In Epiconcept-Paris/EpiCurve: Plot an Epidemic Curve

# library(methods)
library(timeDate)
#library(timeSeries)
#library(fBasics)
#library(plyr)
#library(jsonlite)
library(ggplot2)
#library(gridExtra)
library(EpiCurve)
library(dplyr)
library(scales)
library(knitr)

Cas 1: Données journalières agrégées avec factors

DF <- read.csv("cas_date_osea_jours.csv", stringsAsFactors=FALSE)
# DF <- DF[1, ]
# DF[1, 2] <- 1
#DF$date <- as.Date(DF$date)

# DF_V <- DF[DF[,"factor"] == "Validé", 1:2]
# DF_I <- DF[DF[,"factor"] == "Invalidé", 1:2]
DF2 <- DF %>%
  dplyr::group_by(date) %>%
  dplyr::summarise(value = sum(value)) %>%
  as.data.frame()

Tracé de la courbe épidémiologique

EpiCurve(DF2,
         date = "date",
         freq = "value",
         cutvar = "factor",
         period = "day",
         cutorder = c("Invalidé", "Validé"),
         color=c("#009900", "#000099"),
         ylabel="Nombre de cas",
         xlabel=sprintf("From %s To %s", min(DF$date), max(DF$date)),
         title = "Epidemic Curve",
         note = "Dayly epidemic curve of deseases")

Cas 2: Données hebdomadaires agrégées avec factors

DF <- read.csv2("cas_date_osea_semaines_02.csv", stringsAsFactors=FALSE, fileEncoding="latin1")
#DF <- DF[1:2, ]

kable(DF)

Tracé de la courbe épidémiologique

EpiCurve(DF,
         date = "date",
         freq = "value",
         cutvar = "factor",
         period = "week",
         cutorder = c( "Valid","Invalid"),
         color=c( "#990000","#009900"),
         ylabel="Nombre de cas",
         xlabel=sprintf("Du %s au %s", min(DF$date), max(DF$date)),
         title = "Courbe épidémique hebdomadaire\n")

Cas 3: Données hebdomadaires agrégées sans factors

DF <- read.csv2("cas_date_osea_semaines_02.csv", stringsAsFactors=FALSE) %>%
  select(-factor) %>%
  as.data.frame()
kable(DF)
#DF$date <- as.Date(DF$date)
DF <- DF[,-3]

Tracé de la courbe épidémiologique

EpiCurve(DF,
         date = "date",
         freq = "value",
         period = "week",
         color=c("#990000"),
         ylabel="Nombre de cas",
         xlabel=sprintf("Du %s au %s", min(DF$date), max(DF$date)),
         title = "Courbe épidémique\n")

Cas 4: Données mensuelles agrégées

DF <- read.csv2("cas_date_osea_mois_sansFactor.csv", stringsAsFactors=FALSE)
#DF <- DF[1, ]
kable(DF)
DF$date <- as.Date(paste(DF$date,"-01",sep=""))
# DF <-DF[-3,]

Tracé de la courbe épidémique

EpiCurve(DF,
         date = "date",
         freq = "value",
         period = "month",
         color=c("#990066"),
         ylabel="Nombre de cas",
         xlabel=sprintf("Du %s au %s", min(DF$date), max(DF$date)),
         title = "Courbe épidémique mensuelle\n")

Cas 5: Données mensuelles agrégées avec factors

DF <- read.csv2("cas_date_osea_mois.csv", stringsAsFactors=FALSE, fileEncoding="latin1")
#DF$date <- as.Date(paste(DF$date,"-01",sep=""))
#DF <- DF[1:2, ]
kable(DF)

Tracé de la courbe épidémique

EpiCurve(DF,
         date = "date",
         freq = "value",
         period = "month",
         cutvar = "factor",
         cutorder = c( "Valid","Invalid"),
         colors=c("#990000", "#009900"),
         ylabel="Nombre de cas",
         xlabel=sprintf("Du %s au %s", min(DF$date), max(DF$date)),
         title = "Courbe épidémique mensuelle avec factors\n")

Hourly

date <- seq(as.timeDate("2017-05-10 21:35:22"), as.timeDate("2017-05-12 06:15:12"), by="12 min")
val <- rep(1, length(date))
tri <- rep(c("Alive", "Died","Unknown"), length.out=length(date))
DF <- data.frame(date, val, tri)
names(DF) <- c("date","value", "tri")


EpiCurve(DF,
         date = "date",
         freq = "value",
         period = "hour",
         split = 4,
         cutvar = "tri",
         ylabel="Number of cases",
         xlabel=sprintf("Du %s au %s", min(as.Date(DF$date)), as.Date(max(DF$date))),
         title = "Epidemic Curve")