Data and Code for Epidemiological Modelling and BSR Disease Management

This repository contains the complete datasets, reproducible statistical workflows, and computational forecasting pipelines supporting the study:

“Forecasting and Integrated Management of Basal Stem Rot Caused by Ganoderma ryvardenii on Oil Palm in Ghana.”

The repository provides an integrated analytical framework combining laboratory fungicide sensitivity evaluation, longitudinal field epidemiology, and climate-informed disease forecasting for basal stem rot (BSR) caused by Ganoderma ryvardenii in oil palm.

Included resources comprise:

• Raw and processed datasets from in vitro fungicide assays and a 33-month multi-regional field management trial conducted in Ghana.
• Reproducible R statistical workflows for disease progression analysis, Area Under the Disease Progress Curve (AUDPC) estimation, analysis of variance (ANOVA), and Tukey HSD mean separation.
• Python-based forecasting and feature-engineering pipelines integrating SARIMAX and XGBoost architectures for climate-driven epidemiological prediction.
• Environmental feature engineering workflows incorporating temporal lag structures, seasonal encodings, rainfall transformations, and temperature–humidity interaction variables relevant to tropical disease epidemiology.
• Computational environment configuration files (renv.lock, requirements.txt, and reproducibility metadata) to support transparent cross-platform execution and reproducibility.

The repository is organised to provide a transparent and reviewer-friendly computational workflow linking experimental pathology, field disease management, and predictive epidemiological modelling within a unified reproducible research framework.

Version 1.0 — Initial reproducible research release accompanying manuscript submission.