5 ms·

I would argue that they're all useful but its very tough to be accurate when confounding actions are occurring to the problem. For example, in the US, the incre

by xzel 6y ago

I would argue that they're all useful but its very tough to be accurate when confounding actions are occurring to the problem. For example, in the US, the increase in social distancing measures and mask usage couldn't be easily baked into the original models. Forecasting accurately is very tough. Look at what's been said about Renaissance and its Medallion fund, they're right a little over 50% (they just leverage very heavily). Think about that, the most consistent and dominate hedgefund might only be right about 51% of the time. The issue with just using historical data is the data might be different. But I'm sure all of their models were using data or at least some domain knowledge from the spread in Italy and China.

icelancer 6y ago
>> For example, in the US, the increase in social distancing measures and mask usage couldn't be easily baked into the original models. The IHME model - one of the most cited models - explicitly factored this into their model.
- mattkrause 6y ago
  "Factored in" covers a lot of ground. Here, for reference is the IHME model preprint: https://www.medrxiv.org/content/10.1101/2020.03.27.20043752v1.full.pdf https://www.medrxiv.org/content/10.1101/2020.03.27.20043752v... The parameterization of social distancing is on pages 3-4. They considered four coarse categories of interventions, with the total effect given by a ad hoc score of 1, 0.67, 0.334, or 0. It should be blindingly obvious that can be improved upon with more data and work. Moreover, the effects of social distancing aren't even constant--compliance certainly varies from place to place and over time (enforcement changes, people get restless).
- archgoon 6y ago
  "Starting April 17, we began using mobile phone data to better assess the impact of social distancing across states and countries. These data revealed that social distancing was happening to a larger degree than previously understood, and even before social distancing mandates went into effect." This suggests that social distancing happened 1-2 weeks sooner than their model anticipated. This will give you a much smaller number. What is the policy you believe should have been followed instead? Are you saying that social distancing should have been abandoned? Why do you believe that this would result in fewer deaths?
  - icelancer 6y ago
    No, I am saying they factored it into their models and also undershot their priors that were readily available. If they looked at OpenTable data, they would have realized people were voluntarily socially distancing before state authorities told them they should. In fact, OpenTable data showed that even on the day that the Mayor of NYC told people to go to sit-down restaurants and see movies in person (in early March), y/o/y data showed a net 30% reduction in reservations for restaurants in NYC. People were voluntarily taking precaution well before our government bureaucracies enforced it, and it was available in public datasets. IHME just didn't look hard enough, apparently. Despite what the media keeps pushing by finding pockets of idiots, people aren't stupid. The most at-risk populations realize this and tend to shelter in place on their own and take precautions. de Blasio on March 11th telling people to go out: https://ny.eater.com/2020/3/11/21175497/coronavirus-nyc-restaurants-safe-dine-out https://ny.eater.com/2020/3/11/21175497/coronavirus-nyc-rest... OpenTable data showing a voluntary reduction of restaurant activity despite de Blasio's encouragements: https://ibb.co/r2R9xnT https://ibb.co/r2R9xnT
    - archgoon 6y ago
      What policies are you saying were misguided and should not have been taken based on the predicted elevated death toll? How does one evaluate the OpenTable data and feed it into the model they were using to estimate the amount of social distancing?
      - icelancer 6y ago
        Extended lockdowns are positively correlated with deaths per million residents. https://twitter.com/boriquagato/status/1251943418860728320 https://twitter.com/boriquagato/status/1251943418860728320 I'm saying that lengthy lockdowns, shelter-in-place, and shutting down non-storefront businesses did not provide much value, if any, and possibly had a negative effect. The IHME trended into 95%+ CI territory over half the time. So when posters here say "well the variance was high," that's accounted for in the confidence intervals, which they also missed on wildly. The models justified harsh authoritarian action, and the actual data way, way undershot it. Popular sentiment is "oh well, it saved lives at least" but few, if any, are looking at the acute - and more importantly, chronic - economic costs of these policies that may or may not have even helped beyond just telling people what the risks were. >> How does one evaluate the OpenTable data and feed it into the model they were using to estimate the amount of social distancing? Pretty simple; it was clear that news of COVID-19 alone was enough to cause people to stop going to restaurants and start basic social distancing protocols on their own without government mandating it. EDIT: Shockingly, a bunch of downvotes without explanation are forthcoming.

by xzel 6y ago

icelancer 6y ago

>> For example, in the US, the increase in social distancing measures and mask usage couldn't be easily baked into the original models. The IHME model - one of the most cited models - explicitly factored this into their model.

mattkrause 6y ago
"Factored in" covers a lot of ground. Here, for reference is the IHME model preprint: https://www.medrxiv.org/content/10.1101/2020.03.27.20043752v1.full.pdf https://www.medrxiv.org/content/10.1101/2020.03.27.20043752v... The parameterization of social distancing is on pages 3-4. They considered four coarse categories of interventions, with the total effect given by a ad hoc score of 1, 0.67, 0.334, or 0. It should be blindingly obvious that can be improved upon with more data and work. Moreover, the effects of social distancing aren't even constant--compliance certainly varies from place to place and over time (enforcement changes, people get restless).
archgoon 6y ago
"Starting April 17, we began using mobile phone data to better assess the impact of social distancing across states and countries. These data revealed that social distancing was happening to a larger degree than previously understood, and even before social distancing mandates went into effect." This suggests that social distancing happened 1-2 weeks sooner than their model anticipated. This will give you a much smaller number. What is the policy you believe should have been followed instead? Are you saying that social distancing should have been abandoned? Why do you believe that this would result in fewer deaths?
- icelancer 6y ago
  No, I am saying they factored it into their models and also undershot their priors that were readily available. If they looked at OpenTable data, they would have realized people were voluntarily socially distancing before state authorities told them they should. In fact, OpenTable data showed that even on the day that the Mayor of NYC told people to go to sit-down restaurants and see movies in person (in early March), y/o/y data showed a net 30% reduction in reservations for restaurants in NYC. People were voluntarily taking precaution well before our government bureaucracies enforced it, and it was available in public datasets. IHME just didn't look hard enough, apparently. Despite what the media keeps pushing by finding pockets of idiots, people aren't stupid. The most at-risk populations realize this and tend to shelter in place on their own and take precautions. de Blasio on March 11th telling people to go out: https://ny.eater.com/2020/3/11/21175497/coronavirus-nyc-restaurants-safe-dine-out https://ny.eater.com/2020/3/11/21175497/coronavirus-nyc-rest... OpenTable data showing a voluntary reduction of restaurant activity despite de Blasio's encouragements: https://ibb.co/r2R9xnT https://ibb.co/r2R9xnT
  - archgoon 6y ago
    What policies are you saying were misguided and should not have been taken based on the predicted elevated death toll? How does one evaluate the OpenTable data and feed it into the model they were using to estimate the amount of social distancing?
    - icelancer 6y ago
      Extended lockdowns are positively correlated with deaths per million residents. https://twitter.com/boriquagato/status/1251943418860728320 https://twitter.com/boriquagato/status/1251943418860728320 I'm saying that lengthy lockdowns, shelter-in-place, and shutting down non-storefront businesses did not provide much value, if any, and possibly had a negative effect. The IHME trended into 95%+ CI territory over half the time. So when posters here say "well the variance was high," that's accounted for in the confidence intervals, which they also missed on wildly. The models justified harsh authoritarian action, and the actual data way, way undershot it. Popular sentiment is "oh well, it saved lives at least" but few, if any, are looking at the acute - and more importantly, chronic - economic costs of these policies that may or may not have even helped beyond just telling people what the risks were. >> How does one evaluate the OpenTable data and feed it into the model they were using to estimate the amount of social distancing? Pretty simple; it was clear that news of COVID-19 alone was enough to cause people to stop going to restaurants and start basic social distancing protocols on their own without government mandating it. EDIT: Shockingly, a bunch of downvotes without explanation are forthcoming.