The preparation processes are shown in . Five sub-processes are represented below.
Preparation process (see for data sources).
4.1 Process 1: selecting the activity types
The selection of the activity types to be used in the ISTAM depends strongly on the activity data (i.e. the ACT data source). Some types of activity such as telecommuting were neglected as they were not explicitly related to contact between individuals (and, thus, are not important for infectious disease transmission). Some other activity types needed to be included even if their percentage contribution was small because these activities bring individuals into contact intimately (such as health care). Note that trip activity was neglected in this study to simplify the research and also because of the limited availability of related data sources. All activity types that occur more than 1% in the average time distribution are listed in .
All activity types that take more than 1% in the average time distribution.
4.2 Process 2: selecting the ABs
Specific objects in this application (e.g. different land use units inside one PC6) were classified to reflect the relations between the types of individuals' activities and the types of land use. It was assumed that, within one PC6, no more than one school or industry could exist. Individuals visit certain ABs such as offices, industry and farms for work. However, for certain other ABs such as post offices and banks, some individuals work there while others visit for service. All AB types and corresponding activity types within the ISTAM for this application are listed in .
AB types within ISTAM for application to Eemnes. (The number in brackets is the expected number of staff working in this type of work place while asterisk means one and only one AB of this type within the current PC6.)
4.3 Process 3: building the city
Land use data record the numbers of individuals engaged in every vocation. It was assumed that the expected size of a work place (generated from land use data) of a given vocation type was constant across all PC6 zones of Eemnes. Then, from the number of individuals engaged in a given vocation within each PC6, the number of corresponding work places was computed. For example, if the number of individuals engaged in the health care vocation within a given PC6 is 10, and the expected size of a health care work place is set to be five, then it follows that there should be two health care facilities within this PC6.
4.4 Process 4: synthesizing the population
As the synthesized household data were grid based and, therefore, not compatible with PC6 statistical data, all households within all grid cells of Eemnes were pooled together and then each household with its family members were allocated to the PC6 zones of Eemnes as follows.
Firstly, all individuals were classified according to age structure (). Different sub-classifications, and subsequently simulation of activities, were applied to the above four classifications. It is believed that daily activity patterns are related to individuals' socioeconomic characteristics such as household role, lifestyle and life cycle (Vaughn et al. 1997
; Kulkarni & McNally 2000
). In the study by Janelle et al. (1998)
, the whole population was divided into 14 role groups based on dimensions of gender, marital status, employment, child care, residential tenure and mobility.
Age structure for the population of Eemnes.
In this research, the following dimensions of information were selected: (i) the average working (or study) hours per week (0, 0 hours; 1, 1–15 hours; 2, 16–30 hours; 3, 31–45 hours; 4, more than 45 hours), role in household (1, no family; 2, single parent with children; 3, child with single parent; 4, parent in couple without children; 5, parent in couple with children; 6, child in couple with children), car availability (1, no car; 2, yes and always; 3, yes and sometimes) and day of the week (Sunday to Saturday). Based on these four dimensions, both children between 11 and 18 years and adults in the population were further sub-classified, and their corresponding activity patterns were generated from the activity survey data. If the survey data could not generate a corresponding activity pattern from a specific value of these four dimensions, a replacement activity pattern was assigned at a more aggregated level, i.e. the number of dimensions was reduced. The sequence of the dimensions to be excluded was car availability index, role in household and working (study) hours. For one individual, her/his daily activity pattern was further classified according to the seven weekdays.
4.5 Process 5: assigning activity patterns to individuals
Within the ISTAM, after the time unit is set (15 and 30
min are in common use), one day is divided into a number of units. Thus, the objective of simulating a person's daily activity is actually to assign these time units with certain activity types.
For each value from the combination of the four dimensions mentioned in the §4.4
, aggregated data on the daily distribution of time spent on the main types of activity were computed from the activity survey data (if corresponding data exist). Then, these aggregated data were saved into the database for further use. This activity pattern included not only the average duration for every possible activity but also the probability of the time of commencement for certain activities. Three types of activities were dealt with as exceptions: study time (applicable to children, assuming all children go to school during school hours); working time (applicable to all adult workers, assuming all workers go to work during working hours); and sleeping time. These three types of time were assigned to the individuals as personal properties during the generation of the whole population. For the daily activity of one person of one week day, firstly, these three special types of activities were fixed. Then, from the beginning to the end of the time sequence, the vacant time units were assigned to activity types by the probability weights from the assigned activity pattern in relation to the sociodemographic segment. For spatial location, for every person, her/his household and work place (or school) were fixed from the beginning, and other locations (ABs) were selected randomly (or the spatially closest one was selected). At every time step, individuals can move between different locations.
For both children between 11 and 18 years and adults, their activity patterns were assigned according to their properties in the four dimensions. After these processes, the whole population of this city was built and all types of AB were distributed to all PC6 zones. shows the spatial distribution of households and schools at PC6 levels for the whole of Eemnes city. It is clear that most households are within the boundary of the city centre; so in the following sections the spatial display is zoomed within the boundary of the city centre to highlight the area where most contacts between individuals could occur. shows the spatial distribution of the ABs for work (includes office, industry, farm and school), relaxation (includes sports, social and relaxation places) and maintenance (includes shop, post office, bank and health care places) at PC6 levels.
Spatial distribution of households and schools at PC6 levels. Solid black circles indicate PC6 with a school.
Spatial distribution of ABs for work, relaxation and maintenance at PC6 levels.