---
title: "MSF Survey Dictionaries"
output: 
  rmarkdown::html_vignette:
    toc: true
vignette: >
  %\VignetteIndexEntry{MSF Survey Dictionaries}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  echo = FALSE
)
```

There are four MSF survey dictionaries available:

 - Retrospective mortality and access to care ("Mortality")
 - Malnutrition ("Nutrition") 
 - Vaccination coverage long form ("Vaccination_long")
 - Vaccination coverage short form ("vaccination_short")

> You can read more about the survey dictionaries at <https://r4epis.netlify.com/surveys>

# Retrospective mortality and access to care ("mortality")

## Variables in the dictionary

The Mortality dictionary contains definitions for `r nrow(epidict::msf_dict_survey("Mortality"))` variables:

```{r mortality, results="asis"}
library(epidict)
mortality <- msf_dict_survey("Mortality", compact = TRUE)
names_desc <- mortality[c("name", "label_english", "value_type")]
DT::datatable(names_desc)
```

## Option codes

The dictionaries are exported using option codes that can be translated to
human-readable format. This table shows how they are translated.

```{r mortality_values, results = "asis"}
mortality_codes <- tidyr::unnest(mortality, cols = options)[c("name", "value_type", "option_name", "option_label_english", "option_order_in_set")]
DT::datatable(mortality_codes)
```

# Malnutrition ("nutrition") 

## Variables in the dictionary

The Nutrition dictionary contains definitions for `r nrow(epidict::msf_dict_survey("Nutrition"))` variables:

```{r nutrition, results="asis"}
library(epidict)
nutrition <- msf_dict_survey("Nutrition", compact = TRUE)
names_desc <- nutrition[c("name", "label_english", "value_type")]
DT::datatable(names_desc)
```

## Option codes

The dictionaries are exported using option codes that can be translated to
human-readable format. This table shows how they are translated.

```{r nutrition_values, results = "asis"}
nutrition_codes <- tidyr::unnest(nutrition, cols = options)[c("name", "value_type", "option_name", "option_label_english", "option_order_in_set")]
DT::datatable(nutrition_codes)
```

# Vaccination Coverage ("vaccination_long" or "Vaccination_short")

## Variables in the dictionary
There are two Vaccination dictionaries - a long form and a short form.  
The Vaccination long dictionary contains definitions for `r nrow(epidict::msf_dict_survey("Vaccination_long"))` variables:

```{r vaccination_long, results="asis"}
library(epidict)
vaccination_long <- msf_dict_survey("Vaccination_long", compact = TRUE)
names_desc_long <- vaccination_long[c("name", "label_english", "value_type")]
DT::datatable(names_desc_long)
```

The Vaccination short dictionary contains definitions for `r nrow(epidict::msf_dict_survey("Vaccination_short"))` variables:

```{r vaccination_short, results="asis"}
library(epidict)
vaccination_short <- msf_dict_survey("Vaccination_short", compact = TRUE)
names_desc_short <- vaccination_short[c("name", "label_english", "value_type")]
DT::datatable(names_desc_short)
```


## Option codes

The dictionaries are exported using option codes that can be translated to
human-readable format. This table shows how they are translated.  

For vaccination long:  
```{r vaccination_long_values, results = "asis"}
vaccination_codes_long <- tidyr::unnest(vaccination_long, cols = options)[c("name", "value_type", "option_name", "option_label_english", "option_order_in_set")]
DT::datatable(vaccination_codes_long)
```

For vaccination short:  

```{r vaccination_short_values, results = "asis"}
vaccination_codes_short <- tidyr::unnest(vaccination_short, cols = options)[c("name", "value_type", "option_name", "option_label_english", "option_order_in_set")]
DT::datatable(vaccination_codes_short)
```


# Exploring the dictionaries

You can explore the excel-formatted dictionaries with `browseURL(system.file("extdata", "MSF-survey-dict.xlsx", package = "epidict"))`, but treat it as read-only.