Departments of Psychiatry & Neurology, Johns Hopkins University SOM, Baltimore, Maryland, United States of America.
Joint Artificial Intelligence Center, Pentagon, Washington, DC, United States of America.
PLoS One. 2021 Feb 17;16(2):e0246167. doi: 10.1371/journal.pone.0246167. eCollection 2021.
Intensity and duration of the COVID-19 pandemic, and planning required to balance concerns of saving lives and avoiding economic collapse, could depend significantly on whether SARS-CoV-2 transmission is sensitive to seasonal changes.
Hypothesis is that increasing temperature results in reduced SARS CoV-2 transmission and may help slow the increase of cases over time.
Fifty representative Northern Hemisphere countries meeting specific criteria had sufficient COVID-19 case and meteorological data for analysis.
Regression was used to find the relationship between the log of number of COVID-19 cases and temperature over time in 50 representative countries. To summarize the day-day variability, and reduce dimensionality, we selected a robust measure, Coefficient of Time (CT), for each location. The resulting regression coefficients were then used in a multivariable regression against meteorological, country-level and demographic covariates.
Median minimum daily temperature showed the strongest correlation with the reciprocal of CT (which can be considered as a rate associated with doubling time) for confirmed cases (adjusted R2 = 0.610, p = 1.45E-06). A similar correlation was found using median daily dewpoint, which was highly colinear with temperature, and therefore was not used in the analysis. The correlation between minimum median temperature and the rate of increase of the log of confirmed cases was 47% and 45% greater than for cases of death and recovered cases of COVID-19, respectively. This suggests the primary influence of temperature is on SARS-CoV-2 transmission more than COVID-19 morbidity. Based on the correlation between temperature and the rate of increase in COVID-19, it can be estimated that, between the range of 30 to 100 degrees Fahrenheit, a one degree increase is associated with a 1% decrease-and a one degree decrease could be associated with a 3.7% increase-in the rate of increase of the log of daily confirmed cases. This model of the effect of decreasing temperatures can only be verified over time as the pandemic proceeds through colder months.
The results suggest that boreal summer months are associated with slower rates of COVID-19 transmission, consistent with the behavior of a seasonal respiratory virus. Knowledge of COVID-19 seasonality could prove useful in local planning for phased reductions social interventions and help to prepare for the timing of possible pandemic resurgence during cooler months.
新冠疫情的强度和持续时间,以及为平衡挽救生命和避免经济崩溃的关切而进行的规划,可能在很大程度上取决于 SARS-CoV-2 的传播是否对季节性变化敏感。
假设温度升高会导致 SARS-CoV-2 传播减少,并可能有助于随着时间的推移减缓病例的增加。
50 个符合特定标准的代表性北半球国家,有足够的 COVID-19 病例和气象数据进行分析。
使用回归来发现 50 个代表性国家的 COVID-19 病例对数与时间的关系。为了总结日间变化,并减少维度,我们为每个地点选择了一个稳健的度量标准,即时间系数(CT)。然后,使用这些回归系数进行多元回归,以对抗气象、国家和人口统计学协变量。
最低日平均温度的中位数与确诊病例的 CT 的倒数(可视为与倍增时间相关的速率)相关性最强(调整后的 R2=0.610,p=1.45E-06)。使用与温度高度共线性的日平均露点也发现了类似的相关性,因此未在分析中使用。最低日平均温度与确诊病例对数增长率之间的相关性比死亡病例和 COVID-19 康复病例分别高 47%和 45%。这表明温度的主要影响是 SARS-CoV-2 的传播,而不是 COVID-19 的发病率。根据温度与 COVID-19 增长率之间的相关性,可以估计在 30 到 100 华氏度的范围内,温度每升高 1 度,增长率就会降低 1%,而温度每降低 1 度,增长率就会升高 3.7%。随着大流行进入较冷的月份,这种关于温度降低影响的模型只能随着时间的推移得到验证。
结果表明,北方夏季与 COVID-19 传播速度较慢有关,这与季节性呼吸道病毒的行为一致。了解 COVID-19 的季节性可能有助于在当地分阶段减少社会干预措施,并有助于为较冷月份可能出现的大流行复发做好准备。