1. HEALTH AND DISEASE

Everybody gets sick and everyone eventually dies but, where you live is an important factor in how often and from what causes your health will suffer. Geography offers a powerful set of tools to investigate the spatial patterns of health and health care.

Medical Geography, also sometimes called Health Geography, is a vibrant subfield of the discipline. Great variations are evident in the patterns of both diseases and health care at many scales. Geographers use spatial analyses to figure out why people get sick. Geographers can also analyze patterns of health care, to measure the effectiveness of treatments. This chapter explores the patterns of health, disease, and treatment while presenting examples of how geographers use their epistemology, methodologies and communication strategies in the fight to maintain the health and well-being of individuals and communities both in the United States and elsewhere. 

Image Gallery:

Health and Medical Geography

Figure 4‑1: Lithographic Map - John Snow mapped locations where cholera victims lived in London in an effort to isolate the source of the cause of the disease. Source: Wikimedia

The application of geographic techniques in the quest to address health crises is one of the earliest and most famous uses of spatial statistics to solve a pressing medical problem. In London in 1854, there was a severe outbreak of cholera, a gastrointestinal illness generally caused by drinking water contaminated by human feces. Back then, nobody quite understood that microscopic organisms, like bacteria, were capable of causing such violent illnesses. Instead, most medical experts believed that a kind of poisonous air, called miasma, was responsible for infectious diseases like cholera and the plague. The fear of miasma drove thousands, especially the wealthy, to seek healthy air in mountain or coastal resort towns. John Snow, a physician from London, worked in a neighborhood where there were many cases of cholera during the 1854 outbreak. Snow suspected that the miasmic air could not be the cause of cholera because other neighborhoods had similar air quality characteristics, but not the same rate of cholera. Instead, Snow guessed that the water supply was somehow contaminated, although he could not identify the “poison” in the water, even with a microscope. In order to test his theory, Snow first made a mental map of the locations where people had contracted cholera. He realized that cholera cases were spatially clustered 

Figure 4‑2: London, England.  This memorial water pump commemorates John Snow's scientific breakthrough in the diagnosis of Cholera. Note: the missing pump handle. Wikimedia

around one public water well. Snow then hypothesized that if the handle to the water pump at the geographic center of the cholera outbreak was removed, then local residents would be forced to get water elsewhere, and the incidence of cholera would begin to subside. To test his hypothesis, Snow convinced local authorities to remove the well’s pump handle and indeed the cholera epidemic lessened. Snow later made a physical point map indicating the location of the cholera patients’ residences and the poisoned well. Snow’s effort can be quickly replicated today using GIS and the results of simple statistical analyses of Snow’s data points to the remarkable accuracy of his initial hypothesis. More importantly, Snow’s map overturned centuries of bad science on disease while paving the way for the adoption of the germ theory of disease that is widely accepted today. 

Though cholera still affects several million people per year, causing over 100,000 deaths worldwide, it is no longer the threat it once was, thanks in large part to advancements in basic water sanitation technology. Still, millions of people in the developing world have poor access to clean drinking water. As a result, water-born illnesses similar to cholera kill many thousands, especially children, through dehydration caused by diarrhea and vomiting. 

Health Metrics

World Bank 

Data Bank

An Interactive website with data, maps, and graphics.

How healthy people are in a country, a state, or neighborhood is both critical and complicated. There are various measures of well-being called health metrics, that one could use to compare the physical and/or emotional well-being of persons and/or groups. A health metric that combines several measures known as a health index is probably the most useful type of health metric for a group of people. Experts disagree though on which factors are most important to include in a health index, who should be included in a health index, and what sort of other factors (like poverty or war) should be included in a health index. 

Figure 4‑3: World Map - Infant Mortality Rate. Sub-Saharan Africa has rates ten times that found in the developed world. Source: World Bank

Infant Mortality Rate

One of the most useful health metrics is Infant Mortality Rate (IMR), which is a count of the number of children who die during their first year of life per 1,000 live births in that region. 

Global disparities in IMR are substantial. Much of the variation in infant mortality can be traced to poverty, and the various problems associated with being poor, especially malnutrition. Other factors, including disease, lack of access to quality health care, and unsanitary living conditions also contribute to poor survival rates for infants. For these reasons, the infant mortality rate is an excellent indicator of the overall health of a population. 

Figure 4‑4: US Map - The Infant Mortality Rate in the United States is twice as high in Mississippi than it is in New Hampshire. Source: CDC

Infant mortality rates in the United States are low on average. They should be in the country that spends more on health care by a wide margin than any other country in the world. However, despite the extremely high medical costs in the US, the IMR for American babies is three times higher (6 vs 2 per 1000) than it is for babies born in Finland or Japan. Shockingly, the American IMR is also higher than it is in Botswana, Lebanon, and Cuba. The reason for the high IMR in the US is complex, but poverty and the peculiar American health care system are clearly major factors. The role of women in society also affects a country’s IMR. That piece of the puzzle is explored later in the chapter on gender.

The map of IMR by US state makes it evident that poverty, ethnicity and the local political climate are key predictors of infant health in the US. Babies born in liberal, white and prosperous Vermont are half as likely to die as those born in states with a large number of poor, minority and politically conservative voters – like Mississippi and Alabama. Studies show that the problem lies not so much in the hospital care provided babies but in the 10 months or so after babies come home from the hospital. It is during these later months that the health care system breaks down for infants from poor families, especially if their parents are African-American. But the map shows this is not just a matter of poverty or ethnicity. Cuba, for example has much less wealth than the US, and a higher percentage of people of color, but the Cuban government’s willingness to delivery cheap, accessible healthcare for everyone keeps their IMR lower than United States’ IMR. 

Figure 4‑5: World Map - Life expectance ranges from a low of less than 45 years in parts of Africa to 82.5 in Japan. Source: World Bank.

Life Expectancy

Like IMR, life expectancy is a useful indicator of the overall health of a population. This metric is an estimate of how long a person is expected to live on the day they were born. Calculations are largely based on observed death rates, plus additional considerations. The life expectancy of any group of people can be greatly affected by things like war, or the outbreak of diseases. In Africa, for example, after years of improvement, the life expectancy recently stagnated as AIDS swept across the continent. Iraq and Syria have seen life expectancy downgraded in recent years as wars in the region continue to wear on indefinitely.

In the United States, babies born today can expect to live to be about 79 years old. Again, this isn’t great considering that life expectancy generally is a product of national wealth and health care expenditure. Almost every developed country in the world and even some developing nations (Chile, Cuba, Costa Rica, e.g.) better life expectancies than Americans. Depressingly, in recent years, life expectancy in the US has gone down which indicates troubling trends in our society. Rising poverty and associated lifestyles are generally cited as reasons for the shrinking life span in the US. 

Measure of America

An interactive mapping and data tool with a host of display and download options.

Figure 4‑6: US Map - Life expectancy in Mississippi is 75 years, but in Hawaii, it is over 81. Substantial variation exists within states too. Poverty and ethnicity are key causal variables in the differences. Source: Measure of America / CDC 

The geography of poverty, government policies, and cultural practices all affect longevity. In McDowell County, West Virginia, where Americans have the shortest life expectancy (76.5 males; 81.2 females), you’ll find that their median income is around $25,000 a year, about 20% don’t have health insurance, few people complete college, over 16% suffer from diabetes, and over 35% of adults smoke. Even the homicide rate is exceptionally high McDowell County. As a result, babies born in wealthy and health-conscious Marin County, California can expect to live nearly 15 years longer than babies born in McDowell County, West Virginia. 

County Health Rankings

An interactive mapping/database of health outcomes and quality of life indicators

Ethnicity plays an important role in health too, but it appears to be less important than geography. For example, Asians, perhaps because of their dietary practices, better access to health care, and maybe genetics, can expect to live about 13 years longer than African-Americans in general. When you combine ethnicity, gender, and location, the difference becomes even greater. For example, African American boys born in Washington DC today have a life expectancy of only 66.5 years, whereas Asian-American girls born in Boston are expected to live, on average, to almost 92! On the other hand, African-American boys born today in Minnesota may expect to live to be about 80 years old on average, which is about the same Asian-American boys born in Hawaii. The point is that lifestyles, dietary practices are affected by both ethnicity and geography. Indeed, what may seem a common “ethnic behavior” in one part of the US may not be so common among the same ethnicity in another part of the country.

Physical and Mental Health 

Another way of gathering data about the overall health and well-being of an individual or a group of people is to survey them. Geographers use survey methods to gather information about a wide range of topics. Well done surveys are complex to plan, perform and analyze; so researchers must exercise extreme caution when using survey data, especially when the survey data was collected by others. The world’s largest telephone survey is done by the Centers for Disease Control and Prevention (CDC) with the aid of local health departments. This survey is called the Behavioral Risk Factor Surveillance System (BRFSS) and it provides a substantial amount of quality data about the health and health care of Americans. A number of questions are useful in measuring the quality of life of people around the US. The CDC makes this data available in a variety of formats, including format useable in a GIS, allowing health geographers easy access to exceptionally high-quality data sets necessary to solve numerous health-related problems.

Healthy Days

Centers for Disease Control 

Behavioral Risk Factor Surveillance System 

An outstanding source of data and maps about American’s Health

A couple of the most basic questions asked by the CDC on the BRFSS are “Would you say that in general your health is _______? (Excellent, Very good, good, fair, poor) and “How many days in the past 30 days was your physical health poor?” (numeric answer, none, not sure, refuse to answer). Similar questions are asked about mental health. The answers to these questions can be mapped at various scales (county, city, state, etc.) to paint a compelling picture of a region’s health. Hundreds of researchers, and dozens of organizations working to improve the health and well-being of communities, use this data.

Figure 4‑7: US Map - Eastern Appalachia and parts of the South report five times as many poor health days as some counties in the Upper Midwest. What are the costs to employers and taxpayers?  Source: CDC / County Health 

Survey results indicate a wide variation in the number of days people are sick over the course of any 30-day period in the US. In some places, people on average have less than two “sick days” per month. In other places, especially the Deep South and Appalachia, people are sick, on average, about seven days per month. While a few days difference may not seem noteworthy, multiplied by millions of people that live in most states, it is a huge difference. Chronic illness has significant implications for the economy of a region at the very least. Imagine for a moment how a company looking to open a factory in Appalachia would evaluate the health indicator data for a county where people are sick about three months out of every year? How much money would the factory stand to lose in a location like this? The unhealthy conditions of Americans living in poverty are not only a humanitarian concern but a significant economic drain on the entire US economy because the poor health of Americans in other regions of the country is often passed on to the rest of the country via external costs -like extra taxes and increased health insurance costs.

Figure 4‑8: US Map - Many poor counties have over 10% of their population receiving disability payments from the US government. Age is partly a factor, but unhealthy lifestyles cost American taxpayers billions annually, while contributing to a cycle of poverty. Source: Social Security 

Disability

One of the key outcomes of poor health is disability. Over 10 million Americans were receiving disability payments at the end of 2017. On average, the monthly benefit paid to claimants was around $1,200. The program began in 1957, but expanded rapidly in the 1990s, after cuts to other welfare payments eliminated cash payments to the able-bodied poor, many of whom were economically struggling parents of small children.

The Truth Initiative is a nonprofit organization dedicated to eliminating tobacco use. 

The article linked below discusses the difference in health outcomes for states with prevalent tobacco use:

Tobacco Nation 

Unhealthy lifestyles, dangerous working conditions, risky cultural behaviors, and bad luck all increase the likelihood of individuals becoming dependent on the government for support. By mapping these individuals as groups, we can see very uneven patterns of disability across the US, which strongly suggests that both cultural practices and economic conditions are important causal variables in the creation of a disability crisis in the United States. Employment in mining and factory work seems one predictor of worker disability, which makes sense because those jobs are often physically demanding and sometimes dangerous. A lack of economic diversity in many of these same locations means that few other job opportunities are available for those with only a physical disability. This means, that even if you were injured while working in one job, in some parts of the country, you could find another job where your physical condition didn’t matter. In some parts of the US, because the types of jobs are limited to hard physical labor, an inability to lift heavy objects (for example) would keep you from finding almost any job.

The geographic pattern evident in the map of disability welfare differs wildly from media stereotypes about persons receiving government welfare. Mapping disability coverage offers a counterbalance to a common, misguided stereotype of the urban welfare queen, the politically charged symbol of those who abuse government assistance, generally assigned to women of color. The map of disability payment hotspots shows that in reality, welfare payments go to communities that are overwhelmingly rural, and predominantly white. While it is difficult to estimate the percent of fraudulent disability claims, the intense clustering visible on the map invites further research into why some counties have so many disabled people. It is statistically unlikely that nearly one-third of any region’s total population could be physically disabled by workplace injuries, even though the demographic profiles of poor, rural counties skew toward the elderly and ill-prepared to survive with a disability. To account for this reality, geographers age-adjust data to help account for the fact that older people are more likely to suffer a workplace injury from which they cannot recover. People without a high school diploma may also be declared disabled by an injury that would not qualify as an injury for a person with a college degree. It is reasonable to assume serious injuries normally occur in a somewhat random pattern around the US, therefore should be a somewhat random pattern to the disability map as well. Instead, there is a definite clustering pattern to disability claims in the US, which suggests fraud -which is very difficult to prove. Closely associated with the disability epidemic in the United States is burgeoning opioid drug addiction. Many of the same regions of the US where physical disabilities are very common also suffer from widespread opioid addiction. This crisis is explored more fully in the chapter on crime and punishment.

Autism

One of the disabilities recognized by the US government is Autism, which is, in reality, a group of related conditions characterized by a range of cognitive and behavioral impairment levels, more properly known as Autism Spectrum Disorders (ASDs). ASDs are among the fastest-growing health concerns worldwide. The cause or causes of ASDs is the subject of exceptionally intense debate and millions of hours of research. Nobody yet knows for sure what causes ASD.

Figure 4‑9: Map:  Autism Cluster in wealthy, northwestern Los Angeles, County.  Source: UC Davis Health System

Figure 4‑10: Infographic - In recent years, measles, a disease that was once declared eliminated in 2000 has re-established itself.  Most people who get measles were not vaccinated, so exposure from outside sources spreads rapidly. Source: CDC

Jedi Mind Trick 

Asking “Where do children diagnosed with an Autism Spectrum Disorder live?” provides very important clues about the causes of autism, and the challenges associated with the diagnosis of ASD.

Generally, researchers think that genetics is the primary factor in ASD, but determining causality has proven to be very complex. Partly this is because the symptoms themselves are hard to identify, but it’s also because of the geography of autism. Medical geographers and spatial epidemiologists are heavily involved in autism research because autism clusters are reasonably easy to identify on a map. In greater Los Angeles, for example, unusually high rates of autism appear in Torrance, Beverly Hills, Van Nuys, Calabasas, Laguna Beach, and Mission Viejo. Of course Los Angeles has a well-earned reputation for air pollution, leading some to believe that exposure to airborne toxins is a causal variable. Indeed, there is some evidence to suggest that environmental exposures to various pollutants may function as triggers for the condition, but definitive answers have proven elusive. What is clear is the effect of neighborhood on the diagnosis of ASD. Most of the autism clusters in greater Los Angeles are in wealthy neighborhoods; so geographers suspect that the disorder’s dramatic rise in upscale areas is likely a product of improving diagnostic capabilities among medical professionals serving the upper-middle class, rather than evidence of a real increase in ASD. In poorer areas, where environmental conditions are generally far worse, parents, families and school officials appear to misdiagnose ASD or overlook symptoms that are commonly noticed in wealthier communities. Ethnicity and economics may also affect the likelihood that parents will acknowledge or accept a diagnosis of ASD for their child. The uneven spatial pattern of diagnoses makes the task of identifying the root causes harder because the known pool of persons with diagnosed with ASD is an unrepresentative sample of the true ASD population. 

Vaccinations 

The most controversial topic surrounding ASD has been the popular, but scientifically unproven, belief that vaccinations cause ASDs. These unfounded fears keep many parents from vaccinating children against common, and sometimes deadly, diseases. As a result, a handful of diseases thought extinct have re-established themselves in the US. 

Measles is a classic example. In the year 2000, the CDC declared measles “eliminated” from the US because no Americans had the disease. In the 1960s, millions were infected with measles and hundreds died every year. Today, Americans not vaccinated against measles remain at risk when traveling internationally, or when exposed to international visitors, or immigrants from affected regions. A significant outbreak of measles occurred in Southern California during early 2015, after a tourist with measles visited Disneyland in Anaheim and it spread among unvaccinated children in the region. In 2019, the worst outbreak in many years sent hundreds to hospitals across the country. The worst outbreak was probably in New York City’s Orthodox Jewish community, where exposure to people from Israel is high and vaccination rates are relatively low.

Figure 4‑11: California Counties - Pertussis infection rates vary considerably across California in 2014. Areas with large immigrant populations and large anti-vaccine populations show high infection rates. Source: CDC

Pertussis, better known as “whooping cough” is another disease that has re-emerged in recent years thanks to vaccination paranoia. In recent years, the number of pertussis cases in the US has risen to levels not seen since the 1940s. By mapping pertussis rates by California’s county shows an interesting pattern. Higher rates of pertussis are evident in parts of California with many Latin American migrants. Latinos had by far the highest rate of whooping cough at 174 cases per 100,000 in 2014. This high rate is likely caused by poor access to affordable, quality medical care for pregnant women and infants. Language barriers between patients and health care providers may exacerbate the problem. Extended families who live together in crowded housing, especially if adults recently arrived from Latin America without updated vaccinations, can put at risk the health of infants and small children living within the household. 

The map of pertussis in California also shows outbreaks in some of the wealthiest, best-served counties. Many wealthier families purposefully opt-out of vaccination programs, thereby fueling the pertussis epidemic in otherwise wealthy, healthy and medically well-served communities. In parts of upscale Sonoma County, where pertussis rates were exceptionally high in 2014, several schools had vaccination rates well below the rates considered safe. In some schools, more than half of the children were not vaccinated. Their parents had signed “personal belief exemptions”, which excused children from being vaccinated based on religious or moral grounds.  Still they sent their children to school not immunized against common contagious diseases. Though pertussis is unlikely to kill healthy children in upscale neighborhoods, it is nevertheless highly contagious and spreads into other neighborhoods, or even countries, where infants from poor families are at serious risk from the disease. California eliminated most exemptions for children attending public school in 2015.

Children who are not immunized against disease take advantage of what is called, herd immunity, a condition that characterizes groups of people in which around 90% of the group have developed immunity, generally through vaccinations, to an infectious disease. The group immunity critically lowers the chances of infection for those without vaccinations and/or immunity. This behavior is sometimes used as an example of the free-rider problem, that occurs when individuals take advantage of a community resource without contributing to the maintenance of the shared resource. The free-rider problem echoes the “tragedy of the commons” scenario, discussed in the Political Geography chapter. Those people with compromised immune systems who cannot be vaccinated must rely on herd immunity to keep from getting sick, making it imperative that those with otherwise healthy immune systems get vaccinated for the good of others.

Geography of Disease

Cool Map: 

Health Map

An interactive mapping program from the Boston’s Children Hospital that shows local outbreaks of infectious diseases.

Pertussis is an example of an infectious disease because it is transmitted from person to person. Some infectious diseases also are transferred from animals to people. Infectious diseases, also known as communicable diseases, figure prominently among the leading causes of death in developing countries. In the United States, Europe, and other developed regions, people are more likely to die from non-communicable diseases, such as heart disease, stroke, and cancer. Most non-communicable illnesses are also considered chronic diseases because they affect people over a longer period, and generally affect older adults. Infectious diseases, on the other hand, may affect anyone but are more likely to kill people who are poor, already unhealthy and/or children. In order to demonstrate how geography aids our understanding of health and disease, several short vignettes about specific diseases follow in the paragraphs below.

Figure 4‑12: Seattle, WA - Policemen wear masks during the great influenza pandemic of 1918-20  Source: Wikimedia

Influenza

Influenza, popularly known simply as “the flu” is an airborne infectious disease that generally spreads when someone sneezes or coughs microscopic pathogens (germs) into the air. The flu kills thousands of people each year. Sometimes, flu outbreaks are regional and last only a few months. These short-lived regional outbreaks of diseases are called epidemics. Occasionally, diseases like the flu get out of control, spreading across vast areas and lasting for many months. Massive, worldwide disease outbreaks such as these are termed pandemics. The most infamous flu pandemic was the dreaded Spanish Flu that broke out during World War I and killed somewhere from 50 to 100 million people. Nearly the entire globe was affected, and poor countries, like India and China, suffered exceptionally high death tolls. In the United States, over 1/4th of the population was infected. Over one-half million Americans died from it, far exceeding the number of Americans that died in fighting in World War I. 

Recently, a version of the Spanish Flu (now called H1N1) returned. It was declared a global pandemic and generated worldwide panic. Nobody is sure where the flu strain began or where patient zero (index case) lived, but the epidemiologists traced the first obvious signs of the pandemic to Veracruz Mexico. There, factory-style hog farming may have created conditions ideal for the first known cases to develop and diffuse around January of 2009. 

Figure 4‑13: Canoga Park, CA.  This billboard appeared in LA’s San Fernando Valley in early 2010 as part of a large public health campaign to dampen the effects of the H1N1 influenza outbreak.  The campaign was generally successful. (Link to photo within shared album)

By April 2009, it was clear the flu was rapidly spreading in Mexico. In response, officials drastically curtailed public activity in Mexico City. The European Union Health Commission issued travel advisories, urging people not to travel to Mexico, or the United States, where flu cases were beginning to appear. A variety of quarantine orders swept the globe, keeping people in motels, on cruise ships, and in airports. After about six months, the incidence of new flu cases began to fall, and by February 2010, the pandemic was over. The 2009-2010 flu pandemic officially killed 18,000 worldwide, but other estimates suggest as many as 500,000 died because so many deaths were in parts of Africa and Asia where few laboratories exist capable of confirming the exact causes of death. In the United States, where the public health system responded quickly and efficiently, Americans appear to have suffered only about 10,000 deaths from H1N1, which was nearly normal for a flu season. 

Cool Map: 

FluView

An interactive mapping program from the Centers for Disease Control

Figure 4‑14: US Map by State.  The severity of the flu by state in October, 2009. Note the contagion pattern from Southwest to Northeast. The color ramp violates standard cartographic principle – how?  Source: FluView, CDC

While the 2009 version of H1N1 was apparently less dangerous than its 1918 ancestor, the activity of health departments around the world was essential in averting disaster. Geographers working at the CDC in Atlanta, Georgia knew that a flu outbreak diffusing outward from Mexico were likely to appear first in California or Texas. Indeed, the first American cases appeared in San Diego and Imperial Counties, California, on the Mexican border. Other early cases were in Texas. Armed with data from previous flu outbreaks, computer models and GIS technologies, health geographers working at the CDC were able to accurately predict where, when the flu would flare up in various parts of the United States. Being able to predict the spatial patterns of disease helps health officials direct vaccines and other resources necessary to combat diseases to locations where populations are most at-risk. The outsized effort by the CDC and other public health agencies probably saved thousands of lives in 2009-10.

Malaria

Malaria is another infectious disease that kills at least a million people worldwide every year. It sickens millions more, and by doing so, creates huge burdens on the developmental potential of many regions in Africa and Asia. Malaria is a parasitic infestation of the blood. Malaria is transmitted when female mosquitoes inject parasites into the blood through their saliva as they take a blood meal. Mosquitoes carry around the parasite, so mosquitos are called the disease vector because they transport the infectious parasites between hosts. Flies, ticks, fleas, and lice are other common disease vectors. Malaria is a very complex disease because the parasite that harms people goes through a large number of life stages. The parasite can also lay dormant for long periods, living part of its life in a human host, and some of its life in the mosquito. The parasite can invade multiple parts of the body. Sometimes the parasite is hosted by an animal (monkeys, e.g.) Mosquitos, hosts and parasites all have different spatial behaviors and environmental needs, which contributes to the difficulty of controlling malaria. Solutions require spatial methods and geographic tools. 

Cool Map

Malaria Atlas Project A significant malaria research tool with data, maps and research links.

Malaria has been around for thousands of years, and likely contributed to the fall of the Roman Empire, but it was nearly eradicated in the 1950s. Or so it was believed. After World War II, effective drugs and massive insecticide spraying campaigns appeared to be working miracles against this age-old scourge. However, both the mosquitoes that carry malaria and the disease-causing pathogen evolved over the last few decades, rendering many drugs and pesticides largely useless in the fight against today’s version of malaria.

Malaria in the United States

English colonist who came to the region thought North America to be free of malaria. They didn’t yet understand the source of the disease. They mistakenly thought that it, like cholera, was a product of miasma. Because both European and African settlers brought with them reservoirs of malarial blood within their bodies across the Atlantic Ocean, the disease had only to find a suitable mosquito vector (i.e., Anopheles quadrimaculatus) to begin spreading. Within a generation, malaria had become a serious problem in the American colonies, especially where rice plantations created ideal breeding grounds for mosquitoes. Africans had some measure of resistance to malaria, contributing to their desirability as slaves in the plantation system that grew in during the 1800s. 

Figure 4‑15: US Map - Malaria killed and sickened many thousands in the United States prior to the 20th century. The US Census produced this map from 1880 data. Source: Wikimedia.

By the mid-1800s, malaria was out of control in the United States. A series of changes in American society nearly eradicated malaria within 100 years. The remarkable turnaround was created by several changes in the American economy. The demise of wet-rice culture in the Deep South was the first change. During the 1800s, thousands of mosquito-infested, wet rice paddies were drained all over the southern US as cotton and corn crops became more profitable. The profitability of these new crops also encouraged farmers to drain thousands of acres of swamps and wetlands for use farmland, thus destroying ideal mosquito habitats. By the mid-1800s railroads also began to replace river and canal transportation across the US, thereby redirecting many thousands of travelers away from the places where they were most likely to be bitten by mosquitos. At the same time, steam power began replacing waterpower, eliminating the need for thousands of mill ponds all over the country. People also became more prosperous, moved to cities, built houses with windows and screens and generally got healthier. Eventually the anti-malarial drug quinine became widely available in the United States, helping deplete the blood reservoir of the disease. Another important moment in the battle against malaria came in the early 1900s when scientists discovered that mosquitos transmitted malaria. Slowly, health officials in the US took steps toward mosquito eradication. Government workers drained swamps and manipulated water levels in lakes by constantly raising and lowering dams. They removed vegetation from lakes at the shoreline and provided houses within a mile or so of lakes or ponds window and door screens. 

After World War II thousands of 

Figure 4‑16: Atlanta, Georgia - The Center for Disease Control headquarters includes several emergency management command and control centers featuring GIS displays of data on outbreaks, resources and threats. Source: CDC, press release.

soldiers returned from Asia carrying the malaria pathogen in their blood. The government took steps to prevent malaria from spreading once again. The biggest effort was in the US South where the military already had practice preventing malaria on southern military bases. The secret weapon in this post-war campaign was a new, highly effective insecticide called DDT. The government launched a massive effort spraying DDT on millions of acres across the US. By 1949, the government declared the US free of malaria. The headquarters of the anti-malaria effort was chosen to house the CDC. 

Other countries copied America’s strategy for fighting malaria. Unfortunately, the widespread and indiscriminate application of DDT across the globe created a different crisis of interest to biogeographers. After about 10 years of widespread use of DDT in the US, it became apparent to wildlife biologists and birdwatchers that DDT and related insect poisons were harming animals other than just insects. Anything that ate insects regularly, like birds and fish were at risk. Alarmed by the unusual number of bird deaths in areas sprayed with DDT, environmentalist Rachel Carson wrote the book, Silent Spring, detailing the numerous ecological dangers posed by the overuse of chemical pesticides. In addition to pointing out how chemicals could be responsible for human cancers, and the near inevitability of pesticide resistance, the book also detailed how the toxic effects of pesticides grew slowly over time in the bodies of predators (like birds) through a process called bioaccumulation. Carson’s book also condemned chemical companies for misleading the public about pesticides, which of course drew scathing rebuttals from chemical companies and their allies in Congress. Nevertheless, the book became a best seller and is widely regarded today as a significant milestone in the American environmental movement. The US government banned DDT for agricultural use in the US in 1972, though it is still used in Mexico. Scientists credit the ban on DDT for helping Bald Eagles and other birds-of-prey return from the brink of extinction.

Cancer

One of the leading causes of death in the United States is cancer. Cancer is actually a group of diseases that are characterized by an out-of-control growth of specific body cells that erode life functions. Of the many varieties of the disease, skin cancer is the most common among Americans. It is clearly associated with overexposure to the ultraviolet light from the sun and from tanning beds. Lung cancer kills more Americans than any other type of cancer, and about 90% of lung cancer fatalities are associated with smoking tobacco. Smoking also causes a host of other deadly cancers. Other behavioral factors linked to cancer involve alcohol, weight control, and dietary practices. Cancer is not contagious, but many cancers display spatial patterns similar to infectious diseases. Geographers study cancer and their techniques offer insights into both behavioral and environmental causes of cancer, and as a result – insights into strategies to combat cancer. 

Figure 4‑17: US Map – The overall cancer rate is highest in Southern and Appalachian States where cultural behaviors elevate the risk of getting cancer. Source: CDC Cancer Atlas.

Cultural practices can both cause and help prevent cancers. There are clear regional differences in the rates at which people smoke, exercise, drink booze and eat healthy, making it easy to measure the correlation between lifestyle and cancer rates.

Cool Map 

Interactive Cancer Atlas from the Centers for Disease Control and Prevention 

Allows users to map a variety of cancers by state, ethnicity, and sex.

Some cancers are associated with ethnicity or national heritage. Partly this is because some cancers are inherited. Some forms of breast cancer, for example, are clearly inherited, prompting numerous women with a family history of breast cancer to undo preventative mastectomy surgery. Because genetics traits are often shared among groups of people living in a region, ethnic or national groups often have genetic anomalies predisposing them to specific types of cancer. For example, studies have found that the rate of stomach cancer is above average for Finns and Koreans and that liver cancer for Vietnamese men is higher than other groups. However, because ethnicity and national origins also predict many cultural and economic practices, it is difficult to statistically determine causality. Children who are adopted by people from a different ethnic group, or people who move beyond their ethnic homelands are often studied by medical geographers because such people help separate genetic causes from cultural ones.

Exposure to environmental pollutants is also linked to certain cancers, making geographic methods indispensable in the search for causes and preventative measures. Unlike the national or state maps of cancer showing general trends occurring within arbitrary boundaries, maps plotting cancer clusters at regional or neighborhood levels can be compelling. Consider, for example, mesothelioma, a rare type of lung cancer that showed signs of geographic clustering in the 1960s. By mapping mesothelioma clusters and various types of industry, researchers saw that locations where asbestos was mined and processed had much higher rates of the mesothelioma than regions where mining and processing asbestos was absent. This finding later allowed biomedical researchers to establish a causal relationship between various lung diseases and prolonged exposure to asbestos fibers. 

Cancer Cluster – Cancer Alley

The most famous cancer cluster in America, an area known as Cancer Alley, may not be a cluster at all. The gap between perception and reality here highlights the difficulty of identifying the environmental causes of cancer. Cancer Alley lies along the Mississippi River in Louisiana between Baton Rouge and New Orleans and shares territory with a significant number of petrochemical factories.

Figure 4‑18: Baton Rouge, LA - One of the largest oil refineries in the United States is located on banks of the Mississippi River where transportation advantages accrue. Related industries cluster nearby. What are the health effects of this cluster of petro-chemical industries on the health of Louisianans?  Source: Wikimedia. 

Clearly, this corridor does have one of the highest cancer rates in the United States, but because “Cancer Alley” does not have a statistically significant greater cancer rate versus other parts of Louisiana health geographers doubt that the region is actually a cancer cluster, and doubt that the factories are the cause. Unhealthy lifestyles, poverty and poor access to affordable, high-quality health care both within and beyond this industrial corridor make it difficult to separate the effect of the petrochemical industry on cancer rates from the effects of poverty and unhealthy lifestyles that characterize the entire region. 

Figure 4‑19: Niagara Falls, NY – The Love Canal neighborhood stands abandoned after toxic waste from a landfill was found in the local soil and water in the 1970s. Source: Wikimedia.

Some health problems, such as birth defects, asthma, and miscarriages, are easier to connect to exposure to toxic chemicals. The most well-known toxic pollution site in America is Love Canal, a neighborhood once home to some 900 families near Niagara Falls. It had to be abandoned in the mid-1970s after hundreds of residents were sickened by thousands of tons of toxic chemicals that had been buried nearby 20 years earlier by a chemical company. Poor construction practices and lax environmental regulation allowed the chemicals to begin seeping upwards through the soil into yards and basements. The health of hundreds of residents suffered, and many conditions were found to be far more prevalent there than elsewhere – indicating that the chemicals were the cause.

In recent years, the Flint Michigan Water Crisis has brought some renewed attention to the danger of lead poisoning, a health issue that had declined greatly in the US since the government banned lead additives in paint and gasoline in the 1970s. Flint’s problem grew out of their reliance on very old city water pipes, a search for a cheap source of drinking water and bad mistakes by Flint’s water management team. As a result, people living in older parts of town (poor, African-American) were exposed for many months to poisoned water.

Geography of Care

New York Times: Where A re the Hardest Places to Live in the US? 

A mapped Index of Health and Poverty

The geographical variation in death and disease can also be attributed to the geography of health care. Wealth explains most of the variation in access to quality health care globally and nationally. The health of poor people everywhere suffers from multiple burdens, many of which begin well before a person is born. Impoverished pregnant women may be malnourished and unable to afford the costs associated with proper pre-natal childcare, especially where the government does not provide health care. Poor women also tend to have babies born prematurely, and premature babies often suffer from low birth weight, which in turn invites a number of additional ill-health outcomes, most notably infant death. Poor children often continue to suffer from poor diets and an inability to access regular, high-quality health care throughout their lives which shortens their lives and reduces their capacity to be productive citizens. Many of the poorest areas in the United States have high percentages of physically or mentally disabled citizens. 

Figure 4‑20: US County Map: Orange indicates medically underserved regions, blue indicates medically underserved populations. Source: HRSA

Access to Medical Facilities

Poor people are not attractive customers for profit-driven health care providers. Poor people, especially prior to the Affordable Care Act (Obamacare), frequently had little means to obtain health insurance outside of the government-run Medicaid program. This fact limits health care options for millions of people in the United States. As a result, uninsured people tend to wait until they are very ill to see a doctor, often requiring a visit to a hospital’s emergency room where federal law requires provision of medical care, regardless of the patient’s ability to pay. The government partially reimburses hospitals for the costs of emergency room care, but much of the cost of caring for the indigent is paid for by charities and/or passed on to those with insurance – another example of an economic externality. Hospitals that serve too many indigent patients risk going out of business. As a result, doctors and hospitals avoid many of the poorest areas of the United States, favoring places where well-insured patients generate bigger profits.

Geographers sometimes call regions without medical facilities medical deserts. Most medical deserts are in poor rural areas, but a few inner-city areas in America’s largest cities also suffer from limited access to health care provision. The passage of the Affordable Care Act was intended to shrink or halt the expansion of medical deserts in most of the US, but expansion of medical deserts continues in states where politically conservative politicians opposed to Obamacare prevented their state from funding expansion of Medicaid programs for those who were both too poor to afford private insurance, but not poor enough to qualify for Medicaid. Multiple challenges to Obamacare, especially since the election of Donald Trump have reversed some of the gains made from 2010-2019. An estimated 10-15 million additional uninsured people, largely living in poor, and politically conservative regions, has expanded the threat of medical desertification.

Find Your Local Trauma Center

American Trauma Society:

Interactive Map of Trauma Centers in the US

Figure 4‑21: Maps. On the left is a US map showing one-hour transport distances to trauma centers. Los Angeles area trauma centers and a 45 minute ambulance ride are mapped (right). Source: Traumamaps.org

Geographers also analyze health care access at very local scales. Perhaps the most closely scrutinized region has been Los Angeles’ “South Central” neighborhood. As far back as the 1965 Watt’s Riots, black residents of Los Angeles have complained about poor access to doctors and hospitals. Government officials, in an attempt to shorten the distance residents of South Central LA had to travel for medical care, opened the King-Drew Medical Center in the early 1970s. However, after years of shoddy health care provision by the staff at King Drew, the facility was closed 2007, including its very busy trauma center. The closure angered local residents who would have to be transported to more distant emergency rooms for emergency treatment. Although it was controversial, most residents of South LA have reasonably good access to trauma care compared to residents of many areas of the US. In fact, all Los Angelenos have reasonably good access to trauma centers and hospitals.

Regional Variations in Health Care

In addition to regional variations in access to health care, there are significant variations in the style of health care both within and beyond the borders of the United States. How often people are diagnosed with specific illnesses varies greatly across time and space as do the strategies doctors use to treat conditions. Geography is exceptionally useful in highlighting and addressing these discrepancies. For example, in South Korea, there has been a startling rise in the incidence of thyroid cancer in the last 20 years. The rate is fifteen times higher than it was a generation ago, and it appears at first blush to be an epidemic. But, upon closer study, it turns out that changes in Korea’s health care system simply encouraged doctors to look for thyroid cancer more often than before. Because doctors were looking for the disease more aggressively, they found it far more often. As it turns out, quite few people have thyroid cancer and live with it for many years. Unfortunately, many Koreans chose to have the cancerous thyroid gland removed and as a result suffered more complications than they would have, had not just left it alone. 

Similar situations occur in the United States. The rate of diagnosis of specific diseases as well as the preferred treatment strategy depends a great deal on where you live. For example, If you live in the Southeastern United States, and you get a cold, there’s a much better chance you’ll be prescribed an antibiotic drug than if you live in California, Vermont or Colorado. If you and a cousin are both diagnosed with bad tonsils, where you live may dictate what your doctor suggests as an ideal treatment. You might have them surgically removed, and your cousin may simply get some pain-pills and a note to stay home from school. 

Cool Map

Dartmouth Atlas of Health Care

An interactive web mapping application addressing a variety of health care issues. 

Figure 4‑22: Map - Significant variation in the rate of tonsillectomies exist across parts of New England suggesting inconsistent treatment practices. Spatial Autocorrelation is evident. 

Source: Dartmouth Atlas of Health Care.

These variations in care are troubling because it suggests that geography may be influencing doctors more than accepted medical protocols. Geographers would investigate mapping treatments first, and then conducting a statistical test for spatial autocorrelation to determine if the spatial pattern of treatment is random or clustered. If the pattern of some disease does not mimic the pattern of treatment for that disease, then serious questions about the quality of health care should be raised. 

Health Care Systems

The ability to pay for health care is another important question that medical geographers try to solve. The health profile of people around the globe is worth examining because, despite American’s troubling sense of exceptionalism, which leads us to believe that what happens in other countries is of no value to us, we indeed can learn much from other countries. Except for the United States, citizens of other developed countries access universal health care, which is generally run by the government and funded largely through taxes, with varying levels of individual, or employer payment options. A few countries, like the United Kingdom and Canada have wholly government-run or single-payer programs. 

Enroll America

An Insurance Advocacy Organization with data and mapping tools for analyzing patterns of health insurance

The United States has a peculiar system of health care compared to most of the world. In the US, health care is largely run by companies from the private sector. By some measures, Mexico and Turkey are the only other countries in the world without universal health coverage. In the U.S. about 80% of the hospitals are not-for-profit businesses, but most physicians’ offices function as for-profit enterprises. About two-thirds of those who have insurance in the United States get it through their employer. The US government provides health insurance for about one-quarter of Americans. Medicare is the popular single-payer system (tax-supported), system for the elderly in the US. The poor and/or disabled who are under the age of 65 may qualify for Medicaid an insurance program jointly funded by states and the US government. Together, the government pays about half of all medical costs incurred in the US each year. 

The Affordable Health Care Act - Obamacare

Figure 4‑23: US County Map – “Obamacare” has significantly decreased the number of uninsured persons around the United States, including many locations, like Arkansas and Kentucky, where resistance to the program was intense. Source: New York Times / Enroll America

In 2010, the US Congress passed the Affordable Health Care Act (Obamacare) in an attempt to correct some of the problems with the US health care system. The law requires all citizens to have some kind of health care insurance. The ACA subsidizes the cost of insurance for the poorest of the poor and had a number of provisions designed to reduce health care costs for everyone. When it went into effect, about 16% of the US population was uninsured, but in 2016, only about 8.8 percent had no insurance. 

Obamacare offered some help by extending coverage to more people, especially in the 23 states that accepted an expansion of Medicaid funding. States with significant Republican majorities, largely in the South, on the Great Plains, and Mountain West, declined to expand Medicaid, keeping it difficult for some poor citizens to get health care coverage. 

Risk Pools

A very important feature of the Affordable Care Act was the creation of state-wide health care exchanges, which offered insurance to those who were not eligible for neither Medicare nor Medicaid and could not get employer-provided health insurance. The idea was to create large risk pools of insurance customers who all contribute to a common fund from which individuals in the pool can withdraw money to pay for medical expenses. These risk pools are of interest to geographers because risk pools are defined by state borders, health risks vary greatly not only by individuals but by state of residence.

The key to successful health care exchanges (risk pools) is having a very good ratio of healthy people to sick people. Because chronically ill people most of the pool funds, sustainable insurance pools require that a large majority of participants in the risk pool be very healthy. An abundance of chronically ill people in an insurance pool drives up the cost of insurance for healthy people in the pool, which in turns causes healthy people to drop their insurance or seek it elsewhere, creating a situation in which chronically ill people rapidly deplete the common fund in a process known as an insurance death spiral. Prior to 2010, insurance companies tried to avoid creating unstable risk pools by denying enrollment in a plan to those with a known chronic disease or injury, called a pre-existing condition.

Those without insurance tend to have poor health, live fewer years and occasionally contribute to the proliferation of contagious diseases. Uninsured people can be very expensive for everyone else as well. Under the law, uninsured people still have a right to some health care, but this right only applies in specific instances, usually in an emergency situation, when a medical condition has become expensive to treat. Therefore, uninsured people tend to rely on emergency room care, rather than preventative care. Often, those who wait until they are extremely ill to seek emergency care, find themselves bankrupted by the costs and/or unable to work. Either way, the costs are passed onto taxpayers and to people with health insurance

How to fix the expensive and unfair American health care system is an exceedingly complex issue. Health care has become the main political issue in the US in the last two decades, and it’s sometimes unclear who favors what solution and why. Libertarians (see politics chapter) argue that nobody should be forced to join an insurance pool and that health care costs should be paid by individuals, and health care costs should be determined by the actual cost of care incurred by individuals, not the risk behaviors of a group. If people choose not to pay, then they get should get no treatment. Other conservatives believe that the government must force everyone to pay for health insurance because virtually everyone eventually gets sick and needs medical care. To them, buying health insurance is matter of individual responsibility, that should not be shouldered by the government or taxpayers. Ironically, these views are held most fervently in many of the states with relatively high percentages of voters using government-sponsored Medicaid and Medicare, such as Alabama, Kentucky, and West Virginia.

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Progressive politicians favor more government involvement. They point to the lower costs and better health care outcomes for people living in countries with government-run health care systems. They believe every citizen in the country should be automatically placed in an insurance risk pool of some sort. Clearly, it can be done, but in order to keep taxes low, governments (or insurers) must work hard to keep people healthy to prevent them from costing fellow risk pool members too much in health care costs. In order for it to work, government or insurers must encourage healthy diets, exercise, and regular checkups as part of a healthcare strategy known as preventative healthcare. Progressives point out that the economic logic of our current privatized health care incentivizes unhealthy lifestyles because there are enormous profits to be made by treating, but not curing, chronically ill people. The opioid crisis may indeed be a partial outgrowth of providing long-term treatments for pain, without providing a cure for chronic pain. Meanwhile, there are few monetary rewards for risk pool participants who stay healthy, nor for those who work to prevent people from getting sick. 

Progressive economists also estimate that over the long run, the external costs of our privatized health care system are far greater than what American taxpayers would pay if we adopted a more socialized medical system. For example, they point to the cost of an automobile produced in the United States. A mid-sized sedan built by Ford or General Motors in the United States costs around $2000 more than similar cars built elsewhere, because of the extra costs American manufacturers pay when they provide expensive medical insurance for their workers and retirees. Manufacturers in countries where health care is provided by the government do not bear this cost directly, so the costs of medical care passed on to car buyers are smaller. Some American companies move jobs to places where health care is cheaper, and this results in yet another loss of tax money from both payroll and corporate taxes that would otherwise go to the US Treasury.