Association between environmental factors and COVID-19 in Shanghai, China.

The outbreak of coronavirus disease 2019 (COVID-19) continues to spread worldwide and has led to recession, rising unemployment, and the collapse of the health-care system. The aim of this study was to explore the exposure-response relationship between daily confirmed COVID-19 cases and environmental factors. We used a time-series generalized additive model (GAM) to investigate the short-term association between COVID-19 and environmental factors by using daily meteorological elements, air pollutant concentration, and daily confirmed COVID-19 cases from January 21, 2020, to February 29, 2020, in Shanghai, China. We observed significant negative associations between daily confirmed COVID-19 cases and mean temperature (T _ave ), temperature humidity index (THI), and index of wind effect (K), whereas air quality index (AQI), PM _2.5 , PM ₁₀ NO ₂ , and SO ₂ were significantly associated with the increase in daily confirmed COVID-19 cases. A 1 °C increase in T _ave , one-unit increase in THI, and 10-unit increase in K (lag 0-7 days) were associated with 4.7, 1.8, and 1.6% decrease in daily confirmed cases, respectively. Daily T _ave , THI, K, PM ₁₀ , and SO ₂ had significant lag and persistence (lag 0-7 days), whereas the lag and persistence of AQI, PM _2.5 , and NO ₂ were significant at both lag 0-7 and 0-14 days. A 10-μg/m ³ increase in PM ₁₀ and 1-μg/m ³ increase in SO ₂ was associated with 13.9 and 5.7% increase in daily confirmed cases at lag 0-7 days, respectively, whereas a 10-unit increase in AQI and a 10-μg/m ³ increase in PM _2.5 and NO ₂ were associated with 7.9, 7.8, and 10.1% increase in daily confirmed cases at lag 0-14 days, respectively. Our findings have important implications for public health in the city of Shanghai.
(© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)