Package: EpiEstim 2.4

Anne Cori

EpiEstim: Estimate Time Varying Reproduction Numbers from Epidemic Curves

Tools to quantify transmissibility throughout an epidemic from the analysis of time series of incidence as described in Cori et al. (2013) <doi:10.1093/aje/kwt133> and Wallinga and Teunis (2004) <doi:10.1093/aje/kwh255>.

Authors:Anne Cori [aut, cre], Simon Cauchemez [ctb], Neil M. Ferguson [ctb], Christophe Fraser [ctb], Elisabeth Dahlqwist [ctb], P. Alex Demarsh [ctb], Thibaut Jombart [ctb], Zhian N. Kamvar [ctb], Justin Lessler [ctb], Shikun Li [ctb], Jonathan A. Polonsky [ctb], Jake Stockwin [ctb], Robin Thompson [ctb], Rolina van Gaalen [ctb], Rebecca Nash [ctb], Sangeeta Bhatia [ctb], Jack Wardle [ctb], Andrea Brizzi [ctb]

EpiEstim_2.4.tar.gz
EpiEstim_2.4.zip(r-4.5)EpiEstim_2.4.zip(r-4.4)EpiEstim_2.4.zip(r-4.3)
EpiEstim_2.4.tgz(r-4.4-any)EpiEstim_2.4.tgz(r-4.3-any)
EpiEstim_2.4.tar.gz(r-4.5-noble)EpiEstim_2.4.tar.gz(r-4.4-noble)
EpiEstim_2.4.tgz(r-4.4-emscripten)EpiEstim_2.4.tgz(r-4.3-emscripten)
EpiEstim.pdf |EpiEstim.html
EpiEstim/json (API)
NEWS

# Install 'EpiEstim' in R:
install.packages('EpiEstim', repos = c('https://epiverse-connect.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/mrc-ide/epiestim/issues

Datasets:
  • Flu1918 - Data on the 1918 H1N1 influenza pandemic in Baltimore.
  • Flu2009 - Data on the 2009 H1N1 influenza pandemic in a school in Pennsylvania.
  • Measles1861 - Data on the 1861 measles epidemic in Hagelloch, Germany.
  • MockRotavirus - Mock data on a rotavirus epidemic.
  • SARS2003 - Data on the 2003 SARS epidemic in Hong Kong.
  • Smallpox1972 - Data on the 1972 smallpox epidemic in Kosovo
  • covid_deaths_2020_uk - Data on the 2020-2022 SARS-CoV-2 epidemic in the UK.
  • flu_2009_NYC_school - Data on the 2009 H1N1 influenza pandemic in a school in New York city
  • mers_2014_15 - Data on Middle East Respiratory Syndrome (MERS) in Saudi Arabia.

On CRAN:

10.98 score 94 stars 7 packages 1.2k scripts 1.1k downloads 30 exports 56 dependencies

Last updated 3 months agofrom:238d43548d. Checks:OK: 3 NOTE: 3 ERROR: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 29 2024
R-4.5-winERROROct 29 2024
R-4.5-linuxNOTEOct 29 2024
R-4.4-winNOTEOct 29 2024
R-4.4-macNOTEOct 29 2024
R-4.3-winOKOct 29 2024
R-4.3-macOKOct 29 2024

Exports:aggregate_incbackimpute_Icheck_cdt_samples_convergencecoarse2estimcompute_lambdacompute_si_cutoffcompute_t_mindefault_mcmc_controlsdefault_priorsdiscr_siDiscrSIdraw_epsilondraw_Restimate_advantageestimate_Restimate_R_aggestimate_R_plotsEstimateRfirst_nonzero_incidget_shape_epsilonget_shape_R_flatinit_mcmc_paramsmake_configmake_mcmc_controloverall_infectivityOverallInfectivityprocess_I_multivariantsample_posterior_Rwallinga_teunisWT

Dependencies:abindaweekclicoarseDataToolscodacolorspacecpp11distcretedplyrepitrixfansifarverfitdistrplusgenericsggplot2gluegridExtragtableincidenceisobandlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmcmcMCMCpackmgcvmunsellnlmepatchworkpillarpkgconfigplyrpurrrquantregR6RColorBrewerRcppreshape2rlangscalessodiumSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

Alternative software for estimating the reproduction number

Rendered fromalternative_software.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2023-04-20
Started: 2022-04-01

Dealing with missed generations of infections with EpiEstim

Rendered fromEpiEstim_backimputation.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2024-08-30
Started: 2024-08-30

EpiEstim: a demonstration

Rendered fromshort_demo.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2024-08-30
Started: 2021-04-09

EpiEstim for aggregated incidence data

Rendered fromEpiEstim_aggregated_data.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2023-07-03
Started: 2022-12-07

EpiEstim Vignette

Rendered fromfull_EpiEstim_vignette.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2024-08-30
Started: 2021-04-09

MV-EpiEstim

Rendered fromMV_EpiEstim_vignette.Rmdusingknitr::rmarkdownon Oct 29 2024.

Last update: 2024-08-30
Started: 2021-11-26

Readme and manuals

Help Manual

Help pageTopics
Aggregating daily incidence to longer time windowsaggregate_inc
Impute unobserved generations of infectionbackimpute_I
Checking convergence of an MCMC chain by using the Gelman-Rubin algorithmcheck_cdt_samples_convergence
Link coarseDataTools and EpiEstimcoarse2estim
Compute the overall infectivitycompute_lambda
Index before which at most a given probability mass is capturedcompute_si_cutoff
Compute the smallest index at which joint estimation should startcompute_t_min
Data on the 2020-2022 SARS-CoV-2 epidemic in the UK.covid_deaths_2020_uk
Set default for MCMC controldefault_mcmc_controls
Set default for Gamma priorsdefault_priors
Discretized Generation Time Distribution Assuming A Shifted Gamma Distributiondiscr_si
Function to ensure compatibility with EpiEstim versions <2.0DiscrSI
Draw epsilon from marginal posterior distributiondraw_epsilon
Draw R from marginal posterior distributiondraw_R
Jointly estimate the instantaneous reproduction number for a reference pathogen/strain/variant and the relative transmissibility of a "new" pathogen/strain/variantestimate_advantage
Estimated Instantaneous Reproduction Numberestimate_R
Estimated Instantaneous Reproduction Number from coarsely aggregated dataestimate_R_agg
Wrapper for plot.estimate_Restimate_R_plots
Function to ensure compatibility with EpiEstim versions <2.0EstimateR
Get the first day of non-zero incidence across all variants and locations.first_nonzero_incid
Data on the 2009 H1N1 influenza pandemic in a school in New York cityflu_2009_NYC_school
Data on the 1918 H1N1 influenza pandemic in Baltimore.Flu1918
Data on the 2009 H1N1 influenza pandemic in a school in Pennsylvania.Flu2009
Precompute shape of posterior distribution for epsilonget_shape_epsilon
Precompute shape of posterior distribution for Rget_shape_R_flat
init_mcmc_params Finds clever starting points for the MCMC to be used to estimate the serial interval, e.g. when using option 'si_from_data' in 'estimate_R'init_mcmc_params
Set and check parameter settings of estimate_Rmake_config
make_mcmc_control Creates a list of mcmc control parameters to be used in 'config$mcmc_control', where 'config' is an argument of the 'estimate_R' function. This is used to configure the MCMC chain used to estimate the serial interval within 'estimate_R' (with method "si_from_data").make_mcmc_control
Data on the 1861 measles epidemic in Hagelloch, Germany.Measles1861
Data on Middle East Respiratory Syndrome (MERS) in Saudi Arabia.mers_2014_15
Mock data on a rotavirus epidemic.MockRotavirus
Overall Infectivity Due To Previously Infected Individualsoverall_infectivity
Function to ensure compatibility with EpiEstim versions <2.0OverallInfectivity
Plot outputs of estimate_rplot.estimate_R
Process incidence input for multivariant analyses with estimate_advantageprocess_I_multivariant
sample from the posterior R distributionsample_posterior_R
Data on the 2003 SARS epidemic in Hong Kong.SARS2003
Data on the 1972 smallpox epidemic in KosovoSmallpox1972
Estimation of the case reproduction number using the Wallinga and Teunis methodwallinga_teunis
Function to ensure compatibility with EpiEstim versions <2.0WT