sim.n.vacc.sample.pop: Calculates the number of vaccinations each member of a sample...
In vacem: Vaccination Activities Coverage Estimation Model

Description Usage Arguments Details Value Note Examples

Calculates the number of vaccinations each member of a sample population would receive based upon probabilities generated from the campaigns descriptions and provided the @p rho and @p alpha values.

1 2	sim.n.vacc.sample.pop(obs, camps, rho, alpha, cond.on.accessible=FALSE, z, w, cdf.fun, ...)

`obs`	the synthetic population, i.e. a data frame with one row per observation and columns for @c date of observation and @c age of individual on that date; <i>Note: all ages should be in months</i>
`camps`	a data frame with one row per activity and columns providing the activity's @c date, targeted age range (@c age.low and @c age.high), size of targeted population (@c N) and the number of vaccine doses nominally distributed (@c v)
`rho`	the proportion of the population (scalar) that can be vaccinated, i.e @code1 - rho is the @e inaccessible portion of the general population.
`alpha`	the vaccination efficiency parameter (scalar) for the campaign; @codealpha = -inf implies perfect efficiency, @codealpha = 0 implies random efficiency; see note above
`cond.on.accessible`	a flag indicating whether the probabilities should be conditioned on the individual's inclusion in the accessible population, i.e. @p rho; the default is @c FALSE
`z`	the eligibility matrix for each individual/campaign pairing, i.e. @codez[i,j] = 1 if this individual @c i is eligible for campaign @c j, otherwise @codez[i,j] = 0; <i>Note: if @c z is @c NULL, then the eligibilty matrix is calculated from @p obs and @p camps parameters using @code z.matrix function.</i>
`w`	the weight matrix for each individual/campaign pairing, i.e. @code w[i,k] gives the probability of individual @c i receiving a routine vaccination in year @c k <i>Note: if @c w is @c NULL, then the weight matrix is calculated from @p obs, @p camps, @p cdf.fun and @p ... parameters using @code w.matrix function.</i>
`cdf.fun`	a cumulative distribution function (CDF) used to calculate the probability of routine vaccination based upon age, e.g. @code constant.post.9mo . <i>Note: this parameter is only required if the weight matrix, @p w, is <u>not</u> provided.</i>
`...`	any additional arguments to the @p cdf.fun, e.g. @c lambda <i>Note: this parameter is only required if the weight matrix, @p w, is not provided.</i>

TBD: Add details

a vector containing the number of vaccinations each individual in observation set, @p obs, would have received

@see z.matrix @see w.matrix @see nine.month.pointmass @see constant.post.9mo @see get.win.smooth.expected.mcmcres @see get.win.smooth.thresh.mcmcres

The inefficiency measure @p alpha is defined as the natural log of psi, i.e. @codepsi = e^alpha. @codepsi = 0 (@codealpha = -inf) represents perfect efficiency, i.e. when every dose results in an additional vaccinee. @codepsi = 1 (@codealpha = 0) represents random efficiency, i.e. when probability of any dose resulting in an additional vaccinee is independent of receiving a dose previously during the same campaign.

N <- 100
dates <- as.Date( c( "2005-05-01", "2007-07-02", "2009-09-03" ) )
sample.obs   <- make.sample.pop( N=N, age.low=0, age.high=25,
date=array(dates,dim=N) )
sample.camps <- data.frame( date=(dates - 3*DAYS.PER.MONTH),
N=(0.5*N), v=(0.5*N),
age.low=8, age.high=20, is.SIA=1 )

sim.n.vacc.sample.pop( sample.obs, sample.camps, rho=0.9, alpha=0,
cdf.fun=nine.month.pointmass )