Gompertz model in COVID-19 spreading simulation

Pelinovsky, Efim; Kokoulina, M.V.; Epifanova, A.S.; Kurkin, Andrey; Kurkina, Oxana; Tang, Ming; Macau, Elbert E. N.; Kirillin, Mikhail

doi:10.1016/j.chaos.2021.111699

Cited by 27 publications

(10 citation statements)

References 20 publications

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“…Such compartmental models are also fundamental in approaches that employ the concept of complex networks to describe the epidemic dynamics in a large population with heterogeneous spatial distribution [32][33][34][35][36] . It is also quite common to describe the evolution of epidemic waves with aid of purely phenomenological models, supported by frequentist [37][38][39][40][41][42][43][44][45] or Bayesian 46,47 statistical approaches.…”

Section: Introductionmentioning

confidence: 99%

The starting dates of COVID-19 multiple waves

Gianfelice

Oyarzabal

Cunha

et al. 2022

Chaos: An Interdisciplinary Journal of Nonlinear Science

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The severe acute respiratory syndrome of coronavirus 2 spread globally very quickly, causing great concern at the international level due to the severity of the associated respiratory disease, the so-called COVID-19. Considering Rio de Janeiro city (Brazil) as an example, the first diagnosis of this disease occurred in March 2020, but the exact moment when the local spread of the virus started is uncertain as the Brazilian epidemiological surveillance system was not widely prepared to detect suspected cases of COVID-19 at that time. Improvements in this surveillance system occurred over the pandemic, but due to the complex nature of the disease transmission process, specifying the exact moment of emergence of new community contagion outbreaks is a complicated task. This work aims to propose a general methodology to determine possible start dates for the multiple community outbreaks of COVID-19, using for this purpose a parametric statistical approach that combines surveillance data, nonlinear regression, and information criteria to obtain a statistical model capable of describing the multiple waves of contagion observed. The dynamics of COVID-19 in the city of Rio de Janeiro is taken as a case study, and the results suggest that the original strain of the virus was already circulating in Rio de Janeiro city as early as late February 2020, probably being massively disseminated in the population during the carnival festivities.

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Section: Introductionmentioning

confidence: 99%

The starting dates of COVID-19 multiple waves

Gianfelice

Oyarzabal

Cunha

et al. 2022

Chaos: An Interdisciplinary Journal of Nonlinear Science

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“…For example, Ref. [23] applied Gompertz model to describe the growth dynamics of COVID-19 pandemic. Gompertz [20] studied human mortality for working out a series of mortality tables, and this suggested to him his law of human mortality in which he assumed that the person's resistance to death decreases as the age increases.…”

Section: Gompertz Functions and Gompertz Rulementioning

confidence: 99%

On the Kaniadakis distributions applied in statistical physics and natural sciences

Wada¹,

Scarfone²

2023

Preprint

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“…The Gompertz model is a growth curve that predicts change (Pelinovsky et al, 2022) and is a good predictor of emulsified asphalt mortars' growth and development process. In this study, we employ the Gompertz model to investigate the viscosity growth law of emulsified asphalt during the Frontiers in Materials frontiersin.org demulsification stage to determine the demulsification speed of emulsified asphalt mortar.…”

Section: The Gompertz Modelmentioning

confidence: 99%

Influence of aggregate chemical composition on the demulsification rate of emulsified asphalt

et al. 2022

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Efficient demulsification is vital for the application of emulsified asphalt in road construction. In this paper, the effects of the main chemical components of the aggregates (CaCO3, MgO, Fe2O3, SiO2, Al2O3) on the demulsification process of emulsified asphalt were studied by experiment and simulation using a Gompertz model. The findings indicate that the surface energy, specific surface area, and pH of the chemical components of the aggregates are the most important factors influencing the demulsification speed of the emulsified asphalt. The choice of the aggregate’s main chemical components can accelerate demulsification speed, with the acceleration effect of Al2O3 on anionic (SDBS) emulsified asphalt and MgO on cationic (STAC) emulsified asphalt both reaching 60%. The fit between the Gompertz model and the experimental viscosity curve is greater than 0.93, which verifies the utility of using the Gompertz approach for studying emulsified asphalt-aggregate mortar viscosity changes. A demulsification evaluation function φ(t) of emulsified asphalt is proposed based on the parameters of the Gompertz model. When φ(t) is close to 1, the emulsified asphalt-aggregate mortar is fully demulsified, and setting φ(t)=1 allows the demulsification time of the emulsified asphalt-aggregate mortar to be calculated from the Gompertz model parameters.

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Gompertz model in COVID-19 spreading simulation

Cited by 27 publications

References 20 publications

The starting dates of COVID-19 multiple waves

The starting dates of COVID-19 multiple waves

On the Kaniadakis distributions applied in statistical physics and natural sciences

Influence of aggregate chemical composition on the demulsification rate of emulsified asphalt

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