Resources Repository
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Tools/ModelsPublication, Teaching Resource 2017Publicly Available Software Tools for Decision-Makers During an Emergent Epidemic
Epidemics and emerging infectious diseases are becoming an increasing threat to global populations-challenging public health …
Epidemics and emerging infectious diseases are becoming an increasing threat to global populations-challenging public health practitioners, decision makers and researchers to plan, prepare, identify and respond to outbreaks in near real-timeframes. The aim of this research is to evaluate the range of public domain and freely available software epidemic modelling tools. Twenty freely utilizable software tools underwent assessment of software usability, utility and key functionalities. Stochastic and agent based tools were found to be highly…
Dynamic Simulation | Mathematical Models | Dynamic Transmission | Health/Medicine | Infectious Diseases | Health Systems | Climate/Environment | Science/Technology | Global | Graduate | Doctoral | Professional | 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 | Microsimulation | Calibration/Validation | Health/Medicine | 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 | Dynamic Transmission | Health/Medicine | Infectious Diseases | Health Systems | 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…
Dynamic Simulation | Mathematical Models | Dynamic Transmission | Health/Medicine | Cost-Effectiveness Analysis | Infectious Diseases -
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…
Microsimulation | Mathematical Models | Calibration/Validation | Health/Medicine | Costing Methods | Evidence Synthesis | Chronic Disease/Risk | Health Systems | Policy/Regulation | Clinical Care | Economics/Finance | North America -
ReportPublication 2015Modeling to Improve Policy Decisions in the Americas: Noncommunicable Diseases
In the Region of the Americas, noncommunicable diseases (NCDs) are a clear threat not only …
In the Region of the Americas, noncommunicable diseases (NCDs) are a clear threat not only to human health, but also to a country’s economic development and growth. The evidence on both of these counts is compelling. In 2012, cardiovascular disease, diabetes, cancers, chronic respiratory conditions including asthma, and other NCDs were the cause of 4.5 million deaths in the Americas. Of that total number, 1.5 million of them were premature, occurring among people aged 30-69…
Microsimulation | Mathematical Models | State-Transition | Health/Medicine | Priority Setting/Ethics | Costing Methods | Decision Analysis | Cost-Effectiveness Analysis | Chronic Disease/Risk | Mental Health | Latin America & Caribbean -
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,…
Microsimulation | Mathematical Models | State-Transition | Health/Medicine | Health Systems | Clinical Care -
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…
Microsimulation | Mathematical Models | State-Transition | 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…
Dynamic Simulation | Mathematical Models | Dynamic Transmission | Health/Medicine | Infectious Diseases