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Improving Decision Support for Infectious Disease Prevention and Control
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Improving Decision Support for Infectious Disease Prevention and Control
"This report describes decision-support tools, including models and nonmodeling approaches, that are relevant to infectious disease prevention, detection, and response and aligns these tools with real-world policy questions that the tools can help address. The intended audience includes technical experts - for example, modelers and subject-matter experts - and the policymakers that those experts can support. On one hand, this overview should help modelers and other technical experts understand the questions that policymakers will raise and the decisions they must make. On the other hand, many policymakers can benefit from a basic understanding of the capabilities and limitations of the different tools that may inform their decisions. This report describes the characteristics, requirements, uses, applicability, and limitations of three classes of theory-based models (population, microsimulation, agent-based simulation) and two classes of statistical models (regression-based and machine-learning), as well as several complementary nonmodeling decision-support approaches. The report then aligns all of these tools and approaches with a set of real-world policy questions. Finally, based on a review of published literature, an assessment of the different models and nonmodeling approaches, and recent experiences (such as the 2009 influenza pandemic), the authors recommend nine best practices for using modeling and decision-support tools to inform policymaking"--
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"This report describes decision-support tools, including models and nonmodeling approaches, that are relevant to infectious disease prevention, detection, and response and aligns these tools with real-world policy questions that the tools can help address. The intended audience includes technical experts - for example, modelers and subject-matter experts - and the policymakers that those experts can support. On one hand, this overview should help modelers and other technical experts understand the questions that policymakers will raise and the decisions they must make. On the other hand, many policymakers can benefit from a basic understanding of the capabilities and limitations of the different tools that may inform their decisions. This report describes the characteristics, requirements, uses, applicability, and limitations of three classes of theory-based models (population, microsimulation, agent-based simulation) and two classes of statistical models (regression-based and machine-learning), as well as several complementary nonmodeling decision-support approaches. The report then aligns all of these tools and approaches with a set of real-world policy questions. Finally, based on a review of published literature, an assessment of the different models and nonmodeling approaches, and recent experiences (such as the 2009 influenza pandemic), the authors recommend nine best practices for using modeling and decision-support tools to inform policymaking"--
Produktdetaljer
Sprog: Engelsk
Sider: 50
ISBN-13: 9780833095503
Indbinding: Paperback
Udgave:
ISBN-10: 0833095501
Udg. Dato: 19 aug 2016
Længde: 3mm
Bredde: 306mm
Højde: 306mm
Oplagsdato: 19 aug 2016
Forfatter(e) Osonde A. Osoba, Raffaele Vardavas, David Manheim, Melinda Moore, Margaret Chamberlin


Kategori Smitsomme sygdomme. Infektioner


Sprog Engelsk


Indbinding Paperback


Sider 50


Udgave


Længde 3mm


Bredde 306mm


Højde 306mm


Udg. Dato 19 aug 2016


Oplagsdato 19 aug 2016

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