Resources Repository
-
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 -
ReviewPublication 2016Remembering Howard Raiffa
Howard Raiffa (1924-2016) had a profound influence on all aspects of the decision sciences and on …
Howard Raiffa (1924-2016) had a profound influence on all aspects of the decision sciences and on the fields of systems analysis and operations research. He guided the introduction of the decision sciences into numerous fields such as business, medicine, public health, the environmental sciences, and law, and was instrumental in building world-recognized institutions such as the Kennedy School at Harvard and the International Institute for Applied Systems Analysis near Vienna, Austria. This article is a thoughtful tribute by…
Decision Theory | Preferences/Values | Decision Analysis | Operations Research | Business/Industry | Economics/Finance | Health/Medicine | Military/Defense | North America -
ArticlePublication 2016Estimating Benefits of Regulations Affecting Addictive Goods
The question of how to evaluate lost consumer surplus in benefit−cost analyses is controversial. There …
The question of how to evaluate lost consumer surplus in benefit−cost analyses is controversial. There are clear health benefits of regulations that curb consumption of goods with health risks, such as tobacco products and foods high in fats, calories, sugar, and sodium. Yet, if regulations cause consumers to give up goods they like, the health benefits they experience may be offset by some utility loss, which benefit−cost analyses of regulations need to take into account.…
Decision Theory | Preferences/Values | Benefit-Cost Analysis | Mental Health | Health/Medicine -
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 -
BookPublication 2016Foundations of Decision Analysis
This book is described by the authors as emerging from what they have learned by …
This book is described by the authors as emerging from what they have learned by "teaching decision analysis to thousands of people in the United States and around the world in university classes and special professional educational programs". The early chapters and certain later chapters are written to be accessible to a general audience. Chapters 1 through 17 introduce the foundations of decision analysis without requiring significant mathematical sophistication. Chapter 26 discusses multi-attribute decision problems…
Decision Theory | Decision Psychology | Probability/Bayes | Decision Analysis | Operations Research | Business/Industry | Economics/Finance | Energy/Engineering | Government/Law | Health/Medicine | Military/Defense | Global