A simple but complex enough <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e2650" altimg="si4.svg"><mml:mi>θ</mml:mi></mml:math>-SIR type model to be used with COVID-19 real data. Application to the case of Italy

Ramos, Ángel; Ferrández, Miriam R.; Pérez, María A.; Kubik, Alicja Barbara; Ivorra, Benjamín

doi:10.1016/j.physd.2020.132839

Cited by 33 publications

(19 citation statements)

References 34 publications

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“…This fact was attributed to the novelty of SARS-CoV-2, as well as statistical problems in the model's calibration ( Zhao and Chen, 2020 ). Other reasons can be due to the limitation of traditional modelling approaches because of the difficulties in the selection of specific and suitable predictors of the pandemic in a non-experimental environment ( Ramos et al, 2021 ). Jones and Strigul (2021) have recently concluded that the COVID-19 pandemic shows a chaotic behavior, with the consequence that the epidemic scale and behavior may be essentially unpredictable.…”

Section: Introductionmentioning

confidence: 99%

International trade as critical parameter of COVID-19 spread that outclasses demographic, economic, environmental, and pollution factors

Bontempi

Coccia

2021

Environmental Research

103

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The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the Coronavirus Disease 2019 (COVID-19), generating high numbers of COVID-19 related infected individuals and deaths, is still circulating in 2021 with new variants of the coronavirus, such that the state of emergency remains in manifold countries. Currently, there is still a lack of a full understanding of the factors determining the COVID-19 diffusion that clarify the causes of the variability of infections across different provinces and regions within countries. The main goal of this study is to explain new and main determinants underlying the diffusion of COVID-19 in society. This study focuses on international trade because this factor, in a globalized world, can synthetize different drivers of virus spread, such as mobility patterns, economic potentialities, and social interactions of an investigated areas. A case study research is performed on 107 provinces of Italy, one of the first countries to experience a rapid increase in confirmed cases and deaths. Statistical analyses from March 2020 to February 2021 suggest that total import and export of provinces has a high association with confirmed cases over time (average r > 0.78, p -value <.001). Overall, then, this study suggests total import and export as complex indicator of COVID-19 transmission dynamics that outclasses other common parameters used to justify the COVID-19 spread, given by economic, demographic, environmental, and climate factors. In addition, this study proposes, for the first time, a time-dependent correlation analysis between trade data and COVID-19 infection cases to explain the relation between confirmed cases and social interactions that are a main source of the diffusion of SARS-CoV-2 and subsequent negative impact in society. These novel findings have main theoretical and practical implications directed to include a new parameter in modelling of the diffusion of COVID-19 pandemic to support effective policy responses of crisis management directed to constrain the impact of COVID-19 pandemic and similar infectious diseases in society.

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Section: Introductionmentioning

confidence: 99%

International trade as critical parameter of COVID-19 spread that outclasses demographic, economic, environmental, and pollution factors

Bontempi

Coccia

2021

Environmental Research

103

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“…Для этой цели используются различные модели: модели логистического роста [1][2][3][4], компланарные модели типа SIR, SEIR, SIRS, SAIR [5][6][7][8][9][10][11][12] и др. более сложные [13][14][15][16], которые учитывают различные уточняющие факторы. Чем сложнее модель, тем больше неизвестных параметров она содержит, которые зачастую трудно оценить.…”

Section: математическое моделирование и прогнозирование распространения эпидемии коронавируса Covid-19unclassified

Mathematical modeling and forecasting of the spread of the COVID-19 coronavirus epidemic

Kurkina

Koltsova

2021

Futurity Designing. Digital Reality Problems

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In this paper, using the Feigenbaum logistic map, mathematical modeling of the spread of waves of the coronavirus epidemic in different countries is carried out. It is shown that the chosen model is optimal for describing the complex dynamics of the spread of infections in open, heterogeneous systems with inaccurately specified statistical data. A method for detecting local epidemic waves and determining the model parameters has been developed. It is shown that the model makes it possible to describe statistical data well and make realistic forecasts. The model is used to model the total number of cases, the total number of deaths, recoveries, and the calculation of active cases.

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“…In the last century several compartmental models in epidemiology are derivatives of the type Susceptible, Infected, and Recovered individuals (SIR), see for example [1,2] for further details and recent modeling contributions with more references therein [3][4][5][6][7]. The most widely used models, and among the simplest ones, proved to be those proposed by .…”

Section: Introductionmentioning

confidence: 99%

“…Extensions of SIR-type models have been proposed by several authors, see for example [11][12][13][14] with more reference therein, trying to capture the changes in the dynamics of the model interaction, particularly with respect to the reproductive number R 0 . An overview of some of the mathematical models in epidemiology which appeared in the literature is given in [15], enhanced with a recent publication on COVID-19 modeling a series of the parameter values (rates) given in [3,[16][17][18]. Such parameters will provide good guidelines for our parameter estimation procedure.…”

Section: Introductionmentioning

confidence: 99%

“…The theoretical result such as the existence of positive solutions and their boundedness are important by nature, such as the number of individuals or the biomass dependent on the given model, where they should be positive and bounded. In addition to studying the stability of such a system of equations, the models must be as simple as possible and complex enough as necessary to reflect the reality, see for example [3,19]. Consequently, real life data collection is very important for the parameter estimations in order to understand the interaction between the given subsystems.…”

Section: Introductionmentioning

confidence: 99%

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A mathematical model for the spread of COVID-19 and control mechanisms in Saudi Arabia

Bachar

Khamsi²,

Bounkhel

2021

Adv Differ Equ

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In this work, we develop and analyze a nonautonomous mathematical model for the spread of the new corona-virus disease (COVID-19) in Saudi Arabia. The model includes eight time-dependent compartments: the dynamics of low-risk $S_{L}$ S L and high-risk $S_{M}$ S M susceptible individuals; the compartment of exposed individuals E; the compartment of infected individuals (divided into two compartments, namely those of infected undiagnosed individuals $I_{U}$ I U and the one consisting of infected diagnosed individuals $I_{D}$ I D ); the compartment of recovered undiagnosed individuals $R_{U}$ R U , that of recovered diagnosed $R_{D}$ R D individuals, and the compartment of extinct Ex individuals. We investigate the persistence and the local stability including the reproduction number of the model, taking into account the control measures imposed by the authorities. We perform a parameter estimation over a short period of the total duration of the pandemic based on the COVID-19 epidemiological data, including the number of infected, recovered, and extinct individuals, in different time episodes of the COVID-19 spread.

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A simple but complex enough θ-SIR type model to be used with COVID-19 real data. Application to the case of Italy

Cited by 33 publications

References 34 publications

International trade as critical parameter of COVID-19 spread that outclasses demographic, economic, environmental, and pollution factors

International trade as critical parameter of COVID-19 spread that outclasses demographic, economic, environmental, and pollution factors

Mathematical modeling and forecasting of the spread of the COVID-19 coronavirus epidemic

A mathematical model for the spread of COVID-19 and control mechanisms in Saudi Arabia

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