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A Framework for Modeling Emerging Diseases to Inform Management.

Robin E Russell, Rachel A Katz, Katherine L D Richgels

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    Developing predictive models for emerging zoonotic diseases aids rapid decision-making. These models assess management strategies, quantify uncertainty, and guide research for effective control of novel pathogens.

    Keywords:
    decision analysisemerging diseasesinfectious diseasesmathematical modellingmodel developmentone healthpredictive modellingzoonoseszoonotic diseases

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    Area of Science:

    • Epidemiology
    • Mathematical Modeling
    • Public Health

    Background:

    • Zoonotic diseases pose significant global health threats, necessitating rapid response.
    • Delays in implementing control measures are often caused by uncertainty in disease dynamics and management outcomes.
    • Early-stage modeling is crucial for informed decision-making during disease emergence.

    Purpose of the Study:

    • To demonstrate the development of models for early-stage zoonotic disease systems.
    • To provide a framework for evaluating the success of different management actions.
    • To quantify uncertainty in optimal decision-making for emerging pathogens.

    Main Methods:

    • Utilizing available data to construct mathematical models of disease spread.
    • Incorporating uncertainty quantification into model predictions.
    • Simulating various management interventions to assess their potential impact.

    Main Results:

    • Models can predict pathogen effects and guide the selection of control tactics.
    • The framework quantifies the likelihood of success for different management strategies.
    • Identified critical research areas to reduce decision-making uncertainty.

    Conclusions:

    • Model development is essential for optimal decision-making in zoonotic disease outbreaks.
    • Predictive modeling enhances the evaluation and implementation of control strategies.
    • This approach supports evidence-based public health responses to emerging infectious diseases.