Waterborne Cryptosporidiosis Transmission Model

1. Waterborne Cryptosporidiosis Transmission Model Elizabeth Casman, Mitch Small, Baruch Fischhoff, Claire Palmgren and Felicia Wu Carnegie Mellon University, Department of Engineering and Public Policy Center for the Integrated Study of the Human Dimensions of Global Change

2. CIS oƒ HDGC Carnegie Mellon A model of a waterborne cryptosporidiosis outbreak in the United States was developed integrating scientific, engineering, institutional, and behavioral factors relevant to the risk of contracting cryptosporidiosis from drinking water. The application presented is an evaluation of options for the management of this risk.

3. CIS oƒ HDGC Carnegie Mellon Evaluating Three Research Options for Effects on Cumulative Epidemic Morbidity: 1. Improving consumer education and hence consumer compliance to Boil Water Advisories. 2. Improving epidemiological surveillance 3. Improving rapidity and specificity of water quality testing methodologies

4. Awareness Variables

5. Institutional awareness develops over time Week 1: All awareness = 0; incubation period of disease Week 2: Utility awareness increases to “suspicion of problem” based on results of routine monitoring. Utility requests confirmatory tests. Medical Awareness (Physician Level) increases from 0 to “suspicion of problem” because of increased cases of diarrhoeal illness. Stool samples are submitted to laboratories. Week 3: Health Department Awareness increases from 0 to “suspicion of problem” as reports from laboratories, physicians, and hospitals come in. Medical Awareness increases from “suspicion” to “confirmation of problem” as lab results come in. Utility Awareness remains at “ suspicion” level because managers are waiting for results of the confirmatory test. Week 4: All tests have come in positive and all parties are aware of a Cryptosporidium problem, including the consumers, who were alerted by media coverage.

6. Week CIS oƒ HDGC Carnegie Mellon Cumulative Average Epidemic Morbidity Number of cases peak by Week 3 mean

7. CIS oƒ HDGC Carnegie Mellon

8. Scenario 1 represents the base case, where roughly 50% of consumers will comply correctly with a Boil Water Advisory. Cumulative morbidity peaks at 3 weeks. Varying the fraction of people complying with the Boil Water Advisory from 0% to 100% (Scenarios 2 and 3) does not change the incidence of disease because the Advisory is not issued until Week 4, too late to make a difference. Scenarios 4 through 12 differ from base case assumptions in that it takes a week to correct treatment deficiencies and flush the delivery system. Under this assumption, consumer compliance can have a greater effect on the course of an epidemic, especially if the “turnaround time”, the time between the initial contamination event and when the consumer is told to boil his drinking water, can be shortened by as little as one week. Scenarios 13 through 19 test the effect of reducing the turnaround time for a situation where the utility can correct deficiencies immediately upon becoming aware of them (our base case assumption). If the utility could confirm the presence of Cryptosporidium oocysts in finished water in 2 weeks instead of 4, the epidemic could be averted.

9. CIS oƒ HDGC Carnegie Mellon Conclusions Improving consumer education will have a smaller effect on the outcomes of waterborne cryptosporidiosis epidemics than developing quick, accurate water quality testing methods for Cryptosporidium. Improving epidemiological surveillance will help in retrospectively understanding the etiology of an epidemic, but can’t be used to prevent an epidemic. (It can’t prevent something it has already detected.) Time is of the essence in response to intermittent water treatment failures. Delays of 3 weeks or more between contamination event and response, now the norm, permit the full development of an epidemic.