Detecting infected asymptomatic cases in a stochastic model for spread of Covid-19: the case of Argentina

Barreiro, N. L.; Govezensky, Tzipe; Bolcatto, P. G.; Barrio, Rafael A.

doi:10.1038/s41598-021-89517-5

Cited by 15 publications

(17 citation statements)

References 30 publications

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“…We emphasise that the model is applicable to any country with reliable data, as shown here for UK with the main variants of concern, and previously for Finland, Iceland, Mexico, Spain and Argentina [15][16][17] . The social parameters included in the model, as the different mobility types, allow to distinguish the effects of behavioural and cultural differences.…”

Section: Discussionsupporting

confidence: 54%

“…Survival parameter 0.99 δ Vaccination immunity period 180/360 days η threshold to start an infection focus 0.00005 (c) (a) This value was set to 0 for the Delta variant in order to get a better fit. (b) Values fitted and used with this model in previous works [15][16][17] . (c) Corresponds to start an infection focus with 1 infected person in an averagely populated area.…”

Section: Parametermentioning

confidence: 99%

“…Accordingly, we propose the development of a stochastic geographic expansion model, that includes several different strains, to study the emergence and dynamics of these new variants. The model is based on a previously used discrete mathematical map that starts from an extended SEIRS model [14][15][16][17] . The model is applied to the case of the UK by fitting the actual properties of each strain with the available data.…”

Section: Introductionmentioning

confidence: 99%

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Modelling the interplay of SARS-CoV-2 variants in the United Kingdom

Barreiro

Govezensky

Ventura

et al. 2021

Preprint

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Most COVID-19 vaccines have proved to be effective to combat the pandemic and to prevent severe disease but their distribution proceeds in a context of global vaccine shortage Their uneven distribution favors the appearance of new variants of concern, as the highly transmissible Delta variant, affecting especially non-vaccinated people. We consider that devising reliable models to analyse the spread of the different variants is crucial. These models should include the effects of vaccination as well as non-pharmaceutical measures used to contain the pandemic by modifying social behaviour. In this work, we present a stochastic geographical model that fulfills these requirements. It consists of an extended compartmental model that includes various strains and vaccination strategies, allowing to study the emergence and dynamics of the new COVID-19 variants. The models conveniently separates the parameters related to the disease from the ones related to social behavior and mobility restrictions. The geographical spread of the virus is modeled taking into account the actual population distribution in any given country of interest. Here we choose the UK as model system, taking advantage of the reliable available data, in order to fit the recurrence of the currently prevalent variants. Our computer simulations allow to describe some global features observed in the daily number of cases, as the appearance of periodic waves and the features that determine the prevalence of certain variants. They also provide useful predictions aiming to help planning future vaccination boosters. We stress that the model could be applied to any other country of interest.

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Section: Discussionsupporting

confidence: 54%

Section: Parametermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modelling the interplay of SARS-CoV-2 variants in the United Kingdom

Barreiro

Govezensky

Ventura

et al. 2021

Preprint

Self Cite

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“…In this publication our model is updated to November 20th 2020, when it was first submitted to this journal. Since then it has been extended to consider tracking and isolating asymptomatic individuals [38] , and also to take into account vaccinations and related strategies for mitigating the pandemic [39] , and at the moment we are applying it to study the emergence of new virus variants and their changed epidemiological properties. In these publications we can reproduce the new waves that have been seen during 2021.…”

Section: Discussionmentioning

confidence: 99%

A model for social spreading of Covid-19: Cases of Mexico, Finland and Iceland

Barrio¹,

Kaski²,

Haraldsson³

et al. 2021

Physica A: Statistical Mechanics and its Applications

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The shocking severity of the Covid-19 pandemic has woken up an unprecedented interest and accelerated effort of the scientific community to model and forecast epidemic spreading to find ways to control it regionally and between regions. Here we present a model that in addition to describing the dynamics of epidemic spreading with the traditional compartmental approach takes into account the social behaviour of the population distributed over a geographical region. The region to be modelled is defined as a two-dimensional grid of cells, in which each cell is weighted with the population density. In each cell a compartmental SEIRS system of delay difference equations is used to simulate the local dynamics of the disease. The infections between cells are modelled by a network of connections, which could be terrestrial, between neighbouring cells, or long range, between cities by air, road or train traffic. In addition, since people make trips without apparent reason, noise is considered to account for them to carry contagion between two randomly chosen distant cells. Hence, there is a clear separation of the parameters related to the biological characteristics of the disease from the ones that represent the spatial spread of infections due to social behaviour. We demonstrate that these parameters provide sufficient information to trace the evolution of the pandemic in different situations. In order to show the predictive power of this kind of approach we have chosen three, in a number of ways different countries, Mexico, Finland and Iceland, in which the pandemics have followed different dynamic paths. Furthermore we find that our model seems quite capable of reproducing the path of the pandemic for months with few initial data. Unlike similar models, our model shows the emergence of multiple waves in the case when the disease becomes endemic.

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“…This family of classical compartmental models can be useful tools only if a degree of local stochasticity is added 9 , 10 , accounting for the social behavior (mobility, familiar relationships, etc.) 11 . In this work, we have extended previous approaches by including the possibility of a decrease in the number of susceptible people, as a consequence of a schedule of massive vaccination.…”

Section: Introductionmentioning

confidence: 99%

Strategies for COVID-19 vaccination under a shortage scenario: a geo-stochastic modelling approach

Barreiro

Ventura

Govezensky

et al. 2022

Sci Rep

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In a world being hit by waves of COVID-19, vaccination is a light on the horizon. However, the roll-out of vaccination strategies and their influence on the pandemic are still open questions. In order to compare the effect of various strategies proposed by the World Health Organization and other authorities, a previously developed SEIRS stochastic model of geographical spreading of the virus is extended by adding a compartment for vaccinated people. The parameters of the model were fitted to describe the pandemic evolution in Argentina, Mexico and Spain to analyze the effect of the proposed vaccination strategies. The mobility parameters allow to simulate different social behaviors (e.g. lock-down interventions). Schemes in which vaccines are applied homogeneously in all the country, or limited to the most densely-populated areas, are simulated and compared. The second strategy is found to be more effective. Moreover, under the current global shortage of vaccines, it should be remarked that immunization is enhanced when mobility is reduced. Additionally, repetition of vaccination campaigns should be timed considering the immunity lapse of the vaccinated (and recovered) people. Finally, the model is extended to include the effect of isolation of detected positive cases, shown to be important to reduce infections.

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Detecting infected asymptomatic cases in a stochastic model for spread of Covid-19: the case of Argentina

Cited by 15 publications

References 30 publications

Modelling the interplay of SARS-CoV-2 variants in the United Kingdom

Modelling the interplay of SARS-CoV-2 variants in the United Kingdom

A model for social spreading of Covid-19: Cases of Mexico, Finland and Iceland

Strategies for COVID-19 vaccination under a shortage scenario: a geo-stochastic modelling approach

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