A control framework to optimize public health policies in the course of the COVID-19 pandemic

Pataro, Igor M. L.; Oliveira, Juliane F.; Morato, Marcelo Menezes; Amad, Alan A. S.; Ramos, Pablo Ivan Pereira; Pereira, Felipe Ladeira; Silva, Mateus S.; Jorge, Daniel Cardoso Pereira; Andrade, Roberto F. S.; Barreto, Maurício Lima; Costa, Marcus V. Americano da

doi:10.1101/2021.01.28.21250692

Cited by 3 publications

(2 citation statements)

References 43 publications

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“…The approach is to propose optimal levels of social mobility considering economic and health aspects. As can be seen in Figure 14, the control system calculates optimal stringency values (u(k)) [27] with relevant results. Therefore, the system presented here has a real possibility to be implemented in practice.…”

Section: Perspectives Of Control Engineering Applicationsmentioning

confidence: 99%

“…The critical matter is when applying the social distancing and for how long. In this sense, the control engineering aided by epidemiological models can determine strategies of social distancing that balance health and economic aspects [24][25][26][27]. For this, a social distancing variable has to be incorporated into the epidemiological models.…”

Section: Introductionmentioning

confidence: 99%

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A Real-Time Identification Algorithm and Epidemic Model Associated with Social Distancing Index for Control Applications: COVID-19 Analysis and Simulations in the United States

Costaa

2021

BJSTR

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The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is already the most worrying health problem worldwide. The virus spread rapidly across the countries, making many researchers looking for answers to mitigate the disease's effects. While vaccines are not available on a large scale, mathematical modeling has allowed the scientific community to perform forecasts for decision-making and social distancing policies to decrease the velocity of the COVID-19 transmission. However, dynamic models must represent the pandemic's reality considering validation criteria and an appropriate procedure that ensures realistic simulations. These principles are the only way to make an epidemiological model useful for studying and analyzing practical effects. From a control theory point of view, representative models ensure optimal solutions and allow a more reliable and robust control strategy. Therefore, this paper proposes a parameter identification algorithm for a dynamic pandemic disease model spread, including a new time-varying parameter for control applications. The developed framework uses an epidemiological model, denoted here as , capable of associating the real pandemic dynamics to its biological parameters and the population social mobility in real-time, which can be led by an appropriate optimal control strategy. Simulations and forecasts are performed comparing with official data of the epidemic in the United States.

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Section: Perspectives Of Control Engineering Applicationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Real-Time Identification Algorithm and Epidemic Model Associated with Social Distancing Index for Control Applications: COVID-19 Analysis and Simulations in the United States

Costaa

2021

BJSTR

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Assessing the nationwide impact of COVID-19 mitigation policies on the transmission rate of SARS-CoV-2 in Brazil

Jorge

Vilela

Silva

et al. 2020

Preprint

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COVID-19 is now identified in almost all countries in the world, with poorer regions being particularly more disadvantaged to efficiently mitigate the impacts of the pandemic. In the absence of efficient therapeutics or vaccines, control strategies are currently based on non-pharmaceutical interventions, comprising changes in population behavior and governmental interventions, among which the prohibition of mass gatherings, closure of non-essential establishments, quarantine and movement restrictions. In this work we analyzed the effects of 547 published governmental interventions, and population adherence thereof, on the dynamics of COVID-19 cases across all 27 Brazilian states, with emphasis on state capitals and remaining inland cities. A generalized SEIR model with a time-varying transmission rate (TR), that considers transmission by asymptomatic individuals, is presented. Confirmed COVID-19 cases were used to calibrate the model parameters using non-linear least squares methods. We analyze the changes on the TR and effective reproduction number as a function of both the extent of enforced measures across Brazilian states as well as population movement. The social mobility reduction index, a measure of population movement, together with the stringency index, adapted to incorporate the degree of restrictions imposed by governmental regulations, were used in conjunction to quantify and compare the effects of varying degrees of policy strictness across Brazilian states. Our results show that population adherence to social distance recommendations plays an important role for the effectiveness of interventions, and represents a major challenge to the control of COVID-19 in low- and middle-income countries.

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Where is the Third E in Controlling Coronavirus Disease-19 in Indonesia? A Mini Review

Sirait

Zaluchu

2021

Open Access Maced J Med Sci

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Coronavirus disease (COVID-19) continues to attract global attention and is the most serious health problem today. Indonesia faces a very significant spike in cases in mid-2021. This may be related to inadequate enforcement before cases reach their peak. To review what has happened and what should be done in the future, this paper presents the three Es concept to be applied more consistently in efforts to control COVID-19 in Indonesia.

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A control framework to optimize public health policies in the course of the COVID-19 pandemic

Cited by 3 publications

References 43 publications

A Real-Time Identification Algorithm and Epidemic Model Associated with Social Distancing Index for Control Applications: COVID-19 Analysis and Simulations in the United States

A Real-Time Identification Algorithm and Epidemic Model Associated with Social Distancing Index for Control Applications: COVID-19 Analysis and Simulations in the United States

Assessing the nationwide impact of COVID-19 mitigation policies on the transmission rate of SARS-CoV-2 in Brazil

Where is the Third E in Controlling Coronavirus Disease-19 in Indonesia? A Mini Review

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