NobBS - Nowcasting by Bayesian Smoothing
A Bayesian approach to estimate the number of occurred-but-not-yet-reported cases from incomplete, time-stamped reporting data for disease outbreaks. 'NobBS' learns the reporting delay distribution and the time evolution of the epidemic curve to produce smoothed nowcasts in both stable and time-varying case reporting settings, as described in McGough et al. (2020) <doi:10.1371/journal.pcbi.1007735>.
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jagscpp
7.33 score 19 stars 47 scripts 467 downloads
tbl.now - Tidy Data and Workflow Layer for Epidemic Nowcasting
Defines tidy data structures and package-agnostic workflows for epidemiological nowcasting. The 'tbl_now' class records event, report, and revision dates alongside strata, covariates tagged by model component, censoring, and reporting-delay metadata while remaining compatible with 'dplyr'. Tools support validation, manipulation, diagnostics, visualization, format conversion, retrospective evaluation, and multiple modelling engines. The 'tbl_nowcast' class standardizes probabilistic predictions for plotting, scoring, comparison, and ensembling.
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data-analysisdiseasenowcastingepidemic-surveillanceepidemiologynowcastnowcastingpublic-healthpublic-health-surveillancetibbles
6.46 score 2 stars 1 dependents 40 scripts 155 downloads
diseasenowcasting - Nowcast Time Series of Epidemiological Cases
Implements Bayesian nowcasting models for incident disease cases using a censored point-process approach. The reporting delay is modelled directly as a stochastic process, jointly with the epidemic dynamics, via a censored likelihood. Inference uses RTMB (CppAD autodiff + Laplace approximation). Supports arbitrary epidemic models (including HSGP, AR1, SIR), arbitrary delay families (including LogNormal, GenGamma, Dirichlet), stratified data, extreme-delay detection, and backtesting.
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bayesian-nowcastingbayesian-statisticsdisease-monitoringepidemic-surveillanceepidemiological-modelsepidemiologynowcastnowcastingnowcasting-modelspublic-healthpublic-health-surveillancertmbtime-series
5.26 score 6 stars 19 scripts
deltapif - Estimate Potential Impact and Population Attributable Fractions with Aggregated Data
Uses the delta-method to estimate the Potential Impact Fraction (PIF) and the Population Attributable Fraction (PAF) from summary data. It creates point-estimates, confidence intervals, and estimates of the variance. Provides an extension to the aggregated data method in Chan, Zepeda-Tello et al (2025) <doi:10.1002/sim.70214>.
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4.90 score 2 stars 9 scripts 444 downloads