Mathematic models made by epidemiologist experts from Harvard and prediction from John Hopkins guys are giving huge numbers
between 40 and 70% world adult population will be infected in one year and numbers of deaths will be between 30 and 150 million if their predictions are correct and china didn't lie with the 2% death rate
Read the threads from their twitters, the situation is much much worse than the media is telling constantly with the influenza comparison, and this guys are not nuts, they are top minds of epidemic control.
A brief from their conversations and information would be:
- It is absolutely impossible to stop covid and will be a pandemic
- The death rate could hit 10% in some countries
- Expect between 30 and 70% of the world to be infected
- millions of deaths
- Governments duty now is not to stop the disease as they can't, but try to slow it until we understand it better, have real numbers (chinese ones cannot to be trusted), and we develop a vaccine so the R0 can be <1
- Governments are likely going to adopt the hardest restrictions they can get away, expect quarantines on every country
- Health services on third world countries will collapse, first world will have problems as we are not prepared
- CDC is already saying the virus will be with us more than one season
A lot of the links you provide have alarmist titles and big claims and confusing evidence. Which is strange since the twitter authors are clearly well educated virologists/epidemiologists. But the style of language makes it difficult for me to trust what they are saying. So far I am sticking to research papers and This Week In Virology [0], where there is a lot less dramatic clickbait language and a lot more skeptical analysis of statistics. My conclusion so far is that no one knows how this will play out, but the fear seems to be more dangerous than the actual disease in many places.
Alarming titles indicate quacks more than they indicate actual crisis and we don't have time to check the credentials and the work of the people involved to assess their credibility. Also facts speak for themselves, you don't need alarmism unless you have something to sell.
Also in these instances a general panic can do much more harm than the virus can ever do — we already see fears of an economic recession.
do you use twitter much? these look like standard Twitter threads to me with standard Twitter writing style. threads from blue checkmark guys do tend towards sensational though.
Just as the majority of people who catch the flu don't get tested for it, only the serious cases do.
So we know covid19 spreads much easier than the flu and is orders of magnitude deadlier than the flu for those that get tested/confirmed compared to those that get tested/confirmed with the flu.
Note that they are looking at people who were diagnosed up through Feb 11th. It normally takes people 3 - 4 weeks to die from the disease, and it hasn't even been 3 weeks from Feb 11th, so it seems like this figure is designed as a lower bound.
Current antivirals work on it. Shown effective in animal models and now in human testing in China. A US based test, the patient made a recovery and showed significant improvement one day after dose. This is just antivirals that are already out there that being manufactured. There will be vaccines on the market in 6 to 9 months and antibody treatments shortly after.
Do you have research links? Or this is just internet enecdata? I have been contemplating calling in my Truvada script early and mailing a 30-60 pills to my parents but from my googling seems pointless. that Emtricitabine / Tenofovir most certainly wouldn't help? but I couldn't find much and have no idea
That's absolutely nonsensical paranoia. It's the equivalent of making $1000 month one of your startup, $2000 month two, and immediately claiming that by month 24 you will be making over $16 billion.
Make no mistake, COVID-19 is likely to become an annual community disease. But it's not going to kill 30 million people until like 2120.
There's nothing nonsensical about it. That's a very poor analogy as well, comparing a startup's growth to the spread of a highly-infectious virus.
COVID19 spreads by default. If you leave it alone, it will spread uncontrollably. China went from 0 to 79,000 confirmed cases in 2 months, despite running the largest and most extensive quarantine in human history. If there was no quarantine, you could expect truly exponentially higher number of infections.
The problem with these things is, if the rate of spread is >1, then it becomes exponential. That is, if the average person infects more than one person, then the rate of spread is going to get completely out of control. Unless of course, you can impose measures that reduce the rate of spread to below 1.
With coronavirus, it's not possible to do this. The reason is that many people are asymptomatic for weeks, while at the same time passing the virus to other people. If you cannot identify infections before they have the chance to spread at a rate of >1, then the spread of the disease will by default be exponential.
A startup does not grow exponentially by default. Many actions need to be done correctly to continue growing. A business's default state is death.
COVID19 spreads by default. If you leave it alone, it will spread uncontrollably. China went from 0 to 79,000 confirmed cases in 2 months, despite running the largest and most extensive quarantine in human history.
Sure, but note that they started the strict quarantine protocol after there are already > ten
thousand ick people (and many more already exposed).
With coronavirus, it's not possible to do this. The reason is that many people are asymptomatic for weeks, while at the same time passing the virus to other people. If you cannot identify infections before they have the chance to spread at a rate of >1, then the spread of the disease will by default be exponentia
This is mostly speculation, maybe just applying basic things like hand washing, distance measures pushes it to <1 and it dies down eventually? Besides, we have no data about the rate of infection from people who does not show any symptoms (especially coughing).
There's been a lot of shifts in thinking recently, including by myself, as some things that were explicable via either the typically bad data from an emerging outbreak or "just so" stories about stochasticity, like the cruise ship cases, or the bulk of the cases in South Korea being due to a single massive spreading event in a fairly insular community, turned out to be...well...more common than would be desirable.
The field, as a whole, has started talking much more about mitigation, and less about containment, because attempts to intensively trace and isolate cases are only partially holding the line.
That being said, important caveats to all of this is:
- As Marc Lipsitch notes, those estimates don't tell us how many of those cases will be asymptomatic or mild, because we don't have good numbers for that yet. The difference between "Under the weather for a few days" and "Needs respiratory support in an ICU" is obviously massive.
- Epidemic models inherently assume exponential growth (because that's how epidemics work). But that does mean that small perturbations in how we understand how the disease "works" can dramatically chance projections.
I'm not an epidemiologist, and while I do not like to use argument from authority, I trust this guys because is their work, they do it in top institutions and they won't jeopardize their reputation for some fear-mongering tweets.
Besides my usual request not to follow Eric Feigl-Ding as an authoritative source?
Not really? This is the currently understood state of the science. I would say though that right now several things have broken the "wrong" way in terms of optimistic projections, so it's still possible for the situation to improve.
I know a guy who went to work as a post-doc at Harvard. He left behind experimental samples of human blood that were unlabelled, which I had to inform his former supervisor about. He also had a number of other professional failings. The takeaway is that just because someone has "Harvard" on their resume doesn't mean they are even remotely competent.
And I completely agree, that's why I said I don't like to use arguments of authority, but two of them are not educated in harvard, they are heads of departments and directors from harvard and john hopkins
People educated in those fields with enough renown to claim those positions with a lot to lose for just writing that.
And yes, while they can end being just wrong or spreading fearmongering information, they are the most trusted sources I found
Mathematic models made by epidemiologist experts from Harvard and prediction from John Hopkins guys are giving huge numbers
between 40 and 70% world adult population will be infected in one year and numbers of deaths will be between 30 and 150 million if their predictions are correct and china didn't lie with the 2% death rate
Read the threads from their twitters, the situation is much much worse than the media is telling constantly with the influenza comparison, and this guys are not nuts, they are top minds of epidemic control.
A brief from their conversations and information would be:
- It is absolutely impossible to stop covid and will be a pandemic
- The death rate could hit 10% in some countries
- Expect between 30 and 70% of the world to be infected
- millions of deaths
- Governments duty now is not to stop the disease as they can't, but try to slow it until we understand it better, have real numbers (chinese ones cannot to be trusted), and we develop a vaccine so the R0 can be <1
- Governments are likely going to adopt the hardest restrictions they can get away, expect quarantines on every country
- Health services on third world countries will collapse, first world will have problems as we are not prepared
- CDC is already saying the virus will be with us more than one season
- hope we can avoid more deadly mutations
https://threadreaderapp.com/thread/1228373884027592704.html?...
https://threadreaderapp.com/thread/1231425805898657795.html
https://ccdd.hsph.harvard.edu/research/ncov-making-sense-of-...
https://twitter.com/T_Inglesby
https://twitter.com/DrEricDing
https://twitter.com/mlipsitch