Rolling growth rates

Jens von Bergmann

library(CanCovidData)
library(dplyr)
library(ggplot2)

Download international country timelines.

country_data <- get_country_timeline_ecdc_jhs_data()

case_text_lookup <- c(
    "Confirmed" = "confirmed cases",
    "Deaths" = "deaths",
    "Active" = "active confirmed cases"
) 

country_base_colours <- setNames(c("black",RColorBrewer::brewer.pal(8,"Dark2")),
                                 c("Canada",
                                   "USA",
                                   "Germany",
                                   "France",
                                   "Italy",
                                   "UK",
                                   "Spain",
                                   "Switzerland",
                                   "South Korea"))

Simple growth rate graph

start_cutoff <- 100
window_width <- 7
metric <- "Confirmed"
case_text <- case_text_lookup[metric]

country_data %>%
  filter(Country %in% names(country_base_colours)) %>%
  mutate(total=!!as.name(metric)) %>%
  mutate(region=Country) %>%
  add_days_since(start_cutoff) %>%
  filter(d>=0) %>%
  growth_rate_graph(window_width) +
    scale_color_manual(values=country_base_colours) +
    labs(title=paste0("Countries COVID-19 ",case_text," growth rate"),
       color="Country",
       x=paste0("Days after ",start_cutoff," ",case_text," in rolling window"),
       caption="MountainMath, Data ECDC, JHS") 

Simple log-plot of cases

start_cutoff=100
metric="Confirmed"
case_text <- case_text_lookup[metric]

country_data %>%
  filter(Country %in% names(country_base_colours)) %>%
  mutate(region=factor(Country,levels=names(country_base_colours))) %>%
  mutate(total=!!as.name(metric)) %>%
  add_days_since(start_cutoff) %>%
  filter(d>=0) %>%
  group_by(region) %>%
  filter(max(d)>2) %>%
  total_graph() +
  scale_color_manual(values=country_base_colours,guide=FALSE) +
  labs(title=paste0("COVID-19 ",case_text," in select countries"),
       x=paste0("Days after reporting at least ",start_cutoff," ",case_text),
       y=paste0("Number of ",case_text," (log scale)"),
       caption="MountainMath, Data: ECDC, JHS") 

Simple log-plot of cases for provinces

provincial_data <- get_canada_official_provincial_data() 

provincial_data %>%
  mutate(total=!!as.name(metric)) %>%
  mutate(region=shortProvince) %>%
  add_days_since(50) %>%
  filter(d>=0) %>%
  group_by(region) %>%
  filter(max(d)>2) %>%
  total_graph() +
  scale_color_discrete(guide=FALSE) +
  #scale_color_manual(values=country_base_colours,guide=FALSE) +
  labs(title=paste0("COVID-19 ",case_text," in select countries"),
       colour=NULL,
       x=paste0("Days after reporting at least ",start_cutoff," ",case_text),
       y=paste0("Number of ",case_text," (log scale)"),
       caption="MountainMath, Data: Canada.ca")