AMR/data-raw/AMR_vet.qmd

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---
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()
```