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Tuberculosis Burden Analysis (Korea vs. Global, 1990–2021)

This repository contains the source code and data datasets used in the study: "Tuberculosis burden in Korea compared with global trends, 1990–2021: a comparative ecological time-trend study."

The analysis includes temporal trend assessment using Joinpoint regression, Age-Period-Cohort (APC) analysis, and future forecasting using ARIMA models.

📂 Repository Structure

The project is organized into the following directories corresponding to the analysis steps described in the manuscript:

  • 1_data_merge/: Scripts for data cleaning and merging raw datasets extracted from the GBD 2021 results tool.
  • 2_Table1/: Code for generating the baseline characteristics and summary statistics (Table 1 in the manuscript).
  • 3_age_gender/: Scripts for analyzing and visualizing age- and gender-specific TB burden (related to Figures 2 & 3).
  • 4_dual_axis/: Visualization scripts for dual-axis plots used in the study.
  • 5_Joinpoint/: Data preparation and settings for the Joinpoint Regression Program.
  • 6_APC/: R scripts for the Age-Period-Cohort analysis (Wald test, model fitting).
  • 7_ARIMA/: R scripts for the ARIMA forecasting models (forecasting TB incidence and mortality through 2030).
  • GBD_population/ & tuberculosis_dalys_data.xlsx: Raw data files used as input for the analyses.

🛠️ Software & Requirements

The analysis was performed using the following software:

  • R Statistical Software (for APC analysis, ARIMA forecasting, and data visualization).
    • Key packages: forecast, tseries, ggplot2, apc, etc.
  • Joinpoint Regression Program (Version 5.2.0, National Cancer Institute).

🚀 How to Use

  1. Data Preparation: Ensure the raw data files (.xlsx or .csv) are located in the root directory or the respective folders.
  2. Running the Analysis:
    • For forecasting results, navigate to the 7_ARIMA folder and run the R scripts.
    • For cohort effects, refer to the 6_APC folder.

📞 Contact

For any questions regarding the code or data, please contact the corresponding author of the manuscript.

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Source code and data analysis scripts for the manuscript: "Tuberculosis burden in Korea compared with global trends, 1990–2021: a comparative ecological time-trend study".

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