Package: smidm 1.0

Sonja Jäckle

smidm: Statistical Modelling for Infectious Disease Management

Statistical models for specific coronavirus disease 2019 use cases at German local health authorities. All models of Statistical modelling for infectious disease management 'smidm' are part of the decision support toolkit in the 'EsteR' project. More information is published in Sonja Jäckle, Rieke Alpers, Lisa Kühne, Jakob Schumacher, Benjamin Geisler, Max Westphal "'EsteR' – A Digital Toolkit for COVID-19 Decision Support in Local Health Authorities" (2022) <doi:10.3233/SHTI220799> and Sonja Jäckle, Elias Röger, Volker Dicken, Benjamin Geisler, Jakob Schumacher, Max Westphal "A Statistical Model to Assess Risk for Supporting COVID-19 Quarantine Decisions" (2021) <doi:10.3390/ijerph18179166>.

Authors:Max Westphal [aut], Stefanie Grimm [aut], Sonja Jäckle [aut, cre], Rieke Alpers [aut], Hong Phuc Truong [aut], Amelie Lucker [ctb], Fraunhofer MEVIS [cph], Fraunhofer ITWM [cph]

smidm_1.0.tar.gz
smidm_1.0.tar.gz(r-4.5-noble)smidm_1.0.tar.gz(r-4.4-noble)
smidm_1.0.tgz(r-4.4-emscripten)smidm_1.0.tgz(r-4.3-emscripten)
smidm.pdf |smidm.html
smidm/json (API)

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

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.44 score 11 scripts 612 downloads 11 exports 18 dependencies

Last updated 2 years agofrom:55c28e6f41. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 06 2024
R-4.5-linuxOKDec 06 2024

Exports:calculate_likelihood_negative_testscalculate_posterior_no_infectionscalculate_prior_infectionsget_expected_total_infectionsget_incubation_day_distributionget_infection_densityget_infectiousness_densityget_misc_infection_densityget_serial_interval_densityget_test_sensitivitiespredict_future_infections

Dependencies:clidplyrextraDistrfansigenericsgluelifecyclemagrittrpillarpkgconfigR6Rcpprlangtibbletidyselectutf8vctrswithr

Statistical Modelling for Infectious Disease Management - Contacts

Rendered fromcontacts.Rmdusingknitr::rmarkdownon Dec 06 2024.

Last update: 2022-08-27
Started: 2022-08-27

Statistical Modelling for Infectious Disease Management - Contagious period

Rendered fromcontagious_period.Rmdusingknitr::rmarkdownon Dec 06 2024.

Last update: 2022-08-27
Started: 2022-08-27

Statistical Modelling for Infectious Disease Management - Infection period

Rendered frominfection_period.Rmdusingknitr::rmarkdownon Dec 06 2024.

Last update: 2022-08-27
Started: 2022-08-27

Statistical Modelling for Infectious Disease Management - Prediction of future infections in a group

Rendered fromfuture_infections.Rmdusingknitr::rmarkdownon Dec 06 2024.

Last update: 2022-08-27
Started: 2022-08-27

Statistical Modelling for Infectious Disease Management - Risk assessment group quarantine

Rendered fromrisk_assessment_group_quarantine.Rmdusingknitr::rmarkdownon Dec 06 2024.

Last update: 2022-08-27
Started: 2022-08-27

Readme and manuals

Help Manual

Help pageTopics
Overall likelihoodcalculate_likelihood_negative_tests
Likelihood Kcalculate_likelihood_negative_tests_k
Negative analysis probabilitycalculate_posterior_no_infections
A priori probability of further Infectionscalculate_prior_infections
Generate data extendedgenerate_data_extended
Expected number of total symptomatic infectionsget_expected_total_infections
Vector of day-specific probabilities of disease outbreakget_incubation_day_distribution
Dataframe with dates and probability of infectionget_infection_density
Dataframe with dates and infectiousness probabilityget_infectiousness_density
Dataframe with dates and probability of infectionget_misc_infection_density
Dataframe with dates and contact symptom begin probabilityget_serial_interval_density
Generate infoget_test_sensitivities
One more primary a priori probabilityp_onePrimaryMore
Prediction of future infections per daypredict_future_infections