AMR/data-raw/AMR_vet.qmd

---
title: "AMR Goes Vet"
author: "Jason, Matthew, Javier, Matthijs"
date: "2024-02-20"
format: 
  html: 
    embed-resources: true
---

## Import WHONET data set

```{r, message=FALSE, warning=FALSE}
library(dplyr)
library(readr)
library(tidyr)

# WHONET version of 16th Feb 2024
whonet_breakpoints <- read_tsv("WHONET/Resources/Breakpoints.txt", na = c("", "NA", "-"),
                               show_col_types = FALSE, guess_max = Inf) %>%
  filter(GUIDELINES %in% c("CLSI", "EUCAST"))

dim(whonet_breakpoints)
```

# EDA of Animal Breakpoints

```{r}
whonet_breakpoints |>
  filter(BREAKPOINT_TYPE != "Human")
whonet_breakpoints |>
  filter(BREAKPOINT_TYPE != "Human") |>
  count(BREAKPOINT_TYPE)
whonet_breakpoints |>
  filter(BREAKPOINT_TYPE == "Animal")
```

### Count of all animal breakpoints

```{r}
whonet_breakpoints |>
  filter(BREAKPOINT_TYPE == "Animal") |>
  count(YEAR, HOST, REFERENCE_TABLE = gsub("VET[0-9]+ ", "", REFERENCE_TABLE)) |>
  pivot_wider(names_from = YEAR, values_from = n, values_fill = list(n = 0)) |>
  arrange(HOST, REFERENCE_TABLE)
```

### Cats only

```{r}
whonet_breakpoints |>
  filter(HOST == "Cats", YEAR >= 2021) |> 
  select(GUIDELINES, YEAR, TEST_METHOD, ORGANISM_CODE, R, S) |> 
  mutate(MO_NAME = AMR::mo_shortname(ORGANISM_CODE), .before = R) |> 
  as.data.frame()
```

### Site of infection in cats (2023)

```{r}
whonet_breakpoints |>
  filter(HOST == "Cats", YEAR == 2023) |> 
  mutate(MO = AMR::mo_shortname(ORGANISM_CODE),
         AB = AMR::ab_name(WHONET_ABX_CODE),
         SITE_OF_INFECTION = substr(SITE_OF_INFECTION, 1, 25)) |> 
  arrange(MO, AB) |> 
  select(MO, AB, SITE_OF_INFECTION) |> 
  as.data.frame()
```