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  1. #3901
    Aware since 2004 Witrebel's Avatar
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    Originally Posted by AltarOfPlagues View Post
    it isnt THAT contagious. i tried to tell you off top but you dont wanna listen. if you are fukkin laying in the same bed with the person every single night, breathin up all they air, the rate is like 85%.

    no fukkin shiit 70% wasnt infected. those numbers were never remotely based in any reality. i said you would have to have naked orgies to get these rates.

    the wuhan data was always legit and corroborated by lombardy.

    the rate increases (case and death) could soley be attributed to population densities, sociocultural activities, comorbidities and population age.

    this idea that the infection rate was only capped by the actual number of people was never grounded in anything empirical.

    96 million cases in the US my ass
    Here's to hopping my ass was wrong man. I can't find any granular data to fact check that this holds true after March 8th.

    https://arxiv.org/ftp/arxiv/papers/2003/2003.09320.pdf Here is the original paper that this stems from.

    If you graph the data from the whole of lombardia I don't know that it really holds up. The peak of cases per day occurs on March 21st. If we backdate the onset of symptoms 1 week you get the 14th. If you backdate the contagion event you get peak contagion events per day on March 7th. This is in the middle of the lockdown phase, so the rollup data would still somewhat support lockdown's being the reason cases are peaking. Without granular data to show that those cities had sustained reduction in cases from March 8th onward, I'm not ready to "call it".

    Interestingly enough, it would appear the market is optimistic though.
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    Originally Posted by Witrebel View Post
    Here's to hopping my ass was wrong man. I can't find any granular data to fact check that this holds true after March 8th.

    https://arxiv.org/ftp/arxiv/papers/2003/2003.09320.pdf Here is the original paper that this stems from.

    If you graph the data from the whole of lombardia I don't know that it really holds up. The peak of cases per day occurs on March 21st. If we backdate the onset of symptoms 1 week you get the 14th. If you backdate the contagion event you get peak contagion events per day on March 7th. This is in the middle of the lockdown phase, so the rollup data would still somewhat support lockdown's being the reason cases are peaking. Without granular data to show that those cities had sustained reduction in cases from March 8th onward, I'm not ready to "call it".

    Interestingly enough, it would appear the market is optimistic though.
    Why 7 days from peak contagion to onset of symptoms? That seems kind of long I thought it was 4-5 days?
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    Originally Posted by keyboardworkout View Post
    Chit son I have to put away all of my diamond surfaces now.
    Lurking since '05 - the days of VS gorilla/cloud/goku threads

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    Originally Posted by Kawhilights View Post
    Chit son I have to put away all of my diamond surfaces now.
    " SARS-CoV-2 RNA was identified on a variety of surfaces in cabins of both symptomatic and asymptomatic infected passengers up to 17 days after cabins were vacated on the Diamond Princess but before disinfection procedures had been conducted (Takuya Yamagishi, National Institute of Infectious Diseases, personal communication, 2020). Although these data cannot be used to determine whether transmission occurred from contaminated surfaces, further study of fomite transmission of SARS-CoV-2 aboard cruise ships is warranted. "
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  5. #3905
    Aware since 2004 Witrebel's Avatar
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    Originally Posted by Farley1324 View Post
    Why 7 days from peak contagion to onset of symptoms? That seems kind of long I thought it was 4-5 days?
    Rule of thumb from "my guy".
    A simple 1-1-1 rule for backdating and forward-dating events

    one week from contagion to testing: {hospitalization, confinement, release}
    one week from hospitalization to {ICU, release}
    one week from ICU to {death, release}

    Always hoping for the latter.
    https://twitter.com/oliverbeige/stat...19067605467136

    My guess is that you figure a day or two from onset to account for delays in getting to a testing site and/or getting admitted. Onset of fever <> instant positive test result etc.
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    Okay so ~7 days from contraction to symptoms sufficient enough to push you for a test, which may be a couple days after onset of symptoms. That follows what we know as well as anything at this point
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    Originally Posted by theACEofSPADES View Post
    So how many of y'all are still going to the gym? Mine is closed but apparently will open on the 1st. Not sure if I wanna go, but I'm losing my mind sitting at home
    that is ridiculously weird that it opens so early in the midst of this disaster. think may would be the best option for opening up again
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  8. #3908
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    Originally Posted by Witrebel View Post
    I've been doom and gloom crew since early January. So hopefully my optimism carries some weight here.

    Pretend for a moment that no one has ever said "70% of the population will get this infection" Also forget that the expectation is it takes 60-70% of a population to acquire complete immunity before the virus will burn out.

    Lets just look at the DATA from italy. The Y axis is number of cases. This is restricted to these 4 cities. With shading per city.



    What lockdowns are doing is attempting to reduce the number of transmissions. Transmissions take time to become symptomatic cases. This data is showing when people became symptomatic.

    So then lets overlay the time lag from transmission (contagion event) to symptom onset.



    Here are the italy lockdown dates: https://www.axios.com/italy-coronavi...897494dc6.html




    If you look at the second graph, Italy locked down well after the contagion event had peaked. This data is showing us that the virus was beginning to slow its spread in those cities, BEFORE social distancing was implemented. I do not have the answer why. It does not appear that the reason is that 70% of the entire city was infected. Maybe more like 50%, with half of those people being asymptomatic. This is still a problem for NYC, and it still means hospitals would be overrun for a period of time. But it's a way different picture than I've seen painted so far.
    Thank you for those graphs. Obviously Washingston State has a issue from the outbreak at the retirement home and NYC is so densely packed they are getting hit hard as well. We should focus most resources there and by mid April 80% of the US should be able to go back to a semi normal life.
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  9. #3909
    im gon make some shake AltarOfPlagues's Avatar
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    population densities in sq mi:

    nyc: 26,403
    ny state: 421

    milan: 20,000
    lombardy:1,100

    deagu (sk ground zero): 7,300
    SK total: 1,313

    stop thinking in terms of countries and start thinking in terms of cities.
    Last edited by AltarOfPlagues; 03-24-2020 at 09:28 AM.
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  10. #3910
    Aware since 2004 Witrebel's Avatar
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    Originally Posted by Farley1324 View Post
    Okay so ~7 days from contraction to symptoms sufficient enough to push you for a test, which may be a couple days after onset of symptoms. That follows what we know as well as anything at this point
    Correct. I will say that the datasets I have access to do not support the theory above.



    Blue line is cases per day rolled up for all of lombardia.

    Red line is if you subtract a week to estimate time of contraction.

    Notice how on the blue line, there is a significant valley right around March 8th? The paper was only using data up to March 8th.

    We need good data per city/outbreak cluster that shows that the new cases in lombardia overall are due to the virus reaching new populations, and not further infections in those same subsets that are in the report.

    Basically once again, without good granular data we are in the dark. I would say this theory has at least a 50/50 shot at being correct. And the fact that the market is up nearly 10% today makes me think I'm not the only one looking at this. Does anyone have another good reason to markets are so happy? Other than the money printer goes Brrrrrr?
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    im gon make some shake AltarOfPlagues's Avatar
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    Originally Posted by Witrebel View Post
    Basically once again, without good granular data we are in the dark. I would say this theory has at least a 50/50 shot at being correct. And the fact that the market is up nearly 10% today makes me think I'm not the only one looking at this. Does anyone have another good reason to markets are so happy? Other than the money printer goes Brrrrrr?

    we have more than enough data. distributions are fat tailed, data quantity doesnt matter. make small adjustments and the graphs go apeshiit. the data doesnt matter.

    this why the UK powers that be are brainlets. they were waiting on better and better data. you're lookin at a hurricane off brazil and calculating the destruction in florida.
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    Aware since 2004 Witrebel's Avatar
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    Originally Posted by AltarOfPlagues View Post
    we have more than enough data. distributions are fat tailed, data quantity doesnt matter. make small adjustments and the graphs go apeshiit. the data doesnt matter.

    this why the UK powers that be are brainlets. they were waiting on better and better data. you're lookin at a hurricane off brazil and calculating the destruction in florida.
    Okay but that's not just a fat tail, that's a blowout?

    The paper looks at data up to March 8th, and essentially concludes that the lockdown was late to have an effect, and the reduction in cases and deaths was due to natural causes, not the lockdown.

    If that was the case, you would have expected the "do nothing" case count for lombardia to have topped out around 4,189 cases. Those graphs I posted above show this, as they show the new cases per day virtually flattened out and done by March 8th.

    If we look at lombardia after March 8th, we see that an additional 24,000 or so cases have since been logged. Those cases aren't a fat tail, they are a 5x?

    Possible reasons:

    1) Increased testing.
    2) Virus spreading to other populations outside of the 3 clusters in the paper but within the bounds of lombardia.

    Not saying the theory is wrong, but we do need data from those exact same clusters in the report going past march 8th. If we take that data, and then overlay the number of tests performed, we can validate that the contagion events were decreasing BEFORE the lockdown came. Untill we have that data, it's still just a theory.

    Given that multiple economies just got blown the fuk out, I think it's safe to say we need data before we conclude that all of those governments got it wrong, not to mention the epidemiology experts advising them.
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    Originally Posted by Witrebel View Post
    Given that multiple economies just got blown the fuk out, I think it's safe to say we need data before we conclude that all of those governments got it wrong, not to mention the epidemiology experts advising them.
    everyone is getting it right but 2 weeks + too late. SK got it right, but SK was also very lucky in that they were able to keep it out of seoul.
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    Originally Posted by AltarOfPlagues View Post
    everyone is getting it right but 2 weeks + too late. SK got it right, but SK was also very lucky in that they were able to keep it out of seoul.
    SK did something that most western countries's citizens wouldn't allow, wouldn't cooperate with, and aren't set up to do anyway (nor would we want to be)

    Israel is doing similar but not setup seemingly to go as far as SK

    https://theconversation.com/coronavi...illance-134068
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    Originally Posted by Farley1324 View Post
    SK did something that most western countries's citizens wouldn't allow, wouldn't cooperate with, and aren't set up to do anyway (nor would we want to be)

    Israel is doing similar but not setup seemingly to go as far as SK

    https://theconversation.com/coronavi...illance-134068
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    Originally Posted by Farley1324 View Post
    What do you want a source for?

    I'm lying? What am I lying about and what are you willing to wager on it?
    I'm just using your autist logic against you. If I was lying earlier then you are clearly lying now.

    Now post the data corroborating that everyone is in danger.
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    Originally Posted by Kirra View Post
    I'm just using your autist logic against you. If I was lying earlier then you are clearly lying now.

    Now post the data corroborating that everyone is in danger.
    What am I lying about? Quote it.

    You were lying which is why you wouldn't stand behind what you posted.
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    All this talk about data, and in comes a Stanford Epidimiologist
    https://www.statnews.com/2020/03/17/...reliable-data/

    A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data
    By JOHN P.A. IOANNIDISMARCH 17, 2020
    coronavirus testing
    A nurse holds swabs and a test tube to test people for Covid-19 at a drive-through station set up in the parking lot of the Beaumont Hospital in Royal Oak, Mich.
    PAUL SANCYA/AP
    The current coronavirus disease, Covid-19, has been called a once-in-a-century pandemic. But it may also be a once-in-a-century evidence fiasco.

    At a time when everyone needs better information, from disease modelers and governments to people quarantined or just social distancing, we lack reliable evidence on how many people have been infected with SARS-CoV-2 or who continue to become infected. Better information is needed to guide decisions and actions of monumental significance and to monitor their impact.

    Draconian countermeasures have been adopted in many countries. If the pandemic dissipates — either on its own or because of these measures — short-term extreme social distancing and lockdowns may be bearable. How long, though, should measures like these be continued if the pandemic churns across the globe unabated? How can policymakers tell if they are doing more good than harm?

    Vaccines or affordable treatments take many months (or even years) to develop and test properly. Given such timelines, the consequences of long-term lockdowns are entirely unknown.

    Related: We know enough now to act decisively against Covid-19. Social distancing is a good place to start
    The data collected so far on how many people are infected and how the epidemic is evolving are utterly unreliable. Given the limited testing to date, some deaths and probably the vast majority of infections due to SARS-CoV-2 are being missed. We don’t know if we are failing to capture infections by a factor of three or 300. Three months after the outbreak emerged, most countries, including the U.S., lack the ability to test a large number of people and no countries have reliable data on the prevalence of the virus in a representative random sample of the general population.

    This evidence fiasco creates tremendous uncertainty about the risk of dying from Covid-19. Reported case fatality rates, like the official 3.4% rate from the World Health Organization, cause horror — and are meaningless. Patients who have been tested for SARS-CoV-2 are disproportionately those with severe symptoms and bad outcomes. As most health systems have limited testing capacity, selection bias may even worsen in the near future.

    The one situation where an entire, closed population was tested was the Diamond Princess cruise ship and its quarantine passengers. The case fatality rate there was 1.0%, but this was a largely elderly population, in which the death rate from Covid-19 is much higher.

    Projecting the Diamond Princess mortality rate onto the age structure of the U.S. population, the death rate among people infected with Covid-19 would be 0.125%. But since this estimate is based on extremely thin data — there were just seven deaths among the 700 infected passengers and crew — the real death rate could stretch from five times lower (0.025%) to five times higher (0.625%). It is also possible that some of the passengers who were infected might die later, and that tourists may have different frequencies of chronic diseases — a risk factor for worse outcomes with SARS-CoV-2 infection — than the general population. Adding these extra sources of uncertainty, reasonable estimates for the case fatality ratio in the general U.S. population vary from 0.05% to 1%.

    STAT Reports: STAT’s guide to interpreting clinical trial results
    That huge range markedly affects how severe the pandemic is and what should be done. A population-wide case fatality rate of 0.05% is lower than seasonal influenza. If that is the true rate, locking down the world with potentially tremendous social and financial consequences may be totally irrational. It’s like an elephant being attacked by a house cat. Frustrated and trying to avoid the cat, the elephant accidentally jumps off a cliff and dies.

    Could the Covid-19 case fatality rate be that low? No, some say, pointing to the high rate in elderly people. However, even some so-called mild or common-cold-type coronaviruses that have been known for decades can have case fatality rates as high as 8% when they infect elderly people in nursing homes. In fact, such “mild” coronaviruses infect tens of millions of people every year, and account for 3% to 11% of those hospitalized in the U.S. with lower respiratory infections each winter.

    These “mild” coronaviruses may be implicated in several thousands of deaths every year worldwide, though the vast majority of them are not documented with precise testing. Instead, they are lost as noise among 60 million deaths from various causes every year.

    Although successful surveillance systems have long existed for influenza, the disease is confirmed by a laboratory in a tiny minority of cases. In the U.S., for example, so far this season 1,073,976 specimens have been tested and 222,552 (20.7%) have tested positive for influenza. In the same period, the estimated number of influenza-like illnesses is between 36,000,000 and 51,000,000, with an estimated 22,000 to 55,000 flu deaths.

    Note the uncertainty about influenza-like illness deaths: a 2.5-fold range, corresponding to tens of thousands of deaths. Every year, some of these deaths are due to influenza and some to other viruses, like common-cold coronaviruses.

    In an autopsy series that tested for respiratory viruses in specimens from 57 elderly persons who died during the 2016 to 2017 influenza season, influenza viruses were detected in 18% of the specimens, while any kind of respiratory virus was found in 47%. In some people who die from viral respiratory pathogens, more than one virus is found upon autopsy and bacteria are often superimposed. A positive test for coronavirus does not mean necessarily that this virus is always primarily responsible for a patient’s demise.

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    If we assume that case fatality rate among individuals infected by SARS-CoV-2 is 0.3% in the general population — a mid-range guess from my Diamond Princess analysis — and that 1% of the U.S. population gets infected (about 3.3 million people), this would translate to about 10,000 deaths. This sounds like a huge number, but it is buried within the noise of the estimate of deaths from “influenza-like illness.” If we had not known about a new virus out there, and had not checked individuals with PCR tests, the number of total deaths due to “influenza-like illness” would not seem unusual this year. At most, we might have casually noted that flu this season seems to be a bit worse than average. The media coverage would have been less than for an NBA game between the two most indifferent teams.

    Some worry that the 68 deaths from Covid-19 in the U.S. as of March 16 will increase exponentially to 680, 6,800, 68,000, 680,000 … along with similar catastrophic patterns around the globe. Is that a realistic scenario, or bad science fiction? How can we tell at what point such a curve might stop?

    The most valuable piece of information for answering those questions would be to know the current prevalence of the infection in a random sample of a population and to repeat this exercise at regular time intervals to estimate the incidence of new infections. Sadly, that’s information we don’t have.

    In the absence of data, prepare-for-the-worst reasoning leads to extreme measures of social distancing and lockdowns. Unfortunately, we do not know if these measures work. School closures, for example, may reduce transmission rates. But they may also backfire if children socialize anyhow, if school closure leads children to spend more time with susceptible elderly family members, if children at home disrupt their parents ability to work, and more. School closures may also diminish the chances of developing herd immunity in an age group that is spared serious disease.

    This has been the perspective behind the different stance of the United Kingdom keeping schools open, at least until as I write this. In the absence of data on the real course of the epidemic, we don’t know whether this perspective was brilliant or catastrophic.

    Flattening the curve to avoid overwhelming the health system is conceptually sound — in theory. A visual that has become viral in media and social media shows how flattening the curve reduces the volume of the epidemic that is above the threshold of what the health system can handle at any moment.

    Related: The novel coronavirus is a serious threat. We need to prepare, not overreact
    Yet if the health system does become overwhelmed, the majority of the extra deaths may not be due to coronavirus but to other common diseases and conditions such as heart attacks, strokes, trauma, bleeding, and the like that are not adequately treated. If the level of the epidemic does overwhelm the health system and extreme measures have only modest effectiveness, then flattening the curve may make things worse: Instead of being overwhelmed during a short, acute phase, the health system will remain overwhelmed for a more protracted period. That’s another reason we need data about the exact level of the epidemic activity.

    One of the bottom lines is that we don’t know how long social distancing measures and lockdowns can be maintained without major consequences to the economy, society, and mental health. Unpredictable evolutions may ensue, including financial crisis, unrest, civil strife, war, and a meltdown of the social fabric. At a minimum, we need unbiased prevalence and incidence data for the evolving infectious load to guide decision-making.

    In the most pessimistic scenario, which I do not espouse, if the new coronavirus infects 60% of the global population and 1% of the infected people die, that will translate into more than 40 million deaths globally, matching the 1918 influenza pandemic.

    The vast majority of this hecatomb would be people with limited life expectancies. That’s in contrast to 1918, when many young people died.

    One can only hope that, much like in 1918, life will continue. Conversely, with lockdowns of months, if not years, life largely stops, short-term and long-term consequences are entirely unknown, and billions, not just millions, of lives may be eventually at stake.

    If we decide to jump off the cliff, we need some data to inform us about the rationale of such an action and the chances of landing somewhere safe.

    John P.A. Ioannidis is professor of medicine and professor of epidemiology and population health, as well as professor by courtesy of biomedical data science at Stanford University School of Medicine, professor by courtesy of statistics at Stanford University School of Humanities and Sciences, and co-director of the Meta-Research Innovation Center at Stanford (METRICS) at Stanford University.

    About the Author
    John P.A. Ioannidis
    jioannid@stanford.edu
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    That article was already posted in here, it's from a week ago and reads like it

    "Some worry that the 68 deaths from Covid-19 in the U.S. as of March 16 will increase exponentially to 680, 6,800, 68,000, 680,000 … along with similar catastrophic patterns around the globe. Is that a realistic scenario, or bad science fiction? How can we tell at what point such a curve might stop?"

    The first step of that has already come trie.

    Of course, exponential doesn't have to mean literally 10x more at every 'step' and exponential doesn't have to mean literally a 1,000x increase
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    Unfortunately an increase in Italy

    +5249 infected
    +743 dead
    +894 recovered
    bbsitum crew*

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    Originally Posted by cromofo View Post
    Unfortunately an increase in Italy

    +5249 infected
    +743 dead
    +894 recovered

    Oh FFS.


    So we're going to have to wait like a week to see what the outlier is (the two days down, or yesterday)
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    They need to get antibody testing rolled out nationwide ASAP. We need to know how many have been infected and got over it (likely for literally months now since we know patient zero goes WAY back into like mid January IIRC from what I read) as well as start to test those with little to no symptoms.

    Our death rate is well under 2% (like 1.2% last I checked), but that's only of the most extreme symptoms since we know they won't test you if you're not having difficulty breathing or have been in contact with a known infected person(s).

    We know there's at LEAST 2-3X more infected that have little to no symptoms but aren't being added to the "official" infected number. So what does that really put the death rate at? .5%, likely even less.

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    Originally Posted by R3L3NTL3SS View Post
    They need to get antibody testing rolled out nationwide ASAP. We need to know how many have been infected as well as start to test those with little to no symptoms.

    Our death rate is well under 2%, but that's only of the most extreme symptoms since we know they won't test you if you're not having difficulty breathing or have been in contact with a known infected person(s).

    We know there's at LEAST 2-3X more infected that have little to no symptoms but aren't being added to the "official" infected number. So what does that really put the death rate at? Well under 1%, likely even less.
    Keep in mind that math assumes every person currently infected and alive will not die. Remember the lags between onset of symptoms, testing, and death (where applicable). Early on in the exponential rampup we should expect cases to spike before deaths.

    So, we still don't know enough to say (common theme eh)
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    are the preexisting health conditions that are at risk only respiratory? i got neurological preexisting health conditions

    i don't think i have respiratory. i mean ive had bronchitis, pneumonia, asthma when i was a kid... sinus infections as a teen but i dont think they are conditions anymore
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  25. #3925
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    Originally Posted by cromofo View Post
    Unfortunately an increase in Italy

    +5249 infected
    +743 dead
    +894 recovered

    this is a good number

    5 day trend, 15% 14% 10% 8% 8%
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    Originally Posted by Farley1324 View Post
    Keep in mind that math assumes every person currently infected and alive will not die
    That is true, but unless we see an insane spike by next week in the percentage, it's probably safe to say that the 1.2% or so we're at now will be a pretty set in stone percentage. (+/-)
    It has been like 1.2-1.6% since the start of testing basically.

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    Originally Posted by R3L3NTL3SS View Post
    That is true, but unless we see an insane spike by next week in the percentage, it's probably safe to say that the 1.2% or so we're at now will be a pretty set in stone percentage. (+/-)
    It has been like 1.2-1.6% since the start of testing basically.
    the death knell for healthcare for all? what is the political impetus to test LESS?
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    COVID-19 is a new disease and there is limited information regarding risk factors for severe disease. Based on currently available information and clinical expertise, older adults and people of any age who have serious underlying medical conditions might be at higher risk for severe illness from COVID-19.

    Based upon available information to date, those at high-risk for severe illness from COVID-19 include:

    People aged 65 years and older
    People who live in a nursing home or long-term care facility
    Other high-risk conditions could include:
    People with chronic lung disease or moderate to severe asthma
    People who have serious heart conditions
    People who are immunocompromised including cancer treatment
    People of any age with severe obesity (body mass index [BMI] >40) or certain underlying medical conditions, particularly if not well controlled, such as those with diabetes, renal failure, or liver disease might also be at risk
    People who are pregnant should be monitored since they are known to be at risk with severe viral illness, however, to date data on COVID-19 has not shown increased risk
    Many conditions can cause a person to be immunocompromised, including cancer treatment, bone marrow or organ transplantation, immune deficiencies, poorly controlled HIV or AIDS, and prolonged use of corticosteroids and other immune weakening medications

    Those are the groups of people who might be at risk of severe sides.

    1/3 of Americans fall into those categories? Maybe when looked at as a whole. Definitely not when looked at by ahe group
    Last edited by BOZZ; 03-24-2020 at 10:56 AM.

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    Trump just said on a town hall that he hopes to open the country back up (or as much as possible) by Easter . . . but said it needs to be discussed further.
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    Originally Posted by taf1968 View Post
    Trump just said on a town hall that he hopes to open the country back up (or as much as possible) by Easter . . . but said it needs to be discussed further.
    Everyone knows im a 110% trump supporter.... but he is a fukcing idiot if he thinks things gonna go right in a week or 2
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