Management strategies in a SEIR model of COVID 19 community spread

Rǎdulescu, Anca; Williams, Cassandra; Cavanagh, Kieran

doi:10.48550/arxiv.2003.11150

Cited by 9 publications

(9 citation statements)

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“…Because we model transmissions as occurring across a contact network (which is a substantially different model than has been commonly used to date for this virus) comparison of this model parameter is difficult. However, two studies (Fang et al, 2020;Radulescu and Cavanagh, 2020) which have comparable interpretations of this parameter to ours both use a value of β = 0.1, which we also take as our baseline value for this parameter.…”

Section: Applying the Sei(q)r Model To Sars-cov-2mentioning

confidence: 90%

Modifying the Network-Based Stochastic SEIR Model to Account for Quarantine

Groendyke,

Combs

2020

Preprint

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In this article, we present a modification to the network-based stochastic SEIR epidemic model which allows for modifications to the underlying contact network to account for the effects of quarantine. We also discuss the changes needed to the model to incorporate situations where some proportion of the individuals who are infected remain asymptomatic throughout the course of the disease. Using a generic network model where every potential contact exists with the same common probability, we conduct a simulation study in which we vary four key model parameters (transmission rate, probability of remaining asymptomatic, and the mean lengths of time spent in the Exposed and Infectious disease states) and examine the resulting impacts on various metrics of epidemic severity, including the effective reproduction number. We find that the mean length of time spent in the Infectious state and the transmission rate are the most important model parameters, while the mean length of time spent in the Exposed state and the probability of remaining asymptomatic are less important.

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Section: Applying the Sei(q)r Model To Sars-cov-2mentioning

confidence: 90%

Modifying the Network-Based Stochastic SEIR Model to Account for Quarantine

Groendyke,

Combs

2020

Preprint

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“…SEIR model has also been recently adopted in the analysis of the COVID-19 pandemic 4,49,50 . The SEIR model assumes individuals carry lifelong immunity to the disease upon recovery, however, there have been clinical findings showing that patients who have recovered from COVID-19 can get reinfected with the virus [51][52][53] . Even though the immune response to this novel virus is not yet fully understood, the possibility of reinfection cannot be ruled out.…”

Section: Epidemiological Modelmentioning

confidence: 99%

Evaluation of non-pharmaceutical interventions and optimal strategies for containing the COVID-19 pandemic

Zhou¹,

Zhang²,

Santi³

et al. 2022

Preprint

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Given multiple new COVID-19 variants are continuously emerging, non-pharmaceutical interventions are still primary control strategies to curb the further spread of coronavirus. However, implementing strict interventions over extended periods of time is inevitably hurting the economy. With an aim to solve this multi-objective decision-making problem, we investigate the underlying associations between policies, mobility patterns, and virus transmission. We further evaluate the relative performance of existing COVID-19 control measures and explore potential optimal strategies that can strike the right balance between public health and socio-economic recovery for individual states in the US. The results highlight the power of state of emergency declaration and wearing face masks and emphasize the necessity of pursuing tailor-made strategies for different states and phases of epidemiological transmission. Our framework enables policymakers to create more refined designs of COVID-19 strategies and can be extended to inform policy makers of any country about best practices in pandemic response.

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“…Other studies have been developed to investigate the influence of interventional policies. Radulescu et al (2020) developed a mathematical model to predict the extent of the disease diffusion by considering existing policies such as transportation constraints, reduction of service levels, as well as social distancing. Using the SEIR model, Godio et al (2020) studied the prevalence of the SARS Co-2 with a random approach to optimize model parameters using particle swarm optimization K 51,8 method to increase the reliability of predictions and show that changes in transmission rates have a great impact on how to implement the general quarantine policy.…”

Section: Literature Reviewmentioning

confidence: 99%

A system dynamics approach to COVID-19 pandemic control: a case study of Iran

Abdolhamid

Pishvaee

Aalikhani

et al. 2021

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PurposeThe purpose of this paper is to develop a system dynamics approach based on Susceptible, Exposed, Infected, Recovered (SEIR) model to investigate the coronavirus pandemic and the impact of therapeutic and preventive interventions on epidemic disaster.Design/methodology/approachTo model the behavior of COVID-19 disease, a system dynamics model is developed in this paper based on SEIR model. In the proposed model, the impact of people's behavior, contact reduction, isolation of the sick people as well as public quarantine on the spread of diseases is analyzed. In this model, data collected by the Iran Ministry of Health have been used for modeling and verification of the results.FindingsThe results show that besides the intervening policies, early application of them is also of utmost priority and makes a significant difference in the result of the system. Also, if the number of patients with extreme conditions passes available hospital intensive care capacity, the death rate increases dramatically. Intervening policies play an important role in reducing the rate of infection, death and consequently control of pandemic. Also, results show that if proposed policies do not work before the violation of the hospital capacity, the best policy is to increase the hospital’s capacity by adding appropriate equipment.Research limitations/implicationsThe authors also had some limitations in the study including the lack of access to precise data regarding the epidemic of coronavirus, as well as accurate statistics of death rate and cases in the onset of the virus due to the lack of diagnostic kits in Iran. These parameters are still part of the problem and can negatively influence the effectiveness of intervening policies introduced in this paper.Originality/valueThe contribution of this paper includes the development of SEIR model by adding more policymaking details and considering the constraint of the hospital and public health capacity in the rate of coronavirus infection and death within a system dynamics modeling framework.

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Management strategies in a SEIR model of COVID 19 community spread

Cited by 9 publications

References 0 publications

Modifying the Network-Based Stochastic SEIR Model to Account for Quarantine

Modifying the Network-Based Stochastic SEIR Model to Account for Quarantine

Evaluation of non-pharmaceutical interventions and optimal strategies for containing the COVID-19 pandemic

A system dynamics approach to COVID-19 pandemic control: a case study of Iran

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