WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing, Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong Special Administrative Region, China.
Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Tahir Foundation Building, 12 Science Drive 2, Singapore, 117549, Singapore.
Sci Rep. 2020 Nov 24;10(1):20469. doi: 10.1038/s41598-020-76888-4.
Meteorological drivers are known to affect transmissibility of respiratory viruses including respiratory syncytial virus (RSV), but there are few studies quantifying the role of these drivers. We used daily RSV hospitalization data to estimate the daily effective reproduction number (R), a real-time measure of transmissibility, and examined its relationship with environmental drivers in Singapore from 2005 through 2015. We used multivariable regression models to quantify the proportion of the variance in R explained by each meteorological driver. After constructing a basic model for RSV seasonality, we found that by adding meteorological variables into this model we were able to explain a further 15% of the variance in RSV transmissibility. Lower and higher value of mean temperature, diurnal temperature range (DTR), precipitation and relative humidity were associated with increased RSV transmissibility, while higher value of maximum wind speed was correlated with decreased RSV transmissibility. We found that a number of meteorological drivers were associated with RSV transmissibility. While indoor conditions may differ from ambient outdoor conditions, our findings are indicative of a role of ambient temperature, humidity and wind speed in affecting RSV transmission that could be biological or could reflect indirect effects via the consequences on time spent indoors.
气象因素已知会影响呼吸道病毒(包括呼吸道合胞病毒 RSV)的传播力,但目前很少有研究量化这些因素的作用。我们使用每日 RSV 住院数据来估计每日有效繁殖数(R),这是衡量传染性的实时指标,并在 2005 年至 2015 年期间检查了其与新加坡环境因素的关系。我们使用多变量回归模型来量化每个气象因素对 R 的方差的解释比例。在为 RSV 季节性构建了基本模型之后,我们发现通过将气象变量添加到该模型中,我们能够进一步解释 RSV 传染性变化的 15%。平均温度、日较差(DTR)、降水和相对湿度较低和较高值与 RSV 传染性增加有关,而最大风速较高值与 RSV 传染性降低有关。我们发现,许多气象因素与 RSV 的传染性有关。虽然室内条件可能与室外环境条件不同,但我们的研究结果表明,环境温度、湿度和风速对 RSV 传播的影响可能是生物学的,也可能反映了通过对室内活动时间的影响产生的间接影响。