Estimate the Unit-Wide Probability of COVID-19
c(person(given = "Eric",
family = "Brown",
role = c("aut", "cre"),
email = "eb@ericebrown.com",
comment = c(ORCID = "0000-0002-1575-2606")),
person(given = "Wei",
family = "Wang",
role = c("ctb"))
)
We propose a method to estimate the probability of an
undetected case of COVID-19 in a defined setting, when a given number of
people have been exposed, with a given pretest probability of having
COVID-19 as a result of that exposure. Since we are interested in undetected
COVID-19, we assume no person has developed symptoms (which would warrant
further investigation) and that everyone was tested on a given day, and all
tested negative.
Eric Brown [aut, cre] (<https://orcid.org/0000-0002-1575-2606>),
Wei Wang [ctb]

Subnational Data for the Covid-19 Outbreak
c(person(given = "Sam Abbott",
role = c("aut", "cre"),
email = "sam.abbott@lshtm.ac.uk",
comment = c(ORCID = "0000-0001-8057-8037")),
person("Katharine", "Sherratt",
email = "katharine.sherratt@lshtm.ac.uk",
role = c("aut"),
comment = c(ORCID = "0000-0003-4413-453X")),
person("Jonnie", "Bevan",
email = "jonnie.bevan@tessella.com",
role = c("aut")),
person("Hamish", "Gibbs",
email = "Hamish.Gibbs@lshtm.ac.uk",
role = c("aut"),
comment = c(ORCID = "0000-0003-4413-453X")),
person("Joel", "Hellewell",
email = "joel.hellewell@lshtm.ac.uk",
role = c("aut"),
comment = c(ORCID = "0000-0003-2683-0849")),
person("James", "Munday",
email = "james.munday@lshtm.ac.uk",
role = c("aut")),
person("Patrick", "Barks",
email = "patrick.barks@epicentre.msf.org",
role = c("ctb")),
person("Paul", "Campbell",
email = " paul.campbell@epicentre.msf.org",
role = c("aut")),
person("Flavio", "Finger",
email = "flavio.finger@epicentre.msf.org",
role = c("ctb"),
comment = c(ORCID = "0000-0002-8613-5170")),
person("Sebastian", "Funk",
email = "sebastian.funk@lshtm.ac.uk",
role = c("aut")))
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. Data sources included:
WHO <https://dashboards-dev.sprinklr.com/data/9043/global-covid19-who-gis.json>, <https://covid19.who.in>;
ACAPS interventions <https://data.humdata.org/dataset/acaps-covid19-government-measures-dataset>;
patient linelist: <https://github.com/beoutbreakprepared/nCoV2019>),
regional data (Afghanistan: <https://data.humdata.org/dataset/afghanistan-covid-19-statistics-per-province>;
Belgium: <https://epistat.wiv-isp.be/covid>; Brazil: <https://github.com/wcota/covid19br>;
Canada: <https://health-infobase.canada.ca/>; Colombia: <https://github.com/danielcs88/colombia_covid-19>;
Germany: <https://npgeo-corona-npgeo-de.hub.arcgis.com/datasets/dd4580c810204019a7b8eb3e0b329dd6_0>;
India: <https://api.covid19india.org/>; Italy: <https://github.com/pcm-dpc/COVID-19>;
Russia: <https://github.com/grwlf/COVID-19_plus_Russia>;  UK: <https://coronavirus.data.gov.uk>,
<https://github.com/tomwhite/covid-19-uk-data>; USA: <https://github.com/nytimes/covid-19-data>),
and geocoding data (Colombia: <https://en.wikipedia.org/wiki/ISO_3166-2:CO>; Russia: <https://en.wikipedia.org/wiki/ISO_3166-2:RU>).
readr, dplyr, tibble, purrr, stringr, magrittr, memoise,
lubridate, tidyr, httr, yaml, readxl, xml2, rvest, jsonlite,
countrycode
Sam Abbott [aut, cre] (<https://orcid.org/0000-0001-8057-8037>),
Katharine Sherratt [aut] (<https://orcid.org/0000-0003-4413-453X>),
Jonnie Bevan [aut],
Hamish Gibbs [aut] (<https://orcid.org/0000-0003-4413-453X>),
Joel Hellewell [aut] (<https://orcid.org/0000-0003-2683-0849>),
James Munday [aut],
Patrick Barks [ctb],
Paul Campbell [aut],
Flavio Finger [ctb] (<https://orcid.org/0000-0002-8613-5170>),
Sebastian Funk [aut]