tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of epidemics and Tplyr — release velocity, themes, recent moves, and the top alternatives to consider.
epidemics swapped its C++ engine for odin — and quietly inverted how contact matrices must be passed.
epidemics ships composable compartmental model structures — default SEIR-V, Vacamole, diphtheria and Ebola — with classes for populations, interventions and vaccination campaigns. After more than two years without a release, 0.5.0 landed in July 2026 carrying both an engine migration and a breaking input-convention change. Maintainership moved to a new lead back in 0.4.0.
Tplyr made clinical summary tables explain where every number came from.
Tplyr builds clinical summary tables through a layered grammar — count, descriptive statistics, and shift layers assembled onto a table object. The 1.0.0 release added a traceability metadata framework that lets a user ask which source rows produced any given cell, and later releases extended it to cases the first pass missed. The package is maintained by Atorus within the pharmaverse ecosystem.
epidemics ships composable compartmental model structures — default SEIR-V, Vacamole, diphtheria and Ebola — with classes for populations, interventions and vaccination campaigns. After more than two years without a release, 0.5.0 landed in July 2026 carrying both an engine migration and a breaking input-convention change. Maintainership moved to a new lead back in 0.4.0.
The package's history is a sequence of deliberate breaking releases: 0.2.0 renamed every model function and vectorised the ODE models, 0.3.0 restructured the Ebola model into two levels and made replicates the default, and 0.5.0 rewrites the compiled core. The direction is toward a smaller, more declarative model definition layer with the numerical work delegated to a dedicated tool.
With the default, Vacamole and diphtheria systems now declared in odin, the Ebola model is the obvious remaining candidate for the same treatment.
Tplyr builds clinical summary tables through a layered grammar — count, descriptive statistics, and shift layers assembled onto a table object. The 1.0.0 release added a traceability metadata framework that lets a user ask which source rows produced any given cell, and later releases extended it to cases the first pass missed. The package is maintained by Atorus within the pharmaverse ecosystem.
Post-1.0 work has been about completing the metadata story and filling gaps in layer composition rather than adding table types — metadata for missing subjects, add_anti_join(), missing-subject rows, data limiting, and fixes to nested count layers where an inner value appears under several outer groups. Releases cluster tightly after a major version, then go quiet, and the window ends with a patch issued days after the release it corrects.
Further releases will most likely continue closing traceability and nested-layer edge cases rather than introducing new layer types, following the pattern of both post-1.0 feature releases.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either epidemics or Tplyr.
A tables-listings-graphs package that reached CRAN and then went quiet.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
See all epidemics alternatives → · See all Tplyr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. epidemics is currently shipping more aggressively (velocity 3.8 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. epidemics is currently shipping more aggressively (velocity 3.8 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top epidemics alternatives in Analytics are ranked by recent ship velocity. Browse the "epidemics alternatives" section above for the current picks, or visit /alternatives/epidemics for the full list with editorial commentary on each.
Top Tplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "Tplyr alternatives" section above for the current picks, or visit /alternatives/tplyr for the full list with editorial commentary on each.