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      A Framework for Modeling Emerging Diseases to Inform Management

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          Abstract

          The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.

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          Most cited references41

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          Emerging Infectious Diseases of Wildlife-- Threats to Biodiversity and Human Health

          P. Daszak (2000)
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            Factors in the emergence of infectious diseases.

            "Emerging" infectious diseases can be defined as infections that have newly appeared in a population or have existed but are rapidly increasing in incidence or geographic range. Among recent examples are HIV/AIDS, hantavirus pulmonary syndrome, Lyme disease, and hemolytic uremic syndrome (a foodborne infection caused by certain strains of Escherichia coli). Specific factors precipitating disease emergence can be identified in virtually all cases. These include ecological, environmental, or demographic factors that place people at increased contact with a previously unfamiliar microbe or its natural host or promote dissemination. These factors are increasing in prevalence; this increase, together with the ongoing evolution of viral and microbial variants and selection for drug resistance, suggests that infections will continue to emerge and probably increase and emphasizes the urgent need for effective surveillance and control. Dr. David Satcher's article and this overview inaugurate Perspectives, a regular section in this journal intended to present and develop unifying concepts and strategies for considering emerging infections and their underlying factors. The editors welcome, as contributions to the Perspectives section, overviews, syntheses, and case studies that shed light on how and why infections emerge, and how they may be anticipated and prevented.
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              Is Open Access

              Epidemic processes in complex networks

              , , (2015)
              In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.
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                Author and article information

                Journal
                Emerg Infect Dis
                Emerging Infect. Dis
                EID
                Emerging Infectious Diseases
                Centers for Disease Control and Prevention
                1080-6040
                1080-6059
                January 2017
                : 23
                : 1
                : 1-6
                Affiliations
                [1]U.S. Geological Survey, Madison, Wisconsin, USA (R.E. Russell, K.L.D. Richgels, D.P. Walsh);
                [2]University of Massachusetts, Amherst, Massachusetts, USA (R.A. Katz);
                [3]U.S. Geological Survey, Turner Falls, Massachusetts, USA (R.A. Katz, E.H.C. Grant);
                [4]University of Wisconsin, Madison (K.L.D. Richgels)
                Author notes
                Address for correspondence: Robin E. Russell, 6006 Schroeder Rd, National Wildlife Health Center, U.S. Geological Survey, Madison, WI 53711, USA; email: rerussell@ 123456usgs.gov
                Article
                16-1452
                10.3201/eid2301.161452
                5176225
                27983501
                5fbf20d6-ef35-4efb-96eb-c271f242ee97
                History
                Categories
                Perspective
                Perspective
                A Framework for Modeling Emerging Diseases to Inform Management

                Infectious disease & Microbiology
                zoonotic diseases,zoonoses,decision analysis,one health,emerging diseases,infectious diseases,mathematical modelling,model development,predictive modelling

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