Summary
Epidemiology
Epidemiologirelaterede pakker for Debian Med
Denne metapakke vil installere værktøjer, som er brugbare i epidemiologisk
forskning. Flere pakker gør brug af GNU R-datasproget for statistiske
undersøgelser. Det kan være en god ide at læse den engelske artikel »A
short introduction to R for Epidemiology«, som kan ses her
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 |
bookworm | 1.0.9-1 | all |
trixie | 1.0.9-2 | all |
bullseye | 0.1.4+git20200528.5c04080+ds-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
Tensorer og dynamiske neurale netværk i Python - Pythongrænseflade
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Versions of package python3-torch |
Release | Version | Architectures |
bookworm | 1.13.1+dfsg-4 | amd64,arm64,ppc64el,s390x |
bullseye | 1.7.1-7 | amd64,arm64,armhf,ppc64el,s390x |
sid | 2.4.1-4 | amd64,arm64,ppc64el,riscv64,s390x |
upstream | 2.5.1 |
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License: DFSG free
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PyTorch er en Pythonpakke, der tilbyder to funktioner på højt niveau.
(1) Tensorberegning (som NumPy) med stærk GPU-acceleration
(2) Dybe neurale netværk bygget på et båndbaseret autograd-system
Du kan genbruge dine favoritpakker fra Python såsom NumPy, SciPy og Cython for at udvide PyTorch efter behov.
Dette er versionen kun for cpu af PyTorch (Pythongrænseflade).
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
Inferens af tidsstemplede fylogenier og forfædres rekonstruktion - Python 3
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Versions of package python3-treetime |
Release | Version | Architectures |
buster | 0.5.3-1 | all |
bullseye | 0.8.1-1 | 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 giver rutiner til genopbygning af forfædresekvenser og maksimal likelihoo-inferens af molekylært ur-fylogenier, dvs. et træ hvor alle grene er skaleret, så placeringen af terminalknudepunkter svarer til deres samplingstider, og interne knuder er placeret ved mest sandsynlige tidspunkt for afvigelse.
TreeTime sigter mod at nå et kompromis mellem sofistikerede sandsynlighedsmodeller for evolution og hurtig heuristik. Det implementerer GTR-modeller af forfædres inferens og optimering af grenlængden, men tager
trætopologien som givet. For at optimere sandsynligheden for tidsskaleret
fylogenier, treetime bruger en iterativ tilgang, som først inferer
forfædresekvenser givet træets grenlængde og optimerer derefter positionerne for ubegrænsede d-noder på tidsaksen og gentages derefter
denne cyklus. Den eneste topologioptimering er (valgfri) opløsning på
polytomier på en måde, der er mest (cirka) konsistent med prøvetagning af tidsbegrænsninger på træet. Pakken er designet til brug som et selvstændigt værktøj eller som et bibliotek brugt i større fylogenetisk analyse af arbejdsgange.
Funktioner
- rekonstruktion af forfædresekvens (marginalt og fælles maksimum
sandsynlighed)
- inferens af molekylært ur-træ (marginalt og fælles maksimum
sandsynlighed)
- inferens af GTR-modeller
- genstart for at opnå den bedste root-to-tip-regression
- autokorreleret afslappet molekylært ur (med normalt forudgående)
Denne pakke indeholder Python 3-modulet.
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r-cran-covid19us
Tilfælde af COVI-19 i USA forberedt for GNU R
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Versions of package r-cran-covid19us |
Release | Version | Architectures |
trixie | 0.1.9-1 | all |
bookworm | 0.1.9-1 | all |
bullseye | 0.1.7-1 | all |
sid | 0.1.9-1 | all |
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License: DFSG free
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Denne pakke tilbyder et GNU R-omslag omkring »COVID Tracking Project API« https://covidtracking.com/api/ der tilbyder data på tilfælde af COVID-19 i USA.
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r-cran-diagnosismed
Præcisionsevaluering af diagnostisk test for læger
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Versions of package r-cran-diagnosismed |
Release | Version | Architectures |
bookworm | 0.2.3-7 | all |
bullseye | 0.2.3-7 | all |
stretch | 0.2.3-4 | all |
trixie | 0.2.3-7 | all |
sid | 0.2.3-7 | all |
buster | 0.2.3-6 | all |
jessie | 0.2.3-3 | 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 er en GNU R-pakke til analyse af data fra
præcisionsevalueringer af diagnostiske test af sundhedsbetingelser. Det
bliver udviklet til anvendelse i sundhedsvæsenet. Pakken er i stand til at
estimere følsomhed og specificitet fra kategoriske og fortløbende
testresultater, inklusive enkelte evalueringer af ubestemmelige
resultater, eller sammenligning af forskellige kategoriske test, samt
estimering af rimelige afgrænsninger af test. Dette vises på en måde som
ofte anvendes i sundhedsvæsenet. Der er endnu ingen grafisk grænseflade.
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r-cran-epi
GNU R epidemiologisk analyse
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Versions of package r-cran-epi |
Release | Version | Architectures |
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 |
jessie | 1.1.67-4 | amd64,armel,armhf,i386 |
stretch | 2.7-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 2.53-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 2.53-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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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Funktioner til demografisk og epidemiologisk analyse i Lexis-programmet,
dvs. register- og kohorte-opfølgningsdata, inklusive intervalcensorerede
data og repræsentation af data i flere tilstande. Indeholder også nyttige
funktioner til tabulering og plotning. Indeholder også nogle epidemiologiske datasæt.
Epi-pakken er primært fokuseret på »klassisk« kronisk sygdomsepidemiologi.
Pakken er vokset ud af kurset »Statistical Practice in Epidemiology using
R« (se http://www.pubhealth.ku.dk/~bxc/SPE).
Der er en kort introduktion til epidemiologi med R tilgængelig på
http://staff.pubhealth.ku.dk/%7Ebxc/Epi/R-intro.pdf
Vær opmærksom på at siderne 38-120 fra denne blot er manualsiderne til Epi-
pakken.
Epi er ikke den eneste R-pakke til epidemiologisk analyse. En pakke med
tættere tilhørsforhold til smitsom sygdomsepidemiologi er pakken epitools,
der også er tilgængelig gennem Debian.
Epi anvendes af Biostatistisk Afdeling ved Københavns Universitet.
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r-cran-epibasix
GNU R Elementary Epidemiological-funktioner
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Versions of package r-cran-epibasix |
Release | Version | Architectures |
bullseye | 1.5-2 | all |
stretch | 1.3-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 1.3-1 | amd64,armel,armhf,i386 |
buster | 1.5-1 | all |
sid | 1.5-2 | all |
trixie | 1.5-2 | all |
bookworm | 1.5-2 | all |
Debtags of package r-cran-epibasix: |
field | medicine |
interface | commandline |
role | program |
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License: DFSG free
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Elementary Epidemiological-funktioner for et
Epidemiology/Biostatistics-forskningskursus.
Denne pakke indeholder elementære værktøjer for analyse af gængse
epidemiologiske problemer, fra estimering af prøvestørrelse, via 2x2
kontingens tabelanalyse og grundlæggende målinger for aftale (kappa,
sensitivitet). Passende udskrivnings- og summeringsudtryk skrives også for
at facilitere fortolkning når det er muligt. Denne pakke er under
udvikling, så der tages godt imod alle kommentarer eller forslag.
Kildekoden er kommenteret udførligt for at facilitere ændring. Målgruppen
inkluderer forskningsstuderende i forskellige epi/biostatistiske kurser.
Epibasix blev udviklet i Canada.
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r-cran-epicalc
GNU R epidemiologisk beregner
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Versions of package r-cran-epicalc |
Release | Version | Architectures |
bookworm | 2.15.1.0-5 | all |
sid | 2.15.1.0-5 | all |
trixie | 2.15.1.0-5 | all |
bullseye | 2.15.1.0-5 | all |
buster | 2.15.1.0-4 | all |
stretch | 2.15.1.0-2 | all |
jessie | 2.15.1.0-1 | 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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Funktioner der gør det let at foretage epidemiologiske beregninger med R.
Flere datasæt fra formaterne Dbase (.dbf), Stata (.dta), SPSS (.sav),
EpiInfo (.rec) og kommaseparerede værdier (.csv) såvel som R-datarammer, kan
behandles til foretagelse af adskillige epidemiologiske beregninger.
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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 |
bookworm | 2.2-4+dfsg-1 | all |
trixie | 2.2-4+dfsg-1 | all |
sid | 2.2-4+dfsg-1 | all |
buster-backports | 2.2-4+dfsg-1~bpo10+1 | all |
bullseye | 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
GNU R-funktioner for analyse af epidemiologiske data
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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 |
bullseye | 2.0.19-1 | all |
bookworm | 2.0.57+dfsg-1 | all |
sid | 2.0.76+dfsg-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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En pakke til analyse af epidemiologiske data. Indeholder funktioner til
direkte og indirekte at justere mål for sygdomsfrekvens, kvantificere
associationsforanstaltninger på grundlag af en enkelt eller flere lag af
optalte data præsenteret i en antalstabel og beregning af
konfidensintervaller omkring risikoforekomst og skøn for udbrud.
Hjælpefunktioner til brug i metaanalyse, diagnostiske testfortolkninger og
beregninger af størrelse på stikprøve.
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r-cran-epitools
GNU R epidemiologi-værktøjer til data og grafik
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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 |
sid | 0.5-10.1-2 | all |
jessie | 0.5-7-1 | all |
stretch | 0.5-7-1 | all |
buster | 0.5-10-2 | all |
bullseye | 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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GNU R-værktøjer til epidemiologer og dataanalytikere i den offentlige
sundhedssektor. Epitools tilbyder talmæssige værktøjer og
programmeringsløsninger som er blevet anvendt og testet i epidemiologiske
anvendelsesområder fra den virkelige verden.
Mange praktiske problemer i analysen af offentlige sundhedsdata kræver
programmering eller specialprogrammel, og undersøgelsespersonale på
forskellige steder kan duplikere programmeringsindsatsen. Ofte vil simple
analyser, såsom konstruktionen af fortrolighedsintervaller, ikke blive
beregnet og dermed komplicere passende statistiske slutninger for mindre
geografiske områder. Der er mange eksempler på simple og talmæssige
værktøjer som ville forbedre epidemiologers arbejde på lokale
sundhedsafdelinger, og og endnu ikke er parate og tilgængelige til
problemet foran dem. Tilgængeligheden af disse værktøjer vil fremme bredere
anvendelse af passende metoder og fremme evidensbaseret praksis i den
offentlige sundhedssektor.
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r-cran-incidence
GNU R - beregn, håndter, plot og eksempler på forekomst af daterede hændelser
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Versions of package r-cran-incidence |
Release | Version | Architectures |
bookworm | 1.7.3-1 | all |
trixie | 1.7.5-1 | all |
sid | 1.7.5-1 | all |
bullseye | 1.7.3-1 | all |
buster-backports | 1.7.3-1~bpo10+1 | all |
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License: DFSG free
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Denne pakke tilbyder funktioner og klasser til at beregne, håndtere og visualisere forekomst fra daterede hændelser for et defineret tidsinterval. Datoer kan tilbydes i diverse standardformater. Klassen »incidence« bruges til at lagre beregnet forekomst og kan nemt manipuleres, underopdeles og plottes. Derudover kan log-linear-modeller tilpasses til »incidence«-objekter via »fit«. Denne pakke er en del af RECON-værktøjssættet (http://www.repidemicsconsortium.org/) for udbrudsanalyse.
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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
Udtræk summering af tekst med LexRank-algoritmen
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Versions of package r-cran-lexrankr |
Release | Version | Architectures |
sid | 0.5.2-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 0.5.0-2 | amd64,arm64,armhf,i386 |
bullseye | 0.5.2-2 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 0.5.2-8 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
trixie | 0.5.2-8 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
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License: DFSG free
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En R-implementering af LexRank-algoritmen, der implementerer en stokastisk grafbaseret metode til beregning af relativ vigtighed for tekstenheder for naturlig sprogbehandling. Teknikken på problemet Test Summarization (TS) er testet. Extractive TS afhænger af koncepter for sætningsfremtræden i et dokument eller sæt af dokumenter. Fremtræden er typisk defineret i form af tilstedeværelsen af bestemte vigtige ord eller termer af lighed for en pseudosætning med tyngde.
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r-cran-prevalence
GNU R-værktøjer for prævalensvurderingsundersøgelser
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Versions of package r-cran-prevalence |
Release | Version | Architectures |
sid | 0.4.1-1 | all |
bookworm | 0.4.1-1 | all |
trixie | 0.4.1-1 | all |
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License: DFSG free
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Pakken prevalence tilbyder Frequentist- og Bayesian-metoder for prævalensvurderingsundersøgelser. VIGTIGT: TruePrev-funktioner i pakken prevalence kalder på JAGS (Just Another Gibbs Sampler), der derfor skal være tilgængelig på brugerens system. JAGS kan hentes fra http://mcmc-jags.sourceforge.net/.
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r-cran-seroincidence
GNU R seroincidence - lommeregnerværktøj
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Versions of package r-cran-seroincidence |
Release | Version | Architectures |
stretch | 1.0.5-1 | all |
bullseye | 2.0.0-2 | all |
buster | 2.0.0-1 | all |
sid | 2.0.0-3 | all |
trixie | 2.0.0-3 | all |
bookworm | 2.0.0-3 | all |
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License: DFSG free
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Antistofniveauer målt i en tværsnitsundersøgelser af befolkningen, kan
oversættes til et skøn over, hvor hyppigt serokonversioner (nye
infektioner) forekommer. For at fortolke det målte tværsnitsbillede for
antistofniveauer, skal parametre som forudsiger henfaldet af antistoffer
være kendt. I tidligere udgivede rapporter (Simonsen et al. 2009 og
Versteegh et al. 2005), er der indhentet disse oplysninger fra
longitudinelle studier om emner, der havde kulturbekræftede salmonella- og
campylobacterinfektioner. En Bayesiansk tilbageberegningsmodel blev anvendt
til at omdanne antistofmålinger til en estimering af tid siden infektion.
Dette kan anvendes til at estimere seroincidence i tværsnitsstikprøven af
befolkningen. For både den langsgående måling og
tværsnitsmålingen af antistofkoncentrationer blev den indirekte ELISA
anvendt. Modellerne gælder kun for personer over 18 år.
Seroincidence-estimaterne er egnede til overvågning af effekten af
kontrolprogrammer, når repræsentative tværsnitsserumprøver er til rådighed
for analyser. Disse giver mere præcise oplysninger om infektionspres i
mennesker på tværs af lande.
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r-cran-sf
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Versions of package r-cran-sf |
Release | Version | Architectures |
bookworm | 1.0-9+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bullseye | 0.9-7+dfsg-5 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
sid | 1.0-17+dfsg-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch-backports | 0.6-3+dfsg-1~bpo9+1 | arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
stretch-backports | 0.7-2+dfsg-1~bpo9+1 | amd64 |
buster | 0.7-2+dfsg-1 | amd64,arm64,armhf,i386 |
upstream | 1.0-18 |
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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-datavisualisering for statistik indenfor social videnskab
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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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Samling af plot- og tabelfunktioner for datavisualisering. Resultater for diverse statistiske analyser (der ofte bruges i sociale videnskaber) kan visualiseres via denne pakke, inklusive simple og krydstabulerede frekvenser, histogrammer, boksplot, (generaliserede) lineære modeller, blandede effektmodeller, principel komponentanalyse og korrelationsmatricer, klyngeanalyser, punktplot, stakskalaer, effektplot for regressionsmodeller (inklusive interaktionstermer) og meget mere. Denne pakke understøtter data med etiketter.
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r-cran-surveillance
GNU R-pakke for modellering og overvågning af epidemiologiske udbrud
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Versions of package r-cran-surveillance |
Release | Version | Architectures |
jessie | 1.8-0-1 | amd64,armel,armhf,i386 |
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 |
sid | 1.24.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
trixie | 1.24.0-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
Debtags of package r-cran-surveillance: |
field | medicine |
interface | commandline |
role | program |
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License: DFSG free
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Implementering af statiske metoder for modellering og overvågning af tidsserier for antal, proportioner og kategoridata, samt modellering af fortsættende epidemiologiske udbrud.
The monitoring methods focus on aberration detection in count data time
series from public health surveillance of communicable diseases, but
applications could just as well originate from environmetrics,
reliability engineering, econometrics, or social sciences. The package
implements many typical outbreak detection procedures such as the
(improved) Farrington algorithm, or the negative binomial GLR-CUSUM
method of Höhle and Paul (2008) . A novel
CUSUM approach combining logistic and multinomial logistic modeling is
also included. The package contains several real-world data sets, the
ability to simulate outbreak data, and to visualize the results of the
monitoring in a temporal, spatial or spatio-temporal fashion. A recent
overview of the available monitoring procedures is given by Salmon et al.
(2016) .
For the retrospective analysis of epidemic spread, the package provides
three endemic-epidemic modeling frameworks with tools for visualization,
likelihood inference, and simulation. hhh4() estimates models for
(multivariate) count time series following Paul and Held (2011)
and Meyer and Held (2014)
. twinSIR() models the
susceptible-infectious-recovered (SIR) event history of a fixed
population, e.g, epidemics across farms or networks, as a multivariate
point process as proposed by Höhle (2009) .
twinstim() estimates self-exciting point process models for a
spatio-temporal point pattern of infective events, e.g., time-stamped
geo-referenced surveillance data, as proposed by Meyer et al. (2012)
. A recent overview of the
implemented space-time modeling frameworks for epidemic phenomena is
given by Meyer et al. (2017) .
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Official Debian packages with lower relevance
python3-epimodels
Simpel grænseflade til at simulere matematiske epidemiske modeller i Python 3
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Versions of package python3-epimodels |
Release | Version | Architectures |
bookworm | 0.4.0-1 | all |
sid | 0.4.0-4 | all |
trixie | 0.4.0-4 | all |
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License: DFSG free
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Dette bibliotek tilbyder en simpel grænseflade til at simulere matematiske epidemiske modeller i Python 3. Det er en betingelse for programmet epigrass.
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r-cran-cmprsk
GNU R-underdistributionsanalyse af konkurrerende risici
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Versions of package r-cran-cmprsk |
Release | Version | Architectures |
trixie | 2.2-11-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
stretch | 2.2-7-2 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
sid | 2.2-11-1 | amd64,arm64,armel,armhf,i386,mips64el,ppc64el,riscv64,s390x |
buster | 2.2-7-4 | amd64,arm64,armhf,i386 |
bullseye | 2.2-10-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 2.2-11-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
upstream | 2.2-12 |
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License: DFSG free
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Denne GNU R-pakker understøtter estimering, test og regressionsmodeller for underdistributionsfunktioner i konkurrerende risici, som beskrevet i Gray (1988), en klasse af K-prøvetest for sammenligning af de kumulative forekomster af en konkurrerende risiko.
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r-cran-msm
GNU R Multi-state Markov og skjulte Markovmodeller i sammenhængende tid
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Versions of package r-cran-msm |
Release | Version | Architectures |
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 |
stretch | 1.6.4-1 | amd64,arm64,armel,armhf,i386,mips,mips64el,mipsel,ppc64el,s390x |
jessie | 1.4-2 | amd64,armel,armhf,i386 |
bullseye | 1.6.8-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
bookworm | 1.7-1 | amd64,arm64,armel,armhf,i386,mips64el,mipsel,ppc64el,s390x |
buster | 1.6.6-2 | amd64,arm64,armhf,i386 |
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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Funktioner for tilpasning af generel Markov i sammenhængende tid og skjulte
Markov flertilstandsmodeller til data i længderetningen. Både
overgangsrater for Markov og den skjulte Markov-resultatproces kan
modelleres i form af kovariater. Et udvalg af observationsskemaer er
understøttet, inklusive processer observeret på arbitrære tidspunkter,
fuldstændig-observerede processer, og censorerede tilstande.
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shiny-server
Placer Shiny-internetprogrammer på nettet
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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 |
upstream | 1.5.23.1030 |
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License: DFSG free
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Shiny Server lader dig placere Shiny-internetprogrammer og interaktive dokumenter på nettet. Tag dine Shiny-programmer og del dem med din organisation eller verden.
Shiny Server lader dig gå bag statiske diagrammer, og lader dig manipulere dataene. Brugere kan sortere, filtrere eller ændre antagelser i realtid. Shiny-server giver dine brugere mulighed for at tilpasse din analyse for deres specifikke behov og trækker mere indblik ud af dine 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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