By Kent R. Kroeger (Source: NuQum.com, May 28, 2020)

“I don’t believe I am costing lives at all,” said Missouri Governor Mike Parson (R) in late March as he rejected calls for a statewide stay-at-home (SaH) order. “The effects that (a statewide SaH) will have on everyday people are dramatic. That means businesses will close, people will lose their jobs, the economy will be in worse shape than ever.”

At the time Governor Parson said those words, eight Missourians had lost their lives to COVID-19. Two months later, the death toll stands at 705 (or about 115 people per 1 million Missouri residents), putting the Show-Me state at 26th among the 50 states (plus District of Columbia) in the relative number of COVID-19 deaths. Missouri is ranked 37th in the relative number of confirmed COVID-19 cases at 2,088 per 1 million people.

In other words, Missouri’s performance so far in containing the coronavirus is roughly average to above-average.

It can’t emphasized enough that this pandemic is still an ongoing and many of the Middle America states that refused to impose stay-at-home orders, such as Iowa, Nebraska and Arkansas, are now in the middle of their first wave of cases (as opposed to states like New York and New Jersey that are near the end of the first wave).

Still, it is legitimate to consider whether Governor Parson was at least partially correct about SaH orders (though he did end up issuing a SaH order on April 6th). This question is particularly important as all 50 states (plus the District of Columbia) are in the midst of slowly re-opening for business — some faster than others.

What is not helpful nor analytically pertinent is the suggestion that one party is wholly responsible for increasing the number of COVID-19 deaths or worsening an economic recession merely for political gain.

At least, as of today, explicitly political variables (e.g., a state governor’s political party, Trump’s share of the statewide vote in 2016, etc.) offer little information that can explain the relative number of COVID-19 cases and deaths across states.

However, today we are in a period where many of the Democrat-led states (CT, HA, KY, LA, MI, MT, NY, NJ, OR, RI, PA, WA) are witnessing significantly lower numbers of new cases as the first wave of the COVID-19 pandemic nears its end in those states (see Figure 1). Six out of the 10 states with the lowest relative number of new cases in the past week (May 19th to 25th) are led by Democratic governors.

In contrast, four out of the 10 states with the highest relative number of new cases new cases in the past week are led by Republican governors.

Figure 1: A state’s recent new cases (7-day moving average, May 19–25) as a percent of the state’s highest 7-day average (Data from 22 Jan — 25 May)

If there is a partisan effect on how long this pandemic is extending, it is more subtle than appreciated.

A more explanatory hypothesis might be that the start of the summer tourism season is starting to increase new COVID-19 cases for coastal states (AL, CA, GA, ME, MD, MS, NC, SC, TX, VA). Figure 2 shows a selection of beach states and their 7-day moving average trends in new cases.

Figure 2: New COVID-19 Case Trends by Selected Beach States (as of 25 May)

We’ve seen the pictures and video from the Memorial Day weekend: Ocean City, MD tourists cramming along the boardwalk with not even a quarter of the people wearing face masks.

Even you believe it is hard to transmit the COVID-19-causing virus (SARS-CoV-2) or believe its effect is not significantly different from the seasonal flu, not donning a mask is disrespectful to those who believe otherwise. Its called being neighborly and its a small price to pay if that is what it takes to keep our beaches and outdoor entertainment facilities open.

In the next 14 days or so, we will see the impact of the Memorial Day weekend on new COVID-19 cases. If we don’t see a bump, expect almost all states to accelerate their phase-out of business closures and SaH orders. If we witness a surge, on the other hand, the recriminations and calls for extending SaH orders will thunder across cable news networks and social media.

New COVID-19 Path Model (updated through 25 May 2020)

Figure 3 (below) shows the coefficient estimates for a path (mediation) model estimated in JASP, a free statistical software package available here. More detailed results for this path model are in the Appendix at the end of this essay.

As with previous path models I’ve estimated for the COVID-19 pandemic, the outcome of interest is the relative fatality rate for COVID-19 (measured in each state as the number of fatalities per 1 million people). The mediating variable is the relative confirmed case rate (number of cases per 1 million people) and the other predictor variables are: (1) A binary variable for West Coast states (CA, HA, OR, WA), (2) A binary variable for whether a state imposed a SaH order, (3) a binary variable for states that imposed travel restrictions, (4) the number of COVID-19 tests (per 1 million people), and (5) a state’s population density. [Note: An indicator variable for “Beach” states was only weakly correlated with the outcome and mediation variables and was therefore left out of the final path model.]

Overall, the path model in Figure 3 explains 75 percent of the variance in relative confirmed case rates and 93 percent of the variance in relative fatality rates.

Figure 3: COVID-19 Path Model (U.S. data updated through 25 May 2020)

In the case of COVID-19-related fatalities through May 25th, by far, the most significant correlate is the relative number of confirmed cases. That is not surprising. More puzzling is that SaH states have experienced disproportionately more COVID-19 fatalities than non-SaH states, all else equal. This relationship is weak enough, however, that it could change when the first wave of this pandemic is over for every state. Those two variables were the only variables significantly correlated with COVID-19 fatalities.

The more interesting results are for the factors correlated with the relative number of confirmed cases where (as in past models I’ve estimated) a state’s population density and the number of COVID-19 tests (per 1 million people) are the most significant correlates with case rates.

However, we also find two policy variables negatively correlated with case rates (SaH orders and Travel Restrictions). In other words, the presence of a SaH order and travel restrictions in a state independently correlate with fewer COVID-19 cases in that state. This is in consistent with our expectations that these policies should suppress confirmed case numbers (if only temporarily).

Finally, the West Coast states (CA, HA, OR, WA) are also negatively associated with relative confirmed case rates. This relationship has been fairly consistent over time, if previous path models are an indication.

The significance of West Coast states, however, may not be a function of the specific policies in those states (though all four were aggressive in putting SaH orders in place early). There is epidemiological evidence that the U.S. West Coast has been predominately hit by a slightly weaker form of the SARS-CoV-2 virus compared to the U.S. East Coast. For this reason, I hesitate to assume West Coast state policies are the sole reason for their relatively lower case rates. It most likely a combination of the SARS-CoV-2’s pathogenic characteristics and state policies.

Final Thoughts

As I must always caveat any statistical finding related to the COVID-19 pandemic: the pandemic is far from over. In fact, we may only be in the first of many contagion waves for this virus, according to The University of Minnesota’s Center for Infectious Disease Research and Policy (CIDRAP). Indeed, the hopeful discovery and production of a SARS-CoV-2 vaccine by early next year (or possibly late this year) may not completely eliminate the presence of COVID-19 in our lives.

Furthermore, our knowledge about this virus seems to change by the day. On day the CDC can say picking up the virus from surface exposure, and the next day the CDC retracts that statement and says “it is possible to become infected by touching a surface containing the active virus.”

We just don’t know enough to make strong declarative statements yet on what policies will or won’t defeat SARS-CoV-2.

For all of these reasons, the partisan narratives polluting our airwaves over this virus are not helping in the slightest. These partisan tirades from both sides are, in fact, hurting the learning process for those in a decision-making position who must increasingly filter out the noise to get to the facts.

No politician, in the U.S. or elsewhere, has made perfect decisions regarding COVID-19 and they will make mistakes going forward. [I know how successful New Zealand Prime Minister Jacinda Ardern has been in pushing policies that have successfully suppressed the virus in her country; but, remember, New Zealand is an island. They have an advantage. The same goes for Hawaii.]

It is time to chuck the partisan noise driving the coronavirus narrative in the national media and, instead, focus on the actual facts.

Recent COVID-19 data has not been a good news story for a significant number of Republican-led states. Unfortunately for some Democrat-led states (e.g., CA), it has been a tough week for them too.

What is clear from a statistical point of view, the coronavirus does not give a bucket of owl spit about anyone’s political preferences. The coronavirus is brutally apolitical.

Slowly and methodically, the U.S. states are converging towards similar COVID-19 case and death rates, independent of partisanship or public policy. That does not mean public policy is irrelevant. Governors are merely rearranging chairs on the Titanic. Ask Hawaiians if state-level coronavirus policies have made a difference. They have mattered, as we can see with the significance of travel restrictions and statewide stay-at-home orders in the above path model.

Policies matter. But the pathogenic characteristics of the SARS-CoV-2 virus matter more. It is highly contagious and three to four times deadlier than the average seasonal flu, according to the newest estimates by the Centers for Disease Control and Prevention.

So, please wear a mask…even if you are at the beach.

• K.R.K.

Send comments to: kroeger98@yahoo.com

or tweet me at: @KRobertKroeger1

APPENDIX: Path Model Output and Diagnostics

By Kent R. Kroeger (Source: NuQum.com, May 26, 2020)

I stopped counting at 50 — the number essays that came up in Google when I searched on “Why I am not voting…”

And that was after filtering down to essays focused on not voting for president, as opposed to not voting for a particular candidate or party.

So when I decided to write this essay, I knew I wouldn’t say anything new or novel. And that is not my intent.

Rather, I believe the more people who extend their voice into the public arena about their disaffection with the American political system by posting on Medium.com, Facebook, Twitter, or their personal websites, the stronger our message to the two major parties and the news media will be that our political system doesn’t represent our interests or values well enough to inspire voting.

In writing this, I understand that the news media and the social media platforms consciously choose to exclude voices outside their definition of the mainstream. [To be fair, this has been the case since the invention of the movable metal type printing press. Gutenberg printed the Bible after all — what was more mainstream in 15th-century Europe than that?]

Facebook explicitly bans paid ads that suggest voting is useless or advise people not to vote, under the justification that they are fighting voter suppression and interference. More ominously, Facebook announced last year that their “systems are now more effective at proactively detecting and removing this harmful content. We use machine learning to help us quickly identify potentially incorrect voting information and remove it.”

[A Facebook public relations representative did not reply to my inquiries over whether Facebook’s machine learning algorithm censored posts promoting or describing personal reasons for not voting.]

However, Facebook, Google and Twitter’s track record suggests they feel legally and ethically justified in targeting and suppressing a broad range of political speech that deviates from a mainstream consensus. [Comedian Jimmy Dore’s magnificent, towering rant against Twitter over its censoring of tweets suggesting Democrat’s should not have voted in their primaries during the coronavirus pandemic is worth a look-see here.]

My reason for writing this essay focuses on my own sentiments and I am not suggesting people who feel represented under our current political system should stop voting just because I’m not inclined to do so. In fact, if such a person were to do so, it would dilute my message to the two political parties.

But I know there are people like me (if past non-voting behavior is an indication), and if they read this essay, perhaps they might realize they are far from alone.

There are three issues that I expect my preferred presidential candidate to address in a coherent, credible way. I don’t necessarily expect the candidate to know the specifics underlying these issues, but I need to trust their broad intentions. [The only candidate to make me feel that way since Jesse Jackson in 1984 and 1988 has been Tulsi Gabbard.]

Here are my issues:

(1) Ending our nation’s forever wars,

(2) Reversing monetary and fiscal policies that have helped to increase income inequality over the past 30 years, and

(3) Moving this country significantly closer to a universal health care system.

I could have easily added education costs and climate change, but those issues wouldn’t change my decision not to vote for President Donald Trump or former Vice President Joe Biden. From my perspective, they are bad on all these issues, and its not even close. You are free to disagree.

Ending America’s Forever Wars

This is an easy one. The Obama-Biden administration continued George W. Bush’s occupation of two countries (Iraq, Afghanistan) and decided to bomb five more (Syria, Libya, Yemen, Somalia, Pakistan), eventually putting troops in Syria and leaving the country so destabilized that 400,000 Syrian civilians would lose their lives in a civil war which started in 2011.

Barack Obama was the biggest disappointment as president in my lifetime. I feared George W. Bush’s oil buddies would lead this country to a near apocalyptic disaster in the Middle East and they didn’t disappoint, but at least they kept their unwinnable wars down to two.

Biden has been a stronger defender of the Obama war record, even suggesting during a trip to Turkey in early 2016, as the U.S. turned its military focus off of arming anti-Assad jihadists and towards rolling back ISIS, that the U.S. should use its military to take out Assad. The Obama foreign policy team and U.S. military leaders quickly distanced themselves from Biden’s informal remarks, forcing his staff to promptly issue a clarification saying “there is no change in U.S. policy (in Syria).”

If you are tired of Trump’s “off-the-cuff” U.S. foreign policy changes, Biden may not be your relief.

As for Trump’s national security policy, it looks remarkably similar to Obama’s but with the palpable threat of a war with Iran to make my blood pressure even higher.

Trump has not ended any war during his first term and there is no reason to think he will in a second term.

Decreasing Income Inequality

Trump’s administration has spurred real income growth among working class and minority Americans. Whatever damage the coronavirus pandemic has done to the U.S. economy, up to that point, Trump had been successfully in lifting incomes across all income groups.

But in terms of economic inequality, the Trump administration has continued and amplified the same monetary and fiscal policies that have led to the secular increase in U.S. income inequality since the 1980s.

Figure 1: Share of Total Net Worth Held by the Top 1% in the U.S.

Trump didn’t cause income inequality, but the economic growth during his administration has not reduced it. In fact, in addressing the economic damage done by the coronavirus pandemic, Trump and congressional Democrats have mothered one of the most unbalanced economic rescue bills in U.S. history — the $2.2 trillion CARES Act, which includes a tax provision that allows taxpayers to use some business losses to reduce taxes owed on non-business income, such as profits from investments.

Roughly 80 percent of the benefits of this CARES Act tax provision will go to roughly 43,000 taxpayers who earn more than $1 million a year, according to the analysis conducted by the U.S. Congress’ Joint Committee on Taxation.

Biden, like most congressional Democrats, has expressed support for the CARES Act and its tax provisions. And while Biden’s campaign has issued nebulous policy proposals that would extend direct financial support to some Americans affected by the coronavirus, Biden has offered no ideas on the scale of Change.org’s Universal Basic Income (UBI) proposal where monthly payments of $2,000 would go to everyone in the U.S. while the pandemic continues. [The CARES Act distributed $1,200 to some Americans based on income.]

But pandemic stimulus packages aside, the causes of income inequality are rooted much deeper within U.S. public policy. For example, following the worldwide financial crisis of 2007–08, the U.S. Federal Reserve’s quantitative easing (QE) policy — where it buys long-term securities to push down long-term interest rates — resulted in the Fed accumulating $4.5 trillion worth of assets by late 2014. The QE-era Fed policies have been on “as expansive a setting as it ever has been — not only in this recovery, but arguably in the history of the nation,” according to the New York Times.

The Fed’s QE policies during the Obama administration helped grow the Top 1%’s share of total net worth by almost 25 percent (see Figure 1), and that is not just the opinion of people like U.S. Senator Bernie Sanders, the Fed itself acknowledges the connection. In May 2013, Federal Reserve Bank of Dallas President Richard Fisher acknowledged on CNBC that “cheap money has made rich people richer, but has not done quite as much for working Americans.”

More recently, former UK Prime Minister Theresa May said the same thing about similar monetary policies in her country: “”Monetary policy — in the form of super-low interest rates and quantitative easing — has helped those on the property ladder at the expense of those who can’t afford to own their own home.”

And where do Trump and Biden stand on these Fed policies — which are relevant again given the pandemic-caused economic slowdown? Not a word.

How about their policy proposals addressing other causes of inequality, such as CEO compensation or capital-friendly tax policies? Crickets.

Universal Health Care

On his campaign website, Biden posts his five-point plan to improve the U.S. health care system. Among his proposals are lowering Medicare eligibility to 60 years old and including a public option available to individuals not happy with the employer-based health plan.

I could forgive Biden for putting his health care ideas 24th on his list of priorities, if I thought he was willing and capable to push for his health care proposals once elected. But I don’t.

The Obama-Biden administration had two years where the Democrats controlled both congressional chambers and, while letting Nancy Pelosi and congressional Democrats craft what would become known as Obamacare, rolled over like a love sick puppy when a public option was taken out of the legislation.

“Ultimately, the public option failed as a result of many factors, including lack of support from moderate and conservative Democrats, opposition from Republicans and health care interest groups, and ultimately an absence of strong support from the White House,” according to Helen A. Halpin and Peter Harbage of HealthAffairs.org.

Will things be different if Joe Biden is elected? Not likely, according to Wendell Potter, a former Cigna executive turned private healthcare whistleblower. “Biden, Pelosi, and Schumer know the health care special interests can plow millions of dollars into the campaigns of candidates they favor or think they can influence. Because we have no real constraints on that spending, the special interests, as always, are contributing to candidates in both parties, and Biden, Pelosi, and Schumer and others who raise money for themselves and other Dems want to keep as much of it flowing to Dems as possible.”

Given that so many health care insurance, medical equipment, and pharmaceutical executives orbit around the Biden campaign, it is safe to assume they have his ear on health care policy and any real reform ideas, such as a public option, will not make their way into a Biden administration health care bill.

When judging candidates, more important to me than any single issue is whether I trust a candidate to do what they say. In the case of Biden on health care reform, he’s earned my lack of trust.

As for Trump on health care reform, he’s earned a D- up to now, and there is no reason to believe a second Trump term would be different.

It’s a two-party system, but is it my civic duty to pick sides?

Barely a week into my first political campaign job as a canvass coordinator for Iowa Democrat Tom Harkin’s 1984 Senate run, I was once told by my boss, longtime Democratic operative, Teresa Vilmain, “Don’t let people tell you they are not voting or are supporting a third party candidate. We are a two-party system. That’s the choice.”

Her logic was nonsense then and sounds worse today.

For one, we are not explicitly a two-party system. The Constitution doesn’t even mention political parties, and for good reason, according to historian Sarah Pruitt:

“This was no accident. The framers of the new Constitution desperately wanted to avoid the divisions that had ripped England apart in the bloody civil wars of the 17th century. Many of them saw parties — or “factions,” as they called them — as corrupt relics of the monarchical British system that they wanted to discard in favor of a truly democratic government.”

Secondly, non-voting is a legitimate voting choice that carries with it, in the aggregate, significant information that the two major parties can use to increase their chances of winning the next election.

I believe that strategic use of my vote choice in 2020 is more impactful than voting for a candidate that does not come close to representing my interests or values.

Not voting is not a wasted vote when done for this reason. If enough people who feel the same way consistently do not vote, at some point, one of the two parties — probably the one that loses consistently — is going to get their act together and start representing us disaffected non-voters.

I can dream.

I use this analogy when talking about my decision not to vote:

Imagine a country where there are only two movie studios and the people in this country have the habit of going to the movies one weekend every month, regardless of what movies are showing or their quality.

Imagine in this same country the two movies have found it easier to make bad movies, and since the people keep going to the movies regardless of quality, the two movies start making only bad movies.

The only way the two movie studios will start making good movies is if people stop going to see the bad movies.

A similar process has been at play with our two political parties. And, today, I see two presidential parties that make no effort to appeal to my interests and values and, instead, prefer the dark art of propaganda to make their candidates attractive to voters. The parties would rather put lipstick on pigs than modify their core ideas.

For my tastes, the two parties have been nominating gussied up pigs for decades and I’m tired of the farce— which today feels more like a straight up con job. Farces are at least entertaining.

So, President Trump and Mr. Biden, I’ve listened to your words and studied your policies, forgive me if I sit this one out.

• K.R.K.

Send comments to: kroeger98@yahoo.com or tweet me at: @KRobertKroeger1

By Kent R. Kroeger (Source: NuQum.com, May 25, 2020)

The analysis of stool samples is a vital screening method for medical conditions ranging from colorectal cancer, hookworm, rotaviruses, and lactose intolerance.

It seems only logical that the coronavirus (SARS-CoV-2) could also be detected in stool samples.

In Paris, France, researchers monitored genome unit levels of SARS-CoV-2 in waste waters between March 5 to April 23 to determine if variations over time tracked closely with COVID-19 cases observed in the Paris-area.

They did.

Though it has not been peer-reviewed, the researchers posted their preliminary study on May 6th:

“The viral genomes could be detected before the beginning of the exponential growth of the epidemic. As importantly, a marked decrease in the quantities of genomes units was observed concomitantly with the reduction in the number of new COVID-19 cases which was an expected consequence of the lockdown. As a conclusion, this work suggests that a quantitative monitoring of SARS-CoV-2 genomes in waste waters should bring important and additional information for an improved survey of SARS-CoV-2 circulation at the local or regional scale.”

If your reaction to this research is — “Aren’t we already doing this for other diseases and public health issues?” — you would be correct.

This type of real-time health monitoring method dates back at least to the 1990s when environmental scientists began to observe the presence of pharmaceuticals in local waste waters (including illicit drugs), according to Christian G. Daughton, a U.S. Environmental Protection Agency scientist.

First proposed in 2012, Daughton has been developing a bioanalytic method called Sewage Chemical-Information Mining (SCIM) in which sewage is monitored for natural and anthropogenic chemicals produced by everyday actions, activities and behaviors of humans. One variation of this method — BioSCIM — is described by Daughton as “an approach roughly analogous to a hypothetical community-wide collective clinical urinalysis, or to a hypothetical en masse human biomonitoring program.”

When implemented, a BioSCIM program will be able to track community-wide health trends on a continuous basis.

But Daughton is far from alone in proposing this type of sewage-based health monitoring.

“If you are at the mouth of a wastewater treatment plant, you essentially can observe all the chemistry that is being used in a city,” says Rolf Halden, director of the Center for Environmental Health Engineering at Arizona State University’s Biodesign Institute. “You can measure the metabolites that have migrated through a human body. You can look at medications that are being taken. In essence, you’re at a place where you can observe human health in real time.”

Though privacy advocates may have reservations about the government or corporate entities monitoring something so private as our bodily wastes (the ACLU has not returned my phone call on this issue), researchers say the way sewage-based monitoring systems are designed makes it impossible to link individuals — whose genetic identifiers are mixed amidst the metabolites of interest — to specific pharmaceuticals, behavioral by-products, health conditions, and/or diseases.

However, they could tell you what cities and neighborhoods index high on these things, and it is not hard to imagine law enforcement authorities finding a reason to plug into this information. Or national intelligence agencies, perhaps?

Think about it.

Given that SCIM and other community-level biomonitoring techniques are fairly well established, it is astonishing that there is no systematic effort by U.S. cities, counties, states or the national government to use this valid, reliable, and non-intrusive technique for tracking the spread of the coronavirus.

We know the widely reported COVID-19 case numbers in the U.S. and worldwide are inaccurate.

“Inadequate knowledge about the extent of the coronavirus disease 2019 (COVID-19) epidemic challenges public health response and planning,” according to USC public health researchers who recently released an April study on the seroprevalence of SARS-CoV-2 antibodies among adults in Los Angeles County, California. “Most reports of confirmed cases rely on polymerase chain reaction–based testing of symptomatic patients. These estimates of confirmed cases miss individuals who have recovered from infection,with mild or no symptoms, and individuals with symptoms who have not been tested due to limited availability of tests.”

“The number of confirmed COVID-19 cases is a poor proxy for the extent of infection in the community,” one of the study’s researchers, Neeraj Sood, told the USC online news site.

For five months now, on a daily basis, our governments and worldwide news agencies have been reporting inaccurate numbers that do not give an unbiased picture of the coronavirus pandemic. They are bean-counting and they don’t know where all the beans are or which ones to count.

It did not need to be this way. We should have been analyzing our pee and poop from the beginning.

(There was no nice way to say that.)

• K.R.K.

Send comments and stool samples to: kroeger98@yahoo.com or by tweet to: @KRobertKroeger1

By Kent R. Kroeger (Source NuQum.com, May 21, 2020)

 

By Kent R. Kroeger (Source: NuQum.com, May 18, 2020)

Social scientists have long recognized that humans have a psychological need to control their environment and individual perceptions of one’s ability to exert such control affects one’s sense of well-being and happiness.

On a macro-level, Anthropologist Leslie White once wrote that human cultural evolution is the “process of increasing control over the natural environment” through technological progress.

He even proposed a simple equation, known as White’s Energy Formula, to summarize his neoevolutionist view:

C = ET

where E is a measure of energy consumed per capita per year, T is the measure of efficiency of technical factors utilizing the energy and C represents the degree of cultural development.

The coronavirus (SARS-CoV-2) has shaken one of our most durable assumptions about human history: the near uninterrupted progress of human society over time.

Today, we live better than our parents, who lived better than their parents, who lived better than their parents…and on and on it goes.

If we view progress as our ability to produce greenhouse gases and consume heavily processed foodstuffs, we’re kickin’ it like never before. If we take a more comprehensive view of human happiness, however, the progress myth was never true.

As businessman Mark Cuban recently said: “I’m worth billions and I’m afraid to leave my damn house.” But that is just one manifestation of the coronavirus’ power over humans.

We live in the coronavirus’ world for now — and when will that end?

“The (corona)virus dictates the the timeline for lifting restrictions, not us,” said a New York epidemiologist on WNYC-FM last Friday.

Still, since the earliest stages of the COVID-19 pandemic, experts, bureaucrats, and politicians have hammered on the same basic message: We can control the coronavirus.

“We are not at the mercy of this virus,” said the WHO Director-General Tedros Adhanom Ghebreyesusat a March 9th media briefing. “All countries must aim to stop transmission and prevent the spread of COVID-19, whether they face no cases, sporadic cases, clusters or community transmission.”

The WHO Director followed up his press conference with a tweet:

At around the same time, Dr. Marc Lipsitch, a professor of epidemiology and director of the Center for Communicable Disease Dynamics at the Harvard T.H. Chan School of Public Health, wrote:

“The city of Wuhan, China, where Covid-19 started, waited weeks before acknowledging human-to-human transmission and taking measures to control it. Wuhan thus experienced an out-of-control epidemic that overwhelmed the health care system. The city felt these effects for weeks after intense control measures were in place, as newly infected people got sick and required care. Other cities in China watched Wuhan’s experience and imposed strict controls at a much earlier stage in their epidemic: They closed schools, sharply limited social contact, and traced and isolated cases and contacts. These early interventions dramatically slowed transmission. No other Chinese city has repeated Wuhan’s horrific experience so far.

These experiences…show that early and sustained imposition of measures to limit social contact will slow the epidemic. This is desirable for many reasons — fewer total people get infected in a slowly moving epidemic; those who do get infected do so later, on average, so doctors will have learned more about how to care for the illness, and antiviral drugs may even be available.

Most important in light of Wuhan’s crushing experience, a controlled epidemic has a lower peak, reducing the strain on health systems. From the perspective of disease control, every effort should be made, as soon as possible, to slow the spread of the virus and flatten the epidemic curve. If these interventions are not sustained, spread will resume, but every action to slow it buys us some time and probably reduces the total size of the outbreak.”

Within days of the WHO and Dr. Lipsitch statements — as well as from other public officials and epidemiologists around the world — the majority of the northern hemisphere rapidly implemented the core recommendations: (1) school and business closures, (2) lockdowns (‘shelter-in-place’), (3) travel restrictions, (4) social distancing requirements (e.g., masks, “the 6-feet rule”), (5) and the promulgation of stricter personal hygiene techniques (e.g., “20-second hand washing”).

Have these efforts worked? How would we know?

Is the U.S. (& the world) controlling the coronavirus (SARS-CoV-2)?

From the U.S. experience (so far), aggregated to the state-level, the data do not tell us which suppression and mitigation (S&M) efforts have been more effective than others.

Working against the data are numerous methodological issues: (1) states implementing multiple S&M techniques simultaneously (confounding factors), (2) vast majority of states (and all of the large, densely-populated states) implemented ‘shelter-in-place’ orders, though some states adopted this policy later than others (e.g., Texas, Florida, Oklahoma, Kansas), (3) significant variation between states in how otherwise similar S&M techniques were implemented, and, most importantly, (4) the pandemic is not over in the U.S. by any stretch of the imagination.

Adding to these complications is this fact: the COVID-19 pandemic has included more than one coronavirus, with at least one being more contagious than others.

According to a recently released Los Alamos National Laboratory study, a new (mutated) strain of the coronavirus has become dominant in Europe and the U.S. East Coast and is potentially more contagious than versions that dominated China and the U.S. West Coast during the early stages of the pandemic.

If true, how can we compare New York and California’s response to the coronavirus if they are dealing with fundamentally different viruses?

It makes the analysis difficult — but not impossible. Studies using probability-based sampling are already in the field throughout the U.S. and when their results are available, more sophisticated statistical controls will better facilitate such comparisons.

In the meantime, we have U.S. county-level data from Johns Hopkins University (CSSE), updated daily, which continues to suggest four state-level factors are correlated with the spread and lethality of the COVID-19 pandemic in the U.S.: (1) Population density, (2) Testing incidence, and (3) Travel restrictions, and (4) an indicator for West Coast states (CA, HI, OR, WA).

See Figures 1 and 2 for a path model (mediation) analysis of the spread and lethality of the coronavirus in the U.S. at the state-level (through May 15th).

While only a state’s population density (per sq. mile) is significantly correlated both directly and indirectly with the number of COVID-19 deaths (per 1 million people), the total effects are significant for all four factors.

Figure 1: Path model estimates for COVID-19 deaths per 1M (output) and COVID-19 cases per 1M (mediator) for the U.S. through May 15, 2020.

Figure 2: Path model estimates for COVID-19 deaths per 1M (output) and COVID-19 cases per 1M (mediator) for the U.S. through May 15, 2020.

While researchers note that population density alone cannot explain many of the differences in COVID-19 morbidity and mortality across the U.S. — for example, New York City and San Francisco are both densely populated but have significantly different morbidity and mortality rates — it is manifestly a major factor, if not the dominant factor.

As can be seen in Figures 3 and 4, the correlations of state-level population density and state-level COVID-19 case rates and fatality rates have increased over time, reaching in mid- to late-April an apparent threshold of 0.64 (Pearson coefficient) for cases and 0.72 for fatalities.

Figure 3: Correlation between COVID-19 cases (per 1M) and a state’s population density over time (U.S. state-level analysis; data through May 15, 2020).

Figure 4: Correlation between COVID-19 deaths (per 1M) and a state’s population density over time (U.S. state-level analysis; data through May 15, 2020).

To my eyes, this over-time convergence in the correlation coefficient for population density reminds me of how population parameter estimates in sample surveys converge as sample sizes increase.

As for the other variables in the path model, the significance of the West Coast-indicator confirms that something substantively different is happening in those states — be it the characteristics of the virus itself, the S&M policies of those states, or both.

Likewise, as has been the case since I first estimated models for U.S. state-level COVID-19 cases and deaths, those states that implemented internal travel restrictions on its citizens (AL, AZ, DE, FL, HI, ID, KS, KY, ME, MT, ND, NM, OK, RI, SC, TX, UT, VT, WV, WY) are experiencing significantly lower COVID-19 case incidences than other states, all else equal.

Overall, the path model explains about 75 percent of the state-level variance in COVID-19 case incidences and 85 percent of COVID-19 death incidences — all without any reference ‘shelter-in-place’ orders and their timing, which were found to be insignificant in this cross-sectional (i.e., one-point-in-time) analysis when included in the model.

Have the ‘Shelter-in-Place’ orders been ineffective? The state-level evidence is not clear on this question, though I feel some confidence in saying that broad, state-level “Shelter-in-Place’ orders have no statistically significant relationship with state-level case and fatality rates. Unless it is the location of a cluster outbreak, why should Wanakah, New York (Population 2,824) be under a state-ordered lockdown? I can’t find any justification in the data for such a policy.

But does that mean these orders didn’t help moderate the scale of the coronavirus pandemic? Absolutely not.

Imagine there is a parallel universe where New York didn’t institute a ‘Shelter-in-Place’ during the coronavirus pandemic. Do you think the end result would have been the same as in our universe? I don’t.

Unfortunately, we don’t have access to this parallel universe. We have only this one. And in this one New York suffered more than any other U.S. state during the coronavirus pandemic, even with a statewide shutdown.

But do not despair, the path model presented here offers strong evidence that states are far from powerless in addressing viral outbreaks, with testing rates being the most important controllable factor.

Still, the statistical evidence reminds that us that factors outside the control of political actors and subject-matter-experts — population density and a virus’ characteristics (contagiousness and lethality), including regional variations in those characteristics — explain a significant portion of state-level variances in case and fatality rates.

A state cannot easily control its population density or its location on a map and as this pandemic progresses over time, the impression I am left with is that states are becoming more similar, not different, in their COVID-19 case and fatality rates.

In other words, a state’s S&M strategies can definitely ‘flatten the curve,’ but these strategies may be more limited in their ability to change the eventual incidence rates in cases and fatalities.

Are we all going to end up like New York? Probably not, as we do have some control over the COVID-19 pandemic, though probably not as much as we want to believe. And when I say we, I mean our elected politicians.

Watching New York Governor Andrew Cuomo’s daily press conferences on the coronavirus remind me of Billy Crystal’s catch phrase when doing his Fernando Lamas imitation on Saturday Night Live: It is better to look good than to feel good. [An analogous axiom I learned while working in the Federal Government may also apply: It is more important to look busy than to be busy.]

Governor Cuomo sure looks like he knows what he’s doing about the coronavirus, but the reality for New Yorkers is far different.

New York nonetheless leads the country in the relative number of COVID-19 cases (1,458 per 1 million people) and deaths (18,522 per 1 million people) and only New Jersey appears close enough to challenge New York for those two ignominious titles.

In all fairness, New York has seen its number of new cases and fatalities drop dramatically in the past two weeks:

New York is among only six states to see its current 7-day moving average in new confirmed cases fall below 25 percent of its peak. New York’s 7-day moving average peak in cases was 9,909 per day (on April 10th). As of May 15th, New York’s current 7-day moving average is 2,201 per day. The other states under 25 percent of their peak are: Alaska, Hawaii, Idaho, Montana, and Vermont.

New York is also among seven states to see its current 7-day moving average in new deaths fall below 25 percent of its peak. In New York’s case, its 7-day moving average peak in deaths was 951 per day (on April 12th). As of May 15th, New York’s current 7-day moving average is 234 per day. The other states to share this honor with New York are: Alaska, Hawaii, Idaho, Montana, Vermont, and Wyoming.

Barring any major setbacks — which is possible given the virus might be in more control than we realize — New York is the only large-population state on those two lists. [Maybe I was too hard on Governor Cuomo earlier?]

Unfortunately, there is an equally long list of U.S. states that are currently at or near their peaks in COVID-19 cases and deaths (see Figures 5 and 6).

Figure 5: States at or near peak in new COVID-19 cases

Figure 6: States at or near peak in new COVID-19 deaths

Should the data make us optimistic or pessimistic?

Based on the data, I am promiscuous in my belief that the U.S. is on the downhill side of this first coronavirus wave (see Figure 7). As for future waves, there is no consensus among epidemiologists on the shape they will take, but there appears to be a consensus that they will occur.

“This virus is on its own time schedule,” according to University of Minnesota epidemiologist Michael Osterholm. “But we will have some tough months ahead.”

Figure 7: U.S. trend in new COVID-19 cases (as of May 18th)

Unfortunately, the worldwide trend in this first wave of COVID-19 cases is not declining (see Figure 8); but, it is a relatively flat curve, as opposed to a highly peaked one, suggesting mitigation and suppression efforts are working on some level.

Figure 8: Worldwide trend in new COVID-19 cases (as of May 18th)

My optimism also grows as we learn more and more about this virus, particularly about potentially controllable drivers of COVID-19 morbidity and mortality.

For example, a recent UK study found levels of Vitamin D in a population may affect how the coronavirus impacts a population.

“Vitamin D levels are severely low in the aging population especially in Spain, Italy and Switzerland. This is also the most vulnerable group of population for COVID-19,” concludes research conducted by Petre Cristian Ilie (The Queen Elizabeth Hospital Foundation Trust, King’s Lynn), Simina Stefanescu (University of East Anglia), and Lee Smith (Anglia Ruskin University). “We believe, that we can advise Vitamin D supplementation to protect against SARS-CoV2 infection.”

When this pandemic is finally over — and it will end, at the minimum when a reliable vaccine is available — epidemiologists will have the time to

What seems less debatable is whether we can control the coronavirus to our liking. That is not going to happen.

Says researchers at the University of Minnesota’s Center for Infectious Disease Research and Policy (CIDRAP) in their latest analysis of the COVID-19 pandemic:

“We must be prepared for at least another 18 to 24 months of significant COVID-19 activity, with hot spots popping up periodically in diverse geographic areas. As the pandemic wanes, it is likely that SARS-CoV-2 will continue to circulate in the human population and will synchronize to a seasonal pattern with diminished severity over time.”

In other words, the coronavirus remains in charge…until a vaccine is widely available.

• K.R.K.

For data and statistical code used in this analysis, send requests to: kroeger98@yahoo.com

 

By Kent R. Kroeger (Source: NuQum.com, May 13, 2020)

Along with Doomcock, ThatStarWarsGirl, and Geeks+Gamers, YouTube vlogger Nerdrotic (aka Gary Buechler) is a member of the Praetorian Guard for George Lucas’ Star Wars franchise.

Though frequently mocked by the corporate-controlled entertainment media for their religious-like devotion to the Stars Wars myth, Star Wars is not their religion, it is their hobby.

Granted, they use religious terms like ‘canon’ to frame their critiques of how The Disney Company has fundamentally altered the Star Wars myth, but they do so to contextualize their uniformly negative reaction to the Disney Star Wars trilogy that was recently concluded with 2019’s release of The Rise of Skywalker.

They are fans of the Star Wars franchise. No more, no less.

The point of deepest contention between Disney Star Wars critics — sometimes called the Fandom Menace — and the mainstream entertainment media hinges on whether Disney should have respected Star Wars canon (i.e., historical precedent) when producing the trilogy and standalone movies (Rogue One, Solo).

“There has to be a basic foundation,” Buechler said in a recent live broadcast on YouTube. “(For Star Wars) Luke Skywalker was the hero that threw away his light saber to save his father (Darth Vader). He wasn’t going to go to the dark side. That was Luke Skywalker. ”

In contrast, Buechler considers the Disney trilogy’s rendering of Luke Skywalker as unrecognizable to the original character: “Luke Skywalker is not the one (in the Disney trilogy) who had a bad dream and was going to kill his nephew. His sister’s son. His best friend’s son.”

Buechler admits Lucasfilm head Kathleen Kennedy, and The Force Awakens/Rise of Skywalker director J. J. Abrams aren’t required to honor the fans, but if they want those fans to reliably show up for the Disney Star Wars projects, “they need to respect the love people had for that franchise.”

Unfortunately, says Buechler, the Disney people in charge of Star Wars have not demonstrated that respect.

Jeffrey Riley, a Nerdrotic YouTube follower, perhaps put it best: “​Canon is history. If content loses its history, it stops existing.”

And how has Disney responded to these criticisms from fans? “Too bad, so sad,” seems to be their collective reply.

Matt Martin, a member of the Lucasfilm Story Group and creative executive for the animated Star Wars series Rebels, says of critics like Nerdrotic: “Canon is all fake anyway.”

If by ‘fake’ Martin means ‘fiction,’ there is no argument. Star Wars fans don’t consider the original Lucas-produced trilogy movies to be documentaries. They know these movies are science fiction.

Their message to Disney, instead, is that — as fans — they no longer recognize the Star Wars story line; and if Disney had wanted them to turn out in large numbers for the Disney trilogy movies, they would have considered the opinions of the Star Wars fan base.

For example, Han Solo’s unheroic death at the end of “The Force Awakens” represented the tipping point for me and Disney Star Wars movies.

Han Solo deserved better. And Star Wars stopped being fun.

However, for other Star Wars fans I’ve met who say they are done with Disney Star Wars, the cause of their divorce runs the gamut from Han Solo’s ignominious demise in The Force Awakens, Luke Skywalker’s minor role in all three Disney trilogy movies, General Leia Organa’s demonstration of a previously unknown Jedi ability to fly in space without a spacesuit, to the use of light-speed in The Last Jedi to destroy the First Order’s Star Dreadnought.

Star Wars creator George Lucas has publicly complimented The Last Jedi’s director Rian Johnson for taking chances with the Jedi myth. Speaking on his behalf, director and close Lucas friend Ron Howard says, “He’s all for the galaxy expanding and experimenting. That’s what he prefers the most.”

‘Expanding and experimenting’ is one thing; taking a blow torch to the most basic precepts of the Star Wars mythology is an entirely different matter. Not even Lucas can get away with that in the eyes of some fans.

Feel free to mock Star Wars fans for caring about ‘fake’ canon, but if Disney is still a for-profit business — and Disney’s stockholders assume the company is — they should have done a better job understanding the core Star Wars fandom even if they didn’t want to cater exclusively to their desires and expectations.

Henry Ford famously said: “If I had asked people what they wanted, they would have said faster horses.” Kathleen Kennedy probably has a similar quote.

Where did Disney go wrong with their Star Wars trilogy?

A minor dispute among Star Wars fans has developed over when and how the world’s most lucrative science fiction movie franchise started its slide. Was it by Rian Johnson’s canon-mocking The Last Jedi? Was it J. J. Abrams’ The Force Awakens? Was it the last movie in the trilogy — The Rise of Skywalker — that placed the Star Wars franchise on life support? Or did the Lucas-produced prequels deliver the decisive blow long before Disney acquired the franchise?

While I can’t prove how the Star Wars franchise was damaged, I’m confident I know when it happened (see Figure 1): The Force Awakens caused Disney’s Star Wars troubles, not the more reviled Last Jedi.

Worldwide Google searches on the term ‘Star Wars’ have followed a predictable pattern since 2004 (the first year Google search data is available). In the month of a Star Wars movie premiere, Google searches spike, and then fall off until the next Star Wars movie (or until the next May the Fourth Be With You).

The assumption underlying my conclusion is that Google searches are a reliable and valid proxy for assessing public interest in media properties such as Star Wars. There is empirical evidence to support this assumption.

Figure 1: Worldwide Google searches on ‘Star Wars’ from 2004 to present

Had 2005’s Revenge of the Sith inflicted major damage to the Star Wars franchise, we would have expected the next Star Wars film (2016’s The Force Awakens) to have relatively deflated Google search totals. To the contrary, worldwide interest in Star Wars peaked leading into the release of The Force Awakens.

Revenge of the Sith is no longer a suspect, but what about The Force Awakens? — generally considered the best of the Disney trilogy movies (receiving a 93 critics rating on Rotten Tomatoes).

If we set 2016’s Rogue One aside as a unique case (it was a standalone Star Wars movie), and focus on the second Disney trilogy movie — The Last Jedi — the impact of The Force Awakens becomes apparent. Worldwide Google search interest in ‘Star Wars’ fell 55 Google Index points (where an index score of 100 represents the month with the most Google search interest in Star Wars).

Why?

Buechler theorizes Abrams’ unflattering deconstruction of the original saga’s protagonist — Luke Skywalker — and transforming Han Solo from a competent, space-savvy smuggler into a depressed, divorced dad did the critical damage.

Other Star Wars vloggers such as Doomcock have suggested the Disney saga protagonist — Rey — never became a fully-developed character on Luke’s level.

Regardless, the key point in Figure 1 is that blaming Star Wars’ decline on the visually impressive, but storytelling monstrosity — The Last Jedi — is misplaced. By the time of The Rise of Skywalker, public interest in Star Wars was 60 Google Trends Index points below the similar period leading into The Force Awakens. Whatever the cause, Disney squandered their $4 billion Star Wars investment with a series of trilogy movies that alienated preexisting fans and created few new ones.

That is a recipe for a brand management disaster.

Fear not Star Wars fans. The franchise is wounded, not dead.

If I seem pessimistic about the future of Star Wars, let me share two reasons why Star Wars fans should remain optimistic: (1) Other popular culture franchises have survived mediocre middle acts, and (2) the world still thinks and writes about Star Wars more than any other science fiction movie franchise.

On the first point, the Tom Cruise-produced Mission: Impossible movie series suffered a mid-season slump only to come back stronger than ever. After two profitable, if unspectacular movies at the series start (released in the Summers of 1996 and 2000), the third Mission: Impossible installment (directed by J. J. Abrams oddly enough — Is there a pattern forming in his career?) was met with critical but not financial success (see Figure 2).

In the aftermath of Mission: Impossible 3, the franchise’s lowest grossing movie, Paramount Pictures could have easily pulled the plug on any future Mission: Impossible movies. The series seemed to have run its course.

Instead, Cruise brought in a new creative team (director Brad Bird and writers Josh Appelbaum and André Nemec) and released Mission: Impossible: Ghost Protocol in the Summer of 2006 to wide critical praise and strong box office numbers. The two subsequent movies (Rogue Nation and Fallout) have been similarly successful and two more sequels are planned for release in 2021 and 2022. [Is there a harder working person in Hollywood than Tom Cruise?]

Figure 2: Mission: Impossible box office and production costs

The sustained success of the Mission: Impossible franchise can also be seen in Google search data (see Figure 3). From a Google Trends Index score of 55 in April 2006 (Mission: Impossible 3), the three subsequent releases have witnessed peak Google Trends Index scores of 78 (Ghost Protocol), 100 (Rogue Nation) and 88 (Fallout), respectively. Fallout’s figure, however, is deceiving as its spike in Google searches covered a two-month period (instead of one as for the other Mission: Impossible movies). Fallout is the highest grossing Mission: Impossible movie to date.

Figure 3: Google Search Interest in ‘Mission: Impossible’ (US, 2004 to present)

“All franchises have their implausibilities, whether it’s Transformers’ sentient cars or the Fast and Furious’ sentient Vin Diesels. But only the Mission: Impossible franchise has gotten better reviews with every installment, climbing its way up the Rotten Tomatoes rankings as though wearing electromagnetic gloves,” says Cruise biographer Amy Nicholson.

What has sustained Mission: Impossible’s success? Strong creative leadership from the producer/actor (Tom Cruise), screenwriters, and various directors utilized during the six-movie franchise.

Lucasfilm and Disney Strong creative leadership on the top-side has not been the case for the Disney Star Wars saga. But there is no reason why it couldn’t be going forward.

What should maintain Disney’s optimism is that the Star Wars franchise remains among the most talked about in all of popular culture. While Star Wars may have been surpassed in total box office by the Marvel Comics Universe movies, it is still a heavyweight among science fiction movie franchises when it comes to worldwide public interest (see Figure 4).

Figure 4: Comparing Google Search Interest Across Science Fiction Franchises (Worldwide, 2004 to present)

Since 2004, Star Wars claims four of the Top 5 monthly Google Trends Index scores. The Marvel Comics Universe has the fifth ranked month (when Avengers: Endgame was released in April 2019).

Disney would obviously trade their high Google Trends Index scores for Endgame’s worldwide gross receipts. But Google searches do represent something tangible — public interest — and to this day Star Wars maintains a large reservoir of that across the globe.

The modest success of the Disney+Mandalorian series, a sparse story about a lone bounty hunter in the outer reaches of the galaxy, far from the authority of the New Republic, who takes on the responsibility of protecting a child of Yoda’s species in a post-Battle of Endor galaxy.

Star Wars fans will show up if you give them a good reason.

No, Star Wars is not dead. It isn’t even dying. But it is ill.

• K.R.K.

Send comments to: kroeger98@yahoo.com

By Kent R. Kroeger (Source: NuQum.com, May 10, 2020)

One of my first market research jobs was at HBO (New York) in the late-1990s. About two months into the job, a personal assistant to HBO CEO Jeff Bewkes asked me to attend a 4 p.m. executive meeting.

At the time, I was heading the subscription cable network’s yet-to-be-launched “HBO-on-Demand” service and had been verbally abused that morning by the network’s chief financial officer for inconsistencies in my 5-year budget proposal.

The CFO hated subtotals that didn’t add up as much as I hated making them.

As I assumed the 4 p.m. meeting with Mr. Bewkes was to fire me, my office neighbor reminded me that Mr. Bewkes would never lower himself to fire someone at my level.

Typically at HBO firings at my level would consist of a security guard informing you of your termination and then escorting you out of the building. To the extent you saw anyone else, it would be colleagues diving back into their offices as you walk your box full of desk toys and family pictures to the elevator.

After some encouragement from colleagues, my optimism started to rise, though the morning’s tongue-lashing from the network’s second most powerful person was still fresh in my mind.

I don’t remember much about Mr. Bewkes’ office except that it was large, had an dark lacquered desk, and a nice view of Manhattan’s Bryant Park.

I also remember the chair I sat in, as it put me about a foot below Mr. Bewkes eye line and every time I shifted my butt, the leather seat would make a sticky squeak sound. Since I tend to shift a lot (adult ADHD), the noise annoyed everyone in the room, including myself.

After a few small-talk niceties between myself and the three or four other people in the room, none of whom were the CFO (thank God), Mr. Bewkes turned to me to explain why I was there.

“Kent, I appreciate the work you are doing on our on-demand service. I just wanted to get the senior people together who will be working with you on getting it up and running.”

It was a nice introduction.

What Mr. Bewkes said next I have never forgotten.

“I am told you have a market research background and that is exactly the type of person we want launching this new service. For HBO-on-Demand to be successful — and this is true for any media service — you must know and respect your core audience.”

And I did know HBO’s core audience: Young, educated, upwardly mobile professionals.

“I’m HBO’s core audience,” I said.

Mr. Bewkes’ immediate smile sent a jet stream of adrenaline into my system. I was going to nail this meeting. God yes. Director of HBO-on-Demand today. CEO of Time-Warner-Europe by Arbor Day!

“Good. Good,” he shot back.

Good? How about great!? (I didn’t say that, of course.)

Mr. Bewkes leaned back in his chair and paused for a moment. “How long have you been an HBO subscriber?”

Uh oh.

The truth was, at the time, only twice in my life did I have HBO service. The first was as a teenager when I hacked into my neighborhood’s cable TV hub and pirated the service for about a year. The second time was Spring 1997 when I moved into a New Jersey apartment and the service had been paid for through the year by the previous tenant.

Yep. I could feel the swamp water rising above my ankles.

“Since I was a teenager,” was my answer followed by some butt shifting, with accompanying sticky squeaks. “With maybe a couple of service breaks here or there.”

Good lesson in life: When anyone uses the word ‘maybe,’ it often means they are about to throw up a verbal smoke screen.

I prayed Mr. Bewkes’ inquisition about my subscription habits was over.

It wasn’t.

“I believe that if you don’t love the product you sell, you’re in the wrong business,” he said.

That makes sense. Let’s talk about HBO-on-Demand now, I thought to myself.

Mr. Bewkes, still leaning back in his chair, drew wry smile across his lips and asked, “What’s your favorite HBO show?”

My confidence made one final appearance that day. I knew the best answer to his question. It was the show Mr. Bewkes’ launched during his tenure at HBO — the show that heralded the subscription service’s move away from carrying only theatrical movies to providing exclusive, HBO-produced content.

“The Sopranos, of course.”

The Sopranos made Jeff Bewkes one of the most coveted media executives in New York at the time.

It may have been the best answer, but it wasn’t a truthful answer. I had never watched a complete episode of The Sopranos in my life. It was another trendy East Coast show not targeted to people from Iowa who listen to Kansas and the Dave Matthews Band and consider dinner at The Olive Garden or Red Lobster a nice night out.

“Don’t worry, this is not a test.”

But, of course, that is what someone says right before they give you…a test.

Mr. Bewkes turned to the other executives in the room: “I like focus groups. They don’t give you hard numbers, but they give you insights you can only gain from listening to people and seeing their eyes; you get a better perspective.”

Oh, crap.

Mr. Bewkes turned his gaze back to me: “Any favorite Sopranos character?”

Double crap.

“Tony and Big Pussy,” came out of my mouth as if by divine intervention.

Phew! Nailed it again. But please God, let the questions end, I thought.

“A favorite episode?”

OK, I was cooked.

More butt squirming. More sticky squeaking.

“I can’t come up with one right at the moment,” Even more butt shifting. And more glances between Mr. Bewkes and the other executives — but no wry smiling this time.

I will always be grateful to Mr. Bewkes for not going for the kill shot. He knew I was feeding him bull crap. Another butt-kissing young executive. But he had the decency to leave me with at least some thin slice of dignity. Not a lot — an earlobe’s worth.

I worked at HBO for about two more months.

What is the point of this story? I had two takeaways: (1) Don’t feed people verbal crap, and (2) know and respect your core audience.

I don’t follow Lesson 1 very well, but Lesson 2 has been my market research mantra ever since — and particularly useful in political polling research.

Mr. Bewkes understood the basic tenet of marketing: Know your customer.

Indeed, experiences after HBO caused me to augment Mr. Bewkes’ original maxim to include this simple rule: If you want to alter your product so you can expand or change your customer base, give your current core audience a reason to follow. Many won’t, but the more that do, the more likely your product’s new direction will succeed.

This isn’t rocket science — it should be common sense, you would think.

A female-centric Star Wars TV series?

The loosely organized internet mob, self-labeled The Fandom Menace, came out in full force in this past two weeks over a news story that Lucasfilm, headed by Kathleen Kennedy, was going to executive produce a ‘female-centric’ Stars Wars TV series.

Joe Otterson, who broke the story for Variety, reported that Leslye Headland — co-creator of the Netflix series Russian Doll, recently renewed for a second season — will be the showrunner for a new Star Wars series on Disney Plus.

The exact plot of this new series is not known other than it will be female-centered and occur in a different time period than the other Disney Star Wars projects.

The Fandom Menace on YouTube and Twitter quickly ambushed Disney and Kennedy, none more ferociously than the YouTube vlogger Doomcock — future ruler of Earth:

“In light of Hollywood going bankrupt, Disney fighting for its life, and theater chains going under, I thought Hollywood was going to pull its head out of its ass and actually get back to just making entertainment that people want to see. Apparently not. Hollywood hasn’t learned a damn thing…

They (Disney) have picked the wrong person to do this show and I’m not saying that lightly. (Headland) is a social justice warrior typhoon five on the sphincter scale…

(Kathleen Kennedy), you’re gonna turn away from the lesson that the Mandalorian should have taught you — that, when you make even a mediocre series like the Mandalorian, fans will forgive you and watch — and now you’re going to develop an explicitly female-centric series for Disney Plus…

Kathleen Kennedy strikes again. (She) is ramming her agenda down the throats of fans and she’s recruited the social justice warrior equivalent of General Patton to run an entire armored division of woke right down our throats.

I thought Disney was fighting for its life, not trying to take its own life?”

Legions of other Star Wars fans on social media (Nerdrotic, ThatStarWarsGirl, Geeks + Gamers) have voiced similar complaints about this new Star Wars series.

In general, while puzzled why Disney needs another ‘female-centric’ Star Wars project — wasn’t that what the new Disney Star Wars trilogy was all about? — the Fandom’s complaints are more focused on why Kennedy continues to green-light new Star Wars projects despite being responsible for the Disney trilogy debacle.

The capstone to the Disney trilogy — The Rise of Skywalker — was a Frankenstein’s monster of a movie, stitched together so poorly even its director, J. J. Abrams had to confess the negative reviews had merit.

Visit the toy section in your local Target store. Disney Star Wars figurines and toys are sitting on the shelf: Untouched. Unloved. Unpurchased.

In a recent interview with Rebelscum.com, Chuck Terceira, President of Diamond Select Toys, a high-end collectibles manufacturer specializing in pop culture properties, said, “The overall demand for busts and Star Wars products is not what it was 10 or even 5 years ago.”

An interesting statement given that the start of the Disney Star Wars trilogy five years ago should have caused an explosion in demand for such collectibles.

There is an EF5-level storm in the science fiction franchise world right now. The most iconic franchises — Star Wars, Star Trek, Doctor Who — are genuinely at risk of being shelved.

Less iconic science fiction franchises have already met their end: The Terminator, Alien, The Transformers. [In the latter case, we are grateful.]

I don’t expect to see a new Superman movie in my lifetime.

With the exception of the Marvel Comics Universe (MCU) — which has the good problem of trying to match the success of its first phase movies which ended with the multi-billion dollar successes of Avengers: Infinity War and Avengers: Endgame — the other Sci-Fi franchises are struggling.

Why?

I don’t have the answer.

But I can show you the problem using worldwide Google search data obtained through Google Trends.

In the digital age, people can show interest in movie franchises in different ways. There are the traditional ways: go to a movie theater, buy a toy, watch a movie on TV. And there are new ways: Watch a movie on Netflix or some other premium service, download it from a file-sharing website, or stream it on your smartphone. And interest can also be shown simply by searching the internet for information about your favorite movie or franchise.

Google, of course, saves this information in the aggregate and offers it (for free) through Google Trends and other big data services they’ve developed (Google Ngrams is a personal favorite).

As for Google Trends, it has proven to be a valid and reliable data source for economic and social trend forecasters.

And it is the data service I recently used to plot public interest in the following Sci-Fi franchises since 2004: Star Wars, Star Trek, Doctor Who, and the Marvel Comics (which I include for comparison purposes).

The results are not good news. All three of these science fiction franchises — Star Wars, Star Trek, and Doctor Who — are dying from self-inflicted wounds.

But don’t take my word for it. Look at the Google Trends data on the search habits of people worldwide regarding these franchises.

It’s not a happy story.

Google Trends for Star Wars, Star Trek, and Doctor Who (as well as Marvel Comics)

Let us start by describing what a healthy movie franchise looks like based on Google search behaviors, and the best comparison is the Marvel Comics Universe (MCU).

Figure 1 shows worldwide Google search behavior since 2004 on the word ‘Marvel’ using the Google Trends Index which ranges from 0 to 100, where 100 equals the monthly maximum across the analytic time period (Jan 2004 to May 2020). For example, searches on ‘Marvel’ reached a 16-year maximum in April 2019, the month the movie Avengers: Endgame was released. The next highest month for searches on “Marvel” was April 2018, the month Avengers: Infinity War was released.

Figure 1: Google search interest in Marvel Comics (Worldwide, 2004 to present)

The key pattern in worldwide searches on “Marvel” is that they spike with each subsequent MCU movie release, starting with Iron Man in May 2008 through Avengers: Endgame. More importantly, and what distinguishes the MCU as a successful movie franchise, is that with each new MCU movie release, the level of “Marvel” searches increased over the previous movie release. The “peaks” in public interest for “Marvel” rise monotonically over time (i.e., never decreases).

In other words, Disney’s MCU franchise built fan interest and momentum over the course of MCU’s Phase 1 movie catalogue. That is what a successful movie franchise looks like; and while Figure 1 only tracks Google search behavior, this measure correlates strongly with the MCU movie worldwide box office receipts, as displayed in Figure 2.

Figure 2: Relationship between MCU Worldwide Box Office and Google Searches (Jan 2004 to May 2020)

Just in the core MCU movies alone, the MCU has grossed over $12 billion $US, unadjusted for inflation) for Disney/Marvel. Adding in the other MCU origin story movies and their sequels (e.g., Black Panther, Thor, Thor: The Dark World), the MCU catalogue has grossed over $22 billion worldwide. Compare that to the Star Wars movies which have grossed a healthy, but not MCU-level, $10.3 billion worldwide. And Star Wars isn’t even number two all-time — that honor belongs to the 12 Harry Potter movies at $9.2 billion in worldwide movie receipts.

STAR WARS

The MCU is the gold standard for movie franchises, an honor formally belonging to George Lucas’ Star Wars franchise.

To someone like myself, who in June 1977 caught pneumonia standing overnight in line at the Strand Theater so I could be among the first of my friends to see Star Wars (now titled Star Wars: A New Hope), relinquishing the box office title to the MCU has not been easy. But, as The Killers song says, “This is the world we live in.”

Further distressing for Star Wars fans like myself has been the letdown of the Kennedy-produced Disney trilogy movies. There was so much hope among fans in December 2015 just before the release of Star Wars: The Force Awakens (helmed by J. J. Abrams).

The MCU was going to get some real competition from a new Star Wars saga (granted, both franchises are controlled by Disney, rendering a large element of the competition basically meaningless).

Figure 3 shows worldwide Google search interest for the term ‘Star Wars’ from 2004 to May 2020. The high point was December 2015 — which was a 9 percent increase over public interest during the month Star Wars: Revenge of the Sith was released (May 2005).

However, instead of generating interest in the Disney trilogy over time, Disney deflated it with The Force Awakens. Compared to the interest prior to The Force Awakens, interest in ‘Star Wars’ fell 76 percent leading into The Last Jedi and 86 percent prior to the release of The Rise of Skywalker.

Figure 3: Google search interest in Star Wars (Worldwide, 2004 to present)

Wait, wasn’t it The Last Jedi that disappointed fans, not Force Awakens?

No.

The Google search data is uncompromising and clear: The Force Awakens killed public interest in Star Wars, not The Last Jedi. If The Last Jedi had been the culprit, the public interest spike in Star Wars leading into The Last Jedi would have been comparable to The Force Awakens. It was not even close.

Killing Han Solo as ignominiously as J. J. Abrams did and then marginalizing the Star Wars saga’s most important character — Luke Skywalker — was destined to anger Star Wars’ core audience. Why would Disney think otherwise?

Granted, Carrie Fisher’s death in December 2016 and the Last Jedi script leaks may have contributed to some softening in public interest in The Last Jedi, but those events are not comparable to the impact of a Star Wars movie itself.

The Force Awakens did the most damage to the Star Wars franchise.

As for the other two science fiction franchises I investigated in Google Trends — Star Trek and Doctor Who — they have witnessed similar declines in public interest.

In contrast to Star Wars and the MCU, I’ve limited my Google Trends analysis for Star Trek to the U.S and for Doctor Who to the U.K. as their fan bases have been mostly concentrated in the domestic markets of their origin.

We’ll start with Star Trek…

STAR TREK

Between 2004 and today, Google search interest in Star Trek peaked when the J. J. Abrams-helmed reboot of Star Trek debuted in May 2009 (see Figure 4). But, since the reboot, interest in Star Trek has been in a consistent decline — 38 percent lower for 2013’s Star Trek: Into Darkness and 63 percent lower for 2016’s Star Trek: Beyond.

Figure 4: Google search interest in Star Trek (US, 2004 to present)

If you include the two CBS-produced Star Trek TV shows — Discovery and Picard — the downward “trend in peaks” for Star Trek has been steeper than for Star Wars, going from 100 on the Google Trends Index for the Star Trek reboot movie down to 19 for Picard.

Though the Google Trends data tells us little about why interest in Star Trek has declined, Star Trek fans on social media, especially those partial to the Prime timeline (i.e., The Original Series and The Next Generation) over the Kelvin timeline (started by J. J. Abrams’ Star Trek), are not reluctant to share their theories:

These complaints aren’t proof of anything but they capture the general sentiment I’ve seen and heard elsewhere across social media from the most vocal elements of the Star Trek fan base.

That overt sexist, racist and homophobic tirades are occasionally mixed in among otherwise cogent criticisms of the recent Star Trek projects should not detract from the more thoughtful Star Trek fans. It is an unfortunate feature of our social media ecosystem, but hardly the dominate one.

DOCTOR WHO

The last science fiction franchise I investigated was U.K.’s Doctor Who, a long-running TV series that ran from 1963 to 1989 in its first iteration, and then re-started in 2005.

For those unfamiliar, Doctor Who chronicles a time lord called “the Doctor” who travels through time in a space craft called the TARDIS — which looks like a blue British police box. One unique feature of the show is that the lead actor playing “the Doctor” changes whenever the time lord undergoes a “regeneration.” The result is that there have been 13 “Doctors” since the series started, 12 having been played by men, and the most recent being played by a woman, Jodi Whittaker.

Its hard to generalize every Doctor Who episode down to one sentence, but it might go something like this: “The Doctor,” a time lord, is accompanied by one or more human companions as they combat various alien foes in an effort to help people in need or to save past, present or future civilizations.

While I would characterize most Doctor Who shows as more lighthearted and cheeky than serious, some of the best episodes, particularly those when “the Doctor” says goodbye to a companion (or vice versa), can be profound and genuinely heart-breaking.

In other words, the show is very British: Smart. Sharply-written. Well-acted. And moves fluidly between humor and drama.

It is my favorite science fiction franchise. But I am fearful the show will not survive under its current writer (showrunner) Chris Chibnall.

We are fortunate that Google Trends goes back before 2005, the year of the Doctor Who reboot, so we can see the initial UK interest in the Doctor Who reboot (starring the underappreciated 9th Doctor Christopher Eccleston) through to the 13th Doctor (played by Whittaker).

Figure 5 reveals a number of interesting features of Doctor Who interest levels in the UK since 2004. First, interest in Doctor Who leading into the March 2005 reboot was relatively high (Google Trends Index =48) and grew with each new season’s final episode (i.e., “a rising trend in peaks”), climaxing in June 2008 with the Russell T. Davies-penned episode, “Journey’s End” — an episode marking final regular appearance of the Doctor’s very popular companion Donna Noble.

Figure 5: Google search interest in Doctor Who (UK, 2004 to present)

The revival of Doctor Who under Davies’ creative leadership is a textbook example of how to (re)build a science fiction franchise — superior writing, extremely likable actors, and respect for the long time Doctor Who fans who generated the initial excitement prior to the March 2005 reboot. “Know and respect your audience.”

That doesn’t mean a franchise can’t innovate and even violate previously established “canon,” as Davies did when the 10th Doctor short-circuited a regeneration process in order to create a clone of himself.

The problem for the Doctor Who franchise appears to have started following the transition from the 11th Doctor (played by Matt Smith) to the 12th Doctor (played by Peter Capaldi). During Matt Smith’s tenure as the Doctor, Google search interest peaked in November 2013 with the episode “The Day of the Doctor” in which David Tennant, reprising his role as the 10th Doctor, appeared along with the 11th Doctor.

In terms of public interest in the UK, the premiere of the first female “Doctor” (Whittaker) exceeded that of the March 2005 reboot, achieving a Google Trends Index score of 58. Unfortunately, its been downhill from there for Doctor Who and showrunner Chibnall. The last season ending special (December 2019) achieved a Google Trends Index score of 30, the lowest of any season ending Doctor Who episode.

What happened?

I think the best explanations of Doctor Who’s current death spiral comes from those defending the Chibnall-era shows:

I suspect “Steve” is not a Doctor Who fan. Prior to Chibnall, Doctor Who was not political, even as its core theme has always been the defense of the defenseless and dispossessed. That is not a “liberal” agenda, even if “liberals” think it is.

Pre-Chibnall Doctor Who avoided politics for the most part — and in the era of hyper-partisan, that doesn’t seem like a bad idea if you want to build a large audience. The MCU would not be as popular as it is had it decided to use its movie franchise to preach about border walls, privilege and the patriarchy. [Yes, I know Tony Stark, aka Iron Man, supported an Earth shield to protect us from hostile aliens and Captain America didn’t. That issue occupied maybe 10 minutes of a 22-movie franchise.]

The extent to which hot-button issues like racism or sexism were ever addressed on pre-Chibnall Doctor Who, it was done irregularly, and when addressed, done well. That is in stark contrast to the kitschy, two-dimensional way Chibnall handled the 13th Doctor’s Rosa Parks episode (“Rosa,” airing October 2018). If you want to see a superior time treatment of Rosa Parks’ historical significance by a science fiction show, watch the Quantum Leap episode “The Color of Truth — August 8, 1955.” [And I’m not a fan of Quantum Leap.]

‘Wokeness’ seems to inspire bad writing and I wonder why. Perhaps because, nowadays, it is too easy get such scripts approved or through the creative process without significant editing? I do not know.

All I know is that in the case of the three science fiction franchises I value the most — Star Wars, Star Trek, and Doctor Who — ‘wokeness’ is turning off their core audiences in droves. And, no, these franchise defectors are not all Donald Trump supporters.

Know and respect your audience

Jeff Bewkes didn’t invent the ‘know-your-audience’ principle. Its pretty rudimentary to any understanding of business marketing. But sometimes the easy lessons are the hardest to internalize and sustain. Our lives all tend towards complication, not simplicity.

And, in taking over the Star Wars franchise, Disney and Kathleen Kennedy committed the worst blunder of all: they alienated their core audience with a story line that was never going to attract a new audience. They killed Han Solo (who was a shell of his old-self) in the least heroic way possible — as a depressed, divorced dad. They took the franchise’s protagonist — Luke Skywalker, the courageous hero of the whole Lucas-inspired saga — and turned him into a feckless nag with not even the courage to help his sister Leia fight off the new looming menace, the First Order.

And they were going to make Leia, not Luke, the true hero of the Skywalker saga? When (God rest her soul) Carrie Fisher was is no condition to carry the Star Wars franchise in this new direction. Kathleen Kennedy and J. J. Abrams had to know that.

Disney seemed to be begging long time Star Wars fans not to show up for the new trilogy.

A friend recently described first generation Star Wars fans as “50- and 60-something divorced men who say ‘got’ a lot and still call flight attendants ‘stewardesses.’ Kennedy was never going to make a movie for them.

The trouble with that thinking is its inaccuracy. Star Wars fans, like science fiction fans, are misunderstood. They are mainstream entertainment consumers — a multi-billion dollar consumer segment split evenly between men and women and drawn from all age, income and racial/ethnic categories.

An entirely new generation of fans, whose first contact with Star Wars was the animated series Star Wars: The Clone Wars or the Lucas-produced prequel movies, now attend fan conventions in near equal numbers to the first generation fans.

In a 2014 survey of science fiction convention attendees, a subset of science fiction movie fans, the gender breakdown overall was 54 percent male to 46 percent female, but almost even for fans age 30 or under.

Science fiction is mainstream, which is why I understand Kathleen Kennedy and Leslye Headland’s belief that they can create a successful female-centric Star Wars series. There is a potential audience for such a show.

I just don’t believe Kennedy, Headland, or corporate Disney, based on how they butchered the Skywalker saga, have a bloody clue how to do it.

But I also believe Disney will find a way to revive their $4 billion dollar initial investment in Star Wars. Disney always finds a way. Disney marketing since Steamboat Willie has perfected the art of bludgeoning us to the point where we can’t get enough of Disney’s homogenized, entertainment caboodle.

Unfortunately, the other two Sci-Fi franchises — Star Trek and Doctor Who — are dead men walking.

They had great runs, but as George Harrison once sang, all things must pass.

My personal view on why these Sci-Fi franchises are teetering

My first science fiction loves were the British series Doctor Who (introduced to me when Tom Baker played the fourth doctor in the mid-70s and early-80s) and Star Trek (The Original Series).

If things look bleak for Star Wars (though I believe Star Wars will rise again, despite the mediocrity dominating the Disney output so far), the prospects for the Star Trek and Doctor Who franchises are even grimmer.

In both cases, TV ratings for their newest iterations are at or near historic lows, leading some long time fans to also point fingers at the showrunners and executive producers of these franchises for forcing their political agendas into show scripts, instead of good, solid science fiction stories.

In the case of Doctor Who, the thirteenth and latest doctor, Jodi Whittaker, is the first female doctor, which was largely met with positive reactions from fans. Not sitting well with many Doctor Who fans (including myself), however, is the writing that has dominated Chris Chibnall’s two-year tenure as the showrunner (and he’s slated to return for a third). Where once Doctor Who episodes emphasized the science in science fiction (often dealing with time travel), the Chibnall produced shows descend into didactic, high school civics class-level moralizing.

Star Trek has suffered a similar fate under the leadership of CBS TV Studio’s Alex Kurtzman. Where Star Trek creator Gene Roddenberry evoked an optimistic, inclusive image of our future, the newest Star Trek properties paint a bleak future. If the Road Warrior and Logan had a baby, it would be Star Trek: Picard. [That isn’t a fair characterization. Road Warrior and Logan are two of my favorite dystopian-genre movies of all time. Those are great movies. Picard is not a great TV show — just a dispiriting one.]

And then there is the colossus of science fiction movie franchises — Star Wars.

George Lucas changed fundamentally what movies are made and how they are made. Hence, the franchise’s possible demise may do the same.

When a movie like The Rise of Skywalker can cost up to $300 million to make and still be considered a “failure” after grossing over $1.3 billion worldwide, you know there is a structural problem in Hollywood.

I also believe that computer-generated-imagery (CGI) has hurt science fiction movie making as much as helped. I think that’s why I’ve always drifted towards TV shows like Star Trek (The Original Series) and Doctor Who. They are story and character-driven, not special effect-driven.

I suppose its my age that causes this feeling, but I’ve seen my son and his teenage friends watch these movies and, more often than not, they look bored.

Do you know what they like? They like funny characters and funny dialogue. They good writing reinforced by good acting and editing.

I thought Guardians of the Galaxy Vol. 2 had some of the most amazing CGI I have ever seen. The movie’s nemesis, Ego, played by Kurt Russell, lives on a planet that in the IMAX format literally took my breath away.

To my son and his friends, those amazing graphics in Guardians were white noise. When I ask them what they thought of the CGI and special effects, I get answers like: “They were OK.” “Good.” “Cool.” “The Last Jedi was better.”

When they talk among themselves about movies like Guardians, they talk about the characters. The funny lines. Even the CGI-heavy battle scenes are remembered, not by the explosions, but through references to characters’ one-liners (such as Guardians’ Yondu: “I’m Mary Poppins y’all!”)

They crack up laughing every time Drax calls Mantis ugly (if you are not familiar with Guardians, Mantis happens to be very attractive).

Fun dialogue. Good actors. Decent storytelling. Swift pacing. Those are the core elements that form the secret sauce for building lasting science fiction franchises. Star Wars had it. Star Trek had it. And Doctor Who had it.

Have you watched any of those franchises recently?

Here is my one-minute summary: Women are, by nature, good (see the Disney Star Wars trilogy). Some men are good, but stupid (see Solo, Picard or any Doctor Who episode from the 13th doctor’s first season). The other men are bad and also stupid (see any Doctor Who episode from the 13th doctor’s second season). Bad women are bad because of bad men (see Birds of Prey). And everyone is sexist, racist and privileged…except women (watch any hour of MSNBC).

That is why these franchises are dying. Even women don’t want to watch that patronizing crap. People are numbed by the incessant preaching and scolding that defines the most recent Doctor Who episodes. They are depressed by the dystopian future offered by shows like Star Trek: Discovery and Star Trek: Picard.

Science fiction movies used to be fun. And even when they were serious or scary (e.g., Aliens), they were still fun.

Not any more.

If Disney wants a successful female-centric science fiction franchise, they should create a new one. Star Trek creator Gene Roddenberry didn’t want to make The New Adventures of Buck Rogers for a reason: Buck Rogers wasn’t his idea. Instead, he created a new franchise — Star Trek — and changed science fiction entertainment forever. George Lucas and Star Wars even more so. And no science fiction franchise will be as smart as Doctor Who. All three are original ideas created by creative people.

But if the data I’ve presented here are telling, these franchises are done.

I will miss them.

• K.R.K.

Requests for data used in this article can be sent to: kroeger98@yahoo.com

Final note: I apologize for not answering all constructive comments and requests sent to me. There are just too many, but I will continue to try.

APPENDIX: Other Google Trend Graphs

 

 

By Kent R. Kroeger (Source: NuQum.com, May 5, 2020)

Note: In this article I use the terms ‘lockdown’ and ‘stay-at-home’ orders interchangeably.

There is a lot of partisan noise in the news coverage of the coronavirus (COVID-19) pandemic.

“This isn’t about science, this is about control,” Fox News host Laura Ingraham recently told her audience as she questioned the motives of those who believe the U.S. must continue to lockdown until the COVID-19 pandemic is more under control.

Meanwhile, on MSNBC, Chris Hayes was calling the hosts at Fox News “coronavirus truthers” for giving airtime to two California urgent care doctors who believe we no longer need statewide lockdowns, suggesting the cable new network’s coordinated push to “get Americans back to work” was not based on science but on ideology and blind greed.

The “lockdown” is the ideological pivot point for the current U.S. political discourse on the COVID-19 pandemic.

In dispute are three fundamental issues:

(1) What is the actual morbidity (infection) rate of the coronavirus (SARS-CoV-2)?

(2) What is the actual mortality rate of the COVID-19?

(3) How effective have the statewide locksdowns been in containing and suppressing COVID-19?

Multiple large-scale studies based on probability samples will be needed to answer these questions definitively. Suggestions that the science is already established is absurd.

Only four days ago, New York Governor Andrew Cuomo announced results from a Staten Island, New York SARS-CoV-2 antibody study that found 20 percent of residents had been exposed to the virus. For the State of New York, overall, Cuomo said 12 percent had tested positive for the coronavirus.

If the New York results can be extrapolated to the entire U.S. population (it can’t, but for arguments sake), that would mean between 39 and 65 million Americans have had the virus. As of 3 May, around 70,000 Americans have died from COVID-19, meaning a rough estimate of the mortality rate of COVID-19 is somewhere between 0.1 and 0.2 percent — a range that covers the mortality rate for an average flu season and a really, really bad flu season.

Fox News and those two California doctors should have received an apology from Chris Hayes by now.

But the reality is, this New York State and Staten Island studies are just the beginning of the research that needs to be conducted over the next year or two before we know the actual morbidity and mortality rates of COVID-19.

As we are still in the middle of this health crisis, any definitive proclamations one way or the other are generally dubious…including mine.

Have Statewide Lockdowns Helped?

It is not too early to start assessing the effectiveness of statewide “stay-at-home” orders and economic lockdowns, as whether will end them in a same and timely fashion will depend on some quantitative level of knowledge about their utility.

A superficial look at the data suggests the lockdowns are not helping much (Note: This is not my opinion on lockdowns. I am doing this data walk in order to move towards a more evidence-based opinion)

While the states hit the hardest by the COVID-19 pandemic (on a per capita basis) are mostly Democrat-dominated states that decided relatively early in the crisis to issue statewide lockdown (“Stay-at-Home”) orders, states that adopted less stringent lockdown policies (Arkansas, Iowa, South Dakota, Nebraska, North Dakota, Utah and Wyoming) appear to be doing better (see Figure 1).

Figure 1. The relative number of COVID-19 cases and deaths by U.S. State (through 3 May)

Of the 10 states (plus District of Columbia) with the highest relative number of COVID-19 cases, only two were won by Donald Trump in 2016 (Louisiana and Michigan). Conversely, among the 10 states with the lowest relative number of cases, seven were won by Trump (Montana, Alaska, West Virginia, Wyoming, Oklahoma, Texas and Kentucky).

States won by Trump in 2016 average 1,885 COVID-19 cases per 1 million people, whereas states won by Hillary Clinton average 4,818 per 1 million people. Though this difference is significant using a two-sample difference of means t-test (t-statistic = 3.47, p = .001, std. error = 846), in no way can we conclude that Trump (“red”) states are doing better than Clinton (“blue”) states.

Furthermore, the real analytic question is about the effectiveness of “Stay-at-Home” orders, which some red states did implement. In fact, the difference in the relative number of cases between lockdown (“Stay-at-Home”) states and non-lockdown states is not statistically significant; in part, because we have so few instances of non-lockdown states (n = 7).

Also complicating our ability to discern the effectiveness of lockdowns is the variation in lockdown policies across states. Indeed, even a few non-lockdown states (such as Iowa) have implemented elements of a lockdown (such as social distancing recommendations, closing bars and restaurants and forbidding large group gatherings). Perhaps those policies, not a full lockdown, are sufficient to contain the spread of COVID-19?

We must also consider that the state-level differences in Figure 1 could be driven by factors unrelated to lockdowns or other strict suppression policies (e.g., travel restrictions within and between states). For example, previously I’ve argued population density is the dominant variable in explaining state-level differences in the relative number of COVID-19 cases, not mitigation and suppression policies. Trump states are doing better in containing the COVID-19 spread in part due to those states being sparsely populated. At a minimum, we need to control for that before declaring which states are doing a better job than others.

If we further divide lockdown states into two categories — those that locked down within 20 days of their first confirmed COVID-19 case and those that took more than 20 days — we might get a clearer picture of the impact of lockdowns.

Figure 2 shows the three lockdown categories across key measures of the coronavirus. With the exception of testing, there is a linear relationship between the three lockdown categories: Early lockdown states are the highest, late lockdown states are in the middle, and non-lockdown states are lowest on key measures such as population density, relative number of cases and deaths, and changes in cases and deaths since 1 April.

Figure 2: Lockdown Categories by Key Measures (as of 3 May)

Early lockdown states are much more densely populated (690 people per sq. mile), have done more testing (25,290 per 1 million people), have more confirmed cases (4,012 per 1 million people), have more COVID-19-related fatalities (230 per 1 million people), and have experienced larger changes in cases (3,306 per 1 million) and fatalities (212 per 1 million) since 1 April.

If Figures 1 and 2 were all you knew about state lockdowns, it would be hard to declare them successful. In fact, similar “topline” data is repeatedly used in the conservative media to reinforce the narrative that the U.S. should return to work sooner rather than later.

Are they wrong?

I believe as a blanket statement — Lockdowns are not working or necessary any more— they are partially wrong. However, to support my opinion, we need to make sure our state comparisons are made on a level playing field.

Can we compare COVID-19 case and death numbers between states?

The definitional comparability problem between states in measuring COVID-19 cases and deaths is highlighted by the Centers for Disease Control (CDC) in its own tabulations and research on the virus (SARS-CoV-2) and its associated disease (COVID-19). In the CDC’s latest report on COVID-19, here is the language they use to explain why their numbers may be different from state-reported numbers:

Provisional death counts in this (CDC) report will not match counts in other sources, such as media reports or numbers from county health departments. Death data, once received and processed by National Center for Health Statistics (NCHS), are tabulated by the state or jurisdiction in which the death occurred. Death counts are not tabulated by the decedent’s state of residence. COVID-19 deaths may also be classified or defined differently in various reporting and surveillance systems. Death counts in this report include laboratory confirmed COVID-19 deaths and clinically confirmed COVID-19 deaths. This includes deaths where COVID-19 is listed as a “presumed” or “probable” cause. Some local and state health departments only report laboratory-confirmed COVID-19 deaths. This may partly account for differences between NCHS reported death counts and death counts reported in other sources.

My state of New Jersey, for example, only reports COVID-19 deaths that are test-confirmed, except in the case of nursing home deaths where “probable” cases can also be classified as a COVID-19 related death. This may account for why nursing home deaths account for nearly half of New Jersey COVID-19 deaths. Unfortunately, the New Jersey fatality numbers in nursing homes must therefore be considered problematic even if, in the words of Jon Dolan, president of the Health Care Association of New Jersey, the data are “directionally accurate.”

Yowza! Directionally accurate?!

Worse yet, these case and fatality definitions can vary depending on the state where the victim died, according to the CDC.

This is a serious problem if the goal is to compare state-level mitigation and suppression policies. Without detailed case-level data on COVID-19, researchers are at a distinct disadvantage.

Adding to this problem is an even bigger problem, in my opinion. There is significant variation in how diligently states are trying to measure the spread of the coronavirus within their state. As of 3 May, Rhode Island has conducted 67,896 per 1 million people, and New York 50,680 per 1 million. Contrast those numbers to Arizona and South Carolina where, respectively, only 11,144 and 12,467 tests per 1 million have been conducted so far.

Does this mean New York or Rhode Island’s estimate of the morbidity rates (percent of residents that have had the virus) in their respective states are more accurate than Arizona and South Carolina? Not necessarily. It will depend on a number of factors related to the quality of a state’s effort to assess the spread of the coronavirus (see Figure 3), including: (1) COVID-19 test availability, (2) training in using the test, (3) test accuracy, and (4) and selection bias (perhaps the most serious problem if the goal is to generate an unbiased estimate of a state’s morbidity rate). We must also recognize that all of these factors are moving together in time. What was true on Tuesday may not be as true on Friday.

Figure 3: A Model for Assessing the Quality of a State’s COVID-19 Measurement Effort

If a state is only testing health care workers and citizens with severe symptoms (as New Jersey was doing initially), their testing will miss a significant percentage of people who are asymptomatic but still contagious. That is textbook selection bias. Only some form of probability sampling will reliably measure the prevalence of this group or the overall morbidity rate in a geographic location. Some states (hopefully most) are doing that already (New York is, for example). And I am certainly not the first person to call for more random sampling in measuring the COVID-19 pandemic (others doing the same are here, here and here).

Ironically, its the supposedly anti-science Republicans in North Carolina that have pushed for probability sample testing, not the Democrats. Why? The Democrats fear random testing will reveal their fundamental rational for imposing state-level lockdowns — a high COVID-19 mortality rate relative to the common flu — likely won’t be substantiated by the science.

The problem too is that we have a lazy, politically-biased national journalism corps in this country that would rather rely on the deceptive case numbers and case fatality rates pumped out by Johns Hopkins University (JHU-CSSE) and the WHO than insist on scientifically accurate numbers, such as the estimates recently released by a Stanford University study in Santa Clara County, California, showing a significantly higher COVID-19 prevalence rate than the official numbers released by the county and state governments.

“After adjusting for population and test performance characteristics, we estimate that the seroprevalence of antibodies to SARS-CoV-2 in Santa Clara County is between 2.49% and 4.16%, with uncertainty bounds ranging from 1.80% (lower uncertainty bound of the lowest estimate), up to 5.70% (upper uncertainty bound of the highest estimate),” the study said. Those estimates translate to between 48,000 and 81,000 Santa Clara County residents having had the coronavirus (SARS-CoV-2).

At the time of the study’s field closure, April 1st, the State of California and Santa Clara County were reporting a case prevalence of just 956 in the county. The implication of this difference from the Stanford results is profound: If the Stanford study is correct, the mortality rate for COVID-19 is not nearly as high as being implied when the news media reports the Johns Hopkins University case and fatality numbers. If one of the fundamental arguments behind imposing statewide lockdowns is the purportedly high mortality rate for COVID-19 — as high as six percent if using only confirmed cases (as reported by JHU-CSSE) in the denominator — any evidence that pushes that number closer to 0.1 percent (the estimated mortality rate for the common flu) is heresy.

When two urgent care doctors in California suggested as much, YouTube attempted to remove their televised news conference from its social media platform. Facebook and Twitter, at least so far, have resisted the same action.

We don’t need to use the numbers offered by the two California doctors to argue the media-reported COVID-19 mortality rates may be seriously inflated — we have the Stanford study. But is the Stanford University necessarily right? Of course not, but at least that study’s team documented their methodology, giving readers (and the news media) something to critique.

An even larger scientific study in China found a higher fatality rate for COVID-19 than the Stanford study —2.3 percent overall and as high as 14.8 percent for people aged 80 and older. Across other age groups, the fatality rate was found to be as follows:

• Aged 70 to 79 = 8.0%
• Aged 60 to 69 = 3.6%
• Aged 50 to 59 = 1.3%
• Aged 40 to 49 = 0.4%
• Aged 0 to 39 = 0.2%

Let me now reveal my bias regarding statewide lockdown policies: If the Stanford study is correct and the COVID-19 fatality rate is similar to the common flu, it is time to end the statewide lockdowns (while maintaining strict social distancing recommendations). However, if the Chinese study is more accurate, as a man in his mid-50s, a 1.3 percent chance of dying from COVID-19 is too hot for my oatmeal — I’m staying home until there is a vaccine or reliable treatment (and anyone my age or older should do the same).

Which is why the national news media’s attempt to suppress the important scientific debate going on right now about the mortality rate of COVID-19 is reckless and counterproductive.

We may be huddling in our basements for no reason and to little effect? Is the damage being done to the world economy worth being so overly cautious? I would say, ‘No,’ particularly if people are losing their health care coverage or being saddled with large medical bills due to the pandemic.

Do you want to know a way to kill millions of Americans even faster than COVID-19? Take away their health care coverage.

Enough news media bashing. It has become too easy.

The point of this article is to make a preliminary assessment of the effectiveness of statewide lockdowns in controlling the spread and lethality of COVID-19.

Here is my take on the data (as of 3 May 2020)…

After controlling for population density (and other factors), what can we say about statewide lockdowns to control COVID-19?

My answer is not a satisfying one: it is not clear the states with lockdowns are doing better containing the effects of the coronavirus than states without full lockdowns.

One caveat to this finding is important: the COVID-19 pandemic is not over. Many non-lockdown states like Iowa and Nebraska still have not experienced a decisive peak in new daily cases. But also, keep in mind, these state-reported cases and deaths numbers are of dubious quality (see discussion above). The fact that Iowa Governor Kim Reynolds found the Utah-based company to handle Iowa’s COVID-19 testing program through D-list Hollywood celebrity and Iowa-native Ashton Kutcher should tell you all you need to know about how seriously I take Iowa’s measurement program.

[Sidebar: You would think Iowans would have learned their lessons from the Iowa Caucuses vote counting disaster last February when the Iowa Democratic Party chose another Utah-based tech company to count the votes. Are these people morons? What happened to Iowa’s once premiere public education system? That’s a debate for another article — and a heads-up, my conclusions are not kind to Iowa’s political leadership.]

Another caveat is that this is an aggregate (state-level) data analysis. It does not inform us directly about individual-level relationships. So, when you read below that the relative number of tests, indirectly, has a positive relationship to the relative number of COVID-19 deaths, this does not mean states should stop testing to reduce the number of deaths! The result means in the aggregate that states with the most relative testing are also experiencing higher relative fatality rates for COVID-19, all else equal. Correlation is not causation.

A Path Model for COVID-19 Cases and Deaths for U.S. States & D.C.

Using the JHU-CSSE data at the state-level through 3 May (see, I’m no better than those lazy journalists), I estimated a linear path model for explaining state-level COVID-19 confirmed cases and deaths.

To mitigate the noise and bias inherent in the JHU-CSSE fatality numbers, I calculate the fatality incidence as a function of the state’s total population (i.e., deaths per 1 million people). That is not the mortality rate, but its denominator is a more reliable government statistic than the confirmed number of cases.

The variables tested for their relationship to the relative number of COVID-19 deaths (natural log transformed) included:

• A state’s population density (log transformed) (Variable name: LN_P)
• The cumulative number of tests conducted by the state per 1 million people (natural log transformed) (Variable name: LN_T)
• The number of confirmed COVID-19 cases per 1M people (natural log transformed) (Variable name: LN_C)
• Whether a state imposed travel restrictions between and/or within their state (1 = Yes, 0 = No) (Variable name: TRA)
• Whether a state imposed a statewide (“stay-at-home”) lockdown policy (1 = Yes, 0 = No) (Variable name: STA)
• Governor’s political party (1 = Democrat, 0 = Republican…not a value judgment on my part) (Variable name: PAR)

I also tested variables such as the state’s percentage of vote for Trump in 2016 (sorry, but this confirms to me that the state differences seen in Figure 1 above are not substantively meaningful), GDP per capita, number of staffed beds per 1 million people, percent of state’s economy related to China, and percent of population aged 65 and older. None proved statistically significant.

And here are the results…

First, with only seven states not imposing a full statewide lockdown, it will require sizable predicted differences in relative confirmed case and death rates for the lockdown variable’s two levels to be statistically significant, regardless of whether the model is estimated in a Bayesian or Frequentist context.

The linear path model in Figure 4 was estimated using JASP, a free statistical analysis package (with Bayesian estimation for most analytic options) made available by the University of Amsterdam. The model’s diagnostic output, including standard errors, is in the Appendix below.

Figure 4: Path model standardized parameter estimates and residual covariances (data through 3 May 2020)

Interpretation of Results

Lockdowns versus No Lockdowns

Let us plunge right into the variable of most interest: statewide lockdowns (variable: STA). Its direct relationship to the relative number of COVID-19 deaths is positive and significant (β = 0.90, p < .001), while its direct relationship to the relative number of confirmed cases is negative and significant at an α < .10 level (β = -0.48, p = 0.088).

Have statewide lockdowns led to more COVID-19 deaths? No, not likely. There are anecdotal cases where some victims were isolated in their homes and did not get the urgent care needed to save the lives. One of inquiry in this regard is an increased number of younger and middle-aged victims who died from strokes related to COVID-19, some dying in their homes before they could get needed care. In theory, a statewide lockdown could increase those types of fatalities, but not on the level implied by the model here. But, again, this is an aggregate analysis and we cannot make individual-level inferences.

Instead, my interpretation is that unmeasured factors related to both lockdowns and COVID-19 deaths are at play. Although it is possible that states with lockdowns are inflating their COVID-19 numbers and/or non-lockdown states are under-reporting, I think it is far more likely that some unmeasured variable (my guess is ‘time’) is leading to much higher relative fatality rates in lockdown states compared to non-lockdown states. As all of the non-lockdown states are in the interior of the country, they have been among the last to experience their first cases and deaths compared to the coastal lockdown states.

Still, we cannot rule out the possibility that some states are systematically over-reporting or under-reporting their COVID-19 numbers. I offer the previous discussion about New Jersey including “probable” COVID-19 cases in their nursing home fatality counts as a possible avenue for this type of systemic measurement bias (fraud?). I also have anecdotal evidence from talking to friends back in Midwest about some of their family, friends, and neighbors “toughing it out” and not getting tested despite showing COVID-19-type symptoms. That is a Northern European cultural trait with which I have personal experience.

The more interesting result in our path model is that lockdown states, all else equal, are experiencing lower confirmed case rates per 1 million people than non-lockdown states. While lockdown variable is only marginally significant, that could be for a number of issues unrelated to the actual importance of lockdown policies suppressing COVID-19 morbidity rates.

The confirmed COVID-19 cases model certainly has specification error, though the model residuals cases appear random and the model fit at 69 percent is not too bad (see Appendix).

Over time, the observed differences in relative COVID-19 cases have narrowed between lockdown versus non-lockdown states. When this pandemic is over, we may in fact see much higher relative numbers in the non-lockdown states than we see now. That may, in turn, lead to a stronger (negative) statistical relationship between the lockdown variable and COVID-19 case rates.

Other Factors

When looking at total effects (direct + indirect effects), a state’s population density (+ relationship), relative number of administered tests (+), the presence of travel restriction policies at some point during the pandemic (-), and the presence of a Democratic governor are stronger correlates with the relative number of COVID-19 fatalities (+) than is a state’s lockdown policy. As I’ve said, that could change over time as the pandemic progresses into later stages — the question is: How much?

Residual Analysis

One of the benefits of estimating a linear path model is that we can look at the residuals for each state to see which ones are doing better than expected on COVID-19 case and fatality rates and, of course, which ones are doing worse.

According to my analysis, these states highlighted in green in Figure 5 are experiencing a lower rate of COVID-19 cases (per 1 million people) than expected (the presumption is that whatever these states have done, it is working better than other states). The states highlighted in red are experiencing a higher rate of COVID-19 cases (per 1 million) than expected:

Figure 5: Actual versus Expected COVID-19 Confirmed Case Rates (as of 3 May 2020)

Note in Figure 5 that Arkansas is a non-lockdown state, while Florida implemented its lockdown relatively late in their outbreak (29 days after the first confirmed case). The average lockdown state implemented their policy 21 days after the first confirmed case.

Figure 6 shows a similar table for actual versus predicted COVID-19 fatalities per 1 million people.

Figure 6: Actual versus Expected COVID-19 Fatality Rates (as of 3 May 2020)

Non-lockdown state Arkansas now finds itself on the under-performing (red highlight) list with 25 actual COVID-19 fatalities per 1 million people versus an expected 15 fatalities per 1 million people. On the other hand, non-lockdown state Utah is on good side of the ledger with 31 expected COVID-19 fatalities per 1 million people versus an expected fatality rate of 83 per 1 million people.

Final Thoughts

As of now, the quantitative evidence is mixed in support of full, statewide lockdown policies as being effective in mitigating and suppressing the spread of the coronavirus. To the extent lockdowns matter in controlling the spread of the virus, the analysis presented here cannot distinguish what elements of a lockdown policy are most effective. It could be that merely enforcing safe personal behaviors and social distancing — such as face masks, preventing large group activities, and pressuring people to keep at safe personal distances — are having the most impact. ‘Staying-at-Home’ may be unnecessary.

More importantly, the actual mortality rate of COVID-19 (along with the number of new daily cases) is critical information needed to make a wise decision on statewide lockdowns. Some extremely vulnerable populations — the elderly and those with certain preexisting medical conditions — may need to continue to stay at home; but, for the vast majority of Americans, it may not be a wise policy to continue, particularly in light of the economic damage the lockdowns are having across the globe.

South Korea didn’t lockdown. Japan didn’t. Taiwan didn’t. Singapore didn’t. Hong Kong didn’t. Yet, they are all doing better than the U.S. in COVID-19 fatality rates and they didn’t shut down their economies in the process.

The news media and Democrats may continue to dismiss or censor this type of information and cherry-pick evidence that supports full lockdowns, but doing so stunts what should be an open and constructive debate. [Remember those?]

And, frankly, I have provided some tentative evidence to support statewide lockdowns, though I draw no absolute conclusions on the importance of continuing statewide lockdowns.

The empirical question has not been definitively answered on lockdowns and may not be known until this pandemic is over and epidemiologists and public policy researchers can apply more sophisticated modeling to the final numbers. We will eventually find out the true mortality rate for COVID-19 — not unlike what epidemiologists at The University of Puerto Rico at Mayagüez recently did when they concluded the U.S. news media-promoted claims that up to 4,000 Puerto Ricans died in 2017’s Hurricane Maria were substantially inflated. They determined between between 1,069 and 1,568 Puerto Ricans died directly and indirectly from Hurricane Maria. Some will rightfully claim that number is still too big to be acceptable, but it is substantively different from the misinformation promulgated by the U.S. national media not long after Hurricane Maria hit Puerto Rico’s shores.

Similarly, if we want to avoid learning the truth years from now, instead of now, any suggestion that the debate on lockdowns is settled must be treated as nonsense — and potentially harmful to the country.

• K.R.K.

As always, comments can be sent to: kroeger98@yahoo.com

To my readers that have sent constructive comments and not received a reply from me, I apologize. The volume has increased to the point where I am not able to answer all of them. But I do try.

APPENDIX: The Path Model Estimation Output

Model Set-up in JASP

Model Estimation Output

 

By Kent R. Kroeger (Source: NuQum.com, May 2, 2020)

My disaffected Bernie Sanders-supporting friends (and other progressive Democrats abandoned by their party) are telling me Joe Biden is unfit for the Democratic presidential nomination due to an alleged sexual assault 27 years ago.

In the #MeToo-era, how can this accusation not be disqualifying for a Democratic candidate?

A fair question.

For me, however, the depth of my opposition to Biden is unaffected by a sexual assault charge that only now, as he stands ready to gain the party’s nomination, comes to light. No person can adequately defend themselves on a accusation that deep in the foggy past. I had the same opinion with respect to Brett Kavanaugh (and lost political friends because of that stance; many of whom now refuse to believe Biden-accuser Tara Reade despite considerably more corroborating evidence for her story than the allegations made against Kavanaugh).

No, my opposition to Biden is rooted in my direct experience with the man 33 years ago (and for which he is equally unable to defend himself).

That is the definition of a hypocrite and I plead guilty on that charge.

Nonetheless, here is my problem with Joe Biden…

I experienced Biden in the 1980s when he had abundant charisma and hair. In his best moments in the U.S. Senate, he was an inspiring orator — equal to Ted Kennedy — who willingly planted himself in the political center and had measurable influence on major pieces of congressional legislation, as many of his more senior, left-leaning colleagues were voted out of office during the Reagan Revolution.

Joe Biden is not blowing smoke when he says, “I’ve gotten things done.”

He really has. Not always good “things,” mind you, but he has a substantial record of legislative accomplishments. That is not my opinion. Look at his legislative record here. Contrast Biden’s lawmaking achievements to any other candidate in the 2020 Democratic nomination race and it is not even close (Minnesota Senator Amy Klobuchar comes in a distant second to Biden).

However, authoring substantive legislation doesn’t win presidential elections. If it were, Ted Kennedy’s 1980 and 1984 presidential victories would have been followed by Jack Kemp’s two-term presidency.

That didn’t happen.

In my research, I have found swing voters most often judge presidential on two factors: Likability and Trust. Competency plays a role in this dynamic, but mostly through its connection to trust.

In this world, Joe Biden should be the perfect candidate.

Until you actually encounter him, as I did during the 1988 presidential race.

_____________________________________________________________

In Fall 1987, I was starting graduate school at The University of Iowa. In a public policy class, taught by the late Professor Russell Ross, we were graced during one session with an actual presidential candidate: U.S. Senator Joe Biden of Delaware.

Biden in 1987 was imposing, with an almost football player-like physique, whose informal rhetorical tendencies were also laced with good substance and meaty ideas. Among the 1988 Democratic Party presidential candidates, only Jesse Jackson was more impressive, and the two front-runners heading into the Iowa Caucuses, Rep. Richard Gephardt (Missouri) and former Massachusetts Governor Michael Dukakis, were proudly on the opposite end of the charisma scale.

In the first Biden campaign rally I attended, he didn’t disappoint. He spoke simply but eloquently on his disapproval of President Ronald Reagan’s Central American policies (Nicaragua, El Salvador) and transitioned effortlessly into a critique of Reagan’s confrontational approach to the Soviet Union (which he ultimately supported).

What I remember most, however, is that Biden was a natural public speaker: a loud, tenor voice (but not too loud) with expressive, disciplined hands. His signature hand move was to form a fist with his right hand and land an imaginary body blow to whatever point he was trying to emphasize. Biden might be Catholic, but in 1987 he spoke with a evangelical minister’s physicality and magnetism.

After over thirty years of studying the speaking styles and body language of political candidates, I still believe the Joe Biden of 1987 was one of the best public speakers I’ve ever seen. He wasn’t Jesse Jackson, but he was better than Ronald Reagan (and I’ll happily go to my grave defending that comparison).

In many ways, Biden was Bill Clinton before Bill Clinton: A centrist Democrat with an open hostility to New Deal–Great Society interventionism and a cagey acceptance of the liberal Democratic social agenda.

If you could have created the perfect centrist Democrat to beat the George H. W. Bush in 1988, it would have been Joe Biden.

Or, so I thought.

In the 30 minutes Biden commanded the attention of my public policy class, something weird happened towards the end — a personality trait that has become conspicuous in the 2020 presidential campaign.

Joe Biden has a hostility problem.

After he gave my class his standard stump speech focusing — as best as I can recall — on the damage the Reagan economy had done to “hard-working families” (as if to contrast with those lazy families), Biden took questions.

Q & As: The wheelhouse for any great politician (Barack Obama, Bill Clinton, John Kennedy).

One of the last questions came from a female classmate who asked a straightforward question about Biden’s support for many of Ronald Reagan’s conservative legislative triumphs, such as the 1981 tax reform bill — that lowered income tax rates, but, according to the non-partisan Congressional Research Service, did little for economic growth and productivity while disproportionately benefiting the wealthiest Americans — and the 1981 Reagan budget bill — that froze, cut and, in some cases, eliminated federal programs for health, education, and other social services. It was a budget that the Washington Post described as “the reversal of two great waves of government intervention, the New Deal and the Great Society.”

The question by my classmate was not overly hostile. “Do you consider yourself a Reagan Democrat?” was essentially her point.

It was the type of question Bill Clinton would have knocked out of the ballpark during his 1992 presidential campaign; and the 2008 version of Hillary Clinton, as prickly as they come, knew how to forcefully address unfriendly inquisitors without finger wagging or insulting their intelligence.

Not Joe Biden.

He bushwhacked his female inquisitor. The specifics of his verbal attack are now fuzzy, but I recall words and phrases like ‘naive,’ ‘lack of experience,’ and ‘live in the real world’ being directed at her.

The problem wasn’t him, it was her!

This answer shouldn’t have surprised me given that one the campaign themes tested by the 1988 Biden campaign was “Scold the Voter.” [I wish I made that up.] Political researcher Paul Taylor, in fact, documents the fratricidal warfare within the Biden camp that allowed such an titanically stupid idea to have life, if only for a brief moment.

Most shocking to me about Biden’s response to this young woman, however, was the personal nature of his answer. Joe went from zero to light speed on the ferocity scale…for no obvious reason! It was a softball question. I can still see her face, her mouth agape, staring at Professor Ross as though about to ask if she said something wrong.

To Biden’s credit, he admitted he had “been too harsh” in his response, which significantly defused the tension. But the damage was done for me.

A well-balanced politician should be able to explain their votes on major pieces of legislation, particularly complicated budget bills that are typically packed with goodies and pet agendas that politicians can sell to their constituents back home.

It was not a hard question — and certainly not personal in tone.

I left that class thinking Joe Biden was odd, in the scary sense. As if he could, in a moment of passion, kill someone and bury the body along the Rock Creek Parkway. [I’m not saying Joe Biden has done that, only that he seems capable.]

In observing Joe Biden’s career-spanning instances of public fury, often manifesting at the strangest times, it is impossible not to think of his personal tragedies as possible sources of this latent anger. I have genuine empathy for Joe Biden, even as I cringe watching him in situations like this one below where he calls a 21-year-old woman a “lying dog-faced pony soldier”:

Source: Reuters

 

Admittedly, Biden was trying to be funny in supposedly borrowing the “lying dog-faced pony soldier” quote from a John Wayne movie. [More likely, it was a misquoted line from the movie, “Pony Soldier,” starring Tyrone Power.]

But to me, Biden still comes across as needlessly hostile, just as he did 33 years ago.

I realize I’m judging Biden on something far less serious than a sexual assault allegation; but, for that very reason, I feel comfortable using his unambiguous personality traits as judgment factors. The fact that Biden keeps reinforcing my doubts about his temperament through what he says and does in the present only further validates my vote decision process.

Politics is not a forgiving, merciful business. Politicians can once have had problems, but they can’t have problems. Americans love survivors, not victims.

And, since that day in 1987 when Joe Biden came to speak to my class, I can’t get over the feeling that Joe Biden has significant personality problems.

• K.R.K.

Send comments to: kroeger98@yahoo.com