Package: RSurveillance 0.2.1

RSurveillance: Design and Analysis of Disease Surveillance Activities

A range of functions for the design and analysis of disease surveillance activities. These functions were originally developed for animal health surveillance activities but can be equally applied to aquatic animal, wildlife, plant and human health surveillance activities. Utilities are included for sample size calculation and analysis of representative surveys for disease freedom, risk-based studies for disease freedom and for prevalence estimation. This package is based on Cameron A., Conraths F., Frohlich A., Schauer B., Schulz K., Sergeant E., Sonnenburg J., Staubach C. (2015). R package of functions for risk-based surveillance. Deliverable 6.24, WP 6 - Decision making tools for implementing risk-based surveillance, Grant Number no. 310806, RISKSUR (<https://www.fp7-risksur.eu/sites/default/files/documents/Deliverables/RISKSUR_%28310806%29_D6.24.pdf>). Many of the 'RSurveillance' functions are incorporated into the 'epitools' website: Sergeant, ESG, 2019. Epitools epidemiological calculators. Ausvet Pty Ltd. Available at: <http://epitools.ausvet.com.au>.

Authors:Evan Sergeant

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RSurveillance.pdf |RSurveillance.html✨
RSurveillance/json (API)

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

Peer review:

Bug tracker:https://github.com/rostats/rsurveillance/issues

On CRAN:

3.98 score 64 scripts 188 downloads 3 mentions 58 exports 124 dependencies

Last updated 4 years agofrom:42b02e5cd2. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 10 2024
R-4.5-winNOTEOct 10 2024
R-4.5-linuxNOTEOct 10 2024
R-4.4-winNOTEOct 10 2024
R-4.4-macNOTEOct 10 2024
R-4.3-winNOTEOct 10 2024
R-4.3-macNOTEOct 10 2024

Exports:adj.riskadj.risk.simapbinom.agrestibinom.cpbinom.jeffreysdisc.priorepi.calcn.2stagen.apn.binomn.c.freecalcn.c.hpn.freecalcn.freedomn.hpn.hypergeon.pfreen.pooledn.rbn.rb.2stage.1n.rb.2stage.2n.rb.varsen.tppfree.1pfree.calcpfree.equpstar.calcse.parallelse.seriessepsep.binomsep.binom.imperfectsep.exactsep.freecalcsep.hpsep.hypergeosep.passivesep.pfreesep.pooledsep.priorsep.rb.binsep.rb.bin.varsesep.rb.hypergeosep.rb.hypergeo.varsesep.rb2.binomsep.rb2.hypergeosep.syssep.var.sesp.parallelsp.seriessph.binomsph.hpsppsse.combinedsse.rb.2stagetptp.normal

Dependencies:abindaskpassbackportsbase64encBiasedUrnbootbroombslibcachemcarcarDataclassclassIntclicolorspacecorrplotcowplotcpp11data.tableDBIDerivdigestdoBydplyre1071epiRepitoolsevaluatefansifarverfastmapflextablefontawesomefontBitstreamVerafontLiberationfontquiverFormulafsgdtoolsgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtablehighrhtmltoolsisobandjquerylibjsonliteKernSmoothknitrlabelinglatticelifecyclelme4lubridatemagrittrMASSMatrixMatrixModelsmc2dmemoisemgcvmicrobenchmarkmimeminqamodelrmunsellmvtnormnlmenloptrnnetnumDerivofficeropensslpanderpbkrtestpillarpkgconfigpolynomproxypurrrquantregR6raggrappdirsRColorBrewerRcppRcppEigenrlangrmarkdownrstatixs2sassscalessfSparseMstringistringrsurvivalsyssystemfontstextshapingtibbletidyrtidyselecttimechangetinytexunitsutf8uuidvctrsviridisLitewithrwkxfunxml2yamlzipzoo

Readme and manuals

Help Manual

Help pageTopics
Adjusted riskadj.risk
Adjusted risk for simulation modelsadj.risk.sim
Apparent prevalenceap
Agresti-Coull confidence limitsbinom.agresti
Clopper-Pearson exact confidence limitsbinom.cp
Jeffreys confidence limitsbinom.jeffreys
Discounted prior probability of freedomdisc.prior
Effective probability of infection (EPI)epi.calc
2-stage freedom sample sizen.2stage
Sample size for apparent prevalencen.ap
Binomial sample sizen.binom
Freecalc optimum sample size and cut-point number of positivesn.c.freecalc
Hypergeometric (HerdPlus) optimum sample size and cut-point number of positivesn.c.hp
Freecalc sample size for a finite population and specified cut-point number of positivesn.freecalc
Freedom sample sizen.freedom
Hypergeometric (HerdPlus) sample size for finite population and specified cut-point number of positivesn.hp
Hypergeometric sample sizen.hypergeo
Sample size to achieve desired (posterior) probability of freedomn.pfree
Sample size for pooled testing for freedomn.pooled
Risk-based sample sizen.rb
sample size for 2-stage risk-based surveillance, risk factor at cluster level onlyn.rb.2stage.1
Sample size for 2-stage risk-based surveillance, allowing for risk factors at either or both cluster and unit leveln.rb.2stage.2
Risk-based sample size for varying unit sensitivityn.rb.varse
Sample size for true prevalencen.tp
Probability of freedom for single time periodpfree.1
Probability of freedom over timepfree.calc
Equilibrium probability of freedompfree.equ
Design prevalence back-calculationpstar.calc
Sensitivity of tests in parallelse.parallel
Sensitivity of tests in seriesse.series
Population sensitivitysep
Binomial Population sensitivitysep.binom
Binomial population sensitivity for imperfect testsep.binom.imperfect
Population sensitivity for census (all units tested)sep.exact
FreeCalc population sensitivity for imperfect testsep.freecalc
Hypergeometric (HerdPlus) population sensitivity for imperfect testsep.hp
Hypergeometric Population sensitivitysep.hypergeo
Passive surveillance sensitivitysep.passive
Population sensitivity to achieve desired (posterior) probability of freedomsep.pfree
Pooled population sensitivitysep.pooled
Population sensitivity to achieve desired prior probability of freedomsep.prior
Binomial risk-based population sensitivitysep.rb.bin
Binomial risk-based population sensitivity for varying unit sensitivitysep.rb.bin.varse
Hypergeometric risk-based population sensitivitysep.rb.hypergeo
Hypergeometric risk-based population sensitivity for varying unit sensitivitysep.rb.hypergeo.varse
Binomial risk-based population sensitivity for 2 risk factorssep.rb2.binom
Hypergeometric risk-based population sensitivity for 2 risk factorssep.rb2.hypergeo
2-stage population sensitivitysep.sys
Population sensitivity for varying unit sensitivitysep.var.se
Specificity of tests in parallelsp.parallel
Specficity of tests in seriessp.series
Binomial population specificity for imperfect testsph.binom
Hypergeometric population specificity calculationsph.hp
Population specificityspp
System sensitivity by combining multiple surveillance componentssse.combined
Two-stage risk-based system sensitivitysse.rb.2stage
True prevalencetp
Normal approximation confidence limits for true prevalencetp.normal