Evidencias Medicas : Knowing its place: mapping as medical investigationMedicina General y Familiar

The Lancet (Photo credit: Wikipedia)

The Lancet, Volume 379, Issue 9819, Pages 887 - 888, 10 March 2012

doi:10.1016/S0140-6736(12)60383-3

Not for the first time—and not for the last—a new disease appeared to ignore the theories of the day. In the 18th century, everyone knew that yellow fever was a climatic illness: “Distempers of very hot southerly countries, and natural to those climes”, wrote one authority in 1755, were “unnatural to other countries situated in a northern latitude”. And yet, during the 18th century yellow fever travelled up the American coast to attack with increasing frequency cities like Boston, New York, and Philadelphia. Figuring out yellow fever was a matter not only of medical urgency but also of economic survival. In one outbreak, in 1793, Philadelphia lost 10% of its population. “Why should cities be erected”, asked Noah Webster in 1796, “if they are only to be the tombs of men?” Some believed this new fever was a plague-like contagion that somehow travelled in the holds of cargo ships. Others insisted it was generated locally in the foul, fetid airs of unsanitary cities built for trade but not for cleanliness. If it was contagious then only quarantine could tame it. If it was, however, a miasmatic illness then, as sanitarian Benjamin Rush wrote in 1797, the medical response was obvious: “Offal matters, especially those which are of a vegetable nature, should be removed from the neighborhood.”

To test the theory of local miasmatic generation, New York physician Valentine Seaman etched on a copperplate map the street location of patient deaths at the epicentre of an outbreak. On a second plate he located the waste sites of “putrid effluvia” that were suspected sources. Published in the inaugural issue of The Medical Repository in 1798, the result revolutionised disease studies. Just as Andre Vesalius’ De Humani Corporis Fabrica challenged 16th-century physicians to see in dissection the real connections between the skeleton and its musculature, Seaman’s mapping invited his contemporaries to see the relation between the environment and a disease generated in it. The miasmatic theory became visible in the apparent correlation of disease incidence and proximate waste sites of odiferous, “furry miasmata”.

This is the unique thing about mapping: it takes a collection of individual cases and makes of them a uniform event class. Each case is related to all others—inviting measures of density and proximity—and to other elements of the mapped environment. In this way medical maps visualise Hippocrates’ great insight in On Airs Waters, and Places that disease events are related, at one or another level, to the environment in which patients live. Of course, the resulting map is only as good as the theory it tests. In applying a miasmatic theory of local disease generation to yellow fever, Seaman assumed it was spawned in the odiferous urban air. In identifying waste sites to be mapped he therefore identified the origin but not the source of the outbreak. He observed dense populations of mosquitoes buzzing at waste sites—“never before known, by the oldest inhabitants, to have been so numerous as at this season”—but, lacking a theory of insect-born illness, Seaman missed the true vector of transmission.

Mapping is also only as good as the technologies of its presentation. Seaman wrote that he regretted the copperplate technology would not permit more than a few of the many reported cases to be imaged. Nor was it possible to overlay his two maps to make clear comparisons. Quickly, however, these problems were overcome as the old copperplate technology gave way to cheaper, faster more precise printing methods that allowed for the inclusion of more data, and greater ease of publication.

The mapping techniques developed for yellow fever were later used in myriad attempts to understand the 19th century’s great recurring pandemic, cholera. By mid-century it would become the most studied and the most mapped epidemic in history. In England, the first pandemic killed more than 50 000 citizens between 1831 and 1834, spawning a generation of research papers. The study of this disease necessitated better data and a bureaucracy to administer it. In answer, Parliament created the General Register Office in 1836. Beginning in 1837, the map of the British nation was redrawn into a series of registration districts and subdistricts—each supervised by a Medical Officer—to permit ever more precise collection of mortality and morbidity reports. Under the General Register Office, the first modern census of 1841 created a population database that would provide the population denominator in the future study of disease at every scale. For the first time, density analysis and mortality ratios could be argued across the mapped surface on which individual cases became invisible—the specific subsumed by the general. Still, specificity was important. In 1831 The Lancet published a “Map of the Progress of Cholera” occurring “through 700 irruptions” in 2000 towns to argue cholera’s independence from local environmental conditions; it was a “poison which progresses independently” and thus could not be stopped by quarantine or sanitary measures. From New York City to St Petersburg, others mapped cholera as a local miasmatic illness, a contagion, or both. In all these maps, the graphic argument was increasingly combined with numerical and statistical analytics that were either produced in the map or the commentary accompanying it.

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Detail from Valentine Seaman’s map of cases of yellow fever in New York, published in The Medical Repository (1798)

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Detail from The Lancet‘s map of the progress of the cholera in Asia, Europe, Africa published in 1831

Famously, John Snow argued that cholera might be spread by contaminated water. He sought to prove his thesis in two studies, one of a ferocious outbreak in St James, Westminster, in 1854, and the other across South London. In the first he created a non-statistical dot map centred on a single water source: the Broad Street pump. In the second he attempted to assign cases of cholera in south London to water supply company jurisdictions in an attempt to show a correspondence between water quality and disease intensity. Most of Snow’s contemporaries agreed water seemed to be implicated, but that did not mean foul miasmatic odours were irrelevant. Since the Broad Street map, like Seaman’s map, was devoid of statistics or statistical arguments, it left room for other interpretations. Worse, his more ambitious south London study lacked—as Snow would later admit—a solid statistical base. Even with one, as John Simon of the Board of Health concluded in 1856, the maths of the day was incapable of a definitive analysis of the problem. Robert Koch finally settled the question of cholera’s nature when, applying the methods of his new bacteriology, he identified the waterborne Vibrio cholerae in 1883.

If bacteria were the cause of disease, mapping remained the means by which its local source was most easily identified. In the late 19th and 20th centuries, mapping became the tool public health experts used to identify the probable source of a range of outbreaks including cholera, typhoid, typhus, and yellow fever. The map also served to identify new, non-bacterial epidemics. In the 1870s, Alfred Haviland mapped cancer rates in Britain to argue a national epidemic. Within 20 years, maps of cancer mortality from across the British Empire were being published in national health surveys and medical journals. Cancer replaced cholera as the disease to study at every scale, from that of the neighbourhood to the nation. New statistical methods were developed—including confidence ratios, which allowed ever more precise renderings of its prevalence. Once again, these maps served only as well as the theories they embodied. US public health physician W H Frost, for example, attempted to map influenza and poliomyelitis epidemics in the early 20th century. These maps did not serve because, as we now know, viral disease has a different profile from diseases that are bacterially based. It was not until the computer revolution of the 1960s that complex statistical models capable of describing—and thus mapping—viral progression were possible. Finally, predictive models to map viral progression could be constructed. In the 1980s, for example, geographer Peter Gould married gravity and distance decay models with data on HIV/AIDS incidence in the USA to create the first powerfully predictive model of the disease. The resulting maps were disseminated as a video. Still, the old dot map of incidence remained important; it was through mapping the individual geographies of his patients that Abraham Verghese came to see the dynamic of HIV as it affected the rural Tennessee population he served.

By the first decade of the 21st century, maps of a range of new conditions—from H1N1 influenza to West Nile virus—were presented as statistical surfaces in which disease variances were embedded in regional, national, and international geographies. Often presented on the internet, these were typically maps of maps, aggregates of local case studies collected by regional authorities that formed the basis of national investigations. Irrespective of the nature of the disease mapped, or the scale of its presentation, the old Hippocratic insight remained: where cases aggregate its origin is likely to be found in the human and geographical environment. To understand disease, therefore, we map its community of incidence and its environment.