sir_data

A dataset containing simulated SIR model outputs for a population of 1000.

datasets

Integrates methods for epidemiological analysis, modeling, and visualization, including functions for summary statistics, SIR (Susceptible-Infectious-Recovered) modeling, DALY (Disability-Adjusted Life Years) estimation, age standardization, diagnostic test evaluation, NLP (Natural Language Processing) keyword extraction, clinical trial power analysis, survival analysis, SNP (Single Nucleotide Polymorphism) association, and machine learning methods such as logistic regression, k-means clustering, Random Forest, and Support Vector Machine (SVM). Includes datasets for prevalence estimation, SIR modeling, genomic analysis, clinical trials, DALY, diagnostic tests, and survival analysis. Methods are based on Gelman et al. (2013) <doi:10.1201/b16018> and Wickham et al. (2019, ISBN:9781492052040>.

Esther Atsabina Wanjala

EpidigiR

Digital Epidemiological Analysis and Visualization Tools

sir_data function

A data frame with 50 rows and 4 columns:<dl>
 <dt>time</dt>
<dd>Numeric, time point (1 to 50 days).</dd> <dt>Susceptible</dt>
<dd>Numeric, number of susceptible individuals.</dd> <dt>Infected</dt>
<dd>Numeric, number of infected individuals.</dd> <dt>Recovered</dt>
<dd>Numeric, number of recovered individuals.</dd>
</dl>

Format

SIR Model Simulation Data — sir_data

A data frame with 50 rows and 4 columns:<dl>
 <dt>time</dt>
<dd>Numeric, time point (1 to 50 days).</dd>

 <dt>Susceptible</dt>
<dd>Numeric, number of susceptible individuals.</dd>

 <dt>Infected</dt>
<dd>Numeric, number of infected individuals.</dd>

 <dt>Recovered</dt>
<dd>Numeric, number of recovered individuals.</dd>


</dl>

sir_data: SIR Model Simulation Data

Description

Usage

Arguments

Format

Examples