tests/testthat/test-NYCdata.R

In weinbergerlab/ExcessILI: A package and RShiny app to examine excess ILI from syndromic surveillance data

# Open Rproj, which sets Working directory automatically)
library(MMWRweek)

test_that("NYC data is processed correctly", {
  combo1 <- readRDS("../../data/NYC_resp_ili_combo.rds")

  combo1$denom1 <- combo1$ili  / (combo1$ili.prop  + 0.01)
  combo1$denom2 <- combo1$resp / (combo1$resp.prop + 0.01)

  combo1$total.visits <- round((combo1$denom1 + combo1$denom2)/2) + 1

  combo1$state <- "NY"
  combo1 <- combo1[combo1$borough %in% c("Citywide", "Bronx", "Manhattan") &
                   combo1$agec %in% c("1", "2", "3", "4", "5"), ]

  combo1$agec <- as.character(combo1$agec)
  combo1$agec[combo1$agec == "1"] <- "i. u5y"
  combo1$agec[combo1$agec == "2"] <- "ii. 5-17y"
  combo1$agec[combo1$agec == "3"] <- "iii. 18-64y"
  combo1$agec[combo1$agec == "4"] <- "iv. 65+y"
  combo1$agec[combo1$agec == "5"] <- "v. All ages"

  excess_cases1 <-
    excessCases(ds = combo1,
                sub.statevar  = "borough",
                datevar       = "ddate", 
                agevar        = "agec",
                statevar      = "state",
                denom.var     = "total.visits",
                use.syndromes = c("ili", "resp"),
                adj.flu       = 'none')

  dashboardPlot(excess_cases1)

  ili2.resid <- sapply(excess_cases1[['ili']],
                       function(x) sapply(x, "[[", "resid1"), 
                       simplify = "array")

  unexplained.cases <-
    excessExtract(ds = excess_cases1,
                  syndrome = "ili",
                  extract.quantity = "unexplained.cases")

  excess.rr <-
    excessExtract(ds = excess_cases1,
                  syndrome = "ili",
                  extract.quantity = "resid1")


  par(mfrow=c(1,1))
  matplot(exp(excess.rr[,,1]), type='l')
  matplot(unexplained.cases[,-2,1], type='l')

  #Try out ts format package
  n.obs <- 10000
  set.seed(42)

  sim1 <-
    as.data.frame(matrix(NA, nrow=n.obs, ncol=5))

  names(sim1) <- c('state','date','agegrp','ili','resp')

  sim1$state<- c( rep('CT', times=n.obs*0.3),
                  rep("NY", times=n.obs*0.7) )

  sim1$agegrp <- sample(1:5, n.obs, replace=T)
  sim1$date   <- sample(seq.Date(from=as.Date('2019-01-01'),
                                 by='day',
                                 length.out=500), 
                        1000,
                        replace=T)

  sim1$ili  <- rbinom(n=n.obs, size=1, prob=0.05)
  sim1$resp <- rbinom(n=n.obs, size=1, prob=0.1)

  ts1 <- ts_format(line.list=sim1,
                   datevar='date',
                   agevar='agegrp',
                   statevar='state',
                   sub.statevar='none',
                   syndromes=c('ili','resp'))

  expect_true(is.data.frame(ts1))
})