POLITICAL THREAD
- Thread starter kybobcat
- Start date
and I'm sure you're pro abortion. Just shut the hell up will you? Nobody cares less about human life than progressives that's number one. And number two it's not gonna kill half the people that the media lied to you about. This is being exploited to ruin the country's economy period. That's why the demon rats asked for their entire Christmas list in a so called stimulus bill
Just to be clear, and I'm not taking sides here, I think every politician in Washington is a crook - if Trump signs this, then you're admitting that he is complicit in said exploitation?
Buddy, it may be in NYC, but it is coming to your town next! All the experts agree, and Cuomo screamed that into my tiny brain earlier. It’s fn coming, and EVERYONE is gonna get it!
Still teaching mine how to calculate the cosine similarity between 2 vectors, which is great because I do that every day in my actual adult life.
First of all, I don't really pay attention to the news. I get my information from the CDC and their projections. Secondly, in what world would it make sense to destroy the economy? To get Trump out of the WH, that's asinine. It's not like those of a certain political affiliation are immune from this recession. We're all being hurt from this, both physically and fiscally.
Also, enough with these Strawman arguments. First, it's the flu, and now it's abortion? I like how you become combative when you don't have actual ideals. As others have pointed out, it does seem like you are solely here to troll and not expound actual ideals. At least with the other posters that I disagree with are civil or at least appear to be so.
Lastly, most of those provisions included by the Dems are literal pennies on the dollar when compared to the overall price tag of the stimulus package. Yes, I disagree with some of the things, such as raises for those in D.C. that already make more than enough to live on; but to say that they asked for "their entire Christmas list" is one failure of an argument.
I'd like you to posit your position on why this is being exploited to tank the economy. I want to see the facts presented and not just emotion.
Cheers,
Azurricat2010
yes it's terrible it'll destroy the country for generations. If he signs this my enthusiasm for him is gone
I was upset she lost but this is hilarious.
because for radical progressives the end justifies the means and they don't let a crisis go to waste. If that means death, destruction or loss of life that's all fine as long as they get more power and can turn this into a (more) socialist state. If you've studied Saul alinsky and rules for radicals you know these things. After impeachment flamed out they went right into this. When this blows over and it will blow over there's most likely gonna be violence
Most of us have been wearing out the worldometer viewing the China Flu stats.
Have you ventured to the whole site?
https://www.worldometers.info/
It has a world death meter( all causes)
It kind of puts this in perspective.
Watch it spin boys.
Have you ventured to the whole site?
https://www.worldometers.info/
It has a world death meter( all causes)
It kind of puts this in perspective.
Watch it spin boys.
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.
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.
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.
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.
https://www.statnews.com/2020/03/17...e-are-making-decisions-without-reliable-data/
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.
https://www.statnews.com/2020/03/17...e-are-making-decisions-without-reliable-data/
What kind of idiotic BS is this?
1) that's a false premise because we have no clue when either country had their first case.
2) we're not Italy in any shape form or fashion. Trying to compare apples to oranges. Why do people never say "well look at Germany"?
It isn't overrunning us like we were told. By last week, people were supposed to be dying in the street. Instead we have 737 dead nationwide out of over 54,000 KNOWN cases. That's about 1% on known cases. On total cases it's probably .01% or lower.
Compare the flu.
It was understandable to take the initial action given what was forecast. Now we have plenty enough data to show the mortality rate is nothing even remotely close to the forecast.
By Sunday if the rate of infected per test or the mortality rate doesn't shoot upward, it's time to open up shop and end this financial devastation
I would never have guessed! Just redlined the ole sarcasm meter.
I've read this about 10 times now. And I still can't get how she gets from point A to point B.
What friend is white? Is either friend white? Is she friends with a white supremacist? I seriously can't get what she's trying to say.
All I know is the US was at 1k cases 2 weeks ago and now we're over 50k. This is growing exponentially and we'll need to be proactive in slowing this growth down.
Thanks for the reading list.
We’re testing more people now than 2 weeks ago. It doesn’t mean the virus is spreading any faster, it simply means more tests have been given.
All I'm saying is let's focus on the areas that need the most help and let places where it's not an issue go to school and work and open business again. What we've done so far is like amputating both your arms because you have a broken thumb
I'd also like to add that the media did not decide to just start telling the truth about this when they've done nothing but lie since 2000. They don't tell you what will happen they say what they wish happens. I.e. Christine blasey ford had very credible damning testimony....trump colluded with the Russians. He withhold money from Ukraine there was a quid pro quo etc.
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I wish I can have that attitude but honestly, I think the next month will show us where exactly this is headed. I'd love for it to be a relative blip on the radar but I think we'll be close to a million infected in the states by the end of April. I've noticed a number of people comparing it to the Flu or the Swine Flu but with those, we actually have data sets and know-how to combat them.
It's the uncertainty that we're in and the combativeness we see in D.C. that makes me wary.
Agree. I think Easter is too long of a wait yet some (Democrats) want it to last indefinitely (political reasons).
Understandable, but the places that are being hit hard are the ones that move most of this nation's economy. Once Texas and Florida start seeing an increase in cases it'll likely be even worse as those two states, along with CA and NY are economic behemoths amongst a slew of small market states.
A lot of folks yelling about Trump wasn't prepared, gov'e wasn't prepared...and the big one...he closed down some department/agency (don't remember the name) that was responsible for taking care of things like this.....from today's news....
Walter Reed Army Institute of Research (WRAIR) in Silver Spring, Md., dedicated to coronavirus research.
The institute launched its Emerging Infectious Disease Branch about a year and a half ago. Within that period, its researchers completed two Phase 2 clinical trials of Ebola vaccine candidates in the U.S. and Africa, conducted a first-in-human trial of a Middle East Respiratory Syndrome (MERS) vaccine, and developed, manufactured and tested a Zika vaccine.
“We created this department to be already primed and ready to go," WRAIR branch director Dr. Kayvon Modjarrad told Military.com in March 4 interview.
Walter Reed Army Institute of Research (WRAIR) in Silver Spring, Md., dedicated to coronavirus research.
The institute launched its Emerging Infectious Disease Branch about a year and a half ago. Within that period, its researchers completed two Phase 2 clinical trials of Ebola vaccine candidates in the U.S. and Africa, conducted a first-in-human trial of a Middle East Respiratory Syndrome (MERS) vaccine, and developed, manufactured and tested a Zika vaccine.
“We created this department to be already primed and ready to go," WRAIR branch director Dr. Kayvon Modjarrad told Military.com in March 4 interview.
Why is it so hard for people to understand that the numbers we are looking at today happened two weeks ago. That is why the quarantined is for a two week duration.
There are people with a much firmer grasp on things than you leftists do, believe it or not.
Buddy we're way beyond a million infected right this very moment. The only thing holding us back is lack of testing.
They always assumed we'd all get it. That was the whole point of flatten the curve. So don't get confused on the red herring of avoiding infection. That isn't possible and was never the goal. They just assumed a higher percentage would be critical. It just isn't happening.
So it doesn't matter if it's next week or next month or next year. The percentage of critically ill will continue to drop as they confirm more cases. Same with mortality rate. Neither will go up.
So its time to go back to business
All the doctors, hospitals, sick, and dead people are simply making up stuff. Is that what you are saying.
Important to remember that Levi actively, and without exception, supports the people who demanded they get raises, illegals get amnesty, and millions of dollars for “art” or they wouldn’t help Americans who lost their job due to a pandemic.
Maybe he’ll write a few more condescending, run-on, adjective filled sentences that say nothing but make him feel like his associates degree from Sullivan puts him above the rest of the population in response. Who knows? Who cares?
Maybe he’ll write a few more condescending, run-on, adjective filled sentences that say nothing but make him feel like his associates degree from Sullivan puts him above the rest of the population in response. Who knows? Who cares?
You still haven't replied to me. : (. I asked you what you thought about today's headline on CNN.com that said "Trump more popular than ever."
Explain how the numbers are from 2 weeks ago? Do you think the virus just started circulating in the nation 2 weeks ago?
Two weeks is the maximum incubation period, most people that actually get sick start showing signs within 5 days.
I dont know what all the arguments were here but I've noticed this:
"Corporations bad, billionaires. We help workers"
So the solution is to ignore that millions of people actually work for corporations and their helping is to give 4 months or whatever of unemployment. Cool. So after that 4 months where do they go? You know, bc they denied giving the corporations money to keep their workers employed.
But atleast NPR will be fully funded forever...was important to get that in there. A trillion dollar surplus went to 2.5 trillion. Total pennies. 300,000,000 for public broadcasting. Thank God I can now look up what the emissions on my flight are now tho and the airlines are spending on their carbon offsets, NOT the workers.
Atleast righties naturally distrust the govt. I cant understand still believing these people are only doing what's in the best interest for people. You know good and well the left has found a way to get these funds rerouted to them. All of a sudden, like with PP, we'll see public broadcasting donating millions to dem elections.
Doesn't matter. None of them should get a raise for a crises in which they have really done nothing to prevent or help control. Furthermore, for them spending millions on for a 3 1/2 year false claims for impeachment. This is a slap in the face on all Americans
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