14 ms·

This entire plan is based on models that do not align with what we are seeing. The graph on slide two[1] of the official CA govt plan shows hospitalizations Wit

This entire plan is based on models that do not align with what we are seeing. The graph on slide two[1] of the official CA govt plan shows hospitalizations With Intervention rising exponentially, exceeding our hospital capacity in early June. The actual new infection data shows that the rate of new infections has been decreasing since at least 4/4 [2], meaning that the graph of active hospitalizations should be a bell curve with a maximum value of ~10,000 on ~4/20. The mismatch between their models and the observed data does not engender confidence. [1] https://www.gov.ca.gov/wp-content/uploads/2020/04/California-Roadmap-to-Modify-the-Stay-at-Home-Order.pdf https://www.gov.ca.gov/wp-content/uploads/2020/04/California... [2] https://covid-19.direct/state/CA https://covid-19.direct/state/CA

ta1234567890 7y ago
> The graph on slide two[1] of the official CA govt plan shows hospitalizations With Intervention rising exponentially It does not. The exponential curve, per the graph legend, is what would be expected without intervention.
- mikekij 7y ago
  The light blue curve, labeled "With Intervention", is an upward-facing concave curve. Even if it were linear, it does not align with the observed data referenced in the link labeled [2].
  - joe_the_user 7y ago
    OK, looking at the new cases curve on your covid-19.direct page. As presented, you can't really see what the green curve is doing. If you remove the black, total curve, the green new case curve is visible but it seems to be going up and down fairly inconclusively. Until 4/1, it looks like exponential growth. After that, it goes down and then up. Sure, the optimistic view is it's plateaued or going downward and I hope that's true but counting on just twelve days of data seems foolish.
    - mikekij 7y ago
      "If you remove the black, total curve, the green new case curve is visible but it seems to be going up and down fairly inconclusively." The best fit line of new cases after 4/4 is a linear function with a definitively negative slope. It is conclusively not a function that contributes to the upward, concave blue line on the state's graph.
      - joe_the_user 7y ago
        Who cares what the best fit is. There is simply not enough data. You're talking twelves data points with considerable variation. Using statistic doesn't turn muddy and ambiguous data into a clear signal magically.
        mikekij 7y ago
        My point is that there is no extrapolation of the data we’ve seen to date that yields the blue line on their graph.
        joe_the_user 7y ago
        Sure, but I think they are tracing the worst case scenario based on the underlying assumption that the virus increases exponentially. What going to happen is indeed inherently uncertain so we pretty much have to prepare for the worst plausible series of events. Once it becomes clear that a better outcome is fairly likely, then the plans can shift.
okintheory 7y ago
That makes you think it should be a bell curve? Are you arguing it will be a bell curve with such a peak, even if restrictions are weakened or removed? That is unlikely.
- mikekij 7y ago
  I am not. I am arguing that the current trajectory data we're observing [2] does not align with the projections of our current trajectory provided by the government of California (the light blue line labeled 'With Intervention' [1]) [1] https://www.gov.ca.gov/wp-content/uploads/2020/04/California.. https://www.gov.ca.gov/wp-content/uploads/2020/04/California.... [2] https://covid-19.direct/state/CA https://covid-19.direct/state/CA
  - okintheory 7y ago
    But you wrote "meaning that the graph of active hospitalizations should be a bell curve with a maximum value of ~10,000 on ~4/20."? You didn't mean that?
    - mikekij 7y ago
      I meant that "the graph of active hospitalizations should be a bell curve with a maximum value of ~10,000 on ~4/20" with the current mitigations in place. That is not what the government report is projecting. They're projecting unbounded, exponential growth with current mitigations in place, even though that is not in line with the data we've seen over the past two weeks.
archgoon 7y ago
Why should infections follow a bell curve? Shouldn't it be the derivative of a the logistic curve, which should be approximately exponential on both ends. I don't see how a quadratic should show up in the exponent; either mathematically or epidemiologically.
- mikekij 7y ago
  You're pointing out a great ambiguity in the state's graph. Is the hospitalization line a cumulative count of all hospitalizations? Or hospitalizations at any given time? Since the state's hospital capacity is related to hospitalizations at a given time, and not cumulative, I'm assuming the fit of that graph would be a bell curve with a max, followed by a decrease. People either die or leave the hospital.
- wtvanhest 7y ago
  Does anyone have the ability to walk through these explanations in a little more detail. I'm having trouble understanding why infections would be a bell curve, or derivative of a log curve.
  - mikekij 7y ago
    Cumulative infections would not be a bell curve. They'd be a sigmoid curve, approaching some upper limit (e.g. 100,000). Current Hospitalizations, which is the number we should be most concerned about, and is reflected by the orange dots on the state's graph, should start low, max out at a number, and eventually return to 0. That should follow something like a bell curve. I think the confusion is between the "total infections" curve and the "current hospitalizations" curve. The difference between them is huge, and really important. The "Flatten the Curve" idea refers to keeping the number of hospitalizations at any one moment below some upper limit, ideally the state's number of available ICU beds. That's a bell curve.
    - SquishyPanda23 7y ago
      > think the confusion is between the "total infections" curve and the "current hospitalizations" curve. I think the confusion is that if the CDF is the logistic function, then the PDF is the logistic distribution. This is what archgoon is saying. Bell curve refers to a Gaussian distribution, which is different but looks similar. https://en.m.wikipedia.org/wiki/Logistic_distribution https://en.m.wikipedia.org/wiki/Logistic_distribution http://visionlab.harvard.edu/Members/Anne/Math/Logistic_vs_Gaussian.html http://visionlab.harvard.edu/Members/Anne/Math/Logistic_vs_G...
Ninjak8051 7y ago
Additionally, notice that the orange data points (actual hospitalizations) are significantly under the "With Intervention" plot. So why even include the slide? Clearly the assumptions behind the "With Intervention" plot do not match reality TODAY, let alone in a few weeks. Not a good sign if people are making actual decisions based on this.
- mikekij 7y ago
  My former physics professors would have not approved of a graph like this. D+ on the lab at best.
  - dehrmann 7y ago
    https://i.imgur.com/dJ7kHch.png https://i.imgur.com/dJ7kHch.png It's pretty sloppy to show surge capacity on the same graph as total hospitalizations, not active active hospitalizations.
- xienze 7y ago
  > Clearly the assumptions behind the "With Intervention" plot do not match reality TODAY, let alone in a few weeks. I feel like I’m taking crazy pills with the way people are talking about this whole thing still being out of control, when data shows the situation is even better than the most optimistic models were predicting. And by that I mean, pretend I was on HN 3 weeks ago predicting 25K deaths in the USA by today. I’d have been downvoted into oblivion and told I was delusional. But here we are. Clearly NYC was hit far harder than the rest of the country, but it seems like every state and municipality is simply basing their models on NYC case numbers scaled by population. I don’t get it.
  - throwaway237683 7y ago
    You're not crazy. It was very clear from the way the situation was handled even a month ago that CA and NY governors are not wasting time with this good crisis, and are using it for their political gain. The rampant fear mongering was used to overblow the severity of the situation and sell the idea of locking down hard before it's too late, completely disregarding the economy fallout, all the while projecting the image of Strong Leaders and Saviors of the Nation. A bit of too late for this election year (if elections are not postponed, that is!) but definitely will be useful for the next election cycle. The actual data did not support the apocalyptic prognoses then and it looks even more at contrast with what is going on now. But good luck explaining that to a bunch of people scared to death because of the constant hammering of ZOMG PEOPLE ARE DYING!!!!111 from the news. All in all it's a #FakeApocalypse. As it was obvious two months ago.
riazrizvi 7y ago
This plan also ignores the question of the majority of people who have likely been infected with no symptoms that could be identified with widespread Serology/Antibody tests. I find it alarming that this plan ignores that, is the governor priming is for population wide vaccination that is likely to be unnecessary? If we confirm widespread recovery and immunity then larger numbers of people can get back to life as usual quite soon.
- Gibbon1 7y ago
  The plan ignores that because people working on this are consistently finding infection rates of less than a few percent. Stanford tested 2888 samples that were negative for flu and other respiratory viruses and didn't find any positive for SAR-COV2 until Feb 21st and Feb23.
  - riazrizvi 7y ago
    A source for what you are saying is the linked SF article [1] which indicates that of ~3k evidently sick people with flu symptoms, 0.1-1% were confirmed to have COVID-19. Though note this is not random population sampling, on an interesting scale, so ignores asymptomatic question. Worldwide analysis of death rates [2], indicates #infected-so-far = 700-1600 x #dead so far. And data from Iceland [3], the only country with widespread sampling of asymptomatic population, is aligned with these numbers. Based on the analysis and support from Iceland, Covid-19 testing to see if patients actively have the disease are likely inaccurate and also a policy of only permitting testing of severe symptom patients is depressing reported numbers of once infected. [1] https://www.sfgate.com/coronavirus/article/Think-you-got-the-coronavirus-last-winter-stanford-15193019.php https://www.sfgate.com/coronavirus/article/Think-you-got-the... [2] Analysis of #infected today from #dead today, using following assumptions: 1. death statistics are reliable, since cause of death tests can adequately collect fluid samples (a major source of inaccuracy in COVID-19 testing), source = talking to medical staff at Bay Area sites. 2. E[days between first infection and death] = 14 (lost the source at the moment), Therefore, number of dead today D => number of infected 14 days ago = 100 D 3. rate of death increase consistently trends around 25%/day or 15% with full lockdown, source CDC situation reports worldwide excluding regions with restricted access to journalists 4. therefore, #infected today = #infected 14 days ago growing at 25% daily = 22X, or 7X if your region was locked down for last 2 weeks 5. so #infected=2200D or 700D [3] Last week, CDC reported 2 deaths today for Iceland, and admittedly-non-random sampling by DeCode indicated upto 1% of population have/had virus, upto 3600. Iceland has done strict quarantining of confirmed and suspected cases, and extensive testing since February, so despite no lockdown, I would put them at the 700X end of the estimate. They report ~1000 confirmed cases, so they would actually estimate 3600-1000 infected so far. My estimate would have indicated 2200-700 X D (= today's deaths, 2) = 4400 to 1400 cases.
majormajor 7y ago
Can you trust that data to be perfectly comparable? Testing capacity ramped up at a different rate than cases. Testing guidance has been spotty too. The days right after increases in testing access could be very noisy. I would look to the deaths curve much before the new cases curve, even though it's less responsive to changes. I assume fewer deaths have slipped through the cracks (though I'm sure some have).
citilife 7y ago
Something weird happened in California, where 20% of their tests were coming back positive, then all the sudden 04/04/2020 they started seeing <10% positive tests: https://raw.githubusercontent.com/lettergram/covid19-analysis/master/graphs/us-test-ratios-by-state.png https://raw.githubusercontent.com/lettergram/covid19-analysi... They also barely tested at all prior to 04/04/2020: https://raw.githubusercontent.com/lettergram/covid19-analysis/master/graphs/us-tests-by-state.png https://raw.githubusercontent.com/lettergram/covid19-analysi... In generally though, the rate of positive tests is increasing nation wide: https://raw.githubusercontent.com/lettergram/covid19-analysis/master/graphs/us-test-ratios.png https://raw.githubusercontent.com/lettergram/covid19-analysi... Implying we are still on a solid growth curve, as our testing capacity has maintained relatively constant levels: https://raw.githubusercontent.com/lettergram/covid19-analysis/master/graphs/us-counts.png https://raw.githubusercontent.com/lettergram/covid19-analysi... I can't speak to the hospitalization levels, but I suspect people are avoiding the hospital. My roommate decided not to get tested and stay home, even though he was having difficulty breathing. He seems past it after a couple weeks.
- jml7c5 7y ago
  >Something weird happened in California, where 20% of their tests were coming back positive, then all the sudden 04/04/2020 they started seeing <10% positive tests: This is not surprising. When tests were scarce, tests would be rationed to those most suspected of infection.
  - rhizome 7y ago
    Tests are still scarce.
    - mc32 7y ago
      Maybe but it’s all relative. Even a little less scarcity can change those numbers in significant ways.
      - rhizome 7y ago
weaksauce 7y ago
the dotted line is what we would expect if the intervention is removed as of today. the red dots are actual hospitalizations as of right now. the blue line was the predicted line for hospitalizations... she mentions that we are doing better than the prediction as of right now. it was not altogether that clear but in the context of the press briefing it's more clear.
- slg 7y ago
  This is poorly designed graph because it can give the wrong impression when it isn't accompanied with the explanation that was given in the press conference. I am not usually one to make a "this should be higher" comment on HN, but this is the proper interpretation and lots of people are being misled by not seeing it.
Zenst 7y ago
Also the hospital bed line that many draw are all based upon having medical staff for them. So does somewhat depend upon no staff shortages due to illness impacting capacity of hospital bed numbers.
tomerico 7y ago
What bothers me the most is that the comparison is always against a hypothetical "do nothing" strategy, ignoring the fact that different countries have employed different strategies, some of them have been highly successful in containing the disease without any lock down (Korea, Taiwan, and Australia) come to mind.
- ridaj 7y ago
  Aren't the techniques that Taiwan and Korea have employed (testing, isolation of known cases, contact tracing) irrelevant at this stage of contagion? I doubt of the efficacy of contact tracing when you have enough of a percentage of population infected that a single visit to Costco or any other supermarket would mean a very high chance of being there at the same time as an infectious person...
  - tomerico 7y ago
    I think that the answer is that we don't know what's the effect of each measure. The fact that Japan & Australia did not employ contact tracing, but also managed to contain the spread shows that there are other factors at play. It might be face masks use, or temperature (for Australia), but it does show that there are potential alternatives that could be viable.
- prawn 7y ago
  "some of them have been highly successful in containing the disease without any lock down (Korea, Taiwan, and Australia) come to mind." How are you defining lock down here? I live in Australia and most people I know have been working from home for weeks and have had kids out of school during that time. All restaurants have been closed for a while now. There are stops/checks at border entry points between states, even at points 1-2 hours in from the border, enforced quarantine for anyone arriving interstate. Weddings restricted to 5 people, funerals to 10. People are getting fined $1k+ for non-essential travel (group of kids this week copped big fines for getting up and congregating to see the sunrise). At almost every "essential" business I've visited, there have been spacing markers on the floor. Supermarkets have plastic shields between the checkout operator and shopper. Gloves, hand-washing, etc at any food pick-up place I've seen. I don't favour our current leaders at either state or national level, but since Morrison's Hillsong weekend, he's barely put a foot wrong. Senior politicians have been serious and escalated restrictions as appropriate (ignoring Ruby Princess). I'm sure there are more serious levels of lock down, but it's been part of the response in Australia.

ta1234567890 7y ago

> The graph on slide two[1] of the official CA govt plan shows hospitalizations With Intervention rising exponentially It does not. The exponential curve, per the graph legend, is what would be expected without intervention.

mikekij 7y ago
The light blue curve, labeled "With Intervention", is an upward-facing concave curve. Even if it were linear, it does not align with the observed data referenced in the link labeled [2].
- joe_the_user 7y ago
  OK, looking at the new cases curve on your covid-19.direct page. As presented, you can't really see what the green curve is doing. If you remove the black, total curve, the green new case curve is visible but it seems to be going up and down fairly inconclusively. Until 4/1, it looks like exponential growth. After that, it goes down and then up. Sure, the optimistic view is it's plateaued or going downward and I hope that's true but counting on just twelve days of data seems foolish.
  - mikekij 7y ago
    "If you remove the black, total curve, the green new case curve is visible but it seems to be going up and down fairly inconclusively." The best fit line of new cases after 4/4 is a linear function with a definitively negative slope. It is conclusively not a function that contributes to the upward, concave blue line on the state's graph.
    - joe_the_user 7y ago
      Who cares what the best fit is. There is simply not enough data. You're talking twelves data points with considerable variation. Using statistic doesn't turn muddy and ambiguous data into a clear signal magically.
      - mikekij 7y ago
        My point is that there is no extrapolation of the data we’ve seen to date that yields the blue line on their graph.
        joe_the_user 7y ago
        Sure, but I think they are tracing the worst case scenario based on the underlying assumption that the virus increases exponentially. What going to happen is indeed inherently uncertain so we pretty much have to prepare for the worst plausible series of events. Once it becomes clear that a better outcome is fairly likely, then the plans can shift.

okintheory 7y ago

That makes you think it should be a bell curve? Are you arguing it will be a bell curve with such a peak, even if restrictions are weakened or removed? That is unlikely.

mikekij 7y ago
I am not. I am arguing that the current trajectory data we're observing [2] does not align with the projections of our current trajectory provided by the government of California (the light blue line labeled 'With Intervention' [1]) [1] https://www.gov.ca.gov/wp-content/uploads/2020/04/California.. https://www.gov.ca.gov/wp-content/uploads/2020/04/California.... [2] https://covid-19.direct/state/CA https://covid-19.direct/state/CA
- okintheory 7y ago
  But you wrote "meaning that the graph of active hospitalizations should be a bell curve with a maximum value of ~10,000 on ~4/20."? You didn't mean that?
  - mikekij 7y ago
    I meant that "the graph of active hospitalizations should be a bell curve with a maximum value of ~10,000 on ~4/20" with the current mitigations in place. That is not what the government report is projecting. They're projecting unbounded, exponential growth with current mitigations in place, even though that is not in line with the data we've seen over the past two weeks.

archgoon 7y ago

Why should infections follow a bell curve? Shouldn't it be the derivative of a the logistic curve, which should be approximately exponential on both ends. I don't see how a quadratic should show up in the exponent; either mathematically or epidemiologically.

mikekij 7y ago
You're pointing out a great ambiguity in the state's graph. Is the hospitalization line a cumulative count of all hospitalizations? Or hospitalizations at any given time? Since the state's hospital capacity is related to hospitalizations at a given time, and not cumulative, I'm assuming the fit of that graph would be a bell curve with a max, followed by a decrease. People either die or leave the hospital.
wtvanhest 7y ago
Does anyone have the ability to walk through these explanations in a little more detail. I'm having trouble understanding why infections would be a bell curve, or derivative of a log curve.
- mikekij 7y ago
  Cumulative infections would not be a bell curve. They'd be a sigmoid curve, approaching some upper limit (e.g. 100,000). Current Hospitalizations, which is the number we should be most concerned about, and is reflected by the orange dots on the state's graph, should start low, max out at a number, and eventually return to 0. That should follow something like a bell curve. I think the confusion is between the "total infections" curve and the "current hospitalizations" curve. The difference between them is huge, and really important. The "Flatten the Curve" idea refers to keeping the number of hospitalizations at any one moment below some upper limit, ideally the state's number of available ICU beds. That's a bell curve.
  - SquishyPanda23 7y ago
    > think the confusion is between the "total infections" curve and the "current hospitalizations" curve. I think the confusion is that if the CDF is the logistic function, then the PDF is the logistic distribution. This is what archgoon is saying. Bell curve refers to a Gaussian distribution, which is different but looks similar. https://en.m.wikipedia.org/wiki/Logistic_distribution https://en.m.wikipedia.org/wiki/Logistic_distribution http://visionlab.harvard.edu/Members/Anne/Math/Logistic_vs_Gaussian.html http://visionlab.harvard.edu/Members/Anne/Math/Logistic_vs_G...

Ninjak8051 7y ago

Additionally, notice that the orange data points (actual hospitalizations) are significantly under the "With Intervention" plot. So why even include the slide? Clearly the assumptions behind the "With Intervention" plot do not match reality TODAY, let alone in a few weeks. Not a good sign if people are making actual decisions based on this.

mikekij 7y ago
My former physics professors would have not approved of a graph like this. D+ on the lab at best.
- dehrmann 7y ago
  https://i.imgur.com/dJ7kHch.png https://i.imgur.com/dJ7kHch.png It's pretty sloppy to show surge capacity on the same graph as total hospitalizations, not active active hospitalizations.
xienze 7y ago
> Clearly the assumptions behind the "With Intervention" plot do not match reality TODAY, let alone in a few weeks. I feel like I’m taking crazy pills with the way people are talking about this whole thing still being out of control, when data shows the situation is even better than the most optimistic models were predicting. And by that I mean, pretend I was on HN 3 weeks ago predicting 25K deaths in the USA by today. I’d have been downvoted into oblivion and told I was delusional. But here we are. Clearly NYC was hit far harder than the rest of the country, but it seems like every state and municipality is simply basing their models on NYC case numbers scaled by population. I don’t get it.
- throwaway237683 7y ago
  You're not crazy. It was very clear from the way the situation was handled even a month ago that CA and NY governors are not wasting time with this good crisis, and are using it for their political gain. The rampant fear mongering was used to overblow the severity of the situation and sell the idea of locking down hard before it's too late, completely disregarding the economy fallout, all the while projecting the image of Strong Leaders and Saviors of the Nation. A bit of too late for this election year (if elections are not postponed, that is!) but definitely will be useful for the next election cycle. The actual data did not support the apocalyptic prognoses then and it looks even more at contrast with what is going on now. But good luck explaining that to a bunch of people scared to death because of the constant hammering of ZOMG PEOPLE ARE DYING!!!!111 from the news. All in all it's a #FakeApocalypse. As it was obvious two months ago.

riazrizvi 7y ago

This plan also ignores the question of the majority of people who have likely been infected with no symptoms that could be identified with widespread Serology/Antibody tests. I find it alarming that this plan ignores that, is the governor priming is for population wide vaccination that is likely to be unnecessary? If we confirm widespread recovery and immunity then larger numbers of people can get back to life as usual quite soon.

Gibbon1 7y ago
The plan ignores that because people working on this are consistently finding infection rates of less than a few percent. Stanford tested 2888 samples that were negative for flu and other respiratory viruses and didn't find any positive for SAR-COV2 until Feb 21st and Feb23.
- riazrizvi 7y ago
  A source for what you are saying is the linked SF article [1] which indicates that of ~3k evidently sick people with flu symptoms, 0.1-1% were confirmed to have COVID-19. Though note this is not random population sampling, on an interesting scale, so ignores asymptomatic question. Worldwide analysis of death rates [2], indicates #infected-so-far = 700-1600 x #dead so far. And data from Iceland [3], the only country with widespread sampling of asymptomatic population, is aligned with these numbers. Based on the analysis and support from Iceland, Covid-19 testing to see if patients actively have the disease are likely inaccurate and also a policy of only permitting testing of severe symptom patients is depressing reported numbers of once infected. [1] https://www.sfgate.com/coronavirus/article/Think-you-got-the-coronavirus-last-winter-stanford-15193019.php https://www.sfgate.com/coronavirus/article/Think-you-got-the... [2] Analysis of #infected today from #dead today, using following assumptions: 1. death statistics are reliable, since cause of death tests can adequately collect fluid samples (a major source of inaccuracy in COVID-19 testing), source = talking to medical staff at Bay Area sites. 2. E[days between first infection and death] = 14 (lost the source at the moment), Therefore, number of dead today D => number of infected 14 days ago = 100 D 3. rate of death increase consistently trends around 25%/day or 15% with full lockdown, source CDC situation reports worldwide excluding regions with restricted access to journalists 4. therefore, #infected today = #infected 14 days ago growing at 25% daily = 22X, or 7X if your region was locked down for last 2 weeks 5. so #infected=2200D or 700D [3] Last week, CDC reported 2 deaths today for Iceland, and admittedly-non-random sampling by DeCode indicated upto 1% of population have/had virus, upto 3600. Iceland has done strict quarantining of confirmed and suspected cases, and extensive testing since February, so despite no lockdown, I would put them at the 700X end of the estimate. They report ~1000 confirmed cases, so they would actually estimate 3600-1000 infected so far. My estimate would have indicated 2200-700 X D (= today's deaths, 2) = 4400 to 1400 cases.

majormajor 7y ago

Can you trust that data to be perfectly comparable? Testing capacity ramped up at a different rate than cases. Testing guidance has been spotty too. The days right after increases in testing access could be very noisy. I would look to the deaths curve much before the new cases curve, even though it's less responsive to changes. I assume fewer deaths have slipped through the cracks (though I'm sure some have).

citilife 7y ago

Something weird happened in California, where 20% of their tests were coming back positive, then all the sudden 04/04/2020 they started seeing <10% positive tests: https://raw.githubusercontent.com/lettergram/covid19-analysis/master/graphs/us-test-ratios-by-state.png https://raw.githubusercontent.com/lettergram/covid19-analysi... They also barely tested at all prior to 04/04/2020: https://raw.githubusercontent.com/lettergram/covid19-analysis/master/graphs/us-tests-by-state.png https://raw.githubusercontent.com/lettergram/covid19-analysi... In generally though, the rate of positive tests is increasing nation wide: https://raw.githubusercontent.com/lettergram/covid19-analysis/master/graphs/us-test-ratios.png https://raw.githubusercontent.com/lettergram/covid19-analysi... Implying we are still on a solid growth curve, as our testing capacity has maintained relatively constant levels: https://raw.githubusercontent.com/lettergram/covid19-analysis/master/graphs/us-counts.png https://raw.githubusercontent.com/lettergram/covid19-analysi... I can't speak to the hospitalization levels, but I suspect people are avoiding the hospital. My roommate decided not to get tested and stay home, even though he was having difficulty breathing. He seems past it after a couple weeks.

jml7c5 7y ago
>Something weird happened in California, where 20% of their tests were coming back positive, then all the sudden 04/04/2020 they started seeing <10% positive tests: This is not surprising. When tests were scarce, tests would be rationed to those most suspected of infection.
- rhizome 7y ago
  Tests are still scarce.
  - mc32 7y ago
    Maybe but it’s all relative. Even a little less scarcity can change those numbers in significant ways.
    - rhizome 7y ago

weaksauce 7y ago

the dotted line is what we would expect if the intervention is removed as of today. the red dots are actual hospitalizations as of right now. the blue line was the predicted line for hospitalizations... she mentions that we are doing better than the prediction as of right now. it was not altogether that clear but in the context of the press briefing it's more clear.

slg 7y ago
This is poorly designed graph because it can give the wrong impression when it isn't accompanied with the explanation that was given in the press conference. I am not usually one to make a "this should be higher" comment on HN, but this is the proper interpretation and lots of people are being misled by not seeing it.

Zenst 7y ago

Also the hospital bed line that many draw are all based upon having medical staff for them. So does somewhat depend upon no staff shortages due to illness impacting capacity of hospital bed numbers.

tomerico 7y ago

What bothers me the most is that the comparison is always against a hypothetical "do nothing" strategy, ignoring the fact that different countries have employed different strategies, some of them have been highly successful in containing the disease without any lock down (Korea, Taiwan, and Australia) come to mind.

ridaj 7y ago
Aren't the techniques that Taiwan and Korea have employed (testing, isolation of known cases, contact tracing) irrelevant at this stage of contagion? I doubt of the efficacy of contact tracing when you have enough of a percentage of population infected that a single visit to Costco or any other supermarket would mean a very high chance of being there at the same time as an infectious person...
- tomerico 7y ago
  I think that the answer is that we don't know what's the effect of each measure. The fact that Japan & Australia did not employ contact tracing, but also managed to contain the spread shows that there are other factors at play. It might be face masks use, or temperature (for Australia), but it does show that there are potential alternatives that could be viable.
prawn 7y ago
"some of them have been highly successful in containing the disease without any lock down (Korea, Taiwan, and Australia) come to mind." How are you defining lock down here? I live in Australia and most people I know have been working from home for weeks and have had kids out of school during that time. All restaurants have been closed for a while now. There are stops/checks at border entry points between states, even at points 1-2 hours in from the border, enforced quarantine for anyone arriving interstate. Weddings restricted to 5 people, funerals to 10. People are getting fined $1k+ for non-essential travel (group of kids this week copped big fines for getting up and congregating to see the sunrise). At almost every "essential" business I've visited, there have been spacing markers on the floor. Supermarkets have plastic shields between the checkout operator and shopper. Gloves, hand-washing, etc at any food pick-up place I've seen. I don't favour our current leaders at either state or national level, but since Morrison's Hillsong weekend, he's barely put a foot wrong. Senior politicians have been serious and escalated restrictions as appropriate (ignoring Ruby Princess). I'm sure there are more serious levels of lock down, but it's been part of the response in Australia.