Function reference • sars2pack

Overview of the package
`sars2pack-package`	sars2pack: Easy access to and use of iconic COVID-19 data resource
Data resources Data resources that are accessible from this package are somewhat arbitrarily divided into general groupings. For details of each dataset, click on the link. For an overview of data resources, see the Datasets vignette.
Case/test tracking data resources Access datasets that provide insight into how much and where people are moving and how those metrics change over time.
`align_to_baseline()`	Align case tracking locations (for example) to a common baseline
`beoutbreakprepared_data()`	Individual-level data contributed from around the world
`bulk_estimate_Rt()`	Estimate R(t) for all locales in a case-tracking dataset
`combined_us_cases_data()`	gather US states confirmed cases from multiple sources
`coronadatascraper_data()`	Time series cases, hospitalizations, and testing from Corona Data Scraper project
`covidtracker_data()`	US State-level data including test results
`ecdc_data()`	Daily COVID-19 deaths and confirmed cases from the European CDC
`estimate_Rt()`	Estimate R(t) from cumulative case time series
`jhu_data()`	Global COVID-19 data from JHU CSSEGIS
`nytimes_county_data()` `nytimes_state_data()`	United States county and state level data from the New York Times
`owid_data()`	Our world in data worldwide cases and tests
`plot_epicurve()`	Plot a (set of) epidemic curve(s)
`test_and_trace_data()`	Contact tracing counts for United States from testandtrace.com
`usa_facts_data()`	United States state and county level data from USAFacts
`who_cases()`	Global case tracking from the World Health Organization (WHO)
Mobility data resources Access datasets that provide insight into how much and where people are moving and how those metrics change over time.
`apple_mobility_data()`	Access Apple mobility data
`descartes_mobility_data()`	Get US daily mobility data from Descartes Labs
`google_mobility_data()`	Google mobility dataset
projections
`cdc_aggregated_projections()`	Projected deaths from COVID-19 models
healthcare systems and capacity
`kff_icu_beds()`	Kaiser Family Foundation US County-level ICU bed data
`us_hospital_details()`	US hospital dataset
genetic lineage
`cov_glue_lineage_data()`	COVID GLUE datasets
`cov_glue_newick_data()`	COVID GLUE Newick tree
`cov_glue_snp_lineage()`	COVID GLUE snp to lineage and taxon map
Non-pharmaceutical interventions Datasets that catalog details of NPI in the US and Internationally.
`acaps_government_measures_data()`	ACAPS government measures catalogs worldwide COVID-19 government interventions
`coronanet_government_response_data()`	CoronaNet government policy response database
`government_policy_timeline()`	Longitudinal tracking of government interventions to combat COVID-19
`us_state_distancing_policy()`	United States social distancing policies for COVID-19
Line lists Line lists are collections of individual cases and their characteristics.
`beoutbreakprepared_data()`	Individual-level data contributed from around the world
`cov_glue_lineage_data()`	COVID GLUE datasets
`cov_glue_newick_data()`	COVID GLUE Newick tree
Social and economic impacts These datasets help to understand the economic and societal impacts of COVID and associated policy interventions.
`acaps_secondary_impact_data()`	ACAPS secondary effects of COVID-19
`econ_tracker_consumer_spending_city_data()` `econ_tracker_consumer_spending_county_data()` `econ_tracker_consumer_spending_state_data()` `econ_tracker_consumer_spending_national_data()`	United States Consumer Spending
`econ_tracker_employment_city_data()` `econ_tracker_employment_county_data()` `econ_tracker_employment_state_data()` `econ_tracker_employment_national_data()`	United States Employment Data from Econ Tracker and Opportunity Insights
`econ_tracker_unemp_city_data()` `econ_tracker_unemp_county_data()` `econ_tracker_unemp_state_data()` `econ_tracker_unemp_national_data()`	Econ Tracker Unemployment Insurance Claims
`us_county_health_rankings()`	United States county health rankings
Excess deaths ‘Excess mortality’ refers to the difference between deaths from all causes during the pandemic and the historic seasonal average. For many jurisdictions for which data are available, this figure is higher than the official Covid-19 fatalities that are published by governments each day. While not all of these deaths are necessarily attributable to the disease, it does leave a number of unexplained deaths that suggests that the official figures of deaths attributed may significant undercounts of the pandemic’s impact.
`cdc_excess_deaths()`	US CDC excess deaths by week from 2018 to present
`economist_excess_deaths()`	Excess deaths during covid for US and selected countries
`financial_times_excess_deaths()`	Excess deaths tracking by Financial Times
Plotting and visualization These are special purpose helper plots for sars2pack. Note that most are simply wrappers around ggplot2 and friends.
`align_to_baseline()`	Align case tracking locations (for example) to a common baseline
`plot_epicurve()`	Plot a (set of) epidemic curve(s)
Additional datasets These datasets include miscellaneous enrichment datasets for joining with COVID-19 datasets or represent one-off data types.
`acaps_government_measures_data()`	ACAPS government measures catalogs worldwide COVID-19 government interventions
`acaps_secondary_impact_data()`	ACAPS secondary effects of COVID-19
`apple_mobility_data()`	Access Apple mobility data
`beoutbreakprepared_data()`	Individual-level data contributed from around the world
`cci_us_vaccine_data()`	Vaccine allocations and administrations in the United States
`cdc_aggregated_projections()`	Projected deaths from COVID-19 models
`cdc_excess_deaths()`	US CDC excess deaths by week from 2018 to present
`cdc_social_vulnerability_index()`	US CDC Social Vulnerability Index
`coronadatascraper_data()`	Time series cases, hospitalizations, and testing from Corona Data Scraper project
`coronanet_government_response_data()`	CoronaNet government policy response database
`cov_glue_lineage_data()`	COVID GLUE datasets
`cov_glue_newick_data()`	COVID GLUE Newick tree
`cov_glue_snp_lineage()`	COVID GLUE snp to lineage and taxon map
`covidtracker_data()`	US State-level data including test results
`descartes_mobility_data()`	Get US daily mobility data from Descartes Labs
`ecdc_data()`	Daily COVID-19 deaths and confirmed cases from the European CDC
`econ_tracker_consumer_spending_city_data()` `econ_tracker_consumer_spending_county_data()` `econ_tracker_consumer_spending_state_data()` `econ_tracker_consumer_spending_national_data()`	United States Consumer Spending
`econ_tracker_employment_city_data()` `econ_tracker_employment_county_data()` `econ_tracker_employment_state_data()` `econ_tracker_employment_national_data()`	United States Employment Data from Econ Tracker and Opportunity Insights
`econ_tracker_unemp_city_data()` `econ_tracker_unemp_county_data()` `econ_tracker_unemp_state_data()` `econ_tracker_unemp_national_data()`	Econ Tracker Unemployment Insurance Claims
`economist_excess_deaths()`	Excess deaths during covid for US and selected countries
`financial_times_excess_deaths()`	Excess deaths tracking by Financial Times
`google_mobility_data()`	Google mobility dataset
`government_policy_timeline()`	Longitudinal tracking of government interventions to combat COVID-19
`jhu_data()`	Global COVID-19 data from JHU CSSEGIS
`jhu_us_data()`	US counties COVID-19 data from JHU CSSEGIS
`kff_icu_beds()`	Kaiser Family Foundation US County-level ICU bed data
`nytimes_county_data()` `nytimes_state_data()`	United States county and state level data from the New York Times
`oecd_unemployment_data()`	OECD International unemployment statistics
`owid_data()`	Our world in data worldwide cases and tests
`param_estimates_published()`	Published parameter estimates from the literature
`test_and_trace_data()`	Contact tracing counts for United States from testandtrace.com
`us_county_geo_details()`	United States county-level geographic details
`us_county_health_rankings()`	United States county health rankings
`us_healthcare_capacity()`	United States healthcare system capacity by provider
`us_hospital_details()`	US hospital dataset
`us_state_distancing_policy()`	United States social distancing policies for COVID-19
`usa_facts_data()`	United States state and county level data from USAFacts
`who_cases()`	Global case tracking from the World Health Organization (WHO)
`CRF_468_China`	serial interval values fo 468 COVID-19 cases in 93 cities in China
`add_incidence_column()`	Add daily incidence to cumulative case counts data.frame
`align_to_baseline()`	Align case tracking locations (for example) to a common baseline
`available_datasets()` `dataset_details()`	list and detail available sars2pack datasets
`bulk_estimate_Rt()`	Estimate R(t) for all locales in a case-tracking dataset
`cdc_us_linelist_data()`	COVID line list for United States from the CDC
`column_summaries()`	convenience function for summarizing data.frame columns
`combined_us_cases_data()`	gather US states confirmed cases from multiple sources
`country_metadata()`	Get basic country data
`datasets_to_sql()`	Build a data warehouse of all datasets in one line
`demo_simulation()`	set up a simulation as demonstrated by John C Mallery
`econ_tracker_county_geo()` `econ_tracker_city_geo()`	Econ tracker information
`enriched_jhu_data()`	Get enriched jhu dataset enriched with country-level metadata
`estimate_R()`	estimate R0
`estimate_Rt()`	Estimate R(t) from cumulative case time series
`get_series()`	supersimple series extraction
`google_search_trends_data()`	Google search trends for COVID-19 and illness-related terms
`growth_rate_ratio()`	Estimate the growth rate ratio
`integer_to_fips()` `county_to_state_fips()`	convert an integer to fips
`jhu_data_to_excel()`	Create +/- write excel format of enriched JHU global data
`ls_github()`	do an ls of a github repo
`make_cumulative_events()`	generic cumulative_events generator
`mar19df`	march 19 result of CSSEGISandData/COVID-19/ time series data retrieval as data.frame
`mar19dt`	march 19 result of CSSEGISandData/COVID-19/ time series data retrieval as data.table
`min_bic_2020_05_20`	a statewide collection of best AR/MA model orders
`plot2(<R0.sR>)`	version of R0:::plot.R0.sR that does not use dev.new
`plot2()`	generic for simpler plotter for R0.sR
`plot_epicurve()`	Plot a (set of) epidemic curve(s)
`plot_series()`	supersimple series plotter
`plotfit2(<R0.sR>)`	version of R0:::plotfit.R0.sR that does not use dev.new
`plotfit2()`	generic for simpler plotter for plotfit for R0.sR
`sars2pack-package`	sars2pack: Easy access to and use of iconic COVID-19 data resource
`si_cens_G`	MCMC-based model for SI, Gamma family used for censored-data likelihood
`si_cens_L`	MCMC-based model for SI, lognormal family used for censored-data likelihood
`si_cens_W`	MCMC-based model for SI, Weibull family used for censored-data likelihood
`si_pos_G`	MCMC-based model for SI, Gamma family used for positive-data likelihood
`si_pos_L`	MCMC-based model for SI, lognormal family used for positive-data likelihood
`si_pos_W`	MCMC-based model for SI, Weibull family used for positive-data likelihood
`trim_leading_values()`	trim leading repeats of a given value from a vector
`us_population_details()`	Retrieve United States Population data from the US Census Bureau
`world_population_data()`	World population details from United Nations
Additional functionality Find additional functionality related to analysis, plotting, and data included with the package. These extra datasets include miscellaneous enrichment datasets for joining with COVID-19 datasets or represent one-off data types.
`CRF_468_China`	serial interval values fo 468 COVID-19 cases in 93 cities in China
`acaps_government_measures_data()`	ACAPS government measures catalogs worldwide COVID-19 government interventions
`acaps_secondary_impact_data()`	ACAPS secondary effects of COVID-19
`add_incidence_column()`	Add daily incidence to cumulative case counts data.frame
`align_to_baseline()`	Align case tracking locations (for example) to a common baseline
`apple_mobility_data()`	Access Apple mobility data
`available_datasets()` `dataset_details()`	list and detail available sars2pack datasets
`bulk_estimate_Rt()`	Estimate R(t) for all locales in a case-tracking dataset
`cci_us_vaccine_data()`	Vaccine allocations and administrations in the United States
`cdc_aggregated_projections()`	Projected deaths from COVID-19 models
`cdc_excess_deaths()`	US CDC excess deaths by week from 2018 to present
`cdc_social_vulnerability_index()`	US CDC Social Vulnerability Index
`cdc_us_linelist_data()`	COVID line list for United States from the CDC
`column_summaries()`	convenience function for summarizing data.frame columns
`combined_us_cases_data()`	gather US states confirmed cases from multiple sources
`coronadatascraper_data()`	Time series cases, hospitalizations, and testing from Corona Data Scraper project
`coronanet_government_response_data()`	CoronaNet government policy response database
`country_metadata()`	Get basic country data
`cov_glue_snp_lineage()`	COVID GLUE snp to lineage and taxon map
`covidtracker_data()`	US State-level data including test results
`datasets_to_sql()`	Build a data warehouse of all datasets in one line
`demo_simulation()`	set up a simulation as demonstrated by John C Mallery
`descartes_mobility_data()`	Get US daily mobility data from Descartes Labs
`ecdc_data()`	Daily COVID-19 deaths and confirmed cases from the European CDC
`econ_tracker_consumer_spending_city_data()` `econ_tracker_consumer_spending_county_data()` `econ_tracker_consumer_spending_state_data()` `econ_tracker_consumer_spending_national_data()`	United States Consumer Spending
`econ_tracker_employment_city_data()` `econ_tracker_employment_county_data()` `econ_tracker_employment_state_data()` `econ_tracker_employment_national_data()`	United States Employment Data from Econ Tracker and Opportunity Insights
`econ_tracker_unemp_city_data()` `econ_tracker_unemp_county_data()` `econ_tracker_unemp_state_data()` `econ_tracker_unemp_national_data()`	Econ Tracker Unemployment Insurance Claims
`economist_excess_deaths()`	Excess deaths during covid for US and selected countries
`econ_tracker_county_geo()` `econ_tracker_city_geo()`	Econ tracker information
`enriched_jhu_data()`	Get enriched jhu dataset enriched with country-level metadata
`estimate_R()`	estimate R0
`estimate_Rt()`	Estimate R(t) from cumulative case time series
`financial_times_excess_deaths()`	Excess deaths tracking by Financial Times
`get_series()`	supersimple series extraction
`google_mobility_data()`	Google mobility dataset
`google_search_trends_data()`	Google search trends for COVID-19 and illness-related terms
`government_policy_timeline()`	Longitudinal tracking of government interventions to combat COVID-19
`growth_rate_ratio()`	Estimate the growth rate ratio
`integer_to_fips()` `county_to_state_fips()`	convert an integer to fips
`jhu_data()`	Global COVID-19 data from JHU CSSEGIS
`jhu_data_to_excel()`	Create +/- write excel format of enriched JHU global data
`jhu_us_data()`	US counties COVID-19 data from JHU CSSEGIS
`kff_icu_beds()`	Kaiser Family Foundation US County-level ICU bed data
`ls_github()`	do an ls of a github repo
`make_cumulative_events()`	generic cumulative_events generator
`mar19df`	march 19 result of CSSEGISandData/COVID-19/ time series data retrieval as data.frame
`mar19dt`	march 19 result of CSSEGISandData/COVID-19/ time series data retrieval as data.table
`min_bic_2020_05_20`	a statewide collection of best AR/MA model orders
`nytimes_county_data()` `nytimes_state_data()`	United States county and state level data from the New York Times
`oecd_unemployment_data()`	OECD International unemployment statistics
`owid_data()`	Our world in data worldwide cases and tests
`param_estimates_published()`	Published parameter estimates from the literature
`plot2(<R0.sR>)`	version of R0:::plot.R0.sR that does not use dev.new
`plot2()`	generic for simpler plotter for R0.sR
`plot_epicurve()`	Plot a (set of) epidemic curve(s)
`plot_series()`	supersimple series plotter
`plotfit2(<R0.sR>)`	version of R0:::plotfit.R0.sR that does not use dev.new
`plotfit2()`	generic for simpler plotter for plotfit for R0.sR
`sars2pack-package`	sars2pack: Easy access to and use of iconic COVID-19 data resource
`si_cens_G`	MCMC-based model for SI, Gamma family used for censored-data likelihood
`si_cens_L`	MCMC-based model for SI, lognormal family used for censored-data likelihood
`si_cens_W`	MCMC-based model for SI, Weibull family used for censored-data likelihood
`si_pos_G`	MCMC-based model for SI, Gamma family used for positive-data likelihood
`si_pos_L`	MCMC-based model for SI, lognormal family used for positive-data likelihood
`si_pos_W`	MCMC-based model for SI, Weibull family used for positive-data likelihood
`test_and_trace_data()`	Contact tracing counts for United States from testandtrace.com
`trim_leading_values()`	trim leading repeats of a given value from a vector
`us_county_geo_details()`	United States county-level geographic details
`us_county_health_rankings()`	United States county health rankings
`us_healthcare_capacity()`	United States healthcare system capacity by provider
`us_hospital_details()`	US hospital dataset
`us_population_details()`	Retrieve United States Population data from the US Census Bureau
`us_state_distancing_policy()`	United States social distancing policies for COVID-19
`usa_facts_data()`	United States state and county level data from USAFacts
`who_cases()`	Global case tracking from the World Health Organization (WHO)
`world_population_data()`	World population details from United Nations
`beoutbreakprepared_data()`	Individual-level data contributed from around the world
`cov_glue_lineage_data()`	COVID GLUE datasets
`cov_glue_newick_data()`	COVID GLUE Newick tree

Reference

Overview of the package

Data resources

Case/test tracking data resources

Mobility data resources

projections

healthcare systems and capacity

genetic lineage

Non-pharmaceutical interventions

Line lists

Social and economic impacts

Excess deaths

Plotting and visualization

Additional datasets

Additional functionality