Category: Epidemiology

The NFL has a hall of fame in Canton. Cooperstown has the baseball hall of fame. There is even a polka hall of fame in Euclid, Ohio. It is time to create a memorial to prominent figures in public health but instead of a hall of fame, I propose we create a hall of shame to recognize people whose actions have promoted disease, injuries, and death. Here are 10 people worthy of induction into the Public Health Hall of Shame, listed in chronological order.

1. Christopher Columbus

Unlike many of of the Hall of Shame nominees, Christopher Columbus did not knowingly promote the spread of disease but his inadvertent actions make him worthy of inclusion. He was the first worldwide disease importer/exporter. On October 12, 1492, Columbus arrived in the Bahamas bringing to the newly discovered lands European diseases. When he returned to Spain on March 15, 1493, he brought gifts from the New World. One of those gifts carried by crew members was syphilis that then spread to Spanish soldiers. Two years later, in 1495, Pope Innocent VIII invited King Charles of France to wage war against the King of Naples in Italy. Spanish mercenaries employed by the French army brought syphilis with them to Naples and within a few years, syphilis had spread throughout Europe. Because of the association with the French army, syphilis became known as the “French disease” but it was really the Spanish sailors who brought it back with them from the Americas. Recently, historians have proposed that syphilis occurred sporadically in Europe before Columbus sailed but given the correlation with the Naples war, it seems likely that his crew carried the infection on their return to Spain thus fostering its European spread in the 16th century. For his contribution to the spread of syphilis to Europe (even though inadvertently), Christopher Columbus is nominated to the Hall of Shame.

2. Hernán Cortés

Another Spaniard who warrants inclusion in our Hall of Shame was the conquistador, Hernán Cortés. He was from a lesser nobility family in Spain but chose to come to the New World to seek gold and silver rather than live the life of a nobleman in Europe. In February 1519, he sailed from Cuba to Mexico in order to conquer the Aztecs and loot their empire. His force of 1,000 men was no match for the 200,000 residents in the Aztec capital of Tenochtitlan in Central Mexico. But Cortés had a secret weapon… smallpox. One of Cortés’ soldiers had become infected with smallpox before leaving Cuba. The Aztecs and other Native Americans had no immunity to smallpox because it had not existed in the Americas until it was brought by the early European explorers. 70 days after Cortés first arrived in Mexico, 40% of the population of Tenochtitlan was dead from smallpox. Within a few years, between 5-7 million Aztecs and other indigenous Mexicans died from smallpox. Cortés proved that infectious diseases are more powerful in battle than swords and cannon. In all, it is suspected that infectious diseases brought by European explorers resulted in the death of up to 95% of the native population of the Americas. For his actions resulting in the deaths of millions of Native Mexicans due to smallpox, Hernán Cortés is nominated to the Hall of Shame.

Honorable mention: Colonel Henry Bouquet. In June 1763, Bouquet was the commanding officer at Fort Pitt during Potomac’s War. When the fort was under siege by members of the Delaware Tribe, Bouquet needed help to defeat the Native Americans. So, he ordered his men to distribute smallpox-infested blankets to the besieging warriors in an attempt to infect them and reduce their forces. More than 100 Native Americans died from the resultant smallpox outbreak. Bouquet can be considered the father of germ warfare.

3. Anthony Comstock

In 1873, U.S. postal inspector Anthony Comstock formed the New York Society for the Suppression of Vice. Later that year, he lobbied the U.S. Congress to pass what became known as the Comstock Act that prohibited the postal service from delivering obscene material. As a result, more than 15 tons of books that Comstock determined were obscene were destroyed. These included anatomy books used by medical schools because those books included drawings of reproductive organs. Another provision of the Comstock Act was to prohibit the production of or publication of information about methods of contraception or prevention of venereal disease. Comstock was convinced that by making condoms illegal that Americans would stop having sex outside of marriage. He was oblivious to the fact that the drive to have sex is the most powerful drive in all species of living organisms on planet Earth. He zealously prosecuted and imprisoned anyone who defied his definition of morality, including Julius Schmidt, the inventor of the rubber condom. After release from prison, Schmidt resumed condom manufacturing in a clandestine production facility in New York City. During World War I, being unable to legally sell his condoms to the U.S. Army because of the Comstock Act, Schmidt turned to other allied governments that enthusiastically purchased and distributed condoms to their servicemen. As a result, unlike other Allied armies, at any given time, approximately 15% of the U.S. military force in Europe was actively infected with a venereal disease. Eventually, the U.S. government relented and the production and distribution of condoms became legal but not before Comstock’s efforts had resulted in tens of thousands of cases of syphilis and gonorrhea that could otherwise have been prevented. For his efforts to promote the spread of sexually transmitted disease, Anthony Comstock is deserving of induction into the Hall of Shame.

4. Mary Mallon

From 1900 to 1907, Mary Mallon worked for eight wealthy New York families as a cook. At each household where she worked, household members developed typhoid fever. When a public health investigator determined that Ms. Mallon was the common link in the series of typhoid outbreaks, he went to interview her. But when he asked her to provide samples to test, she attacked him with a fork. She was sentenced by the Health Department to quarantine at North Brother Island from 1907 – 1910. She was released from quarantine under the condition that she never resume work as a cook again. However, she went back to cooking for families, restaurants, and hospitals under a false name. Everywhere she went, she left a trail of typhoid cases. In 1915, when 25 inpatients developed typhoid at a hospital where she worked as a cook, she was again sentenced to quarantine at North Brother island where she lived for 23 years. For her efforts to spread typhoid fever as an asymptomatic carrier, she earned the name “Typhoid Mary” and warrants induction into the Hall of Shame.

5. Emma Marie Harrington

Also known as E.C. Harrington, she was an attorney and the first woman registered to vote in San Francisco. She was a champion of progressive issues in California in the early 1900’s. However, she became famous for her actions that today would make her the darling of political conservatives. In March 1918, an army cook at Camp Funston in Kansas became sick with a respiratory infection. Within days, 522 soldiers became ill. Because the U.S. had entered World War I, troops from Camp Funston were sent to Europe to fight. By April, the H1N1 strain of influenza had spread throughout the world. Within 2 years, one-third of the world’s population had become infected. The number of deaths were estimated to be as high as 100 million making it the second most deadly pandemic after the 14th century bubonic plague. Because there were no vaccines or anti-viral medications at that time, the only defense against influenza was to avoid getting it in the first place. The two public health measures that were found to reduce the spread of the infection were face masks and banning mass gatherings. But some Americans considered face mask mandates to be an affront to personal liberty. Many of them organized to oppose face masks which they called “muzzles”. One of these organizations was the San Francisco Anti-Mask League and E. C. Harrington was its president. During the fall of 1918 and early winter of 1919, more than 3,000 San Francisco residents had died from influenza and the death rate per 100,000 was one of the highest in the world. Despite magnitude of deaths, the Anti-Mask League put enormous political pressure on the city government to lift its mask ban. On January 27, 1919, Mrs. Harrington submitted a petition to the city’s Board of Supervisors to repeal the mask ordinance and 5 days later, on February 1, 1919, San Francisco lifted its mask requirement. For helping to promote influenza deaths in 1919 and for later inspiring thousands of anti-maskers during the COVID-19 pandemic, E. C. Harrington deserves nomination into the Hall of Shame.

6. John W. Hill

America’s economic fortunes were built on tobacco. When anticipated riches from early settlements such as Jamestown failed to materialize, the settlers turned to growing tobacco for export to Europe. Demand for tobacco was enormous and soon farms and plantations across the colonies were making their fortunes by growing tobacco. The invention of a machine for large scale manufacturing of cigarettes in 1880 revolutionized the U.S. tobacco industry. After the turn of the century, per capita cigarette consumption increased exponentially. But by 1950, there were increasing reports that tobacco smoke could be harmful to people’s health. The CEOs of the largest cigarette makers – American Tobacco Co., R. J. Reynolds, Philip Morris, Benson & Hedges, U.S. Tobacco Co. and Brown & Williamson, were worried that sales would suffer so they turned to John W. Hill, the founder of Hill & Knowlton, one of the top public relations firms in the country. In 1953, Hill devised a PR campaign to discredit the mounting scientific data and named it “Operation White Coats”. The plan was to employ physicians and scientists (who wore white coats) to downplay the health hazards of cigarette smoke. Operation White Coats was the genesis of the Tobacco Research Council that provided easy-to-obtain grants to prominent medical researchers for studies that showed health benefits of nicotine and other tobacco components. Hill’s cigarette marketing strategy was successful and by 1965, 45% of U.S. adults were daily smokers. In reality many people have contributed to the the misinformation campaigns of American tobacco companies but John W. Hill stands out as of the most effective in denying that smoking cigarettes causes lung cancer, COPD, and other diseases. His has been a legacy of death and even today, smoking accounts for 480,000 deaths per year in the U.S., or about 1 out of every 5 deaths. For his contribution to to the death of millions of Americans since his 1953 advertising campaign, John W. Hill is our 6th nominee to the Hall of Shame.

Honorable Mention: Carrie Nation. She was the public face of the Women’s Christian Temperance Union which was the primary driver of the prohibition movement that led to passing the 18th Amendment to the U.S. Constitution outlawing the sale of alcohol on January 16, 1919. She claimed to have a divine vision from God commanding her to destroy bars and saloons. She traveled across the United States with a hatchet that she would use to smash saloon fixtures and liquor bottles. She described herself as “a bulldog running along at the feet of Jesus, barking at what He doesn’t like”. Overall, prohibition did reduce U.S. alcohol consumption by about 30% but instead of drinking low-alcohol percentage beer, people just started drinking bootlegged liquors. These were produced in unregulated stills and were frequently contaminated with methanol. Sellars of illegal spirits would often water them down and then add various poisonous chemicals to mimic the taste and color of liquors. During prohibition, over 1,000 people per year died from consuming tainted liquor. Within 15 years, it became apparent that prohibition did not stop people from drinking, it only created a market for poisonous moonshine. In 1933, the 21st Amendment repealed prohibition.

7. Peter Duesberg, PhD

In the early 1980’s, gay men were dying from an immunodeficiency syndrome and no one knew why. In 1983, the cause was identified simultaneously by French virologist Luc Montagnier and American virologist Robert Gallo. It was a virus that became known as HIV, or human immunodeficiency virus. Soon after, a lab test was created to diagnose the infection followed by development of AZT, a life-saving anti-viral drug that could treat AIDS. These milestones should have been celebrated by the medical and scientific community as breakthroughs in conquering AIDS. But history has proven that for every disease, there is a disease denialist and for AIDS, the most prominent denialist was Peter Duesberg. He is a Professor of Molecular Biology at the University of California, Berkley who built a successful academic career on his discovery of genes that could cause cancer. He argued that HIV was a harmless virus and that the cause of AIDS was long-term consumption of recreational drugs and anti-viral drugs. Because of his academic credentials, he developed a following of AIDS denialists in the 1990’s. Around the globe, people continued to die of AIDS and by 2000, about 25% of all deaths in South Africa were due to AIDS. Thabo Mbeki, the president of South Africa, convened an AIDS advisory committee to help direct public policy. The committee included Peter Duesberg. Mbeki bought into Duesberg’s AIDS denialism and withheld the use of anti-retroviral drugs in his country. As a result, it is estimated that there were 330,000 preventable deaths from AIDS in South Africa. Duesberg has kept up his claims that HIV does not cause AIDS and as recently as 2012 said on the Joe Rogan podcast that HIV is “one of the most harmless type of viruses we know”. For his actions that contributed to one-third of a million AIDS deaths in South Africa and his inspiration for AIDS denialists everywhere, Peter Duesberg should be nominated for the Public Health Hall of Shame

Honorable Mention: Christine Maggiore. She was diagnosed with HIV in 1992 and became involved in AIDS activism. In 1994, she met Peter Duesberg who convinced her that HIV does not cause AIDS. She came to believe that her own positive HIV test was actually due to an influenza vaccination. She authored a book entitled What If Everything You Thought You Knew about AIDS Was Wrong? and became prominent in the AIDS denialist community. She founded an organization that urged HIV-positive pregnant women to avoid anti-HIV medication. Ironically, she went on to become pregnant herself and refused to take HIV medications. She give birth to a daughter, Eliza Jane, and refused to allow her infant daughter to be tested for HIV. Eliza Jane died of AIDS at age 3 and Christine Maggiore died of AIDS three years later.

8. Jay Dickey

Most of our Hall of Shame nominees are proposed because of their actions that resulted in the proliferation of disease. Although bullets are not a disease, guns have proliferated in the United States just like contagious pathogens. Each year, more than 45,000 Americans die from gunshots and twice that number suffer non-fatal gun injuries. One of the barriers to reducing firearm deaths over the past 25 years has been a law prohibiting research into firearm-related deaths and injuries. The architect of that law was U.S. Representative James Dickey of Arkansas who at the behest of the National Rifle Association, added a clause to the 1996 Omnibus bill that became known as the Dickey Amendment. The amendment stated that “…none of the funds made available for injury prevention and control at the Centers for Disease Control may be used to advocate or promote gun control.” It effectively stopped all research by the CDC into gun-related deaths and injuries. It was not until 2018 that Congress passed a law allowing the CDC to report data on firearm injuries and not until 2020 that Congress allowed funding for firearm injury research by the CDC. By prohibiting the CDC to study gun injuries for 22 years, there was no good data on which to base public policy to reduce firearm injuries and hundreds of thousands of Americans died from guns. Later in his life, Dickey reversed his opinion about gun violence research but he nevertheless deserves inclusion in the Hall of Shame.

Honorable mention: Wayne LaPierre. Mr. LaPierre has been the executive vice president and chief executive of the National Rifle Association since 1991. It was he who was the principal lobbyist who influenced Dickey to add the NRAs amendment to the Omnibus bill in 1996. LaPierre has continued to lobby for the proliferation of guns in the United States. Because of his efforts, the U.S. is now the only country in the world with more guns than people.

9. Andrew Wakefield, MD

As the son of two physicians, it was no surprise that Andrew Wakefield went to medical school at St. Mary’s Medical School in London. He went on to do research in liver and small intestine transplantation and became a member of the Royal College of Surgeons. He developed a hypothesis that the measles virus might be the cause of Crohn’s disease. This evolved into a hypothesis that the measles vaccine might cause Crohn’s disease. Both of these hypotheses were disproven. But Wakefield was undeterred in his quest to link the measles vaccine to some disease. So, he turned to autism and in 1998, he published a paper in The Lancet in which he concluded that 12 children with autism developed “autistic enterocolitis” from the MMR vaccine (measles, mumps, rubella vaccine). He then called for a suspension of childhood vaccination with MMR in a press conference at his hospital. In 2000, he repeated his claims on the CBS news show, 60 Minutes, introducing his theory to American vaccine conspiracy theorists. In 2004, the British public service network Channel 4 reported that before he published his 1998 article about the MMR vaccine, Wakefield submitted a patent for a rival measles vaccine that he said would not cause autism. Presumably, if his vaccine replaced the MMR vaccine worldwide, he would stand to profit enormously. He also started a company to make diagnostic test kits for “autistic enterocolitis” that he predicted would make him $43 million per year. In 2009, his original research was found to be fraudulent and in 2010, The Lancet retracted his 1998 article. Three months later, his medical license was revoked. Dr. Andrew Wakefield’s false claims about the MMR vaccine were the inspiration for other anti-vaxxers. This not only led to thousands of children not receiving appropriate vaccinations but also laid the groundwork for false claims about the COVID-19 vaccines. For his efforts to increase childhood infections, Andrew Wakefield should be included in the Hall of Shame.

Honorable Mention: Robert F. Kennedy, Jr. The son of the late Senator Robert F. (Bobby) Kennedy is an environmental lawyer who makes a living as an anti-vaxxer. Since 2005, he has promoted Andrew Wakefield’s discredited idea that vaccines cause autism. When 2 Samoan infants died in 2018, he opined that the cause of their death was the MMR vaccine. It was later determined that the infants had been errantly injected with a muscle relaxant along with the vaccine and the muscle relaxant was the cause of death. Nevertheless, his views caused many Samoans to forgo the MMR vaccine in their children. As a consequence, in 2019, a measles outbreak resulted in 5,700 infections or 3% of the Samoan population; 83 Samoans died from measles infections. Kennedy became convinced that the preservative thimerosal in vaccines could cause neurological disorders such as autism in children and spread anti-vaccine misinformation. As a result, thousands of pregnant women refused influenza vaccination and thousands of parents refused to allow their children to get flu shots resulting in countless influenza infections and deaths. Many studies have shown that thimerosal in vaccines is safe. He has been a tireless conspiracy theorist and suggested that Anthony Fauci and Bill Gates conspired to prolong the COVID pandemic for financial gain. He promoted the use of ivermectin to treat COVID, despite studies showing that the anti-parasite drug had no effect on COVID infection. Other members of the Kennedy family issued a joint statement about his efforts and said: “…on vaccines he is wrong. And his and others’ work against vaccines is having heartbreaking consequences.”

10. Joseph Mercola, DO

The last of our nominations is for efforts to promote the spread of COVID-19. Dr. Joseph Mercola is an American alternative medicine proponent with a lucrative internet business selling dietary supplements. He stopped seeing patients in 2009 to devote his attention to his internet business and has stated that his net worth is in excess of $100 million. Following in Andrew Wakefield’s shoes, he has been a staunch vaccine critic. It was during the COVID-19 pandemic that Dr. Mercola really hit his stride by promoting unproven supplements (that he sold) as treatments for COVID. He also advocated using inhaled hydrogen peroxide to prevent or cure COVID. An article in the New York Times identified him as the single most influential spreader of COVID misinformation. Becker’s Hospital Review reported that a “Disinformation Dozen” individuals were responsible for 65% of all of the misinformation about COVID and number 1 on that list was Joseph Mercola. His actions have contributed to unfounded fears of effective COVID vaccines and even as of today, one-third of the U.S. population is not fully vaccinated. For his contribution to the perpetuation of the COVID pandemic that has so far killed more than 1 million Americans, Dr. Joseph Mercola is our 10th nominee for induction into the Hall of Shame.

Honorable Mention: Sherri Tenpenny, DO. Occupying the 4th rank in the COVID “Disinformation Dozen” is Ohio’s own Dr. Sherri Tenpenny. She is an anti-vaccine activist who supports the claim that vaccines cause autism. She has written 4 books claiming dangers of vaccines and has stated that COVID vaccines cause death, autoimmune disease, and infertility. She sells these books along with videos and dietary supplements on her website. She stated that COVID-19 vaccines will turn people into “transhumanist cyborgs” and that “by the end of 2022, every fully vaccinated person over the age of 30 may have the equivalent of full-blown vaccine-induced immune suppressed AIDS”. She claims that wearing face masks makes people unhealthy by suppressing their immune systems. In June 2021, she was called by Ohio Republican legislators to testify at the Ohio Statehouse against vaccine mandates. She testified that the COVID vaccines cause people to become magnetized and meanwhile her minions posted on-line videos of spoons stuck to their noses to try to prove her point. Dr. Tenpenny’s claims about magnetism proved to be too far-fetched even for Ohio’s conservative State Representatives and the bill to ban childhood vaccine requirements died in committee.

History is replete with people who have helped to spread disease. Some, like Columbus, did it unknowingly. Some, like Bouquet, did it purposefully. Some, like Comstock, did it in defiance of human nature. Some, like Hill, did it by spreading misinformation. Others, like Mercola, did it in order to make a profit. But whether their actions were intended or unintended, each of our nominees for induction in the  Public Health Hall of Shame helped to promote disease, death, or injury by their actions. The bitter news for the medical profession is that as long as we have people like these 10 inductees, doctors and morticians will never go out of business.

August 9, 2022

Who lives longer, Republicans or Democrats? The answer may surprise you. Many people hold the stereotype of Republicans being wealthy, being better educated, and having better access to healthcare. Democrats often hold the stereotype of being working class, poor, and wanting government healthcare handouts. Intuitively, this would translate to Republicans being healthier and living longer than Democrats.

 

Historically, Republicans were found to be healthier than Democrats. In a 2009 article from the International Journal of Epidemiology, investigators analyzed data from the 1972 – 2006 General Social Surveys and found that survey respondents who identified as Republican had better self-reported health and were less likely than Democrats to be smokers. Similarly, a 2015 article from the journal Political Research Quarterly found that people who identified as having good health were more likely to vote Republican in the preceding presidential election.

A more recent study in the May 2022 edition of the British Medical Journal found that the association of political party with health may be reversing. This study compared the voting patterns of individual U.S. counties in the 5 presidential elections between 2000 to 2019 with the changes in the mortality rates in each of those counties during the same time period. The results indicated that counties voting Democratic had greater improvements in mortality rates than counties voting Republican. Moreover, the separation between improved mortality rates and political party voting only became apparent after 2008. This suggests that there has been a change over the past 15 years with Democrats now becoming the healthier of the two political parties.

It turns out that determining how political party affiliation affects life expectancy and other health metrics is quite difficult. Nowhere on a death certificate is there an entry for the doctor to  record political party. Because our voting choices are confidential, there is no way to do a public record search for how dead Americans voted in the past Therefore, the only way to study political party affiliation and health outcomes is by correlation studies that look at voting patterns and health metrics of different geographic locations.

The Cook Partisan Voting Index

In 1997, a new method of determining political affiliation was developed called the Cook Partisan Voting Index. For the past 25 years, the index has been used to determine how strongly a congressional district or a state leans toward the Republican party or the Democratic Party. The index is based on voting patterns in the previous two presidential elections. The most recent data is based on voting in the 2016 and 2020 elections. The higher the number, the more strongly a state leans towards one political party.

In this table, Democratic-leaning states are in blue and are denoted with negative numbers; the more negative the number, the more the state leans Democratic. Republican-leaning states are in red and denoted with positive numbers; the higher the number, the more the state leans Republican. The most strongly Republican state is Wyoming and the most strongly Democratic states are Vermont and Hawaii. Two states (Nevada and New Hampshire) are equally split between Republican and Democratic parties and they are denoted in purple. The use of negative numbers for Democratic states and positive numbers for Republican states in this table is purely to facilitate statistical comparisons.

The Cook Partisan Index also reports the political leaning by individual congressional district. The most Democratic district is California’s 12th (Oakland area) and the most Republican district is Alabama’s 4th (rural northern Alabama).

Party affiliation and life expectancy

If we use the Cook Partisan Voting Index as a marker for party affiliation, then we can compare states with a high Republican index to states with a high Democratic index and see how those voting patterns correlate with health metrics. Life expectancy is one of the simplest of these metrics. Life expectancy can be measured in several ways. The most common measurements are (1) life expectancy from birth, (2) life expectancy from age 18, and (3) life expectancy from age 65. Each of these measurements has advantages and disadvantages.

Life expectancy from birth will be lower if there is a high infant and childhood mortality rate. Life expectancy from age 18 eliminates infant mortality but will be affected by gun-related deaths, drug overdoses, and motor vehicle deaths that are more common in young adults. Life expectancy from age 65 eliminates those young adulthood causes of death and is more affected by life-long unhealthy habits such as smoking, obesity, and alcohol abuse. For this analysis, let’s use life expectancy from birth since it incorporates all of the variables that can affect mortality from infancy through early adulthood and into older age.

In comparing the Cook Partisan Voting Index to life expectancy from birth, many people would suspect that Republicans would have a longer life expectancy than Democrats. However, just the opposite is true. People living in Democratic party states live longer than those in Republican party states. States that most strongly leaned Democrat had the longest life expectancy.

Overall, life expectancy in states found to be Democratic by the Cook Partisan Voting Index had a mean life expectancy of 79.6 years whereas the mean life expectancy in Republican states was 77.4 years (p < 0.001). This represents an average 2.2 year longer life expectancy in Democrat-leaning states.

Party affiliation and smoking

The finding of longer life expectancy in states that lean Democratic indicates that there has been a change in political party affiliation and health measures compared to older studies that showed Republicans were generally healthier than Democrats. One of the strongest predictors of life expectancy is smoking. In the past, Republicans were less likely to be smokers than Democrats. Could a change in the prevalence of smoking among people voting Republican versus Democrat be partially responsible for the change in life expectancy?

To answer this question, let’s examine the association between the Cook Partisan Voting Index and smoking rates by state. Each year, the Centers for Disease Control reports the percentage of adults in each state who smoke. Overall, the percentage of all Americans who smoke has been steadily falling since the mid-1960’s.

However, there are wide differences in smoking patterns between different states, ranging from a low of 7.9% of adults smoking in Utah to a high of 23.8% of adults smoking in West Virginia. Overall, states that lean Republican have a higher prevalence of smoking than states that lean Democratic (r = 0.64). The average adult smoking rate was 13.7% in Democrat states and 17.8% in Republican states (p < 0.001).

Party affiliation and obesity

A second health demographic that has changed over the past several decades is obesity. Overall, Americans have been becoming more obese each year. The CDC reports that the rate of obesity (BMI > 30) has increased from 30.5% in 2000 to 42.4% in 2018. Similarly, the rate of severe obesity (BMI > 40) has increased from 4.7% to 9.2%. These statistics are from the National Health and Nutrition Survey (NHANES) which is based face-to-face surveys performed in participating American’s homes by a physician and other health professionals.

As with smoking, there are substantial differences in the rate of obesity among different states. The Behavioral Risk Factor Surveillance System (BRFSS) reports obesity rates by state based on adult self-reported information from phone surveys. These self-reported obesity data differ from the NHANES data with a lower overall incidence of obesity than NHANES. This difference has been attributed to differences in how the data are obtained (in-person interview versus phone survey). The state with the highest rate of obesity is West Virginia and the state with the lowest rate of obesity is Colorado. Based on the BRFSS data, states that lean Democratic have an adult obesity prevalence of 29.1% and states that lean Republican have an adult obesity prevalence of 34.3% (p < 0.001)

Party affiliation and COVID mortality

One of the major causes of death in the United States in the past two years has been COVID-19. So far, 1,024,611 Americans are known to have died from COVID and many more have likely died from COVID or COVID complications that were not listed on death certificates. A study published last month in JAMA Internal Medicine found that in 2021, COVID was the 4th leading cause of death in Americans age 25-34 (after accidents, suicide, and assault), the number 1 cause of death in Americans age 45-54, and the 3rd leading cause of death in Americans over age 65 (after cancer and heart disease).

As noted in a previous post, there are significant differences in how Republicans and Democrats fared during the COVID-19 pandemic with residents in Democratic states more likely to be vaccinated against COVID, less likely to become infected with COVID, and less likely to die from COVID than residents in Republican states. By comparing the Cook Partisan Voting Index to the death rate of COVID for each state, we again find that the  there is an association between party affiliation and death from COVID. Overall, 260 people per 100,000 population have died from COVID in Democrat-leaning states whereas 331 per 100,000 died from COVID in Republican-leaning states (p = 0.005).

Party affiliation and personal income

As noted earlier, historically Republicans had a higher self-reported annual income than Democrats. The stereotypical Republican was a capitalism-supporting business owner and the stereotypical Democrat was a blue collar worker who belonged to a union. Personal income has been shown to affect health outcomes with wealthier persons having better health and poorer persons having worse health. Could a change in income demographics between Republicans and Democrats be partially responsible of the shorter life expectancy of residents of Republican states?

By comparing household income to the Cook Partisan Voting Index, we find that residents of states leaning Democratic have a higher annual income than residents of states leaning Republican. The average income in Democratic-leaning sates was $71,264 and the average come in Republican-leaning states was $59,108 (p < 0.001).

Money is only worth what you can buy with it. The highest income states are also the states with the highest cost of living so the above analysis man not necessarily equate to the purchasing power of each household. Nevertheless, it appears that voters favoring Republicans in the last two presidential elections have a different relative annual income than voters favoring Republicans in previous presidential elections. Residents of states who have recently favored Republicans have a lower income than those favoring Democrats.

Today’s Republicans are not your parent’s Republicans

A generation ago, compared to Democrats, Republicans were wealthier, healthier, and less likely to smoke. Today’s Republicans have a lower income, are more obese, are more likely to smoke, and are more likely to die young than Democrats. This generational reversal in the relationship between party affiliation and health metrics has implications for future healthcare utilization.

For example, given a 2.2 year longer life expectancy, residents of Democrat-leaning states would be expected to utilize 18% more Medicare and Social Security benefits than residents of Republican-leaning states (assuming Medicare and Social Security benefits starting at age 65). The longer a person lives, the more elections that person can vote in. The results imply that people voting Democrat will vote in an average of 2 more annual elections over the course of their lifetimes than those who vote Republican.

Obesity is associated with other health conditions such as diabetes, hypertension, sleep apnea, and arthritis. This could indicate that people voting Republican are more likely to have these conditions in addition to being more likely to be smokers. The result could be a higher incidence of disability among people voting Republican than among people voting Democrat.

It seems paradoxical that people living in states that lean toward the Democratic party have higher incomes and thus are in higher income tax brackets and pay more in income tax than people living in states that lean toward the Republican party. Democrats are often characterized as favoring higher taxes whereas Republicans are generally characterized as favoring tax cuts.

We will not fully know all of the healthcare implications for the apparent change in voter demographics for several years. However, it is likely that the evolving differences in health metrics between states that vote Republican and states that vote Democrat will result in very different approaches to healthcare policy.

August 1, 2022

Sometime next month, the United States will surpass one million reported deaths from COVID-19. So, how did your state compare in combating the pandemic? I graded each state by four measures: (1) total cases per 100,000 population, (2) total deaths per 100,000 population, (3) seroprevalence, and (4) percent of the population fully vaccinated. I then created a composite score using all four metrics to give an overall grade for every state plus Washington DC and Puerto Rico. Grades for each metric from A+ through F were assigned with 4 states getting any given grade.

1. Total cases per 100,000 population. These are the cases reported by state health departments to the CDC as of April 28, 2022. The higher the number, the more documented cases occurred since January 2020 per capita. This number does not reflect the true number of cases since many people test positive with home test kits that are not reported to their health departments and many patients with mild or no symptoms do not get tested.
   • Grade A+ states: Puerto Rico, Oregon, Maryland, Hawaii,
   • Grade F states: Alaska, Rhode Island, North Dakota, Tennessee
2. Total deaths per 100,000 population. These are the deaths reported by state health departments to the CDC as of April 28, 2022. The higher the number, the more deaths occurred since January 2020 per capita. Because the deaths from COVID are only counted if COVID is listed as a cause of death on the death certificate, these numbers are undoubtedly also an underestimate since COVID may not be listed on a death certificate if a person did not have a COVID test before dying or if a person died at home and no information about symptoms was available to the physician signing the death certificate.
   • Grade A+ states:Vermont, Hawaii, Puerto Rico, Utah
   • Grade F states: Mississippi, Arizona, Alabama, Tennessee
3. Seroprevalence. This is from the February Nationwide Antibody Seroprevalence Survey. In this study, left-over blood samples from blood drawn from clinical labs are tested for antibodies against the COVID-19 virus. Notably, the specific antibodies tested for are those generated from actual infection and do not result from vaccination. The higher the number, the greater the percentage of the state’s population has actually had a true COVID-19 infection (of note, there is no recent data for North Dakota; because there was no data for Montana and New Hampshire from the February study, data from the January study was used for these two states). Overall, this study estimates that 57.5% of Americans have had a COVID infection. However, because antibody levels decline over time, many people who have had an infection many months previously will no longer have antibodies. Therefore, these numbers likely underestimate the actual percentage of the population that has had an infection.
   • Grade A+ states: Vermont, New Hampshire, Hawaii, Puerto Rico,
   • Grade F states: Iowa, Texas, Mississippi
4. Percent of the population fully vaccinated. This is the percentage of people in each state that have received at least 2 doses of the Pfizer vaccine, 2 doses of the Moderna vaccine, or 1 dose of the Johnson & Johnson vaccine as reported by the CDC. This percentage reflects the entire population of the state, including young children who are not yet eligible to receive vaccinations and therefore the percentage of adults fully vaccinated will be higher.
   • Grade A+ states: Puerto Rico, Rhode Island, Vermont, Maine
   • Grade F states: Alabama, Wyoming, Mississippi, Louisiana
5. Overall score. For each of the above four metrics, states (plus Washington D.C. and Puerto Rico) were ranked 1 through 52. The overall score was calculated by adding the ranks for each of the four metric and determining the average of those 4 numbers. For North Dakota, there is no data available for the seroprevalence study so the overall score was calculated by the average of the other 3 metrics.
   • Grade A+ states: Puerto Rico, Vermont, Hawaii, Maine
   • Grade F states: Tennessee, Mississippi, Arkansas, Alabama

Here are the scores for each state

Alabama

• Case Rate per 100,000 = 26,524; grade: C-
• Death Rate per 100,000 = 398; grade: F
• Seroprevalence = 66.0%; grade: D
• Percent Fully Vaccinated = 51.1%; grade: F
• Overall Rank = 49; grade: F

Alaska

• Case Rate per 100,000 = 33,479; grade: F
• Death Rate per 100,000 = 166; grade: A
• Seroprevalence = 61.0%; grade: C
• Percent Fully Vaccinated = 62.3%; grade: C+
• Overall Rank = 26; grade: C+

Arizona

• Case Rate per 100,000 = 27,773; grade: D
• Death Rate per 100,000 = 411; grade: F
• Seroprevalence = 63.0%; grade: C-
• Percent Fully Vaccinated = 61.5%; grade: C
• Overall Rank = 48; grade: D-

Arkansas

• Case Rate per 100,000 = 27,683; grade: D
• Death Rate per 100,000 = 377; grade: D-
• Seroprevalence = 64.0%; grade: D+
• Percent Fully Vaccinated = 54.4%; grade: D-
• Overall Rank = 50; grade: F

California

• Case Rate per 100,000 = 23,281; grade: B+
• Death Rate per 100,000 = 226; grade: B+
• Seroprevalence = 55.5%; grade: B
• Percent Fully Vaccinated = 72.0%; grade: B+
• Overall Rank = 12; grade: A-

Colorado

• Case Rate per 100,000 = 23,979; grade: B
• Death Rate per 100,000 = 210; grade: A-
• Seroprevalence = 47.9%; grade: A-
• Percent Fully Vaccinated = 70.2%; grade: B
• Overall Rank = 10; grade: A-

Connecticut

• Case Rate per 100,000 = 21,204; grade: A-
• Death Rate per 100,000 = 303; grade: C+
• Seroprevalence = 44.4%; grade: A
• Percent Fully Vaccinated = 79.2%; grade: A
• Overall Rank = 11; grade: A-

Delaware

• Case Rate per 100,000 = 26,902; grade: D+
• Death Rate per 100,000 = 298; grade: C+
• Seroprevalence = 54.0%; grade: B+
• Percent Fully Vaccinated = 69.1%; grade: B
• Overall Rank = 23; grade: B-

Washington D.C.

• Case Rate per 100,000 = 20,112; grade: A-
• Death Rate per 100,000 = 189; grade: A-
• Seroprevalence = 63.6%; grade: D+
• Percent Fully Vaccinated = 74.1%; grade: A-
• Overall Rank = 13; grade: B+

Florida

• Case Rate per 100,000 = 27,568; grade: D
• Death Rate per 100,000 = 344; grade: C-
• Seroprevalence = 58.4%; grade: B-
• Percent Fully Vaccinated = 66.9%; grade: B-
• Overall Rank = 35; grade: C-

Georgia

• Case Rate per 100,000 = 23,689; grade: B
• Death Rate per 100,000 = 356; grade: D
• Seroprevalence = 63.8%; grade: D+
• Percent Fully Vaccinated = 54.7%; grade: D-
• Overall Rank = 37; grade: D+

Hawaii

• Case Rate per 100,000 = 17,089; grade: A+
• Death Rate per 100,000 = 99; grade: A+
• Seroprevalence = 34.2%; grade: A+
• Percent Fully Vaccinated = 78.2%; grade: A
• Overall Rank = 3; grade: A+

Idaho

• Case Rate per 100,000 = 24,947; grade: C+
• Death Rate per 100,000 = 275; grade: B
• Seroprevalence = 67.8%; grade: D-
• Percent Fully Vaccinated = 54.0%; grade: D-
• Overall Rank = 31; grade: C

Illinois

• Case Rate per 100,000 = 24,686; grade: B-
• Death Rate per 100,000 = 298; grade: B-
• Seroprevalence = 60.8%; grade: C+
• Percent Fully Vaccinated = 68.7%; grade: B-
• Overall Rank = 20; grade: B

Indiana

• Case Rate per 100,000 = 25,263; grade: C+
• Death Rate per 100,000 = 350; grade: D+
• Seroprevalence = 61.2%; grade: C
• Percent Fully Vaccinated = 54.8%; grade: D
• Overall Rank = 39; grade: D+

Iowa

• Case Rate per 100,000 = 24,189; grade: B
• Death Rate per 100,000 = 302; grade: C+
• Seroprevalence = 70.7%; grade: F
• Percent Fully Vaccinated = 61.9%; grade: C+
• Overall Rank = 32; grade: C

Kansas

• Case Rate per 100,000 = 26,561; grade: C-
• Death Rate per 100,000 = 295; grade: B-
• Seroprevalence = 62.2%; grade: C-
• Percent Fully Vaccinated = 61.4%; grade: C
• Overall Rank = 29; grade: C

Kentucky

• Case Rate per 100,000 = 29706; grade: D-
• Death Rate per 100,000 = 346; grade: C-
• Seroprevalence = 56.6%; grade: B-
• Percent Fully Vaccinated = 57.4%; grade: D+
• Overall Rank = 42; grade: D

Louisiana

• Case Rate per 100,000 = 25,226; grade: C+
• Death Rate per 100,000 = 370; grade: D-
• Seroprevalence = 68.9%; grade: D-
• Percent Fully Vaccinated = 53.5%; grade: F
• Overall Rank = 45; grade: D-

Maine

• Case Rate per 100,000 = 18,124; grade: A
• Death Rate per 100,000 = 169; grade: A
• Seroprevalence = 35.3%; grade: A
• Percent Fully Vaccinated = 79.5%; grade: A+
• Overall Rank = 4; grade: A+

Maryland

• Case Rate per 100,000 = 17,039; grade: A+
• Death Rate per 100,000 = 239; grade: B
• Seroprevalence = 49.9%; grade: A-
• Percent Fully Vaccinated = 75.6%; grade: A-
• Overall Rank = 9; grade: A-

Massachusetts

• Case Rate per 100,000 = 25,387; grade: C
• Death Rate per 100,000 = 293; grade: B
• Seroprevalence = 52.6%; grade: B+
• Percent Fully Vaccinated = 78.9%; grade: A
• Overall Rank = 15; grade: B+

Michigan

• Case Rate per 100,000 = 24,291; grade: B-
• Death Rate per 100,000 = 360; grade: D
• Seroprevalence = 56.9%; grade: B-
• Percent Fully Vaccinated = 60.1%; grade: C-
• Overall Rank = 27; grade: C+

Minnesota

• Case Rate per 100,000 = 25,692; grade: C
• Death Rate per 100,000 = 226; grade: B+
• Seroprevalence = 60.8%; grade: C+
• Percent Fully Vaccinated = 69.1%; grade: B
• Overall Rank = 18; grade: B

Mississippi

• Case Rate per 100,000 = 26,788; grade: D+
• Death Rate per 100,000 = 417; grade: F
• Seroprevalence = 69.4%; grade: F
• Percent Fully Vaccinated = 51.8%; grade: F
• Overall Rank = 51; grade: F

Missouri

• Case Rate per 100,000 = 23,156; grade: B+
• Death Rate per 100,000 = 330; grade: C
• Seroprevalence = 55.7%; grade: B-
• Percent Fully Vaccinated = 56.0%; grade: D
• Overall Rank = 17; grade: B

Montana

• Case Rate per 100,000 = 25,617; grade: C
• Death Rate per 100,000 = 313; grade: C+
• Seroprevalence = 47.5%; grade: A-
• Percent Fully Vaccinated = 56.7%; grade: D+
• Overall Rank = 19; grade: B

Nebraska

• Case Rate per 100,000 = 24,798; grade: B-
• Death Rate per 100,000 = 216; grade: A-
• Seroprevalence = 65.4%; grade: D
• Percent Fully Vaccinated = 63.6%; grade: C+
• Overall Rank = 22; grade: B-

Nevada

• Case Rate per 100,000 = 23,332; grade: B
• Death Rate per 100,000 = 349; grade: D+
• Seroprevalence = 60.1%; grade: C+
• Percent Fully Vaccinated = 60.8%; grade: C-
• Overall Rank = 25; grade: C+

New Hampshire

• Case Rate per 100,000 = 22,740; grade: A-
• Death Rate per 100,000 = 182; grade: A-
• Seroprevalence = 33.1%; grade: A+
• Percent Fully Vaccinated = 70.2%; grade: B+
• Overall Rank = 6; grade: A

New Jersey

• Case Rate per 100,000 = 25,355; grade: C+
• Death Rate per 100,000 = 376; grade: D-
• Seroprevalence = 60.9%; grade: C+
• Percent Fully Vaccinated = 75.6%; grade: A-
• Overall Rank = 33; grade: C-

New Mexico

• Case Rate per 100,000 = 24,886; grade: B-
• Death Rate per 100,000 = 356; grade: D
• Seroprevalence = 49.1%; grade: A-
• Percent Fully Vaccinated = 71.0%; grade: B+
• Overall Rank = 21; grade: B-

New York

• Case Rate per 100,000 = 26,376; grade: C-
• Death Rate per 100,000 = 347; grade: D+
• Seroprevalence = 61.5%; grade: C
• Percent Fully Vaccinated = 76.9%; grade: A
• Overall Rank = 36; grade: C-

North Carolina

• Case Rate per 100,000 = 25,355; grade: C
• Death Rate per 100,000 = 223; grade: B+
• Seroprevalence = 52.0%; grade: B+
• Percent Fully Vaccinated = 61.0%; grade: C-
• Overall Rank = 14; grade: B+

North Dakota

• Case Rate per 100,000 = 31,620; grade: F
• Death Rate per 100,000 = 297; grade: B-
• Seroprevalence data not available
• Percent Fully Vaccinated = 54.9%; grade: D
• Overall Rank = 41; grade: D

Ohio

• Case Rate per 100,000 = 22,999; grade: B+
• Death Rate per 100,000 = 328; grade: C
• Seroprevalence = 63.2%; grade: C-
• Percent Fully Vaccinated = 58.4%; grade: C-
• Overall Rank = 24; grade: B-

Oklahoma

• Case Rate per 100,000 = 26,293; grade: C-
• Death Rate per 100,000 = 360; grade: D
• Seroprevalence = 69.1%; grade: D-
• Percent Fully Vaccinated = 57.2%; grade: D+
• Overall Rank = 47; grade: D-

Oregon

• Case Rate per 100,000 = 17,038; grade: A+
• Death Rate per 100,000 = 177; grade: A
• Seroprevalence = 46.9%; grade: A
• Percent Fully Vaccinated = 69.9%; grade: B
• Overall Rank = 5; grade: A

Pennsylvania

• Case Rate per 100,000 = 21,973; grade: A-
• Death Rate per 100,000 = 348; grade: D+
• Seroprevalence = 54.6%; grade: B
• Percent Fully Vaccinated = 68.4%; grade: B-
• Overall Rank = 16; grade: B+

Puerto Rico

• Case Rate per 100,000 = 16,358; grade: A+
• Death Rate per 100,000 = 131; grade: A+
• Seroprevalence = 34.3%; grade: A+
• Percent Fully Vaccinated = 83.0%; grade: A+
• Overall Rank = 1; grade: A+

Rhode Island

• Case Rate per 100,000 = 33,226; grade: F
• Death Rate per 100,000 = 333; grade: C-
• Seroprevalence = 53.4%; grade: B+
• Percent Fully Vaccinated = 82.5%; grade: A+
• Overall Rank = 30; grade: C

South Carolina

• Case Rate per 100,000 = 28,592; grade: D-
• Death Rate per 100,000 = 344; grade: C-
• Seroprevalence = 64.5%; grade: D+
• Percent Fully Vaccinated = 56.6%; grade: D
• Overall Rank = 46; grade: D-

South Dakota

• Case Rate per 100,000 = 26,882; grade: D+
• Death Rate per 100,000 = 329; grade: C
• Seroprevalence = 61.3%; grade: C
• Percent Fully Vaccinated = 61.4%; grade: C
• Overall Rank = 38; grade: D+

Tennessee

• Case Rate per 100,000 = 29,715; grade: F
• Death Rate per 100,000 = 382; grade: F
• Seroprevalence = 67.4%; grade: D
• Percent Fully Vaccinated = 54.5%; grade: D-
• Overall Rank = 52; grade: F

Texas

• Case Rate per 100,000 = 23,215; grade: B+
• Death Rate per 100,000 = 298; grade: B-
• Seroprevalence = 69.7%; grade: F
• Percent Fully Vaccinated = 61.4%; grade: C
• Overall Rank = 28; grade: C+

Utah

• Case Rate per 100,000 = 29,026; grade: D-
• Death Rate per 100,000 = 147; grade: A+
• Seroprevalence = 69.2%; grade: D-
• Percent Fully Vaccinated = 64.3%; grade: C+
• Overall Rank = 34; grade: C-

Vermont

• Case Rate per 100,000 = 18,336; grade: A
• Death Rate per 100,000 = 96; grade: A+
• Seroprevalence = 28.9%; grade: A+
• Percent Fully Vaccinated = 81.1%; grade: A+
• Overall Rank = 2; grade: A+

Virginia

• Case Rate per 100,000 = 19,912; grade: A
• Death Rate per 100,000 = 236; grade: B+
• Seroprevalence = 45.1%; grade: A
• Percent Fully Vaccinated = 73.1%; grade: A-
• Overall Rank = 8; grade: A

Washington State

• Case Rate per 100,000 = 19,609; grade: A
• Death Rate per 100,000 = 166; grade: A
• Seroprevalence = 54.3%; grade: B
• Percent Fully Vaccinated = 72.5%; grade: B+
• Overall Rank = 7; grade: A

West Virginia

• Case Rate per 100,000 = 27,938; grade: D-
• Death Rate per 100,000 = 382; grade: D-
• Seroprevalence = 54.6%; grade: B
• Percent Fully Vaccinated = 57.6%; grade: D+
• Overall Rank = 44; grade: D

Wisconsin

• Case Rate per 100,000 = 27,604; grade: D
• Death Rate per 100,000 = 247; grade: B
• Seroprevalence = 66.7%; grade: D
• Percent Fully Vaccinated = 65.5%; grade: B-
• Overall Rank = 40; grade: D+

Wyoming

• Case Rate per 100,000 = 27,049; grade: D+
• Death Rate per 100,000 = 313; grade: C
• Seroprevalence = 62.5%; grade: C-
• Percent Fully Vaccinated = 51.6%; grade: F
• Overall Rank = 43; grade: D

The data indicates that during the pandemic, you were best off living on an island (Puerto Rico or Hawaii). If you couldn’t live on an island, then you were best off living in either Vermont or Maine. The states that were the worst to live in during the pandemic were Tennessee, Mississippi, Arkansas, and Alabama.

But the pandemic is not yet over. Today’s epidemiologic data from the CDC shows that we are likely entering a new COVID -19 surge. Since the beginning of the pandemic, we have seen that the percent test positivity starts going up about 2 weeks before the case numbers rise followed a few days later by a rise in hospitalization rates and then about 2 weeks later by a rise in death rates. The graph below shows that the test percent positivity (yellow curve) began to increase on March 19, 2022 and the case numbers then began to increase on April 5, 2022.

The number of COVID-19 hospitalizations (yellow curve in the graph below) then began to rise on April 7, 2022:

The daily death rate began rising on April 27, 2022 (not shown). With a recent societal move toward elimination of masking and social distancing, the number of cases, hospitalizations, and deaths will likely continue to rise in the coming weeks. So, there is still a chance for states to pull up their grades. But given the geographic variation in cultural attitudes toward infection control, I don’t expect this to happen.

April 29, 2022

Today, I got my second COVID-19 booster. On December 15, 2020, I was one of the first healthcare workers in the United States to get the newly approved Pfizer vaccine. In the nearly 16 months since then, I’ve had a total of 4 COVID vaccinations, 2 shingles vaccinations, and an influenza vaccination. I’m alive, I’m healthy, and I want to stay that way.

But in my home of Franklin County, Ohio, only 74% of adults are fully vaccinated with the initial doses of COVID vaccines and only 41% of adults are both fully vaccinated and received a booster. Franklin County’s vaccination numbers are only slightly worse than the United States as a whole. We are now approaching 1 million American deaths from COVID-19. More than a third of those have occurred since vaccines were available to all adults making most of these deaths preventable. So, why aren’t Americans getting vaccinated?

Vaccine hesitancy is the intersection of ignorance, cowardice, obstinance, and selfishness. Most people who unvaccinated fall into one or more of these categories. Improving vaccination rates requires different tactics for each of these groups of people.

The four causes of vaccine hesitancy

Ignorance. Ignorance about disease and about vaccines is hard to break. Nevertheless, it is probably the easiest of the four barriers to vaccination to overcome. The ally of ignorance is misinformation. A famous adage (incorrectly attributed to Mark Twain) states: “A lie can travel halfway around the world before the truth is putting on its shoes“. I the era of the internet, cable news, and social media, a better adage is: “A lie can travel around the world ten times before truth gets out of bed in the morning“. A subset of the ignorant is the skeptics who can be educated but will only accept education from members of their own kind. An OSU Buckeye fan will won’t be convinced by a Michigan Wolverine fan but might be convinced by a fellow Buckeye. Science is hard to understand and misinformation is a lot easier to understand. Education about vaccines needs to start in middle school science classes, continue in high school health classes, and continue further in physician offices.

Cowardice. Fear is amplified by ignorance. Like ignorance, misinformation is the ally of fear. Some people fear the metal needle, others fear the stuff that is in the syringe, and others just fear science in general. The great facilitator of fear is gossip. When one person tells another that he got a COVID vaccination and his arm was sore for a day, that story gets told to another person who tells another person, and on and on. By the time the tenth person tells the story, the report is that the vaccination caused the guy so much pain that he passed out, had a heart attack, and became impotent. Although education can help overcome cowardice, reassurance is more powerful, particularly when it comes from people you trust like pastors, sports figures, and movie stars. Once again, tribalism plays a role in reassurance. A Republican who won’t accept any reassurance from a Democrat might listen to a fellow Republican.

Obstinance. Some people are impossibly stubborn and no amount of education or reassurance will change their mind. Obstinance is the realm of the hard-core anti-vaxxers. At one extreme are those people who crave the attention they get by being anti-vaxxers or make money by being anti-vaxxers. This kind of secondary gain is nothing new and was the main motivation of snake oil salesmen, purveyors of patent medicines, and ponzi schemers. Robert F. Kennedy, Jr. and Dr. Sheri Tenpenny are examples of people who make a living by being anti-vaxxers. At the other extreme are those people who just can’t admit that they are wrong about anything and will dig their heels in deeper to try to convince themselves that they were right all along. Some obstinate people look for reasons to justify their decisions. For centuries, obstinate people have used their personal interpretation of 2,000 year old passages from the Torah, the Bible, and the Quran to justify a whole variety of hatreds, unhealthy behaviors, social deviance, and crimes. During the COVID pandemic, obstinate people used similar interpretations to claim religious exemptions from vaccination. Obstinance is hard to overcome and sometimes the only tactic that works is public shame.

Selfishness. People who do not get vaccinated because of selfishness often know that vaccines work. They just figure that if everyone else gets vaccinated then the disease will go away and they won’t need a vaccine. The best friend of selfishness is cowardice and the two often go hand-in-hand. Overcoming selfishness often requires a combination of reassurance and shame. However, unlike obstinance, selfishness can sometimes be overcome by private shame rather than public shame.

How do we fix it?

As healthcare workers, our main tools are education and reassurance. As such, we can have the biggest impact on those who are hesitant to get vaccinated because of ignorance and cowardice. It is tempting to use shame but shame is no more useful in changing ignorance than education is in changing obstinance. The trick is to know one’s audience – we should focus on people who are hesitant to get vaccinated because of ignorance or fear. Wasting time and emotional energy on those whose vaccine hesitancy is motivated by obstinance or selfishness is unproductive, frustrating, and exhausting.

COVID-19 is not the first deadly pandemic that the human race has faced and it certainly will not be the last. But we can learn from our public health failures in vaccination and use that knowledge to lay the foundation for more effective public health measures when the next pandemic comes around. The adults when the next pandemic occurs are the children of today. Our focus needs to be on education and reassurance of our children so that ignorance, cowardice, obstinance, and selfishness does not kill them when they are adults.

This pandemic appears to be waning and there are signs that life may be getting back towards normal. For all of the unvaccinated people who are happy to now be taking off their masks and going to restaurants, you can thank everyone who got a vaccination and made it possible.

…you’re welcome.

April 2, 2022

This week, the latest results of the Nationwide COVID-19 Infection-Induced Antibody Seroprevalence (Commercial laboratories) Study was released. These results estimate the percentage of the population of each state that has been infected with COVID-19 as of the end of December 2022. The results are quite remarkable and indicate that there has been enormous variation in the frequency of the infection among the states and among different age groups.

The commercial laboratories seroprevalence study is done monthly and uses left-over samples of blood drawn by commercial laboratories for routine blood tests. Patients getting tested specifically for COVID-19 are excluded. The antibodies detected in this study are directed against the nucleocapsid antigen and these antibodies are only produced from actual infection by the virus. The COVID vaccines produce antibodies against the spike protein antigens and these are not measured by the tests used in the commercial laboratories seroprevalence study.

Limitations of the seroprevalence study

The methodology of the seroprevalence study was published in the April 2021 edition of JAMA Internal Medicine. Because the samples are anonymous, there are several potential limitations of the study that could affect the prevalence results:

1. Healthy adults and children are less likely to have routine blood tests. Therefore, people with chronic diseases are more heavily represented in the samples. If patients with chronic diseases are also more likely to get infected with COVID-19, then the results may overestimate the percentage of the population previously infected with COVID.
2. Because the results depend on blood tests drawn in December 2021 from live patients, those people who died of COVID-19 prior to December 2021 are not included. This results in the study underestimating the percentage of the population infected since the beginning of the pandemic. This limitation can be corrected by adding the number of COVID deaths to the seroprevalence data to get total infection data (see the analysis later in this post).
3. People who do become infected with COVID-19 frequently have lingering symptoms (“long-haulers”) that could prompt their physicians to order various blood tests and this could result in the the seroprevalence study overestimating the percentage of the population previously infected with COVID.
4. Because antibody levels decline over time, it is likely that some patients who had COVID-19 infection early in the pandemic no longer have detectable antibodies against the virus. This could result in the study underestimating the percentage of the population infected since the beginning of the pandemic.
5. People with less access to healthcare due to socio-economic disparities and people who choose to avoid healthcare are less likely to have routine blood tests drawn. These groups include the uninsured, those who choose to not get vaccinated, residents of rural areas, and the poor. These groups are known be at higher risk of becoming infected with COVID-19. This could result in the study underestimating the percentage of the population infected since the beginning of the pandemic.
6. The number of blood tests from North Dakota, South Dakota, and Wyoming was too low for statistical analysis and so the study does not include seroprevalence rates from these three states.

Despite these limitations, compared to other epidemiology studies, the commercial lab seroprevalence study gives us the most accurate estimate of the percentage of the U.S. population that has had a COVID-19 infection. First, it is likely that the limitations above that result in overestimation are balanced out by those limitations that result in underestimation of the number of infections. Second, it is likely that the above limitations apply more-or-less equally among different states, allowing reasonably accurate comparison of the rates of infected between different states.

Differences between states

The CDC regularly reports on the total number of infections (based on nasopharyngeal PCR or rapid antigen tests) per 100,000 population since the pandemic began. These results indicate a low of 12.2% of the population in Maine to a high of 30.2% of the population in Rhode Island. However, these results depend on COVID test results reported to local health department and underestimates the true number of infections because (1) many infected people are asymptomatic and do not get tested, (2) many infected people use retail COVID tests with results that are not reported to the health department, and (3) many symptomatically infected people choose to not get tested. For these reasons, the seroprevalence studies offer a more accurate measure of the true rates of infection. The commercial lab study indicates enormous variations in the rate of COVID among the states and territories from a low of fewer than 1 out of every 10 people to a high of nearly 1 out of every 2 people

States with the lowest rates of infection. 15 states and territories had antibody prevalence rates of less than 30% of their population. The lowest rates were in Puerto Rico (9.7% of the population previously infected) and Hawaii (11.1% of the population previously infected. Living on an island was protective against becoming infected. Rhode Island (which is not really an island) is notable because by nasopharyngeal testing, it has had the highest rate of infection in the U.S. but by seroprevalence testing, it has had one of the lowest rates of infection. Rhode Island has the third highest vaccination rate (78.1% of its population) in the country. It is likely that for Rhode Island, the seroprevalence data is more accurate than the case rates determined by nasopharyngeal testing. The common feature of these 15 states & territories is that they all have high COVID vaccination rates with greater than 65% of their population fully vaccinated. We’ll give these states a grade of “A” for controlling the pandemic.

States with intermediate rates of infection. 19 states had rates of infection between 30-40% of their populations. We’ll give these states a grade of “C” for controlling COVID-19. With a United States overall average of 33.5% of the population previously infected, these states performed about average overall.

States with high rates of infection. 15 states had antibody prevalence rates above 40%. Iowa and Montana tied for the highest rate of infection with 47.7% of their population having been infected during the pandemic. These states also have low COVID vaccination rates with all of these states having fewer than 65% of their population fully vaccinated. This provides additional evidence that vaccination prevents infection. We’ll give these states a grade of “F” for controlling the pandemic. Lamentably, my own state of Ohio is the 4th worst in the country for antibody prevalence. The tone for Ohio’s response to COVID-19 was set early in the pandemic when AR-15 wielding anti-maskers protested in the front yard of our state’s Director of Public Health when she was trying to get her children off to school… she resigned, leaving Ohio with no health department director for months.

Differences between genders

Overall, there was no difference in the antibody prevalence among men (33.2%) and women (33.8%). In most states, the difference in rate of infection between men and women was less than 5 percentage points. However, three states had gender differences of more than 6 percentage points:

• Pennsylvania: 30.3% of men and 39.6% of women
• Indiana: 37.4% of men and 45.0% of women
• Montana: 51.4% of men and 43.9% of women

Differences by age

There was a striking relationship between age and seroprevalence of COVID-19 antibodies with the study indicating that far more younger Americans have been infected than older Americans:

In this table, the second column from the left is the seroprevalence of COVID-19 antibodies indicating past infection for each age group. The third column is the percentage of the population in each age group that has died of COVID since the pandemic began. The fourth column is the sum of the seroprevalence plus the percentage of each age population that died of COVID; this column gives a more accurate number of the total percentages of Americans in each age group that became infected with COVID and then either lived (seropositive group) or died of COVID (% died group). Even correcting for the fact that most of the deaths from COVID occurred in people over age 65, it is still clear that younger Americans were more likely to become infected than older Americans.

The causes for the age differences in infection rates is likely multifactorial. Younger people were more likely to have employment or school exposures whereas retired older people were more likely to be able to isolate at home during the pandemic. Younger people tend to live in larger households with children and adults together whereas older people are more likely to live with only their spouse or to live alone. Older Americans are more likely to be vaccinated than younger Americans. Older people are also more risk-adverse than younger people when it comes to masking and social distancing in public areas.

So what does all of this mean?

There are two ways to get immunity to COVID-19: (1) get vaccinated or (2) get infected. Immunity causes a reduction in the chance of subsequent infection (or re-infection). Immunity causes a greater reduction in the chance of hospitalization from infection (or re-infection). And immunity causes an even greater reduction in the chance of dying from infection (or re-infection).Which type of immunity is better? It appears that vaccination gives better immunity than past infection. But even if the two give equivalent immunity, the risk of dying from a COVID vaccine is negligible whereas the risk of dying from a COVID infection is 1 out of 85 – getting immunity from vaccination is far safer than getting immunity from infection.

Epidemiologists talk of “herd immunity” when enough of the population has immunity from either vaccination or past infection. Most epidemiologists now believe that between 75% and 90% of the population must have immunity in order to bring an end to the pandemic by herd immunity. Because people can get re-infected with COVID, the coronavirus will probably never go away but if we achieve herd immunity, we should be able to keep the number of new infections relatively low. More importantly, herd immunity should keep the number of hospitalizations and deaths extremely low. In other words, the goal of herd immunity is not to prevent all COVID infections but instead to prevent COVID hospitalizations and COVID deaths. Indeed, the current data indicates that most of the people who are hospitalized with COVID are unvaccinated and almost all of the people who are die of COVID are unvaccinated.

Currently, we know that 64% of the U.S. population has immunity by being fully vaccinated. We know that 33.5% of the U.S. population has immunity by having had a past COVID infection. What we do not know is to what extent these two populations overlap; that is, how many people who have had a COVID vaccination also had a COVID infection (either before or after they got their vaccination). Another way of looking at this is that we do not know how many people have immunity from either vaccination or past infection. Certainly more than 64% of the U.S. population has immunity but probably less than 90% has immunity.

To forecast what COVID may look like in future years, consider rhinoviruses. They cause 1/3 to 1/2 of all common colds. Given that the average person gets 2-3 colds per year, most people become infected with a rhinovirus every year and nearly everyone has been infected at least once by adulthood. Because re-infection with COVID can occur, it is likely that COVID will continue to circulate in the community for the indefinite future. Eventually, nearly everyone will have either been infected or been vaccinated. At that point, hospitalization or death from COVID should become uncommon. In other words, COVID won’t go away but it won’t kill you in the future.

The primary goal of medicine is to prevent people from becoming severely ill or dying from infections. A more aspirational (but usually unobtainable) goal is to prevent all infections, even mild ones. As long as there are people with weak immunity against COVID (either because they are not vaccinated or they have not yet been infected), then COVID will continue to cause hospitalization and death.

Therefore, our realistically obtainable goal in public should be to prevent severe COVID infection and prevent death from COVID. In that sense, we are reaching a point where we should not be looking at vaccine mandates but instead be looking at immunity mandates. In other words, instead of requiring all of a business’s employees to be vaccinated, we should be requiring all employees to either be vaccinated or have antibodies indicating past infection.

Immunity mandates should become our new public health doctrines – for our workplaces, our schools, and our military. For me personally, sign me up for a second booster when they become available… but I’ll pass on getting a COVID-19 infection to keep my immunity up.

February 5, 2022

In Monty Python and the Holy Grail, the cart-master chants “Bring out your dead”and a man carries a plague victim and throws him on the cart. The plague victim cries out “But I’m not dead”. The same is true for the COVID-19 pandemic: we want to bury it and go back to normal life but the pandemic is not quite over yet. Nevertheless, it is not too early to determine which states fared best in the epidemiology of the pandemic. So, let’s take a look at the pandemic losers and winners based on CDC data as of today.

Case numbers

The best way to compare case numbers between different states is by using the number of cases per 100,000 population. The lower the number, the better states did in controlling the spread of the disease.

The Winners:

1. Maine 12,225. The lowest case rate in the United States was our northeastern-most state. Maine took an early, aggressive approach to slowing the spread of COVID-19 with closure of restaurants and bars to dine-in customers on March 18, 2020 and with institution of a mandatory 14-day quarantine period for visitors from any other state on April 3, 2020. When restaurants re-opened, face masks were required for all customers and even now, face masks are still required for unvaccinated customers.
2. Hawaii 12,737. On the opposite side of the world, Hawaii took even more aggressive infection control measures, initially prohibiting travelers from other states and then later requiring travelers to provide documentation of vaccination and of a negative COVID test. Because of its isolation, Hawaii was able to maintain tight oversight of anyone coming onto its islands. Currently, Hawaii is considering requiring all visitors to the island to have a booster vaccination.
3. Oregon 13,039. Early institution of state-wide school closures, a stay-at-home order, and an indoor mask mandate helped Oregon keep its case numbers the third-lowest in the U.S.
4. Puerto Rico 13,388. Like Hawaii, Puerto Rico benefited by being an island during the COVID-19 pandemic. Additionally, COVID public health measures were far less politicized in Puerto Rico than in the rest of the country, perhaps because Puerto Ricans do not vote in presidential elections and do not have elected members of the U.S. congress. It is notable that there are no full service Fox Network TV channels or Spanish versions of Fox News in Puerto Rico.
5. Vermont 13,631. Early in the pandemic, Vermont issued a quarantine order for all visitors to the state and also issued a stay-at-home order. Vermont was very aggressive in its vaccination efforts and currently is the most vaccinated state in the country with 78.9% of its population fully vaccinated – Puerto Rico comes in next at 78.5%.

The losers: 

1. Rhode Island 30,265. I was surprised to find that Rhode Island has had the highest case rate in the country. Throughout the pandemic, the Rhode Island case rate looked quite similar to the rest of the country but during the Omicron surge, Rhode Island’s cases peaked at more than 500 per 100,000 on January 11, 2022 which is the highest daily case rate for any state at anytime during the pandemic. This is despite the state having a very high vaccination rate. The good news for residents of Rhode Island is that their COVID death rate has remained relatively low despite the high case numbers.
2. North Dakota, 26,551. Intuitively, one might think that North Dakota’s largely rural population would be protected from COVID-19 given how spread out people are from each other. But state-wide resistance to the institution of infection control measures and a very low vaccination rate resulted in North Dakota having the second highest case rate in the U.S.
3. Utah 25,040. A strongly conservative state, Utah has resisted mask mandates and other infection control measures.
4. Alaska 24,918. A lack of mask mandates and other infection control measures combined with an influx of tourists in the summer of 2021 resulted in a high early fall surge followed by a high Omicron surge.
5. Tennessee 24,782. When Michelle Ficus, the Tennessee vaccination director, raised alarm about the rising case rate and suggested that children should get vaccinated, Tennessee Republican lawmakers’ response was to fire her. This is a reflection of the state’s reluctance to institute public health measures during the pandemic which resulted in Tennessee having the fifth highest case rate in the country.

Death rate

Although case rates do give important information about how easily COVID-19 was spread in a given state, the case rate can be influenced by testing availability and by the population’s willingness to get tested. Also, if more tests are done for screening purposes in one state, then infected but asymptomatic people will be identified which can drive case numbers higher than in other states. The death rates are not affected by these factors. However, death rates can be affected by how well a given state protects its vulnerable population (nursing home residents, the elderly, etc.) and can be affected by the availability and quality of health care in that state. The following are the winners and losers with respect to the number of deaths per 100,000 population.

The Winners:

1. Vermont 75. There is no surprise here. Vermont also had the 5th lowest case numbers in the country and the fewer cases of COVID occur in a state, the fewer people will die of COVID in that state. Vermont also has one of the lowest rates of obesity in the country and obesity is a major risk factor for dying if a person does get COVID. Vermont has the 5th lowest percentage of the population that is uninsured. Together, these factors resulted in Vermont having the lowest COVID mortality rate in the U.S.
2. Hawaii 78. Once again, having a low number of COVID cases results in a low COVID mortality rate. Hawaii’s strict infection control measures including quarantine of incoming visitors kept its COVID deaths much lower than the rest of the country.
3. Puerto Rico 111. Living on an island provided some of the best protection against getting COVID and consequently from dying of COIVD.
4. Utah 124. The state of Utah is a paradox with the third highest case rate but the fourth lowest mortality rate. Utah benefited by having a higher proportion of its cases occurring in the later stages of the pandemic, when the more contagious but less fatal Omicron variant replaced the considerably more lethal Delta variant.
5. Maine 125. The same measures that gave Maine the lowest case rate in the country also gave it the fifth lowest death rate in the country. This is despite Maine having the highest percentage of its population over age 65 compared to all other states. The implications is that community infection control measures are effective, even when you have an inherently high-risk population.

The losers: 

1. Mississippi 359. The state with the highest rate of obesity has had the highest COVID mortality rate. Mississippi also has the fifth highest percentage of its population being uninsured. In addition, Mississippi has the lowest per capita income in the U.S. which likely contributed to barriers to healthcare access. Relative to its population, more Mississippians died than residents of any other state.
2. Arizona 349. On the surface, Arizona should not have the second highest death rate in the country. It is closer to average when it comes to the rate of obesity, population over age 65, income, and vaccination rate. Despite this, COVID has become the state’s most common cause of death.  Arizona’s high death rate has been attributed to its lawmaker’s unwillingness to adopt COVID mitigation measures and its governor has been called the “anti-science governor”.
3. Alabama 342. Factors that contributed to Alabama having the third highest death rate include having the second lowest vaccination rate in the country and the third highest obesity rate in the country. For the first time in history, the annual number of deaths in Alabama exceeded the annual number of births in Alabama.
4. New Jersey 341. Early in the pandemic, there were no vaccines, there were no monoclonal antibody treatments, and infection control measures were not yet fully instituted. The bulk of New Jersey’s deaths occurred in the first 3 months of the pandemic, coincident with the surge in deaths in adjacent New York City. Since then, New Jersey’s death rate has been lower than average but so many people in New Jersey died early in the pandemic that it results in the state having the fourth highest death rate for the pandemic overall.
5. Louisiana 327. Like its neighbor Mississippi, Louisiana has a high rate of obesity and a low per capita income. Like New Jersey, Louisiana experienced a much higher surge in COVID in the first 3 months of the pandemic when we understood less about how COVID is transmitted and about how to treat COVID infection. When COVID hit New Orleans in March 2020, the number of cases overwhelmed the city’s healthcare system and many residents died.

Case fatality rate

If a state had a high case rate, it would be expected to also have a high mortality rate, simply because more people were infected with COVID. The case fatality rate overcomes this by telling us how good a state’s health care systems were in protecting its most vulnerable populations and about how good the health care systems were in treating patients who became ill with COVID. The case fatality rate is the percentage of people infected with COVID who then died of COVID. The case fatality rate averaged 1.2% for the United States as a whole.

The Winners:

1. Utah 0.50%. Having a lower percentage of the population over age 65 than any other state, Utah benefited by being the youngest state in the country. Utah also has a low percentage of the population that is obese. As a consequence, the population of Utah as a whole is considerably less vulnerable to severe COVID and death-by-COVID than other states.
2. Vermont 0.55%. Vermont is one of the clear winners in the COVID pandemic and its second to the lowest case fatality rate is a result of having the highest vaccination rate in the U.S.
3. Alaska 0.56%. Alaska has had one of the highest case number rates in the country but Alaskans who got infected were less likely to die. Because a large portion of Alaska’s COVID cases occurred in the latter portion of the pandemic, a larger number of Alaska’s cases occurred in vaccinated individuals with those vaccines conferring protection against death from COVID. Additionally, a large percentage of its infections were due to the Omicron variant which has a lower case fatality rate than other variants. Alaska also has the second lowest percentage of its population over age 65 in the country meaning that its population was less vulnerable to death, even before vaccines were available.
4. Hawaii 0.61%. With early institution of visitor quarantining and public health measures, Hawaii was able to keep its case numbers very low in the first half of the pandemic and as a consequence, most of Hawaii’s COVID cases occurred in the latter portion of the pandemic, when a large portion of its population was vaccinated and thus protected from COVID death. Hawaiians have good healthcare with only 4.1% of its population uninsured, second only to Massachusetts. Hawaii also has the third lowest rate of obesity and fifth highest rate of vaccination in the country.
5. Puerto Rico 0.83%. Like Hawaii, Puerto Rico was able to keep its case numbers exceptionally low in the first stages of the pandemic when COVID was more likely to be fatal. It has only been in recent months that the territory has seen its cases surge from the less lethal Omicron variant in the setting of having a larger percentage of its population vaccinated than most states.

The losers: 

1. Mississippi 1.61%. The combination of being the most obese state and the fifth least vaccinated state proved lethal to Mississippi residents who became infected with COVID who were more likely to die of their infection than residents of any other state. A high percentage of the state’s population is uninsured with the result of disparities in access to healthcare as well.
2. Pennsylvania 1.54%. Compared with other states, Pennsylvania is fairly average with respect to risk factors such as population over age 65, obesity, vaccination rates, per capita income, and percentage of the population that is uninsured. Pennsylvania was also able to keep its case rate relatively low in the first half of the pandemic. So why were Pennsylvania residents second only to Mississippi residents with respect to likelihood of dying if they became infected with COVID? One possibility is that there was less testing done in Pennsylvania compared to other states with the result that fewer asymptomatic or mildly symptomatic COVID infections were identified, thus driving up the fatality rate among those people who were actually diagnosed. This is suggested by the fact that Pennsylvania’s death rate of 3.2 per 100,000 is closer to average among the states.
3. Arizona 1.52%. The same reasons that Arizona has had the second highest death rate in the country have contributed to it having the third highest case fatality rate. A relatively high case number rate suggests that there was plenty of testing being down (as opposed to Pennsylvania). Arizona did not have a disproportionate number of cases occurring early in the pandemic (as opposed to New Jersey). Arizona’s high case fatality rate may be more a result of its lawmaker’s public health policy and less a result of an inherently more vulnerable population.
4. Alabama 1.52%. A very high rate of obesity coupled with a low vaccination rate resulted in Alabama residents being the fourth most likely to die if they contracted COVID.
5. New Jersey 1.50%. Although New Jersey currently has one of the highest vaccination rates in the country, a large percentage of its cases and deaths occurred in March 2020, before vaccines were available resulting in a high case fatality rate early in the pandemic. In recent months, however, New Jersey’s case fatality rate has been much lower than average and as a result, New Jersey’s experience provides strong evidence that vaccinations prevent deaths.

Vaccination rate

In the preceding analysis, it is pretty clear that states with higher vaccination rates fared better during the COVID pandemic than states with lower vaccination rates. In a previous post, I showed how political party voting patterns are strongly associated with how likely a state’s residents are to be vaccinated. The five states with the highest percentage of the population vaccinated all voted Democrat in the last presidential election and the five states with the lowest vaccination rates all voted Republican in the last presidential election.

The vaccination rate is important not only for keeping a state’s residents alive, but may also be a determining factor for business development in the future. Businesses do want their employees to all be vaccinated in order to control expenses by reducing absenteeism and reducing health care costs. Vaccination also translates into fewer dead employees. But businesses are loath to unilaterally impose mandates for fear of losing some employees and for fear of negative public opinion. Therefore, many businesses may chose to expand their operations in those states where their employees are likely to be vaccinated without having to impose an employee vaccine mandate. In this sense, the vaccine winner states today could become the business winner states in the future.

The Winners:

1. Vermont 78.9%
2. Puerto Rico 78.5%
3. Rhode Island 78.1%
4. Maine 77.1%
5. Connecticut 76.0%

The losers: 

1. Idaho 47.6%
2. Alabama 48.9%
3. Wyoming 49.5%
4. Mississippi 49.7%
5. Louisiana 51.4%

How you can be a winner

Overall, Americans who get COVID have a 1.2% chance of dying from it. In other words, 1 out of every 83 people who become infected will die. So, when you get infected, you are taking a gamble with life and death. By looking at those states that fared well during the pandemic and those that fared poorly, you can determine how to improve your odds of surviving the pandemic:

• Live in a state where lawmakers take science seriously
• Get vaccinated
• Don’t be obese
• Live on an island
• Have health insurance
• It was more important to be strict with infection control measures early in the pandemic than later in the pandemic

January 22, 2022