Resources Repository
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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,…
Microsimulation | Calibration/Validation | Dynamic Simulation | Infectious Diseases | Health/Medicine | 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 Transmission | Calibration/Validation | Dynamic Simulation | Infectious Diseases | Health Systems | Health/Medicine | Global -
ArticlePublication 2016Identifying Cost-Effective Dynamic Policies to Control Epidemics
This paper describes a mathematical decision model for identifying dynamic health policies for controlling epidemics. …
This paper describes a mathematical decision model for identifying dynamic health policies for controlling epidemics. The dynamic policies aim to select the best current intervention based on accumulating epidemic data and the availability of resources at each decision point. An algorithm is proposed to approximate dynamic policies that optimize the population's net health benefit, a performance measure which accounts for both health and monetary outcomes. The authors further illustrate how dynamic policies can be defined and…
Mathematical Models | Dynamic Transmission | Dynamic Simulation | Cost-Effectiveness Analysis | Infectious Diseases | Health/Medicine -
ArticlePublication 2016Combining Microsimulation and Agent-Based Modeling
This paper proposes a hybrid model structure combining microsimulation and agent-based modeling to simulate population …
This paper proposes a hybrid model structure combining microsimulation and agent-based modeling to simulate population dynamics. Microsimulation describes the population dynamics at the individual level, and actions conducted by the individuals are generated by stochastic processes. An emerging method is the agent-based model, which focuses on the interactions among individuals and expects to see unexpected situations created from the interactions. In the proposed hybrid model, the microsimulation model takes a role to depict how an…
Mathematical Models | Microsimulation | Dynamic Simulation | Asia & Pacific -
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…
Costing Methods | Evidence Synthesis | Mathematical Models | Microsimulation | Calibration/Validation | Chronic Disease/Risk | Health Systems | Policy/Regulation | Clinical Care | Economics/Finance | Health/Medicine | North America -
ReviewPublication 2014Markov Modeling & Discrete Event Simulation in Health Care: Systematic Comparison
This review assesses whether the use of Markov modeling (MM) or discrete event simulation (DES) …
This review assesses whether the use of Markov modeling (MM) or discrete event simulation (DES) for cost-effectiveness analysis (CEA) may alter healthcare resource allocation decisions. A systematic literature search and review of empirical and non-empirical studies comparing MM and DES techniques used in the CEA of healthcare technologies was conducted. The primary advantages described for DES over MM were the ability to model queuing for limited resources, capture individual patient histories, accommodate complexity and uncertainty,…
Mathematical Models | State-Transition | Microsimulation | Health Systems | Clinical Care | Health/Medicine -
GuidelinesPublication 2012State-Transition Modeling: A Report of the ISPOR-SMDM Modeling Task Force-3
State-transition modeling includes both Markov model cohort simulation as well as individual-based (first-order Monte Carlo) …
State-transition modeling includes both Markov model cohort simulation as well as individual-based (first-order Monte Carlo) microsimulation. These models have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs. Recommendations are made on choice of model type (cohort vs. individual-level model), model…
Mathematical Models | State-Transition | Microsimulation | Health/Medicine -
GuidelinesPublication 2012Dynamic Transmission Modeling: A Report of the ISPOR-SMDM Modeling Task Force-5
This paper reports the consensus-based guidelines on dynamic transmission modeling in health care. The transmissible …
This paper reports the consensus-based guidelines on dynamic transmission modeling in health care. The transmissible nature of communicable diseases is what sets them apart from other diseases modeled by health economists. The probability of a susceptible individual becoming infected at any one point in time (the force of infection) is related to the number of infectious individuals in the population, will change over time, and will feed back into the future force of infection. These…
Mathematical Models | Dynamic Transmission | Dynamic Simulation | Infectious Diseases | Health/Medicine -
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 | Mathematical Models | Calibration/Validation | Dynamic Simulation | Health/Medicine