Inferring Seasonal Modulation of Early SARS-CoV-2 Transmissibility from Cross-Country Environmental and Population-Level Predictors.

Seasonal variation in SARS-CoV-2 transmissibility is difficult to estimate directly from year-round epidemic data because interventions, behavior, reporting, immunity, and viral evolution change concurrently. We therefore asked whether cross-country differences observed during the initial exponential-growth phase could be used to infer country-specific seasonal modulation. Early-pandemic basic reproduction numbers (R0) from 118 countries were linked to 96 harmonized environmental and population-level predictors. Among nine candidate algorithms evaluated across 100 repeated train-test splits, ridge regression using the combined predictor set provided the best balance of predictive accuracy, generalization, and temporal stability. The selected model was then driven by daily climatological covariates to reconstruct annual baseline R0(t) profiles. Predicted transmissibility generally peaked during winter in the Northern Hemisphere and approximately six months later in the Southern Hemisphere, whereas equatorial countries showed weaker or multimodal patterns. Seasonal forcing amplitude increased strongly with absolute latitude (r = 0.85; mean 0.064 across 77 temperate countries), and predicted R0 peaks aligned more closely with minimum ultraviolet radiation than with minimum temperature. These ecological associations do not establish causality, but they provide country-specific seasonal-forcing parameters for epidemic models and a baseline environmental context for comparing early-pandemic trajectories.