[deleted]
tathougies 6y ago
> A curve was trending exponential, and flattened with lockdown. What's the alternate scenario for what caused the curve to flatten? You cannot honestly believe this. 'Trending exponential' is such a useless buzzword. Exponential growth is only scary depending on the exponent itself. Our models on what that exponent were were absolutely, completely off by orders of magnitude. Just look at Sweden, they were estimating 40k deaths by now and only have three thousand something. Certainly, early action helped flatten the curve, but the original estimates for what the curve would be were incredibly off. There was no overwhelming of hospitals in the US at all, despite warnings that they were imminent, even with behavioral changes. Our country's scientific advisers need to look inward at this point and figure out what went wrong with the models.

pbhjpbhj 6y ago

A possible alternative - and I'm categorically not saying this is true, not even likely - is that Covid19 is more infectious, and more widely infected people. But, that fewer people were susceptible, so there would be more asymptomatic carriers but fewer people hospitalised. If a virus runs out of people to infect then it will peak. You can prove that scenario wrong by testing (if number of 'already infected' is relatively low then this hypothesis would be wrong and the risk of further peaks is higher; I don't have enough data to attempt to disprove such a hypothesis.

lbeltrame 6y ago
This is what (reliable, and I repeat reliable) serological testing might tell us.

deathgrips 6y ago

We raised testing capacity exponentially, but weren't accurately tracking the spread until recently.

deleted 6y ago

[deleted]

downshun 6y ago

Wrong assumptions/data/conclusions from the epidemic model Misattribution of cause

ceejayoz 6y ago
Seems like it should be fairly trivial to test. Different countries went into lockdown at different times. When did each one's curve start to flatten in relation to their lockdowns?
- downshun 6y ago
  'the curve' is based on a model. All models are wrong. No matter how much it is broadcasted.
  - ceejayoz 6y ago
    I'm not referring to the future models, I'm referring to the "how many cases have we confirmed per day" charts. (You could also do it with the excess death charts, given enough time for that data to settle out.) Stuff like https://91-divoc.com/pages/covid-visualization/ https://91-divoc.com/pages/covid-visualization/ and https://www.nytimes.com/interactive/2020/04/21/world/coronavirus-missing-deaths.html https://www.nytimes.com/interactive/2020/04/21/world/coronav....
- mattkrause 6y ago
  Data from Italy makes for a good head-to-head comparison. Five regions locked down much sooner than their neighbors, and fared, at least initially, much better. Preprint: https://t.co/JYf1F5GnYu?amp=1 https://t.co/JYf1F5GnYu?amp=1 Figure S3 is probably the most relevant.
- afterburner 6y ago
  We don't know when each country really got their first COVID-19 infections. That will always complicate analysis, and it will never be trivial. Never mind that we don't fully understand the virus itself, it's new.
  - ceejayoz 6y ago
    Use the spikes in excess death rates, then. https://www.nytimes.com/interactive/2020/04/21/world/coronavirus-missing-deaths.html https://www.nytimes.com/interactive/2020/04/21/world/coronav...
    - afterburner 6y ago
      The relationship between the spike and the beginning of spread is changed by the effectiveness of lockdown/other measures. Not to mention other variables like population density, population activity, etc.

djsumdog 6y ago

That SARS-CoV-2 was in our environment for months longer than thought, that 20% or more of Americans may already have antibodies, that tons of people suffered from not being able to get essential heart, dental and other surgery in preparation for some mythical surge that wouldn't have even happened anyway. That there's no evidence social distancing did anything at all? There are tons of other possibilities here. There simply isn't enough data, and won't be until Feb 2021 where we can retroactively look back at data that is cleaned, pruned and properly averaged.

pbhjpbhj 6y ago
What data do you think will exist by next year that we don't have now? Doctors have recorded those who died with respiratory distress and other Covid19 symptoms, and that tested positive, as being victims -- that data is here now and shows increased deaths haven't been just to co-morbidities not being treated. Test results are available to those in power. The data is around, it's just not public because - I warrant - politicians can't manipulate the story if the public has the full data.
- djsumdog 6y ago
  We have never had time series data for any other illness, to this granularity. The data is also terribly dirty. The CDC doesn't track flu. It tracks pneumonia deaths, and then retroactively uses surveillance data to estimate the number of deaths from different infections. U Washington also seems to be using entirely different data sets than Johns Hopkins and the metrics for international data is not the same at all. I did a post on some of the issues I found: https://battlepenguin.com/tech/fighting-with-the-data/ https://battlepenguin.com/tech/fighting-with-the-data/
esoterica 6y ago
> That SARS-CoV-2 was in our environment for months longer than thought, that 20% or more of Americans may already have antibodies It's generally a good habit to do a little bit of simple arithmetic to see if the claims you are making pass a basic sanity check. If 20% of Americans already have antibodies, then how come NYC has 10x as many deaths per capita as the rest of the country? Did 200% of New Yorkers get infected?

JackFr 6y ago

The curve will always flatten lockdown or no. It can't be exponential forever.

deleted 6y ago
[deleted]

deleted 6y ago

[deleted]

tathougies 6y ago

> A curve was trending exponential, and flattened with lockdown. What's the alternate scenario for what caused the curve to flatten? You cannot honestly believe this. 'Trending exponential' is such a useless buzzword. Exponential growth is only scary depending on the exponent itself. Our models on what that exponent were were absolutely, completely off by orders of magnitude. Just look at Sweden, they were estimating 40k deaths by now and only have three thousand something. Certainly, early action helped flatten the curve, but the original estimates for what the curve would be were incredibly off. There was no overwhelming of hospitals in the US at all, despite warnings that they were imminent, even with behavioral changes. Our country's scientific advisers need to look inward at this point and figure out what went wrong with the models.