Setup | Introduction | Estimating the Serial Interval | Simulated Data Example | Advanced Features: Convergence Diagnostics and Multiple Restarts | Convergence Diagnostics | Multiple Restarts for Robust Estimation | Real Data Example: Scabies Outbreaks | Estimating Time-Varying Reproduction Number (Rt) | Method details | Understanding the 'shift' Parameter | Real Data Example | Zika outbreak in Giradot, Colombia (2015) | References
Package: mitey 0.4.0
mitey: Serial Interval and Case Reproduction Number Estimation
Provides methods to estimate serial intervals and time-varying case reproduction numbers from infectious disease outbreak data. Serial intervals measure the time between symptom onset in linked transmission pairs, while case reproduction numbers quantify how many secondary cases each infected individual generates over time. These parameters are essential for understanding transmission dynamics, evaluating control measures, and informing public health responses. The package implements the maximum likelihood framework from Vink et al. (2014) <doi:10.1093/aje/kwu209> for serial interval estimation and the retrospective method from Wallinga & Lipsitch (2007) <doi:10.1098/rspb.2006.3754> for reproduction number estimation. Originally developed for scabies transmission analysis but applicable to other infectious diseases including influenza, COVID-19, and emerging pathogens. Designed for epidemiologists, public health researchers, and infectious disease modelers working with outbreak surveillance data.
Authors:
mitey_0.4.0.tar.gz
mitey_0.4.0.zip(r-4.7)mitey_0.4.0.zip(r-4.6)mitey_0.4.0.zip(r-4.5)
mitey_0.4.0.tgz(r-4.6-any)mitey_0.4.0.tgz(r-4.5-any)
mitey_0.4.0.tar.gz(r-4.7-any)mitey_0.4.0.tar.gz(r-4.6-any)
mitey_0.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mitey/json (API)
| # Install 'mitey' in R: |
| install.packages('mitey', repos = c('https://kylieainslie.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kylieainslie/mitey/issues
Pkgdown/docs site:https://kylieainslie.github.io
Last updated from:62b60ee9a1. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 202 | ||
| source / vignettes | OK | 287 | ||
| linux-release-x86_64 | OK | 204 | ||
| macos-release-arm64 | OK | 125 | ||
| macos-oldrel-arm64 | OK | 127 | ||
| windows-devel | OK | 178 | ||
| windows-release | OK | 164 | ||
| windows-oldrel | OK | 155 | ||
| wasm-release | OK | 163 |
Exports:compare_n_routesgenerate_synthetic_epidemicplot_si_fitplot_si_fit_resultsi_estimwallinga_lipsitch
Dependencies:clicpp11farverfdrtoolggplot2gluegtableisobandlabelinglifecycleR6RColorBrewerrlangS7scalesvctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Compare Serial Interval Models Across Different Numbers of Transmission Routes | compare_n_routes |
| Generate Synthetic Epidemic Data Using the Renewal Equation | generate_synthetic_epidemic |
| Visualize Serial Interval Distribution Fit to Outbreak Data | plot_si_fit |
| Plot Serial Interval Fit from si_estim Result | plot_si_fit_result |
| Estimate Serial Interval Distribution Using the Vink Method | si_estim |
| Apply Moving Average Smoothing to R Estimates | smooth_estimates |
| Estimate Time-Varying Case Reproduction Number Using Wallinga-Lipsitch Method | wallinga_lipsitch |
