Helps create alerts and determine trends by using various methods to analyze public health surveillance data. The primary analysis method is based upon a published analytics strategy by Benedetti (2019) <doi:10.5588/pha.19.0002>.

Implements Monte Carlo conditional inference for the parameters of a linear nonnormal regression model.

Implements the Cumulative Standardized Binomial Exponentially Weighted Moving Average (CSB-EWMA) control chart for monitoring multiple independent streams with binomial outcomes. Provides exact variance calculations, adaptive control limits, post-hoc identification with multiple testing corrections (Bonferroni, Holm, Benjamini-Hochberg), and visualization tools. The method is described in Muritala et al. (2026) <doi:10.48550/arXiv.2601.09968>.

Calculate the confidence interval and p value for change in C-statistic. The adjusted C-statistic is calculated by using formula as "Somers' Dxy rank correlation"/2+0.5. The confidence interval was calculated by using the bootstrap method. The p value was calculated by using the Z testing method. Please refer to the article of Peter Ganz et al. (2016) <doi:10.1001/jama.2016.5951>.

Calculates pointwise confidence intervals for the cumulative distribution function of the event time for current status data, data where each individual is assessed at one time to see if they had the event or not by the assessment time.

Germline and somatic locus data which contain the total read depth and B allele 
    read depth using Bayesian model (Dirichlet Process) to cluster. Meanwhile, the cluster 
    model can deal with the SNVs mutation and the CNAs mutation.

Flexible tools to fit, tune and obtain absolute risk predictions from regularized cause-specific cox models with elastic-net penalty.

Datasets relating to population in municipalities, municipality/county matching, and how different municipalities have merged/redistricted over time from 2006 to 2024.

Provides object-oriented database management tools for working with large datasets across multiple database systems. Features include robust connection management for 'PostgreSQL' databases, advanced table operations with bulk data loading and upsert functionality, comprehensive data validation through customizable field type and content validators, efficient index management, and cross-database compatibility. Designed for high-performance data operations in surveillance systems and large-scale data processing workflows.