The local stability of a modified multi-strain SIR model for emerging viral strains

Fudolig, Miguel; Howard, Réka

doi:10.1101/2020.03.19.20039198

Cited by 21 publications

(19 citation statements)

References 36 publications

(39 reference statements)

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“…which is positive everywhere in R 2 except at the DFE where it has 0 energy. A time-varying control law α f is derived in (17), that guarantees a negative gradient of the infectious energy of the pandemic, asymptotically leading to disease free equilibrium/DFE.…”

Section: Discussionmentioning

confidence: 99%

“…However, this body of work did not consider the added complexities posed by the emergent variants of SARS-CoV-2. Some of the recent work that consider variants include multiple transmissions rates corresponding to the different strains 7 and use multiple sets of SIRV states to track the evolution of the respective viral infection strains and analyze stability 17 . Optimal control has recently been applied to variant models to compute an effective restriction policy 18,19 .…”

Section: Introductionmentioning

confidence: 99%

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COVID-19 Waves: Variant Dynamics and Control

Dutta¹

2021

Preprint

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The COVID-19 variants driven waves continue to try to nullify the success we achieved through efficacious vaccines, test and quarantine and social restrictions. This paper models the two major variants driven waves by two sets of susceptible-infected-quarantined-recovered-vaccinated-deceased coupled dynamics that is modulated by the three main interventions: vaccination, quarantine and restrictions. This SI2Q2R2VD system is used to demonstrate that the second major novel coronavirus wave in the US is caused by the delta variant and the corresponding rapid surge in infectious cases is driven by the unvaccinated pool of the populace. Next, a feedback control based planned vaccination strategy is derived and is shown to be able to suppress the surge in infections effectively.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

COVID-19 Waves: Variant Dynamics and Control

Dutta¹

2021

Preprint

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“…A potential cause of concern is the low rate of vaccine production and administration 18 coupled with reports of new strains with higher transmission rates 3,4,19 and even with potential for some degree of vaccine resistance 5,6,8,20 . A number of models considered the dynamics of the spread of a 1 vaccine-resistant strain in the population 9,10,21,22 . However, to our knowledge, the interplay of the population vaccination rate with the stochastic dynamics of emergence of a resistant strain has been discussed 23 , but not formally modeled.…”

Section: Mainmentioning

confidence: 99%

SARS-CoV-2 transmission, vaccination rate and the fate of resistant strains

Dermitzakis

et al. 2021

Preprint

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Vaccines are thought to be the best available solution for controlling the ongoing SARS-CoV-2 pandemic [1,2]. However, the emergence of vaccine-resistant strains [3-6] may come too rapidly for current vaccine developments to alleviate the health, economic and social consequences of the pandemic [7,8]. To quantify and characterize the risk of such a scenario, we created a SIR-derived model [9,10] with initial stochastic dynamics of the vaccine-resistant strain to study the probability of its emergence and establishment. Using parameters realistically resembling SARS-CoV-2 transmission, we model a wave-like pattern of the pandemic and consider the impact of the rate of vaccination and the strength of non-pharmaceutical intervention measures on the probability of emergence of a resistant strain. We found a counterintuitive result that the highest probability for the establishment of the resistant strain comes at a time of reduced non-pharmaceutical intervention measures when most individuals of the population have been vaccinated. Consequently, we show that a period of transmission reduction close to the end of the vaccination campaign can substantially reduce the probability of resistant strain establishment. Our results suggest that policymakers and individuals should consider maintaining non-pharmaceutical interventions [7,11,12] throughout the entire vaccination period.

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“…Theoretically, a newer strain may emerge in the population when a preexisting strain has reached equilibrium [ 7 ].…”

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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The local stability of a modified multi-strain SIR model for emerging viral strains

Cited by 21 publications

References 36 publications

COVID-19 Waves: Variant Dynamics and Control

COVID-19 Waves: Variant Dynamics and Control

SARS-CoV-2 transmission, vaccination rate and the fate of resistant strains

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

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