Covid-19 News

  • Robert B.... you might be the person to ask.

    With all the deaths in nursing homes and talk about clotting..

    is there data on death rates comparing people on blood thinners compared to those not on thinners?

    I would expect that that data would be obtainable for those who know how to look for it.

  • They are around, and sometimes you may not like what they say. Lou posted this today, and I thought it was a very good read. Skip to "Two schools of thought":…fluences-covid-19/5718129…fluences-covid-19/5718129

    There are fundamentally two hypotheses about the epidemiological events of this spring: Either the number of people exposed has been high and the fatality rate low, or else the number of people exposed has been low and the fatality rate higher. People in the first camp argue that the exposed population is over 50% in Europe and America, approaching or exceeding herd immunity, and the population death rate is in the range 0.0005. In the second camp, people estimate the population exposure about ten times lower (5%) and the fatality rate correspondingly higher (0.005).

    The story told by people in the first camp is that social distancing slowed but did not prevent transmission of the disease through the population. By now, the presence of the virus is waning because people in many places have already been exposed.

    The story of Ferguson and others in the second camp is that social distancing actually stopped spread of the virus, so that most people in Europe and American have never been exposed. It follows that if we ease restrictions, there is another wave of infections ahead, potentially 20 times larger than the first wave.

    The deep flaw of the recent Ferguson paper is that his team does not consider the first scenario at all. Built into their model, they assume that population level immunity is negligible, and the only thing that has slowed spread of the virus has been social distancing. This is where they put the rabbit in the hat.

    If they had considered the alternative hypothesis, how would it have compared?

    To choose between the two hypotheses, we might compare a region before and after lockdown, or we might compare regions that locked down with regions that didn’t.

    In a preprint response to Ferguson, Homburg and Kuhbandner do a good job with the first approach. They take Ferguson to task for not considering the immunity that spreads through the population along with the disease. They show that exponential expansion had already slowed in England before the effect of the lockdown on mortality data could have been felt.

    Hi Shane,

    That is not a statistics web site, and the arguments there are technical, but not statistics, and have nothing to do with HCQ. Or any other treatment, or how to evaluate observational evidence using multivariate regression studies!

    Nor do I dislike it. I've always been alert to arguments about the shape of the epidemic curve. The epidemiologists use these simple exponentials that are obviously wrong. Their estimates of herd immunity do not take into account the way that those who have more contacts are more likely to catch the disease, nor the way that varied geography and demographics interacts. They are conditioned by what works with Flu, but COVID is not Flu. It appears less easily transmissable, but more likely to do so because asymptomatic transmission is likely. These factors make it likely that Ferguson et al are wrong. But they don't let us conclude yet what is right.

    However I'm also alert to the intricacies of COVID disease and immunity. Who is immune? How much? And are those asymptomatics immune. The news there seems mostly good but is still unclear.

    Finally, Shane, you are guilty of seeing me as posting from weird politics that hopes people will die. On what evidence do you say I would rather the disease were more serious, or that somehow some attachment to a particular theory would, for me, be more powerful than wanting this scourge to be dealt with as cheaply and quickly as possible? And if you pay attention to my recent post, pointing out the non-exponential growth in Florida that Jed posted, you will see that I do not make assumptions about how much the virus will spread if left unchecked. Not either way. Unlike those who seem stuck on one solution.

    I'm calling you out on this. As moderator you should not be making derogatory personal attacks. I know you did not mean to do this, but you will see you sort of were.

  • That seems very high. At any rate, in the UK if you test negative you do not have to self isolate unless there are some unlikely scenarios.…t-your-test-result-means/

    Mark, I do think you should quote the bit of your link relevant when claiming I'm wrong.

    You are right you don't automatically have to self-isolate in the UK. But it is on the cards and likely to happen. If any one of the below is untrue, you must do it.

    I was referring to the Test and Trace condition. In theory (though alas not yet in practice) a lot of the positives will be traced. In that case, even if you test negative, you have to continue self-isolating because the tests are not accurate. If you test positive, Test and Trace will track your contacts.

  • RB - you are perfectly correct in calling out that comparison as anecdotal. And clever enough to know:

    (a) It will convince many here


    (b) it is statistically fraudulent.

    The point is that neither Boris, nor Bolsanaro, was that likely to develop severe COVID (look up the statistics). Boris had clear risk factors, he has had a weight problem for a long time. Bolsanaro maybe less so. But neither of those factors is needed to see that both doing well is expected anyway, so boris being unlucky does not provide evidence that Bolsanaro was particularly lucky (and therefore this would be some small evidence for HCQ as prophylactic).

    Again, HCQ may work. Just as TCM may work. Both have some plausible mechanism. Neither has good evidence. What annoys me is the intellectual dishonesty of those who strongly argue it does work from posting non-evidence. That is why doctors who seriously evaluate these things are so cautious about new treatments. You get this weight of positive observational evidence and it has no weight.

    EDIT for increased accuracy:

    (1) will convince many here is opinion unsupported by evidence

    (2) this matter is probabilistically (not statistically) fraudulent, using a narrower and possibly more correct definition of the two disciplines.


  • Re statistics and observational studies I've not yet found good statistical analysis on those studies.

    I do have a strong recommendation for unbiassed reporting (does not mean it is right, just that it will be wrong in an unbiassed way!). And the reporting is technical-led, which I like.

    These sources have minimal bias and use very few loaded words (wording that attempts to influence an audience by using appeal to emotion or stereotypes). The reporting is factual and usually sourced. These are the most credible media sources.

    Note: STAT delivers fast, deep, and tough-minded journalism. We take you inside science labs and hospitals, biotech boardrooms, and political backrooms. We dissect crucial discoveries. We examine controversies and puncture hype. We hold individuals and institutions accountable. We introduce you to the power brokers and personalities who are driving a revolution in human health.” STAT is produced by Boston Globe Media. In my review of this site, I feel that STAT delivers on its mission. Articles are well researched and direct, without use of loaded words. There is a very slight leftward bias in story selection, but not enough to move to the Left-Center category. (D. Van Zandt 5/6/2017)

    Here is their (recent) take on the search for drugs:…-study-of-covid-19-drugs/

    The analysis, conducted in partnership with Applied XL, a Newlab Venture Studio company, found that one in every six trials was designed to study the malaria drugs hydroxychloroquine or chloroquine, which have been shown to have no benefit in hospitalized patients.

    “If the goal was to optimize the likelihood of figuring out the best treatment options, the system is off course,” said Robert Califf, the head of clinical policy and strategy at Verily Life Sciences and Google Health and a former commissioner of the Food and Drug Administration. The findings show, he said, that too often studies are too small to answer questions, lack real control groups, and put too much emphasis on a few potential treatments, as occurred with hydroxychloroquine.

    Indeed, the analysis found many of the studies are so small — 39% are enrolling or plan to enroll fewer than 100 patients — that they are unlikely to yield clear results. About 38% of the studies have not actually begun enrolling patients.

    “It’s a huge amount of wasted effort and wasted energy when actually a bit of coordination and collaboration could go a long way and answer a few questions,” said Martin Landray, a professor of medicine at Oxford University and one of the lead researchers on the RECOVERY study, a large trial of multiple treatments being run by the U.K. government.

    Not all effort has been for naught. Three of the most important conclusions about Covid-19 treatments so far have come from the RECOVERY trial. It has shown that dexamethasone, an inexpensive steroid, reduced the death rate of Covid-19 patients on ventilators by a third. It has also demonstrated that neither hydroxychloroquine nor a pair of HIV drugs, lopinavir and ritonavir — which had shown some early promise in laboratory models of the disease — benefit hospitalized patients with Covid-19.

    Still, experts say the analysis shows that huge amounts of energy have been expended on haphazard efforts, often without a clear strategy to improve the odds that results would actually inform the care of patients. Faced with intense pressure to develop drugs and vaccines at previously unimaginable speed to push back a global pandemic, researchers may have actually slowed down the rate of progress.

    For instance, 237,000 patient volunteers were to be enrolled in studies of hydroxychloroquine or chloroquine. That’s 35% of the 685,000 patient volunteers whom researchers hoped would be enrolled in any study. Since patients willing to enter studies are one of the scarcest resources in medicine, this means that other potential treatments, such as ivermectin or favipiravir, were not studied.

    Experts added that, because the prognosis for patients with Covid-19 varies so dramatically — some patients have no symptoms, while others die on ventilators — only large studies that randomly assign patients to a treatment or placebo can deliver real insight into whether or not medicines are actually helping patients. Otherwise, researchers are fooled into thinking that differences between groups of patients with varying degrees of illness are caused by the medicines they are testing.

    The RECOVERY study took a unique approach. In order to run such a large study, the researchers stripped down the amount of data collected on each patient — focusing mainly on whether patients lived or died — so that frontline researchers would be able to collect the data. More important, they got buy-in from the U.K.’s National Health Service that such a study was a priority.

    Repeating that model, experts agree, would teach doctors more about how to treat Covid-19, and do so much faster.

    “If more people took the RECOVERY model, or something like it, did that for the drugs they were interested in, in the patients they’re interested in, in their part of the world … we make progress an awful lot quicker,” said Landray.

  • Anti-malarials and Vit D

    These are two types of chemical that, for different reasons, tend to correlate with good outcomes. Vit D - the sunshine vitamin - correlates with those who spend more time in the sun and/or have better diets. Anti-malarials correlate with young populations in malarial countries (specifically a factor for COVID where outcome has such very strong age dependence) .

    I'm taking vit D supplements - should have done it ages ago, was at strong risk of deficiency like many people in high latitudes. And there is unsurprising evidence that high vit D deficiency worsens COVID outcome. No evidence that it is a miracle cure.

    The same is true for Zinc, but my diet is pretty good for zinc, I'm highly unlikely to be deficient.

    Now, how about we get back to a more interesting topic: the shape of that epidemic curve and what evidence we do or don't have for herd immunity at low seropositivity levels. For example. UK seropositivity is around 6% I think. Shane's link…fluences-covid-19/5718129


    That herd immunity had started to reduce Rt very significantly before lockdown, on basis of back-time-adjusted mortality data.

    I applaud such arguments, because they are trying to answer questions we need answers. I'm not sure this particular paper does a good job: though before looking at it I would not know. Initial impressions, it seems to be from outside the people who look seriously at all the most current medical evidence (Ferguson's team did this - they may have made mistakes, but they were informed mistakes. Their much-quoted early papers were in any case before we had much COVID-specifc evidence).

    Worth noting that GlobalResearch (Shane's link) score tin-has conspiracy theory on a media bias check


    Founded in 2001, GlobalResearch or Centre for Research on Globalization is a Canadian conspiracy website. It was founded by Michel Chossudovsky who is currently the President of GlobalResearch and professor emeritus of economics at the University of Ottawa. The website does not have an about page, but they do list the people involved with the operation.

    Read our profile on Canadian government influence on media.

    Funded by / Ownership

    Although GlobalResearch does not state ownership, it is assumed Michel Chossudovky is the owner. Revenue is derived through donations and advertising.

    Analysis / Bias

    In review, GlobalResearch publishes a combination of real news and conspiracy theories. We will focus on the not so real news. GlobalResearch often reports unfavorably about Israel such as this: The Zionist Idea Has Never Been More Terrifying than It Is Today. This unlabeled opinion piece does not provide a single source of evidence for their claims. When it comes to politics they are strongly anti-capitalism and anti-Globalist as their name suggests. While GlobalResearch does promote legitimate humanitarian concerns, its views on science, economics and geopolitics is very questionable. For example, GR promotes anti-vaccination propaganda, 9-11 as a false flag operation, GMO’s are harmful, and Chemtrails. There are so many more, this is just the tip of the iceberg.

    In general, this is a website the purports to be concerned for humanity, yet routinely publishes false information that misleads humanity.

    Failed Fact Checks

    Overall, we rate GlobalResearch a Tin Foil Hat Conspiracy and Strong Pseudoscience website based on the promotion of unproven information such as the dangers of Vaccines and 9-11 as a false flag operation. (D. Van Zandt 7/20/2016) Updated (4/22/2020)


  • [Zelenko] has an outpatient catchment area with a uniquely young age profile, and therefore whose patients will be uniquely less likely to suffer severely from COVID. This unusual demographics make observational studies from him very unhelpful in determining the merit of any treatment unless they are randomised and controlled. The reports don't go into this in the detail that needs to be done to extract any possible real information from his work. Propensity scoring etc with age bands really does not work well unless there are enough bands, and a linear fit is done to correlation with age in each band. The right multivariate analyses will do that but by that point you have so many variables that you need an awful lot of data to determine them to a statistically significant extent. Z's population is relatively very healthy, since young, so difficult for his trials to be informative.

    It wouldn't surprise me to find out Zelenko's patients have one of the highest birth rates on the planet. I know three Satmars (the same sect that live in Kiryas Joel) who have 30 siblings between them - not including themselves. They say they are not out of the ordinary for their community.

  • How about a theoretical argument (Shane you will know I like these) to support the (possibly correct) preprint referenced oin the tin hat conspiracy site. No-one can help being liked by weird people - it does not mean one is wrong.

    That Flu needs 60% - 80% herd immunity to get rid of an outbreak is well understood.

    How might COVID be different?

    Early attendion focussed on much higher Rt (true). But that does not invalidate the same type of modelling.

    (1) How about if the COVID typical transmission method were different. Maybe in populations it spreads more via direct airbourne droplets - as opposed to Flu that spreads very easily via surface contact? Both diseases we know spread both ways, but there could be a signiifcant difference in the relative likelihood

    (2) How about if COVID spreads mainly via asymptomatic carriers (we know Flu does not)

    Now, there is some evidence for (2) though it is not yet well established. I don't know at all the evidence on (1).

    These two questions are relevant because they might influence the way that epidemics can be driven by infection by a relatively small number of key worker (with very large numbers of contacts). Immunity of this pool would then reduce spread significantly. Even with low seropositivity, because these high contact workers will be much more likely to catch COVID, we can then get useful herd immunity.

    I posted ages ago a nice epidemiology modelling paper about this effect, showing how herd immunity levels altered according to the variability of number of contacts in population.

    This is an entirely different argument from the ones here about how most of the population could be naturally immune (say from other CVs) and therefore never seropositive. We have some data from that cruise ship which shows this is not true. A lot of those people ended up seropositive, though many were asymptomatic. Maybe there is more reliable evidence from elsewhere - I'd like to see it.

    Either of these two arguments could mean the epidemic flattens out at a death rate much lower than expected.

    Worth pointing out though that in NY it did not (without lockdown) flatten before the health system was totally overwhelmed. Similarly Spain and Italy, India (I think), various South American countries. The UK was OK, but only just.

  • RB - you are .. clever enough to know:It will convince many here... it is statistically fraudulent.

    "will " = a THH assumption

    'clever' has nothing to do with it

    I am not assumptive enough to say "will" .. perhaps "may" is a better word

    " is statistically Fraudulent" = THH non sequitiur =

    n=1 is not statistics ... the mean and standard deviation are undefined if n=1

    where does fraudulent even come in??? except in the THH attempt to inject fraud

    now if one gets an accumulation of anecdotes... then it is possible to get statistics... with n>!.. and that is happening progressively

    in the end THH's statistical wordplay is nonstatistical rhetoric

  • Shane's (quoted by tin-hat conspiracy site, published in unusual place) reference has the following bibliography:

    1. Flaxmann et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in
    Europe. Nature in press, 2020.
    2. Lauer, S. A. et al. The Incubation Period of Coronavirus Disease 2019 (COVID-19) from
    Publicly Reported Confirmed Cases: Estimation and Application. Ann Intern Med in press,
    3. Verity, R. et al. Estimates of the severity of COVID-19 disease. Lancet Infect Dis in press,


    They reference in support almost none of the available work: (1) they disagree with. (2) and (3) clearly do not answer the various uncertainties here. They make a possible and tendentious argument, which does not consider the many other reasons for the data they quote. Does not mean its wrong. Does mean the paper provides no large support for it being right.

    Finally they do not publish on standard preprint sites that allow comment. At least I have not found such yet.

  • now I need a box of rat poison

    to warfarinise yourself is no simple procedure... you need to get a physcian to prescribe for you..and also have several days worth of blood clotting times (INR) diagnosed..

    otherwise you may end up like a poisoned rat..becaus eof an overdose of warfarin

    anticoagulation monitoring via INR can be DIY.. but it still costs.. the Roche Coaguchek is expensive and the little test strips are also exoensive.. my Dad has been doing that for

    20 years without any massive bleeding episodes..but he has to keep his diet fairly bingeing on alcohol or green veges..

    Anticoagulation , like dexamethasone... is probably only useful when you get hospitalised with severe virally induced inflammation..

    when you have close medical supervsion anyway( hopefully)

    The wise thing is to employ other defensive means first

    social distancing ( in rural areas it is easier).. hand hygiene... Vitamin D...... vitamin C..

    hesperidin does seem to have some justification to it .. citrus juice in moderation..

    oh for a secluded place in the country..with orange trees..

    • Official Post

    Finally, Shane, you are guilty of seeing me as posting from weird politics that hopes people will die. On what evidence do you say I would rather the disease were more serious, or that somehow some attachment to a particular theory would, for me, be more powerful than wanting this scourge to be dealt with as cheaply and quickly as possible? And if you pay attention to my recent post, pointing out the non-exponential growth in Florida that Jed posted, you will see that I do not make assumptions about how much the virus will spread if left unchecked. Not either way. Unlike those who seem stuck on one solution.

    I'm calling you out on this. As moderator you should not be making derogatory personal attacks. I know you did not mean to do this, but you will see you sort of were.

    Are you sure that was me? I do not even think that, so has to be some cross signal, or something I said that came across wrong. Will look back a little later this morning, and see if I can find what it was I said that could be taken as a personal attack. Whatever, rest assured it was not intentional as even you acknowledge.

    And also; there are so many new internet news sites popping up, I seldom take the time to check if they are considered whacko conspiracy based, or mainstream when I link to them. I just look at the quality of the writing.

  • Shane,

    I don't like to rain on your sunny day. But I suggest we factor in this report from Ferguson's team giving their unchanged views on likelihood of herd immunity:…cases-herd-immunity-says/ (popular report)…-6736(20)31357-X/fulltext (article)

    Have deaths from COVID-19 in Europe plateaued due to herd immunity?

    Transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently in marked decline in many countries in Europe, North America, and parts of Asia, following unprecedented governmental interventions aiming to substantially reduce travel and physical contact between individuals. There are two possible and very different explanations for this decline.

    First, the observed declines in cases and deaths could be due to lockdowns (taken to include public orders to stay at home, bans on public gatherings with less than ten people, and curfew of all age groups), social distancing, and other interventions. This would imply that the epidemic is still at a relatively early stage and that a large proportion of the population therefore remain susceptible. Under such a scenario, there is a high risk of renewed transmission if interventions or behavioural modifications are completely relaxed. This first explanation also is consistent with a high infection fatality ratio (IFR) in order to explain the number of deaths that have occurred to date.

    We took a simple, data-driven approach to establish which of these explanations is better supported by data. Our arguments are based on trends in cumulative deaths over time in a number of countries that went into lockdown at different stages in their epidemics, as reported by the European Centre for Disease Prevention and Control on May 18, 2020. For a subset of countries, we also explore data obtained from serology studies on the proportion of the population that has evidence of prior infection. All data sources for these analyses are listed in the appendix. We find that there is little evidence to support an explantaion that relies on herd immunity for the following reasons.

    First, the cumulative per-capita mortality rate from COVID-19 has plateaued at different levels (appendix). The reporting of deaths in different countries with good testing capacity, although not without challenges, is generally considered one of the more reliable statistics on COVID-19 since testing has been prioritised for severe cases. Under herd immunity, the cumulative mortality rate due to COVID-19 per million of the population would be expected to plateau at roughly the same level in different countries (assuming similar basic reproduction numbers). This is not what the data show. For example, in Germany, the Netherlands, and Italy, all countries with good quality health care and testing capacity, the difference in mortality is several fold, with Germany at 95 deaths per million population, the Netherlands at 332 deaths per million population, and Italy at 525 deaths per million population (as of May 17, 2020). Although no data are perfect, it is highly unlikely that differences in mortality reporting across countries could explain this scale of variation. If acquisition of herd immunity was responsible for the drop in incidence in all countries, then disease exposure, susceptibility, or severity would need to be extremely different between populations. Given similar demographics, close geographic proximity, strong genetic similarities, robust health systems, and probable similar previous exposure to other human coronaviruses, there is little evidence to support this. In contrast, if the levelling off of deaths is caused by interventions and associated behavioural changes, then these discrepancies can be explained by the timing and stringency of interventions relative to introduction of the virus.

    I disagree with this. If, for example, previous CV infection determined natural immunity rate that could vary between different nations. It is evidence, but weak evidence.

    Second, countries that went into lockdown early experienced fewer deaths in subsequent weeks. Focusing on countries that applied strict suppression measures, we compared the per-capita deaths at the time of lockdown with the per-capita deaths in the following 6 week period (appendix). If herd immunity had already been reached, we would expect no correlation, or even a negative correlation, as lockdown would not alter the herd immunity threshold in the population or the ultimate death rate per capita. A strong linear trend suggests that countries that went into lockdown earlier experienced fewer deaths in the following 6 week period. This trend is therefore inconsistent with the herd immunity explanation; however, it is exactly what one would expect under the explanation that lockdowns are curtailing transmission and deaths, making them most effective when pre-lockdown transmission is low.

    Yes, this seems a good point to me.

    Third, and finally, a strong and consistent relationship exists between the prevalence of antibodies to SARS-CoV-2 and mortality from COVID-19 in European populations, consistent with an IFR of 0·5–1·0%. Using data from serology studies (appendix), we compared the proportion of the population that has evidence of previous infection, as measured by antibodies (seroprevalence) at a given timepoint, with the proportion of the population that died from COVID-19 up to the same timepoint (appendix). A strong linear relationship between seroprevalence and mortality indicates that disparate regions have experienced a similar mortality per infection.

    This result is informative for several reasons. First, if herd immunity had been reached because of a large proportion of the population being infected, then one would expect to see a higher seroprevalence and a correspondingly lower slope (equivalent to a lower IFR). The current data in Europe are consistent with an IFR of 0·5–1·0%, which is many times higher than seasonal influenza (<0·1%). Second, if one conjectures that differences between the European countries in our analysis are caused by differences in severity or death reporting, then one would expect to see very different slopes between countries. The data do not support this explanation. Third, if herd immunity has been reached in all regions, then one would expect to see relatively little variation in seroprevalence. Taking Spain as an example, for the country to have achieved herd immunity, one would have to assume that the herd immunity threshold differs by a factor of ten between regions. In contrast, all of these patterns are easily explained if one assumes that interventions are acting to keep deaths and infections at pre-herd immunity levels. This would, for example, imply that Denmark and Spain have been experiencing a broadly similar IFR but that Denmark has fewer deaths and lower seroprevalence simply because the epidemic did not progress as far as it did in Spain before lockdown came into place. Evidence from outbreaks in confined settings shows the proportion of individuals infected can reach high levels (eg, more than 60%

    ), providing little reason to think the people in these countries who are currently seronegative are not susceptible to infection.

    Yes, this seems a very good point to me.

    In summary, there are large differences in patterns of per-capita deaths in different countries that are difficult to reconcile with herd immunity arguments but are easily explained by the timing and stringency of interventions. Seroprevalence studies also provide an independent source of information that is highly consistent with mortality data. The herd immunity argument is therefore at odds with both mortality and seroprevalence data, whereas the intervention argument provides a parsimonious explanation for both.

    Although the impacts of current control interventions on transmission need to be balanced against their short-term and long-term economic and health impacts on society, epidemiological data suggest that no country has yet seen infection rates sufficient to prevent a second wave of transmission, should controls or behavioural precautions be relaxed without compensatory measures in place.

    Agreed: 2 out of 3 when only one is needed!

  • Well, I view Bayesian inference (updating prior probabilities based on new evidence) as a sound mathematical probabilistic argument used universally that I perhaps wrongly call statistics. And it is also common sense, which we all use intuitively.

    Whether you call this statistics or no, it remains a valid argument.

    And while you can correctly argue linguistics (that it is probability theory not statistics) you cannot from this semantic wordplay of your own argue that it is either wordplay or garbage.

    I've edited the post to keep you happy, substituting probabilistically for statistically.

  • Gilead fraud!…its-big-remdesivir-study/

    How the story developed: After bribing more than 20 persons of CDC and WHO (see old linked references) and spending some 100mio.$ of Remdesivir for free only the running average result did show some trend. Then all a sudden a Chinese study (did show no effect for Gilead crap) was posted on WHO server and short time later disappeared (asked the bribed mafia friends why..) from the WHO server.

    After this the study was changed to show a shortening in hospitalization time only ... But in fact Gilead stopped the study despite the recommendation to continue.…for-coronavirus-patients/

    What did Kaletra (more or less the same mechanism) show: ICU patient just die in avg. 7 days later.. Now if you stop a study at a random point then all the late deaths fall out of the data and you get a fake positive result by just taking the first 400 of more than 1200...

    We know from many sites that did use both Kaletra/Remdesivir than the later is about 10% better so ICU patient with Gilead crap die 9 days later in avg. ...

    Doctors that use Remdesivir possibly engage in a criminal act as in reality there is no proven positive result except a huge (tax-free as usual) kick-back for hospital owners.

    GlobalResearch often reports unfavorably about Israel such as this: The Zionist Idea Has Never Been More Terrifying than It Is Today. This unlabeled opinion piece does not provide a single source of evidence for their claims.

    Hey man! Do you read no newspapers??? All in fact report: The Zionist Idea Has Never Been More Terrifying than It Is Today.!!! except some blind right wing ones....

    Do you know about the Trump plan? XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX. Well known from psychology as the mirror effect.

    But as usual we know what/who drives you...

    Edited: Best we stay away from the Palestine/Israel issue. Shane

  • I've edited the post to keep you happy,

    It neither makes me neither happy or sad whatever THH writes

    but when he attributes 'will convince' to me = 100% probability of convincing??

    it is not Bayesian

    it is THHist hyperbole...and I don't think like that at all.. I am not God..

    o que sera ..sera . por Deus

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