Modelling the impact of prior immunity, case misclassification and bias oncase-control studies in the investigation of outbreaks of cryptosporidiosis

Cryptosporidiosis is the most common cause of outbreaks of disease linked t o mains water supply in the United Kingdom and the second commonest in the United States. Recent evidence has suggested that prior population immunity may have an impact on the epidemiology of waterborne outbreaks and in part icular prior immunity may reduce the power of case-control studies for demo nstrating association between disease and water consumption behaviour. Howe ver, the degree of impact of prior immunity on the power of epidemiological studies is not yet clear. This paper reports the results of some simple ma thematical models of outbreaks of waterborne disease in populations with va rying levels of immunity due to prior water and non-water exposure. The bas ic outbreak model was run on a spreadsheet. To determine the impact of prio r immunity on case-control studies, further analysis was done using a Monte Carlo method to simulate sampling from cases and controls. It was found th at moderate degrees of prior immunity due to water associated disease could markedly reduce the relative risk of water consumption on illness in water borne outbreaks. In turn this would reduce the power of case-control studie s. In addition, this model was used to demonstrate the impact of case miscl assification and recall bias on case-control studies. Again it was found th at within the model, the results of case-control studies could be significa ntly affected by both these sources of error. Anyone conducting epidemiolog ical investigations of potentially waterborne outbreaks of disease should b e aware of the epidemiological problems. Mistakes from case-control studies will be minimized if the outbreak team pays considerable attention to the descriptive phase of the investigation and if case-control studies are cond ucted as soon as possible after an outbreak is detected.