Outbreak Analysis & Epidemiological Investigation — outbreakanalysis • ClinicoPath

Comprehensive outbreak analysis and epidemiological investigation for infectious disease surveillance and public health research. Analyzes tabular outbreak data to identify attack rates, risk factors, epidemic curves, case-control associations, and spatial-temporal patterns. Essential for outbreak investigation, surveillance analysis, and epidemiological research with robust statistical methods for public health decision-making and intervention planning.

Usage

outbreakanalysis(
  data,
  case_status,
  exposure_vars,
  date_onset,
  location_var,
  person_id,
  age_var,
  sex_var,
  additional_vars,
  outbreak_type = "unknown",
  analysis_type = "combined",
  epidemic_curve_unit = "auto",
  attack_rate_analysis = TRUE,
  risk_factor_analysis = TRUE,
  dose_response_analysis = FALSE,
  temporal_analysis = TRUE,
  spatial_analysis = FALSE,
  statistical_tests = "all_tests",
  confidence_level = 0.95,
  multiple_testing_correction = "holm",
  stratified_analysis = FALSE,
  stratification_vars,
  case_definition = TRUE,
  incubation_period = FALSE,
  exposure_date_var,
  epidemic_curve_plot = TRUE,
  attack_rate_plot = TRUE,
  risk_factor_plot = TRUE,
  spatial_plot = FALSE,
  power_calculation = FALSE,
  sample_size_calculation = FALSE,
  sensitivity_analysis = FALSE,
  comprehensive_report = TRUE,
  public_health_summary = TRUE,
  surveillance_indicators = FALSE,
  data_quality_assessment = TRUE,
  strobe_compliance = TRUE,
  export_for_epiinfo = FALSE
)

Arguments

data: the data as a data frame
case_status: Binary variable indicating case (1) vs control (0) or case vs non-case
exposure_vars: Variables representing potential exposures or risk factors
date_onset: Date of symptom onset or case identification
location_var: Geographic location or administrative unit
person_id: Unique identifier for each individual
age_var: Age of individuals for demographic analysis
sex_var: Sex/gender variable for demographic analysis
additional_vars: Additional variables for descriptive analysis
outbreak_type: Type of outbreak pattern expected
analysis_type: Primary analytical approach for outbreak investigation
epidemic_curve_unit: Time unit for epidemic curve construction
attack_rate_analysis: Calculate attack rates and 95\ intervals
risk_factor_analysis: Perform risk factor analysis with odds ratios and relative risks
dose_response_analysis: Analyze dose-response relationships for quantitative exposures
temporal_analysis: Analyze temporal patterns and epidemic curve characteristics
spatial_analysis: Perform spatial analysis and clustering detection
statistical_tests: Statistical tests for association analysis
confidence_level: Confidence level for confidence intervals
multiple_testing_correction: Multiple testing correction method
stratified_analysis: Perform stratified analysis by demographic variables
stratification_vars: Variables for stratified analysis
case_definition: Analyze case definition sensitivity and specificity
incubation_period: Calculate incubation period statistics
exposure_date_var: Date of exposure for incubation period calculation
epidemic_curve_plot: Generate epidemic curve visualization
attack_rate_plot: Generate attack rate comparison plots
risk_factor_plot: Generate forest plot of risk factors
spatial_plot: Generate spatial distribution maps
power_calculation: Calculate statistical power for detected associations
sample_size_calculation: Provide sample size recommendations for future studies
sensitivity_analysis: Perform sensitivity analysis for case definitions
comprehensive_report: Generate comprehensive outbreak investigation report
public_health_summary: Generate public health summary with recommendations
surveillance_indicators: Calculate surveillance system quality indicators
data_quality_assessment: Assess data completeness and quality issues
strobe_compliance: Ensure STROBE guideline compliance for epidemiological reporting
export_for_epiinfo: Export results in EpiInfo compatible format

Value

A results object containing:

`results$outbreak_overview`					a table
`results$descriptive_summary`					a table
`results$risk_factor_analysis`					a table
`results$temporal_analysis`					a table
`results$epidemic_curve_stats`					a table
`results$spatial_analysis_results`					a table
`results$dose_response_analysis`					a table
`results$stratified_analysis_results`					a table
`results$incubation_period_stats`					a table
`results$case_definition_analysis`					a table
`results$data_quality_report`					a table
`results$power_analysis_results`					a table
`results$surveillance_indicators`					a table
`results$epidemic_curve_plot`					an image
`results$attack_rate_plot`					an image
`results$risk_factor_forest_plot`					an image
`results$spatial_distribution_plot`					an image
`results$dose_response_plot`					an image
`results$outbreak_timeline_plot`					an image
`results$comprehensive_report`					a html
`results$public_health_summary`					a html

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$outbreak_overview$asDF

as.data.frame(results$outbreak_overview)

Examples

data('outbreak_data')

outbreakanalysis(
    data = outbreak_data,
    case_status = "case",
    exposure_vars = c("food_a", "food_b", "water"),
    date_onset = "onset_date",
    location_var = "location"
)