ArticleBMC public health2026
Measuring the impact of climate and air quality on COVID-19 transmission dynamics: a tale of two cities in pandemic preparedness.
Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Abstract
This comparative study investigates the non-linear influence of nine meteorological and air quality factors on COVID-19 transmission in Daegu and Seoul, South Korea, from January to July 2020. Employing Generalized Additive Models (GAMs), percentile-based risk zone identification, and K-means clustering, our analysis demonstrated that environmental factors are highly region-specific, challenging universal public health approaches. In Daegu, the risk profile was strongly shaped by climatic factors (GAM Explained Deviance: 63.0%), exhibiting a U-shaped temperature effect with elevated risk at both extremes. A primary high-risk zone appeared in cool, moderately dry conditions, averaging 278.8 cases per day, consistent with the Cold environmental regime. Conversely, Seoul's risk profile indicated significant air pollutant influence (GAM Explained Deviance: 48.3%), showing monotonic positive relationships for temperature, NO[Formula: see text], and O[Formula: see text]. Crucially, the data revealed a strong positive correlation between temperature and O[Formula: see text] (r = +0.794), indicating warmer periods feature elevated O
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