Michael P Ward, Yuanhua Liu, Shuang Xiao, Zhijie Zhang
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The associations between daily 9:00 am and 3:00 pm temperature (°C), relative humidity (%) and their difference, and a time series of reported daily cases were assessed using univariable and multivariable generalized additive models and a 14-day exponential moving average. Akaike information criterion (AIC) and the likelihood ratio statistic were used to compare different models and determine the best fitting model. A sensitivity analysis was performed by modifying the exponential moving average.</p><p><strong>Results: </strong>During the 87-day time-series, relative humidity ranged widely (< 30-98%) and temperatures were mild (approximately 11-17 °C). The best-fitting (AIC: 1,119.64) generalized additive model included 14-day exponential moving averages of 9:00 am temperature (P < 0.001) and 9:00 am relative humidity (P < 0.001), and the interaction between these two weather variables (P < 0.001). 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引用次数: 6
摘要
背景:自出现严重急性呼吸道冠状病毒2 (SARS-CoV-2)和2019冠状病毒病(COVID-19)大流行以来,越来越多的证据表明,天气因素,特别是温度和湿度,会影响传播。对于最近出现的B.1.617.2 (delta)变体SARS-CoV-2,这种关系可能有所不同。在这里,我们使用来自澳大利亚悉尼冬季爆发的数据和时间序列分析来调查报告病例与温度和相对湿度之间的关系。方法:在疫情高峰期2021年6月16日至9月10日期间,澳大利亚悉尼市5个地方卫生区共报告本地获得性病例31662例。采用单变量和多变量广义加性模型以及14天指数移动平均线,评估了每日9:00 am和3:00 pm温度(°C)、相对湿度(%)及其差异与每日报告病例时间序列之间的关系。采用赤池信息准则(Akaike information criterion, AIC)和似然比统计量对不同模型进行比较,确定最佳拟合模型。通过修正指数移动平均进行敏感性分析。结果:在87天的时间序列中,相对湿度的变化幅度很大。结论:我们认为,在一年中相对湿度较低和温度较高的时期,控制COVID-19疫情,特别是由delta变异引起的疫情尤其具有挑战性。除了疫苗接种外,在这些高风险时期可能需要考虑加强实施其他干预措施,如戴口罩和保持社交距离。
Challenges in the control of COVID-19 outbreaks caused by the delta variant during periods of low humidity: an observational study in Sydney, Australia.
Background: Since the appearance of severe acute respiratory coronavirus 2 (SARS-CoV-2) and the coronavirus disease 2019 (COVID-19) pandemic, a growing body of evidence has suggested that weather factors, particularly temperature and humidity, influence transmission. This relationship might differ for the recently emerged B.1.617.2 (delta) variant of SARS-CoV-2. Here we use data from an outbreak in Sydney, Australia that commenced in winter and time-series analysis to investigate the association between reported cases and temperature and relative humidity.
Methods: Between 16 June and 10 September 2021, the peak of the outbreak, there were 31,662 locally-acquired cases reported in five local health districts of Sydney, Australia. The associations between daily 9:00 am and 3:00 pm temperature (°C), relative humidity (%) and their difference, and a time series of reported daily cases were assessed using univariable and multivariable generalized additive models and a 14-day exponential moving average. Akaike information criterion (AIC) and the likelihood ratio statistic were used to compare different models and determine the best fitting model. A sensitivity analysis was performed by modifying the exponential moving average.
Results: During the 87-day time-series, relative humidity ranged widely (< 30-98%) and temperatures were mild (approximately 11-17 °C). The best-fitting (AIC: 1,119.64) generalized additive model included 14-day exponential moving averages of 9:00 am temperature (P < 0.001) and 9:00 am relative humidity (P < 0.001), and the interaction between these two weather variables (P < 0.001). Humidity was negatively associated with cases no matter whether temperature was high or low. The effect of lower relative humidity on increased cases was more pronounced below relative humidity of about 70%; below this threshold, not only were the effects of humidity pronounced but also the relationship between temperature and cases of the delta variant becomes apparent.
Conclusions: We suggest that the control of COVID-19 outbreaks, specifically those due to the delta variant, is particularly challenging during periods of the year with lower relative humidity and warmer temperatures. In addition to vaccination, stronger implementation of other interventions such as mask-wearing and social distancing might need to be considered during these higher risk periods.
期刊介绍:
Infectious Diseases of Poverty is a peer-reviewed, open access journal that focuses on essential public health questions related to infectious diseases of poverty. It covers a wide range of topics and methods, including the biology of pathogens and vectors, diagnosis and detection, treatment and case management, epidemiology and modeling, zoonotic hosts and animal reservoirs, control strategies and implementation, new technologies, and their application.
The journal also explores the impact of transdisciplinary or multisectoral approaches on health systems, ecohealth, environmental management, and innovative technologies. It aims to provide a platform for the exchange of research and ideas that can contribute to the improvement of public health in resource-limited settings.
In summary, Infectious Diseases of Poverty aims to address the urgent challenges posed by infectious diseases in impoverished populations. By publishing high-quality research in various areas, the journal seeks to advance our understanding of these diseases and contribute to the development of effective strategies for prevention, diagnosis, and treatment.