Dynamic Microsimulation of Health Care Demand, Health Care Finance and the Economic Impact of Health Behavior. Part I: Background and a Comparison with Cell-Based Models

Cell-based health care models, as well as macro-level projections of future population and economic trends used as input to health care models, are limited to a few variables, which makes microsimulation an interesting modeling option, especially as it allows for modeling of the interaction of demographic with social, environmental and economic variables. Micro-approaches can incorporate the wealth of substantive analysis gained from a large number of micro- and macro-level studies with regard to demographic, economic and health behavior. Compared to cell-based macro models, microsimulation can produce useful projections for the analysis of different health-related phenomena considering additional dimensions, i.e., detailed issues regarding health care finance (insurance schemes, individual accounts etc.) and individual risk exposure. This paper constitutes the first part of an investigation of the potential of dynamic microsimulation for the modeling and projection of health care demand, health care finance and the economic impact of health behavior. The main purpose of this part is to provide a brief theoretical background with regard to the dynamic microsimulation approach and a comparison of the microsimulation approach with the cell-based macro approach. Starting with a definition of dynamic microsimulation and a classification of the types and approaches, microsimulation modeling is brought into the context of the life-course paradigm. This paradigm, meanwhile being the dominant paradigm in demography, can also be a useful organizational principle for the study and projection of health-related phenomena using microsimulation. Microsimulation is then compared with cell-based approaches, and the potential strengths as well as drawbacks of the microsimulation approach with regard to health care modeling are investigated. Dynamic microsimulation might turn out to be increasingly appropriate as a modeling approach in this field, which is currently dominated by cell-based macro-models

The Potential of Dynamic Microsimulation in Family Studies: a Review and some Lessons for FAMSIM+

Die Entwicklung von Simulationsmodellen nimmt in der sozioökonomischen Abteilung einen zentralen Forschungsschwerpunkt ein, dies einerseits in der Form von Hochrechnungsmodellen zur Berechnung von Kosten und Verteilungswirkungen familienpolitischer Maßnahmen (Förderungen) - hierzu wurden insbesondere Modelle und Softwarepakete für die Bundesländer Niederösterreich und Wien entwickelt - und andererseits in der Form des dynamischen Mikrosimulationsmodells FAMSIM. Dynamische Mikrosimulation erlaubt es, die Individuen einer Bevölkerung über ihren ganzen Lebenslauf im Computer zu simulieren, was insbesondere zur Erforschung demographischer Prozesse dient bzw. die Erforschung der Auswirkungen dieser Prozesse auf andere Systeme - wie etwa Pensionssysteme. Statische "cell-based" Modelle zur Berechnung der Kosten von Familienförderungen in der Form frei parametrisierbarer Simulationsmodelle auf Basis von realen Antragsdaten zu Förderungen: Anwendungen in Wien und Niederösterreich. Modellierung, Programmierung und ökonometrische Schätzung des dynamischen FAMSIM Modells für 5 Europäische Länder; Internationale Vergleichsstudien zu typischen "Risikomustern" betreffend dem Beginn und Ende von Partnerschaften, Erwerbstätigkeit, Ausbildungen sowie Schwangerschaften/Geburten. Zusammenführung der statischen und dynamischen Modelle zu einem dynamischen Familien - Mikrosimulationsmodell FAMSIM+ zur Erforschung demographischer Prozesse (wie sich verändernder Familienstrukturen) sowie der Evaluierung der Kosten und Wirkung familienrelevanter Maßnahmen im Quer- und Längsschnitt. Dieser Ansatz erlaubt zum Beispiel die Erforschung der Auswirkungen von Erwerbsunterbrechungen zur Kinderbetreuung auf die gesamte weitere Erwerbskarriere einschließlich Pensionsansprüche. Nationale und internationale Kooperationen für verschiedene Anwendungsgebiete, wie derzeit für Bildungsprognosen (Kooperation mit dem Institut für Bildungsforschung der Wirtschaft) sowie im Bereich Altenpflege (Netzwerkpartner im International Network for the Research on Elderly Care INREC)

Family Microsimulation (FAMSIM): Socio-economic Analysis, Simulation and Surveys

Die Entwicklung von Simulationsmodellen nimmt in der sozioökonomischen Abteilung einen zentralen Forschungsschwerpunkt ein, dies einerseits in der Form von Hochrechnungsmodellen zur Berechnung von Kosten und Verteilungswirkungen familienpolitischer Maßnahmen (Förderungen) - hierzu wurden insbesondere Modelle und Softwarepakete für die Bundesländer Niederösterreich und Wien entwickelt - und andererseits in der Form des dynamischen Mikrosimulationsmodells FAMSIM. Dynamische Mikrosimulation erlaubt es, die Individuen einer Bevölkerung über ihren ganzen Lebenslauf im Computer zu simulieren, was insbesondere zur Erforschung demographischer Prozesse dient bzw. die Erforschung der Auswirkungen dieser Prozesse auf andere Systeme - wie etwa Pensionssysteme. Statische „cell-based“ Modelle zur Berechnung der Kosten von Familienförderungen in der Form frei parametrisierbarer Simulationsmodelle auf Basis von realen Antragsdaten zu Förderungen: Anwendungen in Wien und Niederösterreich. Modellierung, Programmierung und ökonometrische Schätzung des dynamischen FAMSIM Modells für 5 Europäische Länder; Internationale Vergleichsstudien zu typischen „Risikomustern“ betreffend dem Beginn und Ende von Partnerschaften, Erwerbstätigkeit, Ausbildungen sowie Schwangerschaften/Geburten. Zusammenführung der statischen und dynamischen Modelle zu einem dynamischen Familien - Mikrosimulationsmodell FAMSIM+ zur Erforschung demographischer Prozesse (wie sich verändernder Familienstrukturen) sowie der Evaluierung der Kosten und Wirkung familienrelevanter Maßnahmen im Quer- und Längsschnitt. Dieser Ansatz erlaubt zum Beispiel die Erforschung der Auswirkungen von Erwerbsunterbrechungen zur Kinderbetreuung auf die gesamte weitere Erwerbskarriere einschließlich Pensionsansprüche. Nationale und internationale Kooperationen für verschiedene Anwendungsgebiete, wie derzeit für Bildungsprognosen (Kooperation mit dem Institut für Bildungsforschung der Wirtschaft) sowie im Bereich Altenpflege (Netzwerkpartner im International Network for the Research on Elderly Care INREC)

Integrated design of transport infrastructure and public spaces considering human behavior: A review of state-of-the-art methods and tools

In order to achieve holistic urban plans incorporating transport infrastructure, public space and the behavior of people in these spaces, integration of urban design and computer modeling is a promising way to provide both qualitative and quantitative support to decision-makers. This paper describes a systematic literature review following a four-part framework. Firstly, to understand the relationship of elements of transport, spaces, and humans, we review policy and urban design strategies for promoting positive interactions. Secondly, we present an overview of the integration methods and strategies used in urban design and policy discourses. Afterward, metrics and approaches for evaluating the effectiveness of integrated plan alternatives are reviewed. Finally, this paper gives a review of state-of-the-art tools with a focus on seven computer simulation paradigms. This article explores mechanisms underlying the complex system of transport, spaces, and humans from a multidisciplinary perspective to provide an integrated toolkit for designers, planners, modelers and decision-makers with the current methods and their challenges

Simulation of household in-home and transportation energy use : an integrated behavioral model for estimating energy consumption at the neighborhood scale

Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 101-109).Household in-home activities and out-of-home transportation are two major sources of urban energy consumption. In light of China's rapid urbanization and income growth, changing lifestyles and consumer patterns - evident in increased ownership of appliances and motor vehicles - will have a large impact on residential energy use in the future. The pattern of growth of Chinese cities may also play an intertwined role in influencing and being influenced by consumption patterns and, thus energy use. Nonetheless, models for evaluating energy demand often neglect the evolution of appliance & vehicle ownership and directly correlate consumption with static characteristics without explicit behavioral links. In this thesis I aim to provide a comprehensive method for understanding household energy behavior over time. Using household survey data and neighborhood form characteristics from Jinan, a mid-sized Chinese city, I explore the relationship between neighborhood design and household-level behaviors and their impact on final energy consumption. My ultimate goal is to provide the modeling engine for the "Energy Proforma©" a tool intended to help developers, designers, and policy-makers implement more energy-efficient neighborhoods. To predict in-home and transportation energy use, and their trade-offs, I develop an integrated household-level micro-simulation framework. The simulation tool is based on a total of eight inter-related behavioral models which estimate out-of-home energy use by predicting trip generation, mode choice and trip length for each household and in-home energy use according to different energy sources. In the various sub-models, relevant dimensions of neighborhood form and design are included as explanatory variables. These models are then combined with modules that update household demographics, appliance & vehicle ownership information, and activity trade-off patterns. These inter-linked models can then be used to estimate the long-term effects of neighborhood design on household energy consumption and greenhouse gas emissions. Unlike separate in-home or out-of-home energy demand models, I develop an integrated simulation framework for forecasting. It captures estimated trade-off effects between in-home and transportation energy-consuming behaviors. The approach produces indicators of detailed behavioral outcomes such as trip mode and trip length choice, making it easier to relate policies, such as mode-oriented strategies, to ultimate outcomes of interest. I ultimately aim to provide urban designers, developers, and policy makers a decision support tool to explore and compare long-term energy performance across proposed neighborhood development projects.by Feifei Yu.S.M. in Transportatio

Calibration of a spatial simulation model with volunteered geographical information

For many scientific disciplines, the continued progression of information technology has increased the availability of data, computation and analytical methodologies including simulation and visualisation. Geographical information science is no exception. In this article, we investigate the possibilities for deployment of e-infrastructures to inform spatial planning, analysis and policy-making. We describe an existing architecture that feeds both static and dynamic simulation models from a variety of sources, including not only administrative datasets but also attitudes and behaviours which are harvested online from crowds. This infrastructure also supports visualisation and computationally intensive processing. The main aim of this article is to illustrate how spatial simulation models can be calibrated with crowd-sourced data. We introduce an example in which popular attitudes to congestion charging in a major UK city (Manchester) were collected, with promotional support from a high-profile media organisation (the BBC). These data are used to estimate the parameters of a transport simulation model, using a hungry estimation procedure which is deployed within a high-performance computational grid. We indicate how the resulting model might be used to evaluate the impact of alternative policy options for regulating the traffic in Manchester. Whilst the procedure is novel in itself, we argue that greater credibility could be added by the incorporation of open-source simulation models and by the use of social networking mechanisms to share policy evaluations much more widely

Introducing CASCADEPOP: an open-source sociodemographic simulation platform for US health policy appraisal

Largescale individual-level and agent-based models are gaining importance in health policy appraisal and evaluation. Such models require the accurate depiction of the jurisdiction’s population over extended time periods to enable modeling of the development of non-communicable diseases under consideration of historical, sociodemographic developments. We developed CASCADEPOP to provide a readily available sociodemographic micro-synthesis and microsimulation platform for US populations. The micro-synthesis method used iterative proportional fitting to integrate data from the US Census, the American Community Survey, the Panel Study of Income Dynamics, Multiple Cause of Death Files, and several national surveys to produce a synthetic population aged 12 to 80 years on 01/01/1980 for five states (California, Minnesota, New York, Tennessee, and Texas) and the US. Characteristics include individuals’ age, sex, race/ethnicity, marital/employment/parental status, education, income and patterns of alcohol use as an exemplar health behavior. The microsimulation simulates individuals’ sociodemographic life trajectories over 35 years to 31/12/2015 accounting for population developments including births, deaths, and migration. Results comparing the 1980 micro-synthesis against observed data shows a successful depiction of state and US population characteristics and of drinking. Comparing the microsimulation over 30 years with Census data also showed the successful simulation of sociodemographic developments. The CASCADEPOP platform enables modelling of health behaviors across individuals’ life courses and at a population level. As it contains a large number of relevant sociodemographic characteristics it can be further developed by researchers to build US agent-based models and microsimulations to examine health behaviors, interventions, and policies

Transportation in Agent-Based Urban Modelling

As the urban population rapidly increases to the point where most of us will be living in cities by the end of this century, the need to better understand urban areas grows ever more urgent. Urban simulation modelling as a field has developed in response to this need, utilising developing technologies to explore the complex interdependencies, feedbacks, and heterogeneities which characterise and drive processes that link the functions of urban areas to their form. As these models grow more nuanced and powerful, it is important to consider the role of transportation within them. Transportation joins, divides, and structures urban areas, providing a functional definition of the geometry and the economic costs that determine urban processes accordingly. However, it has proved challenging to factor transportation into agent-based models (ABM); past approaches to such modelling have struggled to incorporate information about accessibility, demographics, or time costs in a significant way. ABM have not yet embraced alternative traditions such as that in land use transportation modelling that build on spatial interaction in terms of transport directly, nor have these alternate approaches been disaggregated to the level at which populations are represented as relatively autonomous agents. Where disaggregation of aggregate transport has taken place, it has led to econometric models of individual choice or microsimulaton models of household activity patterns which only superficially embody the key principles of ABM. But the explosion in the availability of movement data in recent years, combined with improvements in modelling technology, is easing this process dramatically. In particular, agent-based modelling as a methodology has grown ever more promising and is now capable of emulating the interplay of urban systems and transportation. Here, we explore the importance of this approach, review how transportation has been factored into or omitted from agent-based models of urban areas, and suggest how it might be handled in future applications. Our approach is to take snapshots of different applications and use these to illustrate how transportation is handled in such models

A synthetic population for agent-based modelling in Canada

In order to anticipate the impact of local public policies, a synthetic population reflecting the characteristics of the local population provides a valuable test bed. While synthetic population datasets are now available for several countries, there is no open-source synthetic population for Canada. We propose an open-source synthetic population of individuals and households at a fine geographical level for Canada for the years 2021, 2023 and 2030. Based on 2016 census data and population projections, the synthetic individuals have detailed socio-demographic attributes, including age, sex, income, education level, employment status and geographic locations, and are related into households. A comparison of the 2021 synthetic population with 2021 census data over various geographical areas validates the reliability of the synthetic dataset. Users can extract populations from the dataset for specific zones, to explore ‘what if’ scenarios on present and future populations. They can extend the dataset using local survey data to add new characteristics to individuals. Users can also run the code to generate populations for years up to 2042

Emerging data sources and advanced microsimulation in transport modelling

Transport modelling is an essential tool for policy makers to make informed transport planning decisions for the wellbeing of the society. However, most strategic transport models do not accurately incorporate the dynamics of population and households and their interactions, resulting in inaccurate forecasts of travel and land use demands. While it is highly crucial that strategic transport models provide accurate long-term forecasts that are vital for the appraisal of large transport infrastructure projects, short-term and medium-term forecasts are also integral for enhancing the efficiency of transport systems. Furthermore, in the modern, fast-paced world, emerging data sources are integral in both transport research and practice. For instance, data collected from smartphone travel surveys and electronic ticketing systems can be used to derive deep insights into people’s travel behaviour. Therefore, this thesis is set out to investigate how population evolution modelling can be improved in transport models, and also how emerging data sources can be leveraged to fill existing knowledge gaps. This thesis focuses on two main themes: (1) to explore new opportunities from emerging technologies and data sources and (2) to develop a dynamic microsimulation model that can provide a more accurate population input for a transport demand model and also to enhance the model development process. Using transit smart card data, The first main chapter explores the impacts of transit ridership and reliability on residential property values in Brisbane, Australia. Three frequently used spatial regression techniques in hedonic studies are used along with a simple linear regression model. The second main chapter presents the first analysis on how social media offers a cost effective means to recruit and engage smartphone travel survey participants. On top of that, recommendations on recruitment, marketing, sample representativeness, incentivisation, and deployment of the study are discussed. The third main chapter introduces an open source dynamic microsimulation toolbox for integrated urban modelling. This toolbox allows microsimulation models to be more easily developed and enables several well-known modelling packages in R to be integrated with the models. Finally, the last main chapter presents a demographic microsimulation model, built with the toolbox, that not only simulates the lifecycle of individuals but also the integration of new migrants into the population using a novel household alignment method