Patient Dependency characterizes the epidemiology of disease transmission within multiple small wards with rapid patient turnover. Other variables affecting the epidemiology of resistance are the use of antimicrobial agents, introduction of colonized patients, and efficacy of infection-control measures. A Markov chain model originally made for vector-borne diseases was used to elucidate the relative importance of different routes within intensive care units.

State-of-the-art modeling approaches were used in Britain during the outbreak of 2001 to address such questions as: Were planned control policies sufficient to bring the epidemic under control? What was the optimal intensity of preemptive culling? Would a logistically feasible vaccination program be a more effective control option? This “real-time” use of models, although of help in devising an effective control strategy, also proved controversial.

Although models of infectious diseases have influenced public health policy in the United States, that process and its results could be improved by regular, direct contact and communication between modelers, policy advisors, and other infectious-disease experts. At the U.S. Department of Health and Human Services, the Secretary’s Council on Public Health Preparedness is sponsoring initiatives using various modeling approaches to assess biodefense strategies.

Common themes in this session were: 1) involving substantive experts, thereby ensuring that conceptual frameworks underlying the mathematics are faithful to current understanding of complex natural phenomena, 2) including all possible interventions, which could then be evaluated alone or in various combinations, and 3) identifying inadequacies in available information, for augmentation through further research.