This package compiles a series of publicly available disease outbreak data. Data can be provided as R objects (loaded automatically when loading the package), text files distributed alongside the package, or functions generating a dataset.
The following R datasets are currently available:
data(package="outbreaks")
| Item | Title | | :---------------------------------- | :------------------------------------------------------------------------------ | | covid19_england_nhscalls_2020 | Potential COVID19 cases reported through NHS pathways | | dengue_fais_2011 | Dengue on the island of Fais, Micronesia, 2011 | | dengue_yap_2011 | Dengue on the Yap Main Islands, Micronesia, 2011 | | ebola_kikwit_1995 | Ebola in Kikwit, Democratic Republic of the Congo, 1995 | | ebola_sierraleone_2014 | Ebola in Sierra Leone, 2014 | | ebola_sim | Simulated Ebola outbreak | | ebola_sim_clean | Simulated Ebola outbreak | | fluH7N9_china_2013 | Influenza A H7N9 in China, 2013 | | influenza_england_1978_school | Influenza in a boarding school in England, 1978 | | measles_hagelloch_1861 | Measles in Hagelloch, Germany, 1861 | | mers_korea_2015 | Middle East respiratory syndrome in South Korea, 2015 | | nipah_malaysia | Nipah in Malaysia and Sinagapore, 1997-1999 | | norovirus_derbyshire_2001_school | Norovirus in a primary school in Derbyshire, England, 2001 | | rabies_car_2003 | Dog Rabies in Central African Republic, 2003-2012 | | s_enteritidis_pt59 | Salmonella Enteritidis PT59 outbreak | | sars_canada_2003 | Severe Acute Respiratory Syndrome in Canada, 2003 | | sarscov2_who_2019 | SARS-CoV-2 World Health Organization Situation Reports 2019 Outbreak (COVID-19) | | smallpox_abakaliki_1967 | Smallpox in Abakaliki, Nigeria, 1967 | | varicella_sim_berlin | Simulated Varicella outbreak | | zika_girardot_2015 | Zika in Girardot, Colombia, 2015 | | zika_sanandres_2015 | Zika in San Andres, Colombia, 2015 | | zika_yap_2007 | Zika on the Yap Main Islands, Micronesia, 2007 |
Data sets in outbreaks
To install the current stable, CRAN version of the package, type:
install.packages("outbreaks")
To benefit from the latest features and bug fixes, install the development, github version of the package using:
devtools::install_github("reconverse/outbreaks")
Note that this requires the package devtools installed.
We will try to create a better repository and data submission system at
a later stage. The purpose of the current package is only to share
examplar datasets during the hackathon. Acceptable forms are: - as a
.RData
files in the data/
folder (recommended) - as a text file in
the inst/
folder - as a function loading/assembling/simulating a
dataset
We use the lower case throughout, and snake_case (using underscores) to
separate words for the files and dataset names, so that for a RData
object, a new dataset woud look like: `my_new_data_RData’. Try using
informative names, typically using the disease first. Whenever
available, order fields as: 1. disease: mandatory 2. location:
optional 3. year: optional 4. sim: mandatory if this is a simulated
dataset; otherwise data is assume to be an actual outbreak 5. other:
(any other relevant information)
Maintainer: Finlay Campbell (finlaycampbell93@gmail.com)
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