Summary
Epidemiology
pacchetti relativi all'epidemiologia per Debian Med
Questo metapacchetto installa gli strumenti utili nella ricerca
epidemiologica. Diversi pacchetti utilizzano il linguaggio dati GNU R per
l'investigazione statistica. Potrebbe essere una buona idea leggere
l'articolo "A short introduction to R for Epidemiology" all'indirizzo
http://staff.pubhealth.ku.dk/%7Ebxc/Epi/R-intro.pdf .
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
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Debian Med Epidemiology packages
Official Debian packages with high relevance
python3-seirsplus
Models of SEIRS epidemic dynamics with extensions
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Versions of package python3-seirsplus |
Release | Version | Architectures |
bullseye | 0.1.4+git20200528.5c04080+ds-2 | all |
bookworm | 1.0.9-1 | all |
trixie | 1.0.9-2 | all |
sid | 1.0.9-2 | all |
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License: DFSG free
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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.
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python3-torch
Tensors and Dynamic neural networks in Python (Python Interface)
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Versions of package python3-torch |
Release | Version | Architectures |
sid | 2.4.1-1 | amd64,arm64,ppc64el,riscv64,s390x |
bullseye | 1.7.1-7 | amd64,arm64,armhf,ppc64el,s390x |
bookworm | 1.13.1+dfsg-4 | amd64,arm64,ppc64el,s390x |
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License: DFSG free
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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:
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python3-treetime
inference of time stamped phylogenies and ancestral reconstruction (Python 3)
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Versions of package python3-treetime |
Release | Version | Architectures |
bullseye | 0.8.1-1 | all |
buster | 0.5.3-1 | all |
sid | 0.11.1-1 | all |
trixie | 0.11.1-1 | all |
bookworm | 0.9.4-1 | all |
upstream | 0.11.4 |
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License: DFSG free
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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.
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r-cran-covid19us
casi di COVID-19 negli Stati Uniti preparati per GNU R
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Versions of package r-cran-covid19us |
Release | Version | Architectures |
trixie | 0.1.9-1 | all |
bullseye | 0.1.7-1 | all |
sid | 0.1.9-1 | all |
bookworm | 0.1.9-1 | all |
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License: DFSG free
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Questo pacchetto fornisce un wrapper GNU R per la "COVID Tracking Project
API" (https://covidtracking.com/api/) che fornisce dati sui casi di
COVID-19 negli Stati Uniti.
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r-cran-diagnosismed
toolkit per analisi di accuratezza per test diagnostici medicali
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Versions of package r-cran-diagnosismed |
Release | Version | Architectures |
stretch | 0.2.3-4 | all |
jessie | 0.2.3-3 | all |
buster | 0.2.3-6 | all |
bullseye | 0.2.3-7 | all |
bookworm | 0.2.3-7 | all |
trixie | 0.2.3-7 | all |
sid | 0.2.3-7 | all |
Debtags of package r-cran-diagnosismed: |
devel | lang:r |
field | medicine |
interface | commandline |
role | program |
use | analysing |
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License: DFSG free
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DiagnosisMed è un pacchetto GNU R per analizzare l'accuratezza dei dati da
test diagnostici per valutare le condizioni di salute. È stato creato per
essere usato da professionisti in campo medico. Questo pacchetto aiuta a
stimare la sensibilità e la specificità da risultati di test categorici
e continui incluse alcune valutazioni di risultati indeterminati, oppure
confrontare diversi test categorici e stimare valori limite ragionevoli per
i test e visualizzarli in un modo usato comunemente da professionisti in
campo medico. Non è ancora disponibile un'interfaccia grafica.
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r-cran-epi
analisi epidemiologica GNU R
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Versions of package r-cran-epi |
Release | Version | Architectures |
stretch | 2.7-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 2.32-2 | amd64,arm64,armhf,i386 |
bullseye | 2.43-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.47-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.53-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 2.53-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
jessie | 1.1.67-4 | amd64,armel,armhf,i386 |
upstream | 2.56 |
Debtags of package r-cran-epi: |
field | medicine |
interface | commandline |
role | program |
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License: DFSG free
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Funzioni per analisi demografiche ed epidemiologiche nel diagramma di
Lexis, cioè registrazioni e dati di aggiornamento di un gruppo, inclusi
dati censiti ad intervalli e la rappresentazione di dati multi-stato.
Inoltre vi sono alcune funzioni utili per la tabulazione e il tracciamento
di grafici. Contiene alcuni insiemi di dati epidemiologici.
Il pacchetto Epi è orientato principalmente all'epidemiologia "classica"
per le malattie croniche. Il pacchetto si è sviluppato dal corso di
Statistica applicata all'epidemiologia usando R (vedere
http://www.pubhealth.ku.dk/~bxc/SPE).
Una breve introduzione a R per l'epidemiologia è disponibile su
http://staff.pubhealth.ku.dk/%7Ebxc/Epi/R-intro.pdf
Notare che le pagine 38-120 di questo documento sono semplicemente le
pagine di manuale del pacchetto Epi.
Epi non è l'unico pacchetto R per l'analisi epidemiologica, il pacchetto
epitools, anch'esso disponibile in Debian, è un pacchetto più indirizzato
all'epidemiologia delle malattie infettive.
Epi è usato dal Dipartimento di Biostatistica dell'Università di Copenaghen.
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r-cran-epibasix
funzioni epidemiologiche elementari per GNU R
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Versions of package r-cran-epibasix |
Release | Version | Architectures |
bookworm | 1.5-2 | all |
bullseye | 1.5-2 | all |
buster | 1.5-1 | all |
jessie | 1.3-1 | amd64,armel,armhf,i386 |
sid | 1.5-2 | all |
trixie | 1.5-2 | all |
stretch | 1.3-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
Debtags of package r-cran-epibasix: |
field | medicine |
interface | commandline |
role | program |
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License: DFSG free
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Funzioni epidemiologiche elementari per un corso universitario di
epidemiologia/biostatistica.
Questo pacchetto contiene strumenti elementari per l'analisi di problemi
epidemiologici comuni, che vanno dalla stima della grandezza di un campione
all'analisi di tabelle di contingenza 2x2 e misure di base di concordanza
(kappa, sensibilità/specificità). Vengono inoltre prodotti, quando
possibile, rapporti riassuntivi e stampe appropriati per facilitare
l'interpretazione. Questo pacchetto è in fase di sviluppo, perciò qualsiasi
commento o suggerimento è benvenuto. Il codice sorgente è largamente
commentato per facilitare modifiche. L'utenza a cui è indirizzato include
studenti universitari di vari corsi di statistica epidemiologica/biologica.
Epibasix è stato sviluppato in Canada.
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r-cran-epicalc
calcolatore epidemiologico per GNU R
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Versions of package r-cran-epicalc |
Release | Version | Architectures |
trixie | 2.15.1.0-5 | all |
jessie | 2.15.1.0-1 | all |
stretch | 2.15.1.0-2 | all |
buster | 2.15.1.0-4 | all |
bullseye | 2.15.1.0-5 | all |
bookworm | 2.15.1.0-5 | all |
sid | 2.15.1.0-5 | all |
Debtags of package r-cran-epicalc: |
devel | lang:r |
field | medicine, statistics |
interface | commandline |
role | program |
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License: DFSG free
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Funzioni per rendere facile il calcolo epidemiologico in R.
Permette di elaborare insiemi di dati da Dbase (.dbf), Stata (.dta),
SPSS (.sav), EpiInfo (.rec) e valori separati da virgole (.csv) o anche
gruppi di dati in R per eseguire diversi calcoli epidemiologici.
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r-cran-epiestim
GNU R estimate time varying reproduction numbers from rpidemic curves
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Versions of package r-cran-epiestim |
Release | Version | Architectures |
trixie | 2.2-4+dfsg-1 | all |
buster-backports | 2.2-4+dfsg-1~bpo10+1 | all |
bullseye | 2.2-4+dfsg-1 | all |
bookworm | 2.2-4+dfsg-1 | all |
sid | 2.2-4+dfsg-1 | all |
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License: DFSG free
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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)
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r-cran-epir
funzioni GNU R per analisi di dati epidemiologici
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Versions of package r-cran-epir |
Release | Version | Architectures |
jessie | 0.9-59-1 | all |
stretch | 0.9-79-1 | all |
buster | 0.9-99-1 | all |
bookworm | 2.0.57+dfsg-1 | all |
sid | 2.0.76+dfsg-1 | all |
bullseye | 2.0.19-1 | all |
Debtags of package r-cran-epir: |
devel | lang:r |
field | medicine |
interface | commandline |
role | program |
use | analysing |
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License: DFSG free
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Un pacchetto per analizzare dati epidemiologici. Contiene funzioni per
regolare direttamente e indirettamente misure della frequenza di malattie,
quantificare misure di associazioni sulla base di strati singoli o multipli
di dati numerici presentati in una tabella di contingenza e calcolare
intervalli di confidenza sul rischio di incidenza e le stime delle
percentuali di incidenza. Sono fornite funzioni varie per l'uso in
meta-analisi, interpretazione di test diagnostici e calcoli della
dimensione del campione.
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r-cran-epitools
strumenti GNU R per epidemiologia per dati e grafici
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Versions of package r-cran-epitools |
Release | Version | Architectures |
bookworm | 0.5-10.1-2 | all |
trixie | 0.5-10.1-2 | all |
bullseye | 0.5-10.1-2 | all |
buster | 0.5-10-2 | all |
stretch | 0.5-7-1 | all |
jessie | 0.5-7-1 | all |
sid | 0.5-10.1-2 | all |
Debtags of package r-cran-epitools: |
field | medicine |
interface | commandline |
role | program |
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License: DFSG free
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Strumenti GNU R per epidemiologi e analisti di dati. Epitools fornisce
strumenti numerici e soluzioni software che sono state usate e testate in
applicazioni epidemiologiche nel mondo reale.
Molti problemi pratici nell'analisi dei dati sulla salute pubblica
richiedono programmazione o software speciale e gli studiosi, in diversi
luoghi, possono fare sforzi di programmazione duplicati. Spesso analisi
semplici, come la costruzione di intervalli di confidenza, non sono
calcolate e perciò complicano un'inferenza statistica corretta per aree
geografiche limitate. Ci sono molti esempi di strumenti numerici semplici e
utili che migliorerebbero il lavoro degli epidemiologi nei dipartimenti di
salute pubblica e che, però, non sono disponibili immediatamente per i
problemi reali che si trovano di fronte. La disponibilità di questi
strumenti incoraggerà un più vasto uso dei metodi appropriati e promuoverà
politiche di salute pubblica basate su prove.
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r-cran-incidence
calcolo, gestione, disegno e modellazione in GNU R dell'incidenza di eventi con data
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Versions of package r-cran-incidence |
Release | Version | Architectures |
trixie | 1.7.5-1 | all |
buster-backports | 1.7.3-1~bpo10+1 | all |
bullseye | 1.7.3-1 | all |
bookworm | 1.7.3-1 | all |
sid | 1.7.5-1 | all |
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License: DFSG free
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Fornisce funzioni e classi per calcolare, gestire e visualizzare l'incidenza
da eventi con data per un intervallo di tempo definito. Le date possono
essere fornite in vari formati standard. La classe "incidence" è usata per
memorizzare l'incidenza calcolata e può essere facilmente manipolata,
divisa in sottoinsiemi e disegnata. In aggiunta può essere fatto il fit di
modelli log-lineari su oggetti "incidence" usando "fit". Questo pacchetto
fa parte dell'insieme di strumenti RECON
(http://www.repidemicsconsortium.org/) per l'analisi di epidemie.
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r-cran-kernelheaping
GNU R kernel density estimation for heaped and rounded data
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Versions of package r-cran-kernelheaping |
Release | Version | Architectures |
sid | 2.3.0-1 | all |
bookworm | 2.3.0-1 | all |
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License: DFSG free
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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.
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r-cran-lexrankr
extractive summarization of text with the LexRank algorithm
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Versions of package r-cran-lexrankr |
Release | Version | Architectures |
buster | 0.5.0-2 | amd64,arm64,armhf,i386 |
sid | 0.5.2-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 0.5.2-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 0.5.2-8 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.5.2-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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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.
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r-cran-prevalence
strumenti GNU R per studi di calcolo della prevalenza
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Versions of package r-cran-prevalence |
Release | Version | Architectures |
trixie | 0.4.1-1 | all |
bookworm | 0.4.1-1 | all |
sid | 0.4.1-1 | all |
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License: DFSG free
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Il pacchetto prevalence fornisce metodi frequentisti e bayesiani per studi
di valutazione della prevalenza. IMPORTANTE: le funzioni truePrev nel
pacchetto prevalence chiamano JAGS (Just Another Gibbs Sampler), che perciò
deve essere disponibile nel sistema dell'utente. JAGS può essere scaricato
da http://mcmc-jags.sourceforge.net/.
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r-cran-seroincidence
strumento GNU R per calcolare la sieroincidenza
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Versions of package r-cran-seroincidence |
Release | Version | Architectures |
sid | 2.0.0-3 | all |
trixie | 2.0.0-3 | all |
bookworm | 2.0.0-3 | all |
bullseye | 2.0.0-2 | all |
buster | 2.0.0-1 | all |
stretch | 1.0.5-1 | all |
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License: DFSG free
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I livelli di anticorpi misurati in campioni di popolazione trasversali
possono essere tradotti in stime della frequenza con cui avvengono
sieroconversioni (nuove infezioni). Per poter interpretare i livelli
anticorpali trasversali misurati, devono essere conosciuti i parametri di
predizione del decadimento degli anticorpi. In rapporti precedentemente
pubblicati (Simonsen et al. 2009 e Versteegh et al. 2005), queste
informazioni sono state ottenute da studi longitudinali su soggetti che
avevano infezioni da Salmonella o Campylobacter confermate colturalmente. È
stato utilizzato un modello bayesiano di calcolo all'indietro per
convertire le misure anticorpali in una stima del tempo trascorso
dall'infezione. Ciò può essere utilizzato per stimare la sieroincidenza nel
campione trasversale della popolazione. Per entrambe le misure
longitudinale e trasversale delle concentrazioni anticorpali, è stato usato
un metodo ELISA indiretto. I modelli sono validi solo per soggetti con più
di 18 anni. Le stime della sieroincidenza sono adatte per monitorare
l'effetto di programmi di controllo quando sono disponibili per l'analisi
campioni di siero trasversali rappresentativi. Questi forniscono
informazioni più accurate sulla pressione dell'infezione nella popolazione
umana in più nazioni.
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r-cran-sf
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Versions of package r-cran-sf |
Release | Version | Architectures |
sid | 1.0-17+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 0.9-7+dfsg-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 0.7-2+dfsg-1 | amd64,arm64,armhf,i386 |
stretch-backports | 0.7-2+dfsg-1~bpo9+1 | amd64 |
stretch-backports | 0.6-3+dfsg-1~bpo9+1 | arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.0-9+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
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License: DFSG free
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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.
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r-cran-sjplot
GNU R data visualization for statistics in social science
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Versions of package r-cran-sjplot |
Release | Version | Architectures |
bullseye | 2.8.7-1 | all |
stretch-backports | 2.6.2-1~bpo9+1 | all |
buster | 2.6.2-1 | all |
bookworm | 2.8.12+dfsg-1 | all |
sid | 2.8.16+dfsg-1 | all |
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License: DFSG free
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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.
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r-cran-surveillance
pacchetto GNU R per la modellazione e il monitoraggio di fenomeni epidemici
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Versions of package r-cran-surveillance |
Release | Version | Architectures |
jessie | 1.8-0-1 | amd64,armel,armhf,i386 |
sid | 1.24.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.23.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.20.3-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.19.0-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.16.2-1 | amd64,arm64,armhf,i386 |
stretch | 1.13.0-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
Debtags of package r-cran-surveillance: |
field | medicine |
interface | commandline |
role | program |
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License: DFSG free
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Metodi statistici per la modellazione e il monitoraggio di serie temporali
di conteggi, proporzioni e dati categorici, così come per la modellazione
di processi puntuali di fenomeni epidemici nel tempo continuo.
I metodi di monitoraggio si focalizzano sul rilevamento di aberrazioni in
serie temporali di conteggi da dati di sorveglianza per la salute pubblica
di malattie trasmissibili, ma potrebbero anche esserci applicazioni per
l'environmetrica, l'ingegneria dell'affidabilità, l'econometria o le
scienze sociali. Il pacchetto implementa molte comuni procedure di
rilevamento di epidemie, come l'algoritmo di Farrington (migliorato) o il
metodo GLR-CUSUM negativo binomiale di Höhle & Paul (2008)
. È anche incluso un approccio CUSUM
innovativo che combina modellazione logistica e logistica multinomiale. Il
pacchetto contiene diversi insiemi di dati di casi reali, la capacità di
simulare dati di epidemie e di visualizzare i risultati del monitoraggio in
maniera temporale, spaziale o spazio-temporale. Una recente panoramica
delle procedure di monitoraggio disponibili è fornita in Salmon et al.
(2016) .
Per l'analisi retrospettiva di diffusioni epidemiche, il pacchetto fornisce
tre infrastrutture di modellazione endemica-epidemica con strumenti per
visualizzazione, inferenza di verosimiglianza e simulazione. hhh4() stima
modelli per serie temporali di conteggi (multivariate) secondo Paul & Held
(2011) e Meyer & Held (2014)
. twinSIR() modella la cronologia di eventi SIR
(suscettibili-infetti-rimossi) di una popolazione fissa, ad esempio
epidemie tra fattorie o reti, come un processo puntuale multivariato come
proposto da Höhle (2009) .
twinstim() stima modelli di processi puntuali auto-eccitanti per un modello
puntuale spazio-temporale di eventi infettivi, ad esempio dati di
sorveglianza georeferenziati con marcatura temporale, come proposto da
Meyer et al. (2012) . Una recente
panoramica delle infrastrutture di modellazione spazio-tempo implementate
per i fenomeni epidemici è fornita in Meyer et al. (2017)
.
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Official Debian packages with lower relevance
python3-epimodels
semplice interfaccia per simulare modelli epidemici matematici in Python 3
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Versions of package python3-epimodels |
Release | Version | Architectures |
bookworm | 0.4.0-1 | all |
sid | 0.4.0-2 | all |
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License: DFSG free
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Questa libreria fornisce una semplice interfaccia per simulare modelli
epidemici matematici in Python 3. È una precondizione per il programma
epigrass.
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r-cran-cmprsk
GNU R subdistribution analysis of competing risks
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Versions of package r-cran-cmprsk |
Release | Version | Architectures |
bookworm | 2.2-11-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 2.2-11-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
sid | 2.2-11-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bullseye | 2.2-10-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
stretch | 2.2-7-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
buster | 2.2-7-4 | amd64,arm64,armhf,i386 |
upstream | 2.2-12 |
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License: DFSG free
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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.
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r-cran-msm
modelli multistato di Markov e di Markov nascosti in tempo continuo per GNU R
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Versions of package r-cran-msm |
Release | Version | Architectures |
jessie | 1.4-2 | amd64,armel,armhf,i386 |
sid | 1.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.8-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
bookworm | 1.7-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 1.6.8-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.6.6-2 | amd64,arm64,armhf,i386 |
stretch | 1.6.4-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
upstream | 1.8.1 |
Debtags of package r-cran-msm: |
interface | commandline |
role | program |
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License: DFSG free
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Funzioni per il fitting di modelli generici multi-stato di Markov e di
Markov nascosti in tempo continuo a dati longitudinali. Sia le probabilità
di transizione tra gli stati markoviani sia il processo di output del
modello di Markov nascosto possono essere modellati in termini di
covariate. Sono gestiti svariati schemi di osservazione, inclusi processi
osservati ad intervalli arbitrari, processi osservati completamente e stati
censurati.
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shiny-server
put Shiny web apps online
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Versions of package shiny-server |
Release | Version | Architectures |
bookworm | 1.5.20.1002-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.5.20.1002-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.5.20.1002-2 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
upstream | 1.5.23.1030 |
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License: DFSG free
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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.
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Packaging has started and developers might try the packaging code in VCS
chime
COVID-19 Hospital Impact Model for Epidemics
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Versions of package chime |
Release | Version | Architectures |
VCS | 0.2.1-1 | all |
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License: MIT
Debian package not available
Version: 0.2.1-1
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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.
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epifire
model the spread of an infectious disease in a population
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Versions of package epifire |
Release | Version | Architectures |
VCS | 3.34.0+dfsg-1 | all |
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License: BSD-3-clause
Debian package not available
Version: 3.34.0+dfsg-1
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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.
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netepi-analysis
network-enabled tools for epidemiology and public health practice
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Versions of package netepi-analysis |
Release | Version | Architectures |
VCS | 0.9.0-2 | all |
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License: HACOS
Debian package not available
Version: 0.9.0-2
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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.
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netepi-collection
network-enabled tools for epidemiology and public health practice
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Versions of package netepi-collection |
Release | Version | Architectures |
VCS | 1.8.4-2 | all |
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License: HACOS
Debian package not available
Version: 1.8.4-2
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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.
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r-cran-covid19
GNU R Coronavirus COVID-19 data acquisition and visualization
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Versions of package r-cran-covid19 |
Release | Version | Architectures |
VCS | 0.2.1-1 | all |
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License: GPL-3
Debian package not available
Version: 0.2.1-1
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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.
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ushahidi
web platform for information collection
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Versions of package ushahidi |
Release | Version | Architectures |
VCS | 2.7.4-1 | all |
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License: LGPL-3+
Debian package not available
Version: 2.7.4-1
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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.
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No known packages available but some record of interest (WNPP bug)
framework for creating agent based simulations
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License: BSD
Debian package not available
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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
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