Debian Med Project
Help us to see Debian used by medical practitioners and biomedical researchers! Join us on the Salsa page.
Summary
Epidemiology
데바안 Med 역학 관련 패키지

이 메타패키지는 역학 연구에 유용한 도구를 설치할 것 입니다. 통계 조사를 위해 GNU R 데이타 언어를 사용하는 여러 패키지들. "A short introduction to R for Epidemiology (역학을 위한 R에 대한 간략한 소개)" 논문을 http://staff.pubhealth.ku.dk/%7Ebxc/Epi/R-intro.pdf 에서 읽어보는 것이 좋습니다.

Description

For a better overview of the project's availability as a Debian package, each head row has a color code according to this scheme:

If you discover a project which looks like a good candidate for Debian Med to you, or if you have prepared an unofficial Debian package, please do not hesitate to send a description of that project to the Debian Med mailing list

Links to other tasks

Debian Med Epidemiology packages

Official Debian packages with high relevance

python3-seirsplus
Models of SEIRS epidemic dynamics with extensions
Versions of package python3-seirsplus
ReleaseVersionArchitectures
bookworm1.0.9-1all
trixie1.0.9-2all
bullseye0.1.4+git20200528.5c04080+ds-2all
sid1.0.9-2all
Popcon: 0 users (0 upd.)*
Versions and Archs
License: DFSG free
Git

This package implements generalized SEIRS infectious disease dynamics models with extensions that model the effect of factors including population structure, social distancing, testing, contact tracing, and quarantining detected cases.

Notably, this package includes stochastic implementations of these models on dynamic networks.

python3-torch
Tensors and Dynamic neural networks in Python (Python Interface)
Versions of package python3-torch
ReleaseVersionArchitectures
bookworm1.13.1+dfsg-4amd64,arm64,ppc64el,s390x
bullseye1.7.1-7amd64,arm64,armhf,ppc64el,s390x
sid2.5.0+dfsg-1amd64,arm64,ppc64el,riscv64,s390x
upstream2.5.1
Popcon: 126 users (28 upd.)*
Newer upstream!
License: DFSG free
Git

PyTorch is a Python package that provides two high-level features:

(1) Tensor computation (like NumPy) with strong GPU acceleration (2) Deep neural networks built on a tape-based autograd system

You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend PyTorch when needed.

This is the CPU-only version of PyTorch (Python interface).

Please cite: Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai and Soumith Chintala:
Registry entries: SciCrunch 
python3-treetime
inference of time stamped phylogenies and ancestral reconstruction (Python 3)
Versions of package python3-treetime
ReleaseVersionArchitectures
buster0.5.3-1all
bullseye0.8.1-1all
sid0.11.1-1all
trixie0.11.1-1all
bookworm0.9.4-1all
upstream0.11.4
Popcon: 0 users (2 upd.)*
Newer upstream!
License: DFSG free
Git

TreeTime provides routines for ancestral sequence reconstruction and the maximum likelihoo inference of molecular-clock phylogenies, i.e., a tree where all branches are scaled such that the locations of terminal nodes correspond to their sampling times and internal nodes are placed at the most likely time of divergence.

TreeTime aims at striking a compromise between sophisticated probabilistic models of evolution and fast heuristics. It implements GTR models of ancestral inference and branch length optimization, but takes the tree topology as given. To optimize the likelihood of time-scaled phylogenies, treetime uses an iterative approach that first infers ancestral sequences given the branch length of the tree, then optimizes the positions of unconstraine d nodes on the time axis, and then repeats this cycle. The only topology optimization are (optional) resolution of polytomies in a way that is most (approximately) consistent with the sampling time constraints on the tree. The package is designed to be used as a stand-alone tool or as a library used in larger phylogenetic analysis workflows.

Features

  • ancestral sequence reconstruction (marginal and joint maximum likelihood)
  • molecular clock tree inference (marginal and joint maximum likelihood)
  • inference of GTR models
  • rerooting to obtain best root-to-tip regression
  • auto-correlated relaxed molecular clock (with normal prior)

This package provides the Python 3 module.

Registry entries: Bioconda 
r-cran-covid19us
cases of COVID-19 in the United States prepared for GNU R
Versions of package r-cran-covid19us
ReleaseVersionArchitectures
trixie0.1.9-1all
bookworm0.1.9-1all
bullseye0.1.7-1all
sid0.1.9-1all
Popcon: 4 users (4 upd.)*
Versions and Archs
License: DFSG free
Git

This package provides a GNU R wrapper around the 'COVID Tracking Project API' https://covidtracking.com/api/ providing data on cases of COVID-19 in the US.

r-cran-diagnosismed
medical diagnostic test accuracy analysis toolkit
Versions of package r-cran-diagnosismed
ReleaseVersionArchitectures
bookworm0.2.3-7all
bullseye0.2.3-7all
stretch0.2.3-4all
trixie0.2.3-7all
sid0.2.3-7all
buster0.2.3-6all
jessie0.2.3-3all
Debtags of package r-cran-diagnosismed:
devellang:r
fieldmedicine
interfacecommandline
roleprogram
useanalysing
Popcon: 6 users (4 upd.)*
Versions and Archs
License: DFSG free
Git

DiagnosisMed is a GNU R package to analyze the accuracy of data from diagnostic tests evaluating health conditions. It was designed to be used by health professionals. This package helps estimating sensitivity and specificity from categorical and continuous test results including some evaluations of indeterminate results, or compare different categorical tests, and estimate reasonable cut-offs of tests and display it in a way commonly used by health professionals. No graphical interface is available yet.

r-cran-epi
GNU R epidemiological analysis
Versions of package r-cran-epi
ReleaseVersionArchitectures
buster2.32-2amd64,arm64,armhf,i386
bullseye2.43-1amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
bookworm2.47-1amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
jessie1.1.67-4amd64,armel,armhf,i386
stretch2.7-1amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x
sid2.53-1amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x
trixie2.53-1amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x
upstream2.56
Debtags of package r-cran-epi:
fieldmedicine
interfacecommandline
roleprogram
Popcon: 35 users (27 upd.)*
Newer upstream!
License: DFSG free
Git

Functions for demographic and epidemiological analysis in the Lexis diagram, i.e. register and cohort follow-up data, including interval censored data and representation of multistate data. Also some useful functions for tabulation and plotting. Contains some epidemiological datasets.

The Epi package is mainly focused on "classical" chronic disease epidemiology. The package has grown out of the course Statistical Practice in Epidemiology using R (see http://www.pubhealth.ku.dk/~bxc/SPE).

There is A short introduction to R for Epidemiology available at http://staff.pubhealth.ku.dk/%7Ebxc/Epi/R-intro.pdf Beware that the pages 38-120 of this is merely the manual pages for the Epi package.

Epi is not the only R-package for epidemiological analysis, a package with more affinity to infectious disease epidemiology is the epitools package which is also evailable in Debian.

Epi is used in the Department of Biostatistics of the University of Copenhagen.

Please cite: Martyn Plummer and Bendix Carstensen: Lexis: An R Class for Epidemiological Studies with Long-Term Follow-Up. Journal of Statistical Software 38(5):1-12 (2011)
r-cran-epibasix
GNU R Elementary Epidemiological Functions
Versions of package r-cran-epibasix
ReleaseVersionArchitectures
bullseye1.5-2all
stretch1.3-2amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x
jessie1.3-1amd64,armel,armhf,i386
buster1.5-1all
sid1.5-2all
trixie1.5-2all
bookworm1.5-2all
Debtags of package r-cran-epibasix:
fieldmedicine
interfacecommandline
roleprogram
Popcon: 5 users (4 upd.)*
Versions and Archs
License: DFSG free
Git

Elementary Epidemiological Functions for a Graduate Epidemiology / Biostatistics Course.

This package contains elementary tools for analysis of common epidemiological problems, ranging from sample size estimation, through 2x2 contingency table analysis and basic measures of agreement (kappa, sensitivity/specificity). Appropriate print and summary statements are also written to facilitate interpretation wherever possible. This package is a work in progress, so any comments or suggestions would be appreciated. Source code is commented throughout to facilitate modification. The target audience includes graduate students in various epi/biostatistics courses.

Epibasix was developed in Canada.

r-cran-epicalc
GNU R Epidemiological calculator
Versions of package r-cran-epicalc
ReleaseVersionArchitectures
bookworm2.15.1.0-5all
sid2.15.1.0-5all
trixie2.15.1.0-5all
bullseye2.15.1.0-5all
buster2.15.1.0-4all
stretch2.15.1.0-2all
jessie2.15.1.0-1all
Debtags of package r-cran-epicalc:
devellang:r
fieldmedicine, statistics
interfacecommandline
roleprogram
Popcon: 6 users (4 upd.)*
Versions and Archs
License: DFSG free
Git

Functions making R easy for epidemiological calculation.

Datasets from Dbase (.dbf), Stata (.dta), SPSS(.sav), EpiInfo(.rec) and Comma separated value (.csv) formats as well as R data frames can be processed to do make several epidemiological calculations.

r-cran-epiestim
GNU R estimate time varying reproduction numbers from rpidemic curves
Versions of package r-cran-epiestim
ReleaseVersionArchitectures
bookworm2.2-4+dfsg-1all
trixie2.2-4+dfsg-1all
sid2.2-4+dfsg-1all
buster-backports2.2-4+dfsg-1~bpo10+1all
bullseye2.2-4+dfsg-1all
Popcon: 4 users (4 upd.)*
Versions and Archs
License: DFSG free
Git

Tools to quantify transmissibility throughout an epidemic from the analysis of time series of incidence as described in Cori et al. (2013) and Wallinga and Teunis (2004) .

r-cran-epir
GNU R Functions for analysing epidemiological data
Versions of package r-cran-epir
ReleaseVersionArchitectures
jessie0.9-59-1all
stretch0.9-79-1all
buster0.9-99-1all
bullseye2.0.19-1all
bookworm2.0.57+dfsg-1all
sid2.0.76+dfsg-1all
Debtags of package r-cran-epir:
devellang:r
fieldmedicine
interfacecommandline
roleprogram
useanalysing
Popcon: 50 users (55 upd.)*
Versions and Archs
License: DFSG free
Git

A package for analysing epidemiological data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, and computing confidence intervals around incidence risk and incidence rate estimates. Miscellaneous functions for use in meta-analysis, diagnostic test interpretation, and sample size calculations.

r-cran-epitools
GNU R Epidemiology Tools for Data and Graphics
Versions of package r-cran-epitools
ReleaseVersionArchitectures
bookworm0.5-10.1-2all
trixie0.5-10.1-2all
sid0.5-10.1-2all
jessie0.5-7-1all
stretch0.5-7-1all
buster0.5-10-2all
bullseye0.5-10.1-2all
Debtags of package r-cran-epitools:
fieldmedicine
interfacecommandline
roleprogram
Popcon: 8 users (4 upd.)*
Versions and Archs
License: DFSG free
Git

GNU R Tools for public health epidemiologists and data analysts. Epitools provides numerical tools and programming solutions that have been used and tested in real-world epidemiologic applications.

Many practical problems in the analysis of public health data require programming or special software, and investigators in different locations may duplicate programming efforts. Often, simple analyses, such as the construction of confidence intervals, are not calculated and thereby complicate appropriate statistical inferences for small geographic areas. There are many examples of simple and useful numerical tools that would enhance the work of epidemiologists at local health departments and yet are not readily available for the problem in front of them. The availability of these tools will encourage wider use of appropriate methods and promote evidence-based public health practices.

r-cran-incidence
GNU R compute, handle, plot and model incidence of dated events
Versions of package r-cran-incidence
ReleaseVersionArchitectures
bookworm1.7.3-1all
trixie1.7.5-1all
sid1.7.5-1all
bullseye1.7.3-1all
buster-backports1.7.3-1~bpo10+1all
Popcon: 4 users (4 upd.)*
Versions and Archs
License: DFSG free
Git

Provides functions and classes to compute, handle and visualise incidence from dated events for a defined time interval. Dates can be provided in various standard formats. The class 'incidence' is used to store computed incidence and can be easily manipulated, subsetted, and plotted. In addition, log-linear models can be fitted to 'incidence' objects using 'fit'. This package is part of the RECON (http://www.repidemicsconsortium.org/) toolkit for outbreak analysis.

r-cran-kernelheaping
GNU R kernel density estimation for heaped and rounded data
Versions of package r-cran-kernelheaping
ReleaseVersionArchitectures
sid2.3.0-1all
bookworm2.3.0-1all
Popcon: 2 users (3 upd.)*
Versions and Archs
License: DFSG free
Git

In self-reported or anonymised data the user often encounters heaped data, i.e. data which are rounded (to a possibly different degree of coarseness). While this is mostly a minor problem in parametric density estimation the bias can be very large for non-parametric methods such as kernel density estimation. This package implements a partly Bayesian algorithm treating the true unknown values as additional parameters and estimates the rounding parameters to give a corrected kernel density estimate. It supports various standard bandwidth selection methods. Varying rounding probabilities (depending on the true value) and asymmetric rounding is estimable as well: Gross, M. and Rendtel, U. (2016) (). Additionally, bivariate non- parametric density estimation for rounded data, Gross, M. et al. (2016) (), as well as data aggregated on areas is supported.

r-cran-lexrankr
extractive summarization of text with the LexRank algorithm
Versions of package r-cran-lexrankr
ReleaseVersionArchitectures
sid0.5.2-8amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x
buster0.5.0-2amd64,arm64,armhf,i386
bullseye0.5.2-2amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
bookworm0.5.2-8amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
trixie0.5.2-8amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x
Popcon: 4 users (5 upd.)*
Versions and Archs
License: DFSG free
Git

An R implementation of the LexRank algorithm implementing stochastic graph-based method for computing relative importance of textual units for Natural Language Processing. The technique on the problem of Text Summarization (TS) is tested. Extractive TS relies on the concept of sentence salience to identify the most important sentences in a document or set of documents. Salience is typically defined in terms of the presence of particular important words or in terms of similarity to a centroid pseudo-sentence.

Please cite: Güneş Erkan and Dragomir R. Radev: LexRank: Graph-based Lexical Centrality as Salience in Text Summarization. (eprint) Journal of Artific Intelligence Research 22:457-479 (2004)
r-cran-prevalence
GNU R tools for prevalence assessment studies
Versions of package r-cran-prevalence
ReleaseVersionArchitectures
sid0.4.1-1all
bookworm0.4.1-1all
trixie0.4.1-1all
Popcon: 2 users (3 upd.)*
Versions and Archs
License: DFSG free
Git

The prevalence package provides Frequentist and Bayesian methods for prevalence assessment studies. IMPORTANT: the truePrev functions in the prevalence package call on JAGS (Just Another Gibbs Sampler), which therefore has to be available on the user's system. JAGS can be downloaded from http://mcmc-jags.sourceforge.net/.

r-cran-seroincidence
GNU R seroincidence calculator tool
Versions of package r-cran-seroincidence
ReleaseVersionArchitectures
stretch1.0.5-1all
bullseye2.0.0-2all
buster2.0.0-1all
sid2.0.0-3all
trixie2.0.0-3all
bookworm2.0.0-3all
Popcon: 4 users (4 upd.)*
Versions and Archs
License: DFSG free
Git

Antibody levels measured in a cross-sectional population samples can be translated into an estimate of the frequency with which seroconversions (new infections) occur. In order to interpret the measured cross-sectional antibody levels, parameters which predict the decay of antibodies must be known. In previously published reports (Simonsen et al. 2009 and Versteegh et al. 2005), this information has been obtained from longitudinal studies on subjects who had culture-confirmed Salmonella and Campylobacter infections. A Bayesian back-calculation model was used to convert antibody measurements into an estimation of time since infection. This can be used to estimate the seroincidence in the cross-sectional sample of population. For both the longitudinal and cross-sectional measurements of antibody concentrations, the indirect ELISA was used. The models are only valid for persons over 18 years. The seroincidence estimates are suitable for monitoring the effect of control programmes when representative cross-sectional serum samples are available for analyses. These provide more accurate information on the infection pressure in humans across countries.

Please cite: PFM Teunis, JCH van Eijkeren, CW Ang, YTHP van Duynhoven, JB Simonsen, MA Strid and W van Pelt: Biomarker dynamics: estimating infection rates from serological data. (PubMed) Statistics in Medicine 31(20):2240–2248 (2012)
r-cran-sf
Simple Features for R
Versions of package r-cran-sf
ReleaseVersionArchitectures
bookworm1.0-9+dfsg-1amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
bullseye0.9-7+dfsg-5amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
sid1.0-17+dfsg-1amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x
stretch-backports0.6-3+dfsg-1~bpo9+1arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x
stretch-backports0.7-2+dfsg-1~bpo9+1amd64
buster0.7-2+dfsg-1amd64,arm64,armhf,i386
upstream1.0-19
Popcon: 168 users (99 upd.)*
Newer upstream!
License: DFSG free
Git

Support for simple features, a standardized way to encode spatial vector data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for geometrical operations, and to 'PROJ' for projection conversions and datum transformations.

r-cran-sjplot
GNU R data visualization for statistics in social science
Versions of package r-cran-sjplot
ReleaseVersionArchitectures
bullseye2.8.7-1all
stretch-backports2.6.2-1~bpo9+1all
buster2.6.2-1all
bookworm2.8.12+dfsg-1all
sid2.8.16+dfsg-1all
Popcon: 22 users (13 upd.)*
Versions and Archs
License: DFSG free
Git

Collection of plotting and table output functions for data visualization. Results of various statistical analyses (that are commonly used in social sciences) can be visualized using this package, including simple and cross tabulated frequencies, histograms, box plots, (generalized) linear models, mixed effects models, principal component analysis and correlation matrices, cluster analyses, scatter plots, stacked scales, effects plots of regression models (including interaction terms) and much more. This package supports labelled data.

r-cran-surveillance
전염병 현상의 모델링 및 모니터링을 위한 GNU R 패키지
Versions of package r-cran-surveillance
ReleaseVersionArchitectures
jessie1.8-0-1amd64,armel,armhf,i386
bookworm1.20.3-1amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
bullseye1.19.0-2amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
buster1.16.2-1amd64,arm64,armhf,i386
stretch1.13.0-1amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x
sid1.24.0-1amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x
trixie1.24.0-1amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x
upstream1.24.1
Debtags of package r-cran-surveillance:
fieldmedicine
interfacecommandline
roleprogram
Popcon: 6 users (8 upd.)*
Newer upstream!
License: DFSG free
Git

전염병 형상의 연속 지점 프로세스 모델링뿐만 아니라, 시계열 갯수, 비율 및 범주형 데이터의 모델링 및 모니터링을 위한 통계적 방법.

모니터링 방법은 전염병에 대한 공중 보건 감시의 카운트 데이터 시계열에서 이상 감지에 중점을 두지만 어플리케이션은 환경 측정, 신뢰성 공학, 계량 경제학 또는 사회 과학에서 유래할 수도 있습니다. 패키지는 (개선된) Farrington 알고리즘이나 Höhle 및 Paul(2008) 의 음이항 GLR-CUSUM 방법과 같은 많은 일반적인 발병 감지 절차를 구현합니다. 로지스틱과 다항 로지스틱 모델링을 결합한 새로운 CUSUM 접근 방식도 포함되어 있습니다. 패키지에는 여러 실제 데이터 세트, 발병 데이터를 시뮬레이션하는 기능, 시간적, 공간적 또는 시공간적 방식으로 모니터링 결과를 시각화하는 기능이 포함되어 있습니다. 이용 가능한 모니터링 절차에 대한 최근의 개요는 Salmon et al. (2016) 에 의해 제공됩니다.

전염병 확산에 대한 회고적 분석을 위해 패키지는 시각화, 가능성 추론 및 시뮬레이션을 위한 도구가 포함된 세 가지 풍토병-전염병 모델링 프레임워크를 제공합니다. hhh4()는 Paul and Held(2011) 및 Meyer and Held(2014) 에 따라 (다변량) 카운트 시계열에 대한 모델을 추정합니다. TwinSIR()은 Höhle(2009) 이 제안한 다변량 포인트 프로세스로 농장이나 네트워크 전반에 걸친 전염병과 같은 고정 인구의 SIR(감수성 감염 복구) 이벤트 기록을 모델링합니다. Twinstim()은 Meyer 등이 제안한 것처럼 감염성 이벤트의 시공간 포인트 패턴(예: 타임스탬프가 지정된 지리 참조 감시 데이터)에 대한 자기 흥분점포인트 프로세스 모델을 추정합니다. (2012) . 전염병 현상에 대해 구현된 시공간 모델링 프레임워크에 대한 최근 개요는 Meyer et al. (2017) 에 의해서 제공됩니다.

Please cite: Maëlle Salmon, Dirk Schumacher and Michael Höhle: Monitoring Count Time Series in R: Aberration Detection in Public Health Surveillance. Journal of Statistical Software 70(10):1-35 (2016)

Official Debian packages with lower relevance

python3-epimodels
simple interface to simulate mathematical epidemic models in Python3
Versions of package python3-epimodels
ReleaseVersionArchitectures
bookworm0.4.0-1all
sid0.4.0-4all
trixie0.4.0-4all
Popcon: 0 users (1 upd.)*
Versions and Archs
License: DFSG free
Git

This library provides a simple interface to simulate mathematical epidemic models in Python3. It is a precondition for the program epigrass.

r-cran-cmprsk
GNU R subdistribution analysis of competing risks
Versions of package r-cran-cmprsk
ReleaseVersionArchitectures
trixie2.2-11-1amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x
stretch2.2-7-2amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x
sid2.2-11-1amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x
buster2.2-7-4amd64,arm64,armhf,i386
bullseye2.2-10-1amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
bookworm2.2-11-1amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
upstream2.2-12
Popcon: 36 users (27 upd.)*
Newer upstream!
License: DFSG free
Git

This GNU R package supports estimation, testing and regression modeling of subdistribution functions in competing risks, as described in Gray (1988), A class of K-sample tests for comparing the cumulative incidence of a competing risk.

Please cite: Jason P. Fine and Robert J. Gray: A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc 94(446):496-509 (1999)
r-cran-msm
지속 시간에서 GNU R 다중 상태 마르코프 및 은닉 마르코프 모델
Versions of package r-cran-msm
ReleaseVersionArchitectures
sid1.8-1amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x
trixie1.8-1amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x
stretch1.6.4-1amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x
jessie1.4-2amd64,armel,armhf,i386
bullseye1.6.8-1amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
bookworm1.7-1amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
buster1.6.6-2amd64,arm64,armhf,i386
upstream1.8.2
Debtags of package r-cran-msm:
interfacecommandline
roleprogram
Popcon: 58 users (52 upd.)*
Newer upstream!
License: DFSG free
Git

일반적인 지속 시간 마르코프 및 은닉 마르코프 다중 상태 모델을 종단 데이타에 맞추기 위한 함수. 마르코프 전이 속도와 은닉 마르코프 출력 프로세스는 공변 측면에서 모델링 될 수 있습니다. 임의의 시간에 관측된 프로세스, 완전히 관측 된 프로세스, 검열 상태등을 포함해서 다양한 관측 스키마가 지원됩니다.

Please cite: Christopher H. Jackson: Multi-State Models for Panel Data: The msm Package for R. Journal of Statistical Software 38(8):1-29 (2011)
shiny-server
put Shiny web apps online
Versions of package shiny-server
ReleaseVersionArchitectures
bookworm1.5.20.1002-1amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x
sid1.5.20.1002-3amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x
upstream1.5.23.1030
Popcon: 47 users (0 upd.)*
Newer upstream!
License: DFSG free
Git

Shiny Server lets you put shiny web applications and interactive documents online. Take your Shiny apps and share them with your organization or the world.

Shiny Server lets you go beyond static charts, and lets you manipulate the data. Users can sort, filter, or change assumptions in real-time. Shiny server empower your users to customize your analysis for their specific needs and extract more insight from the data.

Packaging has started and developers might try the packaging code in VCS

chime
COVID-19 Hospital Impact Model for Epidemics
Versions of package chime
ReleaseVersionArchitectures
VCS0.2.1-1all
Versions and Archs
License: MIT
Debian package not available
Git
Version: 0.2.1-1

Penn Medicine - COVID-19 Hospital Impact Model for Epidemics

This tool was developed by the Predictive Healthcare team at Penn Medicine. For questions and comments please see our contact page. Code can be found on Github. Join our Slack channel if you would like to get involved!

The estimated number of currently infected individuals is 533. The 91 confirmed cases in the region imply a 17% rate of detection. This is based on current inputs for Hospitalizations (4), Hospitalization rate (5%), Region size (4119405), and Hospital market share (15%).

An initial doubling time of 6 days and a recovery time of 14.0 days imply an R_0 of 2.71.

Mitigation: A 0% reduction in social contact after the onset of the outbreak reduces the doubling time to 6.0 days, implying an effective R_t of 2.712.712.71.

epifire
model the spread of an infectious disease in a population
Versions of package epifire
ReleaseVersionArchitectures
VCS3.34.0+dfsg-1all
Versions and Archs
License: BSD-3-clause
Debian package not available
Git
Version: 3.34.0+dfsg-1

EpiFire is a C++ applications programming interface (API) that does two things:

  • Model the spread of an infectious disease in a population
  • Generate and manipulate networks of nodes and edges

While the network code can be used independently from the epidemiological code and vice versa—they are conceptually and functionally distinct—from the beginning, the libraries were developed to be compatible with each other. What EpiFire excels at is simulating the stochastic spread of disease on contact networks.

Please cite: Thomas Hladish, Eugene Melamud, Luis Alberto Barrera, Alison Galvani and Lauren Ancel Meyers: EpiFire: An open source C++ library and application for contact network epidemiology. (PubMed,eprint) BMC Bioinformatics 13:76 (2012)
netepi-analysis
network-enabled tools for epidemiology and public health practice
Versions of package netepi-analysis
ReleaseVersionArchitectures
VCS0.9.0-2all
Versions and Archs
License: HACOS
Debian package not available
Git
Version: 0.9.0-2

NetEpi, which is short for "Network-enabled Epidemiology", is a collaborative project to create a suite of free, open source software tools for epidemiology and public health practice. Anyone with an interest in population health epidemiology or public health informatics is encouraged to examine the prototype tools and to consider contributing to their further development. Contributions which involve formal and/or informal testing of the tools in a wide range of circumstances and environments are particularly welcome, as is assistance with design, programming and documentation tasks.

This is a tool for conducting epidemiological analysis of data sets, both large and small, either through a Web browser interface, or via a programmatic interface. In many respects it is similar to the analysis facilities included in the Epi Info suite, except that NetEpi Analysis is designed to be installed on servers and accessed remotely via Web browsers, although it can also be installed on individual desktop or laptop computers.

The software was developed by New South Wales Department of Health.

Remark of Debian Med team: See also: http://www.stockholmchallenge.se/data/2123 and

http://www.publish.csiro.au/?act=view_file&file_id=NB07103.pdf

netepi-collection
network-enabled tools for epidemiology and public health practice
Versions of package netepi-collection
ReleaseVersionArchitectures
VCS1.8.4-2all
Versions and Archs
License: HACOS
Debian package not available
Git
Version: 1.8.4-2

NetEpi, which is short for "Network-enabled Epidemiology", is a collaborative project to create a suite of free, open source software tools for epidemiology and public health practice. Anyone with an interest in population health epidemiology or public health informatics is encouraged to examine the prototype tools and to consider contributing to their further development. Contributions which involve formal and/or informal testing of the tools in a wide range of circumstances and environments are particularly welcome, as is assistance with design, programming and documentation tasks.

NetEpi Case Manager is a tool for securely collecting structured information about cases and contacts of communicable (and other) diseases through Web browsers and the Internet. New data collection forms can be designed and deployed quickly by epidemiologists, using a "point-and-click" interface, without the need for knowledge of or training in any programming language. Data can then be collected from users of the system, who can be located anywhere in the world, into a centralised database. All that is needed by users of the system is a relatively recent Web browser and an Internet connection ("NetEpi" is short for "Network-enabled Epidemiology"). In many respects, NetEpi Case Manager is like a Web-enabled version of the data entry facilities in the very popular Epi Info suite of programmes published by the US Centers for Disease Control and Prevention, and in the Danish EpiData project, which is available for several languages. The software was developed by the Centre for Epidemiology and Research of the New South Wales Department of Health, with contributions from Population Health Division of the Australian Government Department of Health and Ageing.

The software was developed by New South Wales Department of Health.

Remark of Debian Med team: See also: http://www.stockholmchallenge.se/data/2123 and

http://www.publish.csiro.au/?act=view_file&file_id=NB07103.pdf

r-cran-covid19
GNU R Coronavirus COVID-19 data acquisition and visualization
Versions of package r-cran-covid19
ReleaseVersionArchitectures
VCS0.2.1-1all
Versions and Archs
License: GPL-3
Debian package not available
Git
Version: 0.2.1-1

This GNU R package provides pre-processed, ready-to-use, tidy format datasets of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic. The latest data are downloaded in real-time, processed and merged with demographic indicators from several trusted sources. The package implements advanced data visualization across the space and time dimensions by means of animated mapping. Besides worldwide data, the package includes granular data for Italy, Switzerland and the Diamond Princess.

ushahidi
web platform for information collection
Versions of package ushahidi
ReleaseVersionArchitectures
VCS2.7.4-1all
Versions and Archs
License: LGPL-3+
Debian package not available
Git
Version: 2.7.4-1

Ushahidi is a platform that allows information collection, visualization and interactive mapping, allowing anyone to submit information through text messaging using a mobile phone, email or web form.

It can be used to monitor epidemic diseases, measuring the impact of natural disasters, uncovering corruption, and empowering peace makers.

No known packages available but some record of interest (WNPP bug)

repast - wnpp
framework for creating agent based simulations
License: BSD
Debian package not available

Repast Simphony is a free and open source agent-based modeling toolkit that simplifies model creation and use. Repast Simphony offers users a rich variety of features including the following:

  • Fluid model component development using any mixture of Java, Groovy, and flowcharts in each project;
  • A pure Java point-and-click model execution environment that includes built-in results logging and graphing tools as well as automated connections to a variety of optional external tools including the R statistics environment, *ORA and Pajek network analysis plugins, A live agent SQL query tool plugin, the VisAD scientific visualization package, the Weka data mining platform, many popular spreadsheets, the MATLAB computational mathematics environment, and the iReport visual report designer;
  • An extremely flexible hierarchically nested definition of space including the ability to do point-and-click and modeling and visualization of 2D environments; 3D environments; networks including full integration with the JUNG network modeling library as well as Microsoft Excel spreadsheets and UCINET DL file importing; and geographical spaces including 2D and 3D Geographical Information Systems (GIS) support;
  • A range of data storage "freeze dryers" for model check pointing and restoration including XML file storage, text file storage, and database storage;
  • A fully concurrent multithreaded discrete event scheduler;
  • Libraries for genetic algorithms, neural networks, regression, random number generation, and specialized mathematics;
  • An automated Monte Carlo simulation framework which supports multiple modes of model results optimization;
  • Built-in tools for integrating external models;
  • Distributed computing with Terracotta;
  • Full object-orientation;
  • Optional end-to-end XML simulation
  • A point-and-click model deployment system
Remark of Debian Med team: Please read also
 http://www.tbiomed.com/content/5/1/11
 http://lists.debian.org/debian-med/2009/08/msg00013.html (and following mails)
*Popularitycontest results: number of people who use this package regularly (number of people who upgraded this package recently) out of 245926