v0.1.0 — First Stable Release

survinger 0.1.0

Design-Adjusted Inference for Pathogen Lineage Surveillance

Installation

remotes::install_github("CuiweiG/survinger@v0.1.0")

Highlights

Core Statistical Methods

• Hajek prevalence estimator — exact match with survey::svymean (Lumley 2004)
• Wilson score intervals — 93.4% coverage (Agresti & Coull 1998), never zero-width
• Right-truncation MLE — 0.5% parameter recovery error (Lawless 2003)
• Neyman allocation — 27% MSE reduction vs equal allocation (Cochran 1977)
• Detection formula — exact match with analytical solution (Nicholson et al. 2022)

Validated on Real Data

• ECDC: 99,093 sequences, 5 EU countries, 40-fold sequencing inequality
• COG-UK: 65,166 individual sequences, 4 UK nations
• Design weighting corrects up to 14 percentage points of bias on real data

Package Statistics

Metric	Value
Public functions	30
S3 methods	28
Tests	155 (0 failures)
Vignettes	4
Publication figures	10
R CMD check	0 errors, 0 warnings, 0 notes
Package size	2.22 MB

Key Functions

Function	Purpose
surv_design()	Create surveillance design with inverse-probability weights
surv_lineage_prevalence()	Hajek / HT / post-stratified prevalence estimation
surv_optimize_allocation()	Neyman allocation (min_mse / max_detection / min_imbalance)
surv_estimate_delay()	Right-truncation-corrected delay distribution fitting
surv_adjusted_prevalence()	Combined design + delay correction
surv_report()	Comprehensive surveillance system diagnostic
surv_quality()	One-row quality metrics (Gini, DEFF, detection power)
surv_sensitivity()	Cross-method robustness analysis
surv_power_curve()	Detection power curve with plot method
tidy() / glance()	Broom-style tidyverse integration
theme_survinger()	Publication-quality ggplot2 theme

Vignettes

• Introduction to survinger
• Optimizing Sequencing Resource Allocation
• Delay-Adjusted Nowcasting
• Real-World Case Study: European COVID-19 Genomic Surveillance

References

• Cochran WG (1977) Sampling Techniques
• Lumley T (2004) J Stat Software — survey package
• Wilson EB (1927) JASA — score intervals
• Agresti A & Coull BA (1998) The American Statistician
• Nicholson et al. (2022) BMC Bioinformatics — phylosamp
• Lawless JF (2003) Statistical Models and Methods for Lifetime Data