Resources Repository
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GuidelinesPublication 2012Modeling Using Discrete Event Simulation: A Report of the ISPOR-SMDM Modeling Task Force-4
This paper reports on consensus-based guidelines on the application of DES in a health care …
This paper reports on consensus-based guidelines on the application of DES in a health care setting, covering the range of issues to which DES can be applied. Discrete event simulation (DES) is a form of computer-based modeling that provides an intuitive and flexible approach to representing complex systems. The article works through the different stages of the modeling process: structural development, parameter estimation, model implementation, model analysis, and representation and reporting. Recommendations are made for…
Evidence Synthesis | Dynamic Simulation | Calibration/Validation | Health/Medicine | Mathematical Models -
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…
Dynamic Simulation | Calibration/Validation | Value of Information | Health/Medicine | Costing Methods | Health Outcomes | Mathematical Models | State-Transition | Dynamic Transmission | Microsimulation | Decision Analysis | Infectious Diseases -
ArticlePublication 2023Simulation-Based Estimates and Projections of Global, Regional and Country-Level Maternal Mortality by Cause, 1990-2050
While progress has been made globally to reduce maternal deaths, measurement remains a challenge given …
While progress has been made globally to reduce maternal deaths, measurement remains a challenge given the many causes and frequent underreporting of maternal deaths. The authors developed a structural microsimulation model of Global Maternal Health (GMatH) for 200 countries and territories using demographic, epidemiologic, clinical and health system data synthesized from the medical literature, Civil Registration Vital Statistics systems and Demographic and Health Survey data. The model was calibrated to empirical data from 1990 to…
Evidence Synthesis | Calibration/Validation | Health/Medicine | Health Outcomes | Microsimulation | Maternal/Reproductive Health | Health Systems | Clinical Care | Global -
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,…
Dynamic Simulation | Calibration/Validation | Health/Medicine | Microsimulation | Infectious Diseases | Sub-Saharan Africa -
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…
Dynamic Simulation | Calibration/Validation | Health/Medicine | Dynamic Transmission | Infectious Diseases | Health Systems | 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…
Evidence Synthesis | Calibration/Validation | Health/Medicine | Mathematical Models | Chronic Disease/Risk | Health Systems | Clinical Care | 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…
Evidence Synthesis | Calibration/Validation | Health/Medicine | Costing Methods | Mathematical Models | Microsimulation | Chronic Disease/Risk | Health Systems | Policy/Regulation | Clinical Care | Economics/Finance | North America -
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.…
Calibration/Validation | Value of Information | Health/Medicine | Mathematical Models -
ArticlePublication 2023Simulation-Based Comparative Effectiveness Analysis of Policies to Improve Global Maternal Health Outcomes
The Sustainable Development Goals include a target to reduce the global maternal mortality ratio (MMR) …
The Sustainable Development Goals include a target to reduce the global maternal mortality ratio (MMR) to less than 70 maternal deaths per 100,000 live births by 2030, with no individual country exceeding 140. However, on current trends the goals are unlikely to be met. The authors used an empirically calibrated Global Maternal Health microsimulation model, which simulates individual women in 200 countries and territories to evaluate the impact of different interventions and strategies from 2022…
Calibration/Validation | Health/Medicine | Health Outcomes | Mathematical Models | Microsimulation | Maternal/Reproductive Health | Health Systems | Clinical Care | Global