gdpm

The goal of gdpm is to provide the data from the General Department of Preventive Medicine (GDPM) of Vietnam.

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("epix-project/gdpm")

Example

library(gdpm)

The package contains epidemiological data in 29 epidemiological data frames, each data frame corresponding to one syndromic disease. For example, chickenpox:

chickenpox <-  getid(chickenpox)
head(chickenpox)
#>      province    month year incidence_chickenpox mortality_chickenpox
#> 5293 An Giang  January 1980                   NA                   NA
#> 5297 An Giang February 1980                   NA                   NA
#> 5298 An Giang    March 1980                    2                   NA
#> 5299 An Giang    April 1980                   NA                   NA
#> 5300 An Giang      May 1980                   NA                   NA
#> 5301 An Giang     June 1980                   NA                   NA

The data are expressed by the incidence or number of cases and mortality or the number of death per province, month and year. See below, the section on the getid function, for an illustration of the specificity of this function.

The structure of the data frame is:

str(chickenpox)
#> 'data.frame':    17784 obs. of  5 variables:
#>  $ province            : chr  "An Giang" "An Giang" "An Giang" "An Giang" ...
#>  $ month               : Ord.factor w/ 12 levels "January"<"February"<..: 1 2 3 4 5 6 7 8 9 10 ...
#>  $ year                : int  1980 1980 1980 1980 1980 1980 1980 1980 1980 1980 ...
#>  $ incidence_chickenpox: int  NA NA 2 NA NA NA 7 NA NA NA ...
#>  $ mortality_chickenpox: int  NA NA NA NA NA NA NA NA NA NA ...

Note that time is coded by the 2 variables year and month. The latter is a factor in which the coding of the levels follows their chronological order:

levels(chickenpox$month)
#>  [1] "January"   "February"  "March"     "April"     "May"      
#>  [6] "June"      "July"      "August"    "September" "October"  
#> [11] "November"  "December"

Head and tail of the data frame chickenpox:

head(chickenpox)
#>      province    month year incidence_chickenpox mortality_chickenpox
#> 5293 An Giang  January 1980                   NA                   NA
#> 5297 An Giang February 1980                   NA                   NA
#> 5298 An Giang    March 1980                    2                   NA
#> 5299 An Giang    April 1980                   NA                   NA
#> 5300 An Giang      May 1980                   NA                   NA
#> 5301 An Giang     June 1980                   NA                   NA
tail(chickenpox)
#>       province     month year incidence_chickenpox mortality_chickenpox
#> 45020 Vinh Phu      July 2017                   68                    0
#> 44620 Vinh Phu    August 2017                   21                    0
#> 4561  Vinh Phu September 2017                   30                    0
#> 45520 Vinh Phu   October 2017                   22                    0
#> 45420 Vinh Phu  November 2017                   49                    0
#> 44720 Vinh Phu  December 2017                   49                    0

Exporting to EPIPOI

Below is a function that queries the GDPM data from a disease x ("mumps", "measles", etc…) and exports the variable var (either "incidence" or "mortality") to an excel in a format compatible with EPIPOI:

export2epipoi <- function(x, var = "incidence") {
  require(gdpm)
  require(dplyr)
  require(tidyr)
  require(openxlsx)
  x %>%
    getid_() %>%
    select(year, month, province, starts_with(var)) %>%
    mutate(month = as.integer(month)) %>%
    arrange(year, month) %>%
    spread(province, 4) %>%
    write.xlsx(paste0(x, "_epipoi.xlsx"))
}

Its usage would be:

export2epipoi("mumps")