surveil: Time Series Models for Disease Surveillance

Fits time trend models for routine disease surveillance tasks and returns probability distributions for a variety of quantities of interest, including age-standardized rates, period and cumulative percent change, and measures of health inequality. The models are appropriate for count data such as disease incidence and mortality data, employing a Poisson or binomial likelihood and the first-difference (random-walk) prior for unknown risk. Optionally add a covariance matrix for multiple, correlated time series models. Inference is completed using Markov chain Monte Carlo via the Stan modeling language. References: Donegan, Hughes, and Lee (2022) <doi:10.2196/34589>; Stan Development Team (2021) <>; Theil (1972, ISBN:0-444-10378-3).

Version: 0.3.0
Depends: R (≥ 3.5.0)
Imports: rstantools (≥ 2.1.1), methods, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), tidybayes (≥ 3.0.0), dplyr (≥ 1.0.7), rlang (≥ 0.4.0), tidyr (≥ 1.1.0), ggplot2 (≥ 3.0.0), gridExtra (≥ 2.0), scales (≥ 0.4.0), ggdist (≥ 3.0.0)
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥, RcppParallel (≥ 5.0.1), rstan (≥ 2.26.0), StanHeaders (≥ 2.26.0)
Suggests: rmarkdown, knitr, testthat
Published: 2024-07-08
DOI: 10.32614/CRAN.package.surveil
Author: Connor Donegan ORCID iD [aut, cre]
Maintainer: Connor Donegan <connor.donegan at>
License: GPL (≥ 3)
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: surveil citation info
Materials: README NEWS
CRAN checks: surveil results


Reference manual: surveil.pdf
Vignettes: Age-standardized rates
Measuring health inequality
Using surveil for public health research
MCMC with surveil


Package source: surveil_0.3.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): surveil_0.3.0.tgz, r-oldrel (arm64): surveil_0.3.0.tgz, r-release (x86_64): surveil_0.3.0.tgz, r-oldrel (x86_64): surveil_0.3.0.tgz
Old sources: surveil archive


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