tetano
Editor, Senior Moderator
Int J Environ Res Public Health
. 2020 Jun 30;17(13):E4693.
doi: 10.3390/ijerph17134693.
Modeling and Forecasting the COVID-19 Temporal Spread in Greece: An Exploratory Approach Based on Complex Network Defined Splines
Konstantinos Demertzis[SUP] 1 [/SUP], Dimitrios Tsiotas[SUP] 1 2 3 [/SUP], Lykourgos Magafas[SUP] 1 [/SUP]
Affiliations
Abstract
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.
Keywords: COVID-19 coronavirus pandemic; modeling; modularity optimization algorithm; outbreak; prediction; regression splines.
. 2020 Jun 30;17(13):E4693.
doi: 10.3390/ijerph17134693.
Modeling and Forecasting the COVID-19 Temporal Spread in Greece: An Exploratory Approach Based on Complex Network Defined Splines
Konstantinos Demertzis[SUP] 1 [/SUP], Dimitrios Tsiotas[SUP] 1 2 3 [/SUP], Lykourgos Magafas[SUP] 1 [/SUP]
Affiliations
- PMID: 32629791
- DOI: 10.3390/ijerph17134693
Abstract
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.
Keywords: COVID-19 coronavirus pandemic; modeling; modularity optimization algorithm; outbreak; prediction; regression splines.