Package: epidemics 0.4.0.9000

Rosalind Eggo

epidemics: Composable Epidemic Scenario Modelling

A library of compartmental epidemic models taken from the published literature, and classes to represent affected populations, public health response measures including non-pharmaceutical interventions on social contacts, non-pharmaceutical and pharmaceutical interventions that affect disease transmissibility, vaccination regimes, and disease seasonality, which can be combined to compose epidemic scenario models.

Authors:Pratik Gupte [aut, cph], Rosalind Eggo [aut, cph, cre], Edwin Van Leeuwen [aut, cph], Adam Kucharski [ctb, rev], Tim Taylor [ctb, rev], Banky Ahadzie [ctb], Alexis Robert [ctb], Hugo Gruson [rev], Joshua W. Lambert [rev], James M. Azam [rev], Alexis Robert [rev]

epidemics_0.4.0.9000.tar.gz
epidemics_0.4.0.9000.zip(r-4.7)epidemics_0.4.0.9000.zip(r-4.6)epidemics_0.4.0.9000.zip(r-4.5)
epidemics_0.4.0.9000.tgz(r-4.6-x86_64)epidemics_0.4.0.9000.tgz(r-4.6-arm64)epidemics_0.4.0.9000.tgz(r-4.5-x86_64)epidemics_0.4.0.9000.tgz(r-4.5-arm64)
epidemics_0.4.0.9000.tar.gz(r-4.7-arm64)epidemics_0.4.0.9000.tar.gz(r-4.7-x86_64)epidemics_0.4.0.9000.tar.gz(r-4.6-arm64)epidemics_0.4.0.9000.tar.gz(r-4.6-x86_64)
epidemics_0.4.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
epidemics/json (API)

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

Bug tracker:https://github.com/epiverse-trace/epidemics/issues

Pkgdown/docs site:https://epiverse-trace.github.io

On CRAN:

Conda:

decision-supportepidemic-modellingepidemic-simulationsepidemiologyepiverseinfectious-disease-dynamicsmodel-librarynon-pharmaceutical-interventionsrcpprcppeigenscenario-analysisvaccination

7.63 score 18 stars 63 scripts 20 exports 16 dependencies

Last updated from:516555d78a. Checks:2 ERROR, 11 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64ERROR174
linux-devel-x86_64ERROR182
source / vignettesOK280
linux-release-arm64OK203
linux-release-x86_64OK189
macos-release-arm64OK130
macos-release-x86_64OK221
macos-oldrel-arm64OK132
macos-oldrel-x86_64OK426
windows-develOK159
windows-releaseOK152
windows-oldrelOK183
wasm-releaseOK140

Exports:as.interventionas.vaccinationcombine_populationsepidemic_peakepidemic_sizegravity_contactinterventionis_contacts_interventionis_interventionis_populationis_rate_interventionis_vaccinationmodel_defaultmodel_diphtheriamodel_ebolamodel_vacamolenew_infectionsoutcomes_avertedpopulationvaccination

Dependencies:backportsBHcheckmatecinterpolateclidata.tabledeSolvedigestgluejsonliteodinR6RcppRcppEigenringwithr

Getting started with epidemic scenario modelling components
Prepare population and initial conditions | Note on social contacts data | Run epidemic model | Prepare data and visualise infections | References

Last update: 2026-06-05
Started: 2023-03-06

Getting started with modelling interventions targeting social contacts
Prepare population and initial conditions | Note on social contacts data | Prepare an intervention | Run epidemic model | Prepare data and visualise infections | References

Last update: 2026-06-05
Started: 2023-04-14

Modelling a diphtheria outbreak in a humanitarian camp setting
Modelling an outbreak with pre-existing immunity | Modelling an outbreak with changing population sizes | References

Last update: 2026-06-05
Started: 2024-03-14

Modelling in multiple populations
Combining two populations | Note on connectivity matrix | Combining two populations using a gravity model | Note on gravity connectivity matrix | Combining n populations using a gravity model

Last update: 2026-06-05
Started: 2025-04-29

Modelling intervention scenarios
Which model components can be passed as lists | Setting up the epidemic context | Creating a list of intervention sets | Output type for list intervention inputs | Combinations of intervention and vaccination scenarios | Modelling epidemic response scenarios with parameter uncertainty | Output type for intervention and parameter set combinations | Comparing response scenarios with parameter uncertainty | Counter-intuitive effects of time-limited interventions | References

Last update: 2026-06-05
Started: 2024-03-14

Modelling interventions that change infection parameters
Prepare population and initial conditions | Modelling an intervention on the transmission rate

Last update: 2026-06-05
Started: 2024-03-14

Modelling leaky vaccination and hospitalisation outcomes with Vacamole
Modifications for epidemics | Prepare population and initial conditions | Prepare a two dose vaccination campaign | Model epidemic using Vacamole | Visualise model outcomes | Vacamole ODE system for | References

Last update: 2026-06-05
Started: 2024-03-14

Modelling overlapping and sequential interventions targeting social contacts
Prepare population and initial conditions | Examine the baseline | Modelling overlapping interventions | School closures | Workplace closures | Combining interventions | Re-applying workplace closures

Last update: 2026-06-05
Started: 2024-03-14

Modelling parameter uncertainty
Obtaining estimates of disease transmission rate | Passing a vector of transmission rates | Output type for vector parameter inputs | Passing parameter sets | Passing vectors of epidemic duration | References

Last update: 2026-06-05
Started: 2024-05-07

Modelling responses to a stochastic Ebola virus epidemic
Prepare population and initial conditions | Prepare model parameters | Run epidemic model | Prepare data and visualise infections | Applying interventions that reduce transmission | Modelling the roll-out of vaccination | Modelling a multi-pronged ebola response | Details: Discrete-time Ebola virus disease model | Hospitalisation, funerals, and removal | References

Last update: 2026-06-05
Started: 2024-03-14

Modelling the effect of a vaccination campaign
Prepare population and initial conditions | Prepare a vaccination campaign

Last update: 2026-06-05
Started: 2023-04-14

Modelling time-dependence and seasonality in transmission dynamics
Setup and initial conditions | Defining a time-dependent function | Model with time-dependent transmission | Non-pharmaceutical interventions and time-dependence | Timing vaccination to prevent epidemic peaks

Last update: 2026-06-05
Started: 2024-03-14

Reducing parameters required for final size estimation
Different use cases of finalsize and epidemics | Converting scenarios between finalsize and epidemics | Prepare population and model parameters | Implementing vaccination in epidemics | Calculating individuals vaccinated in epidemic model | Implementing vaccination in finalsize | Consideration of computational speed | References

Last update: 2026-06-05
Started: 2023-10-25

Design principles for epidemics
Scope | Output | Package architecture | Design decisions | Epidemic modelling | ODE systems and models | Stochastic models | Classes | Function vectorisation | Miscellaneous decisions | Dependencies | Contribute

Last update: 2025-07-17
Started: 2024-03-11

Guide to developing epidemics features
Scope | A guide to package structure | Adding or removing model parameters | Modifying compartmental flows without changing compartments | Modelling births, immigration, and background mortality | Modelling sources of infectious individuals such as from zoonotic spillover_rate | Modelling waning immunity | Modifying which parameters can be time dependent | Group-specific infection parameters | Adding epidemiological compartments | Changing vaccination rates over time

Last update: 2025-07-17
Started: 2024-05-30