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Thinking "its not accurate enough" should not EVER be a reason to decide not to try something that could potentually help in this unprecedented situation. It ma

Thinking "its not accurate enough" should not EVER be a reason to decide not to try something that could potentually help in this unprecedented situation. It may well not work well enough but we won't know unless we try! Each individual incremental activity, process, treatment, protection or APP that takes us a little closer to successfully fighting this thing should be done and done in conjunction with the others.

eli 7y ago
Especially when you have no particular knowledge or citations as to what an appropriate standard for "enough" might be.
- deeringc 7y ago
  Exactly - I have huge respect for Bruce Schneier when it comes to matters relating to cryptography. But apart from commenting on the security, privacy and other technical aspects of these apps, I'm not sure on which authority he's giving these opinions on matters relating to epidemiology. At very least I'd like him to give some supporting scientific citations. But as it stands, Bruce's opinion on the medical and public health efficacy of these apps is no more valuable than yours or mine.
kxyvr 7y ago
Actually, yes it should, but it depends on the numbers and this is a well studied area of statistics. One of the many issues is whether or not someone who flags positive is actually positive and whether someone who flags negative is actually negative. This depends not only the sensitivity (if someone is sick, will they flag positive) and specificity (if someone is healthy, will they flag negative), but on how prevalent a disease is within a population. That last quantity is constantly changing, which also means that this calculation is constantly changing, which can and should affect policy. Now, the issue is that if you start telling a bunch of healthy people that they're actually sick and want them to quarantine or that a bunch of sick people are actually healthy and that they're free to go there are consequences. One, people will lose faith in the system and stop listening at all. Two, healthy people who work in an essential area can now not actually do their job. Three, sick people in an essential area are now going back to work and getting other people sick. That doesn't mean that nothing should be done. However, it may absolutely mean that this particular method should not be done because it will cause more harm than doing the proverbially nothing. As for this particular article, it's not great because it doesn't actually work these numbers. It would be a good article if it actually calculated whether or not the app is worthwhile given a certain prevalence, sensitivity, and specificity. Personally, I don't know rate of prevalence of COVID-19 nor the sensitivity or specificity of the existing tests. However, I still strongly reject the premise that any test or contact tracing app is better than none at all. In order to fully beat a dead horse, here's the wiki that runs through how to calculate these numbers: https://en.wikipedia.org/wiki/Sensitivity_and_specificity https://en.wikipedia.org/wiki/Sensitivity_and_specificity I don't like their presentation, but it is what it is. Here is some Octave code that runs through their example with some more readable names: % Total population pop = 2030; % If someone is sick, will they test positive sensitivity = 0.67; % If someone is healthy, will they test negative specificity = 0.91; % Prevalence of the disease prevalence = 0.0148; % Works some numbers sick_pop = pop * prevalence; healthy_pop = pop * (1-prevalence); sick_pop_tested_positive = round(sick_pop * sensitivity); sick_pop_tested_negative = round(sick_pop * (1-sensitivity)); healthy_pop_tested_negative = round(healthy_pop * specificity); healthy_pop_tested_positive = round(healthy_pop * (1-specificity)); % Derive some useful quantities fprintf( ... ['Of those who tested as sick, percent of those actually ' ... 'sick (positive predictive value): %2.1f%%\n'], ... 100*(sick_pop_tested_positive / ... (sick_pop_tested_positive + healthy_pop_tested_positive))); fprintf( ... ['Of those who tested as healthy, percent of those actually ' ... 'healthy (negative predictive value): %2.1f%%\n'], ... 100*(healthy_pop_tested_negative / ... (healthy_pop_tested_negative + sick_pop_tested_negative))); > Of those who tested as sick, percent of those actually sick (positive predictive value): 10.0% > Of those who tested as healthy, percent of those actually healthy (negative predictive value): 99.5%
finnthehuman 7y ago
>Thinking "its not accurate enough" should not EVER be a reason to decide not to try something that could potentually help in this unprecedented situation. It may well not work well enough but we won't know unless we try! You do know you're using this line reasoning against the guy who literally invented the phrase "security theater," right?
- sanderjd 7y ago
  The analogy is definitely apt, but the difference is that we know a lot less about what is going to help with this problem than we did about the terrorism problem. Furthermore, it seems like contact tracing has helped in some countries who are already doing it, so there is some evidence it is not just theater.

eli 7y ago

Especially when you have no particular knowledge or citations as to what an appropriate standard for "enough" might be.

deeringc 7y ago
Exactly - I have huge respect for Bruce Schneier when it comes to matters relating to cryptography. But apart from commenting on the security, privacy and other technical aspects of these apps, I'm not sure on which authority he's giving these opinions on matters relating to epidemiology. At very least I'd like him to give some supporting scientific citations. But as it stands, Bruce's opinion on the medical and public health efficacy of these apps is no more valuable than yours or mine.

kxyvr 7y ago

Actually, yes it should, but it depends on the numbers and this is a well studied area of statistics. One of the many issues is whether or not someone who flags positive is actually positive and whether someone who flags negative is actually negative. This depends not only the sensitivity (if someone is sick, will they flag positive) and specificity (if someone is healthy, will they flag negative), but on how prevalent a disease is within a population. That last quantity is constantly changing, which also means that this calculation is constantly changing, which can and should affect policy. Now, the issue is that if you start telling a bunch of healthy people that they're actually sick and want them to quarantine or that a bunch of sick people are actually healthy and that they're free to go there are consequences. One, people will lose faith in the system and stop listening at all. Two, healthy people who work in an essential area can now not actually do their job. Three, sick people in an essential area are now going back to work and getting other people sick. That doesn't mean that nothing should be done. However, it may absolutely mean that this particular method should not be done because it will cause more harm than doing the proverbially nothing. As for this particular article, it's not great because it doesn't actually work these numbers. It would be a good article if it actually calculated whether or not the app is worthwhile given a certain prevalence, sensitivity, and specificity. Personally, I don't know rate of prevalence of COVID-19 nor the sensitivity or specificity of the existing tests. However, I still strongly reject the premise that any test or contact tracing app is better than none at all. In order to fully beat a dead horse, here's the wiki that runs through how to calculate these numbers: https://en.wikipedia.org/wiki/Sensitivity_and_specificity https://en.wikipedia.org/wiki/Sensitivity_and_specificity I don't like their presentation, but it is what it is. Here is some Octave code that runs through their example with some more readable names: % Total population pop = 2030; % If someone is sick, will they test positive sensitivity = 0.67; % If someone is healthy, will they test negative specificity = 0.91; % Prevalence of the disease prevalence = 0.0148; % Works some numbers sick_pop = pop * prevalence; healthy_pop = pop * (1-prevalence); sick_pop_tested_positive = round(sick_pop * sensitivity); sick_pop_tested_negative = round(sick_pop * (1-sensitivity)); healthy_pop_tested_negative = round(healthy_pop * specificity); healthy_pop_tested_positive = round(healthy_pop * (1-specificity)); % Derive some useful quantities fprintf( ... ['Of those who tested as sick, percent of those actually ' ... 'sick (positive predictive value): %2.1f%%\n'], ... 100*(sick_pop_tested_positive / ... (sick_pop_tested_positive + healthy_pop_tested_positive))); fprintf( ... ['Of those who tested as healthy, percent of those actually ' ... 'healthy (negative predictive value): %2.1f%%\n'], ... 100*(healthy_pop_tested_negative / ... (healthy_pop_tested_negative + sick_pop_tested_negative))); > Of those who tested as sick, percent of those actually sick (positive predictive value): 10.0% > Of those who tested as healthy, percent of those actually healthy (negative predictive value): 99.5%

finnthehuman 7y ago

>Thinking "its not accurate enough" should not EVER be a reason to decide not to try something that could potentually help in this unprecedented situation. It may well not work well enough but we won't know unless we try! You do know you're using this line reasoning against the guy who literally invented the phrase "security theater," right?

sanderjd 7y ago
The analogy is definitely apt, but the difference is that we know a lot less about what is going to help with this problem than we did about the terrorism problem. Furthermore, it seems like contact tracing has helped in some countries who are already doing it, so there is some evidence it is not just theater.