A Chinese elevator with instructions on how to avoid touching the buttons so as to avoid spreading SARS-CoV-2/Wikimedia Commons

Number crunchers around the world are having a field day trying to sort out the whys and wherefores of the SARS-CoV-2 virus, the driver of the Great Pandemic of 2020.

The pre-print service Rvix listed 5,212 SARS-CoV-2-related studies as of Sunday night with 4,202 on medRxiv for health care and 1,010 on bioRxiv for biology.

Collectively, the studies are a testament to the limits of science, which rarely deals in black and white but in the probability that the grey in question is more black than white or vice versa.

Search Rxiv thoroughly and you will find evidence that:

• Bad air increases the risks of catching and dying from COVID-19 and bad air doesn’t increase the risk of catching and dying from COVID-19.
• The warmer weather of summer is likely to seriously slow the spread of the disease, and climate is likely to have little or nothing to do with the spread of the disease.
• Obesity appears linked to COVID-19, and obesity doesn’t appear linked to COVID-19.
• People of color are at significantly greater risk of catching and dying from COVID-19, or maybe not so much.

In some cases, multiple studies weight heavily one way or the other. In other cases, the studies are confusingly contradictory.

This is the nature of science. It is science’s fundamental weakness, and its greatest strength. As Gen. George S. Patton once famously observed, “if everyone is thinking alike, someone isn’t thinking.”

Science is built on the idea that everything needs to be questioned and then questioned again. This makes science ill-equipped to provide clearcut answers in the short term, but better equipped to arrive at a reasoned, factually supported consensus in the long term.

Baby steps

Science is still working in the short term with the SARS-CoV-2 virus that causes COVID-19. Those 5,212 studies have provided a lot of information. What all of the information means is far from fully sorted.

When people proclaim that public policy should be dictated solely by listening to the scientists, they clearly don’t understand science, or they like what they’re hearing from the scientist to whom they’re listening.

He or she might or might not have the right answers.

Dr. Anthony Fauci, the man leading the battle against COVID in the U.S., and Dr. Anders Tegnell, who is leading the same struggle in Sweden, are both scientists trying to do the best job they can with what information is available.

Tegnell isn’t trying to maximize the number of Swedish dead, although some have essentially accused him of that. And Fauci isn’t some sinister operative trying to steer the U.S. into the next Great Depression, though that his how some have tried to paint him. 

They’re both scientists trying to offer to political leaders what they believe to be the best possible advice. At this point, there appear to be more scientists backing the ultra-conservative Fauci approach to the pandemic than the more liberal Anders approach, but the game is still in the first half, maybe the first quarter.

It’s going to be a long time before anyone really knows which of their strategies was best because it’s going to take a while to tally the scorecard. One thing that is known about COVID-19 now – nearly all the studies agree on this – is that the disease is killing a lot of old people who were already sick with other chronic, often terminal, diseases.

Some of those people likely would have died this year with or without COVID-19. Annual mortality figures will start to sort some of that out at the end of the year, but even then the picture could remain foggy for a while.

There are fears that the COVID-19 scare might have kept many people with potentially treatable diseases – among them a variety of cancers – away from hospitals for months now. If that is the case, more cancer deaths might start to show up in the future.

If they do, does one blame them on COVID-19, or on the way humans have managed the COVID-19 pandemic? It’s not an easy question to answer.

Cancer kills somewhere around 600,000 people per year in this country, according to the American Cancer Society, which notes a 27 percent drop in deaths over the course of the last 25 years  “mostly due to steady reductions in smoking and advances in early detection and treatment.”

Smoking rates are unlikely to change due to COVID-19 – though strangely enough study after study has found smoking protective against the disease – but early detection and treatment could be seriously impacted.

If the gains made since 1991 were to be lost, the country could be looking at a rise in cancer deaths near 200,000. Cancer is the nation’s second-leading killer, according to the Centers for Disease Control.

Heart disease is number one; it kills almost 650,000 people per year. It is another of the so-called “co-morbidities” that have increased COVID-19 death rates. The state of New York, which now has the highest COVID-19 death rate in the world, reports that 90 percent of the people who died there had at least one comorbidity.

The counting problem

No one can even guess how many of them might have died within the year, or how much – if at all – annual mortality reports will record drops in deaths by heart disease, cancer, dementia and other diseases at year’s end because the people who would have died from those diseases were killed instead by COVID-19.

About 2.8 million people per year die in the U.S., according to the CDC, so even small decreases in deaths from the co-morbidities could add up to significant numbers. The number of Americans dead from COVID-19 is now nearing 118,000 and growing steadily.

A University of Washington researcher has predicted 500,000 deaths by year’s end if as many people catch COVID-19 this year as caught the flu, but adds in a study published in Health Affairs that “with mitigation strategies, the death toll will be lower. For example, the recent White House COVID-19 Taskforce projections of 100,000–200,000 deaths this year from COVID-19 is made with assumptions about the effectiveness of social distancing directives and measures currently in place.”

Social distancing has been studied since the Spanish flu killed an estimated 675,000 Americans in 1918 and 1919. (If COVID-19 were to prove as deadly, the comparable number of dead from COVID-19 – given the 228 percent increase in the U.S. population since the early 1900s – could reach around 2 million.)

What science learned in the 1900s about how viruses survived and thrived during the Spanish flu hasn’t changed since. SARS-CoV-2 has been spreading and growing in the same way the Spanish flu did, or the common flu still does, by jumping from human to human.

The more space one puts between people, the harder it is for any virus to make that jump. What remains unknown about SARS-CoV-2 at this point is how efficiently it can move through the air or by attaching itself to other objects in the form of fomites, but it is clear that the easiest way to catch it – as with other viruses – is to spend a lot of time close to someone who is infected.

This is not new; this is the old and known.

Chinese scientists who studied 381 COVID-19 outbreaks which infected 1,245 people in 120 cities in April reported that “home outbreaks were the dominant category (254 of 318 outbreaks; 79.9 percent), followed by transport (108; 34 percent).”

Most of the cases involved the infection of three to five people in the home. The number of infections traced to food, entertainment and shopping venues was small, but the number of people infected in such places was often near twice as many as in the home.

The researchers noted also that they “identified only a single outbreak in an outdoor environment….Our study does not rule out outdoor transmission of the virus. However, among our 7,324 identified cases in China with sufficient descriptions, only one outdoor outbreak involving two cases occurred in a village in Shangqiu, Henan. A 27-year-old man had a conversation outdoors with an individual who had returned from Wuhan,” which is believed to be where the pandemic started.

The study did not report how far apart the two people were or how long the conversation lasted. The closer the contact and the longer it lasts has also been known to increase the risk of catching infectious viruses since days of the Spanish flu as has the danger of enclosed spaces.

The Chinese researchers noted the latter specifically in their study.

“We cannot pinpoint the exact transmission routes from these identified outbreaks,” they wrote. “Most health authorities advised that the COVID-19 virus is transmitted mainly by close contact and via the fomite (objects) route. The China NHC also suggested that long-range aerosol transmission may occur when certain conditions are met, such as in crowded enclosures or spaces with poor ventilation…..We do not have data on the hygiene conditions and human density of the infection venues of the 318 outbreaks studied here.”

But they added that their study did lead them to examine building ventilation rates, which they found wanting.

“For example,” they wrote, “the required ventilation rate is only 3 to 9 liters per second (L/s) per person in shopping malls and 2 to 8 L/s per person in public buses, whereas a ventilation rate of 8 to 10 L/s per person is required for good indoor air quality. An international systematic review showed that a rate as high as 25 L/s per person may be
needed.

“Many existing buildings are crowded, poorly ventilated, and unhygienic. A comprehensive review of ventilation conditions in Chinese indoor environments by Ye etal. showed that the CO2 concentration can reach 3,500 ppm in some buildings. The design and operation of buildings have also been under pressure to reduce energy use and increase human productivity.”

Dirty air

This problem is not unique to China.

U.S. “commercial ventilation requirements were lowered in the early 1980s, largely as an energy-conservation measure,” a 2016 study published by Harvard University reported. “With such design changes comes the potential for negative consequences to indoor environmental quality because decreased ventilation can lead to increased
concentration of indoor pollutants. Building related illnesses and sick building syndrome
were first reported in the 1980s as ventilation rates decreased with significant
annual costs and productivity losses due to health symptoms attributable to the indoor
environment.” 

As Americans who have been working from home during the pandemic begin to return to offices, SARS-CoV-2 might bring a whole new meaning to sick building syndrome.

Though U.S. officials are of the opinion that the virus is most often spread by the invisible droplets people emit when they breathe, speak and shout, the Chinese have suggested the virus could be spread by free-floating aerosols as well.

After studying a case in which 10 people in three separate families dining at a restaurant caught COVID-19, one group of Chinese researchers concluded, they most likely were infected by aerosols in the poorly ventilated building, and warned that “aerosol transmission of SARS-CoV-2 due to poor ventilation may explain the community spread of COVID-19.”

The studies that have linked particulate matter in the air to increased cases of COVID-19 could also suggest airborne transmission. Or the studies could be wrong.

As a group of scientists from Predictive Science Inc. in San Diego noted in a recent paper, “studies are beginning to highlight specific parameters that may be playing a role (of the spread of SARS-CoV-2) (but) few have attempted to thoroughly estimate the relative importance of these disparate variables that likely include: climate, population demographics, and imposed state interventions.

“In this report, we compiled a database of more than 28 potentially explanatory variables for each of the 50 U.S. states through early May 2020. Using a combination of traditional statistical and modern machine learning approaches, we identified those variables that were the most statistically significant, and, those that were the most important.”

They went on to report finding a number of variables that appeared statistically significant, but added that most were overwhelmed by two simple factors: population density – which would explain the high death rates in New York City, Boston and other dense-packed U.S. cities – and mobility.

‘This suggests that the biggest impact on COVID-19 deaths was, at least initially, a function of where you lived, and not what you did,” they wrote. “In contrast to these variables, while still statistically significant, race/ethnicity, health, and climate effects could only account for a few percent of the variability in deaths.”

They also warned against “over-interpreting data” given the possibility for all sorts of odds associations that have no discernible connection to a virus.

“Our initial dataset contained a number of other variables that were dropped from the formal analysis, primarily because, although there might be an obvious association with deaths, there was no conceivable driving mechanism (i.e., causal relationship),” they wrote. “For example, we found that the political affiliation of each state (as measured by the results of the 2016 election) was a strong and statistically significant explanatory variable. In addition to this simply being a confounding variable for several others, such as population-weighted density (Republican states tend to be more rural) and the efficacy of lockdowns (Democratic states typically implemented orders earlier and/or more stringently), its variation serves no useful role in explaining the number of deaths.”

The same, it might be said, could prove true of any number of other variables as science continues to sort the ways of a novel virus. There will be information that is meaningful, and information that is not.

At this time, three of the four states with the lowest death rate are red: Alaska, Montana and Wyoming, which combined average 2.2 deaths per 100,000 population. All of the top four states – New York, New Jersey, Massachusetts and Connecticut – are solidly blue and average 133 deaths per 100,000.