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EpiNow2 vs gtsummary

A side-by-side editorial comparison of EpiNow2 and gtsummary — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

EpiNow2 vs gtsummary: at a glance

FeatureEpiNow2gtsummary
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesepidemiology, bayesian-modelling, reproduction-number, r-packageclinical-tables, analysis-results-data, regression-summaries, reproducible-reporting
Last editorial update5h ago1h ago
WebsiteVisit →Visit →

What is EpiNow2?

EpiNow2 unified its model interface, then went back to deepen the estimators behind it

EpiNow2 estimates reproduction numbers, infections and delay distributions from incomplete epidemiological reporting data. 1.8.0 was the structural turning point: every main modelling function now returns a consistent S3 object with `fit`, `args` and `observations`, reachable through shared accessors. The releases either side of it work on estimator quality — accumulation of irregularly reported data in 1.7.0, and a substantial expansion of `estimate_truncation()` in 1.9.0.

Read the full EpiNow2 trajectory →

What is gtsummary?

gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.

gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.

Read the full gtsummary trajectory →

EpiNow2 vs gtsummary: editorial side-by-side

E
EpiNow2
ANALYTICS
0.0

EpiNow2 unified its model interface, then went back to deepen the estimators behind it

◆ Current state

EpiNow2 estimates reproduction numbers, infections and delay distributions from incomplete epidemiological reporting data. 1.8.0 was the structural turning point: every main modelling function now returns a consistent S3 object with `fit`, `args` and `observations`, reachable through shared accessors. The releases either side of it work on estimator quality — accumulation of irregularly reported data in 1.7.0, and a substantial expansion of `estimate_truncation()` in 1.9.0.

◆ Where it's heading

The package spent this window paying down interface debt and is now extending from the tidier base. Options that existed only for `estimate_infections()` have been propagated outward: `estimate_truncation()` gained the full `dist_spec` delay families, `obs_opts()` observation model selection between Poisson and negative binomial, and the `likelihood` and `return_likelihood` settings that make prior-only fits and loo-compatible output possible. Hardcoded assumptions are being replaced by specifiable ones in the same motion — the truncation model's additive noise term was a fixed `sigma ~ normal(0, 1)` prior and is now a `dist_spec` argument.

◆ Prediction

Expect the remaining modelling functions to keep converging on the shared options interface, since the last two releases have each moved another function onto it. A new `estimate_dist()` for interval-censored linelist data suggests delay estimation is the area still gaining surface.

G
gtsummary
ANALYTICS
0.0

gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.

◆ Current state

gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.

◆ Where it's heading

The ARD work is the through-line. Table IDs exist so gather_ard() can return a named list; hierarchical tables gained per-level sorting and targeted filtering; ARD inputs are pre-processed so sorting applies to non-standard shapes. The package is becoming a structured-results engine that happens to render tables, rather than a renderer alone. Alongside that, 2.2.0 restored data pre-processing that 2.0 had removed after the reduced functionality hurt users — a maintainer willing to reverse a major-version decision.

◆ Prediction

Expect the hierarchical and ARD functions, introduced as a preview without a full deprecation cycle, to keep stabilizing toward a settled API rather than new table types appearing.

Alternatives to EpiNow2 and gtsummary

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 EpiNow2 or gtsummary.

See all EpiNow2 alternatives → · See all gtsummary alternatives →

Recent activity from EpiNow2 and gtsummary

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agoEpiNow2estimate_truncation gains full delay and observation options
  2. 2mo agogtsummaryTheme elements no longer evaluated by default
  3. 6mo agoEpiNow2Unified return objects and shared accessors across all models
  4. 8mo agogtsummaryARD strata functions and finer theme control
  5. 11mo agogtsummaryPer-level hierarchical sorting and labeled stacking
  6. 1y agogtsummaryTable splitting, ID labeling, and add_difference_row
  7. 1y agogtsummaryData pre-processing restored after the 2.0 removal
  8. 1y agoEpiNow2Patch for an upstream rstan issue
  9. 1y agogtsummarytbl_merge gains explicit merge columns
  10. 1y agoEpiNow2Accumulation for irregularly reported data; unified priors
  11. 1y agoEpiNow2Matern kernel spectral density fix and GP prior revert
  12. 1y agoEpiNow2Gaussian Process model improvements and explicit defaults

Frequently asked questions

What is the difference between EpiNow2 and gtsummary?

Both compete on the same themes — r-package — within Analytics. EpiNow2 and gtsummary are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is EpiNow2 better than gtsummary?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. EpiNow2 and gtsummary are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to EpiNow2?

Top EpiNow2 alternatives in Analytics are ranked by recent ship velocity. Browse the "EpiNow2 alternatives" section above for the current picks, or visit /alternatives/epinow2 for the full list with editorial commentary on each.

What are the best alternatives to gtsummary?

Top gtsummary alternatives in Analytics are ranked by recent ship velocity. Browse the "gtsummary alternatives" section above for the current picks, or visit /alternatives/gtsummary-r for the full list with editorial commentary on each.