Climate-informed forecasting of the respiratory pharmaceutical demand in Greece from a spatio-temporal panel dataset

Abstract Respiratory medicines are among the first lines of defence when weather and climate push vulnerable lungs past their limits. This study quantifies how atmospheric conditions shape weekly prescription volumes and examines what continued global warming implies for pharmaceutical planning in Greece. A national retail panel of prescription respiratory sales for 20 regions (2016–2023) is combined with high-resolution meteorological reanalysis to estimate two classes of models: a Spatial Lag of X panel with region and week-of-year fixed effects, and a climate-augmented fixed-effects distributed lag forecaster. The spatial specification shows that contemporaneous conditions in neighbouring regions, especially warmer temperatures and stronger winds, exert more systematic effects on local demand than purely local shocks—positive for temperature, negative for wind—with spillovers concentrated within distance bands of a few hundred kilometres. The forecasting model couples short distributed lags of climatic variables with autoregressive dynamics and attains one-year-ahead accuracy with mean absolute percentage errors around 11%. A purely exogenous variant driven only by climatic regressors is then run on weekly projections from global climate models under alternative forcing pathways, yielding scenario-conditioned trajectories of national respiratory pharmaceutical needs. By the late 2020s, these projections indicate peak-season demand roughly 25–35% above recent (2022–2023) levels and about 45–55% above pre-pandemic volumes. Taken together, the results support climate-aware, spatially resolved procurement strategies and underscore the value of integrating routine pharmaceutical data into health-system adaptation to a warming atmosphere.