The package was developed since Jan. 2020 and originally hosted on GuangchuangYu/nCov2019. This repo contains an up-to-date version with data from new sources (from worldometers and JHUCSSE) and new data types (vaccine and therapeutics data).
- Latest data of coronavirus cases: worldometers
- Historical data of coronavirus cases : JHUCSSE
- Vaccine data: raps.org
- Therapeutics data: raps.org
Fetching data using API provided by disease.sh
Find out more on the vignette vignette.
Guangchuang YU and Tianzhi Wu
If you use nCov2019, please cite the following article:
Wu T, Hu E, Ge X*, Yu G*. 2021. nCov2019: an R package for studying the COVID-19 coronavirus pandemic. PeerJ 9:e11421 https://doi.org/10.7717/peerj.11421
Get the development version from github:
## install.packages("remotes")
remotes::install_github("YuLab-SMU/nCov2019")res <- query()to query 5 types of statistics- global summary,
- latest data
- historical data
- vaccine data
- therapeutic data
x <- res$globalto access global summary datasummary(x)will return global overviewx$affectedCountrieswill return total affected countries,(other 20 types of statistics is available)
y <- res$latestory <- res$historicalto accesslatestorhistoricaldatay["global"]will return all countries' statisticsy[country]will return country level statistics- For countries in
China,UK,Australia,Canada,Denmark,FranceandNetherlands, provincial data is also available andy[country,province]will return statistics data of the selected province
z <- res$vaccineory <- res$therapeuticsto accessvaccineortherapeuticdatasummary(z)will return the summary of their trial phasez["all"]will return all candidatez[ID="id1"]each vaccine or therapeutics candidate has an id, this will return detail description of the selected candidate (e.g., "id1")
plot()to present data on mapdashboard()to open Shiny app dashboard
Run the script example.R in R using source("example.R"), will produce the following figure:
