Resources Repository
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Resource PackWeb Portal, Teaching Resource 2018Resource Pack: Cervical Cancer Models
This resource pack, curated by the Center for Health Decision Science, is a collection of …
This resource pack, curated by the Center for Health Decision Science, is a collection of models of HPV-related cervical cancer, differing in design, structure and features based on analytic objectives. In many ways, HPV and its related diseases represent a prototypical public health problem given the communicable and non-communicable nature of disease, opportunities for intervention along the entire disease spectrum (e.g., primary and secondary prevention, diagnosis, treatment), the varied ages at which interventions are targeted…
Dynamic Simulation | Calibration/Validation | Health/Medicine | Economics/Finance | Mathematical Models | State-Transition | Dynamic Transmission | Microsimulation | Cost-Effectiveness Analysis | Infectious Diseases | Chronic Disease/Risk | Health Systems | Clinical Care | Business/Industry | Science/Technology | Global -
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…
Dynamic Simulation | Calibration/Validation | Health/Medicine | Mathematical Models | State-Transition | Dynamic Transmission | Microsimulation -
Resource PackPublication, Teaching Resource 2018Resource Pack: Models for Health Decision Science
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 mathematical models used in health decision science (e.g., microsimulation, dynamic transmission, agent-based, etc.). Resources include overviews, guidelines, tutorials, and applications relevant to a broad range of clinical and public health topics. A decision analytic approach relies on the use of a mathematical model to formally structure the components of the decision over time. Models are particularly useful when multiple data sources…
Dynamic Simulation | Health/Medicine | Economics/Finance | Mathematical Models | State-Transition | Dynamic Transmission | Microsimulation | Climate/Environment | Science/Technology -
Resource PackWeb Portal, Teaching Resource 2017Resource Pack: Valuing Vaccines and GAVI
This resource pack on valuing vaccines and GAVI was curated by the Center for Health …
This resource pack on valuing vaccines and GAVI was curated by the Center for Health Decision Science to showcase existing information and analyses to motivate students, educators and others to pursue new applications of decision science methods to the public health challenge of vaccine preventable illnesses.
Calibration/Validation | Health/Medicine | Economics/Finance | Preferences/Values | Priority Setting/Ethics | Costing Methods | Mathematical Models | Dynamic Transmission | Benefit-Cost Analysis | Cost-Effectiveness Analysis | Infectious Diseases | Child/Nutrition | Health Systems | Global Governance | Government/Law | Science/Technology | Global | Graduate | Doctoral | Professional | Critical Thinking/Analysis | Policy Translation | Quantitative Literacy -
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 -
Resource PortalWeb Portal, Teaching Resource 2024MIDAS
MIDAS is a collaborative network of research scientists who use computational, statistical and mathematical models …
MIDAS is a collaborative network of research scientists who use computational, statistical and mathematical models to understand infectious disease dynamics and thereby assist the nation to prepare for, detect and respond to infectious disease threats. Midas focuses on research topics such as: Dynamics of emergence and spread of pathogens; Identification and surveillance of infectious diseases; Effectiveness and consequences of intervention strategies; Host/pathogen interactions; Ecological, climatic, economic and evolutionary dimensions of infectious diseases; The roles of behavior and behavioral adaptation in…
Dynamic Simulation | Calibration/Validation | Health/Medicine | Mathematical Models | Dynamic Transmission | Risk Analysis | Cost-Effectiveness Analysis | Technology Assessment | Infectious Diseases | Health Systems | Policy/Regulation | Climate/Environment | Science/Technology | Global | Graduate | Doctoral | Professional | Critical Thinking/Analysis | Conceptual Mapping | Quantitative Literacy -
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 | Health/Medicine | Economics/Finance | Costing Methods | Evidence Synthesis | Mathematical Models | Microsimulation | Chronic Disease/Risk | Health Systems | Policy/Regulation | Clinical Care | North America -
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…
Dynamic Simulation | Calibration/Validation | Health/Medicine | Evidence Synthesis | Mathematical Models