The Geographical Conditioning of Regional Differentiation Characterising the COVID-19 Pandemic in European Countries DOI Open Access
Marcin Mazur, Jerzy Bański, Wioletta Kamińska

et al.

International Journal of Environmental Research and Public Health, Journal Year: 2024, Volume and Issue: 21(10), P. 1342 - 1342

Published: Oct. 10, 2024

The aim of this paper is to assess the influence selected geographical factors on diversity development COVID-19 pandemic in Europe’s regions, and its dynamics across continent. work took into account 250 NUTS-2 regions. datasets included course (two dependent variables), intervening actions (four variables research background), potential environmental socio-economic conditioning (twelve independent variables). variables’ set was composed two indexes: morbidity temporal inertia. scope 23 March 2020–15 May 2022, with weekly resolution. By means multiple linear regression model, administrative natural assessed. Finally, a synthetic Regional Epidemic Vulnerability Index (REVI) for each individual region calculated. It allowed us classify regions three categories: resistant, neutral, or sensitive. REVI’s spatial distribution indicates that zone above-average vulnerability occurred western part Europe around Alps. Therefore, focus ought extend beyond regional statistics, towards relationships, like contiguous transit position. This also validated strong impact national borders.

Language: Английский

Novel stochastic descriptors of a Markovian SIRD model for the assessment of the severity behind epidemic outbreaks DOI
Vasileios E. Papageorgiou

Journal of the Franklin Institute, Journal Year: 2024, Volume and Issue: 361(12), P. 107022 - 107022

Published: June 13, 2024

Language: Английский

Citations

5

Commentary on “Stochastic modeling of computer virus spreading with warning signals” DOI
Vasileios E. Papageorgiou

Journal of the Franklin Institute, Journal Year: 2024, Volume and Issue: 361(9), P. 106916 - 106916

Published: May 10, 2024

Language: Английский

Citations

4

Poisson random measure noise-induced coherence in epidemiological priors informed deep neural networks to identify the intensity of virus dynamics DOI Creative Commons
Saima Rashid, Ayesha Siddiqa, Fekadu Tesgera Agama

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: May 17, 2025

Differential equations-based epidemiological compartmental systems and deep neural networks-based artificial intelligence can effectively analyze combat monkeypox (MPV) transmission with Poisson random measure noise into a stochastic SEIQR (susceptible, exposed, infected, quarantined, recovered) model human population SEI infected) for rodent population. Compartmental models have estimates of parameter complications, whereas machine learning algorithms struggle to understand MPV's progression lack elucidation. This research introduces Levenberg Marquardt backpropagation networks (LMBNNS) in training, new approach that combines frameworks (ANNs) explain the complex mechanisms MPV. Meanwhile, description proves existence uniqueness global positive solution. A threshold is determined employed identify factors lead infection general public. Furthermore, other criteria are developed eliminate within entire The MPV eliminated if [Formula: see text], but continues text]. study depends on two functional scenarios quantitatively clarify theoretical results. An adapted dataset generated employing Adam algorithm minimize mean square error (MSE) by setting its data effectiveness 81% 9% testing, 10% validation. solver's accuracy validated minimal absolute complementing responses every hypothetical situation. In order verify adaptation's reliability precision, productivity measured using histogram, changeover state, prediction addressing model. Visual representations used illustrate investigation compare Utilizing this hybrid approach, we want increase our comprehension disease propagation, strengthen forecasting competencies, influence more efficient public health actions. combination processes approaches creates powerful tool capturing inherent uncertainties infectious dynamics, as well accurate framework real-time epidemic prevention.

Language: Английский

Citations

0

Transient analysis of a SIQS model with state capacities using a non-homogeneous Markov system DOI
Vasileios E. Papageorgiou, Georgios Vasiliadis

Journal of the Franklin Institute, Journal Year: 2024, Volume and Issue: 362(1), P. 107347 - 107347

Published: Nov. 5, 2024

Language: Английский

Citations

2

Estimating the Prevalence of Terrorism under Control Policies. A Statistical Modelling Approach DOI
Vasileios E. Papageorgiou

Applied Mathematical Modelling, Journal Year: 2024, Volume and Issue: 137, P. 115642 - 115642

Published: Aug. 18, 2024

Language: Английский

Citations

0

Inference of a Susceptible–Infectious stochastic model DOI Creative Commons
Giuseppina Albano, Virginia Giorno, Francisco Torres‐Ruiz

et al.

Mathematical Biosciences & Engineering, Journal Year: 2024, Volume and Issue: 21(9), P. 7067 - 7083

Published: Jan. 1, 2024

We consider a time-inhomogeneous diffusion process able to describe the dynamics of infected people in susceptible-infectious epidemic model which transmission intensity function is time-dependent. Such well suited some classes micro-parasitic infections individuals never acquire lasting immunity and over course everyone eventually becomes infected. The stochastic related deterministic transformable into non homogeneous Wiener so probability distribution can be obtained. Here we focus on inference for such process, by providing an estimation procedure involved parameters. point out that time dependence infinitesimal moments makes classical methods inapplicable. proposed based Generalized Method Moments order find suitable estimate drift variance transformed process. Several simulation studies are conduced test procedure, these include case, comparison with results obtained applying MLE made, cases dependent particular attention periodic cases. Finally, apply real dataset.

Language: Английский

Citations

0

The Geographical Conditioning of Regional Differentiation Characterising the COVID-19 Pandemic in European Countries DOI Open Access
Marcin Mazur, Jerzy Bański, Wioletta Kamińska

et al.

International Journal of Environmental Research and Public Health, Journal Year: 2024, Volume and Issue: 21(10), P. 1342 - 1342

Published: Oct. 10, 2024

The aim of this paper is to assess the influence selected geographical factors on diversity development COVID-19 pandemic in Europe’s regions, and its dynamics across continent. work took into account 250 NUTS-2 regions. datasets included course (two dependent variables), intervening actions (four variables research background), potential environmental socio-economic conditioning (twelve independent variables). variables’ set was composed two indexes: morbidity temporal inertia. scope 23 March 2020–15 May 2022, with weekly resolution. By means multiple linear regression model, administrative natural assessed. Finally, a synthetic Regional Epidemic Vulnerability Index (REVI) for each individual region calculated. It allowed us classify regions three categories: resistant, neutral, or sensitive. REVI’s spatial distribution indicates that zone above-average vulnerability occurred western part Europe around Alps. Therefore, focus ought extend beyond regional statistics, towards relationships, like contiguous transit position. This also validated strong impact national borders.

Language: Английский

Citations

0