Resources Repository
-
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 | Mathematical Models | Dynamic Transmission | Calibration/Validation | Risk Analysis | Cost-Effectiveness Analysis | Technology Assessment | Infectious Diseases | Health Systems | Policy/Regulation | Climate/Environment | Health/Medicine | Science/Technology | Global | Graduate | Doctoral | Professional | Critical Thinking/Analysis | Conceptual Mapping | Quantitative Literacy -
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 | 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…
Dynamic Simulation | Microsimulation | Mathematical Models | Asia & Pacific -
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 | Priority Setting/Ethics | Costing Methods | Decision Analysis | Cost-Effectiveness Analysis | Chronic Disease/Risk | Mental Health | Health/Medicine | 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 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…
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 | Infectious Diseases | Health/Medicine -
ArticlePublication 2011Dynamic Policies for Controlling Spread of Emerging Infections
This paper illustrates the design and implementation of a dynamic health policy for the control …
This paper illustrates the design and implementation of a dynamic health policy for the control of a novel strain of influenza, where two types of interventions are assumed to be available during the epidemic: (1) vaccines and antiviral drugs, and (2) transmission reducing measures, such as social distancing or mask use, that may be turned "on" or "off" repeatedly during the course of epidemic. A modeling approach is described for developing dynamic health policies that allow…
Dynamic Simulation | Mathematical Models | Dynamic Transmission | Infectious Diseases | Health Systems | Policy/Regulation | Health/Medicine | Science/Technology | Global -
ReviewPublication 2011Simulation Models of Obesity: A Review of the Literature
Simulation models combine information from a variety of sources to provide a useful tool for …
Simulation models combine information from a variety of sources to provide a useful tool for examining how the effects of obesity unfold over time and impact population health. They can aid in the understanding of the complex interaction of the drivers of diet and activity and their relation to health outcomes. This paper provided an overview of different types of simulation models used to evaluate the potential impact of policies to address the obesity epidemic.…
Microsimulation | Mathematical Models | State-Transition | Calibration/Validation | Decision Analysis | Cost-Effectiveness Analysis | Child/Nutrition | Chronic Disease/Risk | Economics/Finance | Food/Agriculture | Health/Medicine