Management strategies in a SEIR-type model of COVID 19 community spread

Rǎdulescu, Anca; Williams, Cassandra; Cavanagh, Kieran

doi:10.1038/s41598-020-77628-4

Cited by 169 publications

(140 citation statements)

References 30 publications

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“…In Pereira et al (2020), a mathematical model to predict the infection dynamics of Brazil is studied. In Rǎdulescu et al (2020), a traditional mathematical model for the dynamics of spread in the New York State is considered to predict the infection. In Kyrychko et al (2020), a mathematical model for the dynamics of the transmission of the disease in Ukraine is analyzed.…”

Section: Literature Survey On Mathematical Modelsmentioning

confidence: 99%

RETRACTED ARTICLE: The prediction of the lifetime of the new coronavirus in the USA using mathematical models

Selvakumar

Lokesh

2021

Soft Comput

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The World Health Organization (WHO) on December 31, 2019, was informed of several cases of respiratory diseases of unknown origin in the city of Wuhan in the Chinese Province of Hubei, the clinical manifestations of which were similar to those of viral pneumonia and manifested as fever, cough, and shortness of breath. And, the disease caused by the virus is named the new coronavirus disease 2019 and it will be abbreviated as 2019-nCoV and COVID-19. As of January 30, 2020, the WHO classified this epidemic as a global health emergency (Chung et al. in Radiology 295(1):202–207, 2020). It is an international real-life problem. Due to deaths, globally everyone is under fear. Now, it is the responsibility of researchers to give hope to the people. In this article, we aim to better protect people and general pandemic preparedness by predicting the lifetime of the disease-causing virus using three mathematical models. This article deals with a complex real-life problem people face all over the world, an international real-life problem. The main focus is on the USA due to large infection and death due to coronavirus and thereby the life of every individual is uncertain. The death counts of the USA from February 29 to April 22, 2020, are used in this article as a data set. The death counts of the USA are fitted by the solutions of three mathematical models and a solution to an international problem is achieved. Based on the death rate, the lifetime of the coronavirus COVID-19 is predicted as 1464.76 days from February 29, 2020. That is, after March 2024 there will be no death in the USA due to COVID-19 if everyone follows the guidelines of WHO and the advice of healthcare workers. People and government can get prepared for this situation and many lives can be saved. It is the contribution of soft computing. Finally, this article suggests several steps to control the spread and severity of the disease. The research work, the lifetime prediction presented in this article is entirely new and differs from all other articles in the literature.

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Section: Literature Survey On Mathematical Modelsmentioning

confidence: 99%

RETRACTED ARTICLE: The prediction of the lifetime of the new coronavirus in the USA using mathematical models

Selvakumar

Lokesh

2021

Soft Comput

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“…Our specification of a spatial modification of the conventional SIR model adheres to the modeling philosophy that one should introduce the minimum necessary modifications of the most parsimonious model (Harris 2020b ). One might contend that the appropriate base model would instead be the SEIR (susceptible-exposed-infective-resistant) version, which has been widely employed in studies of SARS-CoV-2 transmission (Godio et al 2020 ; Radulescu et al 2020 ; Li et al 2021 ). It is hardly clear, however, that the problem of coming up with the additional between-state transition parameters in the SEIR model is any more tractable than our problem of devising an inflation factor to account for unascertained cases in Sect.…”

Section: Discussionmentioning

confidence: 99%

Los Angeles County SARS-CoV-2 Epidemic: Critical Role of Multi-generational Intra-household Transmission

Harris

2021

J Bioecon

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We observed wide variation in the incidence of confirmed COVID-19 cases in 300 communities making up Los Angeles County, the largest county by population in the United States. The surge in incidence from October 19, 2020 to January 10, 2021, accounting for two-thirds of all confirmed cases since the start of the epidemic, was concentrated in communities with a high prevalence of multi-generational households. This indicator of household structure was a more important predictor of the surge in incidence than the prevalence of households with low income or with at least one high-risk worker. Based upon a spatial adaptation of the standard SIR model, the cumulative incidence of COVID-19, adjusted for underascertainment of both asymptomatic and symptomatic cases, ranged from under 10% in low multi-generational communities to over 30% in high multi-generational communities.

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“…We assume that exposed individuals are already able to transmit the virus [43] , so the status change from

can be caused by the second-order interactions of type either

, with respective transition rate constants

and

, see Fig. 8 for an illustration.…”

Section: Modeling Covid-19 Epidemic Spreadingmentioning

confidence: 99%

Mathematical modeling of spatio-temporal population dynamics and application to epidemic spreading

Winkelmann

Zonker

Schütte

et al. 2021

Mathematical Biosciences

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Agent based models (ABMs) are a useful tool for modeling spatio-temporal population dynamics, where many details can be included in the model description. Their computational cost though is very high and for stochastic ABMs a lot of individual simulations are required to sample quantities of interest. Especially, large numbers of agents render the sampling infeasible. Model reduction to a metapopulation model leads to a significant gain in computational efficiency, while preserving important dynamical properties. Based on a precise mathematical description of spatio-temporal ABMs, we present two different metapopulation approaches (stochastic and piecewise deterministic) and discuss the approximation steps between the different models within this framework. Especially, we show how the stochastic metapopulation model results from a Galerkin projection of the underlying ABM onto a finite-dimensional ansatz space. Finally, we utilize our modeling framework to provide a conceptual model for the spreading of COVID-19 that can be scaled to real-world scenarios.

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Management strategies in a SEIR-type model of COVID 19 community spread

Cited by 169 publications

References 30 publications

RETRACTED ARTICLE: The prediction of the lifetime of the new coronavirus in the USA using mathematical models

RETRACTED ARTICLE: The prediction of the lifetime of the new coronavirus in the USA using mathematical models

Los Angeles County SARS-CoV-2 Epidemic: Critical Role of Multi-generational Intra-household Transmission

Mathematical modeling of spatio-temporal population dynamics and application to epidemic spreading

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