Resources Repository
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EditorialPublication 2020Waiting for Certainty on COVID-19 Antibody Tests — At What Cost?
This perspective anticipates the availability of serologic antibody testing and considers its potential usefulness in mitigation …
This perspective anticipates the availability of serologic antibody testing and considers its potential usefulness in mitigation policy to reduce COVID-19 transmission. For example: Could we screen for serologic antibodies as a proxy for possible immunity and identify people who could return to the workplace with less severe mitigation measures? The authors acknowledge the uncertainties raised by many policy actors, including the WHO, such as, "Do antibodies confer immunity and, if so, for how long? How accurate is…
Probability/Bayes | Test Performance | Technology Assessment | Infectious Diseases | Health Systems | Policy/Regulation | Government/Law | Health/Medicine | Global | North America -
GuidelinesPublication 2012Modeling Good Research Practices - Overview: A Report of the ISPOR-SMDM Modeling Task Force-1
This paper provides an overview of the work of the joint Task Force between the …
This paper provides an overview of the work of the joint Task Force between the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM), provides the overarching recommendations, and discusses future work that is needed. The audience for these papers includes anyone who build models, stakeholders who utilize their results, and those concerned with the use of models to support decision making. This article is part 1 of…
Value of Information | Costing Methods | Health Outcomes | Mathematical Models | State-Transition | Dynamic Transmission | Microsimulation | Calibration/Validation | Dynamic Simulation | Decision Analysis | Infectious Diseases | Health/Medicine -
GuidelinesPublication 2012Model Parameter Estimation and Uncertainty Analysis: A Report of the ISPOR-SMDM Modeling Task Force-6
This paper discusses methods for the reporting of uncertainty, both in terms of deterministic sensitivity …
This paper discusses methods for the reporting of uncertainty, both in terms of deterministic sensitivity analysis techniques and probabilistic methods. Stochastic (first-order) uncertainty is distinguished from both parameter (second-order) uncertainty and from heterogeneity, with structural uncertainty relating to the model itself forming another level of uncertainty. The article describes the process of estimating model inputs, whether these are point estimates or distributions. It also explores the link between parameter uncertainty, decision uncertainty, and value-of-information analysis.…
Value of Information | Mathematical Models | Calibration/Validation | Health/Medicine