Leakage-Aware Ordinal Prequential Forecasting of District-Level Conflict Severity in Bangladesh

Abstract—Reliable district-level conflict forecasting requires
models that distinguish ordered severity while controlling temporal
leakage, geographic heterogeneity, class imbalance, reporting
processes, and non-stationarity. We propose a leakage-aware
prequential framework for forecasting next-month Low, Medium,
and High conflict severity across all 64 districts of Bangladesh.
The study integrates three data sources: (1) ACLED, comprising
31,613 reconciled conflict-event records; (2) NASA POWER,
providing precipitation, temperature, and wind variables; and (3)
geoBoundaries ADM2, providing district-level spatial information.
Their integration produces a complete 11,904-observation districtmonth panel spanning 186 months. Severity is defined by a
study-specific analytical index combining next-month events and
reported fatalities, with the High cutoff (c = 6) frozen from an
initial 60-month history.