Mathematical modelling and optimal cost-effective control of COVID-19 transmission dynamics

Olaniyi, Samson; Obabiyi, O.S.; Okosun, Kazeem Oare; Oladipo, Abiodun Tinuoye; Adewale, S. O.

doi:10.21203/rs.3.rs-84331/v1

Cited by 5 publications

(4 citation statements)

References 17 publications

(18 reference statements)

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“…The need of integrated science to fight the COVID-19 pandemic is apparent [ 8 ]. Different approaches are necessary ranging from mouse models [ 9 ] or behavioural response of the population [ 10 ] to mathematical and simulation models [ 11 ].…”

Section: Numerical Simulations For the New Strainmentioning

confidence: 99%

Forecasting the Effects of the New SARS-CoV-2 Variant in Europe

Area

Nieto

2021

The Scientific World Journal

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Due to the emergence of a new SARS-CoV-2 variant, we use a previous model to simulate the behaviour of this new SARS-CoV-2 variant. The analysis and simulations are performed for Europe, in order to provide a global analysis of the pandemic. In this context, numerical results are obtained in the first 100 days of the pandemic assuming an infectivity of 70%, 56%, and 35%, respectively, higher for the new SAR-CoV-2 variant, as compared with the real data.

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Section: Numerical Simulations For the New Strainmentioning

confidence: 99%

Forecasting the Effects of the New SARS-CoV-2 Variant in Europe

Area

Nieto

2021

The Scientific World Journal

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“…It is important to note that in each simulation, the presence of two strain types in the community is taken into account. Table 1 presents the parameter values for various models of Covid-19, which are derived from ten different references [15,39,[48][49][50][51][52][53][54][55]. Notably, the units in the table are given in terms of per day (day −1 ).…”

Section: Plos Onementioning

confidence: 99%

Omicron vs. the rest: Assessing the competitive dynamics and coinfection scenarios of COVID-19 strains on a social network

Jabraeilian,

Jamali

2024

PLoS ONE

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The rapid spread and evolving nature of COVID-19 variants have raised concerns regarding their competitive dynamics and coinfection scenarios. In this study, we assess the competitive interactions between the Omicron variant and other prominent variants (Alpha, Beta and Delta) on a social network, considering both single infection and coinfection states. Using the SIRS model, we simulate the progression of these variants and analyze their impact on infection rates, mortality and overall disease burden. Our findings demonstrate that the Alpha and Beta strains exhibit comparable contagion levels, with the Alpha strain displaying higher infection and mortality rates. Moreover, the Delta strain emerges as the most prevalent and virulent strain, surpassing the other variants. When introduced alongside the less virulent Omicron strain, the Delta strain results in higher infection and mortality rates. However, the Omicron strain’s dominance leads to an overall increase in disease statistics. Remarkably, our study highlights the efficacy of the Omicron variant in supplanting more virulent strains and its potential role in mitigating the spread of infectious diseases. The Omicron strain demonstrates a competitive advantage over the other variants, suggesting its potential to reduce the severity of the disease and alleviate the burden on healthcare systems. These findings underscore the importance of monitoring and understanding the dynamics of COVID-19 variants, as they can inform effective prevention and mitigation strategies, particularly with the emergence of variants that possess a relative advantage in controlling disease transmission.

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Section: Single Infection Modelmentioning

confidence: 99%

Omicron vs. the Rest: Assessing the Competitive Dynamics and Coinfection Scenarios of COVID-19 Strains on a Social Network

Jabraeilian,

Jamali

2023

Preprint

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The rapid spread and evolving nature of COVID-19 variants have raised concerns regarding their competitive dynamics and coinfection scenarios. In this study, we assess the competitive interactions between the Omicron variant and other prominent variants (Alpha, Beta, and Delta) on a social network, considering both single infection and coinfection states. Using the SIRS model, we simulate the progression of these variants and analyze their impact on infection rates, mortality, and overall disease burden. Our findings demonstrate that the Alpha and Beta strains exhibit comparable contagion levels, with the Alpha strain displaying higher infection and mortality rates. Moreover, the Delta strain emerges as the most prevalent and virulent strain, surpassing the other variants. When introduced alongside the less virulent Omicron strain, the Delta strain results in higher infection and mortality rates. However, the Omicron strain's dominance leads to an overall increase in disease statistics. Remarkably, our study highlights the efficacy of the Omicron variant in supplanting more virulent strains and its potential role in mitigating the spread of infectious diseases. The Omicron strain demonstrates a competitive advantage over the other variants, suggesting its potential to reduce the severity of the disease and alleviate the burden on healthcare systems. These findings underscore the importance of monitoring and understanding the dynamics of COVID-19 variants, as they can inform effective prevention and mitigation strategies, particularly with the emergence of variants that possess a relative advantage in controlling disease transmission.

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Mathematical modelling and optimal cost-effective control of COVID-19 transmission dynamics

Cited by 5 publications

References 17 publications

Forecasting the Effects of the New SARS-CoV-2 Variant in Europe

Forecasting the Effects of the New SARS-CoV-2 Variant in Europe

Omicron vs. the rest: Assessing the competitive dynamics and coinfection scenarios of COVID-19 strains on a social network

Omicron vs. the Rest: Assessing the Competitive Dynamics and Coinfection Scenarios of COVID-19 Strains on a Social Network

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