In annecori/mRIIDSprocessData: Epidemiological forcasting using real-time data

library(dplyr)
library(magrittr)
library(stringr)
library(ggplot2)
library(purrr)

Introduction

given <- here::here("output", "MRIIDS Ebola Epi Curve Data.csv") %>%
    readr::read_csv(.)

p <- ggplot(given, aes(Date, Guinea)) + geom_point()
p <- p + geom_ribbon(aes(x = Projections_from,
                         ymin = ymin4.Guinea,
                         ymax = ymax4.Guinea),
                     alpha = 0.5)
p <- p + geom_line(aes(x = Projections_from, y = y4.Guinea))
p

p2 <- ggplot(given, aes(Date, Liberia)) + geom_point()
p2 <- p2 + geom_ribbon(aes(x = Projections_from,
                         ymin = ymin4.Liberia,
                         ymax = ymax4.Liberia),
                     alpha = 0.5)
p2 <- p2 + geom_line(aes(x = Projections_from, y = y4.Liberia))
p2

p3 <- ggplot(given, aes(Date, `Sierra Leone`)) + geom_point()
p3 <- p3 + geom_ribbon(aes(x = Projections_from,
                         ymin = `ymin4.Sierra Leone`,
                         ymax = `ymax4.Sierra Leone`),
                     alpha = 0.5)
p3 <- p3 + geom_line(aes(x = Projections_from, y = `y4.Sierra Leone`))
p3