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Case-control studies are important in infectious disease epidemiology for rapidly identifying and controlling risks, but challenges, including the need for speed, can place practical restrictions on control selection and recruitment. The biased comparisons that result can hamper or, worse, mislead investigators. Following a 2009 outbreak of Shiga-like toxin-producing Escherichia coli O157 infection associated with a petting farm in southeast England, it was hypothesized that case behavior alone could be used to identify risks. Case-patients' exposures were randomized on a case-by-case basis, and the resulting permuted data were compared with the actual events preceding illness by conditional logistic regression analysis. There was good agreement between the risks identified by using our new method and the risks elicited in the original outbreak case-control studies. This was also the case in analysis of 2 further historical outbreaks. These initial findings suggest that the technique, which we have called the "case-chaos" technique, appeared to be useful in this setting. Analysis of simulated data supports this view. Circumventing the need for traditional control data has the potential to reduce outbreak investigation lead times, leading to earlier interventions and reduced morbidity and mortality. However, further validation is necessary, coupled with an awareness of limitations of the method.

The “Case-Chaos Study” as an Adjunct or Alternative to Conventional Case-Control Study Methodology