On the Transmission Dynamics of SARS-CoV-2 in a Temperate Climate

被引:3
作者
Kioutsioukis, Ioannis [1 ]
Stilianakis, Nikolaos I. [2 ,3 ]
机构
[1] Univ Patras, Dept Phys, Rion 26504, Greece
[2] European Commiss, Joint Res Ctr JRC, I-2027 Ispra, Italy
[3] Univ Erlangen Nurnberg, Dept Biometry & Epidemiol, D-91054 Erlangen, Germany
关键词
asymptomatic infections; temperature; humidity; SARS-CoV-2; COVID-19; predictability; transmission; epidemiological model; DRUG-RESISTANCE; INFLUENZA; EPIDEMIC; EMERGENCE;
D O I
10.3390/ijerph18041660
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
An epidemiological model, which describes the transmission dynamics of SARS-CoV-2 under specific consideration of the incubation period including the population with subclinical infections and being infective is presented. The COVID-19 epidemic in Greece was explored through a Monte Carlo uncertainty analysis framework, and the optimal values for the parameters that determined the transmission dynamics could be obtained before, during, and after the interventions to control the epidemic. The dynamic change of the fraction of asymptomatic individuals was shown. The analysis of the modelling results at the intra-annual climatic scale allowed for in depth investigation of the transmission dynamics of SARS-CoV-2 and the significance and relative importance of the model parameters. Moreover, the analysis at this scale incorporated the exploration of the forecast horizon and its variability. Three discrete peaks were found in the transmission rates throughout the investigated period (15 February-15 December 2020). Two of them corresponded to the timing of the spring and autumn epidemic waves while the third one occurred in mid-summer, implying that relaxation of social distancing and increased mobility may have a strong effect on rekindling the epidemic dynamics offsetting positive effects from factors such as decreased household crowding and increased environmental ultraviolet radiation. In addition, the epidemiological state was found to constitute a significant indicator of the forecast reliability horizon, spanning from as low as few days to more than four weeks. Embedding the model in an ensemble framework may extend the predictability horizon. Therefore, it may contribute to the accuracy of health risk assessment and inform public health decision making of more efficient control measures.
引用
收藏
页码:1 / 17
页数:17
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