In CDCgov/SaviR: ITF Situational Awareness and Visualization

knitr::opts_chunk$set(
  warning = FALSE,
  message = FALSE,
  echo = FALSE,
  eval = FALSE
)

# A minimal set of libraries needed for virtually all analyses
# Your script should add to this list.
library(SaviR)
library(dplyr)
library(tidyr)
library(here)
library(lubridate)
library(sf)
library(AzureStor)

# ---- Dates / Time stamps -----------------
run_time <- Sys.time()
run_date <- as.Date(run_time)

# Sunday of the current week
run_week_start <- floor_date(run_date, "week", week_start = 7)

# --- File paths -------------------------------------
routine_reports_root <- here()

# --- Variant data connection ----------------------
token <- AzureRMR::get_azure_token("https://storage.azure.com",
  tenant = Sys.getenv("AZURE_TENANT_ID"),
  app = Sys.getenv("AZURE_APP_ID"),
  password = Sys.getenv("AZURE_APP_SECRET")
)

con <- storage_container("https://edavsynapsedatalake.dfs.core.windows.net/ddphsis-cgh/", token=token)

# Cases/Deaths/Vax from only WHO source
df_who <- get_combined_table("WHO")

# Cases/Deaths/Vax from WHO + JHU for HK, Macau, Taiwan, and China
df_both <- get_combined_table("Both")

# Hospitalization data - to be added

# Testing data
df_testing <- get_testing_long()

# Create vaccination manufactuere data set
df_vax_man <- left_join(onetable, get_vax_manufacturers(), by = "id")

# Date that vaccine metrics were last updated
df_vax_dates <- get_vax_dates()

# Variant data
df_metadata<- storage_read_csv(con, "DGHT/ITF-SAVI/Sequencing/Outputs/metadata_allcountries.csv", show_col_types = FALSE)

CDCgov/SaviR documentation built on April 14, 2025, 7:46 a.m.