fuck off
- Thread starter LaoTze
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Fuck you fuck you fu-curiosity.
To fuck for the cunt! to fuck for the cunt! to fuck for the country.
To fuck for the cunt! to fuck for the cunt! to fuck for the country.
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When so many others go off separately on their own Wuhan thread, what the fucking fuck must my thread be merged into some cheebye wuhan thread?
BECAUSE SOME LANJEOW CHEEBYE MODERATOR WANT WHAT I SAY IN HIS FUCKING THREAD???
AND AFTER I MOVED IT OUT, TO MOVE THAT BACK IN AND LET ALL OTHER WUHAN THREADS SPREAD ABOUT LIKE COCKROACHES FUCKING ABOUT?
BECAUSE SOME LANJEOW CHEEBYE MODERATOR WANT WHAT I SAY IN HIS FUCKING THREAD???
AND AFTER I MOVED IT OUT, TO MOVE THAT BACK IN AND LET ALL OTHER WUHAN THREADS SPREAD ABOUT LIKE COCKROACHES FUCKING ABOUT?
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It should be noted that the graph is in log scale. If it was in real terms the graph would look a lot more parabolic in presentation.
The first takeaway is that the infection rate is still expanding at an exponential level and no sign that the infection rate is slowing down. Therefore to answer the question - will we get to 100,000 within a week? No one knows but the model is projecting it will and so far the model is tracking in line with the reported infection numbers.
The second takeaway is whatever measures that are currently being taken is not slowing down the infection rate because the actual trajectory of the graph is not showing any slowing down. At some point I expect to see numbers indicating a slow down in infection rate via a deviation in actual data vs projected data as illustrated in the graph. When the incoming data starts to support such a state of slowing down then we will know but how soon can we see that is an unknown.
Finally, a 45 degree expansion angle is normally quite sustainable as a natural state but given it is in log scale, some reservation of such an interpretation would apply. In other words, my concern is it might have some way to go before the graph starts to slow down. .
IT AS SUPPOSED TO BE 10,000 TODAY. SO IT IS SLOWING DOWN A BIT
The first takeaway is that the infection rate is still expanding at an exponential level and no sign that the infection rate is slowing down. Therefore to answer the question - will we get to 100,000 within a week? No one knows but the model is projecting it will and so far the model is tracking in line with the reported infection numbers.
The second takeaway is whatever measures that are currently being taken is not slowing down the infection rate because the actual trajectory of the graph is not showing any slowing down. At some point I expect to see numbers indicating a slow down in infection rate via a deviation in actual data vs projected data as illustrated in the graph. When the incoming data starts to support such a state of slowing down then we will know but how soon can we see that is an unknown.
Finally, a 45 degree expansion angle is normally quite sustainable as a natural state but given it is in log scale, some reservation of such an interpretation would apply. In other words, my concern is it might have some way to go before the graph starts to slow down. .
IT AS SUPPOSED TO BE 10,000 TODAY. SO IT IS SLOWING DOWN A BIT
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This is a twitter thread by an infectious disease specialist in the UK, featuring good quality data and papers on the topic so far, and she keeps it up to date as well. There has been a lot of debates on here about how deadly this disease is (and to that extent, the mortality rate). The fact of the matter is we simply do not have enough data to draw a solid conclusion ( see: https://www.nejm.org/doi/full/10.1056/NEJMp2000929 ). As eluded by other members already, there are potentially many who have caught the disease but they either suffered from very mild symptoms or none at all, and did not seek any medical attention. Table below for comparison of recent viral outbreaks.
![[IMG]](https://www.nejm.org/na101/home/literatum/publisher/mms/journals/content/nejm/0/nejm.ahead-of-print/nejmp2000929/20200124/images/img_xlarge/nejmp2000929_t1.jpeg "[IMG]")
https://news.sina.cn/zt_d/yiqing0121?wm=3200_0002
Live tracking of all the nCOV-2019 in China, it seems to update on an hourly basis and all data are pulled from each province's respective health department. This is in Chinese, but the 4 numbers above to map corresponds to: confirmed case, suspect case, death, and cured respectively from left to right. This should put to rest any argument about Chinese government not being transparent about the outbreak.
https://mp.weixin.qq.com/s/tJgis_HkAyASFpnL0ZZRDg
The 3rd edition of national guidance on diagnosis + treatment of nCOV-2019; this is circulated on a wechat medical group, and unfortunately only in Chinese as well. Very technical documents where it offers clinical definitions and suggested treatments; interestingly it also recommends traditional chinese medicine formulary for treatment.
https://mp.weixin.qq.com/s/Ra67Qfagw5XMF0LcPUhY-g
Presentation slides given by Wuhan doctors, mainly focusing on the radiology findings of the disease. Again in Chinese only and a very technical document.
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Construction of 2 new Wuhan hospitals being live streamed
https://m.yangshipin.cn/video?type=2&pid=600016637
https://m.yangshipin.cn/video?type=2&pid=600016637
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https://www.theatlantic.com/science...t-and-far-will-new-coronavirus-spread/605632/
The Deceptively Simple Number Sparking Coronavirus Fears
ED YONG JANUARY 28, 2020
When a new disease emerges, health organizations turn to a seemingly simple number to gauge whether the outbreak will spread. It’s called the basic reproduction number—R0, pronounced R-nought—and though useful for decision-makers, it’s a nightmare for public communication. In brief, R0 is the average number of people who will catch the disease from a single infected person, in a population that’s never seen that disease before. If R0 is 3, then on average, every case will create 3 new cases. But even though it seems incredibly straightforward, it’s hard to calculate and tricky to interpret.
R0 is important because if it’s greater than 1, the infection will probably keep spreading, and if it’s less than 1, the outbreak will likely peter out. So it offers vital information to organizations and nations as they consider how to respond to an outbreak—such as the one the world is currently experiencing.
Since December, a previously unknown coronavirus, now called 2019-nCoV, emerged in the Chinese city of Wuhan. There have been more than 4,500 confirmed cases, the vast majority of which have been in mainland China. But several dozen cases have been detected in more than 15 other countries, and as the outbreak has spread, so has fear. Public health researchers have sped to estimate the R0 of the new disease, and as they have shared their findings, this number has fueled several alarmed missives on social media.
Over the last week, at least six teams of researchers, along with the World Health Organization have published estimates of R0 for the new coronavirus. All of these groups used different methods but their results have been mostly consistent, with estimates hovering between 2 and 3. The WHO was a little more conservative than the others, with estimates of 1.4 to 2.5. One Chinese team is a clear outlier, with estimates of 3.3 to 5.5. And a British-led group initially published a high average value of 3.8 last week before revising it downwards to 2.5 as new data emerged.
In the intervening time, however, some observers seized upon the 3.8 figure, with one Harvard doctor describing it as “thermonuclear pandemic level bad” in a tweet that has since between retweeted over 16,000 times. That’s a dubious interpretation, and here are six reasons why.
First, the R0 estimates for the new coronavirus are in line with those for many other diseases. They’re similar to those for SARS (2 to 5) and HIV (also 2 to 5), and considerably lower than for measles (12 to 16).
Second, a bigger R0 doesn’t necessarily mean a worse disease. Seasonal flu has an R0 that hovers around 1.3, and yet infects millions of people every year. SARS had an R0 of 2 to 5 and infected just over 8,000 people. The number is a measure of potential transmissibility. It does not actually tell you how fast a disease will spread.
“People make the mistake of thinking that a high R0 means that you’re inevitably going to end up with a pandemic, and that’s not what it means at all,” says Maia Majumder from Harvard Medical School, who published one of the seven estimates for the new virus. In her view, if the number is higher than 1, we should take the disease seriously. But exactly how high it is beyond that threshold isn’t very informative at this stage.
Why? Because, third, R0 is an average. Let’s say the virus has an R0 of 2. This could mean that every single infected person passes the virus to two other people. It could also mean that one infected person is a “superspreader” who infects 100 people, while 49 infected people infect no one. These two scenarios have radically different implications for what will happen during an outbreak.
Superspreader events are dangerous for health care workers, but counter-intuitively, they can sometimes be a good sign. They suggest that most infected people won’t actually perpetuate the outbreak, while the most problematic cases “may be more likely to be recognized due to their dramatic nature,” writes David Fisman of the University of Toronto. This attention can mean control measures are put into place more readily, he explains in a posting to the PROMED email list. Other coronaviral diseases like SARS and MERS involved superspreader events, although it’s still too early to say if 2019-nCoV will do the same.
Fourth, R0 is not easy to calculate. That’s especially true in the early days of an epidemic, when it’s not even clear how many cases there have been. Some people might have been infected without showing symptoms. Others might not have reported their symptoms to health authorities. Absent clear data on who has the disease, let alone how they’re moving around and interacting with other people, scientists have to calculate R0 by doing complicated simulations using a variety of possible methods. That’s why early estimates can vary so wildly, and why they should be taken with a grain of salt.
Fifth, R0 is not some magical, immutable property of the virus itself. It depends on how likely someone is to be infected after contact with an infectious person, and how often such contacts occur—and these quantities are also affected by how societies deal with a virus. When SARS first emerged, transmission dynamics played out very differently in China and Canada, which is why the virus’s R0 values cover a wide range from 2 to 5. “In places with good infection control, where you can isolate cases as soon as they happen, you’ll see a lower R0 than say in places where an outbreak initially took off,” says Majumder.
The current R0 estimates for the new coronavirus are specific to Wuhan, and mostly to the era before people knew about the virus. New estimates will emerge as the virus spreads to places that are now aware of and watching for it. “Likely, these will all be significantly lower,” says Kristian Andersen, a virologist at Scripps Research Translational Institute.
Sixth, R0 is not destiny. It is a measure of a disease’s potential. And once nations realize that a new disease exists, they can actively screen for it, check that health care workers are using proper protection, or instigate quarantines. Even simple steps like hand-washing might make a difference. All of these measures could potentially lower the chances that the virus will spread and ensure that its actual transmission rate—the quantity known simply as R—is less than R0, and ideally less than 1. There are a few reassuring signs: One study suggests that patients are now being isolated just one day after showing symptoms, as opposed to after six days at the start of the outbreak.
None of this should be cause for complacency. The new virus is a serious threat, and the world should absolutely start considering what to do if containment measures fail. But at a time of great uncertainty, people grasp for solid answers, and numbers seem to offer them.
This new virus has emerged at a time when scientists have more avenues than ever for publishing their data and comparing notes. That can be a good thing, since fast and open communication can help to bring diseases to heel more quickly. The risk is that a complicated number is released without context into a world that doesn’t know how to think about it. “Getting these R0 values out very rapidly is super important,” says Andersen. “But the way that some people and news outlets have interpreted what they mean… that part is problematic.”
The Deceptively Simple Number Sparking Coronavirus Fears
ED YONG JANUARY 28, 2020
When a new disease emerges, health organizations turn to a seemingly simple number to gauge whether the outbreak will spread. It’s called the basic reproduction number—R0, pronounced R-nought—and though useful for decision-makers, it’s a nightmare for public communication. In brief, R0 is the average number of people who will catch the disease from a single infected person, in a population that’s never seen that disease before. If R0 is 3, then on average, every case will create 3 new cases. But even though it seems incredibly straightforward, it’s hard to calculate and tricky to interpret.
R0 is important because if it’s greater than 1, the infection will probably keep spreading, and if it’s less than 1, the outbreak will likely peter out. So it offers vital information to organizations and nations as they consider how to respond to an outbreak—such as the one the world is currently experiencing.
Since December, a previously unknown coronavirus, now called 2019-nCoV, emerged in the Chinese city of Wuhan. There have been more than 4,500 confirmed cases, the vast majority of which have been in mainland China. But several dozen cases have been detected in more than 15 other countries, and as the outbreak has spread, so has fear. Public health researchers have sped to estimate the R0 of the new disease, and as they have shared their findings, this number has fueled several alarmed missives on social media.
Over the last week, at least six teams of researchers, along with the World Health Organization have published estimates of R0 for the new coronavirus. All of these groups used different methods but their results have been mostly consistent, with estimates hovering between 2 and 3. The WHO was a little more conservative than the others, with estimates of 1.4 to 2.5. One Chinese team is a clear outlier, with estimates of 3.3 to 5.5. And a British-led group initially published a high average value of 3.8 last week before revising it downwards to 2.5 as new data emerged.
In the intervening time, however, some observers seized upon the 3.8 figure, with one Harvard doctor describing it as “thermonuclear pandemic level bad” in a tweet that has since between retweeted over 16,000 times. That’s a dubious interpretation, and here are six reasons why.
First, the R0 estimates for the new coronavirus are in line with those for many other diseases. They’re similar to those for SARS (2 to 5) and HIV (also 2 to 5), and considerably lower than for measles (12 to 16).
Second, a bigger R0 doesn’t necessarily mean a worse disease. Seasonal flu has an R0 that hovers around 1.3, and yet infects millions of people every year. SARS had an R0 of 2 to 5 and infected just over 8,000 people. The number is a measure of potential transmissibility. It does not actually tell you how fast a disease will spread.
“People make the mistake of thinking that a high R0 means that you’re inevitably going to end up with a pandemic, and that’s not what it means at all,” says Maia Majumder from Harvard Medical School, who published one of the seven estimates for the new virus. In her view, if the number is higher than 1, we should take the disease seriously. But exactly how high it is beyond that threshold isn’t very informative at this stage.
Why? Because, third, R0 is an average. Let’s say the virus has an R0 of 2. This could mean that every single infected person passes the virus to two other people. It could also mean that one infected person is a “superspreader” who infects 100 people, while 49 infected people infect no one. These two scenarios have radically different implications for what will happen during an outbreak.
Superspreader events are dangerous for health care workers, but counter-intuitively, they can sometimes be a good sign. They suggest that most infected people won’t actually perpetuate the outbreak, while the most problematic cases “may be more likely to be recognized due to their dramatic nature,” writes David Fisman of the University of Toronto. This attention can mean control measures are put into place more readily, he explains in a posting to the PROMED email list. Other coronaviral diseases like SARS and MERS involved superspreader events, although it’s still too early to say if 2019-nCoV will do the same.
Fourth, R0 is not easy to calculate. That’s especially true in the early days of an epidemic, when it’s not even clear how many cases there have been. Some people might have been infected without showing symptoms. Others might not have reported their symptoms to health authorities. Absent clear data on who has the disease, let alone how they’re moving around and interacting with other people, scientists have to calculate R0 by doing complicated simulations using a variety of possible methods. That’s why early estimates can vary so wildly, and why they should be taken with a grain of salt.
Fifth, R0 is not some magical, immutable property of the virus itself. It depends on how likely someone is to be infected after contact with an infectious person, and how often such contacts occur—and these quantities are also affected by how societies deal with a virus. When SARS first emerged, transmission dynamics played out very differently in China and Canada, which is why the virus’s R0 values cover a wide range from 2 to 5. “In places with good infection control, where you can isolate cases as soon as they happen, you’ll see a lower R0 than say in places where an outbreak initially took off,” says Majumder.
The current R0 estimates for the new coronavirus are specific to Wuhan, and mostly to the era before people knew about the virus. New estimates will emerge as the virus spreads to places that are now aware of and watching for it. “Likely, these will all be significantly lower,” says Kristian Andersen, a virologist at Scripps Research Translational Institute.
Sixth, R0 is not destiny. It is a measure of a disease’s potential. And once nations realize that a new disease exists, they can actively screen for it, check that health care workers are using proper protection, or instigate quarantines. Even simple steps like hand-washing might make a difference. All of these measures could potentially lower the chances that the virus will spread and ensure that its actual transmission rate—the quantity known simply as R—is less than R0, and ideally less than 1. There are a few reassuring signs: One study suggests that patients are now being isolated just one day after showing symptoms, as opposed to after six days at the start of the outbreak.
None of this should be cause for complacency. The new virus is a serious threat, and the world should absolutely start considering what to do if containment measures fail. But at a time of great uncertainty, people grasp for solid answers, and numbers seem to offer them.
This new virus has emerged at a time when scientists have more avenues than ever for publishing their data and comparing notes. That can be a good thing, since fast and open communication can help to bring diseases to heel more quickly. The risk is that a complicated number is released without context into a world that doesn’t know how to think about it. “Getting these R0 values out very rapidly is super important,” says Andersen. “But the way that some people and news outlets have interpreted what they mean… that part is problematic.”
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China develops rapid Coronavirus test that works in under 15 MINUTES
The test takes between eight and 15 minutes to produce a result and is currently being mass-manufactured at a rate of 4,000 kits per day, with the city government in Wuxi exploring efforts to boost production even further.
The first batch of kits has reportedly already been deployed to the frontlines at the epicentre of the outbreak, Wuhan, in Hubei province.
https://www.rt.com/news/479705-china-develop-coronavirus-rapid-test/
The test takes between eight and 15 minutes to produce a result and is currently being mass-manufactured at a rate of 4,000 kits per day, with the city government in Wuxi exploring efforts to boost production even further.
The first batch of kits has reportedly already been deployed to the frontlines at the epicentre of the outbreak, Wuhan, in Hubei province.
https://www.rt.com/news/479705-china-develop-coronavirus-rapid-test/
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Didn't mention the accuracy. Please don't bring into Singapore
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Novel coronavirus may spread via digestive system: experts
http://www.xinhuanet.com/english/2020-02/02/c_138749620.htm
http://www.xinhuanet.com/english/2020-02/02/c_138749620.htm
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https://www.sciencemag.org/news/2020/01/mining-coronavirus-genomes-clues-outbreak-s-origins
Guys, see above is a new article published on the website of Science, arguably THE most authoritative scientific journal in the world. Two main points that may be relevant to our current discussion on the potential conspiracy theories:
1. The Chinese scientists openly shared the whole genome of the 2019-nCov.
2. Experts around the world carefully mined the sequence and knocked down the idea that the pathogen came from a lab.
The second half of the article specifically discussed the possibility of an accidental release from a lab. Peter Daszak, an ecologist working closely with Chinese scientists said that they found >500 novel coronaviruses on over 1,2000 Chinese bats and other species that they've collected in the wild. And 50 of these coronaviruses are very similar to SARS and the current 2019-nCoV. There is no evidence that the current 2019-nCoV is man-made.
Guys, see above is a new article published on the website of Science, arguably THE most authoritative scientific journal in the world. Two main points that may be relevant to our current discussion on the potential conspiracy theories:
1. The Chinese scientists openly shared the whole genome of the 2019-nCov.
2. Experts around the world carefully mined the sequence and knocked down the idea that the pathogen came from a lab.
The second half of the article specifically discussed the possibility of an accidental release from a lab. Peter Daszak, an ecologist working closely with Chinese scientists said that they found >500 novel coronaviruses on over 1,2000 Chinese bats and other species that they've collected in the wild. And 50 of these coronaviruses are very similar to SARS and the current 2019-nCoV. There is no evidence that the current 2019-nCoV is man-made.
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COMPARE CHINA RESPONSE TO WUHAN VIRUS AND USA RESPONSE TO THE SWINE FLU IN 2009
AND WUHAN DISINFECTING ON INDUSTRIAL SCALE
https://www.facebook.com/groups/331959467607740/permalink/639361386867545/
AND WUHAN DISINFECTING ON INDUSTRIAL SCALE
https://www.facebook.com/groups/331959467607740/permalink/639361386867545/
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WHO warns overseas virus spread may be 'tip of the iceberg'
Read more at https://www.todayonline.com/world/who-warns-overseas-virus-spread-may-be-tip-iceberg
Read more at https://www.todayonline.com/world/who-warns-overseas-virus-spread-may-be-tip-iceberg
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New coronavirus found in Japan evacuees who initially tested negative
New coronavirus found in Japan evacuees who initially tested negative : China_Flu
New coronavirus found in Japan evacuees who initially tested negative : China_Flu
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