Disease Transmission Models for Public Health Decision Making: Analysis of Epidemic and Endemic Conditions Caused by Waterborne Pathogens. (Articles)
Eisenberg, Joseph N. S., Brookhart, M. Alan, Rice, Glenn, Brown, Mary, Colford, John M., Jr., Environmental Health Perspectives
Developing effective policy for environmental health issues requires integrating large collections of information that are diverse, highly variable, and uncertain. Despite these uncertainties in the science, decisions must be made. These decisions often have been based on risk assessment. We argue that two important features of risk assessment are to identify research needs and to provide information for decision making. One type of information that a model can provide is the sensitivity of making one decision over another on factors that drive public health risk. To achieve this goal, a risk assessment framework must be based on a description of the exposure and disease processes. Regarding exposure to waterborne pathogens, the appropriate framework is one that explicitly models the disease transmission pathways of pathogens. This approach provides a crucial link between science and policy. Two studies--a Giardia risk assessment case study and an analysis of the 1993 Milwaukee, Wisconsin, Cryptosporidium outbreak--illustrate the role that models can play in policy making. Key words: Cryptosporidium, epidemic, Giardia, infectious disease, mathematical models, waterborne pathogens. Environ Health Perspect 110:783-790 (2002). [Online 17 June 2002]
Infectious diseases are a major cause of morbidity and mortality worldwide. In a recent study by the World Health Organization, ranking the global burden of diseases, five of the top seven diseases in developing countries were caused by infectious pathogens (1). Although infectious diseases are not as prevalent in developed countries, the emergence of human immunodeficiency virus, hepatitis C, Lyme disease, Cryptosporidium, and others has resulted in a resurgence of public health concern with infectious disease. To obtain regional estimates of disease burden, data are often collected through surveillance activities. These patterns of disease discerned through surveillance are caused by complex interactions of social, biologic, and environmental processes. Although surveillance information can be used to estimate a crude measure of disease burden, seldom can it provide information on the specific underlying causes of disease. Models of disease transmission, on the other hand, can provide a framework from which to address these questions of causality. Because an understanding of the specific causes of disease is crucial in attempts to design effective intervention and control strategies, these models can be useful in decision making.
One fundamental property of infectious diseases, including diseases caused by waterborne pathogens, is that these complex interactions always result from an infectious individual or environmental source transmitting the pathogen to a susceptible individual (2). In this article we provide a perspective suggesting that a thorough understanding of the system of interdependent transmission pathways is crucial in formulating sound public health policy decisions. The theoretical framework proposed explicitly models the transmission pathways of waterborne infectious pathogens that cause disease. We demonstrate that this model structure offers a framework that can be applied when data are limited. With limited data, the model can be used to assess which data must be collected to improve understanding of the relevant processes, as well as to provide sensitivity information for decision making. Targeted interventions to reduce disease then may be more responsibly designed and their potential impacts more thoroughly analyzed using the model framework.
The epidemiology of diseases caused by waterborne pathogens suggests that illness arises in two broad settings: outbreaks and endemic transmission. A large number of observed cases occur from outbreaks and can be reasonably characterized by incidence data collected through outbreak investigations. …