Contact rate epidemic control of COVID-19: an equilibrium view

Élie, Romuald; Hubert, Emma; Turinici, Gabriel

doi:10.1051/mmnp/2020022

Cited by 72 publications

(50 citation statements)

References 59 publications

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“…We consider a COVID-19 SEIR model [ 14 , 15 ] with vaccination control [ 19 ] as follows. where the control input V is the number of vaccinated individuals per day, N = S + E + I + R ≤ N 0 is the total population in the region ( N 0 is the initial total population in the region), S , E , I , R and D are the number of susceptible, exposed, infectious and recovered population in the region, respectively, and D is the number of deaths from SARS-CoV-2 in the region.…”

Section: Methodsmentioning

confidence: 99%

Control strategies for COVID-19 epidemic with vaccination, shield immunity and quarantine: A metric temporal logic approach

Topcu

2021

PLoS ONE

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Ever since the outbreak of the COVID-19 epidemic, various public health control strategies have been proposed and tested against the coronavirus SARS-CoV-2. We study three specific COVID-19 epidemic control models: the susceptible, exposed, infectious, recovered (SEIR) model with vaccination control; the SEIR model with shield immunity control; and the susceptible, un-quarantined infected, quarantined infected, confirmed infected (SUQC) model with quarantine control. We express the control requirement in metric temporal logic (MTL) formulas (a type of formal specification languages) which can specify the expected control outcomes such as “the deaths from the infection should never exceed one thousand per day within the next three months” or “the population immune from the disease should eventually exceed 200 thousand within the next 100 to 120 days”. We then develop methods for synthesizing control strategies with MTL specifications. To the best of our knowledge, this is the first paper to systematically synthesize control strategies based on the COVID-19 epidemic models with formal specifications. We provide simulation results in three different case studies: vaccination control for the COVID-19 epidemic with model parameters estimated from data in Lombardy, Italy; shield immunity control for the COVID-19 epidemic with model parameters estimated from data in Lombardy, Italy; and quarantine control for the COVID-19 epidemic with model parameters estimated from data in Wuhan, China. The results show that the proposed synthesis approach can generate control inputs such that the time-varying numbers of individuals in each category (e.g., infectious, immune) satisfy the MTL specifications. The results also show that early intervention is essential in mitigating the spread of COVID-19, and more control effort is needed for more stringent MTL specifications. For example, based on the model in Lombardy, Italy, achieving less than 100 deaths per day and 10000 total deaths within 100 days requires 441.7% more vaccination control effort than achieving less than 1000 deaths per day and 50000 total deaths within 100 days.

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Section: Methodsmentioning

confidence: 99%

Control strategies for COVID-19 epidemic with vaccination, shield immunity and quarantine: A metric temporal logic approach

Topcu

2021

PLoS ONE

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“…Local authorities needed to continuously verify compliance with mitigation measures through monitoring by health officials and police actions (checkpoints, use of drones, fine or jail threats etc.). This behaviour might be related to costs that individuals affected by epidemic control measures paid in terms of health, including loss of social relationships, psychological pressure, increasing stress and health hazards resulting in a substantial damage to population well-being [ 12 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

Effects of information-induced behavioural changes during the COVID-19 lockdowns: the case of Italy

Buonomo

Marca

2020

R. Soc. open sci.

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The COVID-19 pandemic that started in China in December 2019 has not only threatened world public health, but severely impacted almost every facet of life, including behavioural and psychological aspects. In this paper, we focus on the ‘human element’ and propose a mathematical model to investigate the effects on the COVID-19 epidemic of social behavioural changes in response to lockdowns. We consider an SEIR-like epidemic model where the contact and quarantine rates depend on the available information and rumours about the disease status in the community. The model is applied to the case of the COVID-19 epidemic in Italy. We consider the period that stretches between 24 February 2020, when the first bulletin by the Italian Civil Protection was reported and 18 May 2020, when the lockdown restrictions were mostly removed. The role played by the information-related parameters is determined by evaluating how they affect suitable outbreak-severity indicators. We estimate that citizen compliance with mitigation measures played a decisive role in curbing the epidemic curve by preventing a duplication of deaths and about 46% more infections.

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“…As commonly done in the current literature, we do not take into account the reaction of individuals in response to the virus prevalence dynamics, as discussed e.g. in Elie et al (2020). Anticipating realistic individuals behaviors in such context is still difficult, as no available data allows to tackle this phenomenon properly.…”

Section: Numerical Approximation Of the Solutionmentioning

confidence: 99%

COVID-19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability

Charpentier

Élie

Laurière

et al. 2020

Math. Model. Nat. Phenom.

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An extended SIR model, including several features of the recent COVID-19 outbreak, is considered: the infected and recovered individuals can either be detected or undetected and we also integrate an intensive care unit (ICU) capacity. We identify the optimal policy for controlling the epidemic dynamics using both lockdown and detection intervention levers, and taking into account the trade-off between the sanitary and the socio-economic cost of the pandemic, together with the limited capacity level of ICU. With parametric specification based on the COVID-19 literature, we investigate the sensitivities of various quantities on the optimal strategies. The optimal lockdown policy is structured into 4 phases: First a quick and strong lockdown intervention to stop the exponential growth of the contagion; second a short transition to reduce the prevalence of the virus; third a long period with full ICU capacity and stable virus prevalence; finally a return to normal social interactions with disappearance of the virus. The optimal scenario avoids the second wave of infection, provided the lockdown is released sufficiently slowly. Whenever massive resources are introduced to detect infected individuals, the pressure on social distancing can be released, whereas the impact of detection of immune individuals reveals to be more moderate.

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Contact rate epidemic control of COVID-19: an equilibrium view

Cited by 72 publications

References 59 publications

Control strategies for COVID-19 epidemic with vaccination, shield immunity and quarantine: A metric temporal logic approach

Control strategies for COVID-19 epidemic with vaccination, shield immunity and quarantine: A metric temporal logic approach

Effects of information-induced behavioural changes during the COVID-19 lockdowns: the case of Italy

COVID-19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability

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