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epiforecasts / covidregionaldata

An interface to subnational and national level COVID-19 data. For all countries supported, this includes a daily time-series of cases. Wherever available we also provide data on deaths, hospitalisations, and tests. National level data is also supported using a range of data sources as well as linelist data and links to intervention data sets.
https://epiforecasts.io/covidregionaldata/
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South Africa new reported cases around higher than Our World In Data/WHO #474

Open bquilty25 opened 6 months ago

bquilty25 commented 6 months ago

I have been using this package to plot the waves in South Africa from 2020-2023. When updating the figure I noticed that the number of new cases reported each day was substantially higher than it was previously, and compared to data downloaded from Our World In Data:

sa_cases

github-actions[bot] commented 6 months ago

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seabbs commented 6 months ago

Thanks Billy. As you may have noticed covidregionaldata hasn't had a patch in a fair while so issues may have crept in. Can you post a reprex of what you are doing to get data? In particular what data source are you using for SA?

bquilty25 commented 6 months ago

Hey Sam,

It was with default arguments, so I guess WHO (see below). I haven't tried downloading from source separately yet (https://covid19.who.int/WHO-COVID-19-global-data.csv), but just wanted to flag.

sa_dat <- get_national_data(countries = "South Africa") 

sa_plot <- read_csv("data/owid-covid-data.csv")%>%
  filter(iso_code == "ZAF") %>%
  mutate(date = as.Date(date)) %>%
  filter(date <= as.Date("2023-01-01")) %>% 
  ggplot(aes(x = date, y = new_cases))+
  geom_col(alpha = 0.75, aes(fill = "OWID/WHO"))+
  geom_point(data = sa_dat %>% 
               mutate(date = as.Date(date)) %>%
               filter(date <= as.Date("2023-01-01")),
             aes(x = date,y = cases_new, fill = "covidregionaldata"))+
  labs(x = "",y = "Daily reported cases")+
  scale_fill_brewer(palette = "Set2")

ggsave("results/sa_cases.png", width=200, height=100, units="mm", dpi=600, bg="white")
bquilty25 commented 6 months ago

Ah looks like it may be an issue with the source data:

sa_dat <- get_national_data(countries = "South Africa")

sa_plot <- read_csv("data/owid-covid-data.csv") %>%
  filter(iso_code == "ZAF") %>%
  mutate(date = as.Date(date)) %>%
  filter(date <= as.Date("2023-01-01")) %>%
  ggplot(aes(x = date, y = new_cases)) +
  geom_col(alpha = 0.75, aes(colour = "OWID/WHO")) +
  geom_point(
    data = sa_dat %>%
      mutate(date = as.Date(date)) %>%
      filter(date <= as.Date("2023-01-01")),
    aes(x = date, y = cases_new, colour = "covidregionaldata")
  ) +
  geom_line(
    data = read_csv("https://covid19.who.int/WHO-COVID-19-global-data.csv") %>%
      filter(Country == "South Africa") %>%
      filter(Date_reported <= as.Date("2023-01-01")),
    aes(x = Date_reported, y = New_cases, colour = "WHO")
  ) +
  labs(x = "", y = "Daily reported cases") +
  scale_colour_brewer(palette = "Set2")

sa_cases