Analysis of CDC social control measures using an agent-based simulation of an influenza epidemic in a city

Background: the transmission of infectious disease amongst the human population is a complex process which requires advanced, often individual-based, models to capture the space-time details observed in reality.Methods: an Individual Space-Time Activity-based Model (ISTAM) was applied to simulate the effectiveness of non-pharmaceutical control measures including: (1) refraining from social activities, (2) school closure and (3) household quarantine, for a hypothetical influenza outbreak in an urban area.Results: amongst the set of control measures tested, refraining from social activities with various compliance levels was relatively ineffective. Household quarantine was very effective, especially for the peak number of cases and total number of cases, with large differences between compliance levels. Household quarantine resulted in a decrease in the peak number of cases from more than 300 to around 158 for a 100% compliance level, a decrease of about 48.7%. The delay in the outbreak peak was about 3 to 17 days. The total number of cases decreased to a range of 3635-5403, that is, 63.7%-94.7% of the baseline value.When coupling control measures, household quarantine together with school closure was the most effective strategy. The resulting space-time distribution of infection in different classes of activity bundles (AB) suggests that the epidemic outbreak is strengthened amongst children and then spread to adults. By sensitivity analysis, this study demonstrated that earlier implementation of control measures leads to greater efficacy. Also, for infectious diseases with larger basic reproduction number, the effectiveness of non-pharmaceutical measures was shown to be limited.Conclusions: simulated results showed that household quarantine was the most effective control measure, while school closure and household quarantine implemented together achieved the greatest benefit. Agent-based models should be applied in the future to evaluate the efficacy of control measures for a range of disease outbreaks in a range of settings given sufficient information about the given case and knowledge about the transmission processes at a fine scal

PUMA - a multi-agent model of urban systems

It is increasingly recognised that land use change processes are the outcome of decisions made by individual actors, such as land owners, authorities, firms and households. As multi-agent models provide a natural framework for modelling urban processes on the level of individual actors, Utrecht University, Eindhoven University of Technology and RIVM are developing PUMA (Predicting Urbanisation with Multi-Agents), a full fledged multi-agent system of urban processes. PUMA consists of various modules, representing the behaviours of specific actors. The land conversion module describes farmers', authorities', investors' and developers' decisions to sell or buy land and develop it into other uses. The households module describes households' housing careers in relation to life cycle events (marriage, child birth, aging, job change etc.). The firms module includes firms' demography and their related demand for production facilities leading to location choice processes. The daily activity pattern module describes the trips made and locations visited by individuals to carry out certain tasks. This module generates aggregated effects of individual behaviours (congestion, pollution, noise), affecting households' or firms' longer term location decisions. The paper describes the model system architecture and the interactions between the modules. Particular attention is devoted to the households module that includes a behaviourally sophisticated model of households' process of awakening (deciding to actively search for another dwelling), search and acceptance of an offered dwelling. This model was calibrated on the Dutch Housing Preferences Survey. Based on the disaggregate housing search and acceptance model, the households module describes housing market dynamics and indicates the demand for new dwellings per region. The paper describes the model specification and calibration in detail. The households module was implemented and tested for the Northwing of the Dutch Randstad, including about 1.5 million households and 1.6 million dwellings. The paper describes the implementation and the first model results.

Road pricing and (re)location decisions households

Road pricing policies are, after a cooling down period of a couple of years, again prominently back on the political agenda in the Netherlands. But also in the period of less political interest, research in the field of (road) pricing policies continued in other countries as well as in the Netherlands. Most research literature focuses on the economic and acceptability aspects of pricing policies. The geographical aspects of transport pricing however have received much less attention so far. This paper focuses on possible influences of road pricing policies on residential and work location choice of households. The paper starts with analyzing the importance of transport and location related variables in residential location decisions, when the choice to relocate itself has been made. For this analysis data from a stated choice experiment is used. Choice screens within the experiment consisted of two alternatives. In total, per respondent nine choice screens were shown. Transport related variables within the experiment were commuting travel time, fuel cost and toll cost. The location related variables consisted of the residential environment, the number of bedrooms and the monthly housing costs. Analysis of the results gives insight into the importance of for example toll costs on the final location choice when a decision to relocate itself has already been made. However this type of analysis does not give insight into the number of people who are actually considering changing location when a form of road pricing is introduced. Therefore the second part of the paper continues with analyzing the extent to which people are likely to relocate due to road pricing. The effect of different types of pricing measures and pricing levels on this inclination to relocate are examined. For the analysis, data from a stated preference questionnaire is used. The paper finally concludes with an examination of important explaining variables for moving house or changing job due to road pricing. Some important findings are for example that older people (above 40 years of age), people with a higher income and persons getting a travel cost compensation from their employer are less willing to move due to a pricing measure. People with a higher education level however are more willing to relocate.

Taste Heterogeneity and Substitution Patterns in Models of the Simultaneous Choice of Activity Timing and Duration

The recent growth of interest in activity-based methods has focused particular attention on travellers’ decision making regarding the timing and duration of their participation in activities. However, to date these two dimensions of activity participation have been largely treated separately. It is clear, however, that in general, the benefit that an individual derives from participating in an activity will depend inter alia both upon the time at which the activity is undertaken and the amount of time devoted to the activity. Moreover, it is also clear that this benefit will also depend on a wide range of other factors such as the quality of the activity opportunities available at particular destinations and the intensity with which activities are undertaken. Since these factors are inherently difficult or impossible to completely characterise or measure via conventional travel or time use data sources, it is likely that such decisions will also be characterised by significant unobserved heterogeneity. Based on earlier theoretical work by the authors, this paper proposes a model for the simultaneous choice of the timing and duration of activities and associated travel and uses data from a stated preference experiment to estimate the parameters of this model. The first section of the paper provides a brief review of the existing literature on activity timing and duration choice. The second section introduces the theoretical approach, which assume that the marginal utility derived from activities encompasses two distinct components; one derived from the duration of activity involvement and the other derived from activity participation at a particular time-of-day. A number of alternative additive and multiplicative specifications are introduced and their properties are explored. The third section briefly describes the stated preference data, which was collected in a survey undertaken in London in which respondents were presented with a number of scenarios in which they were asked to choose between alternative tours involving a single destination activity. The timing and duration both of the destination activity and the associated travel varied across scenarios. The fourth section discusses the empirical specification and estimation of the model and presents the estimation results. This uses an error-components formulation of the mixed multinomial logit model to account both for unobserved heterogeneity in tastes and for heteroskedascity and complex substitution patterns amongst activity alternatives. Particular attention is given to the use of advanced optimisation techniques needed to estimate the non-linear utility function expressing individuals’ timing and duration preferences.The fifth section discusses the significance of the results and their potential application to a number of practical transport planning problems including the prediction of user response to travel demand management policies and accessibility planning. The paper closes with some overall conclusions and a discussion of future research directions.