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10.3390/ijerph17134693 http://scihub22266oqcxt.onion/10.3390/ijerph17134693 32629791!7370089!32629791     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32629791&cmd=llinks): Failed to open stream: HTTP request failed! 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Modeling and Forecasting the COVID-19 Temporal Spread in Greece: An Exploratory Approach based on Complex Network Defined Splines |pdf=|usr=}}{{32629791}} gab.com Text Modeling and Forecasting the COVID-19 Temporal Spread in Greece: An Exploratory Approach based on Complex Network Defined Splines JO: Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=32629791 #FOAvip Within the complex framework of anti-COVID-19 health management, where the criteria of diagnostic testing, the availability of public-health resources and services, and the applied anti-COVID-19 policies vary between countries, the reliability and accuracy in the modeling of temporal spread can prove to be effective in the worldwide fight against the disease. This paper applies an exploratory time-series analysis to the evolution of the disease in Greece, which currently suggests a success story of COVID-19 management. The proposed method builds on a recent conceptualization of detecting connective communities in a time-series and develops a novel spline regression model where the knot vector is determined by the community detection in the complex network. Overall, the study contributes to the COVID-19 research by proposing a free of disconnected past-data and reliable framework of forecasting, which can facilitate decision-making and management of the available health resources. Twit Text FOAVip Modeling and Forecasting the COVID-19 Temporal Spread in Greece: An Exploratory Approach based on Complex Network Defined Splines ????Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=32629791 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32629791 #FOAvip English Wikipedia <ref>{{Cite pmid|32629791}}</ref> Modeling and Forecasting the COVID-19 Temporal Spread in Greece: An Exploratory Approach based on Complex Network Defined Splines #MMPMID32629791 Demertzis K; Tsiotas D; Magafas L Int J Environ Res Public Health 2020[Jun]; 17 (13): ä PMID32629791show ga Within the complex framework of anti-COVID-19 health management, where the criteria of diagnostic testing, the availability of public-health resources and services, and the applied anti-COVID-19 policies vary between countries, the reliability and accuracy in the modeling of temporal spread can prove to be effective in the worldwide fight against the disease. This paper applies an exploratory time-series analysis to the evolution of the disease in Greece, which currently suggests a success story of COVID-19 management. The proposed method builds on a recent conceptualization of detecting connective communities in a time-series and develops a novel spline regression model where the knot vector is determined by the community detection in the complex network. Overall, the study contributes to the COVID-19 research by proposing a free of disconnected past-data and reliable framework of forecasting, which can facilitate decision-making and management of the available health resources. |Betacoronavirus/isolation & purification[MESH] |COVID-19[MESH] |Coronavirus Infections/*epidemiology/*transmission[MESH] |Forecasting[MESH] |Greece/epidemiology[MESH] |Humans[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology/*transmission[MESH] |Public Health[MESH] |SARS-CoV-2[MESH]Modeling and Forecasting the COVID-19 Temporal Spread in Greece: An Ex(epmc).pdf DeepDyve Pubget Overpricing