add.factors: add.factors Adds specific exposure factors to the 'pdm' data...

In HumanExposure/SHEDSDevel: The SHEDS-HT model for estimating human exposure to chemicals.

Description

add.factors Adds specific exposure factors to the pdm data table, which is output from the add.media function. Here, "specific" means taking into account the age, gender, season, and exposure media for each person.

Usage

add.factors(n, gen.f, med.f, exp.f, surf, pdm)

Arguments

n	Number of persons
gen.f	Non-media specific exposure factors as a data table. Output from the gen.factor.tables function.
med.f	Media specific exposure factors presented as a data table. Output from the med.factor.tables function.
exp.f	Distributional parameters for the exposure factors. Output of the exp.factors function.
surf	A list of surface media. Modified output of the read.media.file function.
pdm	A data table containing the pd data frame of physiological and demographic parameters for each theoretical person, and the dur array, which specifies the duration of exposure to each potential exposure medium for each person in pd. Output of the add.media function.

Details

The process of adding specific exposure factors to pdm involves multiple steps. First, w is determined, which is the number of general factors plus the product of the number of media-specific factors and the number of surface media. Air media do not have media specific factors in this version of SHEDS. An array, q, of uniform random samples is generated, with one row per person and w columns. A zero matrix, r, of the same size is defined. Once these matrices are defined, the media-specific factors are determined. Two nested loops over variable and surface type generate the values, which are stored in r. Next, another FOR loop determines the general factors. The p data set contains the age, gender, and season for each person. These two data sets are then merged. The evaluation of these factors is handled by the eval.factors function. One of the exposure factors is handwash.freq. This was also part of SHEDS-Multimedia, where it represented the mean number of hours in the day with hand washing events. An important aspect of that model was that because each person was followed longitudinally, the actual number of hand washes on each day varied from one day to the next. Because of this, the distribution for handwash.freq did not need to be restricted to integer values, as (for example) a mean of 4.5 per day is acceptable and achievable, while choosing integer numbers of hand washes each day. One of the early goals with SHEDS.HT was to attempt to reproduce selected results from SHEDS-Multimedia. Therefore, similar logic was built into the current model. The hand.washes variable is sampled from a distribution centered on handwash.freq, and then rounded to the nearest integer. The bath variable is another difficult concept. In theory, baths and showers are recorded on the activity diaries. In practice, the activity diaries were constructed from approximately 20 separate studies, some of which did not contain enough detail to identify separate bath or shower events. The result is that about half of all diaries record such events, but the true rate in the population is higher. The bath.p variable was created to address this. It represents the probability that a non bath/shower activity diary should actually have one. Therefore, if the diary has one, then SHEDS automatically has one. Otherwise, a binomial sample using bath.p as the probability is drawn. A bath/shower occurs unless both of these are zero. The effectiveness of hand washes or bath/shower at removing chemical from the skin is determined in the post.exposure function.

Value

pdmf A data set containing the pdm data table as well as media specific exposure factors, the number of baths taken, and the number of hand wash events occurring per day per person contained in pdm.

Author(s)

Kristin Isaacs, Graham Glen

See Also

eval.factors, post.exposure

HumanExposure/SHEDSDevel documentation built on Oct. 30, 2019, 6:49 p.m.