As the search for the magic bullet that will stop the SARS-CoV-2 virus continues and the global death toll from COVID-19 climbs ever upward, it’s time to talk science.
The good news is that science has been slowly winning the war against the pandemic.
As the number of cases steadily rises, the odds of survival are improving even more significantly. More than 12.1 million people have now suffered through the disease brought on by SARS-CoV-2, according to the Worldometer tracker , and nearly 11.5 million have survived.
As of today, 94 percent of the people whose cases have been resolved are alive.
When the pandemic began, the survival percentage was down in the mid-80s. Some of the increase in survival rate is likely due to more testing uncovering more of the less serious cases, but there is little doubt that doctors have gotten a better handle on how to treat severe COVID-19.
The bads news is that a vaccine to prevent the disease is months away, never to be found, or expected to be of limited use, all depending largely on the hopes of who is talking.
And this pretty much defines science, which answers few questions in the short term but provides a path to answer many questions over time.
A long, winding road
COVID-19 is underlining both science’s strengths and its weaknesses.
As science exists in the moment, it is scoring big marks for adaptively managing medical treatments and finding effective uses for old drugs. Modern science has become highly skilled in this regard.
Properly conducted, randomized controlled trials (RCTs), sometimes also referred to as randomized clinical trials, are very good at sorting out which chemicals work to fight disease and which don’t even if the researchers can’t always figure out how the drugs work.
RCTs have become the gold standard for managing the “placebo effect,” which can appear to make some drugs effective even if the effect is really in someone’s head. The placecbo effect is the ultimate in humans believing what they want to believe even if the scientific evidence is lacking.
President Donald Trump’s favorite drugs – the old malaria treatments hydroxychloroquine and chloroquine – are a case in point here. Some early observational studies appeared to indicate these could help treat COVID-19; some later studies indicated the drug could cause deadly heart problems.
A later randomized clinical trial concluded both of those observations were wrong.
“The trial results, which were published in the New England Journal of Medicine, determined that hydroxychloroquine was not able to prevent the development of COVID-19 any better than a placebo. Further, 40 percent of trial participants taking hydroxychloroquine developed non-serious side effects – predominantly nausea, upset stomach or diarrhea. However, the trial found no serious side effects or cardiac complications from taking hydroxychloroquine,” reported the University of Minnesota, which led that RCT.
Trump, however, continues to believe in hydroxycholoroquine because some doctors still believe in hydroxycholorquine, and it is possible that a future RCT might ferret out some benefit to the drug.
That sort of thing has happened before, which is why the use of the meta-analysis to look at the conclusions of many studies began trending in science decades ago.
“Since the term and modern approaches to research synthesis were first introduced in the 1970s, meta-analysis has had a revolutionary effect in many scientific fields, helping to establish evidence-based practice and to resolve seemingly contradictory research outcomes,” scientists tracking its 40-year history observed in Nature in 2018. “At the same time, its implementation has engendered criticism and controversy, in some cases general and others specific to particular disciplines.”
Disagreeing is fundamental
Almost everything in science spark pushback because science is more about questions than about answers. By its very nature, it questions everything because so few things prove definitive over time.
Once the smallest particle of matter known to man was dust, and then along came Robert Boyle in 1661 with a hypothesis suggesting clusters of far smaller “particles” creating what he hypothesized to be “corpuscles,” or what we now call molecules.
What followed were ever smaller particles of matter: the atom, the electrons spinning around the atom, then quarks and leptons, and the hunt continues for ever smaller particles because that’s what science does.
It is a search for answers destined to spawn more questions.
Still, most Americans believe in science, and why wouldn’t they?
Science helped the United States become a world power and more. Science drove the engines of commerce that helped win the war to save the world from the Axis powers.
Science built the bomb that finally brought that war to an end and in the process created the fear of mutually assured destruction that has kept the globe free of another world war since 1945.
Science put a man in space and men on the moon, and in the process spun off much of the technology that makes modern life so easy and comfortable that were someone from the early 1900s to come back to life tomorrow he or she wouldn’t recognize these United States.
On the journey from then until now, the country has also become in many ways a technocracy. As a society, we’ve forfeited a lot of our decision making to “experts” because we’ve become conditioned to want the help of experts and then to need the help of experts.
Few people today can fix many, if any, of the things on which their lives depend.
If the computer on which this is being read goes down in the middle of the story and the problem isn’t solved with a simple reboot, most people will be done reading until they find a good tech.
The situation is much the same if their motor vehicle of choice fails or most anything else goes kaput. Most Americans today are helpless without experts.
We have in some ways become hostage to them. Many people can’t even train a dog. They need an expert.
Truths, likelihoods and beliefs
These are the people who in the midst of this pandemic crisis chant “listen to the scientists” with little understanding of the weaknesses of science most especially in the short term.
Science is not geared toward fixing today’s problem on the morrow. The science of the moment is to scientific knowledge what journalism is to history – the first, rough draft.
The only truly definitive things science knows about SARS-CoV-2 today are based on what knowledge was accumulated through 100 years of the study of infectious diseases:
- Viruses spread most easily from person to person, and if you keep people apart you can slow or stop their spread.
- Good hygiene kills “germs,” and dead germs can’t spread disease.
- Animals (and humans are animals) develop anti-bodies against disease, and once enough of them develop anti-bodies, you get what is called “herd immunity.”
The theory of herd immunity is credited to British researchers, William Topley and Graham Wilson, who in 1923 recognized that when a certain number of mice were vaccinated against a bacteria the spread of the bacteria through the mouse population slowed and eventually ended.
Their conclusion was that once a population of animals contained enough members resistant to an infectious disease, the disease would be unable to spread for lack of available hosts.
There is a big debate about herd immunity now because of some studies indicating COVID-19 specific antibodies don’t last long. Of course, there are also studies arguing those antibodies hang on for quite some time or program our so-called “T cells,” which organize the bodies defenses against disease, to battle SAR-CoV-2 – the COVID-19 causing virus – for an unknown length of time.
How this all plays out has major implications for how the virus circulates through the global population in the future with or without a vaccine.
Who knows, it might even restart the debate Topley and Wilson are crediting with ending when they published their work on herd immunity. Up until then the scientists had been arguing over how and why epidemics end.
“This controversy was between those who believed that epidemics terminated because of changes in the properties of the infectious agent (e.g., loss of ‘virulence’ resulting from serial passage) and those
who argued that it reflected the dynamics of the interaction between susceptible, infected, and immune segments of the population,” Paul E.M. Fines wrote in a history for Epidemiologic Reviews decades ago. “Each argument was supported by observations and by mathematical reasoning. It was the latter explanation that won the day; and its simple mathematical
formulation, the ‘mass action principle,’ which has become a cornerstone of epidemiologic theory, provides one of the simplest logical arguments for indirect protection by herd immunity.”
Despite the massive spread of SARS-CoV-2 around the globe today, there have been no suggestions of any country coming anywhere close to achieving the number of infected individuals, generally considered somewhere above 50 percent and possibly as high as 70 percent, necessary to reach herd immunity.
The big experiment
Sweden has been widely criticized for following a more liberal response to COVID-19 and gambling on herd immunity. Swedes were told to social distance, and limits were put on the size of public gatherings. But in general Swedes went on living their lives, albeit a bit more cautiously.
“Sweden has also created interest around the world by following its own path of using a “soft” approach — not locking down, introducing mostly voluntary restrictions and spurning the use of masks,” the Swedish scientists who signed onto that commentary wrote.
“It is possible that the Public Health Authority actually believed that the Swedish approach was the most appropriate and sustainable one, and that the other countries, many of which went into lockdown, would do worse. Perhaps this, and not herd immunity, is the main reason the authorities are desperately clinging to their strategy. Or perhaps an unwillingness to admit early mistakes and take responsibility for thousands of unnecessary deaths plays into this resistance to change. Nevertheless, the result at this stage is unequivocal.”
Since then, however, the situation has changed in Sweden. While the U.S. and some other countries have experienced a rising, second wave of COVID-19 deaths, daily deaths from COVID-19 in Sweden have continued a downward trend that started in late April.
The number of new infections has not fallen nearly as fast as the death rate, but most interesting is that the number of serious cases – those forcing people into intensive care units (ICU) as doctors try to save them – have flatlined.
Since July 24, Sweden reports the admission of only six people to UCIs despite reported new infection rates lingering at 200 to 300 people for most of July.
What does it mean?
In the short term, Swedish national epidemiologist Anders Tegnell, the man at the eye of the storm hammering that nation’s COVID-19 policy, has argued it mainly means Sweden is doing more testing and catching more of the less serious cases.
But Tegnell has also sounded optimistic. At the end of July, he dismissed the need for new measures to stem the pandemic in Sweden calling such measures “not necessary.”
“Asked if he prefers waiting for a potential negative trend, i.e. a spike in cases, before considering new measures, Tegnell said: ‘I think that’s what you normally do and the reason why so many countries have started with face masks is because they’ve taken away other measures and then you need to do something more,’ Tegnell said. ‘If you don’t want to have a complete lockdown, go for face masks instead. Sweden is not there.”’
Masks have now been ordered in public places in many U.S. states where infections are on the rise, and masks are helping to add fuel to the country’s raging political tribalism given scientific disagreement as to their significance.
Apparently, the U.S. is not alone.
“Masking lack of evidence with politics” is how the directors of the Centre for Evidence-Based Medicine at England’s Oxford University headlined their analysis of an issue driving “increasing polarised and politicised views.”
Some studies have concluded masks can make a big difference. Others have questioned that conclusion.
Researchers from John Hopkins School of Medicine who drilled down into the behavior of Maryland residents concluded the big risk is close interactions between people. They could find no statistical significance to masking and noted that “collection of data related to mask use is nuanced as there are several factors that can affect the efficacy of masks that are challenging to collect via this online format such as fit, type of mask,
frequency of touching/adjusting mask, etc.”
It also depends on how one crunches the numbers.
“In sensitivity analyses that restricted analyses to recent mask use and recent SARS-CoV-2 infection,” they reported, “consistent indoor mask use was significantly associated with a lower likelihood of infection.”
Their work was published on the MedRxiv preprint server and was not peer-reviewed as is the case for much of the science being published now. The floodgates have opened, and the confusing and convoluted path that science winds on its way to finding answers has been exposed.
It takes a considerable amount of time and a lot of effort to turn the unknown into the known. And in the interim, public policy stumbles on.
National, state and local leaders make decisions on science that might seem largely right today, largely wrong tomorrow, and sure to be second-guessed if the outcome is less than perfect.
And overlaying all of this is the politics of the moment. Some people now have so much faith in public masking – though there is no science to truly prove you should have much faith in public masking at all – that they believe anyone who isn’t wearing a mask is trying to kill them.
Norwegian scientists – who like most government scientists do not subject their work to peer review – calculated the odds of that as pretty low.
“Given the low prevalence of COVID-19 currently (in Norway), even if facemasks are assumed to be effective, the difference in infection rates between using facemasks and not using facemasks would be small,” they reported in a rapid review. “Assuming that 20 percent of people infectious with SARS-CoV-2 do not have symptoms, and assuming a risk reduction of 40 person for wearing a facemask, 200,000 people would need to wear facemasks to prevent one new infection per week in the current epidemiological situation.”
They offered no details on how they arrived at that conclusion, and Norway is somewhat unique in that it has kept its infection rate fairly low with an emphasis on social distancing and an aggressive program of testing, tracing and isolation of those suffering from COVID-19.
The state of New Jersey is an order of magnitude worse at 179.2 per 100,000; and the state of New York is close to that at 168.5 per 100,000. Masks are standard apparel in both states.
Both states are also densely populated and depend heavily on mass transit to move people. Both of those are problems in the current situation, the John Hopkins researchers concluded.
“The more people move the more likely they are to test positive for SARS-CoV-2,” they reported. “If you must travel, practice social distancing as it reduces the likelihood of testing positive.
“Avoid public transport to the extent possible.”
Alaska – a state in which it is pretty easy to social distance (if not totally isolate) and where there is almost no public transport – has a death rate of 3.3 per 100,000. Wyoming, which is similar, has a death rate of 4.5 per 100,000.
Both are doing better than Norway, which is widely considered to be doing very good in fending off the pandemic. But maybe it’s just luck.
A lot of studies are starting to suggest demographic factors largely beyond government control – population density, the number of old people in the population, the general movement of people between homes and jobs, the general health of the population, socioeconomic status and more – could turn out to be the big determinant factors in how deadly the pandemic from country to country and state to state.
Only time will tell if that is the case because that’s what science requires. What we know today in the fluidity of the movement might be proven to be largely wrong when everything is sorted in the future.
As scientists from the U.S. universities of Stanford and Northwestern, and Australia’s University of Sydney warned their colleagues in a study titled “A Tale of Two Models,” congratulating “ourselves on our decision to implement lockdown, citing the number of lives that were saved, we should resist this temptation, and examine other possible explanations. Failure to do this and therefore misattribute causation could mean we fail to find the optimal solution to this very challenging and complex problem, given that complete lockdown can also have many adverse consequences.
“Observational data need to be dissected very carefully and substantial uncertainty may remain even with the best modeling. Regardless, causal interpretations from models that are not robust should be avoided. Given the analyses that we have performed using the two models that the Imperial College (of England) team has developed, one cannot exclude that the attribution of benefit to complete lockdown is a modeling
Science: it’s a messy and complicated business.