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OT: Tracking Current Developments in Coronavirus Science and Public Health

1246

Comments

  • @espiegel123 said:

    @richardyot said:
    Another puzzle is why some areas seem to be affected so much more drastically than others: why is the death rate (and also the all-cause mortality rate) in Lombardy, New York, and London so high whereas in other places such as Germany and Japan it's much lower.

    Btw, Germany's success is not on the same scale as Japan's. It is doing well compared to Western Europe but the response was not nearly as effective as in Japan.

    In Japan, there have been 2 deaths per million people. Germany is at 55. California is at 27.

    japan is doing literally 20 times better than Germany.

    Germany has managed it with less extreme measures than California but we should be looking at Japan as an example of success more than anywhere in the west.

    Are those results down to more testing though, so lowering the death rate?

    There’s hardly any testing in the UK, you have to be pretty seriously ill to have one, so potentially tens, if not hundreds of thousands of people could have been infected but not recorded in the figures.

    I know of at least ten personally who say they’ve had it, recovered at home, but not recorded in the figures.

  • Out of interest, who here has had their BCG when they were young? I had, and my sister had, while at school here in the UK. My wife had hers at school in Jamaica.

  • @u0421793 said:
    Out of interest, who here has had their BCG when they were young? I had, and my sister had, while at school here in the UK. My wife had hers at school in Jamaica.

    Yes I had it, but from what I’ve seen there isn’t much concrete evidence that it can help reduce the risk of infection from Coronavirus.

  • @MonzoPro said:

    @espiegel123 said:

    @richardyot said:
    Another puzzle is why some areas seem to be affected so much more drastically than others: why is the death rate (and also the all-cause mortality rate) in Lombardy, New York, and London so high whereas in other places such as Germany and Japan it's much lower.

    Btw, Germany's success is not on the same scale as Japan's. It is doing well compared to Western Europe but the response was not nearly as effective as in Japan.

    In Japan, there have been 2 deaths per million people. Germany is at 55. California is at 27.

    japan is doing literally 20 times better than Germany.

    Germany has managed it with less extreme measures than California but we should be looking at Japan as an example of success more than anywhere in the west.

    Are those results down to more testing though, so lowering the death rate?

    There’s hardly any testing in the UK, you have to be pretty seriously ill to have one, so potentially tens, if not hundreds of thousands of people could have been infected but not recorded in the figures.

    I know of at least ten personally who say they’ve had it, recovered at home, but not recorded in the figures.

    The case numbers per million are hard to interpret anywhere since testing varies so much from country to country (and region to region in large countries). On top of the that are questions of reliability even where testing is being done.

    Japan’s case rate is likely artificially low because of lack of testing but their number of deaths per million would have to be massive undercounts (like by a factor of 26) to be in the same ballpark as the best of Western Europe (Germany). It is interesting to see that in Japan, the people want a stronger response even though compared to the West, they are doing well.

  • @espiegel123 said:
    Paper out today that estimates that in the neighboring county in Northern California that there may have been 90 times as many infected people in early April as were indicated by blood tests. The paper has not yet completed the peer-review process. If it is accurate, it indicates that mortality rate is a lot lower than we've thought and that a much higher percentage of cases are asymptomatic than have been realized. I haven't seen any analyses of the paper yet by the epidemiologists that I follow.

    https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1?cf_chl_jschl_tk=3994fd33b88b7643bc24978c5bda66db9c792784-1587140719-0-ATt5KciAQ4OMW-W73PMdxvUda7AhOB6U9r52Xa9PPyrooMejvf8lJlBEXjazLk9hTsKf3E_s9WGra0wsLh6YUVE4P1WSk0dseqg6c24Wj-A_MpDLOi7IqEaalWWRxiXErcqUF7uS_0vk6DyUJb7Ii_8oWEpqw0ssv8TD39t30u3IFcOIhKCj3MHKxyxOl5vbjF30ANDz3pS4iQ4OMv0QrtPFgPcYMqqMnXB4Z3cP_CLF80cxmD8fOHLN7NxVFmU33YDxFERBZ_9kezS0VivNznMXUmYJddI_VBtjTkAeJFTeReVVFyDiKAiCV9aHlGbRtey3Ky2YH8GiP9ed5hlOm3I

    A very worthwhile follow up about possible methodological and interpretation issues in the paper which probably result in an exaggerated result. Read through to the end to see epidemiologist Mark Lipsitch’s discussion about the problems with flu-to-covid comparisons.

    TLDR: the test subjects may not be a random sampling (I.e. they may have been recruited using ads that would have more appeal to people that were symptomatic or had been exposed to symptomatic people, the tests may have a different specificity than assumed, deaths attributed to flu use much less restrictive attribution than covid deaths at this time).

  • @espiegel123 said:

    @espiegel123 said:
    Paper out today that estimates that in the neighboring county in Northern California that there may have been 90 times as many infected people in early April as were indicated by blood tests. The paper has not yet completed the peer-review process. If it is accurate, it indicates that mortality rate is a lot lower than we've thought and that a much higher percentage of cases are asymptomatic than have been realized. I haven't seen any analyses of the paper yet by the epidemiologists that I follow.

    https://www.medrxiv.org/content/10.1101/2020.04.14.20062463v1?cf_chl_jschl_tk=3994fd33b88b7643bc24978c5bda66db9c792784-1587140719-0-ATt5KciAQ4OMW-W73PMdxvUda7AhOB6U9r52Xa9PPyrooMejvf8lJlBEXjazLk9hTsKf3E_s9WGra0wsLh6YUVE4P1WSk0dseqg6c24Wj-A_MpDLOi7IqEaalWWRxiXErcqUF7uS_0vk6DyUJb7Ii_8oWEpqw0ssv8TD39t30u3IFcOIhKCj3MHKxyxOl5vbjF30ANDz3pS4iQ4OMv0QrtPFgPcYMqqMnXB4Z3cP_CLF80cxmD8fOHLN7NxVFmU33YDxFERBZ_9kezS0VivNznMXUmYJddI_VBtjTkAeJFTeReVVFyDiKAiCV9aHlGbRtey3Ky2YH8GiP9ed5hlOm3I

    A very worthwhile follow up about possible methodological and interpretation issues in the paper which probably result in an exaggerated result. Read through to the end to see epidemiologist Mark Lipsitch’s discussion about the problems with flu-to-covid comparisons.

    TLDR: the test subjects may not be a random sampling (I.e. they may have been recruited using ads that would have more appeal to people that were symptomatic or had been exposed to symptomatic people, the tests may have a different specificity than assumed, deaths attributed to flu use much less restrictive attribution than covid deaths at this time).

    There are a number of epidemiologists expressing a lot of doubt about the paper’s conclusions this morning. Apparently a small difference in the number of false positives would have a very large impact...and the authors assume an extremely low (near zero) number of false positives (which does not seem consistent according to epidemiologists with the tests being used).

  • McDMcD
    edited April 2020

    I found a series of YouTube Videos created by and for Emergency Medicine folks calle "EM:Rap Live".

    Watch an intensive care Dr (Sara) explain her findings at the 30 minute mark. She follows up over the next few episodes for additional disclosures.

    One idea she is currently working through:

    Intubating Covid-19 patients may be a bad idea

    Too few benefitted from this approach.

    The patients O2 might be at 65% (with extreme hypoxia) but report feeling fine: "happy hypoxia".
    If they decide to intubate... everyone on the team must don protective gear and then the patient make
    linger and then collapse as the tissues of the lungs become damaged and fail.

    The extreme pressures of the ventilators might injure their lungs and a better approach might be:

    • awake proning (6 hours on stomach - ideally with a massage mattress for comfort)
    • CPAP (Continuous Positive Airway Pressure) machines

    NOTE: Home CPAP units would aerosolize the virus but if you are giving care to someone and you have it. This could be important to evaluate as potential remedy to help the lungs survive with less damage and avert death and reach the recovery phase when the antibodies start to win the molecular contest for supremacy in the growth rates.

    I looked into CPAP machines and they require being tested for sleep disorders and an RX to obtain one.
    My wife sees a pulmonologist so we might be able to see if he would write the RX and we can prepare for the potential. I'm expecting to see hospitals start to order huge numbers of CPAP machines as alternative patient support devices to help more patients survive without their lungs collapsing under the strain of the late Covid-19 recovery cycle.

    We have a local musician that spent 3 weeks on the ventilator and was taken off it this week. One of the lucky ones.

    There's significant science happening with the teams observing these first wave patients that will benefit those that follow until there's a preventative therapy.

    We are on the verge of a populist push back and another round of hospital meltdowns so watching Emergency Medicine videos is a good place to better understand how to improve your odds if you're someone at risk.

    (Black market CPAP machines? Do you have one?)

  • edited April 2020

    Very interesting article by a data scientist:

    https://medium.com/@ali_razavian/covid-19-from-a-data-scientists-perspective-95bd4e84843b

    (edit) I would also recommend reading the comments on the article as there are some worthwhile counterpoints.

  • @richardyot said:
    Very interesting article by a data scientist:

    https://medium.com/@ali_razavian/covid-19-from-a-data-scientists-perspective-95bd4e84843b

    (edit) I would also recommend reading the comments on the article as there are some worthwhile counterpoints.

    The article is written by expert in data analysis but not an expert in epidemiology. There seems a lot wrong in his analysis. And a lot of emphasis on numbers that lay people focus on but not epidemiologists -- who have talking a lot about what data can be safely extrapolated out from test data.

    All agree that the number of infeois much higher than reported infections but there is a lot of uncertainty being expressed as to whether the undercount is off by factors of 5, 10, 50, 100. No one knows.

    One thing that they stress is that the tests themselves have enough unreliability that it throws a monkey wrench at interpretation.

    A few red flags to me in that article you posted are the notion that once the first death has been recorded , exponential growth of the infections has ended. And deaths simply lag. That the pandemic will have played itself out by the end of April.

    By his reasoning, we would have a massively higher death toll in California than anywhere else in the country. But that hasn't happened. The notion that the epidemic had completed its run before we went into lockdown in March is pretty obviously not true...otherwise we'd see far more total fatalities than in New York.

  • @espiegel123 said:

    @richardyot said:
    Very interesting article by a data scientist:

    https://medium.com/@ali_razavian/covid-19-from-a-data-scientists-perspective-95bd4e84843b

    (edit) I would also recommend reading the comments on the article as there are some worthwhile counterpoints.

    The article is written by expert in data analysis but not an expert in epidemiology. There seems a lot wrong in his analysis. And a lot of emphasis on numbers that lay people focus on but not epidemiologists -- who have talking a lot about what data can be safely extrapolated out from test data.

    All agree that the number of infeois much higher than reported infections but there is a lot of uncertainty being expressed as to whether the undercount is off by factors of 5, 10, 50, 100. No one knows.

    One thing that they stress is that the tests themselves have enough unreliability that it throws a monkey wrench at interpretation.

    A few red flags to me in that article you posted are the notion that once the first death has been recorded , exponential growth of the infections has ended. And deaths simply lag. That the pandemic will have played itself out by the end of April.

    By his reasoning, we would have a massively higher death toll in California than anywhere else in the country. But that hasn't happened. The notion that the epidemic had completed its run before we went into lockdown in March is pretty obviously not true...otherwise we'd see far more total fatalities than in New York.

    I agree, but I thought it was an interesting perspective. We are still fumbling for the truth, so I think it's worth considering all points of view. I also think it's highly unlikely that the pandemic will be over in April, or even May or June. What's more I think the death rate is also going to be higher than his prediction, but the data from Iceland is certainly worth further examination.

    The Diamond Princess, Iceland, the town of Vo, all seem to point to a low-ish mortality rate and a high number of completely asymptomatic carriers.

  • @richardyot said:

    @espiegel123 said:

    @richardyot said:
    Very interesting article by a data scientist:

    https://medium.com/@ali_razavian/covid-19-from-a-data-scientists-perspective-95bd4e84843b

    (edit) I would also recommend reading the comments on the article as there are some worthwhile counterpoints.

    The article is written by expert in data analysis but not an expert in epidemiology. There seems a lot wrong in his analysis. And a lot of emphasis on numbers that lay people focus on but not epidemiologists -- who have talking a lot about what data can be safely extrapolated out from test data.

    All agree that the number of infeois much higher than reported infections but there is a lot of uncertainty being expressed as to whether the undercount is off by factors of 5, 10, 50, 100. No one knows.

    One thing that they stress is that the tests themselves have enough unreliability that it throws a monkey wrench at interpretation.

    A few red flags to me in that article you posted are the notion that once the first death has been recorded , exponential growth of the infections has ended. And deaths simply lag. That the pandemic will have played itself out by the end of April.

    By his reasoning, we would have a massively higher death toll in California than anywhere else in the country. But that hasn't happened. The notion that the epidemic had completed its run before we went into lockdown in March is pretty obviously not true...otherwise we'd see far more total fatalities than in New York.

    I agree, but I thought it was an interesting perspective. We are still fumbling for the truth, so I think it's worth considering all points of view. I also think it's highly unlikely that the pandemic will be over in April, or even May or June. What's more I think the death rate is also going to be higher than his prediction, but the data from Iceland is certainly worth further examination.

    The Diamond Princess, Iceland, the town of Vo, all seem to point to a low-ish mortality rate and a high number of completely asymptomatic carriers.

    I’d suggest that epidemiologists she’d more fruitful light on all the issues. After all they understand BOTH the math/data visualization aspect AND the scientific context. I find articles like the one you posted dangerously misleading because the authors just play number games without understanding the science or context and so don’t recognize (as the author of that article didn’t) dissonance between their conclusions and relevant details.

    A few weeks ago, an epidemiologist did a piece by piece takedown of a different article on Medium demonstrating errors in assumptions and interpretation made by the author of a piece on Medium that had gone viral (which has since been taken down). His overall point was that interpreting numbers and doing meaningful analysis requires an understanding of the underlying science and that there is a lot more to epidemiology than is obvious to even savvy non-epidemiologists.

    He made the point that there have been a lot of people not in the field (and that includes doctors that aren’t epidemiologists) getting a lot of eyeballs on posts that only get a part of the story right and that there are lots of epidemiologists putt Mg things out there with much better information INCLUDING pointing out what they don’t know.

    A point many keep making is that even if the undercount is massive in terms of total infections that does not suggest that concern has been overblown.

    Another important point that has been made a few times is that there are a few reasons why comparing the fatality rate to the flu is misleading.

    One of those issues, which is mentioned in that Medium article, is that even if the fatality rate is similar, lack of a vaccine and natural immunity will result in a massive death toll and strain on the healthcare system.

    Also, and people seem aware of this point, flu death attribution is made with less restrictive attribution than COVID deaths. Mark Lipitch (epidemiologist at Harvard) points out that if you used the same methodology for flu as for COVID19 attribution, the number of attributed deaths would be about 1/10th of the figures we use. His point being that anyone that compares flu lethality to COVID19 fatality without mentioning this is being misleading (intentionally or not).

    If anyone is on Twitter, I recommend following these epidemiologists:

    Carl Bergstrom @CT_Bergstrom
    Natalie Dean @nataliexdean
    Marc Lipsitch @mlipsitch

    They have been providing some great ongoing commentary and context for helping understand and interpret the information and the various studies coming out.

    Bergstrom had a couple of interesting threads about the dangers of pursuing herd immunity that is well worth one’s time.

    Natalie Dean and a few others had some great insights to share about the various serological studies being published.

  • @espiegel123 said:

    @richardyot said:

    @espiegel123 said:

    @richardyot said:
    Very interesting article by a data scientist:

    https://medium.com/@ali_razavian/covid-19-from-a-data-scientists-perspective-95bd4e84843b

    (edit) I would also recommend reading the comments on the article as there are some worthwhile counterpoints.

    The article is written by expert in data analysis but not an expert in epidemiology. There seems a lot wrong in his analysis. And a lot of emphasis on numbers that lay people focus on but not epidemiologists -- who have talking a lot about what data can be safely extrapolated out from test data.

    All agree that the number of infeois much higher than reported infections but there is a lot of uncertainty being expressed as to whether the undercount is off by factors of 5, 10, 50, 100. No one knows.

    One thing that they stress is that the tests themselves have enough unreliability that it throws a monkey wrench at interpretation.

    A few red flags to me in that article you posted are the notion that once the first death has been recorded , exponential growth of the infections has ended. And deaths simply lag. That the pandemic will have played itself out by the end of April.

    By his reasoning, we would have a massively higher death toll in California than anywhere else in the country. But that hasn't happened. The notion that the epidemic had completed its run before we went into lockdown in March is pretty obviously not true...otherwise we'd see far more total fatalities than in New York.

    I agree, but I thought it was an interesting perspective. We are still fumbling for the truth, so I think it's worth considering all points of view. I also think it's highly unlikely that the pandemic will be over in April, or even May or June. What's more I think the death rate is also going to be higher than his prediction, but the data from Iceland is certainly worth further examination.

    The Diamond Princess, Iceland, the town of Vo, all seem to point to a low-ish mortality rate and a high number of completely asymptomatic carriers.

    I’d suggest that epidemiologists she’d more fruitful light on all the issues. After all they understand BOTH the math/data visualization aspect AND the scientific context. I find articles like the one you posted dangerously misleading because the authors just play number games without understanding the science or context and so don’t recognize (as the author of that article didn’t) dissonance between their conclusions and relevant details.

    A few weeks ago, an epidemiologist did a piece by piece takedown of a different article on Medium demonstrating errors in assumptions and interpretation made by the author of a piece on Medium that had gone viral (which has since been taken down). His overall point was that interpreting numbers and doing meaningful analysis requires an understanding of the underlying science and that there is a lot more to epidemiology than is obvious to even savvy non-epidemiologists.

    He made the point that there have been a lot of people not in the field (and that includes doctors that aren’t epidemiologists) getting a lot of eyeballs on posts that only get a part of the story right and that there are lots of epidemiologists putt Mg things out there with much better information INCLUDING pointing out what they don’t know.

    A point many keep making is that even if the undercount is massive in terms of total infections that does not suggest that concern has been overblown.

    Another important point that has been made a few times is that there are a few reasons why comparing the fatality rate to the flu is misleading.

    One of those issues, which is mentioned in that Medium article, is that even if the fatality rate is similar, lack of a vaccine and natural immunity will result in a massive death toll and strain on the healthcare system.

    Also, and people seem aware of this point, flu death attribution is made with less restrictive attribution than COVID deaths. Mark Lipitch (epidemiologist at Harvard) points out that if you used the same methodology for flu as for COVID19 attribution, the number of attributed deaths would be about 1/10th of the figures we use. His point being that anyone that compares flu lethality to COVID19 fatality without mentioning this is being misleading (intentionally or not).

    If anyone is on Twitter, I recommend following these epidemiologists:

    Carl Bergstrom @CT_Bergstrom
    Natalie Dean @nataliexdean
    Marc Lipsitch @mlipsitch

    They have been providing some great ongoing commentary and context for helping understand and interpret the information and the various studies coming out.

    Bergstrom had a couple of interesting threads about the dangers of pursuing herd immunity that is well worth one’s time.

    Natalie Dean and a few others had some great insights to share about the various serological studies being published.

    The audiob.us forum profile pages for those epidemiologists are broken

  • @u0421793 said:

    @espiegel123 said:

    @richardyot said:

    @espiegel123 said:

    @richardyot said:
    Very interesting article by a data scientist:

    https://medium.com/@ali_razavian/covid-19-from-a-data-scientists-perspective-95bd4e84843b

    (edit) I would also recommend reading the comments on the article as there are some worthwhile counterpoints.

    The article is written by expert in data analysis but not an expert in epidemiology. There seems a lot wrong in his analysis. And a lot of emphasis on numbers that lay people focus on but not epidemiologists -- who have talking a lot about what data can be safely extrapolated out from test data.

    All agree that the number of infeois much higher than reported infections but there is a lot of uncertainty being expressed as to whether the undercount is off by factors of 5, 10, 50, 100. No one knows.

    One thing that they stress is that the tests themselves have enough unreliability that it throws a monkey wrench at interpretation.

    A few red flags to me in that article you posted are the notion that once the first death has been recorded , exponential growth of the infections has ended. And deaths simply lag. That the pandemic will have played itself out by the end of April.

    By his reasoning, we would have a massively higher death toll in California than anywhere else in the country. But that hasn't happened. The notion that the epidemic had completed its run before we went into lockdown in March is pretty obviously not true...otherwise we'd see far more total fatalities than in New York.

    I agree, but I thought it was an interesting perspective. We are still fumbling for the truth, so I think it's worth considering all points of view. I also think it's highly unlikely that the pandemic will be over in April, or even May or June. What's more I think the death rate is also going to be higher than his prediction, but the data from Iceland is certainly worth further examination.

    The Diamond Princess, Iceland, the town of Vo, all seem to point to a low-ish mortality rate and a high number of completely asymptomatic carriers.

    I’d suggest that epidemiologists she’d more fruitful light on all the issues. After all they understand BOTH the math/data visualization aspect AND the scientific context. I find articles like the one you posted dangerously misleading because the authors just play number games without understanding the science or context and so don’t recognize (as the author of that article didn’t) dissonance between their conclusions and relevant details.

    A few weeks ago, an epidemiologist did a piece by piece takedown of a different article on Medium demonstrating errors in assumptions and interpretation made by the author of a piece on Medium that had gone viral (which has since been taken down). His overall point was that interpreting numbers and doing meaningful analysis requires an understanding of the underlying science and that there is a lot more to epidemiology than is obvious to even savvy non-epidemiologists.

    He made the point that there have been a lot of people not in the field (and that includes doctors that aren’t epidemiologists) getting a lot of eyeballs on posts that only get a part of the story right and that there are lots of epidemiologists putt Mg things out there with much better information INCLUDING pointing out what they don’t know.

    A point many keep making is that even if the undercount is massive in terms of total infections that does not suggest that concern has been overblown.

    Another important point that has been made a few times is that there are a few reasons why comparing the fatality rate to the flu is misleading.

    One of those issues, which is mentioned in that Medium article, is that even if the fatality rate is similar, lack of a vaccine and natural immunity will result in a massive death toll and strain on the healthcare system.

    Also, and people seem aware of this point, flu death attribution is made with less restrictive attribution than COVID deaths. Mark Lipitch (epidemiologist at Harvard) points out that if you used the same methodology for flu as for COVID19 attribution, the number of attributed deaths would be about 1/10th of the figures we use. His point being that anyone that compares flu lethality to COVID19 fatality without mentioning this is being misleading (intentionally or not).

    If anyone is on Twitter, I recommend following these epidemiologists:

    Carl Bergstrom @CT_Bergstrom
    Natalie Dean @nataliexdean
    Marc Lipsitch @mlipsitch

    They have been providing some great ongoing commentary and context for helping understand and interpret the information and the various studies coming out.

    Bergstrom had a couple of interesting threads about the dangers of pursuing herd immunity that is well worth one’s time.

    Natalie Dean and a few others had some great insights to share about the various serological studies being published.

    The audiob.us forum profile pages for those epidemiologists are broken

    They must have deleted their accounts? I guess with a pandemic on they don't have much time for music...

  • @richardyot said:

    @u0421793 said:

    @espiegel123 said:

    @richardyot said:

    @espiegel123 said:

    @richardyot said:
    Very interesting article by a data scientist:

    https://medium.com/@ali_razavian/covid-19-from-a-data-scientists-perspective-95bd4e84843b

    (edit) I would also recommend reading the comments on the article as there are some worthwhile counterpoints.

    The article is written by expert in data analysis but not an expert in epidemiology. There seems a lot wrong in his analysis. And a lot of emphasis on numbers that lay people focus on but not epidemiologists -- who have talking a lot about what data can be safely extrapolated out from test data.

    All agree that the number of infeois much higher than reported infections but there is a lot of uncertainty being expressed as to whether the undercount is off by factors of 5, 10, 50, 100. No one knows.

    One thing that they stress is that the tests themselves have enough unreliability that it throws a monkey wrench at interpretation.

    A few red flags to me in that article you posted are the notion that once the first death has been recorded , exponential growth of the infections has ended. And deaths simply lag. That the pandemic will have played itself out by the end of April.

    By his reasoning, we would have a massively higher death toll in California than anywhere else in the country. But that hasn't happened. The notion that the epidemic had completed its run before we went into lockdown in March is pretty obviously not true...otherwise we'd see far more total fatalities than in New York.

    I agree, but I thought it was an interesting perspective. We are still fumbling for the truth, so I think it's worth considering all points of view. I also think it's highly unlikely that the pandemic will be over in April, or even May or June. What's more I think the death rate is also going to be higher than his prediction, but the data from Iceland is certainly worth further examination.

    The Diamond Princess, Iceland, the town of Vo, all seem to point to a low-ish mortality rate and a high number of completely asymptomatic carriers.

    I’d suggest that epidemiologists she’d more fruitful light on all the issues. After all they understand BOTH the math/data visualization aspect AND the scientific context. I find articles like the one you posted dangerously misleading because the authors just play number games without understanding the science or context and so don’t recognize (as the author of that article didn’t) dissonance between their conclusions and relevant details.

    A few weeks ago, an epidemiologist did a piece by piece takedown of a different article on Medium demonstrating errors in assumptions and interpretation made by the author of a piece on Medium that had gone viral (which has since been taken down). His overall point was that interpreting numbers and doing meaningful analysis requires an understanding of the underlying science and that there is a lot more to epidemiology than is obvious to even savvy non-epidemiologists.

    He made the point that there have been a lot of people not in the field (and that includes doctors that aren’t epidemiologists) getting a lot of eyeballs on posts that only get a part of the story right and that there are lots of epidemiologists putt Mg things out there with much better information INCLUDING pointing out what they don’t know.

    A point many keep making is that even if the undercount is massive in terms of total infections that does not suggest that concern has been overblown.

    Another important point that has been made a few times is that there are a few reasons why comparing the fatality rate to the flu is misleading.

    One of those issues, which is mentioned in that Medium article, is that even if the fatality rate is similar, lack of a vaccine and natural immunity will result in a massive death toll and strain on the healthcare system.

    Also, and people seem aware of this point, flu death attribution is made with less restrictive attribution than COVID deaths. Mark Lipitch (epidemiologist at Harvard) points out that if you used the same methodology for flu as for COVID19 attribution, the number of attributed deaths would be about 1/10th of the figures we use. His point being that anyone that compares flu lethality to COVID19 fatality without mentioning this is being misleading (intentionally or not).

    If anyone is on Twitter, I recommend following these epidemiologists:

    Carl Bergstrom @CT_Bergstrom
    Natalie Dean @nataliexdean
    Marc Lipsitch @mlipsitch

    They have been providing some great ongoing commentary and context for helping understand and interpret the information and the various studies coming out.

    Bergstrom had a couple of interesting threads about the dangers of pursuing herd immunity that is well worth one’s time.

    Natalie Dean and a few others had some great insights to share about the various serological studies being published.

    The audiob.us forum profile pages for those epidemiologists are broken

    They must have deleted their accounts? I guess with a pandemic on they don't have much time for music...

    All three? What are the chances of that happening, eh?

  • @u0421793 said:

    @richardyot said:

    @u0421793 said:

    @espiegel123 said:

    @richardyot said:

    @espiegel123 said:

    @richardyot said:
    Very interesting article by a data scientist:

    https://medium.com/@ali_razavian/covid-19-from-a-data-scientists-perspective-95bd4e84843b

    (edit) I would also recommend reading the comments on the article as there are some worthwhile counterpoints.

    The article is written by expert in data analysis but not an expert in epidemiology. There seems a lot wrong in his analysis. And a lot of emphasis on numbers that lay people focus on but not epidemiologists -- who have talking a lot about what data can be safely extrapolated out from test data.

    All agree that the number of infeois much higher than reported infections but there is a lot of uncertainty being expressed as to whether the undercount is off by factors of 5, 10, 50, 100. No one knows.

    One thing that they stress is that the tests themselves have enough unreliability that it throws a monkey wrench at interpretation.

    A few red flags to me in that article you posted are the notion that once the first death has been recorded , exponential growth of the infections has ended. And deaths simply lag. That the pandemic will have played itself out by the end of April.

    By his reasoning, we would have a massively higher death toll in California than anywhere else in the country. But that hasn't happened. The notion that the epidemic had completed its run before we went into lockdown in March is pretty obviously not true...otherwise we'd see far more total fatalities than in New York.

    I agree, but I thought it was an interesting perspective. We are still fumbling for the truth, so I think it's worth considering all points of view. I also think it's highly unlikely that the pandemic will be over in April, or even May or June. What's more I think the death rate is also going to be higher than his prediction, but the data from Iceland is certainly worth further examination.

    The Diamond Princess, Iceland, the town of Vo, all seem to point to a low-ish mortality rate and a high number of completely asymptomatic carriers.

    I’d suggest that epidemiologists she’d more fruitful light on all the issues. After all they understand BOTH the math/data visualization aspect AND the scientific context. I find articles like the one you posted dangerously misleading because the authors just play number games without understanding the science or context and so don’t recognize (as the author of that article didn’t) dissonance between their conclusions and relevant details.

    A few weeks ago, an epidemiologist did a piece by piece takedown of a different article on Medium demonstrating errors in assumptions and interpretation made by the author of a piece on Medium that had gone viral (which has since been taken down). His overall point was that interpreting numbers and doing meaningful analysis requires an understanding of the underlying science and that there is a lot more to epidemiology than is obvious to even savvy non-epidemiologists.

    He made the point that there have been a lot of people not in the field (and that includes doctors that aren’t epidemiologists) getting a lot of eyeballs on posts that only get a part of the story right and that there are lots of epidemiologists putt Mg things out there with much better information INCLUDING pointing out what they don’t know.

    A point many keep making is that even if the undercount is massive in terms of total infections that does not suggest that concern has been overblown.

    Another important point that has been made a few times is that there are a few reasons why comparing the fatality rate to the flu is misleading.

    One of those issues, which is mentioned in that Medium article, is that even if the fatality rate is similar, lack of a vaccine and natural immunity will result in a massive death toll and strain on the healthcare system.

    Also, and people seem aware of this point, flu death attribution is made with less restrictive attribution than COVID deaths. Mark Lipitch (epidemiologist at Harvard) points out that if you used the same methodology for flu as for COVID19 attribution, the number of attributed deaths would be about 1/10th of the figures we use. His point being that anyone that compares flu lethality to COVID19 fatality without mentioning this is being misleading (intentionally or not).

    If anyone is on Twitter, I recommend following these epidemiologists:

    Carl Bergstrom @CT_Bergstrom
    Natalie Dean @nataliexdean
    Marc Lipsitch @mlipsitch

    They have been providing some great ongoing commentary and context for helping understand and interpret the information and the various studies coming out.

    Bergstrom had a couple of interesting threads about the dangers of pursuing herd immunity that is well worth one’s time.

    Natalie Dean and a few others had some great insights to share about the various serological studies being published.

    The audiob.us forum profile pages for those epidemiologists are broken

    They must have deleted their accounts? I guess with a pandemic on they don't have much time for music...

    All three? What are the chances of that happening, eh?

    Maybe it's a conspiracy - have you considered that? 🤔 THINK CRITICALLY.

  • New paper suggests that new saliva-based tests are more accurate (and easier to administer) than the nasopharyngeal swab-based tests:

    https://www.medrxiv.org/content/10.1101/2020.04.16.20067835v1#disqus_thread

    One of the things that epidemiologists have been chattering a lot about is that a lot of the testing that has been (and is currently) being done is of somewhat unknown quality.

    There has always been a consensus that there are many more infections out there than recorded -- but the recent serological test results (which so far are all controversial) have made it clear that we have no idea of the magnitude of the undercount. Estimates are everywhere from 2x to 999x (although the Swedish paper that proposed 999x has been withdrawn -- after major problems with their math were documented).

  • Excess mortality figures for New York, England & Wales, France, and Spain:

    https://www.nytimes.com/interactive/2020/04/21/world/coronavirus-missing-deaths.html

  • A vaccine developers explains why a COVID19 might not put an end to the virus:

    https://threadreaderapp.com/thread/1252698777296797698.html

  • @richardyot said:

    @u0421793 said:

    @richardyot said:

    @u0421793 said:

    @espiegel123 said:

    @richardyot said:

    @espiegel123 said:

    @richardyot said:
    Very interesting article by a data scientist:

    https://medium.com/@ali_razavian/covid-19-from-a-data-scientists-perspective-95bd4e84843b

    (edit) I would also recommend reading the comments on the article as there are some worthwhile counterpoints.

    The article is written by expert in data analysis but not an expert in epidemiology. There seems a lot wrong in his analysis. And a lot of emphasis on numbers that lay people focus on but not epidemiologists -- who have talking a lot about what data can be safely extrapolated out from test data.

    All agree that the number of infeois much higher than reported infections but there is a lot of uncertainty being expressed as to whether the undercount is off by factors of 5, 10, 50, 100. No one knows.

    One thing that they stress is that the tests themselves have enough unreliability that it throws a monkey wrench at interpretation.

    A few red flags to me in that article you posted are the notion that once the first death has been recorded , exponential growth of the infections has ended. And deaths simply lag. That the pandemic will have played itself out by the end of April.

    By his reasoning, we would have a massively higher death toll in California than anywhere else in the country. But that hasn't happened. The notion that the epidemic had completed its run before we went into lockdown in March is pretty obviously not true...otherwise we'd see far more total fatalities than in New York.

    I agree, but I thought it was an interesting perspective. We are still fumbling for the truth, so I think it's worth considering all points of view. I also think it's highly unlikely that the pandemic will be over in April, or even May or June. What's more I think the death rate is also going to be higher than his prediction, but the data from Iceland is certainly worth further examination.

    The Diamond Princess, Iceland, the town of Vo, all seem to point to a low-ish mortality rate and a high number of completely asymptomatic carriers.

    I’d suggest that epidemiologists she’d more fruitful light on all the issues. After all they understand BOTH the math/data visualization aspect AND the scientific context. I find articles like the one you posted dangerously misleading because the authors just play number games without understanding the science or context and so don’t recognize (as the author of that article didn’t) dissonance between their conclusions and relevant details.

    A few weeks ago, an epidemiologist did a piece by piece takedown of a different article on Medium demonstrating errors in assumptions and interpretation made by the author of a piece on Medium that had gone viral (which has since been taken down). His overall point was that interpreting numbers and doing meaningful analysis requires an understanding of the underlying science and that there is a lot more to epidemiology than is obvious to even savvy non-epidemiologists.

    He made the point that there have been a lot of people not in the field (and that includes doctors that aren’t epidemiologists) getting a lot of eyeballs on posts that only get a part of the story right and that there are lots of epidemiologists putt Mg things out there with much better information INCLUDING pointing out what they don’t know.

    A point many keep making is that even if the undercount is massive in terms of total infections that does not suggest that concern has been overblown.

    Another important point that has been made a few times is that there are a few reasons why comparing the fatality rate to the flu is misleading.

    One of those issues, which is mentioned in that Medium article, is that even if the fatality rate is similar, lack of a vaccine and natural immunity will result in a massive death toll and strain on the healthcare system.

    Also, and people seem aware of this point, flu death attribution is made with less restrictive attribution than COVID deaths. Mark Lipitch (epidemiologist at Harvard) points out that if you used the same methodology for flu as for COVID19 attribution, the number of attributed deaths would be about 1/10th of the figures we use. His point being that anyone that compares flu lethality to COVID19 fatality without mentioning this is being misleading (intentionally or not).

    If anyone is on Twitter, I recommend following these epidemiologists:

    Carl Bergstrom @CT_Bergstrom
    Natalie Dean @nataliexdean
    Marc Lipsitch @mlipsitch

    They have been providing some great ongoing commentary and context for helping understand and interpret the information and the various studies coming out.

    Bergstrom had a couple of interesting threads about the dangers of pursuing herd immunity that is well worth one’s time.

    Natalie Dean and a few others had some great insights to share about the various serological studies being published.

    The audiob.us forum profile pages for those epidemiologists are broken

    They must have deleted their accounts? I guess with a pandemic on they don't have much time for music...

    All three? What are the chances of that happening, eh?

    Maybe it's a conspiracy - have you considered that? 🤔 THINK CRITICALLY.

    Thanks for the three twitter people (and for the laugh as well.... :))

  • Ah, now this is interesting.

    https://onlinelibrary.wiley.com/doi/full/10.1002/jmv.25728
    and
    https://www.nature.com/articles/s41423-020-0424-9

    These two are from quite early on, but correlate with something I’ve been thinking about.

    What if:

    (as is the case) a proportion of people get infected, a proportion of them exhibit symptoms, a proportion of them exhibit severe symptoms, and a proportion of them die, and that’d be a direct death due to COVID-19, without any doubt in the matter.

    However (hypothetically), a proportion of people get infected, do not exhibit symptoms or at least severe symptoms, and then swan around either thinking they were lucky or that there was nothing to make a fuss about after all.

    Then within a year or so they’re dead. But dead from other reasons, COVID-19 isn’t written down on the death certificate.

    Is it possible that the effect on the asymptomatic, the symptomatic, the severely symptomatic (but not the dead) is to impart through the CNS a marked diminishing of immune system functioning, almost an acquired immune deficiency situation a bit like AIDS. The kids and younger generation happy in the fact that they’re not affected, but highly depressed by their being contained in quarantine, if they go out and meet up and get infected might only last another year or so before they all drop dead.

  • @u0421793 said:
    Ah, now this is interesting.

    https://onlinelibrary.wiley.com/doi/full/10.1002/jmv.25728
    and
    https://www.nature.com/articles/s41423-020-0424-9

    These two are from quite early on, but correlate with something I’ve been thinking about.

    What if:

    (as is the case) a proportion of people get infected, a proportion of them exhibit symptoms, a proportion of them exhibit severe symptoms, and a proportion of them die, and that’d be a direct death due to COVID-19, without any doubt in the matter.

    However (hypothetically), a proportion of people get infected, do not exhibit symptoms or at least severe symptoms, and then swan around either thinking they were lucky or that there was nothing to make a fuss about after all.

    Then within a year or so they’re dead. But dead from other reasons, COVID-19 isn’t written down on the death certificate.

    Is it possible that the effect on the asymptomatic, the symptomatic, the severely symptomatic (but not the dead) is to impart through the CNS a marked diminishing of immune system functioning, almost an acquired immune deficiency situation a bit like AIDS. The kids and younger generation happy in the fact that they’re not affected, but highly depressed by their being contained in quarantine, if they go out and meet up and get infected might only last another year or so before they all drop dead.

    I think you are getting into the realms of fantasy. This is not like HIV which gets into and binds with the cells nucleus, then remains dormant.

  • A couple of epidemiologists and virologists were discussing this yesterday and were skeptical that this anti-viral can have a significant impact on overall outcome but also said that unlike chloroquine that it did not seem that there were many bad side effects. They also said that if it turns out that it really does reduce the number of days of suffering even by just a couple of days that is good (the hospitalized people suffer a lot).

    But, they expressed concern that non-experts will overhype the significance of this. AND suggested that follow-ups need to be done (and one of the people involved in one of the studies was in agreement) with better experimental design as the design of the trials was compromised by the desire to get speedy results.

  • Worth reading for those curious about the downside of pursuing herd immunity naturally:

    https://threadreaderapp.com/thread/1256828515057467393.html

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