Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria.
Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria.
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DOI：
10.1371/journal.pcbi.1009973
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发表时间：
2022-04
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
作者：
SARS-CoV-2在更精细的时空尺度上传播的区域差异背后的驱动因素尚未得到充分理解。在这里，我们开发了一种数据驱动的建模方法，该方法基于年龄结构的房室模型，将116个奥地利地区与一组适当选择的控制区域进行比较，以通过气象因素，非药物干预和流动性的组合来解释当地传播率的变化。我们发现，超过60%的观察到的区域变化可以解释这些因素。气温和湿度下降、云量增加、降水和缺乏公共活动缓解措施是病毒传播增加的最大驱动因素，导致与天气较好的地区相比，传播率翻了一番。我们推测，对于经历向不利天气条件转变的大型事件几乎没有缓解措施的地区特别容易成为下一个季节性SARS-CoV-2波的成核点。天气如何在精细的时空尺度上调节SARS-CoV-2的传播仍然没有完全了解。在这里，我们使用一个受控的区域比较隔离的影响，五种不同的气象因素，四种类型的非药物干预措施，以及个人层面的流动性在奥地利的传播率。我们发现，超过60%的区域变化可以解释这些因素。温度和湿度与传输率呈负相关，而云量和降水量与传输率增加相关。我们还注意到，针对大型活动的限制产生了特别强烈的影响。我们的研究结果表明，天气向冬季条件的转变，加上大型聚会的缓解措施很少，这两个因素共同推动了季节性SARS-CoV-2波的早期增长。
The drivers behind regional differences of SARS-CoV-2 spread on finer spatio-temporal scales are yet to be fully understood. Here we develop a data-driven modelling approach based on an age-structured compartmental model that compares 116 Austrian regions to a suitably chosen control set of regions to explain variations in local transmission rates through a combination of meteorological factors, non-pharmaceutical interventions and mobility. We find that more than 60% of the observed regional variations can be explained by these factors. Decreasing temperature and humidity, increasing cloudiness, precipitation and the absence of mitigation measures for public events are the strongest drivers for increased virus transmission, leading in combination to a doubling of the transmission rates compared to regions with more favourable weather. We conjecture that regions with little mitigation measures for large events that experience shifts toward unfavourable weather conditions are particularly predisposed as nucleation points for the next seasonal SARS-CoV-2 waves. How weather modulates the spread of SARS-CoV-2 on fine spatio-temporal scales is still not fully understood. Here we use a controlled regional comparison to isolate the impact of five different meteorological factors, four types of non-pharmaceutical interventions as well as individual-level mobility on transmission rates in Austria. We find that more than 60% of regional variations can be explained by these factors. Temperature and humidity relate inversely with transmission rates whereas cloudiness and precipitation correlate with increasing transmission. We also observe a particularly strong impact of restrictions targeting large events. Our results suggest that a combination of weather shifts towards winter conditions combined with little mitigation measures for large gatherings drive the early growth of seasonal SARS-CoV-2 waves.
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影响因子：
9.8
作者：
Althouse BM;Wenger EA;Miller JC;Scarpino SV;Allard A;Hébert-Dufresne L;Hu H
通讯作者：
Hu H
影响因子：
29.9
作者：
Haug, Nils;Geyrhofer, Lukas;Klimek, Peter
通讯作者：
Klimek, Peter
DOI：
10.1016/j.scitotenv.2020.143783
发表时间：
2021-02-25
期刊：
The Science of the total environment
影响因子：
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作者：
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通讯作者：
Lao XQ
影响因子：
7.8
作者：
Gómez CE;Perdiguero B;Esteban M
通讯作者：
Esteban M
影响因子：
1.8
作者：
Gross, Bnaya;Zheng, Zhiguo;Havlin, Shlomo
通讯作者：
Havlin, Shlomo