What causes such big differences in cities' tolls?

What causes such big differences in cities’ tolls?


COVID-19 data as of May 31, 2020. Credit: The Conversation, CC-BY-ND Source: U.S. Census, NOAA, City of New York, City of San Francisco

San Francisco and New York City both reported their first COVID-19 cases during the first week of March. On March 16, San Francisco announced it was ordering residents to stay home to avoid spreading the coronavirus, and New York did the same less than a week later. But by the end of May, while San Francisco had attributed 43 deaths to COVID-19, New York City’s death count was over 20,000.

What explains the stark difference in COVID-19-related deaths between these two cities? Is the delay in the stay-at-home order responsible? What about city-specific measures taken to mitigate COVID-19 before the order? Is something else going on?

The divergent trajectories of San Francisco and New York City, while especially striking, are not unique. Worldwide, COVID-19 is having highly variable effects. Within the U.S., infections, hospitalizations and deaths have skyrocketed in nearly all major cities in the Northeast while remaining fairly low in some other metropolitan centers, such as Houston, Phoenix and San Diego.

How cities and states implemented public health interventions, such as school closures and stay-at-home orders, has varied widely. Comparing these interventions, whether they worked and for whom, can provide insights about the disease and help improve future policy decisions. But accurate comparisons aren’t simple.

The range of COVID-19 interventions implemented across the U.S. and worldwide was not random, making them difficult to compare. Among other things, population density, household sizes, public transportation use and hospital capacity may have contributed to the differences in COVID-19 deaths in San Francisco and New York City. These sorts of differences complicate analyses of the effectiveness of responses to the COVID-19 pandemic.

As a biostatistician and an epidemiologist, we use statistical methods to sort out causes and effects by controlling for the differences between communities. With COVID-19, we’ve often seen comparisons that don’t adjust for these differences. The following experiment shows why that can be a problem.

Coronavirus deaths in San Francisco vs. New York: What causes such big differences in cities' tolls?
Credit: Laura Balzer/Github, CC BY-ND

City simulations reveal a paradox

To illustrate the dangers of comparisons that fail to adjust for differences, we set up a simple computer simulation with only three hypothetical variables: city size, timing of stay-at-home orders and cumulative COVID-19 deaths by May 15.

For 300 simulated cities, we plotted COVID-19 deaths by the delay time, defined as the number of days between March 1 and the order being issued. Among cities of comparable size, delays in implementing stay-at-home orders are associated with more COVID-19 deaths—specifically, 40-63 more deaths are expected for each 10-day delay. The hypothetical policy recommendation from this analysis would be for immediate implementation of stay-at-home orders.

Now consider a plot of the same 300 simulated cities that doesn’t take city size into consideration. The relationship between delays and deaths is reversed: Earlier implementation in this simulation is strongly associated with more deaths, and later implementation with fewer deaths. This apparent paradox occurs because of the causal relationships between city size, delays and COVID-19 deaths. Strong connections or associations between two variables don’t guarantee that one variable causes another. Correlation does not imply causation.

Failing to properly address these relationships can create misperceptions with dramatic implications for policymakers. In these simulations, the analysis that fails to consider city size would lead to an erroneous policy recommendation to delay or never implement stay-at-home orders.

Coronavirus deaths in San Francisco vs. New York: What causes such big differences in cities' tolls?
Credit: Laura Balzer/Github, CC BY-ND

It gets more complicated

Of course, causal inference in real life is more complicated than in a computer simulation with only three variables.

In addition to confounding factors like community size, substantial evidence suggests that public health interventions do not protect all people equally.

In San Francisco, stark disparities have emerged. For example, comprehensive testing of the Mission District revealed 95% of people testing positive were Hispanic. Factors like socioeconomic status, race and ethnicity, and many others, vary widely among communities and can impact COVID-19 infection and death rates. Differences among community residents makes appropriate interpretation of comparisons, such as between San Francisco and New York, even more difficult.

So how do we effectively learn in the current environment?

While especially pressing now, the analytic challenges posed by COVID-19 are not new. Public health experts have long used data from nonrandomized studies—even in the midst of epidemics. During the Cholera outbreak in London in 1849, John Snow, famed in epidemiologic circles, used available data, simple tools and careful consideration to identify a water pump as a source of disease spread. Evidence-based decisions require both data and appropriate methods to analyze data.

Cities and communities worldwide vary in important ways that can complicate public health research. The rigorous application of causal inference methods that can take into account differences between populations is necessary to guide policy and to avoid misinformed conclusions.


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Coronavirus deaths in San Francisco vs. New York: What causes such big differences in cities’ tolls? (2020, June 2)
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How our brains can be manipulated to tribalism

How our brains can be manipulated to tribalism


Credit: CC0 Public Domain

Tribalism has become a signature of America within and without since the election of President Trump. The nation has parted ways with international allies, left the rest of the world in their effort to fight the climate change, and most recently the pandemic, by leaving the World Health Organization. Even the pandemic was not a serious issue of importance to our leaders. We did not care much about what was happening in the rest of the world, as opposed to the time of previous pandemics when we were on the ground in those countries helping block the progress so long as it was China’s or the European Union’s problem. This marks drastic change from previous U.S. altruistic attitude, including during the World War II.

Whether Trump is the cause or effect of the changes in America’s collective attitude, an attribute of our current president is his eagerness and ability to use fear for intimidation of those who disagree with him, and subordination and shepherding of those who support him.

Fear is arguably as old as life. It is deeply ingrained in the living organisms that have survived extinction through billions of years of evolution. Its roots are deep in our core psychological and biological being, and it is one of our most intimate feelings. Danger and war are as old as human history, and so are politics and religion.

I am a psychiatrist and neuroscientist specializing in fear and trauma, and I have some thoughts on how politics, fear and tribalism are intertwined in the current events.

We learn fear from tribe mates

Like other animals, humans can learn fear from experience, such as being attacked by a predator, or witnessing a predator attacking another human. Furthermore, we learn fear by instructions, such as being told there is a predator nearby.

Learning from our tribe mates is an evolutionary advantage that has prevented us from repeating dangerous experiences of other humans. We have a tendency to trust our tribe mates and authorities, especially when it comes to danger. It is adaptive: Parents and wise old men told us not to eat a special plant, or not to go to an area in the woods, or we would be hurt. By trusting them, we would not die like a great-grandfather who died eating that plant. This way, we accumulated knowledge.

Tribalism has been an inherent part of human history, and is closely linked with fear. There has always been competition between groups of humans in different ways and with different faces, from brutal wartime nationalism to a strong loyalty to a football team. Evidence from cultural neuroscience shows that our brains even respond differently at an unconscious level simply to the view of faces from other races or cultures.

At a tribal level, people are more emotional and consequently less logical: Fans of both teams pray for their team to win, hoping God will take sides in a game. On the other hand, we regress to tribalism when afraid. This is an evolutionary advantage that would lead to the group cohesion and help us fight the other tribes to survive.

Tribalism is the biological loophole that many politicians have banked on for a long time: tapping into our fears and tribal instincts. Abuse of fear has killed in many faces: extreme nationalism, Nazism, the Ku Klux Klan and religious tribalism have all led to heartless killing of millions.

The typical pattern is to give the other humans a different label than us, perceive them as less than us, who are going to harm us or our resources, and to turn the other group into a concept. It does not have to necessarily be race or nationality. It can be any real or imaginary difference: liberals, conservatives, Middle Easterners, white men, the right, the left, Muslims, Jews, Christians, Sikhs. The list goes on and on.

This attitude is a hallmark of the current president. You could be a Chinese, a Mexican, a Muslim, a Democrat, a liberal, a reporter or a woman. So long as you do not belong to his immediate or larger perceived tribe, he portrays you as subhuman, less worthy, and an enemy.

Retweeting “The only good Democrat is a dead Democrat” is a recent example of how he feeds, and feeds off of such divisive and dehumanizing tribalism.

When building tribal boundaries between “us” and “them,” politicians have managed very well to create virtual groups of people that do not communicate and hate without even knowing each other: This is the human animal in action!

Fear is uninformed, illogical and often dumb

Very often my patients with phobias start with: “I know it is stupid, but I am afraid of spiders.” Or it may be dogs or cats, or something else. And I always reply: “It is not stupid, it is illogical.” We humans have different functions in the brain, and fear oftentimes bypasses logic. In situations of danger, we ought to be fast: First run or kill, then think.

This human tendency is meat to the politicians who want to exploit fear: If you grew up only around people who look like you, only listened to one media outlet and heard from the old uncle that those who look or think differently hate you and are dangerous, the inherent fear and hatred toward those unseen people is an understandable (but flawed) result.

To win us, politicians, sometimes with the media’s help, do their best to keep us separated, to keep the real or imaginary “others” just a “concept.” Because if we spend time with others, talk to them and eat with them, we will learn that they are like us: humans with all the strengths and weaknesses that we possess. Some are strong, some are weak, some are funny, some are dumb, some are nice and some not too nice.

Fear can easily turn violent

There is a reason that the response to fear is called the “fight or flight” response. That response has helped us survive the predators and other tribes that have wanted to kill us. But again, it is another loophole in our biology to be abused. By scaring us, the demagogues turn on our aggression toward “the others,” whether in the form of vandalizing their temples, harassing them on the social media, of killing them in cold blood.

When demagogues manage to get hold of our fear circuitry, we often regress to illogical, tribal and aggressive human animals, becoming weapons ourselves—weapons that politicians use for their own agenda.

The irony of evolution is that while those attached to tribal ideologies of racism and nationalism perceive themselves as superior to others, in reality they are acting on a more primitive, less evolved and more animal level.


The politics of fear: How it manipulates us to tribalism


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This article is republished from The Conversation under a Creative Commons license. Read the original article.The Conversation

Citation:
Trump, the politics of fear and racism: How our brains can be manipulated to tribalism (2020, June 2)
retrieved 2 June 2020
from https://medicalxpress.com/news/2020-06-trump-politics-racism-brains-tribalism.html

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part may be reproduced without the written permission. The content is provided for information purposes only.





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