Abstract
ABSTRACT The annual burden of severe acute respiratory infection (SARI) is enormous, and environmental factors may have a vital role in respiratory infections. This study aimed to investigate the potential effects of the atmospheric environment on SARI. A time-series analysis was performed on the relationship between atmospheric environment and 136,989 SARI cases by distributed lag non-linear model. Wind speed, PM10, PM2.5, O3, and CO exhibited differential effects at a range of lag times or exposure ranges. Air pressure, temperature, and diurnal temperature range showed risk effects in the full range. The lag effect of high pollution was stronger, appeared earlier, and lasted longer than that of low pollution. Most environmental factors had a certain non-linear lag relationship with SARI. Low wind speed and high air pollution may be increasing risk factors for SARI.
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