Monthly Archives: September 2020

Are China and Russia moving too fast on a coronavirus vaccine?

[Above graphic is a combined image from a 3D medical animation, depicting the shape of the coronavirus as well as the cross-sectional view. Image shows the major elements including the Spike S protein, HE protein, viral envelope, and helical RNA (Image by https://www.scientificanimations.com; used under the Creative Commons Attribution-Share Alike 4.0 International license.]

By Kent R. Kroeger (Source: NuQum.com, September 22, 2020)

In May, the University of Minnesota’s Center for Infectious Disease Research and Policy (CIDRAP) — one of the world’s leading research centers on infectious diseases — issued a warning about any expectations of a coronavirus vaccine being available soon or 100 percent effective once available.

Among CIDRAP’s recommendations for policymakers were these two warnings:

States, territories, and tribal health authorities should plan for the worst-case scenario, including no vaccine availability or herd immunity.

Risk communication messaging from government officials should incorporate the concept that this pandemic will not be over soon and that people need to be prepared for possible periodic resurgences of disease over the next 2 years.

Five months later, their cautious words remain relevant.

While the world may be closer than ever to its first regulatory-approved coronavirus vaccine — at least nine vaccines are already in Stage 3 testing — there is a concern among scientists that this first vaccine may not be effective enough to achieve herd immunity (estimated to be around 60 to 70 percent of a population) and could discourage the development of significantly better alternatives.

This month, China announced it has started to deploy two state-approved coronavirus vaccines— both developed by Sinopharm, a state-owned pharmaceutical company — and has already vaccinated over 100,000 people.

Remarkable is that China is doing this while still in Phase 3 trials for the vaccines (see Figure 1 below for a description of the five stages/phases in vaccine development).

In addition to China, Russia has also approved a new coronavirus vaccine.

Scientists outside of China are predictably concerned and skeptical of China’s aggressive vaccine rollout.

“One needs to carefully conduct clinical trials of adequate size with adequate time for follow-up, look at both efficacy and safety, and those data have to be very carefully reviewed before you start giving the vaccine to people outside of a carefully designed clinical trial,” Daniel Salmon, director of the Institute for Vaccine Safety at Johns Hopkins, told Vox’s Lili Pike.

Phase 3 trials are critical as they involve around 30,000 test subjects and are designed to reveal rare, adverse reactions to test vaccines. For example, if just 1 out of 30,000 vaccine recipients (0.33 percent) has a fatal reaction to an otherwise highly-effective vaccine (say, 90%), that could translate into 260,000 vaccine-related deaths if the vaccine were given to the entire world population.

Figure 1: The 5 Stages of Vaccine Development

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Image courtesy of Wellcome Trust

However, John Moore, an immunologist at Weill Cornell Medical College, believes China, given its current low infection rates, could afford to wait until Phase 3 trials are completed in order ensure a safe and effective vaccine.

But Moore’s calculus ignores a more powerful dynamic behind China (and Russia) aggressively rolling out coronavirus vaccines far ahead of standard practice in new vaccine development, which typically takes around 10 years.

The fastest development ever was for the mumps vaccine which took four years from start to final regulatory approval.

The economies of China and Russia have been deeply hurt by the coronavirus pandemic (as have all world economies) and there is a strong incentive to end this pandemic as soon as possible — even at the risk of exposing their own citizens to potentially unsafe or ineffective vaccines. The cost-benefit analysis in autocratic societies is fundamentally different than in capitalist democracies such as in the U.S. and European countries.

If China and/or Russia are successful with their early vaccine deployments, they will become the model example for future Lean Six Sigma workshops.

Somehow China and Russia have done in seven months what typically take seven years.

A Half-Baked Cost-Benefit Analysis

The following cost-benefit analysis is meant merely as a thought experiment and is not a formal exercise in risk management. However, it is intended to loosely approximate the analyses underlying the decision by the Chinese and Russians governments to accelerate their vaccine developments.

In the following analysis of an hypothetical early rollout vaccine, these assumptions were used:

  • The coronavirus infection fatality ratio equals 0.0084, the most recent CDC estimate (i.e., 0.84 percent of those who contract the virus will die).
  • All world citizens (7.8 billion) are vaccinated by the early rollout vaccine and at roughly the same time.
  • The early rollout vaccine has a fatality ratio of 0.0033 (i.e., 0.33 percent) — an extremely high ratio that would never be approved by a U.S. or European regulatory body.
  • Calculations of total coronavirus deaths (coronavirus deaths + vaccine deaths) are based on a vaccine effectiveness rates of 40%, 60%, 80%, and 90%. (Note: Most vaccines are between 85 and 95 percent effective, according to OurWorldInData.org)
  • A coronavirus-related estimate of worldwide deaths assumes everyone is either effectively vaccinated or ineffectively vaccinated. Among those ineffectively vaccinated, they will either die from the vaccination or contract the virus. Those with highly-adverse reactions to the vaccine are rolled into the vaccine fatality rate.
  • If no vaccine is ever developed, everyone contracts the virus at roughly the same point in time.
  • This analysis ignores retransmission.

Figure 2 shows the estimated total number of coronavirus-related worldwide deaths for each vaccine effectiveness rate. It is important to note that this is a near worst-case scenario in terms of the vaccine fatality rate (VFR). A vaccine with a VFR of 0.0033 would never be approved by regulators. In the real world, due to strict development requirements, vaccines are extremely safe and this hypothetical cost-benefit analysis is not meant to challenge that scientifically-supported fact.

Figure 2: Hypothetical Cost-Benefit Analysis of Early Rollout Vaccine

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Nonetheless, an analysis like the one in Figure 2 is being done across the dozens of pharmaceutical and research institutes working on a coronavirus vaccine right now.

Given that many epidemiologists are estimating that the herd immunity rate for the coronavirus is probably between 60 and 70 percent, a vaccine effectiveness rate less than that might not halt the epidemic.

But as Figure 2 shows, in a near worst-case scenario — a 60 percent effective vaccine with a high fatality rate — such a vaccine could save a net of 29 million people (i.e., the number of people who would have died without a vaccine [65.5 million] minus those who would die with a full vaccine rollout [36.4 million]).

Would you approve of a vaccine with that outcome? I wouldn’t. The Federal Drug Administration most certainly wouldn’t. But would China or Russia? Maybe.

The U.S. gross domestic product (GDP) shrank 9.5 percent in 2020 Quarter 2 due to the coronavirus. In the same period, the Organisation for Economic Co-operation and Development (OECD) area saw their economies fall by 9.8 percent.

As for China, its GDP fell 6.8 percent in 2020 Quarter 1 due to the coronavirus (though it did rise by 3.2 percent in 2020 Quarter 2, according to the Chinese government).

In turn, Russia has watched the price of oil — one of its most important exports — fall from $54-a-barrel in late-September 2019 (WTI crude) to $39-a-barrel (as of 22 Sep 2020). Likewise, natural gas prices have fallen from $2.43 (USD/MMBtu) in late-September 2019 (NYMEX natural gas futures) to $1.79 (USD/MMBtu) as of 22 Sep 2020.

Undeniably, China and Russia both depend heavily on a strong world economy, including economic activity with the U.S. and the OECD countries. The quicker the end to this pandemic, the sooner their economies can fully rebound.

And what about the billions of people in the developing world who are going to be among the last to get a coronavirus vaccine given that a small number of wealthy countries — representing just 13 percent of the world’s population — have already purchased 51 percent of the world’s coronavirus vaccine supply before its been approved and mass-produced?

If China and Russia have produced reasonably effective and safe coronavirus vaccines, they could become heroes to the developing world, who currently face the likely prospect of multinational pharmaceutical companies — that have already extracted billions of dollars from their governments to encourage production an effective coronavirus vaccine — extracting even more billions in profits once they produce an approved vaccine.

Still, a 60 percent effective vaccine under our simplifying assumptions here would still result in 36 million coronavirus-related deaths. That’s a lot. In nine months, the coronavirus has killed around 1 million people worldwide.

By rough comparison, AIDS/HIV has killed 33 million people worldwide since its identification in 1981 (or about 850,000 per year).

History has proven relatively wealthy people can tolerate large numbers of premature deaths as long as its not them. The real question is, will they tolerate China or Russia threatening profits of U.S and European pharmaceutical companies?

Vaccine Failures in the Past

In history, two vaccines are often cited as examples of how things can go wrong with vaccines rolled out too early or carelessly.

The “Cutter Incident” in 1955 resulted in 10 deaths and 164 cases of permanent paralysis after 200,000 people received a polio vaccine that had been improperly produced. That’s an adverse reaction rate of 0.09 percent. The “Cutter Incident” was 26 times more lethal than the 0.0033 percent vaccine fatality rate assumption made in this analysis.

In 1976, another vaccine debacle occurred in the U.S. where within 10 weeks approximately 45 million people were vaccinated for the “swine flu.” The vaccinations stopped however after few cases of the virus ever developed and around 450 Guillain-Barré syndrome cases emerged, resulting in 53 deaths (i.e., 0.001 percent of swine flu vaccine recipients had a highly-adverse outcome).

A personal anecdote:

My family received the swine flu vaccine in 1976 resulting in my father experiencing a severe allergic reaction to it. As told to him by his doctor, since my father had an egg allergy (though minor), he may have reacted to the swine flu vaccine because it had been grown in eggs. However, my father received many flu vaccines after that (and, in all likelihood, having been grown in eggs) and never had a similarly severe reaction.

A few afterthoughts

I want to emphasize this essay is not a tirade against vaccines or the value a strict regulatory standards in their development.

There is no substitute for good science.

But it appears the apparently premature rollout of a coronavirus vaccine in China will end in one of two outcomes: (1) an epic failure that will go down in history as how not to develop a vaccine during a global pandemic, (2) or the start of a revolution in how such vaccines will be developed and approved going forward.

Is it possible regulatory authorities in wealthy countries are too risk averse in applying laws, standards and rules regarding vaccine approvals? Given the many advancements in bioscience over the past two decades, can safe and effective vaccines in some cases be turned around from start to finish in under a year?

We may find out one way or another very soon.

  • K.R.K.

Comments can be sent to: nuqum@protonmail.com
or DM on Twitter at: @KRobertKroeger1

Why have the countries with the strictest coronavirus measures had the worst outcomes?

By Kent R. Kroeger (Source: NuQum.com; September 20, 2020)

[The data used in this essay is available on GITHUB]

The answer to the headline question is an easy one with a simple look at the international COVID-19 data: The countries hardest hit by the COVID-19 virus were forced to pursue the strictest suppression and mitigation (S&M) policies.

In causal language: The strictness of coronavirus policies increased as the crisis increased.

The national and international news organizations have continued to ignore this question and its answer under the assumption it encourages some — especially those of the conservative persuasion — to conclude such policies are ineffective, perhaps even counterproductive.

In hoping to protect us from “misinformation,” the news media is neglecting its role in explaining the most dangerous worldwide pandemic since the 1918 Spanish Flu Pandemic, and in doing so, is stunting an important public discussion on coronavirus S&M policies options.

As the data below within the most advanced economies tentatively shows, there is strong evidence that coronavirus S&M policies do work — though they may not have been pursued early or long enough to counterbalance the undeniable potency and elusiveness of SARS-CoV-2 (“the coronavirus”) and its associated disease (COVID-19). According to the evidence presented below, it takes at least three weeks for S&M policies to have an impact on containing the coronavirus.

In many cases, however, countries begin easing their S&M policies soon after new COVID-19 cases start declining.

The Stringency Index

Ourworldindata.org provides a lovely time-series data resource on the coronavirus S&M policies that have be pursued by countries since the pandemic’s start. For this analysis, I selected the Government Stringency Index, compiled by Oxford University’s OxCGRT Project (Thomas Hale, Sam Webster, Anna Petherick, Toby Phillips, and Beatriz Kira, Oxford COVID-19 Government Response Tracker, Blavatnik School of Government)

They describe their Government Stringency Index as follows:

The OxCGRT project calculate a Government Stringency Index, a composite measure of nine of the response metrics.

The nine metrics used to calculate the Government Stringency Index are: school closures; workplace closures; cancellation of public events; restrictions on public gatherings; closures of public transport; stay-at-home requirements; public information campaigns; restrictions on internal movements; and international travel controls.

You can explore changes in these individual metrics across the world in the sections which follow in this article.

The index on any given day is calculated as the mean score of the nine metrics, each taking a value between 0 and 100. See the authors’ full description of how this index is calculated.

A higher score indicates a stricter government response (i.e. 100 = strictest response). If policies vary at the subnational level, the index is shown as the response level of the strictest sub-region.

It’s important to note that this index simply records the strictness of government policies. It does not measure or imply the appropriateness or effectiveness of a country’s response. A higher score does not necessarily mean that a country’s response is ‘better’ than others lower on the index.

What makes the Stringency Index particularly helpful for policy analysis is that it is measured over time, giving analysts the ability to examine the dynamic relationship between government S&M policies and coronavirus outcomes (e.g.,  confirmed cases and deaths).

Figure 1 shows a summary of the Stringency Index for 29 countries. It should be noted I have not included mainland China in this analysis over questions about data quality. As most of the analyses below are at the within-country level, this exclusion does not affect my conclusions.

Figure 1: Summary of the Stringency Index for 29 countries (weekly data, 30 weeks)

Over 30 weeks of coronavirus data (obtained through Johns Hopkins University – CSSE), the Portugal, Italy, U.S., U.K., and Spain have, on a weekly average, maintained the strictest S&M policies. It is not a coincidence that these countries have also experienced the worst coronavirus outcomes (see Figures 2 and 3 below).

Conversely, Taiwan, Macao, Japan, Sweden, and Iceland have pursued the least strict S&M policies over the same period.

Figure 2: The Relationship between the Stringency Index and weekly changes in COVID-19 Confirmed Cases (per 1 million people)

There is a weak but statistically significant positive relationship between the strictness of coronavirus S&M policies and weekly changes in per capita COVID-19 confirmed cases, even with Taiwan and Macao removed from the analysis.

This does not mean strict S&M policies cause a rise in new COVID-19 cases. It merely reflects that countries hit hardest by the virus were impelled to adopt stricter lockdown policies. As the coronavirus continued to rise in the midst of those policy adoptions, countries respond accordingly by increasing the strictness of those policies.

Figure 3 below shows a similar pattern between the Stringency Index and weekly per capita changes in COVID-19 deaths. Though not statistically significant, it is interesting to note that Sweden is an outlier in this graph. Sweden chose a less strict S&M path and experienced coronavirus outcomes no different than some countries that pursed must stricter policies. In contrast, New Zealand, South Korea, Hong Kong, and Singapore chose strict S&M policies and achieved fewer coronavirus deaths per capita. [Soon we will better know the differences in economic outcomes in these countries — which may or may not offer some rationalization for Sweden’s deviant policy choices.]

Figure 3: The Relationship between the Stringency Index and weekly changes in COVID-19 Deaths (per 1 million people)

While the data like that in Figures 2 and 3 are often used by lockdown cynics to argue against such policies — and, full disclosure, I believe the final words on the effectiveness of lockdown and other S&M policies have not been close to being written — these charts tell us nothing about the impact of these policies.

We need to look at the data over time (I choose weekly-level data to eliminate some of the noise inherent in the coronavirus daily data) and see if there are statistically significant relationships between the strictness of S&M policies and coronavirus outcomes. For this effort, I focus mostly on weekly changes in COVID-19 cases (per 1 million people) in countries known to have eventually implemented sophisticated, wide-scale testing COVID-19 testing programs.

S&M Policies & Changes in COVID-19 Cases

The Appendix (below) contains cross-correlation function (CCF) plots for time lags in the Stringency Index and weekly changes in COVID-19 cases per capita for all 29 countries. However, for this essay I will highlight those countries most illustrative of this common relationship in the data: There is a contemporaneous, positive correlation between the strictness of government S&M policies and changes in COVID-19 cases.

But there is also another consistent feature in the data: Changes in COVID-19 cases are negatively associated with the strictness of government S&M policies around three weeks prior.

We can’t conclude for certain these government S&M policies are causing these declines in COVID-19 cases, but that is the clear implication. We also can’t say anything about the relative size of this impact, assuming it is causal.

How to Read CCF Plot: The cross correlation function is the correlation between the observations of two time series Xt and Yt, separated by k time units (the correlation between Yt+k and Xt). In this analysis, Y is the change in confirmed COVID-19 cases and X is the level of the Stringency Index. We use the cross correlation function to determine whether there is a relationship between two time series. To determine whether a relationship exists between the two series, look for a large correlation, with the correlations on both sides that quickly become non-significant. This plot also requires that the series are stationary and one is white noise.

The change in confirmed COVID-19 cases (Y) and the level of the Stringency Index (X) variables were first differenced prior to running the CCF plots in order to make the series stationary.

Figure 4: CCF Plot for Total Sample of 29 Countries (Change in Confirmed Cases and Stringency Index)

The CCF plots for Germany and Austria demonstrate this relationship at the country-level and that is roughly seen to various degrees for most of the 29 countries (see Figures 4 and 5).

Figure 5: CCF Plot for Germany (Change in Confirmed Cases and Stringency Index)

Figure 5: CCF Plot for Austria (Change in Confirmed Cases and Stringency Index)

While the CCF plots are suggestive of a meaningful relationship between S&M policies and changes in COVID-19 cases, we don’t know the strength of that association relative to other factors or the specific S&M policies that are most effective in containing the coronavirus.

Those questions won’t be definitively answered here, but we can get some clues.

Utilizing the panel data structure of our dataset (i.e., repeated measures of the same countries over time), I estimated a panel regression models with changes in COVID-19 cases as the dependent variable and the Stringency Index (lagged 0 and 3 months) and time (in weeks) as the independent variables. Dummy variables were also included for each country.

Figure 6 shows the statistical code used to generate the linear model and its output (in SPSS).

Figure 6: Panel Regression Model for Weekly Changes in COVID-19 Cases

The first table of interest in Figure 6 is the “Tests of Between-Subjects Effects.” All of the independent variables are statistically significant at the 0.05 alpha-level, except for time (WEEK).

The “partial ETA squared” column indicates the effect size for each independent variable and the sum effect of the 29 countries. By far, the sum of the country-specific effects (eta = 0.341) are most powerfully associated with changes in COVID-19 cases. Some countries have simply done a better job than others in implementing their S&M policies. Among the worst performers in that regard is the U.S., whose effect is contained in the intercept parameter (a = 613.2). In other words, compared to the average country in an average week, the U.S. has more 613 new COVID-19 cases per 1 million people.

In America’s defense, we have 50 different states (and the District of Columbia) implementing 50 different coronavirus S&M policies, with minimal central government control (compared to governments in other advanced economic countries).

The coronavirus pandemic may be one case where central government planning is an advantage.

The “Parameter Estimates” table reveals that the significant independent variables are in the expected direction. For example, the parameter for the Stringency Index (lagged 3 months) is negative (b = -0.399). When the Stringency Index goes up, COVID-19 cases go down.

The eta-squared (i.e. effect size) of the Stringency Index (lagged 3 months) is relatively small (eta = 0.061) compared to the country-specific effects (eta = 0.341), but that is in part due to the imperfect measurement of S&M policy strictness contained in the Stringency Index. In other words, an 80 index score in Germany is not necessarily the same as an 80 index score in the U.S. or Spain.

Unfortunately, the overall fit of the model (adjusted R-square = 0.375) also suggests S&M policies do not explain as much of the variation in new COVID-19 cases across countries as we would hope.

Clearly, the spread of the coronavirus is harder to control than governments would like (see Figure 2 above). Among the 29 countries analyzed in this essay, a few governments are doing it well (Taiwan, New Zealand, South Korea, Japan, Australia, Greece, Finland, Norway), and a few others are doing it less poorly (Germany, Denmark, Canada, Austria). But the rest are struggling.

Final Thoughts

With the recent death of Ruth Bader Ginsburg and the political tussle over President Trump’s SCOTUS nominee and resulting confirmation process, few realize another political tsunami may hit on October 2nd — the day the U.S. Commerce Department releases the 2020 Q2 GDP numbers at the state-level.

While no single economic data release can definitely answer the question — How have coronavirus suppression and mitigation policies affected the aggregate economy? — this upcoming data release should offer our best, most comprehensive state-level picture of the coronavirus pandemic’s impact on economic activity. And, inevitably, detailed comparisons of “red” state and “blue” state outcomes will ensue, along with the predictable political noise.

Admittedly and with deep regret, the conclusions drawn here about the positive impact of S&M policies on the spread of the coronavirus do not factor in their significant economic and social costs. Without conducting a fully-specified tradeoff analysis between S&M policies and their economic consequences, policymakers are ill-equipped to select the most effective measures that both contain the coronavirus and allow as much normal economic activity as possible.

Up to now, the news media, scientists, policy analysts, and political elites continue to come up short in this effort.

With the October 2nd release of U.S. state-level  GDP data, hopefully this neglect will be reversed, even if the data’s political implications help one party more than the other.

Forgive me if I keep my expectations low in that regard.

  • K.R.K.

Comments can be sent to: nuqum@protonmail.com
or DM me on Twitter at: @KRobertKroeger1

 

Appendix

 

“Cuties” and the TikTokification of Childhood

By Kent R. Kroeger (Source: NuQum.com; September 16, 2020)

Real people. Real videos.

That’s the tagline for TikTok, the video-sharing social networking service owned by ByteDance, a Beijing-based internet technology company founded in 2012. Its users are able to create 3 to 60 second videos, often including simple special effects designed to attract viewers and encourage broad-based sharing across the platform.

It sounds innocent enough, right? Unfortunately, in the hands of regular people, its frequently a dumping ground for some of humanity’s worst instincts and obsessions.

Along with similar social media services — such as Instagram — TikTok has become an attractive landing spot for millions of mostly unfunny (frequently obscene) amateur videos. It’s a cesspool of self-indulgent nonsense.

In other words, a perfect reflection of today’s popular culture.

Yes, occasionally these social media videos are clever, usually involving lip-syncing and/or dancing (see here), but more often are sad attempts at fleeting fame by celebrity-wannabes (see here). And far too often these videos are sexually explicit.

Its the latter case that provides the indirect subtext to this year’s most controversial film, Cuties-a French film currently available on Netflix. According to the internet-based entertainment service, the film is a “coming-of-age” story about an 11-year-old French-Senegalese girl, Ami, who must deal with the combined stresses of her father bringing a second wife into her home (her family is Muslim), coping with the pressures of a being a pre-teen in a new school, and a growing awareness of her burgeoning femininity.

Ami’s coping method? Joining a group of “free-spirited” dancers named “the cuties” at school.

With that description, you might think Cuties is something you’d find on The Disney Channel. However, if you thought that, you would be very wrong.

Very wrong.

Congresswoman Tulsi Gabbard (D-HI) recently posted her opinion of the film on Twitter:

“Child porn Cuties will certainly whet the appetite of pedophiles and help fuel the child sex trafficking trade. One in four victims of trafficking are children. It happened to my friend’s 13 year old daughter. Netflix, you are now complicit. #CancelNetflix”

That is a harsh indictment. But could the movie really be that offensive? It is, after all, on Netflix. Offensive content and child porn are two different things. As a libertarian, I may find something offensive, but my basic instinct is to protect the right of free expression. For someone to call Cuties ‘child porn’ is an extraordinary charge.

Gabbard is not alone in that opinion. Texas Senator Ted Cruz recently sent a letter to U.S. Attorney General William Barr asking for the U.S. Justice Department to investigate the production of Cuties and Netflix’s distribution of the film, writing:

“The film routinely fetishizes and sexualizes these pre-adolescent girls as they perform dances simulating sexual conduct in revealing clothing, including at least one scene with partial child nudity. These scenes in and of themselves are harmful. And it is likely that the filming of this movie created even more explicit and abusive scenes, and that pedophiles across the world in the future will manipulate and imitate this film in abusive ways.”

In other words, Cruz is concerned that, in addition to the finished product itself, child abuse may have occurred during the filming process. What was left on the editing room floor? And what did the director and producers do to elicit these behaviors from underage girls?

If I were answering the latter question, I’d say spend 30 minutes on TikTok and you’ll find almost all of those dance moves in Cuties (“twerking” being just one example) openly available for imitation by young girls all over the world. A director doesn’t need to teach today’s young girls how to dance like this, they already are.

That is essentially the line of argument the movie’s director, Maïmouna Doucouré, offered in her recent Washington Post editorial piece:

I was at a community event in Paris a few years ago when a group of young girls came on the stage dressed and dancing in a very risque way. They were only 11 years old, and their performance was shocking. Curious to understand what was happening on that platform, I spent the next year and a half interviewing more than a hundred 10- and 11-year-old girls across the city.
The result was my movie “Mignonnes,” or “Cuties” in English. I wanted to make a film in the hope of starting a conversation about the sexualization of children. The movie has certainly started a debate, though not the one that I intended.
Puberty is such a confusing time. You are still a child, with all that wonderful naivete and innocence, but your body is changing, and you’re self-conscious and curious about its impact on others all at the same time.
The stories that the girls I spoke to shared with me were remarkably similar. They saw that the sexier a woman is on Instagram or TikTok, the more likes she gets. They tried to imitate that sexuality in the belief that it would make them more popular. Spend an hour on social media and you’ll see preteens — often in makeup — pouting their lips and strutting their stuff as if they were grown women. The problem, of course, is that they are not women, and they don’t realize what they are doing. They construct their self-esteem based on social media likes and the number of followers they have.
To see these youngsters put so much pressure on themselves so early was heartbreaking. Their insights and experiences with social media informed “Cuties.”
And that’s why I made “Cuties”: to start a debate about the sexualization of children in society today so that maybe — just maybe — politicians, artists, parents and educators could work together to make a change that will benefit children for generations to come. It’s my sincerest hope that this conversation doesn’t become so difficult that it too gets caught up in today’s “cancel culture.”

Netflix has said pretty much the same thing: Cuties is social commentary AGAINST sexualizing young girls. This is a film about these pressures being experienced by young girls everywhere.

Both sides can’t be right. Can they?
I had no choice but to watch Cuties myself, with a stopwatch in hand (Yes, a stopwatch) and a pad of paper to jot down brief descriptions of the most problematic scenes.
Here are my impressions from the film…
First, there were only 6 minutes within the 96-minute film where I felt a line had been crossed by the filmmaker. One offensive scene in particular had the Cuties dance team performing sex acts while wearing minimal clothing. In other scenes, often cited by the film’s critics, an 18-year–old girl (portraying a 15-year-old) is briefly topless and at one point the movie’s protagonist, Ami, after being humiliated at school, takes a selfie of her private parts and posts them on social media (though no actual nudity is seen).
For what its worth, the most offensive scene for me was near the end of the movie when Ami pushes one of her dance team members into a river, nearly killing her, and walks away showing no obvious regret. Any empathy I felt for the character of Ami up to that point evaporated.
Still, to the film’s credit, it did make the filmmaker’s opinion clear that Ami’s membership in the Cuties dance group was not, ultimately, a positive and empowering outlet for her.  After breaking down into tears during a Cuties on-stage performance and running home,  Ami is comforted by her mother who protects Ami from an aunt’s judgmental rant about Ami’s dance clothes. In the end, Ami is not forced to attend her father’s wedding to the second wife and, instead, puts on jeans and a t-shirt and goes out to play jump rope with friends.
Despite the movie’s offensive moments, my immediate impression of the film was, in fact, that it was a solid critique about the over-sexualization of young girls today, particularly the traumatizing impact it can have for girls growing up in traditionally conservative communities.
Yet, I had a lingering negative impression as well. The legitimate message of the film cannot be wholly detached from the offensive scenes in the film.
Are Gabbard and Cruz right, or is the director’s defense of the film on firmer ground? I despise censorship and will 99 times out of a 100 err on the side of freedom in such debates.
But I’m struggling to do it this time.
Forget the twerking in Cuties for a moment. Imagine if the movie had instead been a strident attack on sexual abuse against young girls. Just because young girls are sexually abused every day somewhere in the world doesn’t mean you can make a movie graphically showing young girls getting sexually abused.
Children must be protected–including protection from filmmakers with otherwise good intentions.
But Cuties didn’t have any explicit sex scenes, only implied sex–and even then the girls were clothed. Isn’t that fundamentally different from child porn?
I genuinely don’t know.
Keeping in mind that I am not a lawyer, let us look at actual U.S. law and how it addresses child pornography.
According to the U.S. Justice Department, “Images of child pornography are not protected under First Amendment rights, and are illegal contraband under federal law. Section 2256 of Title 18, United States Code, defines child pornography as any visual depiction of sexually explicit conduct involving a minor (someone under 18 years of age).  Visual depictions include photographs, videos, digital or computer generated images indistinguishable from an actual minor, and images created, adapted, or modified, but appear to depict an identifiable, actual minor.  Undeveloped film, undeveloped videotape, and electronically stored data that can be converted into a visual image of child pornography are also deemed illegal visual depictions under federal law.”
The basic definitions of child pornography are contained in Section 2256 of Title 18 in U.S. Code:
Given what I saw in Cuties, as a non-lawyer, I am drawn to the second line in Section 2256: “Sexually explicit conduct” means actual or simulated.
Is there any other way of describing the  most explicit dance scenes in Cuties than as a group of underage girls simulating sex.

As brief as those scenes were in Cuties, I’m reminded of the late Supreme Court Justice Potter Stewart’s definition of ‘pornography’ when I conclude: There are scenes in Cuties that look like child pornography to me.

Do we live in a country where the law allows adults to coach and direct children on how to simulate sex acts? I want to believe the answer is “No.” Its one thing that children learn of these behaviors through social media and mimic them on their own. It is entirely different — and far more disturbing— for an adult to participate in this process, regardless of their intent.

Doucouré understandably points out in her Washington Post editorial that Cuties was approved by the French government’s child protection authorities, but what is that endorsement worth? The the issue here is U.S. law, not French.
In a country that continues to force the imprisonment of Julian Assange, a publisher of whistleblower information that embarrassed the U.S. government, I do not believe free speech is alive and well in the U.S. today. To the contrary, it is under a daily siege, abandoned by a mainstream media complex that attends to financial bottom lines at the expense of the First Amendment.
Only an establishment tool believes the U.S. has fully protected freedoms of speech and press.
Nonetheless, I cannot abandon my tentative belief that Cuties may have crossed one of those few lines allowing the government to intervene in the censorship of a creative property.
Cuties was offensive, even as it offered an insightful critique of modern society and how hard it is for young girls to navigate our over-sexualized culture. These two beliefs are not contradictory.
I understand why some are defending this movie. But I also understand the outrage. It is legitimate and not powered by some QAnon-backed hate campaign. In my opinion, Cuties violates a common understanding of what constitutes child pornography.
Equally important, the controversy over Cuties is one our society needs to have and should not be short-circuited by a partisan, unproductive decent into slander and name-calling.
– K.R.K.
Send comments to: nuqum@protonmail.com
or DM me on Twitter at: @KRobertKroeger1

Did Israel loosen coronavirus restrictions too soon?

Diagram above shows the number of COVID-19 cases and deaths in Israel as of September 8, 2020. (Image by Hbf878)

By Kent R. Kroeger (Source: NuQum.com; September 14, 2020)

If one were to pick a country best equipped to deal with the challenges of the coronavirus, one’s first choice might have been Israel.

This is a small-population country (8.9 million) that knows how to control the movement of people and commerce across and within its borders. In 2011, according to the United Nations Office for the Coordination of Humanitarian Affairs (OCHA), Israel had approximately 500 roadblocks and checkpoints in the West Bank alone, not including the almost 500 “flying” (or “random”) roadblocks that exist at any given moment in time.

Israel also has a world-class, universal health care system–ranked 4th among 48 nations, according to a 2013 Bloomberg study in which the  U.S. ranked near the bottom. Only Hong Kong, Singapore and Japan ranked higher than Israel.

On a indirect level, Israel ranks high among the advanced economies for its science and technological innovation–a quality that would, presumably, be of value during a pandemic in which the antagonizing pathogen is largely unfamiliar.

Israel should have been an exemplar during this health crisis–and early in the pandemic, the country was just that.

“Israel beat the coronavirus. Or at least that’s what the public were led to believe. Benjamin Netanyahu held a press conference to crow about Israel’s ‘great success story’ and how foreign leaders the world over were calling him for advice on how to battle the pandemic,” writes Middle East-focused journalist Neri Zilber. “Fast forward two months and there are over a thousand new infections per day. On a per capita basis the curve is a sheer straight line hurtling upwards to American and Brazilian levels.”

Figure 1 (below) shows the two coronavirus waves that have hit Israel. The first wave started in March and peaked at around 15 deaths-a-day in mid-April, and near the end of May the pandemic appeared to be a thing of the past.

Figure 1: COVID-19 Cases and Deaths in Israel (through 8 Sep 2020)

However, in early-June, Israel’s new case numbers began to rise again and rose precipitously through July. Likewise, by a lag of a week or two, the number of new COVID-19 deaths similarly rose.

What went wrong in Israel?

The answers may offer valuable insights to the rest of the world.

For starters, we are dealing with a virus that doesn’t give a damn about the politicians, media stars and policy analysts trying to leverage the pandemic for professional gain. The coronavirus spreads because it can. Yes, policies matter–but only to a degree.

The epidemiological textbooks argue that suppression and mitigation policies–particularly with highly contagious viruses like SARS-CoV-2 (the coronavirus)–are intended to “flatten the curve” in order to lessen the short-term burden on hospitals until a vaccine is available and/or the population attains “herd immunity” levels.

But as WHO Director General Tedros Adhanom recently said, a vaccine for the coronavirus will not necessarily be a “silver bullet” allowing us to go back to normal.

Should a vaccine be developed by the end of the year, it may not be 100 percent effective. According to the U.S. Centers for Disease Control and Prevention (CDC), since 2009, flu vaccines have been no more than 60 percent effective for any given year.

“It’s dangerous for us to be putting all of our eggs in one basket – that a vaccine will become available and this is going to save the day – and forget to remain focused on what we should be doing this very moment,” says Vaccinologist Jon Andrus, an adjunct professor of global health at George Washington University’s Milken Institute School of Public Health.

Other epidemiologists echo Andrus’ sentiment, eager to remind us that widespread testing, case identification and tracing, wearing masks, maintaining hygiene and social distancing cannot be neglected even after a safe and effective vaccine becomes widely available.

In Israel’s case, the coronavirus’ summer resurgence has multiple possible causes. Among the earliest cited was the reopening of schools at the end of May.

One study on the resurgence–conducted by Israel’s Health Ministry–showed educational institutions were the most likely location for spreading the virus, accounting for about 10 percent of documented cases.

But epidemiologists have identified additional possible sources of Israel’s second coronavirus wave, such as:

(1) an increased number of public gatherings, particularly weddings. Between June 15 and June 25 there were 2,092 weddings in Israel–a significant spike over previous weeks,
(2) the Israeli government easing its stringent lockdown policies in late May (see Figure 2 below),
(3) an inadequate network of testing labs and technicians able to track and contain the virus,
(4) the failure of the Netanyahu government to prepare Israelis for the potential return to stringent lockdown policies should a resurgence of the virus occur,
(5) the failure to enlist the logistical expertise of the Israeli Defense Forces (IDF) earlier,
(6) and, perhaps the most politically sensitive issue in Israel during this pandemic, is the disproportionate number of coronavirus cases and deaths occurring in Israeli Arab and Jewish ultra-Orthodox (haredi) communities–which have a higher incidence of large families and where people are more likely to attend large religious and cultural gatherings.
Figure 2: COVID-19 Policy Responses by Israel (Containment and Health Index / Lockdown Stringency Index)

That last point is particularly contentious as it has led some in Israel to question why the Israel’s Health Ministry loosened restrictions on the  number of worshipers allowed in synagogues prior to the Tisha B’Av fast (which occurred on July 29-30). There are indications that religious gatherings associated with the Tisha B’Av fast may have been a significant avenue for the virus’ spread within the ultra-Orthodox community.

Israeli research has persuasively already shown that synagogues were a common place for the coronavirus to spread during the first wave of the pandemic–accounting for nearly a quarter of known cases not brought in from abroad or contracted at home, according to a report published by Israel’s Coronavirus National Information and Knowledge Center.

Did Israel loosen restrictions too soon?

The apparent answer to this question is “Yes.”

Figure 2 offers visual (though not definitive) evidence that the resurgence of the coronavirus in June and July was preceded by the loosening of coronavirus restrictions, starting in late-April.

Still, we need more systematic evidence showing that changes in public policy have a measurable, meaningful impact on coronavirus outcomes (i.e., cases and deaths).

Using two policy indexes developed by the OxCGRT Project, I analyzed Israel’s policy responses to the coronavirus over time and found a significant, negative relationship between increases in Israeli coronavirus policy measures and decreases in daily coronavirus cases.

For some background, the OxCGRT project calculates a number of policy indexes related to the coronavirus. One index is the Government Stringency Index, a composite measure of nine response metrics: School closures; workplace closures; cancellation of public events; restrictions on public gatherings; closures of public transport; stay-at-home requirements; public information campaigns; restrictions on internal movements; and international travel controls. The index is calculated as the mean score of the nine metrics, each taking a value between 0 and 100. A higher score indicates a stricter government response (i.e. 100 = strictest response). If policies vary at the subnational level, the index is shown as the response level of the strictest sub-region.

The other index of interest is the Containment and Health Index, a composite measure of eleven coronavirus policy response metrics, building on the Government Stringency Index by adding two additional indicators: Testing policy and the extent of contact tracing.

As the two indexes are highly correlated (see Figure 2), for the following analysis I use only the Containment and Health Index.

Additionally, I aggregated the daily coronavirus case data to the weekly level to help reduce data noise. This left me with a time-series data set containing 31 weeks of data.

When comparing daily occurrences of COVID-19 cases in Israel and the country’s policy efforts to control the virus, there was a significant (negative) relationship between those two variables in the fourth, fifth, and sixth weeks after implementation of those policies (see Figure 3).  As coronavirus suppression and mitigation policies are increased, new daily coronavirus cases go down. More simply, it takes at least a month before coronavirus containment efforts have a measurable impact on daily changes in new coronavirus cases in Israel.

Figure 3: Cross-correlation between COVID-19 Policy Responses by Israel (Containment and Health Index / Lockdown Stringency Index)

 

Did Israel relax its coronavirus containment policies too soon?

The answer is a definitive ‘Yes.’

Based on the data, had Israel increased its coronavirus containment efforts at the earliest signs of a second wave increase (i.e, mid-June), the country would probably not be suffering the current increases the country it is now witnessing.

That conclusion is mere conjecture, perhaps, but the dynamics seem rather clear: It takes around a month for coronavirus policies to have an impact and, if true, requires a level of “policy patience” seemingly incompatible with today’s current political environment.

Israel is far from alone in the coronavirus crisis. My hope is that their experience will help inform  other countries on how aggressive they need to be to control this virus.

  • K.R.K.

Send comments to:  nuqum@protonmail.com
or DM me on Twitter at: @KRobertKroeger1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Who is the bigger liar? Joe Biden or Donald Trump?

By Kent R. Kroeger (Source: NuQum.com; September 1, 2020)

As we head into the peak season for political lies, half-truths and pre-planned obfuscations, I dug out an old article I wrote a couple of years ago about how political lies and deceits are ill-defined and typically misconstrued in the national news media.

This problem was particularly evident during the news coverage of the Republican National Convention last week when President Donald Trump’s acceptance speech produced a predictable flurry of stories about how the “lies” in his speech.

Trump’s parade of desperate lies reveals one big and awful truth(Wash. Post)

Fact check: Trump makes more than 20 false or misleading claims in accepting presidential nomination (CNN)

Trump’s Acceptance Speech Was 70 Minutes of Rambling Lies(Vice.com)

His reported lies ranged from claiming the U.S. has “the largest and most advanced (COVID-19) testing system in the world” (Fact: The U.S. has conducted more COVID-19 tests than any other country outside of China) to suggesting that the Paycheck Protection Program for small businesses during the coronavirus pandemic has “saved or supported more than 50 million American jobs” (which is most likely an exaggeration).

Oddly, the news media ignored one of Trump’s genuine untruths spoken during his acceptance speech: That a President Biden would bring socialism to America.

Joe Biden is as socialist as I am a Mongolian sheep herder.

On the topic of Joe Biden, the same news media that torched Trump for the truthfulness of his acceptance speech was noticeably silent on the Democratic nominee’s own acceptance speech.

Granted, Biden’s speech contained little concrete information and so few testable propositions that it was impossible for anyone to judge its veracity.

But there was one moment that forced me to jump out of my Mr. Bubble bath as I watched his speech:

“(This election) is about winning the heart and, yes, the soul of America,” intoned Biden during his Democratic Party acceptance speech. “Winning it for the generous among us, not the selfish…For all the young people who have known only an America of rising inequity and shrinking opportunity (emphasis mine).”

No reason to fact-check that statement, right? Except for the fact that eight of those years of growing wealth inequality were on the Obama-Biden administration’s watch. Deception doesn’t always require telling factual lies. Sometimes you just have to put facts in the wrong frame and context.

Image for post
Source: Federal Reserve of St. Louis

If the percentage of wealth owned by the Top 1 percent matters, it is hard for me to take Joe Biden seriously on economic inequality. Since 1989, when reliable data collection started on the issue, one president stands out as doing more for the Top 1 percent than any other: Barack Obama. It’s not even close.

In the second quarter of 1989 (during the George H.W. Bush administration), the Top 1 percent owned 23.5 percent of all U.S. wealth. In the first quarter of 2020, that percentage is now 31.2 percent.

Where it gets interesting is in how this percentage has changed across presidential administrations. Assuming the first two quarters of any administration belongs to the prior administration, the differences across the last five administrations on wealth inequality are stark (see Figure 1).

Figure 1: Change in % of U.S. Wealth Controlled by Top 1% (by Presidential Administration, 1989 to Q1 2020, unadjusted for term length)

Image for post

Under the Obama administration, the Top 1 percent gained an additional 4.4 percent of the nation’s total wealth. The next closest administration for helping the extremely wealthy is George H.W. Bush’s four-year tenure at 1.8 percent — and had he been president for Obama’s eight years this number would project to 3.6 percent.

And how friendly has Trump’s administration been to the Top 1 percent?

If we include 2020’s first quarter — the first measurement period in which the coronavirus makes an impact on the U.S. economy — the Trump administration has not been nice to the wealthy. Under Trump, they’ve lost 0.8 percent of the nation’s total wealth, mostly due to dramatic declines in the equity markets.

But that comparison is not fair to the Obama administration. Trump hasn’t served an eight-year term and the coronavirus pandemic masks the genuine gains the wealthiest Americans made prior to 2020.

If we judge Trump on the data prior to the coronavirus pandemic (i.e., Q3 2017 to Q4 2019), a more accurate picture emerges.

Excluding 2020, America’s wealthiest one percent have seen a 0.7 percentage point increase in their share of U.S. wealth. Projecting that number over an eight-year term, the Trump administration would be on pace to increase that share by 2.2 percentage points.

I don’t care what your political leanings are, Barack Obama did disproportionately more for America’s wealthiest than any other president in recent history. Trump looks only marginally better in comparison.

And this money grab by the wealthy is not a function of economic growth.

Under Bill Clinton, the U.S. economy grew by 33.6 percent — more than any other recent president, even after adjusting for term length — and, yet, the Top 1 percent gained only 1.4 percentage points more of the nation’s wealth.

In other words, Bill Clinton grew the U.S. economy for everyone, while Barack Obama disproportionately grew it for the Top 1 percent.

You would think the national news media would call out Joe Biden on his claim that he was for America’s most economically dispossessed.

But, of course, they didn’t.

And why should we hold Biden accountable for what happened under the Obama administration? Beyond the fact that Biden continuously touts his role during the Obama years, the reality is that Obama had a heavy hand in ensuring Biden’s nomination is indisputable.

According to the New York Times, “With calibrated stealth, Mr. Obama has been considerably more engaged in the campaign’s denouement than has been previously revealed, even before he endorsed Mr. Biden on Tuesday.

I’m not sure what ‘denouement’ means, but I’m pretty sure it means Obama helped tipped the scales in Biden’s favor during the Democratic Party’s nomination race. And that most likely means Biden is beholden to the same donor class that helped make Obama a two-term president.

So what is the bigger falsehood? That Trump has led a strong federal effort to combat the coronavirus, or that Joe Biden is a nemesis to the super-wealthy?

I know my answer.

  • K.R.K.

Comments on this article can be sent to: kroeger98@yahoo.com
or DM me on Twitter at: @KRobertKroeger1