R/calc_doses.R

In arranhamlet/popvac_package: Generate population level vaccination data from a csv template.

#' Calculates the number of doses used from coverage.
#' 
#' @param vacc.cov The vaccination coverage 3d array.
#' @param year The year the vaccination campaign took place in.
#' @param country The ISO code of the vaccination campaign took place in.
#' @param adm1 The adm1 location the vaccination campaign took place in.
#' @param adm2 The adm2 location the vaccination campaign took place in.
#' @param doses The doses used in the vaccination campaign.
#' @param coverage The coverage of the vaccination campaign took place in.
#' @param agemin The minimum age targeted.
#' @param agemax The maximum age targeted.
#' @param skew This affects how vaccination campaigns are applied. If the skew is set to -1 then campaigns are applied to the whole population, regardless of prior vaccination status. If the skew is set to 0 then campaigns are applied only to the unvaccinated population. Finally, if the skew is set to 1 then the campaigns are applied to the same population as susbsequent campaigns.
#' @examples 
#' calc.doses(vacc.cov=campaigns,year=2016,country="AGO",adm1="AGO1",adm2=NA,doses=NA,coverage=.9,agemin=10,agemax=50,skew=0)
#' @keywords internal


calc.doses = function(vacc.cov,year,country=NA,adm1=NA,adm2=NA,doses=0,coverage=NA,agemin=0,agemax=100,skew=0) {
  
  if(!is.na(coverage)) {
    
    if(coverage>1) coverage<-coverage/100 # re-scale from percentage to proportion
    coverage<-min(coverage,1)
    
    if(!is.na(country)[1]) { x1<-which(dn1.0 %in% country)
    } else if(!is.na(adm1)[1]) { x1<-which(dn1.1 %in% adm1)
    } else if(!is.na(adm2)[1]) { x1<-which(dn1.2 %in% adm2)
    } else { stop("missing country/adm1/adm2 information.\n")
    }
    x2<-match(year+1,dn2) 
    x3.min<-agemin+1
    x3.max<-agemax+1
    tot.pop<-sum(pop1.adm2[x1,x2,x3.min:x3.max],na.rm=T)
    
    doses<-tot.pop*coverage
  }
  
  return(doses)
  
}