R code for graph showing NZ lockdown vs. Cases

lockdownvsCases.R

# MoH is the ministry of Health all cases demographics csv file
# https://www.health.govt.nz/our-work/diseases-and-conditions/covid-19-novel-coronavirus/covid-19-data-and-statistics/covid-19-case-demographics#case-details
library(readr)
library(dplyr)
library(ggplot2)
library(ggthemes)
library(lubridate)

# you need to provide csv name
file_name <- "covid_cases_2021-09-14.csv"
update_date = as.Date(gsub("[^1234567890-]","",file_name))
# update date needed because any current day info is partial
# rather than complete

MoH <- read_csv(file_name, 
                col_types = cols(
                  `Report Date` = col_date(format = ""),
                  `Case Status` = col_character(),
                  Sex = col_character(),
                  `Age group` = col_character(),
                  DHB = col_character(),
                  `Overseas travel` = col_character(),
                  Historical = col_character()))

complete_sequence <- data.frame(case_date = seq.Date(from=as.Date("2020-02-1"), 
                                                     to=as.Date("2021-09-13"), 
                                                     by="day"), n=0)
NZexAuck <- MoH %>% 
  filter(`Overseas travel` != "Yes",
         !(DHB %in% c("Managed Isolation & Quarantine",
                  "Auckland","Counties Manukau",
                  "Waitemata")),
         is.na(Historical)) %>%
  count(case_date = `Report Date`) %>%
  bind_rows(complete_sequence) %>%
  arrange(desc(n)) %>%
  group_by(case_date) %>%
  slice(1) %>%
  ungroup() %>%
  mutate(n = ifelse(n=0,0,1), region="NZ excluding Auckland")
  
NZexAuck <- MoH %>% 
  filter(`Overseas travel` != "Yes",
         !(DHB %in% c("Managed Isolation & Quarantine",
                      "Auckland","Counties Manukau",
                      "Waitemata")),
         is.na(Historical)) %>%
  count(case_date = `Report Date`) %>%
  bind_rows(complete_sequence) %>%
  arrange(desc(n)) %>%
  group_by(case_date) %>%
  slice(1) %>%
  ungroup() %>%
  mutate(Legend = ifelse(n==0,"No new cases","Some new cases"), region="NZ excluding\nAuckland") %>% select(-n)

Auckland <- MoH %>% 
  filter(`Overseas travel` != "Yes",
         DHB %in% c("Auckland","Counties Manukau",
                      "Waitemata"),
         is.na(Historical)) %>%
  count(case_date = `Report Date`) %>%
  bind_rows(complete_sequence) %>%
  arrange(desc(n)) %>%
  group_by(case_date) %>%
  slice(1) %>%
  ungroup() %>%
  mutate(Legend = ifelse(n==0,"No new cases","Some new cases"), region="Auckland NZ") %>% select(-n)

bind_rows(Auckland, NZexAuck) %>% 
  mutate(Legend=factor(Legend), region=factor(region)) %>%
  ggplot(aes(x=case_date, y=as.numeric(region), colour=Legend)) + 
  geom_segment(aes(yend=as.numeric(region)+.1, xend=case_date))

# for my purposes Lockdown is any day containing 2 or more minutes of level 3 or 4
lockdown1NZ <- data.frame(case_date = seq.Date(from=as.Date("2020-03-26"), 
                                               to=as.Date("2020-05-13"), 
                                               by="day"), Legend="Lockdown", stringsAsFactors = FALSE)
lockdownAU1 <- data.frame(case_date = seq.Date(from=as.Date("2020-03-26"), 
                                               to=as.Date("2020-05-13"), 
                                               by="day"), Legend="Lockdown", stringsAsFactors = FALSE)
lockdownAU2 <- data.frame(case_date = seq.Date(from=as.Date("2020-08-12"), 
                                               to=as.Date("2020-08-30"), 
                                               by="day"), Legend="Lockdown", stringsAsFactors = FALSE)
lockdownAU3 <- data.frame(case_date = seq.Date(from=as.Date("2021-02-28"), 
                                               to=as.Date("2021-03-07"), 
                                               by="day"), Legend="Lockdown", stringsAsFactors = FALSE)
lockdown2NZ <- data.frame(case_date = seq.Date(from=as.Date("2021-08-18"), 
                                              to=as.Date("2021-09-07"), 
                                              by="day"), Legend="Lockdown", stringsAsFactors = FALSE)
lockdownAU4 <- data.frame(case_date = seq.Date(from=as.Date("2021-08-18"), 
                                               to=as.Date("2021-09-13"), 
                                               by="day"), Legend="Lockdown", stringsAsFactors = FALSE)
Freedom <- data.frame(case_date = seq.Date(from=as.Date("2020-02-01"), 
                                               to=as.Date("2021-09-13"), 
                                               by="day"), Legend="No Lockdown", stringsAsFactors = FALSE)

lockauck <- bind_rows(lockdownAU1, lockdownAU2, lockdownAU3, lockdownAU4, Freedom) %>%
  arrange(case_date, Legend) %>% group_by(case_date) %>% slice(1) %>% ungroup() %>%
  mutate(region = "Auckland NZ Lockdown")

locknz <- bind_rows(lockdown1NZ, lockdown2NZ, Freedom) %>%
  arrange(case_date, Legend) %>% group_by(case_date) %>% slice(1) %>% ungroup() %>%
  mutate(region = "NZ excluding\nAuckland Lockdown")

grf <- bind_rows(Auckland, NZexAuck, lockauck, locknz) %>% 
  mutate(Legend=factor(Legend), region=factor(region)) %>%
  ggplot(aes(x=case_date, y=as.numeric(region), colour=Legend)) + 
  geom_segment(aes(yend=as.numeric(region)+.5, xend=case_date), size=1.5) +
  scale_colour_colorblind(name="Legend:") +
  annotate("text", y=1.6, x=as.Date("2020-03-01"), label="Auckland Days with New Covid Cases", hjust=0) + 
  annotate("text", y=2.6, x=as.Date("2020-03-01"), label="Auckland Days with Lockdown (Level 4 or Level 3)", hjust=0)  +
  annotate("text", y=3.6, x=as.Date("2020-03-01"), label="NZ ex. Auckland Days with New Covid Cases", hjust=0) + 
  annotate("text", y=4.6, x=as.Date("2020-03-01"), label="NZ ex. Auckland Days with Lockdown (Level 4 or Level 3)", hjust=0) +
  labs(x="Date", title="NZ lockdown days and new cases days, Feb 2020 to present",
       caption ="data source: govt.nz") +
  guides(colour = guide_legend(override.aes = list(size=3)))

davidise_graph(grf)