11 ms·

The Metric We Need to Manage Covid-19

209 points by sethbannon 7y ago

zuhayeer 7y ago
Jupyter notebook for this available here: https://github.com/k-sys/covid-19/blob/master/Realtime%20R0.ipynb https://github.com/k-sys/covid-19/blob/master/Realtime%20R0....
drtillberg 7y ago
I would be really impressed if it were possible to control for the differences that would occur if one state did a very good job tracing potential cases and then testing them (Massachusetts), versus more ordinary blanket efforts elsewhere.
- corpMaverick 7y ago
  I think we will see the overall work when we look at deaths. It is lagging though.
  - CydeWeys 7y ago
    The author needs to re-run the analysis using only deaths, or deaths plus hospitalizations (if those figures are available). I fear that all the model reveals as currently written is how well states are getting a handle on their testing, and paradoxically showing states with better testing as worse off because of the growing number of cases.
justlexi93 7y ago
It is hard to tell if this will even work since a lot of people all around the world can't even follow the simple rule of not going out and just staying at home.
MiguelVieira 7y ago
This site does this https://epiforecasts.io/covid/posts/national/united-states/ https://epiforecasts.io/covid/posts/national/united-states/
- demirev 7y ago
  Some great work here - I am surprised I haven't seen this one before.
- alkonaut 7y ago
  This site also uses "confirmed cases" instead of deaths. That would be useful many weeks ago, but now in most countries it's no longer a useful number. It should use deaths and a country specific reporting factor for e.g. whether deaths include only hospital deaths or also other deaths, if only deaths with positive tests or includes assumed Covid deaths.
corpMaverick 7y ago
For lack of better charts. I have been calculating by hand the number of days since total cases(or deaths) were half as they are today. Example there are 586k cases today. How many days ago we had 290k ? Almost 10 days. So it is still doubling, but not as fast. A week ago it was doubling every 7 days.
- Taek 7y ago
  I've been following the the death rate, because I think deaths are probably a more accurate statistic than cases - less likely that a covid19 death goes unreported. This of course is a significantly lagging indicator, but it has been long enough that we can see social distancing is working.
  - _bxg1 7y ago
    > less likely that a covid19 death goes unreported I don't think this is true at all. Many people die at home. Many die without having ever been officially tested. I've read that in some places the death toll is only counted from those who were tested and then died in a hospital.
    - MikeAmelung 7y ago
      It's definitely still "less likely" that a death goes unreported versus an infection without a death. Both numbers are shit, but deaths likely less so.
      - aledalgrande 7y ago
        I think deaths might be unreliable too, because 1) we don't know the mortality rate, we're extrapolating it from bad data and then using an extrapolated number to calculate a trend and 2) mortality rate would change between different groups, e.g. sick and old people vs healthy people, depending how infections spread.
        spuz 7y ago
zaroth 7y ago
How can a confidence interval possibly be calculated without accounting for the number of tests—not just the number of positive tests—and the total population size? What TFA shows us is the Rt assuming that all cases are known. The model which knows nothing about testing rate, cannot possibly be used to predict R0 or Rt. As a simple proof, consider what the model would output I f testing simply stopped. 0 out of 0 tests positive. After several days, the model outputs an Rt=0 with 100% confidence. If you could account for testing rate, and then attempt to account for missed cases through proxies using hospitalization rates, ILI surveillance data, excess fatality, as well as incubation period, and an asymptomatic rate... maybe then you could draw error bars around an estimate of Rt that would pass the smell test? If testing was run against 1,000 randomly selected people per geographical area each day, with a positivity rate reported over time, that would provide the perfect basis for making these calculations. The time series of test results that we actually have today require enormous amounts of unpacking before they can be used safely to extrapolate much of anything.
- richk449 7y ago
  Rt is based on the rate of change, not the absolute value, right? So if testing coverage is constant in time, then doesn’t it drop out? Of course, it isn’t constant with time, but it is also probably not changing that drastically over short time frames (like the seven days the author uses), so it shouldn’t throw the results off too much.
  - zaroth 7y ago
    Even if the number of tests stay the same, but just the testing criteria shift over time, it would invalidate the daily positive test count for use in determining Rt without somehow adjusting for the resulting bias.
- lolc 7y ago
  At first I was happy to see a confidence interval in the plot. Then I realized the plots are based on the same numbers anybody else uses: new cases. I'm tired of people stretching the available numbers too thin. There is only so much information we can get out of them. And yes like you say I hope we will see daily sampling soon. As tests are geared up that should be easy enough. As an aside: The RKI in Germany is collecting weekly samples to track the flu. They have been testing for Corona now for eight weeks. In those tests, they found 11 positive samples out of 1089. I don't know the reliability of the tests though. The numbers are certainly too small to estimate noise after eight weeks.
deleted 7y ago
[deleted]
squidproquo 7y ago
Interesting article. In late March I built a simple SEIRD model for a few US states with python. It was very difficult to estimate R0. R0 is essentially Beta/Gamma, where Beta^-1 is is time between contacts and Gamma^-1 is the time until recovery. I think what should be added to this analysis is population density. Each state has a different rate that people come into contact with one another. It would make sense that R0 in NYC is much higher than in Iowa. Also this website is crowdsourcing US COVID-19 mortality forecasts if anyone is into data modeling: https://www.unitarity.com/app/challenges/us-coronavirus-outbreak/events/apr-20 https://www.unitarity.com/app/challenges/us-coronavirus-outb... This website
glofish 7y ago
Now ask yourself - do you believe that Louisiana has a more stringent, more accepted and more enforced lockdown than say Massachusetts or Pennsylvania? Yet the epidemic seems to slow more drastically in Lousiana than most other states. Why is that? Investigating that seems to be more fruitful avenue. Perhaps there is more validity to the initial theory that the virus is a lot less virulent in high humidity and heat. Many more observations seem to back that. Low number of cases in India or Brazil etc.
- knzhou 7y ago
  You're cherry-picking. Louisiana is on the low side, but Alabama, Texas, and Georgia are on the high side. In noisy and unreliable data it's always possible to pick a single data point that supports any desired conclusion. I'd say that all we can conclude is that everybody should stay vigilant.
  - guscost 7y ago
    Like from a few weeks back, the conclusion that COVID-19 will kill 10% of people who contract it, based on the testing from one town in northern Italy.
  - doodlebugging 7y ago
    >In noisy and unreliable data it's always possible to pick a single data point that supports any desired conclusion. Reminds me of the Principle of Propaganda - You can prove anything if you ignore enough facts or data.
  - jsight 7y ago
    I've been following Georgia's data for a while now, and I actually think they are closer to Louisiana than you realize. Over the last few weeks, it wasn't unusual to see counties stop growing for days at a time only to suddenly jump by 20-30%. I think there are effects being seen from the lack of early testing rather than an indication of recent spread during the (very recent) higher temperatures.
- r00fus 7y ago
birdyrooster 7y ago
I also would like to see this broken down by city because the state highly dilutes the signal when trying to rate the responses of major metropolitan governments.
johnchristopher 7y ago
Totally off-topic: interesting, it's the first usage of the default 2020 wordpress theme I see in the wild.
caseyf7 7y ago
So cool to see Kevin doing a deep dive on this crisis with the goal of making an impact. It says a lot about his character that he chooses to spend his time doing this.
- gpu_explorer 7y ago
  But also I think that it's tiresome for people without background in study of disease (or long experience like Bill Gates) to get involved. Not only this but it can be dangerous with any area like diseases. This is the same as problem that you see in the White House of America with this son-in-law of president. Systrom has no experience with infectious diseases or study of diseases (or I did not hear about it yet and he does not say about it), and human society needs very much people who are experts right now. Maybe Systrom could also use tech to help as this is his area of expertise.
dan-robertson 7y ago
If you look at test results you probably won’t learn much. There will be far fewer tests than cases and most cases will never be tested. It seems more likely that you’ll just be measuring some other effect of how testing is done, for example if the number of tests per day ramps up slowly (and non exponentially) then it seems likely that you will observe Rt to be decreasing (as the number of confirmed cases isn’t shooting up), especially if people are mostly only tested when they turn up in hospital and are expected to be positive. I don’t know how much the author’s model accounts for that but I find the confidence intervals very unconvincing. I would expect them to be much larger. This study tries to estimate Rt in several European countries from the death rates though there are issues with those statistics too: https://imperialcollegelondon.github.io/covid19estimates/ https://imperialcollegelondon.github.io/covid19estimates/
- ulfw 7y ago
  You're spot on. Kevin's idea and graphs are nice but they rely on a flawed hypothesis, namely that all states test the same way, taste the same amount per capita etc. They don't. So our graphs can only be as good as the numbers we put in and testing is still very insufficient.
- henrikschroder 7y ago
  I saw an interesting alternate statistics where you measure the overall mortality rate and compare to previous years. EU only, but something like this might exist elsewhere as well: http://euromomo.eu/ http://euromomo.eu/ The data lags behind a bit, but since it measures total number of deaths, it doesn't matter if different countries measure coronoa-related deaths differently. Everyone measures actual deaths. The numbers are hard to fudge for politicians who wants to boost their results. As a bonus, this also measures how your society is handling the pandemic overall. We know that people will die of the lockdowns as a second-order or third-order effect, and this way we can measure that as well.
  - OscarCunningham 7y ago
    The lockdowns will also reduce deaths from other contagious diseases and accidents, particularly car crashes.
_nalply 7y ago
Edit: Sorry, I made a mistake. Trying to measure Rt seems to be a good idea. However it's not clear how the proposal calculates Rt. No formulas and no references to raw data. So I am afraid this is not very useful. This said, I could imagine that an approach which takes the number of confirmed cases and the total number of tests could work to estimate Rt. The idea is that while the number of cases is not a good estimator we can try to get a better estimator using the number of tests as well. It's a bit tricky, however, because a low number of tests could mean that only the probable cases are tested which skews the numbers.
- Aeolun 7y ago
  Did you miss the link to the notebook containing all the code and calculations?
  - _nalply 7y ago
    Yes, I goofed up. Sorry.
LatteLazy 7y ago
It's really too late to manage this. Testing hasn't been made available in time mostly due to total failure to plan and political decisions not to manage any of this. All we can do now is turn up and down the level of isolation depending on how many ventilators and ICU beds are available. We will have to do that on a sort of feedback, trial and error basis because we lack capacity and what capacity we do have is being wasted. The only question is whether anyone will be held accountable for this colossal mess and the preventable deaths its caused, or if we will just accept this happening ever 5 or so years...
- arrrg 7y ago
  Depends. If active cases can be pushed down to a mange-able level (i.e. a level where contact tracing is a realistic option and outbreaks can be, by and large, contained) a return to relative normalcy could still be possible. So that’s another one, two months of tight lockdown to push down active cases (to, say, 500 in the NY area). Then it becomes feasible to throw massive amounts of people at those 500 cases and to do aggressive contact tracing and quarantining of all contacts. Maybe just by people interviewing the infected, calling around, playing detective (a bit slow), maybe also with the help of contact tracing through mobile phones. Also, you obviously would need to be able to test for the virus (ideally) whenever someone shows the slightest hint of related symptoms (and since those are so unspecific and not exactly rare you would have to expand testing capability). Some measures will obviously stay in place, but many of the most drastic and impactful ones could be reduced since there wouldn’t really be uncontrollable community spread. That, to me, sounds like a realistic plan (unlike a complete lockdown until then or trying to let the wave wash over us) for the time until we have a vaccine and until that vaccine is availible in sufficient quantities. Of course, this depends a lot on whether we can push down active cases so low. South Korea seems to be nearly or already there. Of course we do not know whether China tells the complete truth, but even if they lie quite a bit they are also probably nearly or already there. Outbreaks with exponential growth haven’t happened there at least, of that we can be relatively certain (because that would be hard to hide). So, yeah, it’s probably possible if we can push effective R a bit below zero for a couple of weeks to get into a position where we can regain control. Maybe. Hopefully.
KaiserPro 7y ago
Again, much as these are pretty, without decent test data, they are a sideshow. The emphasis really should now be on proper sampling of a cross section of the population. That should really be weekly testing of 1000 or more, over a range of backgrounds and wealth. Only then can we really see the impact. Using mortality is only really useful when we know what the r0 is, or the mortality rate. We don't know either.
- lukeschlather 7y ago
  Looks like we're testing 10000 a day on weekdays, and over 5000 on weekends. I find it difficult to believe with all that testing going on that no one is reserving 3% of the weekly tests to do proper estimation as you suggest. https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/testing-in-us.html https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/test...
  - ceejayoz 7y ago
    Locally (upstate NY) per our pediatrician they're only testing people with symptoms bad enough to put them at risk of hospitalization. We're still very short.
    - lukeschlather 7y ago
      Isn't that what you would expect any clinician to say, even if they were doing sampling? They're not going to use people asking for tests, they're going to select a group of people at random from the general population and invite them to be tested. Everyone else who has no symptoms they're going to politely say they're not testing people with no symptoms.
      - ceejayoz 7y ago
        The point is that tests are still in extremely short supply, at least around here.
  - KaiserPro 7y ago
standardUser 7y ago
Are there similar calculations for European countries? Several countries are easing lockdowns based on the idea that the transmission rate has become manageable. I'd love to see how those numbers stack up to US states. EDIT: Turns out there is... https://epiforecasts.io/covid/posts/global/ https://epiforecasts.io/covid/posts/global/
jrd79 7y ago
Your second rank ordering chart, the one by the upper bound of Rt, is deceptive and misleading. North Dakota and Arkansas only have a high upper bound because there are so few cases that the uncertainty is high. That chart and any analysis associated with it are completely without merit.
nabla9 7y ago
Without systematic random testing these numbers are describing testing activity, not effective reproductive rate. Infection rate is not the same as number of cases.
cityzen 7y ago
Does having a popular mobile app make people scientists? This elitist shit is annoying. I would much rather see him write up something about how he is distributing his wealth to help with the coronavirus rather than this stuff.
- dna_polymerase 7y ago
  He sold Instagram years ago, so it's no longer his. Also, instead of blindly launching an ad hominem attack against him, judge the article on its contents. Of course, having success in one area doesn't mean he is an expert in another, but it doesn't exclude the possibility as well.
usaar333 7y ago
Good post discussing Rt (rarely brought up), but a few points are lacking: * in the face of increasing (and volatile) testing capacity, Rt is being significantly over-estimated by looking at case counts. It's improbable CA still had an Rt above 1 the first week of April with covid deaths linear by the second week. More likely Rt was 1 about a week after the SIP (late march). * Ignoring "herd immunity" effects of Rt. Some of the "under control" states (NY, Louisiana) have had very high infection rates which in their own end has dropped Rt down. NYC is a strong example of this - with > 20% of the city having been infected, well, Rt will drop dramatically just by so many contacts already having immunity. * Implying this argues for states locking down now. I agree there is heavy evidence favoring lockdowns weeks ago to have avoided many deaths, but at this point, any lockdown is going to take a week to have an impact on even confirmed cases. The most susceptible populations (essential workers) are the very ones exempted from lockdowns (and less susceptible ones have already voluntarily socially distanced), so there's likely not much gain to be had. Sweden is conveniently our low density control group using mostly voluntary measures (WA State is similar through March 23) and its peak passing a week ago is a sign that Rt drops under 1 faster than you think.

209 points by sethbannon 7y ago

Jupyter notebook for this available here: https://github.com/k-sys/covid-19/blob/master/Realtime%20R0.ipynb https://github.com/k-sys/covid-19/blob/master/Realtime%20R0....

drtillberg 7y ago

I would be really impressed if it were possible to control for the differences that would occur if one state did a very good job tracing potential cases and then testing them (Massachusetts), versus more ordinary blanket efforts elsewhere.

corpMaverick 7y ago
I think we will see the overall work when we look at deaths. It is lagging though.
- CydeWeys 7y ago
  The author needs to re-run the analysis using only deaths, or deaths plus hospitalizations (if those figures are available). I fear that all the model reveals as currently written is how well states are getting a handle on their testing, and paradoxically showing states with better testing as worse off because of the growing number of cases.

justlexi93 7y ago

It is hard to tell if this will even work since a lot of people all around the world can't even follow the simple rule of not going out and just staying at home.

MiguelVieira 7y ago

This site does this https://epiforecasts.io/covid/posts/national/united-states/ https://epiforecasts.io/covid/posts/national/united-states/

demirev 7y ago
Some great work here - I am surprised I haven't seen this one before.
alkonaut 7y ago
This site also uses "confirmed cases" instead of deaths. That would be useful many weeks ago, but now in most countries it's no longer a useful number. It should use deaths and a country specific reporting factor for e.g. whether deaths include only hospital deaths or also other deaths, if only deaths with positive tests or includes assumed Covid deaths.

corpMaverick 7y ago

For lack of better charts. I have been calculating by hand the number of days since total cases(or deaths) were half as they are today. Example there are 586k cases today. How many days ago we had 290k ? Almost 10 days. So it is still doubling, but not as fast. A week ago it was doubling every 7 days.

Taek 7y ago
I've been following the the death rate, because I think deaths are probably a more accurate statistic than cases - less likely that a covid19 death goes unreported. This of course is a significantly lagging indicator, but it has been long enough that we can see social distancing is working.
- _bxg1 7y ago
  > less likely that a covid19 death goes unreported I don't think this is true at all. Many people die at home. Many die without having ever been officially tested. I've read that in some places the death toll is only counted from those who were tested and then died in a hospital.
  - MikeAmelung 7y ago
    It's definitely still "less likely" that a death goes unreported versus an infection without a death. Both numbers are shit, but deaths likely less so.
    - aledalgrande 7y ago
      I think deaths might be unreliable too, because 1) we don't know the mortality rate, we're extrapolating it from bad data and then using an extrapolated number to calculate a trend and 2) mortality rate would change between different groups, e.g. sick and old people vs healthy people, depending how infections spread.
      - spuz 7y ago

zaroth 7y ago

How can a confidence interval possibly be calculated without accounting for the number of tests—not just the number of positive tests—and the total population size? What TFA shows us is the Rt assuming that all cases are known. The model which knows nothing about testing rate, cannot possibly be used to predict R0 or Rt. As a simple proof, consider what the model would output I f testing simply stopped. 0 out of 0 tests positive. After several days, the model outputs an Rt=0 with 100% confidence. If you could account for testing rate, and then attempt to account for missed cases through proxies using hospitalization rates, ILI surveillance data, excess fatality, as well as incubation period, and an asymptomatic rate... maybe then you could draw error bars around an estimate of Rt that would pass the smell test? If testing was run against 1,000 randomly selected people per geographical area each day, with a positivity rate reported over time, that would provide the perfect basis for making these calculations. The time series of test results that we actually have today require enormous amounts of unpacking before they can be used safely to extrapolate much of anything.

richk449 7y ago
Rt is based on the rate of change, not the absolute value, right? So if testing coverage is constant in time, then doesn’t it drop out? Of course, it isn’t constant with time, but it is also probably not changing that drastically over short time frames (like the seven days the author uses), so it shouldn’t throw the results off too much.
- zaroth 7y ago
  Even if the number of tests stay the same, but just the testing criteria shift over time, it would invalidate the daily positive test count for use in determining Rt without somehow adjusting for the resulting bias.
lolc 7y ago
At first I was happy to see a confidence interval in the plot. Then I realized the plots are based on the same numbers anybody else uses: new cases. I'm tired of people stretching the available numbers too thin. There is only so much information we can get out of them. And yes like you say I hope we will see daily sampling soon. As tests are geared up that should be easy enough. As an aside: The RKI in Germany is collecting weekly samples to track the flu. They have been testing for Corona now for eight weeks. In those tests, they found 11 positive samples out of 1089. I don't know the reliability of the tests though. The numbers are certainly too small to estimate noise after eight weeks.

deleted 7y ago

[deleted]

squidproquo 7y ago

Interesting article. In late March I built a simple SEIRD model for a few US states with python. It was very difficult to estimate R0. R0 is essentially Beta/Gamma, where Beta^-1 is is time between contacts and Gamma^-1 is the time until recovery. I think what should be added to this analysis is population density. Each state has a different rate that people come into contact with one another. It would make sense that R0 in NYC is much higher than in Iowa. Also this website is crowdsourcing US COVID-19 mortality forecasts if anyone is into data modeling: https://www.unitarity.com/app/challenges/us-coronavirus-outbreak/events/apr-20 https://www.unitarity.com/app/challenges/us-coronavirus-outb... This website

glofish 7y ago

Now ask yourself - do you believe that Louisiana has a more stringent, more accepted and more enforced lockdown than say Massachusetts or Pennsylvania? Yet the epidemic seems to slow more drastically in Lousiana than most other states. Why is that? Investigating that seems to be more fruitful avenue. Perhaps there is more validity to the initial theory that the virus is a lot less virulent in high humidity and heat. Many more observations seem to back that. Low number of cases in India or Brazil etc.

knzhou 7y ago
You're cherry-picking. Louisiana is on the low side, but Alabama, Texas, and Georgia are on the high side. In noisy and unreliable data it's always possible to pick a single data point that supports any desired conclusion. I'd say that all we can conclude is that everybody should stay vigilant.
- guscost 7y ago
  Like from a few weeks back, the conclusion that COVID-19 will kill 10% of people who contract it, based on the testing from one town in northern Italy.
- doodlebugging 7y ago
  >In noisy and unreliable data it's always possible to pick a single data point that supports any desired conclusion. Reminds me of the Principle of Propaganda - You can prove anything if you ignore enough facts or data.
- jsight 7y ago
  I've been following Georgia's data for a while now, and I actually think they are closer to Louisiana than you realize. Over the last few weeks, it wasn't unusual to see counties stop growing for days at a time only to suddenly jump by 20-30%. I think there are effects being seen from the lack of early testing rather than an indication of recent spread during the (very recent) higher temperatures.
r00fus 7y ago

birdyrooster 7y ago

I also would like to see this broken down by city because the state highly dilutes the signal when trying to rate the responses of major metropolitan governments.

johnchristopher 7y ago

Totally off-topic: interesting, it's the first usage of the default 2020 wordpress theme I see in the wild.

caseyf7 7y ago

So cool to see Kevin doing a deep dive on this crisis with the goal of making an impact. It says a lot about his character that he chooses to spend his time doing this.

gpu_explorer 7y ago
But also I think that it's tiresome for people without background in study of disease (or long experience like Bill Gates) to get involved. Not only this but it can be dangerous with any area like diseases. This is the same as problem that you see in the White House of America with this son-in-law of president. Systrom has no experience with infectious diseases or study of diseases (or I did not hear about it yet and he does not say about it), and human society needs very much people who are experts right now. Maybe Systrom could also use tech to help as this is his area of expertise.

dan-robertson 7y ago

If you look at test results you probably won’t learn much. There will be far fewer tests than cases and most cases will never be tested. It seems more likely that you’ll just be measuring some other effect of how testing is done, for example if the number of tests per day ramps up slowly (and non exponentially) then it seems likely that you will observe Rt to be decreasing (as the number of confirmed cases isn’t shooting up), especially if people are mostly only tested when they turn up in hospital and are expected to be positive. I don’t know how much the author’s model accounts for that but I find the confidence intervals very unconvincing. I would expect them to be much larger. This study tries to estimate Rt in several European countries from the death rates though there are issues with those statistics too: https://imperialcollegelondon.github.io/covid19estimates/ https://imperialcollegelondon.github.io/covid19estimates/

ulfw 7y ago
You're spot on. Kevin's idea and graphs are nice but they rely on a flawed hypothesis, namely that all states test the same way, taste the same amount per capita etc. They don't. So our graphs can only be as good as the numbers we put in and testing is still very insufficient.
henrikschroder 7y ago
I saw an interesting alternate statistics where you measure the overall mortality rate and compare to previous years. EU only, but something like this might exist elsewhere as well: http://euromomo.eu/ http://euromomo.eu/ The data lags behind a bit, but since it measures total number of deaths, it doesn't matter if different countries measure coronoa-related deaths differently. Everyone measures actual deaths. The numbers are hard to fudge for politicians who wants to boost their results. As a bonus, this also measures how your society is handling the pandemic overall. We know that people will die of the lockdowns as a second-order or third-order effect, and this way we can measure that as well.
- OscarCunningham 7y ago
  The lockdowns will also reduce deaths from other contagious diseases and accidents, particularly car crashes.

_nalply 7y ago

Edit: Sorry, I made a mistake. Trying to measure Rt seems to be a good idea. However it's not clear how the proposal calculates Rt. No formulas and no references to raw data. So I am afraid this is not very useful. This said, I could imagine that an approach which takes the number of confirmed cases and the total number of tests could work to estimate Rt. The idea is that while the number of cases is not a good estimator we can try to get a better estimator using the number of tests as well. It's a bit tricky, however, because a low number of tests could mean that only the probable cases are tested which skews the numbers.

Aeolun 7y ago
Did you miss the link to the notebook containing all the code and calculations?
- _nalply 7y ago
  Yes, I goofed up. Sorry.

LatteLazy 7y ago

It's really too late to manage this. Testing hasn't been made available in time mostly due to total failure to plan and political decisions not to manage any of this. All we can do now is turn up and down the level of isolation depending on how many ventilators and ICU beds are available. We will have to do that on a sort of feedback, trial and error basis because we lack capacity and what capacity we do have is being wasted. The only question is whether anyone will be held accountable for this colossal mess and the preventable deaths its caused, or if we will just accept this happening ever 5 or so years...

arrrg 7y ago
Depends. If active cases can be pushed down to a mange-able level (i.e. a level where contact tracing is a realistic option and outbreaks can be, by and large, contained) a return to relative normalcy could still be possible. So that’s another one, two months of tight lockdown to push down active cases (to, say, 500 in the NY area). Then it becomes feasible to throw massive amounts of people at those 500 cases and to do aggressive contact tracing and quarantining of all contacts. Maybe just by people interviewing the infected, calling around, playing detective (a bit slow), maybe also with the help of contact tracing through mobile phones. Also, you obviously would need to be able to test for the virus (ideally) whenever someone shows the slightest hint of related symptoms (and since those are so unspecific and not exactly rare you would have to expand testing capability). Some measures will obviously stay in place, but many of the most drastic and impactful ones could be reduced since there wouldn’t really be uncontrollable community spread. That, to me, sounds like a realistic plan (unlike a complete lockdown until then or trying to let the wave wash over us) for the time until we have a vaccine and until that vaccine is availible in sufficient quantities. Of course, this depends a lot on whether we can push down active cases so low. South Korea seems to be nearly or already there. Of course we do not know whether China tells the complete truth, but even if they lie quite a bit they are also probably nearly or already there. Outbreaks with exponential growth haven’t happened there at least, of that we can be relatively certain (because that would be hard to hide). So, yeah, it’s probably possible if we can push effective R a bit below zero for a couple of weeks to get into a position where we can regain control. Maybe. Hopefully.

KaiserPro 7y ago

Again, much as these are pretty, without decent test data, they are a sideshow. The emphasis really should now be on proper sampling of a cross section of the population. That should really be weekly testing of 1000 or more, over a range of backgrounds and wealth. Only then can we really see the impact. Using mortality is only really useful when we know what the r0 is, or the mortality rate. We don't know either.

lukeschlather 7y ago
Looks like we're testing 10000 a day on weekdays, and over 5000 on weekends. I find it difficult to believe with all that testing going on that no one is reserving 3% of the weekly tests to do proper estimation as you suggest. https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/testing-in-us.html https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/test...
- ceejayoz 7y ago
  Locally (upstate NY) per our pediatrician they're only testing people with symptoms bad enough to put them at risk of hospitalization. We're still very short.
  - lukeschlather 7y ago
    Isn't that what you would expect any clinician to say, even if they were doing sampling? They're not going to use people asking for tests, they're going to select a group of people at random from the general population and invite them to be tested. Everyone else who has no symptoms they're going to politely say they're not testing people with no symptoms.
    - ceejayoz 7y ago
      The point is that tests are still in extremely short supply, at least around here.
- KaiserPro 7y ago

standardUser 7y ago

Are there similar calculations for European countries? Several countries are easing lockdowns based on the idea that the transmission rate has become manageable. I'd love to see how those numbers stack up to US states. EDIT: Turns out there is... https://epiforecasts.io/covid/posts/global/ https://epiforecasts.io/covid/posts/global/

jrd79 7y ago

Your second rank ordering chart, the one by the upper bound of Rt, is deceptive and misleading. North Dakota and Arkansas only have a high upper bound because there are so few cases that the uncertainty is high. That chart and any analysis associated with it are completely without merit.

nabla9 7y ago

Without systematic random testing these numbers are describing testing activity, not effective reproductive rate. Infection rate is not the same as number of cases.

cityzen 7y ago

Does having a popular mobile app make people scientists? This elitist shit is annoying. I would much rather see him write up something about how he is distributing his wealth to help with the coronavirus rather than this stuff.

dna_polymerase 7y ago
He sold Instagram years ago, so it's no longer his. Also, instead of blindly launching an ad hominem attack against him, judge the article on its contents. Of course, having success in one area doesn't mean he is an expert in another, but it doesn't exclude the possibility as well.

usaar333 7y ago

Good post discussing Rt (rarely brought up), but a few points are lacking: * in the face of increasing (and volatile) testing capacity, Rt is being significantly over-estimated by looking at case counts. It's improbable CA still had an Rt above 1 the first week of April with covid deaths linear by the second week. More likely Rt was 1 about a week after the SIP (late march). * Ignoring "herd immunity" effects of Rt. Some of the "under control" states (NY, Louisiana) have had very high infection rates which in their own end has dropped Rt down. NYC is a strong example of this - with > 20% of the city having been infected, well, Rt will drop dramatically just by so many contacts already having immunity. * Implying this argues for states locking down now. I agree there is heavy evidence favoring lockdowns weeks ago to have avoided many deaths, but at this point, any lockdown is going to take a week to have an impact on even confirmed cases. The most susceptible populations (essential workers) are the very ones exempted from lockdowns (and less susceptible ones have already voluntarily socially distanced), so there's likely not much gain to be had. Sweden is conveniently our low density control group using mostly voluntary measures (WA State is similar through March 23) and its peak passing a week ago is a sign that Rt drops under 1 faster than you think.