Gaopei Zhu1, Yuhang Zhu1,2, Zhongli Wang3, Weijing Meng4, Xiaoxuan Wang1, Jianing Feng1, Juan Li1, Yufei Xiao1, Fuyan Shi5, Suzhen Wang6. 1. Department of Health Statistics, School of Public Health, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China. 2. Department of Child and Adolescent Psychiatry, Psychotherapy, and Psychosomatics, Center for Psychosocial Medicine, University Medical Center Hamburg-Eppendorf, Martinistraße 52, W 29, 20246, Hamburg, Germany. 3. School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, People's Republic of China. 4. School of Life Sciences and Technology, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China. 5. Department of Health Statistics, School of Public Health, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China. shifuyan@126.com. 6. Department of Health Statistics, School of Public Health, Weifang Medical University, No. 7166 Baotong West Street, Weifang, 261053, People's Republic of China. wangsz@wfmc.edu.cn.
Abstract
BACKGROUND: The COVID-19 has caused a sizeable global outbreak and has been declared as a public health emergency of international concern. Sufficient evidence shows that temperature has an essential link with respiratory infectious diseases. The objectives of this study were to describe the exposure-response relationship between ambient temperature, including extreme temperatures, and mortality of COVID-19. METHODS: The Poisson distributed lag non-linear model (DLNM) was constructed to evaluate the non-linear delayed effects of ambient temperature on death, by using the daily new death of COVID-19 and ambient temperature data from January 10 to March 31, 2020, in Wuhan, China. RESULTS: During the period mentioned above, the average daily number of COVID-19 deaths was approximately 45.2. Poisson distributed lag non-linear model showed that there was a non-linear relationship (U-shape) between the effect of ambient temperature and mortality. With confounding factors controlled, the daily cumulative relative death risk decreased by 12.3% (95% CI [3.4, 20.4%]) for every 1.0 °C increase in temperature. Moreover, the delayed effects of the low temperature are acute and short-term, with the most considerable risk occurring in 5-7 days of exposure. The delayed effects of the high temperature appeared quickly, then decrease rapidly, and increased sharply 15 days of exposure, mainly manifested as acute and long-term effects. Sensitivity analysis results demonstrated that the results were robust. CONCLUSIONS: The relationship between ambient temperature and COVID-19 mortality was non-linear. There was a negative correlation between the cumulative relative risk of death and temperature. Additionally, exposure to high and low temperatures had divergent impacts on mortality.
BACKGROUND: The COVID-19 has caused a sizeable global outbreak and has been declared as a public health emergency of international concern. Sufficient evidence shows that temperature has an essential link with respiratory infectious diseases. The objectives of this study were to describe the exposure-response relationship between ambient temperature, including extreme temperatures, and mortality of COVID-19. METHODS: The Poisson distributed lag non-linear model (DLNM) was constructed to evaluate the non-linear delayed effects of ambient temperature on death, by using the daily new death of COVID-19 and ambient temperature data from January 10 to March 31, 2020, in Wuhan, China. RESULTS: During the period mentioned above, the average daily number of COVID-19deaths was approximately 45.2. Poisson distributed lag non-linear model showed that there was a non-linear relationship (U-shape) between the effect of ambient temperature and mortality. With confounding factors controlled, the daily cumulative relative death risk decreased by 12.3% (95% CI [3.4, 20.4%]) for every 1.0 °C increase in temperature. Moreover, the delayed effects of the low temperature are acute and short-term, with the most considerable risk occurring in 5-7 days of exposure. The delayed effects of the high temperature appeared quickly, then decrease rapidly, and increased sharply 15 days of exposure, mainly manifested as acute and long-term effects. Sensitivity analysis results demonstrated that the results were robust. CONCLUSIONS: The relationship between ambient temperature and COVID-19mortality was non-linear. There was a negative correlation between the cumulative relative risk of death and temperature. Additionally, exposure to high and low temperatures had divergent impacts on mortality.
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