Resources Repository
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ArticlePublication 2020Expanding Oral Disease Treatment is Cost Effective
This study developed a stochastic microsimulation model of oral health conditions, type-2 diabetes (T2D), T2D-related …
This study developed a stochastic microsimulation model of oral health conditions, type-2 diabetes (T2D), T2D-related microvascular diseases, and CVD, to project the cost-effectiveness of expanding periodontal treatment coverage among patients with T2D and periodontitis. Previous randomized trials found that treating periodontitis improved glycemic control in patients with type 2 diabetes (T2D), thus lowering the risks of developing T2D-related microvascular diseases and cardiovascular disease (CVD). The micro-simulation model parameters were obtained from the nationally representative National…
Calibration/Validation | Mathematical Models | Microsimulation | Cost-Effectiveness Analysis | Chronic Disease/Risk | Health/Medicine | North America | Graduate -
Resource PackPublication, Teaching Resource 2018Resource Pack: Model Calibration and Validation
This resource pack, curated by the Center for Health Decision Science, provides broad exposure to …
This resource pack, curated by the Center for Health Decision Science, provides broad exposure to empirical calibration and validation methods for mathematical models used in health decision analysis. Included are a selection of overviews, guidelines, tutorials, and applications. Given the complexity of diseases and variation in data quality, there are invariably a number of parameters that are unobserved or cannot be estimated directly but can be inferred through the process of model calibration. Model calibration…
Calibration/Validation | Mathematical Models | State-Transition | Dynamic Transmission | Microsimulation | Dynamic Simulation | Health/Medicine -
Tutorial/PrimerPublication, Teaching Resource 2017Bayesian Methods for Calibrating Health Policy Models: A Tutorial
This article provides a tutorial on Bayesian approaches for model calibration. It describes the theoretical …
This article provides a tutorial on Bayesian approaches for model calibration. It describes the theoretical basis for Bayesian calibration approaches as well as pragmatic considerations that arise in the tasks of creating calibration targets, estimating the posterior distribution, and obtaining results to inform the policy decision. These considerations, as well as the specific steps for implementing the calibration, are described in the context of an extended worked example about the policy choice to provide (or…
Calibration/Validation | Infectious Diseases | Health/Medicine -
ArticlePublication 2017Using Data-Driven Agent-Based Models to Forecast Emerging Infectious Diseases
This paper describes an agent-based model framework developed to forecast the 2014-15 Ebola epidemic, which …
This paper describes an agent-based model framework developed to forecast the 2014-15 Ebola epidemic, which was subsequently used in the Ebola forecasting challenge. Producing timely and reliable forecasts for an epidemic of an emerging infectious disease is a challenge. Epidemiologists and policy makers have to deal with poor data quality, limited understanding of the disease dynamics, a rapidly changing social environment and the uncertainty around the effects of various interventions in place. In this setting,…
Calibration/Validation | Microsimulation | Dynamic Simulation | Infectious Diseases | Health/Medicine | Sub-Saharan Africa -
ReviewPublication 2017Validation and Calibration of Structural Models that Combine Information from Multiple Sources
This is a review of calibration and validation methods in mathematical modeling. Such models that …
This is a review of calibration and validation methods in mathematical modeling. Such models that attempt to capture structural relationships between their components and combine information from multiple sources are increasingly used in medicine. The authors provide an overview of methods for model validation and calibration and survey studies comparing alternative approaches. Model validation entails a confrontation of models with data, background knowledge, and other models, and can inform judgments about model credibility. Calibration involves…
Calibration/Validation | Mathematical Models | Health/Medicine -
ArticlePublication 2017Likelihood Approach for Calibration of Stochastic Epidemic Models
Stochastic transmission dynamic models are especially useful for studying the early emergence of novel pathogens …
Stochastic transmission dynamic models are especially useful for studying the early emergence of novel pathogens given the importance of chance events when the number of infectious individuals is small. However, methods for parameter estimation and prediction for these types of stochastic models remain limited. This paper describes a calibration and prediction framework for stochastic compartmental transmission models of epidemics. The proposed method applies a linear noise approximation to describe the size of the fluctuations, and…
Calibration/Validation | Dynamic Transmission | Dynamic Simulation | Infectious Diseases | Health Systems | Health/Medicine | Global -
ArticlePublication 2015Cancer Models and Real-World Data: Better Together
Decision-analytic models synthesize available data on disease burden and intervention effectiveness to project estimates of …
Decision-analytic models synthesize available data on disease burden and intervention effectiveness to project estimates of the long-term consequences of care. While models have been influential in informing US cancer screening guidelines under ideal conditions, incorporating detailed data on real-world screening practice has been limited given the complexity of screening processes and behaviors throughout diverse health delivery systems in the United States. The authors describe the synergies that exist between decision-analytic models and health care utilization…
Calibration/Validation | Evidence Synthesis | Mathematical Models | Chronic Disease/Risk | Health Systems | Clinical Care | Health/Medicine | Science/Technology | North America -
ArticlePublication 2015Population Health Model (POHEM): An Overview
This paper provides an overview of the rationale, methodology and applications of the Population Health …
This paper provides an overview of the rationale, methodology and applications of the Population Health Model (POHEM). POHEM is a health microsimulation model, developed at Statistics Canada in the early 1990s. The authors describe that POHEM draws together rich multivariate data from a wide range of sources to simulate the lifecycle of the Canadian population, specifically focusing on aspects of health. The model dynamically simulates individuals’ disease states, risk factors, and health determinants, in order…
Calibration/Validation | Costing Methods | Evidence Synthesis | Mathematical Models | Microsimulation | Chronic Disease/Risk | Health Systems | Policy/Regulation | Clinical Care | Economics/Finance | Health/Medicine | North America -
Tutorial/PrimerPublication, Teaching Resource 2015Calibration of Complex Models through Bayesian Evidence Synthesis: A Tutorial
This tutorial demonstrates how to implement a Bayesian synthesis of diverse sources of evidence to …
This tutorial demonstrates how to implement a Bayesian synthesis of diverse sources of evidence to calibrate the parameters of a complex model. To illustrate these methods, the authors demonstrate how a previously developed Markov model for the progression of human papillomavirus (HPV-16) infection was rebuilt in a Bayesian framework. Transition probabilities between states of disease severity are inferred indirectly from cross-sectional observations of prevalence of HPV-16 and HPV-16–related disease by age, cervical cancer incidence, and…
Calibration/Validation | Infectious Diseases