https://mp.weixin.qq.com/s/-JQ1yad68FhRXJ0fym6yJg
气候观察室 2025年07月15日
题目：Attribution of Air Temperature Variation to the Incidence of COVID-19
作者：Rui Wang, Jianping Huang, Xinbo Lian, Han Li, Yingjie Zhao, Beidou Zhang, Dongliang Han
机构：College of Atmospheric Sciences, Lanzhou University
期刊：Geophysical Research Letters
时间：2025年7月
摘要：COVID-19发病率呈现周期性波动，反复感染浪潮可能导致未来大规模爆发。气温是影响病毒传播的关键环境因子，但其具体作用机制与定量效应仍缺乏深入研究。本研究基于中国31个省份2020–2022年412,167例每日病例数据，系统解析了气温与COVID-19的关联。结果表明：持续性低温与急剧降温均显著提升传播风险，且存在显著区域差异阈值：当气温低于3.15°C（华北）、0.55°C（东北）、16.39°C（华东）、9.38°C（华中）、13.39°C（西南）和−5.56°C（西北），并伴随>0.32°C、>0.67°C、>0.12°C、>2.12°C、>1.42°C及>1.55°C的降温幅度时，疫情暴发风险激增。低温环境直接驱动88.06%的病例，而温度骤降贡献率达59.33%。极端低温引发的COVID-19相对风险最高可达4.53。本研究填补了气温-COVID-19关联机制的认知空白，为恶劣气象条件下的精准防控提供科学依据。
Figure 1 Illustration of the overall methodology and procedural steps of the study.
 Figure 2 Daily Tem_Avg analysis during high Incidence periods of COVID-19 in each province (a). The base color of the map represents provincial-level mean Tem_Avg values during high-incidence periods. The colored circles indicate the comparative difference in daily Tem_Avg between high- and low- incidence periods for each province. (b) Represent four categories respectively: high incidence at low temperatures (Beijing), high incidence at high temperatures (Xizang), high incidence at both low and high temperatures (Jiangsu), and no significant difference in air temperature during high incidence periods (Shanghai). The orange lines/shadows represent the daily Tem_Avg during periods of low incidence. The blue lines/shadows depict the daily Tem_Avg during high incidence periods in colder conditions, while the red lines/shadows show the daily Tem_Avg during high incidence periods in warmer conditions. Light blue horizontal lines indicate the average daily Tem_Avg (with mean ± SD) during high incidence periods, and light red horizontal lines show the same for low incidence periods (with mean ± SD). The red bars represent the daily average number of confirmed COVID-19 cases. The extreme air temperature at which the risk of COVID-19 is highest in each province (c). The base colors of the left map are determined by the extreme low air temperatures in each province that are associated with the highest COVID-19 incidence risk, whereas the base colors of the right map are determined by the extreme high air temperatures that pose the highest risk. (d) Represent three categories, respectively: extreme low temperature (Beijing), extreme high temperature (Xizang), and the presence of both extreme low and high temperatures (Shanghai) when the relative risk (RR) is maximized. The three-dimensional exposure-lag-response plot demonstrates the risk of COVID-19 incidence varying with Tem_Avg and lag time. The blue line and its shading depict the maximum RR and its 95% confidence interval (CI) under low temperatures, while the red line and its shading represent the maximum RR and 95% CI under high temperatures.
 Figure 3 Analysis of air temperature fluctuation during high incidence periods of COVID-19 in each province (a). The base color of the national map is determined by the μ values of the probability density fitted curves for each province, representing the air temperature difference with the highest possibility of COVID-19 incidence. The left map depicts the situations where the high incidence period corresponds to low air temperatures, while the right map shows the situations where the high incidence period corresponds to high air temperatures. (b) Represent five categories respectively: high incidence during low-temperature drops (Beijing), high incidence during low-temperature rises (Shanghai), high incidence during high-temperature drops (Xizang), high incidence during low-temperature drops and high-temperature rises (Anhui), and high incidence during temperature drops at both cold and warm extremes (Hainan). The blue bars represent the distribution of COVID-19 confirmed cases within the range of air temperature fluctuation during the high incidence period under low temperature conditions. The orange bars represent the distribution of COVID-19 confirmed cases within the range of air temperature fluctuation during the high incidence period under high temperature conditions, with the width of each bar representing 1°C. The solid lines are fitted probability density curves, all following a normal distribution, and the dashed lines indicate the μ value of the normal distribution parameters. The red circles represent the numbers of confirmed COVID-19 cases. The figure (c) displays the sorted probability distribution of air temperature fluctuations for each province. The blue line represents a 1-degree decrease in temperature, while the red line represents a 1-degree increase. The blue background indicates conditions during low air temperatures, and the orange background indicates conditions during high air temperatures.
 Figure 4 Schematic diagram of the distribution of provinces with high COVID-19 incidence under low temperatures and decreasing temperatures, and prevention strategies. The blue-shaded areas on the map identify regions experiencing high case incidence during periods of low temperatures, while blue arrows indicate areas where additional temperature drops exacerbate transmission risks. The bar chart displays the proportion of confirmed COVID-19 cases due to low air temperatures and the proportion of confirmed cases due to decreasing air temperatures for each province.
文献引用：Wang, R., Huang, J., Lian, X., Li, H., Zhao, Y., Zhang, B., & Han, D. (2025). Attribution of air temperature variation to the incidence of COVID‐19. Geophysical Research Letters, 52, e2025GL116345. https://doi.org/10.1029/2025GL116345 |
发表于 2025-8-20 16:11:30
