Debian Med Project
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Zusammenfassung
Epidemiology
Debian Med: Pakete mit Bezug zur Epidemiologie

Dieses Metapaket wird nützliche Werkzeuge für die epidemiologische Forschung installieren. Verschiedene Pakete nutzen die Datensprache GNU R für statistische Untersuchungen. Es könnte eine gute Idee sein, den Artikel »A short introduction to R for Epidemiology« bei http://staff.pubhealth.ku.dk/%7Ebxc/Epi/R-intro.pdf zu lesen.

Die Liste auf der rechten Seite enthält verschiedene Softwareprojekte, die für das Debian Med Projekt von Interesse sind. Derzeit sind nur einige von diesen als Debianpakete verfügbar. Zielsetzung ist es jedoch, all die Software für Debian Med zu paketieren, um einen qualitativ hochwertiges Debian Pure Blend (interne Anpassung von Debian an spezielle Bedürfnisse) zu erstellen.

Um einen besseren Überblick über die Verfügbarkeit der Projekte als Debian Paket zu geben, hat jede Kopfzeile einen Farbcode entsprechend diesem Schema:

Wenn Sie ein Projekt entdecken, das ein guter Kandidat für Debian Med zu sein scheint, oder wenn Sie ein inoffizielles Debianpaket erstellt haben, zögern Sie bitte nicht eine Beschreibung des Projekts an die Debian Med Mailingliste zu schicken.

Links zu Aufgaben

Debian Med Epidemiology packages

Offizielle Debianpakete mit hoher Relevanz

Epigrass
Wissenschaftliches Werkzeug für Simulationen und Szenarioanalyse im epidemiologischen Beziehungsnetz
Versions of package epigrass
ReleaseVersionArchitectures
sid2.0b3~dfsg-2all
squeeze2.0b3~dfsg-2all
lenny1.5.1-4all
Debtags of package epigrass:
fieldmedicine
interfacex11
roleprogram
scopeapplication
uitoolkitqt
useviewing, analysing
works-withdb
x11application
Popcon: 10 users (4 upd.)*
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Debtags
Lizenz: DFSG free
Svn

Epigrass ist eine Software für die Visualisierung, Analyse und Simulation von epidemischen Prozessen in georeferenzierten Netzen.

EpiGrass kann mit GRASS GIS interagieren, von wo es Karten und ähnliche geografische Informationen übernehmen kann. Trotzdem ist für die Nutzung der meisten Features von EpiGrass die Installation von GRASS GIS nicht erforderlich.

R-cran-epi
GNU R epidemiological analysis
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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.

R-cran-epibasix
GNU R Elementary Epidemiological Functions
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sid1.1-1+b1armel,mipsel,powerpc,i386,s390,amd64,sparc,alpha,ia64,mips,hppa
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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-epitools
GNU R Epidemiology Tools for Data and Graphics
Versions of package r-cran-epitools
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squeeze0.5.3-2all
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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.

Offizielle Debianpakete mit niedriger Relevanz

R-cran-msm
»GNU R«-Modelle Multi-State Markov und Hidden Markov in kontinuierlicher Zeit
Versions of package r-cran-msm
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sid0.9.3-1+b1armel,mipsel,powerpc,i386,s390,amd64,sparc,alpha,ia64,mips,hppa
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upstream0.9.4
Popcon: 18 users (45 upd.)*
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Lizenz: DFSG free
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Funktionen zur Parameterbestimmung von generellen zeitkontinuierlichen und Hidden-Markov-Multi-State-Modellen zu längslaufenden Daten. Sowohl Übergangsraten in Markov-Modellen als auch der Hidden-Markov-Ausgabeprozess können modelliert werden, innerhalb der Gesetze der Zusatzwerte (covariates). Eine Auswahl von Beobachtungsschemata wird unterstützt, inklusive Beobachtung von Prozessen zu beliebigen Zeiten, vollständig überwachte Prozesse und zensierte Stadien.

Debianpakete in contrib oder non-free

R-cran-surveillance
development and the evaluation of epidemiological outbreak detection algorithms
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The R-package 'surveillance' is a framework for the development and the evaluation of outbreak detection algorithms in univariate and multivariate routine collected public health surveillance data. It is hosted on CRAN..

The intention of the R-package surveillance is to provide open source software for the visualization and monitoring of count data time series in public health surveillance. Potential users are epidemiologists and others working in applied infectious disease epidemiology. Furthermore, surveillance also provides a data structure and framework for methodological developments of surveillance algorithms.

Paketierung hat begonnen und Entwickler könnten einen Versuch mit dem Code im VCS starten

Netepi-analysis
network-enabled tools for epidemiology and public health practice
Verantwortlich: Andreas Tille
Lizenz: MPL 1.1
Debianpaket nicht verfügbar
SVN

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.

There is also a Google code project page at http://code.google.com/p/netepi/

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
Verantwortlich: Andreas Tille
Lizenz: MPL 1.1
Debianpaket nicht verfügbar
SVN

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.

See also: http://www.stockholmchallenge.se/data/2123 and http://www.publish.csiro.au/?act=view_file&file_id=NB07103.pdf

*Pupularitätswetbewerbsergebnisse: Anzahl der Nutzer, die das Paket regelmäßig nutzen (Anzahl der Nutzer, die das Paket kürzlich aktualisiert haben) von insgesamt 89111