Evolution has provided humans with their senses, and we are bound by them. In the English language “inconsequential” is a synonym for “small”—the conflation of the minute with the insignificant is explicable by evolutionary selection. Things that are small are typically not immediate threats to life, so evolutionary selection has had our senses concentrate more on things that were larger and could immediately threaten existence. The invisible, by definition, would not be subject to physical (as distinct from cultural or genetic) evolution. Our senses delude us and provide a false feeling of security. These preconceptions hinder our understanding of history and lead us into a great deal of misunderstanding. The minute and/or invisible have had inordinate and still unappreciated effects on history and human society. In chapter 2, we presented an outline of history emphasizing the impact of pathogens on human society. The prevailing disease ecology was of paramount importance throughout human history until the medical and scientific discoveries of the late nineteenth century.
Here we explain the changing role of infectious diseases over time within an explanation (model) of long-run economic growth that contains cycles (feedback effects), one “virtuous,” the other “vicious.” Our explanation of long-run economic growth combines the effects of population growth, fundamental principles of microbiology, and public health. We discuss alternative explanations of long-run economic growth based on the insights of Adam Smith and Thomas Malthus. Our own explanation, emphasizing the impact of pathogens, combines the Smithian and Malthusian insights to elaborate an explanation of long-run economic growth that is consistent with history, science, and economic principles. In our explanation, we posit a virtuous economic growth cycle offset by a vicious biological cycle. These cycles were embedded in the process of long-run economic growth (rising incomes) prior to the twentieth century. In the pre-twentieth century world, increasing per capita output inevitably contributed to another process that led to the spread of diseases and lowered incomes. The exact temporal sequence was stochastic, but it was predictable in the long run. These pathogenic infections had significant effects on history, economic development, and the well-being of humanity.
We begin with a highly simplified model of economic growth in an exchange economy.1 As populations increase, markets expand and the expanded markets induce greater specialization, which in turn increases output and productivity. (Wages are positively related to the increased output that is attributable to an additional worker times the additional revenue that the increased output produces.) This is in essence Adam Smith’s observation that specialization is limited by the extent (size) of the market. Growing markets and incomes increase the demand for all sorts of services. We emphasize the demand for transport services (broadly construed to include resources devoted to facilitating exchange) because they (1) are easily explicable, (2) have feedback effects on the size of markets (which propels the cycle), and (3) are an important aspect in determining the size of the market and the concomitant specialization in economic activities.2
An increase in demand and the absolute amount of goods traded makes profitable a series of investments in the transportation sector. These investments include (but are not limited to) warehouses, wharves, ports, roads, lighthouses, specialized financial services, firms specialized in the provision of inputs to the expanding transport sector, canals, and the creation of institutions (laws and customs) that create, define, and enforce contract law. In order to make the argument more intuitive and less abstract, we simplify even further on the inland shipment of materials. There are many different ways to transport material given the resources available.3 For example, in the nineteenth century, material could be transported by human hands, in backpacks, by gravity chutes, by mule or horse, by wagon, railroads, canals, or other means. Which technique was used depended on which was cheaper, and that in turn depended on the absolute physical volume shipped. It does not make economic sense to build a railroad to deliver one pound of sand to a market 10 miles away; it is cheaper hiring someone to carry it. But if you wish to transport 100 million tons of sand a distance of 10 miles with the technology and costs prevailing in mid-nineteenth century England, then hiring people to carry it would be disastrously expensive compared to the costs of delivery using a specially constructed road or rail line. Typically the costs of transport are determined by two parts, fixed costs and operating costs; more specialized facilities have high fixed costs and lower operating costs. Only if the volume of freight is large will the average costs (operating costs plus fixed costs divided by total volume of freight) be lower than techniques that use no (or less costly) specialized facilities and have high operating costs.
There are two basic economic points here: (1) there is no free lunch. If you want low operating costs, you have to pay high fixed costs; alternatively, if you want low fixed costs, then operating (or variable) costs are high. And (2) specialization and increasing productivity are limited by the size of the market. As markets expand, the creation of a network of high fixed-cost modes of transport with low variable costs becomes economic. Given the volume of traffic, these high fixed-cost, low variable-cost modes allow substantial reductions in the overall average cost of transportation. The costs of inland transportation in the United States in the mid-nineteenth century were from 1/5 to less than 1/10 the ton-mile charges prevalent in the 1820s as canals were built. Canals were not constructed in the United States until late in the eighteenth century, and no canal of major importance was completed before the 1820s; yet canals were known and constructed since early antiquity. The reason that their construction was effectively delayed until the nineteenth century was that the size of the American market was not large enough to make them economically viable. With the growth of population, both the absolute size of the market and the absolute volume of freight grew; only then were canals financially viable in the United States. The construction of canals resulted in a substantial widening of the market, which induced more growth and had feedback effects on the transport sector.
This explanation of economic growth is derivative from Adam Smith; the major difference between our explanation of economic growth and Adam Smith's is that we explicitly incorporate feedback effects. Increases in population increase market size, and the increased market size affects how production is organized. Increased specialization leads to rising output (and wages) per worker, as production costs fall. Besides its intuitive appeal, we emphasize developments in transport because of transportation’s role in the transmittal of diseases.
Increased market size leads to more specialized modes of transport that have lower average costs given the increased volume of goods (and passengers) they carry. The reduction in the average costs of transport leads to increases in the size of markets that stimulate still more investments in specialized transport services, and further declines in costs. This is the virtuous cycle of economic growth. Extensive economic growth increases market size; increasing market size leads to more specialization and greater output per worker. Increasing incomes propel further increases in market size as people buy more goods and services (rather than make them at home or do without) with their increasing incomes.
Before the twentieth century, this virtuous cycle of “Smithian” economic growth was attenuated by a vicious biological (“Malthusian”) cycle. Increased market size provided a resource for the pathogens that prey on humanity. In the centuries before the twentieth, a significant increase in human density was always associated with substantial increases of biological resources for microparasites. With increased human densities came animals that provided transportation and food. Both humans and their animals excreted waste products that were not subject to sanitary disposal. Waste products contaminated water supplies, foods, housing, and soils, and exposed people to the microbes they harbored. This created ideal breeding grounds for opportunistic infestations by newly introduced microbial pathogens. Along with increased animal populations came plant foods that fed both humans and their beasts. In the absence of modern storage and packaging, plant foods attracted their own set of microbes and vermin that harbored and spread pathogens. The result was that the total biomass available to pathogens increased exponentially because of (1) the increases in income, human numbers, and density; (2) a disproportionate increase in domestic animals associated with the increasing population and increasing incomes; (3) the increased organic wastes that humans and their animals generated; (4) the increase in plant food stored next to humans and their animals; and (5) the vermin the increased biomass attracted.
We explicitly note the paradoxical role of increased incomes in the transmission of diseases. Increased income led to an increase in demand for both more food and “higher quality” foods. (“Higher quality” here refers to foods derived from animals such as meat, milk, and cheese.) The increases in the urban populations and incomes led to a more than proportional increase in the demand for animal products. This in turn led to a more than proportional increase in the urban biomass available to disease-causing microbes as the animals, plant foods, and the waste products associated with them increased. Increasing incomes had a positive effect on the biomass, such that the total increase in the biomass was disproportionally greater than the increase in the human population.
The increased biomass surrounding human communities allowed pathogens to become more abundant; increased human densities also facilitated the transmission of infectious diseases among humans. As infectious diseases became more rapidly transmitted and widespread, more people were sick more often. The decline in transport times and costs abetted the process; the consequences were an increase in diseases throughout the trade networks. The resultant increase in human morbidity and mortality associated with these pathogens had their impact throughout the entire world as globalization proceeded until the improvements in medicine, sanitation, and public health curtailed infectious diseases toward the end of the nineteenth century.
Our explanation of long-run economic growth emphasizes the connections between population growth and economic development, including developments in transportation. We now present a more formal (austere) model of our thinking and concentrate on explaining the relationships between a denser biomass and the transmission of infectious parasitic diseases in a model of long-run economic growth.
Adam Smith recognized that specialization enhances productivity, but that the size of the market constrains specialization. An absolutely large market engenders greater specialization, and consequently productivity and income. We take this as a starting point and examine it within the framework and interpretation presented in Stigler (1951). Our model is a variant of the Smith–Stigler model; the Stigler model concerns firm behavior, while ours is an economy-wide model where the cost functions are for economy-wide production functions. While the use of economy-wide cost functions rather than individual firm functions is not critical to understanding the Smithian model, it is critical in examining the Malthusian doctrine.
Consider a closed economy with no technological change; the stock of technology is fixed and known; yet not all technology is economically feasible.4 Techniques that require substantial fixed costs and incur relatively low variable costs are not feasible in markets below some minimum size. Figure 3.1 illustrates these features: The curves AA', BB', and CC' represent the economy-wide cost functions. These economy-wide aggregates are not specific to a firm. For each of the cost curves, total output is on the horizontal axis and total costs (measured in labor units) are on the vertical axis; capital inputs are fixed for each cost curve at a different level as shown by the height of their intersection with the vertical axis. For example, the curve BB' has total non–labor fixed costs of OB units of labor. Economies of scale (decreasing average or unit costs) exist on each cost curve because of the existence of the fixed costs OA, OB, and OC, respectively, for each of the functions; each cost curve has a continuously increasing slope.
Average cost per unit of output (measured in labor units) in figure 3.1 is measured by the slope of a straight line from the origin to any point on a specific cost curve. Average productivity per unit of input (measured in labor units) would be the inverse of this slope. (We show this later in figure 3.2.) Notice that although there are continuously increasing marginal costs (as measured by the slope of each specific function; each of the curves get progressively steeper as output increases); average costs initially fall and then increase.
The use of labor inputs as the unit in which to measure fixed costs and variable costs has a long tradition and it yields some distinct advantages (for the history of labor theories of value in economics, see Blaugh 1997). First, it allows us to equate costs and living standards (as measured in output per unit of labor) in a perfect inverse function. Second, “total costs” in labor units allow us to examine the Malthusian model on its own terms. Third, as an empirical matter, the rise, or fall, in living standards over time is the stuff of economic history and development.
There are a variety of techniques available to produce output. Figure 3.1 illustrates only three of the possible techniques. For the sake of exposition, the diagram can be thought of as depicting the cost functions for transportation (measured in ton-miles). Curve AA' represents the costs of hauling by pack train, curve BB' by wagon train, and curve CC' by railroad. Only if the market generates a critical mass of more than X1 output will pack trains (AA') be abandoned in favor of wagons (BB'). A volume of transportation greater than X2 makes railroads (CC') more economic than wagons. At the “critical masses” (outputs X1 and X2), the costs for competing techniques are the same, beyond those outputs it becomes economical to switch to the higher fixed-cost/lower variable-cost techniques. Beyond each critical mass, the higher fixed-cost technique yields a lower average cost per unit.5
The curve OZ is formed by the locus of all the minimum total costs for given outputs using different techniques. Accordingly, OZ represents the least total-cost method of production for given levels of output when techniques are allowed to vary. It can be considered the long-run total-cost curve formed by the minimum points for outputs using specific, efficient techniques. As it is drawn, OZ is a continuous function; implying that there is an optimum total cost function for each output. This assumption is not necessary for the argument. All that is necessary is that each discrete change in output has associated with it a total cost function with greater fixed costs and lower marginal costs. A continuous function, however, has the advantage of being described with familiar and accessible mathematics.
This model is representative of Adam Smith’s thesis: population growth leads to larger market size, which in turn leads to more specialized techniques (higher fixed costs and lower variable costs) and increased productivity. This results in the demand curve for resources shifting to the right leading to higher real wage rates as both the marginal and the average productivity of labor rise.
A straightforward Malthusian model may be illustrated with figure 3.2, which is figure 3.1 with all of the “short-run” cost curves eliminated except BB'. For illustrative purposes, we examine curve BB'. Since the slope of it is continuously increasing, diminishing returns (that is, increasing marginal costs) exist throughout the entire range of BB' (and all other specific cost curves). This is the “pure” Malthusian case. A less “pure” one would have a range of increasing returns and then decreasing returns to scale. The specification chosen here is less restrictive and, because the curves are economy-wide cost curves, has greater fidelity to the Malthusian doctrine. In figure 3.2 average costs are falling (or alternatively, living standards rising) up to output Xi on the cost function BB'. The output Xi has the lowest average cost (highest average productivity); average costs (the slope of the straight line OL) are at a minimum for technique BB' (OL is just tangent to BB') at output Xi, beyond Xi average costs rise. The range of outputs beyond Xi and on curve BB' represent the Malthusian range of increasing average costs as output expands. While the lowest average cost for technique BB' occurs at Xi, referring back to figure 3.1, the critical point—the output level where it becomes cheaper to produce using technique CC' rather than BB'—occurs at the smaller output, X2; Xi will be at an output in the range of X3, where the production technique CC' is just tangent to the long-run optimum curve OZ in figure 3.1.
The obvious difference between the Malthusian and Smithian models is that the Malthusian doctrine holds techniques constant, whereas the Smithian doctrine allows the use of more specialized techniques that are economical at higher volumes of output. Framed in this manner, the Smithian model is more dynamic in that it allows switching techniques. However, the Smithian model is innocent of biological dynamics. The Malthusian model has an intuition that increasing numbers can lead to impoverishment.
Whether technology is “fixed” or not under these conditions is debatable. North (1968) and Rosenberg (1982) address the meaning of technological change. In discussing productivity increases in North Atlantic shipping in the eighteenth century, North argues there was no technological change because the techniques that were used in the mid-eighteenth century had been available (but not used in the North Atlantic trade) a hundred years earlier. Rosenberg contends that it was the adoption of the technology that allowed productivity to increase; consequently it was technological change. North’s point is that the availability (or the lack thereof) of technology did not constrain shippers from adopting the technology earlier than they did. What did constrain shippers was that, for a variety of reasons (one being market size), the optimum mid-eighteenth century technology was noneconomic in 1680. Rosenberg’s argument, in its essence, is tautological: if an increase in productivity is related to the adoption of a technology, it is by definition technological change. North’s position is more commonsensical: technological changes apply to developments that were previously physically impossible. The advantage of North’s position is that it allows one to distinguish between changes due to relative factor prices (or market growth), and changes due to the relaxation of physical constraints.
Purists may object to the Smithian model because it does not hold the technology used constant, thus violating the strict interpretation of “holding all other factors constant” in the Malthusian theory. But if population density enters into production decisions, and we insist on a strict interpretation of “holding all other factors constant,” then Malthusian theory is internally inconsistent. An increase in population would lead to an increase in density, thus violating the proviso to hold other factors constant, unless the amount of resources change, which also violates the proviso to hold other factors constant. As a result, the crucial issue is empirical: Does population density enter into the choice of technologies?
At the risk of belaboring the obvious, there is abundant empirical evidence that population and market density both affect how production is organized. Subway systems (undergrounds), pipelines, jumbo jets, sidewalks, and railroads are just some examples of density and market-size dependent techniques. The theoretical (and empirical) literature in economics of standard “U-shaped” long-run average cost curves for competitive firms, and downward sloping long-run average cost curves for firms that are “natural” monopolies, rests on economies of scale. There is no dispute: Both market size and population density influence real-world technologies.
Our combined model of long-run economic growth embeds the Malthusian intuition within the framework of a closed Smithian economy. The crucial facet of our combined model is the relationship of population growth with an increase in human density per square mile. With a denser biomass of humanity, microorganisms that prey on humanity will become more abundant, and increasing human density allows the transmission of infectious diseases to occur more rapidly. The knowledge of the correlation of population densities with diseases is well known in the biological literature (Varley, Gradwell, and Hassell 1973; Wilson, Miles, and Parker 1984). Perhaps the best indication of its acceptance is that the relationship between disease, deaths, and population has been formulated into “Farr’s Law.” According to LeRiche and Milner (1971, p. 276), “This ‘law’ states that there is a linear relationship between population density and death rate, using the logarithms of the life-table death rates as the ordinate and the density expressed as persons per square mile as the abscissa.” Lee (1987, p. 451) disputes the exact specification of “Farr’s Law,” nevertheless he too observes a negative relationship between human density and the reproduction rate. Rather than an exact specification, “Farr’s Law” should be thought of as a Law of Density; as density increases a species’ morbidity and mortality increase. A straightforward statement on the impact of population on disease can be found in Fox, Hall, and Elveback (1970, p. 102): “Very simply, increasing the density of population favors the spread of infectious agents to man, whether from human or nonhuman sources and whether by direct or indirect means.”
Increased human densities also are highly correlated with increased densities of domestic animals. Combined, these increased densities will increase the diseases that infect humanity. Some major zoonotic diseases (originating in animal populations but transmitted to humans) that result from increased animal and human densities are anthrax, botulism, brucellosis, hemorrhagic fevers, plague, leptospirosis, rabies, salmonella, tetanus, trichinosis, and toxoplasmosis. Some major diseases (most having zoonotic origins) that are now considered non-zoonotic as they have been modified over the millennia so that they no longer depend on direct animal to human contact to spread are chicken pox, cholera, ergotism, hookworm, influenza, malaria, measles, mumps, onchocerciasis (river blindness), polio, rubella, and schistosomiasis.6
These listings of diseases are not exhaustive, nor can they ever be as knowledge is incomplete and pathogens and their hosts are constantly evolving. Evolving microorganisms ensure that humanity will be constantly exposed to “new” diseases.7 An examination of the table of contents of textbooks devoted to infectious diseases reveals literally scores of infections that are communicable to or between humans. The listed diseases are thought to be “major” in their impact on the human community. Zoonotic diseases are infections that are typically not chronic to humans. An infected human either recovers or does not from an exposure to a zoonose; the human is typically not the source for further human infections. “Typically” has to be inserted in these statements because under some conditions a zoonotic disease can be spread by humans to other humans; pneumonic plague is a good example of an initial zoonotic infection that can be spread to the lungs and then be passed human to human.
Increased density leads to increased diseases and infections. This results in increasing rates of morbidity and mortality. Increasing mortality lowers population, which lowers output via the reverse of the Smithian cycle outlined above. Offsetting the Smithian virtuous cycle will be a mortality-induced decrease in density that ultimately reduces morbidity and mortality. Morbidity adds complexity to the model, but it is important to the explanation. Increased density increases morbidity as well as mortality. If the microorganisms invading the human body do not lead to a relatively rapid demise, we would expect the debilitated people still to engage in productive activities albeit at a lower level of efficiency. Recall the effects of infectious diseases on the developing brain (and body) of infants and children (Eppig, Fincher, and Thornhill 2010); over time (intellectually and physically) stunted individuals will comprise the bulk of the labor force in the disease-rich Malthusian environment. Given that a unit of infected human labor is less productive than before the organism appeared (uninfected human labor), income from labor activities per human (uncorrected for quality) would decrease.
The long-run equilibrium for our combined model is not transparent. An increase in population may lead to an increase or decrease in the equilibrium wage rate and in income per capita depending on (1) the increase in productivity due to increased specialization and (2) the offsetting reduction in productivity due to increased morbidity. Although there is no unambiguous equilibrium, the main features of the model are notable: morbidity, mortality, and economic growth are all endogenous to the model. Before sanitation, clean water, and modern medical procedures were introduced, an increasing human biomass per unit of land inevitably led (after some lags) to increased human morbidity and mortality.
Abstracting from the historical transportation developments, figure 3.3 illustrates a schematic outline of our combined model. Starting with the middle box and moving upward, population growth can increase per capita incomes and wages via the “virtuous” Smithian cycle (population growth’s positive impact on market size and specialization, which impacts positively on incomes). Alternatively, starting with the middle box and moving downward, the impact of population growth on increasing population density leads to a “vicious” cycle of increased morbidity that may actually lower incomes below what had been attained before population growth began. The increase in morbidity reduces the productivity of humans, or alternatively, the amount of effort a person can produce. The increased density also increases mortality, which then reduces population. These latter consequences are identified as the vicious Malthusian cycle.
The schema in figure 3.3 is purposely simple. Omitted are other variables that affect the elements included in the model. For example, an increase in population density is related to increases in morbidity and mortality; ignored are a host of other factors that mitigate or accentuate its impact. Among the omitted factors are (1) temperature, (2) humidity, (3) consumption patterns, (4) societal behavior that affects the transmission of diseases, and (5) diet.8
Wrigley and Schofield (1981) in their history of the English population have similar models (also see Wrigley 1986). However, their models have neither economic growth nor morbidity or mortality as endogenous variables. They do recognize that diseases and high death rates are associated with urbanization, but they do not connect the cause of higher real incomes being the increased market size; that is, population density (Wrigley and Schofield 1981, pp. 415, 463). It appears that in their models economic growth and high wages appear exogenously in “a less healthy environment” (p. 415). Although they do have some intimations of the model presented here, in their explicit models, they treat economic growth as exogenous, and they are Malthusians in their treatment of population growth. To them, population growth lowers real incomes because the price of food is bid up. The link between population growth and lowered real incomes is broken in the Wrigley and Schofield (1981, pp. 474, 478) models for the early and late nineteenth century; prior to the nineteenth century, their models are Malthusian—increased population growth lowers living standards.9
Figure 3.4 is illustrative of our thinking on the linkages between population growth, developments in transportation, and the economics of diseases. As in our other schematic diagrams, the algebraic signs associated with the avenues of causation indicate the impact that the causal variable has on its target. Starting at the top and working through figure 3.4, note that an increase in population (or the workforce) increases market size and specialization. We focus on the effects of greater specialization on transport. The increase in specialized transport services has two effects: one is to increase the speed of transport; the other is to increase productivity (lower costs per unit). The increased productivity increases the volume of traded goods, which has two effects: (1) it has a feedback effect that increases the size of the market and specialization and (2) it increases the number and variety of diseases transported. The increased speed and regularity of transport services also affect diseases positively because shorter voyage times allow infectious pathogens to survive and to be transmitted more frequently than would have happened with slower transportation.
Transport speed is important in the transmission of diseases because many disease-causing pathogens cannot survive long outside a host body.10 For example, measles has an incubation period of 8 to 12 days and is contagious for 7 to 9 days (Cliff, Haggert, and Smallman-Raynor 1998, p. 89). Consequently, the probability that the measles virus could survive an ocean voyage of 54 days on an extremely crowded ship, such as the Mayflower, would be remote. The passengers and crew would be rapidly infected and either dead or cured (and not infectious) by the end of the voyage. (A person who has recovered from measles has lifetime immunity and is not infectious.) The same is true for other diseases whose incubation and infectious periods are relatively short, and whose victims do not become (relatively) asymptomatic carriers. Typhoid fever is an example of a disease that can infest someone who shows no visible sign of the disease yet harbor it and can spread it. (Typhoid Mary is a notorious example of this in the literature of diseases.) Regardless of these considerations, the reduction in the costs (including money, time, and rigors) of transportation increases the frequency of people and other infectious agents (ticks, lice, mosquitoes, among others) traveling long distances.
With respect to figure 3.4, increasing market size leads to specialized transport services that yield greater speeds and volumes of transport. These increase the transmission of diseases, which increase morbidity and mortality. But the final outcome of increasing specialization on morbidity and mortality is uncertain because an increase in specialization increases income, which reduces the susceptibility of people to diseases and their outcomes. Increasing incomes can reduce diseases in a number of ways: (1) the additional resources of a family or individual allowed the consumption of better food and discarding of leftovers obtained earlier but not consumed. In an era that lacked refrigeration, leftovers generated a high risk of food poisoning. (2) More money allowed the family to obtain bigger living quarters; the increase in the space per member of the living unit reduced the transmission of infectious diseases. (3) Additional income allowed the purchase of more clothing and cleaning, and those reduced the transmission of arthropod-borne diseases. And (4) more money allowed the purchase of other goods and services (quinine, clean water, waste removal, among others) that reduced the probability that members of the living unit will contract an infectious disease. However, before the late nineteenth century, increased incomes were not sufficient to reduce the increased morbidity and mortality associated with cities and urbanization. Before modern sanitation, purified water supplies, food preservation, refrigeration, and other such developments, an increase in income may have ameliorated some of the effects of increased density on diseases and their consequences, but in no way did it completely offset these consequences. Increased density, then, was conjoined with increased morbidity and mortality.
In a series of papers, Fogel (1986, 1991, 1992, 1995) argues that better nutrition was instrumental in reducing morbidity and mortality. His argument is not inconsistent with the one presented here, although we place a much greater weight on amelioration of diseases and, as a result, on sanitation and other public health measures. Taking explicit exception to Fogel’s nutrition hypothesis are Tsoulouhas (1992) and Johansson (1994). Tsoulouhas finds that technological change is endogenously related to population growth and thus better explains the reduction in morbidity and mortality, and Johansson emphasizes the absence of any link between nutrition (and/or income) and morbidity and mortality prior to the twentieth century.11
The scholarly literature on living standards in the pre–Civil War United States has two contradictory strands. One is that income (both total and per capita) in the United States increased from soon after the War of 1812 through 1860. The other strand is that America experienced a long-term decline in the biological standard of living, based on anthropometric evidence of a decrease in the heights of Americans starting with (circa) 1830s birth cohorts.12 Data supporting both propositions appear to be well founded, so there is an “Antebellum Puzzle”: Why did human heights decline as income rose? One explanation suggests that when welfare or well-being is assessed historically, traditional measures of income might be inadequate. The reason is that traditional monetary measures of the level of income may overestimate the true growth of income, or they may not accurately measure the distribution of income, especially, the distribution of food resources, over the entire population. The proponents of anthropometrics argue that in some cases anthropometric measures are superior measures of welfare or well-being.
An alternative explanation for the so-called Antebellum Puzzle of increasing incomes and falling human heights, and the one we espouse, is that the disease environment deteriorated even as incomes rose during the nineteenth century. The deteriorating disease environment affected the biological standard of living and, as a result, average heights fell. Before the nineteenth century, local and regional disease pools predominated. But with the turn of the century, these local and regional diseases, both from within the nation and from abroad, became more widespread throughout the United States causing a decline in the biological standard of living. The spread of diseases was a worldwide phenomenon of the nineteenth century, paradoxically reducing the health status of populations as incomes increased at unprecedented rates of sustained growth. The American experience was one reflection of this phenomenon.
The integration of local and regional disease pools took place for a number of reasons; we highlight six of them. (1) The rapid expansion of the cotton South and the system of plantation agriculture cultivated by an enslaved African and African-American labor force spread diseases. (2) The growth in population, increased population densities, and the increased biomass (both human and nonhuman) facilitated the transmission of disease-bearing pathogens. (3) The growth of great cities (apart from the general increase in populations) allowed diseases to exist where before they would not have long survived. Cities provided a habitat and a focal point for diseases that had previously been unknown or episodic in the United States. (4) The declines in the rigors, time, and money costs of transportation allowed the sick, infected, and asymptomatic to travel across vast distances, infecting people along their routes and at their final destinations. (5) Beginning in the early nineteenth century, declines in transport costs and times initiated the migrations of peoples across continents and oceans; these migrations (both domestic and foreign) exposed natives and migrants to new disease ecologies that adversely affected both. The migrants were exposed to diseases that were new to them, but native to the ecologies of their new homes. And the migrants brought their diseases with them, adversely affecting the natives. (The word “migrant” is not literally accurate; tourists, sailors, merchants, and other people who traveled long distances also spread diseases.) (6) The declines in transport costs and times also led to a vast increase in the absolute volume of trade; this also brought diseases to both the established and newly settled areas of the United States. Falling mean heights and rising real incomes are now explicable, and the Antebellum Puzzle evaporates.13
Ambiguities abound in all aspects of life. Specialization increases human productivity, output, and living standards and is limited by the size of the market. Increasing populations and incomes, reductions in transport costs and times, and changes in technology enable markets to increase enormously. Increasing market size carries with it increased specialization and its concomitant benefits that have the effect of enhancing the agents that caused the increased market size. But the virtuous cycle of increasing market size, population, and income (or progress) was cemented in a Faustian bargain with parasites and pathogens.
Before the era of modern sanitation, public health, and low-cost potable water, increases in human populations and economic activities were accompanied by increases in the pathogens that attack and parasitize humans. The integration of the global economy in the nineteenth and twentieth centuries also integrated diseases globally. The nineteenth century was a watershed; in that century, diseases spread and proliferated enormously. Cholera escaped from its confines in the Indian subcontinent so that by 1800 it was in Europe and it crossed the Atlantic soon thereafter. “Diarrheal diseases” (an appellation that is used because there are too many different pathogens that cause the symptom to have each one separately identified) spread and were killers throughout the world. Tuberculosis (“consumption”) took on an added virulence within the confines of densely populated great cities. Sexually transmitted diseases also proliferated in the anonymity of urban conglomerations. Other diseases wrecked havoc and caused devastation in populations that had little or no previous exposure to them.
All these diseases were extraordinary burdens on humanity. Countervailing these developments were advances in science, health, medicine, and sanitation. Before the nineteenth century, it was obvious to virtually all knowledgeable observers that great cities were pest holes devouring people. Before the nineteenth century, death and disease were constant, albeit unwelcome, companions in the major cities of ancient Rome, Byzantium, Venice, London, and Paris. The nineteenth century differed from these earlier times, building on the framework established in the eighteenth century—the Enlightenment, or the Age of Reason. In the nineteenth century, humanity witnessed a systematic and effective attack on the spread of pathogens that afflicted humanity. As one of the agents of the attack on disease, Louis Pasteur said, “Fortune favors a prepared mind.” The nineteenth century mind was prepared in a variety of ways to initiate advances against human disease. The Enlightenment taught people to ask questions rather than deferring to “God’s will”; the microscope, modern chemistry, statistics, and the scientific method of empiricism were all necessary preconditions for a sustained counter attack on infectious disease. We should not, however, forget that the population was large enough and rich enough to afford and allow people to specialize and study “esoteric” subjects such as the life cycle of parasitic diseases. Economics has played a part, and by no means a minor role, in the pageant of humanity’s labors against disease and premature death.