Rethinking John Snow's South London study: A Bayesian evaluation and recalculation

Abstract

Famously, John Snow attempted to convince a critical professional audience that public water supplied to South London residents by private companies was a principal vector for the transmission of cholera. The result has been called the sine qua non of the ''epidemiological imagination,'' a landmark study still taught today. In fact, Snow twice attempted to prove public water supplies spread cholera to the South London population. His first, published in 1855, suffered from an incomplete data set that limited its descriptive and predictive import. In 1856, armed with new data, Snow published a more definitive study. This paper describes a previously unacknowledged methodological and conceptual problem in Snow's 1856 argument. We review the context of the South London study, identify the problem and then correct it with an empirical Bayes estimation (EBE) approach. The result hopefully revitalizes Snow's research as a teaching case through the application of a contemporary statistical approach. r

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“…The influence of BA can be seen in mathematics, statistics, computer science, bioinformatics, economics, physics, ecosystem, parasitology, and epidemiology as well as in human and veterinary medicine (Ashby and Smith, 2000;Basáñez et al, 2004;Dowd and Meyer, 2003;Fienberg, 2006;Gardner, 2002). A classic example of applying BA in order to make inductive reasoning from an effect to a cause is during 1855 to 1865 in London, England, where John Snow had used BA as his inductive reasoning to scientifically convince audiences that a source of cholera transmission was from a private water supplier company (Koch and Denike, 2006).…”

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“…But Simon was right. Absent a kind of Bayesian analysis, and the statistics available were insufficient to provide conclusive proof; 21 and without the identification of and a means of testing for what we now know is the bacterial agent, the quality of the water could not be adequately ascertained.…”