Archive for the ‘Health’ Category

Vaccine worship is almost as bad as anti-vax

October 18, 2020

Anti-vax may be utterly stupid but vaccine worship is not far behind.

Let us not forget the public health fiasco with swine influenza vaccine and narcolepsy. In October 2009, Sweden’s public health services carried out a mass vaccination program against swine influenza. Six million doses of GlaxoSmithKline’s H1N1 influenza vaccine Pandemrix were administered. The vaccine was approved for use by the European Commission in September 2009, upon the recommendations of the European Medicines Agency. By August 2010, both the Swedish Medical Products Agency (MPA) and the Finnish National Institute for Health and Welfare (THL) launched investigations regarding the development of narcolepsy as a side effect.

An increased risk of narcolepsy was found following vaccination with Pandemrix, a monovalent 2009 H1N1 influenza vaccine that was used in several European countries during the H1N1 influenza pandemic. This risk was initially found in Finland, and then other European countries also detected an association.

CDC

Today over 400 people of those vaccinated in Sweden suffer from narcolepsy.

Narcolepsy is a central nervous system disorder characterized by excessive daytime sleepiness (EDS) and abnormal manifestations of rapid eye movement (REM) sleep. This disorder is caused by the brain’s inability to regulate sleep-wake cycles normally. The condition is incurable and life long. Some treatments can help to alleviate symptoms. 

It is the same “experts” and institutions who decided on mass use of Pandemrix who are now inventing public health strategies for Covid-19. Meanwhile a vaccine for the coronavirus is still in its early stages of development and clinical trials. Some of these “expert” strategies are just fairy tales and fantasy.

Vaccinations generally work. Particular vaccinations sometimes don’t. Whether any particular vaccine against Covid-19 will work remains to be seen. The experience with other coronaviruses provides no track record which inspires great confidence.

I get worried when people say they believe in science. To be scientific is to be skeptical. If some science has to be believed in, then whatever it is that has to be believed, is not science.


“What the pandemic has taught us about science” – Matt Ridley

October 14, 2020

Matt Ridley’s article in the Rational Optimist expresses much of my frustration with gullible journalists and the opportunism of the scientific fraternity (where over half are bean counters or clerks and don’t do any science) to exploit every funding opportunity. The money being thrown at Covid-19 research is far too tempting to expect that the charlatans will stay away. More than three hundred different projects being funded for developing a vaccine suggests that either we are so clueless that 300 different paths need to be pursued or that we have a number of fake projects being funded. I am not impressed when projects are funded to “study” how long the virus remains viable on mobile phones as opposed to plastic bags, or when the number of authors on Covid-19 papers are counted and “analysed”.

As Matt Ridley writes:

“…. peer review is often perfunctory rather than thorough; often exploited by chums to help each other; and frequently used by gatekeepers to exclude and extinguish legitimate minority scientific opinions in a field”.

His article is re-blogged here.

What the pandemic has taught us about science – Matt Ridley

The scientific method remains the best way to solve many problems, but bias, overconfidence and politics can sometimes lead scientists astray.

The Covid-19 pandemic has stretched the bond between the public and the scientific profession as never before. Scientists have been revealed to be neither omniscient demigods whose opinions automatically outweigh all political disagreement, nor unscrupulous fraudsters pursuing a political agenda under a cloak of impartiality. Somewhere between the two lies the truth: Science is a flawed and all too human affair, but it can generate timeless truths, and reliable practical guidance, in a way that other approaches cannot.

In a lecture at Cornell University in 1964, the physicist Richard Feynman defined the scientific method. First, you guess, he said, to a ripple of laughter. Then you compute the consequences of your guess. Then you compare those consequences with the evidence from observations or experiments. “If [your guess] disagrees with experiment, it’s wrong. In that simple statement is the key to science. It does not make a difference how beautiful the guess is, how smart you are, who made the guess or what his name is…it’s wrong.”

So when people started falling ill last winter with a respiratory illness, some scientists guessed that a novel coronavirus was responsible. The evidence proved them right. Some guessed it had come from an animal sold in the Wuhan wildlife market. The evidence proved them wrong. Some guessed vaccines could be developed that would prevent infection. The jury is still out.

Seeing science as a game of guess-and-test clarifies what has been happening these past months. Science is not about pronouncing with certainty on the known facts of the world; it is about exploring the unknown by testing guesses, some of which prove wrong.

Bad practice can corrupt all stages of the process. Some scientists fall so in love with their guesses that they fail to test them against evidence. They just compute the consequences and stop there. Mathematical models are elaborate, formal guesses, and there has been a disturbing tendency in recent years to describe their output with words like data, result or outcome. They are nothing of the sort.

An epidemiological model developed last March at Imperial College London was treated by politicians as hard evidence that without lockdowns, the pandemic could kill 2.2 million Americans, 510,000 Britons and 96,000 Swedes. The Swedes tested the model against the real world and found it wanting: They decided to forgo a lockdown, and fewer than 6,000 have died there.

In general, science is much better at telling you about the past and the present than the future. As Philip Tetlock of the University of Pennsylvania and others have shown, forecasting economic, meteorological or epidemiological events more than a short time ahead continues to prove frustratingly hard, and experts are sometimes worse at it than amateurs, because they overemphasize their pet causal theories.

A second mistake is to gather flawed data. On May 22, the respected medical journals the Lancet and the New England Journal of Medicine published a study based on the medical records of 96,000 patients from 671 hospitals around the world that appeared to disprove the guess that the drug hydroxychloroquine could cure Covid-19. The study caused the World Health Organization to halt trials of the drug.

It then emerged, however, that the database came from Surgisphere, a small company with little track record, few employees and no independent scientific board. When challenged, Surgisphere failed to produce the raw data. The papers were retracted with abject apologies from the journals. Nor has hydroxychloroquine since been proven to work. Uncertainty about it persists.

A third problem is that data can be trustworthy but inadequate. Evidence-based medicine teaches doctors to fully trust only science based on the gold standard of randomized controlled trials. But there have been no randomized controlled trials on the wearing of masks to prevent the spread of respiratory diseases (though one is now under way in Denmark). In the West, unlike in Asia, there were months of disagreement this year about the value of masks, culminating in the somewhat desperate argument of mask foes that people might behave too complacently when wearing them. The scientific consensus is that the evidence is good enough and the inconvenience small enough that we need not wait for absolute certainty before advising people to wear masks.

This is an inverted form of the so-called precautionary principle, which holds that uncertainty about possible hazards is a strong reason to limit or ban new technologies. But the principle cuts both ways. If a course of action is known to be safe and cheap and might help to prevent or cure diseases—like wearing a face mask or taking vitamin D supplements, in the case of Covid-19—then uncertainty is no excuse for not trying it.

A fourth mistake is to gather data that are compatible with your guess but to ignore data that contest it. This is known as confirmation bias. You should test the proposition that all swans are white by looking for black ones, not by finding more white ones. Yet scientists “believe” in their guesses, so they often accumulate evidence compatible with them but discount as aberrations evidence that would falsify them—saying, for example, that black swans in Australia don’t count.

Advocates of competing theories are apt to see the same data in different ways. Last January, Chinese scientists published a genome sequence known as RaTG13 from the virus most closely related to the one that causes Covid-19, isolated from a horseshoe bat in 2013. But there are questions surrounding the data. When the sequence was published, the researchers made no reference to the previous name given to the sample or to the outbreak of illness in 2012 that led to the investigation of the mine where the bat lived. It emerged only in July that the sample had been sequenced in 2017-2018 instead of post-Covid, as originally claimed.

These anomalies have led some scientists, including Dr. Li-Meng Yan, who recently left the University of Hong Kong School of Public Health and is a strong critic of the Chinese government, to claim that the bat virus genome sequence was fabricated to distract attention from the truth that the SARS-CoV-2 virus was actually manufactured from other viruses in a laboratory. These scientists continue to seek evidence, such as a lack of expected bacterial DNA in the supposedly fecal sample, that casts doubt on the official story.

By contrast, Dr. Kristian Andersen of Scripps Research in California has looked at the same confused announcements and stated that he does not “believe that any type of laboratory-based scenario is plausible.” Having checked the raw data, he has “no concerns about the overall quality of [the genome of] RaTG13.”

Given that Dr. Andersen’s standing in the scientific world is higher than Dr. Yan’s, much of the media treats Dr. Yan as a crank or conspiracy theorist. Even many of those who think a laboratory leak of the virus causing Covid-19 is possible or likely do not go so far as to claim that a bat virus sequence was fabricated as a distraction. But it is likely that all sides in this debate are succumbing to confirmation bias to some extent, seeking evidence that is compatible with their preferred theory and discounting contradictory evidence.

Dr. Andersen, for instance, has argued that although the virus causing Covid-19 has a “high affinity” for human cell receptors, “computational analyses predict that the interaction is not ideal” and is different from that of SARS, which is “strong evidence that SARS-CoV-2 is not the product of purposeful manipulation.” Yet, even if he is right, many of those who agree the virus is natural would not see this evidence as a slam dunk.

As this example illustrates, one of the hardest questions a science commentator faces is when to take a heretic seriously. It’s tempting for established scientists to use arguments from authority to dismiss reasonable challenges, but not every maverick is a new Galileo. As the astronomer Carl Sagan once put it, “Too much openness and you accept every notion, idea and hypothesis—which is tantamount to knowing nothing. Too much skepticism—especially rejection of new ideas before they are adequately tested—and you’re not only unpleasantly grumpy, but also closed to the advance of science.” In other words, as some wit once put it, don’t be so open-minded that your brains fall out.

Peer review is supposed to be the device that guides us away from unreliable heretics. A scientific result is only reliable when reputable scholars have given it their approval. Dr. Yan’s report has not been peer reviewed. But in recent years, peer review’s reputation has been tarnished by a series of scandals. The Surgisphere study was peer reviewed, as was the study by Dr. Andrew Wakefield, hero of the anti-vaccine movement, claiming that the MMR vaccine (for measles, mumps and rubella) caused autism. Investigations show that peer review is often perfunctory rather than thorough; often exploited by chums to help each other; and frequently used by gatekeepers to exclude and extinguish legitimate minority scientific opinions in a field.

Herbert Ayres, an expert in operations research, summarized the problem well several decades ago: “As a referee of a paper that threatens to disrupt his life, [a professor] is in a conflict-of-interest position, pure and simple. Unless we’re convinced that he, we, and all our friends who referee have integrity in the upper fifth percentile of those who have so far qualified for sainthood, it is beyond naive to believe that censorship does not occur.” Rosalyn Yalow, winner of the Nobel Prize in medicine, was fond of displaying the letter she received in 1955 from the Journal of Clinical Investigation noting that the reviewers were “particularly emphatic in rejecting” her paper.

The health of science depends on tolerating, even encouraging, at least some disagreement. In practice, science is prevented from turning into religion not by asking scientists to challenge their own theories but by getting them to challenge each other, sometimes with gusto. Where science becomes political, as in climate change and Covid-19, this diversity of opinion is sometimes extinguished in the pursuit of a consensus to present to a politician or a press conference, and to deny the oxygen of publicity to cranks. This year has driven home as never before the message that there is no such thing as “the science”; there are different scientific views on how to suppress the virus.

Anthony Fauci, the chief scientific adviser in the U.S., was adamant in the spring that a lockdown was necessary and continues to defend the policy. His equivalent in Sweden, Anders Tegnell, by contrast, had insisted that his country would not impose a formal lockdown and would keep borders, schools, restaurants and fitness centers open while encouraging voluntary social distancing. At first, Dr. Tegnell’s experiment looked foolish as Sweden’s case load increased. Now, with cases low and the Swedish economy in much better health than other countries, he looks wise. Both are good scientists looking at similar evidence, but they came to different conclusions.

Having proved a guess right, scientists must then repeat the experiment. Here too there are problems. A replication crisis has shocked psychology and medicine in recent years, with many scientific conclusions proving impossible to replicate because they were rushed into print with “publication bias” in favor of marginally and accidentally significant results. As the psychologist Stuart Ritchie of Kings College London argues in his new book, “Science Fictions: Exposing Fraud, Bias, Negligence and Hype in Science,” unreliable and even fraudulent papers are now known to lie behind some influential theories.

For example, “priming”—the phenomenon by which people can be induced to behave differently by suggestive words or stimuli—was until recently thought to be a firmly established fact, but studies consistently fail to replicate it. In the famous 1971 Stanford prison experiment, taught to generations of psychology students, role-playing volunteers supposedly chose to behave sadistically toward “prisoners.” Tapes have revealed that the “guards” were actually instructed to behave that way. A widely believed study, subject of a hugely popular TED talk, showing that “power posing” gives you a hormonal boost, cannot be replicated. And a much-publicized discovery that ocean acidification alters fish behavior turned out to be bunk.

Prof. Ritchie argues that the way scientists are funded, published and promoted is corrupting: “Peer review is far from the guarantee of reliability it is cracked up to be, while the system of publication that’s supposed to be a crucial strength of science has become its Achilles heel.” He says that we have “ended up with a scientific system that doesn’t just overlook our human foibles but amplifies them.”

At times, people with great expertise have been humiliated during this pandemic by the way the virus has defied their predictions. Feynman also said: “Science is the belief in the ignorance of experts.” But a theoretical physicist can afford such a view; it is not much comfort to an ordinary person trying to stay safe during the pandemic or a politician looking for advice on how to prevent the spread of the virus. Organized science is indeed able to distill sufficient expertise out of debate in such a way as to solve practical problems. It does so imperfectly, and with wrong turns, but it still does so.

How should the public begin to make sense of the flurry of sometimes contradictory scientific views generated by the Covid-19 crisis? There is no shortcut. The only way to be absolutely sure that one scientific pronouncement is reliable and another is not is to examine the evidence yourself. Relying on the reputation of the scientist, or the reporter reporting it, is the way that many of us go, and is better than nothing, but it is not infallible. If in doubt, do your homework.


Sweden: Covid 19 deaths no longer stick out.

October 12, 2020

 As schools and colleges have opened and partying has resumed, the number of infections have been rising.

However the deaths attributed to Covid-19 no longer stick out of the average of deaths/day (all causes).


Courage! Science (and bean-counters) cannot control the pandemic

October 7, 2020

Ten months on and I keep hearing the inane slogan “Follow the science”. But the best medical advice is floundering and is still no more than the basic common sense advice of “avoid being infected”. The simple reality is that the best our current science has to offer was unable to prevent the pandemic and is unable to curtail it or bring it under control. The Covid-19 virus cannot, at least for now, be eradicated.

While the medical fraternity is doing great things in treating those infected and is expending enormous money and energy in finding a vaccine, the epidemiological fraternity has failed spectacularly in both preventing the pandemic and in controlling or curtailing the pandemic. But more damaging is the illusion they promote that they are in control. Pretending you can when you cannot is bordering on gross negligence. Essentially they have nothing more to offer than the best advice available at the time of the Black Death almost 700 years ago.

I begin to suspect that epidemiology is more about bean-counting than about science. The political process which has relied on these bean-counters has vacillated between cowardice and courage.


100 years after the Spanish flu, virology still has far to go

October 4, 2020

Medical science does wonders. From amazing surgical procedures to an incredible variety of drugs and a fantastic array of tools and equipment, medicine, as it is practiced today, is light years ahead of where it was in 1918 at the time of the Spanish flu. Yet, medical science has not been capable of quickly defeating the current Wuhan virus pandemic. Health care has improved beyond recognition. Compared to 100 years ago, health services can deploy a bewildering variety of drugs and equipment and therapies to treat the infected.

The effects of the current pandemic are most often compared with the effects of the Spanish flu in 1918. The flu virus was identified in 1933 and the first flu vaccine came out in 1942. However, even today the flu vaccine is thought to be effective only in a little over 50% of cases. It is estimated that the Spanish flu, over a period of 3 years killed between 25 and 39 million people and that about 500 million were infected when the global population was only about 1,800 million. Today with a global population of 7, 200 million it is estimated that at least 35 million have been infected and, so far, over 1 million are thought to have died. The pandemic has lasted 6 months and is still ongoing. The virus was identified very quickly – perhaps one month – but only after the data repressed by the Chinese government and the WHO – leaked out.

The hunt for a vaccine is only 6 months old. There are at least 300 groups actively searching for one. Around 30 proposed vaccines have entered some kind of clinical trials. Estimates of when a vaccine could be readily available range from 6 months to 2 years to never. Money is being thrown at vaccine development at unprecedented levels. Certainly some of the groups chasing a vaccine have zero chance of success but cannot resist the temptation of huge amounts of easy money.

But virology is far from a settled science. In fact, there is still debate on whether a virus is living or not. That there are 300 different groups seeking a vaccine is, itself, evidence of 300 different opinions. During the past 6 months a bewildering variety of suggestions have been made for prophylactics, remedies and cures. Every single one has come from a “medical specialist”. The best advice is still “avoid infection” (by social distancing and masks which may or may not work), and hope. There are no preventive drugs and there are no cures (beyond treating symptoms). If and when vaccines are found, they will vary in how effective they are. Estimates of how expensive a vaccine may be range from 30$ to 300$ per dose for either a one-dose or a two-dose vaccine, with immunity available for periods ranging from 3 months to 1 year after vaccination.

Everyday new “experts” are trotted out on TV. But the science is not settled and there are no experts. The simple reality is that compared to 100 years ago, this pandemic has medical science just as stymied as the Spanish flu did – but at a very much higher level of knowledge.


At least 44 vaccines under Phase 1 -3 trials

September 1, 2020

There may never be a vaccine.

A vaccine may apparently be developed but long term effects will be unknown.

The most plausible scenario is that there may be promising vaccine available for mass usage, and with a reasonable level of safety, in the summer of 2021.

RAPS has an illuminating post detailing the various vaccines under trial and their status:

Researchers worldwide are working around the clock to find a vaccine against SARS-CoV-2, the virus causing the COVID-19 pandemic. Experts estimate that a fast-tracked vaccine development process could speed a successful candidate to market in approximately 12-18 months – if the process goes smoothly from conception to market availability.

To date, just one coronavirus vaccine has been approved. Sputnik V – formerly known as Gam-COVID-Vac and developed by the Gamaleya Research Institute in Moscow – was approved by the Ministry of Health of the Russian Federation on 11 August. ………. 

The pandemic has created unprecedented public/private partnerships. Operation Warp Speed (OWS) is a collaboration of several US federal government departments including Health and Human Services and its subagencies, Agriculture, Energy and Veterans Affairs and the private sector. Within OWS, the US National Institutes of Health (NIH) has partnered with more than 18 biopharmaceutical companies to accelerate development of drug and vaccine candidates for COVID-19 (ACTIV). The COVID-19 Prevention Trials Network (COVPN) has also been established, which combines clinical trial networks funded by the National Institute of Allergy and Infectious Diseases (NIAID): the HIV Vaccine Trials Network (HVTN), HIV Prevention Trials Network (HPTN), Infectious Diseases Clinical Research Consortium (IDCRC), and the AIDS Clinical Trials Group.

The COVAX initiative, part of the World Health Organization’s (WHO) Access to COVID-19 Tools (ACT) Accelerator, is being spearheaded by the Coalition for Epidemic Preparedness Innovations (CEPI); Gavi, the Vaccine Alliance; and WHO. The goal is to work with vaccine manufacturers to offer low-cost COVID-19 vaccines to countries. Currently, CEPI’s candidates from companies Inovio, Moderna, CureVac, Institut Pasteur/Merck/Themis, AstraZeneca/University of Oxford, Novavax, University of Hong Kong, Clover Biopharmaceuticals, and University of Queensland/CSL are part of the COVAX initiative. There are further candidates being evaluated in the COVAX Facility from the United States and internationally.

The US government has chosen three vaccine candidates to fund for Phase 3 trials under Operation Warp Speed: Moderna’s mRNA-1273, The University of Oxford and AstraZeneca’s AZD1222, and Pfizer and BioNTech’s BNT162. Members of ACTIV have suggested  developing safe controlled human infection models (CHIMs) for human trials could take 1-2 years. A sponsor would need to provide data from placebo-controlled trials indicating their vaccine is at least 50% effective against COVID-19 in order to be authorized for use, according to FDA guidance issued and effective 30 June. 

The 44 candidates ( as of 31st August 2020) are:

AAVCOVID, Ad26.COV2-S, Ad5-nCoV, AdCOVID, Adenovirus-based vaccine, AdimrSC-2f, Adjuvant recombinant vaccine candidate, AZD1222/Covishield, Bacillus Calmette-Guerin (BCG) live-attenuated vaccine, bacTRL-Spike, BBIBP-CorV, BNT162, ChAd-SARS-CoV-2-S, CoronaVac, COVAX-19, Covaxin, gp96-based vaccine, GRAd-COV2, GRAd-COV2, HaloVax, HDT-301, Ii-Key peptide COVID-19 vaccine, Inactivated vaccine, INO-4800, LineaDNA, LUNAR-COV19, Molecular clamp vaccine, mRNA lipid nanoparticle (mRNA-LNP) vaccine, mRNA-1273, mRNA-based vaccine, mRNA-based vaccine, NVX-CoV2373, PittCoVacc, Plant-based adjutant COVID-19 vaccine candidate, Protein subunit vaccine, Recombinant vaccine 1, Recombinant vaccine 2, SCB-2019, Self-amplifying RNA vaccine, Sputnik V, T-COVIDTM, V590, V591, ZyCoV-D

Covid candidate vaccines (pdf)


 

The Wuhan virus and common sense

July 26, 2020

Common sense went on vacation sometime in March 2020.

It seems to be an extended vacation and it is not certain when it will return.

Virus sense

Lockdowns seem to be counterproductive. They solve nothing. Instead they extend the life of the virus and prolong the pandemic. They could have maximized the global death toll. The only positive is that they may reduce the load on the hospitals.

The two areas where Sweden got it wrong were:

  • they did not restrict infection sources from reaching the care homes, and
  • they locked up the elderly in their “infected prisons”

But all the rest they did right.


 

Epidemiology is still more art than science and sometimes just speculation

July 24, 2020

The Wuhan virus, after 6 months, is still not under control.

I have grown a little tired of being told by all kinds of people that they are just following the science in the fight against the Wuhan virus. What science? There is a widespread delusion that epidemiology is a “settled science”. Epidemiology is, in reality, a mix of science and art and of “social science” (which is always a politicized view of behaviour). It is about “the frequency and pattern of health events in a population”. With a little known virus, as in this case, epidemiology relies on models and speculation. When the speculation is garbage, the model results are also, necessarily, garbage. The model results have ranged from the ridiculously complacent to the grotesquely alarmist, but what they all have in common is that they are/were wrong. Nothing surprising in that. That is the nature of modelling. A mathematical model is nothing more than a crystal ball and model results are always forecasts of the future. The problem lies in the delusion that epidemiology is an exact science and that model results give a sound and certain basis for public policy.

In the absence of a vaccine we are being led (or misled) by politicians blindly following the epidemiologists’ speculations about both the characteristics of the unknown virus and about social behaviour. In the space of 4 months the “best” epidemiologists at the WHO have changed their view of the Wuhan virus from being “non communicable between humans”, to “communicable by liquid droplets between humans”, to now be of “air borne transmission”. The experts have been divided whether transmission is from the symptomatic or from the asymptomatic. There are as many speculative views about when herd immunity can be achieved as there are epidemiologists. No one really knows. Art not science. Herds are always moving and herd immunity depends upon leaving the weak behind. Public policy is floundering as it staggers from lockdowns to no lockdowns to social distancing, from masks to no masks to some masks to masks for some, and from testing those with symptoms to restricted testing to mass testing. There is no certainty about whether testing is to be for the virus or for antibodies to the virus.

The Center for Disease Control has this definition of epidemiology:

Epidemiology is the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems.

But then they go on:

…. the practice of epidemiology is both a science and an art.

The reliance on speculation and the resulting weaknesses of epidemiology are well known and there are many scientific articles about spurious but statistically significant epidemiological forecasts. This article in the BMJ from 2004 is just an example.

The scandal of poor epidemiological research

Something surely must be wrong with epidemiology when the new editors of a leading journal in the field entitle their inaugural offering, “Epidemiology—is it time to call it a day?” Observational epidemiology has not had a good press in recent years. Conflicting results from epidemiological studies of the risks of daily life, such as coffee, hair dye, or hormones, are frequently and eagerly reported in the popular press, providing a constant source of anxiety for the public.  In many cases deeply held beliefs, given credibility by numerous observational studies over long periods of time, are challenged only when contradicted by randomised trials. In the most recent example, a Cochrane review of randomised trials shows that antioxidant vitamins do not prevent gastrointestinal cancer and may even increase all cause mortality. 
Now Pocock et al describe the quality and the litany of problems of 73 epidemiological studies published in January 2001 in general medical and specialist journals. …… Worryingly, Pocock et al find that the rationale behind the choice of confounders is usually unclear, and that the extent of adjustment varies greatly. They also confirm that observational studies often consider several exposures, outcomes, and subgroups. This results in multiple statistical tests of hypotheses and a high probability of finding associations that are statistically significant but spurious. 

Modern epidemiology starting from – say – the 1854 London cholera outbreak has vastly improved public health. But it is not just a science and it is certainly not a “settled science”. The Wuhan virus is not under control. The various public policy interventions (lockdowns of various kinds and the deselection of the old for treatment) have prolonged, rather than shortened, the outbreak. The lockdowns may have protected health systems while maximizing the number of deaths. In fact, politicians have often abdicated responsibility for public policy to epidemiologists and bureaucrats who have not been best-suited to make political decisions. In other cases public policy has exploited epidemiology to protect the system rather than protecting people.

This is not so much to criticize epidemiology as to criticize the manner in which public policy has misused epidemiology. Epidemiology can only be an input for determining public policy. It cannot replace common sense. And it is not a convenient shelter for politicians to hide behind.


 

Has “flattening the curve” maximized the number of Wuhan virus deaths?

July 22, 2020

I am beginning to think that the international lockdowns may have been a colossal mistake.

The primary objective of “flattening the curve” was to protect health services, not to minimize deaths.

In theory, flattening the curve should have given the same number of deaths but over a longer period of time. In practice, the flattened curve has kept the pandemic alive for much longer than necessary. The lockdowns have ensured that no general immunity has been achieved anywhere. The total number of deaths could well have been lower with a more intense but short-lived pandemic.

 

“Flattening the curve” Theory

“Flattening the curve” Actual?

The assumption that the curve can be flattened without affecting the area under the curve is speculative and unjustified. The two curves cannot be equated. The reality is that extending the tail of the curve by attempting to flatten the peak may have done more damage than good.

Have the lockdowns actually saved any lives?

Or have they extended the pandemic such that more lives have been lost than if there had been no lockdowns. And at the cost of a global economic shutdown. Fewer lives lost per day but for a very, very long time as opposed to many lives lost per day over a much shorter period of time.

Flattening the curve may well have maximized the number of deaths.

The Chief Minister of Karnataka State in India actually made some sense yesterday when he said:

“There will be no lockdown in Bengaluru from tomorrow. However, I humbly request the people of Karnataka — with folded hands — to wear masks and to practice social distancing. This is the only way to combat COVID-19, at least till a vaccine is found,  …….. People can resume work and businesses as usual, outside containment zones. A stable economy is essential for the state to combat the coronavirus pandemic effectively.” 

Indeed. Protecting a health service in a collapsed economy is not possible.


 

So what exactly have the lockdowns achieved?

July 20, 2020

The Wuhan virus continues to lay waste.

Cases are on the rise again.

Deaths are also rising globally.

The pandemic is now expected to continue into 2021.

There will be no reliable vaccine at least until spring 2021.

So, what exactly have the lockdowns and economic disruption achieved?

If anything?

But one thing is certain. The lockdowns have extended the life of the pandemic.

Without any lockdowns there may well have been a sharper peak.

But it could possibly all have been over by now.

The WHO is clueless. It went from “no person-to-person transmission” to “transmission by fluids only” and is now on to “air-borne transmission”.

Alarmist models don’t make for settled science.


 

 

 


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