Package: epiflows 0.2.1
Pawel Piatkowski
epiflows: Predicting Disease Spread from Flow Data
Provides functions and classes designed to handle and visualise epidemiological flows between locations. Also contains a statistical method for predicting disease spread from flow data initially described in Dorigatti et al. (2017) <doi:10.2807/1560-7917.ES.2017.22.28.30572>. This package is part of the RECON (<https://www.repidemicsconsortium.org/>) toolkit for outbreak analysis.
Authors:
epiflows_0.2.1.tar.gz
epiflows_0.2.1.zip(r-4.5)epiflows_0.2.1.zip(r-4.4)epiflows_0.2.1.zip(r-4.3)
epiflows_0.2.1.tgz(r-4.4-any)epiflows_0.2.1.tgz(r-4.3-any)
epiflows_0.2.1.tar.gz(r-4.5-noble)epiflows_0.2.1.tar.gz(r-4.4-noble)
epiflows_0.2.1.tgz(r-4.4-emscripten)epiflows_0.2.1.tgz(r-4.3-emscripten)
epiflows.pdf |epiflows.html✨
epiflows/json (API)
NEWS
| # Install 'epiflows' in R: |
| install.packages('epiflows', repos = c('https://epiverse-connect.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/reconhub/epiflows/issues
- Brazil_epiflows - Yellow Fever Data from Brazil; 2016-12 to 2017-05
- YF_Brazil - Yellow Fever Data from Brazil; 2016-12 to 2017-05
- YF_coordinates - Yellow Fever Data from Brazil; 2016-12 to 2017-05
- YF_flows - Yellow Fever Data from Brazil; 2016-12 to 2017-05
- YF_locations - Yellow Fever Data from Brazil; 2016-12 to 2017-05
Last updated 1 years agofrom:2fdb4d22d8. Checks:OK: 5 NOTE: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 09 2024 |
| R-4.5-win | NOTE | Nov 09 2024 |
| R-4.5-linux | NOTE | Nov 09 2024 |
| R-4.4-win | OK | Nov 09 2024 |
| R-4.4-mac | OK | Nov 09 2024 |
| R-4.3-win | OK | Nov 09 2024 |
| R-4.3-mac | OK | Nov 09 2024 |
Exports:add_coordinatesas.SpatialLinesDataFrameestimate_risk_spreadget_coordinatesget_flowsget_idget_locationsget_nget_pop_sizeget_varsglobal_varsgrid_epiflowsmake_epiflowsmap_epiflowsset_varsset_vars<-vis_epiflows
Dependencies:askpassbase64encbitopsbslibcachemclicolorspacecpp11crosstalkcurldigestdplyrepicontactsevaluatefansifarverfastmapfontawesomefsgenericsgeosphereggmapggplot2gluegtablehighrhtmltoolshtmlwidgetshttrigraphisobandjpegjquerylibjsonliteknitrlabelinglatticelazyevalleafletleaflet.providerslifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplyrpngpurrrR6rappdirsrasterRColorBrewerRcpprlangrmarkdownsassscalesspstringistringrsysterrathreejstibbletidyrtidyselecttinytexutf8vctrsviridisLitevisNetworkwithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Subset `epiflows` objects | [.epiflows |
| Add/Retrieve location coordinates | add_coordinates get_coordinates get_coordinates.epiflows |
| Convert to SpatialLinesDataFrame class | as.SpatialLinesDataFrame as.SpatialLinesDataFrame.epiflows |
| epiflows | epiflows |
| Travel-related disease cases spreaded to other locations from an infectious location | estimate_risk_spread estimate_risk_spread.default estimate_risk_spread.epiflows |
| Access flow data | get_flows get_flows.epiflows |
| Access population identifiers in epiflows objects | get_id |
| Access flow data | get_locations get_locations.epiflows |
| get the number of cases per flow | get_n get_n.epiflows |
| Get population size for each entry in locations | get_pop_size get_pop_size.epiflows |
| Access location metadata | get_vars get_vars.epiflows set_vars set_vars.epiflows set_vars<- set_vars<-.epiflows |
| Epiflow Global Variables | epiflows.vars global_vars |
| Visualise epidemic flows using a grid | grid_epiflows |
| Create an epiflows object | make_epiflows make_epiflows.data.frame make_epiflows.integer make_epiflows.numeric |
| Map flows of people between locations | map_epiflows |
| Various plots for epiflows objects | plot.epiflows |
| Print method from epiflows objects | print.epiflows |
| Visualise epidemic flows using visNetwork | vis_epiflows |
| Yellow Fever Data from Brazil; 2016-12 to 2017-05 | Brazil_epiflows YF_Brazil YF_coordinates YF_flows YF_locations |