The Math of Life and Death
Book Notes Written with a loving hand by kitt some time around 20:18 on 23 November 2020Oh, I enjoyed this book so much. I am on a roll with choosing non-fiction books that delight me. I strongly recommend this book for its exploration of various ways different areas of mathematics can help us understand the world around us. This book also delivers a whole bunch of (previously unknown to me) biases, all dealing with math, giving me even more joy.
In a very approachable way giving many examples from the real world and history (none of these "two trains are on tracks going in opposite directions at forty kilometers an hour" problems), the various chapters discuss exponential growth and decay (Chapter 1), sensitivity and specificity specifically in medicine (Chapter 2), how math (statistics, in particular) is used in legal matters (Chapters 3 and 4), different numbering systems (Chapter 5), algorithms in general and how they can apply to one's life (the 37% rule is a very common algorithm used to illustrate how algorithms can make our lives better, see also Algorithms to Live By), and the most relevant topic of 2020: mathematical epidemiology, or the topic of epidemics, pandemics, and the spread of disease.
I mean, discussions of false positives and false negatives, how one can intimidate jurors with numbers, how to interpret stats you read in the news (hint: context matters a LOT), an overview of virus transmission (asshat anti-vaxers not understanding that vaccines don't cause autism, a leaky intestinal system causes autism, but that's another line of research that didn't get earlier funding because Jenny McCarthy decided murdering thousands of children was a better "mother feeling," leaving scientists to debunk her shit first for public health before finding the true cause of autism, but here we are), and ideas that can help people live better lives.
One of the good things, for some people anyway, about the book is that there are very few equations in the book, making the book approachable to anyone who doesn't like, or thinks he can't do, math.
Strongly recommended. Fun, informative read.
The application of the God Equation can be seen as an attempt to take difficult life and death decisions out of our subjective hands and place them under the control of an objective mathematical formula. This point of view plays on the seeming impartiality and objectivity of mathematics, but neglects to recognize that the subjective decisions are simply being diverted out of sight in the form of judgments on quality of life and cost effectiveness thresholds at earlier stages of the decision making process.
Chapter 2, English version, not in the American version of the book
Mathematics, at its most fundamental, is pattern. Every time you look at the world you are building your own model of the patterns you observe.
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Refusing to believe reports of the core’s explosion, Akimov relayed incorrect information about the reactor’s state, delaying vital containment efforts. Upon eventually realizing the full extent of the destruction, he worked, unprotected, with his crew to pump water into the shattered reactor.
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The greater our acquaintance with the routines of everyday life, the quicker we perceive time to pass, and generally, as we age, this familiarity increases. This theory suggests that, to make our time last longer, we should fill our lives with new and varied experiences, eschewing the time-sapping routine of the everyday. Neither of the above ideas explains the almost perfectly regular rate at which our perception of time seems to accelerate. That the length of a fixed period of time appears to reduce continually as we age suggests an “exponential scale” to time.
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Today, more people in the world die from being overweight than from being underweight.
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The main problem with BMI is that it can’t distinguish between muscle and fat. This is important because excess body fat is a good predictor of cardiometabolic risk. BMI is not. If the definition of obesity were instead based on high-percentage body fat, between 15 and 35 percent of men with non-obese BMIs would be reclassified as obese. For example, “skinny-fat” individuals, with low muscle but high levels of body fat and consequently normal BMI, fall into the undetected “normal-weight obesity” category. A recent cross-population study of forty thousand individuals found that 30 percent of people with BMI in the normal range were cardiometabolically unhealthy. The obesity crisis may be much worse than our BMI-based figures suggest. However, BMI both under- and over-diagnoses obesity. The same study found that up to half of the individuals that BMI classified as overweight and over a quarter of BMI-obese individuals were metabolically healthy.
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Alternatively, by blowing as much air as you can into an empty airtight bag and then sealing and submersing it in water, you can use Archimedes’s principle to estimate your lung capacity a few weeks into your new exercise program.
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Using this idea, all Archimedes needed to do was to take a pan balance with the crown on one side and an equal mass of pure gold on the other. In air, the pans would balance. However, when the scales were placed underwater, a fake crown (which would be larger in volume than the same mass of denser gold) would experience a larger buoyant force as it displaced more water, and its pan would consequently rise. This principle from Archimedes is used to accurately calculate body fat percentage. A subject is first weighed in normal conditions, then reweighed while sitting completely submerged on an underwater chair attached to a set of scales. The differences in the dry and underwater weight measurements can be used to calculate the buoyant force acting on the individual while underwater, which can in turn be used to determine the person’s volume, given the known density of water. This volume, in conjunction with figures for the density of fat and lean components of the human body, can be used to estimate the body fat percentage and provide more accurate assessments of health risks.
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False alarms typically refer to an alarm triggered by something other than the expected stimulus. A staggering 98 percent of all burglar-alarm activations in the United States are thought to be false alarms. This prompts the question, Why have an alarm at all? As we get used to incorrect alerts, we become more reluctant to investigate their causes. Burglar alarms are by no means the only warnings with which we have become overfamiliar. When the smoke detector goes off, we are usually already opening a window and scraping the soot off our toast. When we hear a car alarm outside, very few of us will even get off the sofa and stick our heads outside to investigate. When alarms become an inconvenience rather than an aid, and when we no longer trust their output, we are said to be suffering alarm fatigue. This is a problem because situations in which alarms become so routine that we ignore them, or disable them completely, can be less sensible than not having the alarm in the first place,
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This trade-off exists because we are typically testing for proxies rather than the phenomena themselves. The test that misdiagnosed Mark Stern as HIV positive does not test for the HIV virus. Rather, it tests for antibodies that the body’s immune system raises in an attempt to fight off the virus. However, high HIV-associated antibody loads can be raised by something as innocuous as the flu vaccination. Similarly, most home pregnancy tests do not look for the presence of a viable embryo implanted in the woman’s womb. Typically, these tests look for elevated levels of the hormone HCG, produced after implantation of the embryo. Such proxy indicators are often called surrogate markers. Tests can be wrong because markers similar to the surrogate can trigger a positive result.
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For some tests, a more accurate version is not available. In these cases, we should remember that even a second run of the same test can dramatically improve the precision of its results. We should never be afraid to ask for a second opinion. Clearly, even doctors—the perceived experts—don’t always have the firmest grasp of the figures, despite the illusion of confidence they exude. Before you start to worry yourself unduly based on assertions of a single test, find out its sensitivity and specificity and work out the likelihood of an incorrect result. Question the illusion of certainty and take the power of interpretation back into your own hands.
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Two events are dependent if knowledge of one event influences the probability of the other. Otherwise they are independent. When presented with the probabilities of individual events, common practice is to multiply these probabilities together to find the probability of the combination of the events occurring.
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A suspect is found whose license plate matches the five digits remembered by the witness. If the suspect is innocent, then only ninety-nine other cars are out there, out of the 10 million cars on the road, whose plates match the first five digits. Therefore, the probability that the witness observed such a license plate if the suspect is innocent is 99/10,000,000, less than one in one hundred thousand (1/100,000). This tiny probability of seeing the evidence if the suspect is innocent seems to overwhelmingly indicate the suspect’s guilt. However, to assume so is to commit the prosecutor’s fallacy. The probability of seeing the evidence if the suspect is innocent is not the same as the probability of the suspect being innocent, once that piece of evidence has been observed. Recall that ninety-nine of the hundred cars that match the witness’s description do not belong to the suspect. The suspect is just one of a hundred people who drive such a car. The probability of the suspect’s guilt given their license plate, therefore, is just one in a hundred—exceedingly unlikely. Other evidence tying the suspect to the area of the crime or eliminating the other cars from being in the area would increase the probability of the suspect’s guilt. However, based on the single piece of evidence, the overwhelmingly likely conclusion should be that the suspect is innocent. The prosecutor’s fallacy is only truly effective when the chance of the innocent explanation is extremely small, otherwise it is too easy to see through the fallacious argument.
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than ever. Simultaneously, there is a concomitant increase in the numerical skills required to interpret their findings. In many cases there is no hidden agenda, the statistics are just difficult to interpret. However, for many reasons it might benefit one party or another to put a spin on a particular finding.
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Small, unrepresentative, or biased samples, in conjunction with leading questions and selective reporting, can all make for unreliable statistics. More subtle still are the statistics used out of context so that we have no way to judge whether, for example, a 300 percent increase in cases of a disease represents an increase from one patient to four or from half a million patients to 2 million. Context is important. It’s not that these different interpretations of numbers are lies—each one is a small piece of the true story on which someone has shone a light from a preferred direction—it’s just that they are not the whole truth. We are left to try to piece together the true story behind the hyperbole.
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Advertisers know that numbers are widely perceived as being indisputable facts. Adding a figure to an ad can be extremely persuasive and lend power to the promoter’s argument.
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The apparent objectivity of statistics seems to say, “Don’t just trust what we’re saying, trust this piece of indisputable evidence.”
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A more appropriate question for Liddle to ask might have been, “If a black US citizen comes across someone while out walking alone, who should they be more scared will kill them: another black person, or a law enforcement officer?” To find out the answer we need to compare the per capita rates of black-victim killings perpetrated by black people and by police officers. We find the per capita rates, as presented in table 11, by dividing the total number of black victims killed by a particular group (black people or police officers) by the size of the group. Black people were responsible for 2,380 killings of other black people in 2015, but with over 40.2 million black US citizens, the per capita rate is relatively small—around one in seventeen thousand. Police officers were “rightly or wrongly” responsible for killing 307 black people in 2015. With 635,781 police officers, this amounts to a per capita killing rate that is just below one killing per two thousand police officers—over eight times higher than the rate for black US citizens. It seems that a black person walking down the street should be more alarmed to see a police officer approaching than another black person.
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Of course we have not accounted for the fact that encounters with the police are often confrontational, and US police are typically armed. It’s perhaps not surprising that those authorized to wield lethal force do so more frequently than the general population at large. By exactly the same mathematics, we can show that white people should also be more scared of law enforcement officers (per capita white killing rate of one per thousand officers) than other white people (per capita white killing rate of one per ninety thousand white people), despite more white people killing other white people than police officers killing white people. That police officers have twice as high a per capita rate of killing white people than black people is because the country has more white people.
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a statistic that is at the heart of the Black Lives Matter movement: that the 12.6 percent of the population who are black account for 26.8 percent of police killings, while the 73.6 percent who are white account for just 51.0 percent.
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Other subtle signs can indicate a manipulated statistic. If presenters are confident of the veracity of their figures, then they won’t be afraid to give the context and the source for others to check. As with Gorka’s terrorism tweet, a contextual vacuum is a red flag when it comes to believability. Lack of details on survey results, including the sample size, the questions asked, and the source of the sample—as we saw in L’Oréal’s advertising campaign—is another warning sign. Mismatched framing, percentages, indexes, and relative figures without the absolutes, as in the NCI’s Breast Cancer Risk Tool, should set alarm bells ringing. The spurious inferences of a causative effect from uncontrolled studies or subsampled data—as often seen in the conclusions drawn from trials of alternative medicine—are yet more tricks to watch out for. If an initially extreme statistic suddenly rises or falls—as with gun crime in the United States—be on the lookout for regression to the mean. More generally, when a statistic is pushed your way, ask yourself the questions “What’s the comparison?” “What’s the motivation?” and “Is this the whole story?” Finding the answers to these three questions should take you a long way toward determining the veracity of the figures. Not being able to find the answers tells its own story.
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When you arrive at the cinema and need to pay to park at the meter, the ticket machine probably won’t provide change. If you have enough coins in your pocket, you probably want to make up the exact price as quickly as possible. In one greedy algorithm, which many of us will reach for intuitively, we insert coins sequentially, each time adding the largest-value coin that is less than the remaining total.
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For all the 1-2-5 currencies, as well as the US coinage system, the greedy algorithm described
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above does make up the total using the smallest number of coins.
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Any currency for which each coin or note is at least twice as valuable as the next smallest denomination will satisfy the greedy property.
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Measures implemented to reduce employee absence, including reducing paid sick leave, are causing a marked rise in people coming to work regardless of how bad they might be feeling, leading unintentionally to more illness and overall lowered rates of efficiency. Presenteeism is particularly prevalent in health care and teaching. Ironically, nurses, doctors, and teachers feel so obligated to the large numbers of people they safeguard that they often put them at risk by coming in to work while under the weather.
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Perhaps surprisingly, diseases with high case fatality rates tend to be less infectious. If a disease kills too many of its victims too quickly, then it reduces its chances of being passed on. Diseases that kill most of the people they infect and also spread efficiently are very rare and are usually confined to disaster movies. Although a high case fatality rate significantly raises the fear associated with an outbreak, diseases with high R0 but lower case fatality may end up killing more people by virtue of the larger numbers they infect.
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One of the most effective options for reducing disease spread is vaccination. By taking people directly from susceptible to removed, bypassing the infective state, it effectively reduces the size of the susceptible population. Vaccination, however, is typically a precautionary measure applied in an attempt to reduce the probability of outbreaks. Once
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outbreaks are in full swing, it is often impractical to develop and test an effective vaccine in time.
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Similarly, it’s impractical in the real world to quarantine a high proportion of the population for a long time. Running a mathematical model presents no such concerns. We can test models in which everyone is quarantined or no one, or anywhere in between, in an attempt to balance the economic impact of this enforced isolation with the effect it has on the progression of the disease. This is the real beauty of mathematical epidemiology—the ability to test out scenarios that are infeasible in the real world, sometimes with surprising and counterintuitive results. Math has, for example, shown that for diseases such as chicken pox (varicella) isolation and quarantine may be the wrong strategy. Trying to segregate children with and without the disease will undoubtedly lead to numerous missed schooldays and workdays to avoid what is widely considered to be a relatively mild disease. Perhaps more significant, though, mathematical models prove that quarantining healthy children can defer their catching the disease until they are older, when the complications from chicken pox can be far more serious. Such counterintuitive effects of a seemingly sensible strategy such as isolation might never have been fully understood if not for mathematical interventions.
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Childhood diseases show these typical periodic outbreak patterns because the effective reproduction number varies over time with the population of susceptible individuals. After a big outbreak has affected large swathes of the unprotected-child population, a disease such as scarlet fever doesn’t just disappear. It persists in the population, but with an effective reproduction number that hovers around 1. The disease only just sustains itself. As time goes by, the population ages, and new, unprotected children are born. As the unguarded fraction of the population grows, the effective reproduction number becomes higher and higher, making new outbreaks increasingly likely. When an outbreak finally takes off, the victims to whom the disease spreads are usually at the unprotected younger end of the demographic, because most of the older populace are already immune through experiencing the disease. Those people who didn’t get the disease as children are typically afforded some protection because they fraternize with fewer of the infected age group.
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The most effective way to reduce the size of the susceptible population is through vaccination. The question of how many to vaccinate to achieve herd immunity relies on reducing the effective reproduction number to below 1.
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In general we can only afford to leave 1/R0 of the population unvaccinated and must protect the remaining fraction (1−1/R0 of the population) if we are to achieve the herd immunity threshold.
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Next Journal
Blog Written with a loving hand by kitt some time around 18:17 on 23 November 2020Much to my disappointment, the journal that I have fallen in love with (Moleskine daily diary, large size, ripe yellow, which I ignore the dates in and use as a lined journal) has been discontinued by Moleskine, after running ALL OF ONE YEAR (good thing I bought two, which lasted me the whole year). Talk about teasing customers. Thanks, Moleskine. The 18 month daily is pretty darn great, too (lasting all of nine months with normal use), but some time around seven months, I'd start looking for another journal. The 12 month daily diary has just the right number of pages, though Moleskine FINALLY came out with a large size EXPANDED to 400 pages, which is also a great size, just the wrong color.
I am, however, near the end of my current notebook, I'll likely finish it up in about six weeks, which is about the right time to decide on the next journal. I'm breaking my usual streak and going EXTRA LARGE SIZE, and cracking myself up.
I mean, neon green extra large. Cracking me up.
Blood on Snow
Book Notes Instead of being asleep at 20:55 on 22 November 2020, kitt created this:This is book one of the Blood on Snow series.
So, I rather liken this book to The Cleaner in the sense that the main character is a killer, and we are, somehow, I do not know how, we are supposed to feel sorry for the guy when things don't work out well. I am not a fan. I rather like Nesbø's Harry Hole series, so I thought I'd give this one a try.
Ehhhhhh...
We have Olav Johansen, who is a fixer. He fixes the problems of, read: murders people for, the local top pimp and heroin kingpin, who is in a turf war with another heroin kingpin, I mean crime boss.
The crime boss Daniel Hoffmann contracts Olav to kill his wife, Corina, whom Hoffmann suspects of adultery. Turns out, Corina's lover does exist, and is more than a bit of an asshole. So, Olav kills the lover instead.
Apparently, fixers aren't supposed to think. Instead, they are supposed to just follow through on orders.
What makes the tale interesting is that the narrator, Olav, is actually thoroughly delusional. The story we read might be the his story, but might not be, we don't know. That not knowing is what makes this book more interesting than seen at first view.
That said, while I like the writing, I'm not a fan of the premise.
If you're a fan of Nesbø, sure, read the book. If not, eh, skip.
The way Maria was in love with her junkie boyfriend. Some women don’t know what’s best for them, they just leak love without demanding anything in return. It’s almost as if the very lack of any reciprocation just makes them worse. I suppose they’re hoping they’ll be rewarded one day, poor things. Hopeful, hopeless infatuation. Someone ought to tell them that isn’t how the world works.
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“What do you want to do, Olav?”
I got up from the kitchen chair. “See if I can find you a blanket.”
“I mean, what are we going to do?”
She was okay. You know someone’s okay if they can ignore things they can’t do anything about and move on. Wish I was like that.
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“You haven’t asked,” she said in the darkness.
“No,” I said.
“Why not?”
“I suppose I’m just not a very inquisitive person.”
“But you must be wondering. Father and son…”
“I assumed you’d tell me whatever you felt like telling me when you felt like it.”
The bed creaked as Corina turned towards me. “What if I never said anything?”
“Then I’d never find out.”
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I was walking across the frozen path with short, quick steps, my knees slightly bent. That’s something you learn as a child in Norway.
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And Canada.
She helped me off with it, then ran her fingers over the bruises left by the Dane’s bullets. Loving. Fascinated. Kissed them. And as I lay in bed and felt the shakes come, and she wrapped the duvet around me, I felt just like before when I lay in Mum’s bed. It almost didn’t hurt any more. And it felt as if I could escape it all, but it wasn’t up to me; I was a boat on a river, and the river was in charge. My fate, my destination was already determined. Which just left the journey, the time it took and the things you saw and experienced along the way. Life seems simple when you’re sufficiently ill.
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Half-Resurrection Blues
Book Notes Written with a loving hand by kitt some time around 21:14 on 21 November 2020This is the first book of the "A Bone Street Rumba" series. I picked up the book after a second recommendation for it, one from Claire and one from the XOXO slack. One of the strong recommendations from both was, "listen to this book." The book is read by the author, whose voice caresses the listener as it takes the listener on a wild ride.
So, I listened to this book more than I read it. The audio version recommendation? Totally worth it.
In this book, we are introduced to Carlos Delacruz, an in-betweener who is half-alive, half-dead. He worked as an agent for the New York Council of the Dead, a vague power group who directs its people to reap souls to keep the dead in the underworld, and the living out of the underworld. We learn about Carlos as he vaguely recalls things. He doesn't recall his life before his resurrection. He follows the rules of the Council. He leads the dead back to the underworld, or reaps their soul for the second death or some such.
At the beginning of the tale, Carlos meets up with another inbetweener, wait what, there are others? and kills him, per the order of the Council. Turns out, on his dying breath, the guy Carlos kills asks Carlos to watch over his sister, Sasha. Another wait what? She is also an inbetweener. And apparently very very hot. Of course they hook up. But what is this pull and what are all these ngks? Well, the ngks are tiny, exercise bike riding spirits with a hive mind contracted to kill an old spirit in order to open the entrance between the Underworld and the real world. They're kinda mean, too.
So, Carlos uncovers his past, Sasha's past, what the ngks are, who is orchestrating the opening of the Underworld, and just how meh the Council is. The book is a fun read, worth reading / listening to.
"At first? Chaos. The hungry dead will pour through the gate, scatter out into the world in their vast multitudes. The living will wander in. There is always a painful period of absolute crisis at the pinnacle of any great change.”
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Thoughts on a California Curfew
Blog Instead of being asleep at 23:17 on 19 November 2020, kitt created this:California went into curfew tonight. All non-essential businesses must be closed between 10pm and 5am for purple (the worst) rated counties (most of us) for the next month.
On the news, we hear people interviewed saying, "This is stupid. What the virus is going to be more active from 10pm until morning?"
Which shows just how much our country lacks any type of critical thinking skills and any form of creativity. It also shows just how disrespectful people are, which is one of the many reasons were are in this mess in the first place.
Heaven forbid people could actually speculate on what is actually happening. Heaven forbid people would actually try to understand the reasoning for a measure, or understand why the curfew would be considered a helpful measure.
Allow me to, once again, think for the people who choose not to think, and speculate for just 3 minutes. I set my timer for three minutes and...
1. Curfew means that traditionally late night venues will need to be closed. Said late night venues include bars and strip joints, both places where people drink alcohol. Drinking means no mask, which means higher transmission rates. Alcohol also means lowered inhibitions which means people are more likely to engage in risky behaviors leading to the spread of the virus. Curfew reduces these vectors.
2. Curfew forces people back into their homes, if they have one, early. This means that people will leave whatever (stupid, idiotic) larger group they may be in and in a place where they can be sheltering. Curfew breaks apart larger group that may happen in the evening.
Wow, typing this up, and I'm only at one minute and forty five seconds so far.
3. Curfew means that law enforcement and health workers have a chance at a break, a moment to breathe, before needing to care for the idiots who are not sheltering during the day. Wouldn't that be nice?
4. Curfew is an experiment to see if we can reduce transmission rates by altering this part of people's behavior.
Meh. Rather than complaining about the rule, maybe the irresponsible person being interviewed could, you know, show some curiosity and find out WHY the rule went into effect.
Oh, I just found out the interviewed person I quoted above is a Republican. OF FUCKING COURSE. Republicans are the group of irresponsible people who like to believe you can wish away an organism that is LITERALLY KILLING US. Explains his response: he wants to fight reason, fight science, manipulate people to keep power.
Good lord. I hope he catches Covid-19, has it very bad, and survives.