SARS-CoV-2 Mutation Burden in Relation to Air Quality Index

This study investigates the association between ambient environmental conditions and SARS-CoV-2 nucleotide-level mutation burden across six countries (Bangladesh, Germany, India, Israel, Pakistan, and the USA) from 2020 to 2025. Using 153 whole-genome sequences aligned to Wuhan-Hu-1 (NC_045512.2), we quantified Spike (S) and Nucleocapsid (N) gene divergence and correlated these with satellite-derived (NASA SEDAC) and synthetically modeled (WHO-based) air quality index (AQI) estimates, along with historical temperature data (Open-Meteo). We report a statistically significant inverse global correlation between environmental stress and Spike mutation burden: higher WHO daily AQI (Spearman ρ = –0.485, p < 0.001), NASA annual AQI (ρ = –0.312, p < 0.001), and mean temperature (ρ = –0.404, p < 0.001) are associated with fewer nucleotide substitutions in the Spike gene. In contrast, Nucleocapsid mutations show no consistent association, suggesting protein-specific evolutionary constraints. We acknowledge that Country-stratified analyses reveal no significant within-country signals, likely due to limited temporal resolution and national-level environmental aggregation. These findings do not establish causality but suggest that environmental factors may modulate viral evolutionary dynamics potentially through reduced transmission duration, accelerated immune clearance, or surveillance biases tied to regional pandemic timing. The dataset, code, and visualizations are provided to support reproducibility and further hypothesis testing. Our observation of reduced Spike mutation burden in high-AQI/high-temperature regions aligns with biophysical models of viral decay under environmental stress, but may also reflect global disparities in genomic surveillance timing. While we cannot establish causality, the robust global correlation invites mechanistic studies on how air pollution modulates within-host viral evolution. References: Biryukov et al. (2020) - Temperature/humidity effects on stability Fauver et al. (2021, Cell) - Global genomic surveillance biases Méndez et al. (2021) - Pollution and respiratory immunity van Dorp et al. (2020, Virus Evol) - Mutation rate estimates in SARS-CoV-2