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Electronic circuit implementation of the compartmental models for population dynamics of COVID-19 like epidemics

Modelling of population dynamics of epidemic diseases is crucial in developing effective strategies for curbing the diseases. It helps us identify the various parameters that can help control the epidemic if the modelling is done carefully. Physical modelling of the dynamics in the form of circuits...

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Detalles Bibliográficos
Autores principales: THAFASAL IJYAS, V P, MAYET, ABDULILAH MOHAMMAD
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer India 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896071/
http://dx.doi.org/10.1007/s12046-022-01821-6
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author THAFASAL IJYAS, V P
MAYET, ABDULILAH MOHAMMAD
author_facet THAFASAL IJYAS, V P
MAYET, ABDULILAH MOHAMMAD
author_sort THAFASAL IJYAS, V P
collection PubMed
description Modelling of population dynamics of epidemic diseases is crucial in developing effective strategies for curbing the diseases. It helps us identify the various parameters that can help control the epidemic if the modelling is done carefully. Physical modelling of the dynamics in the form of circuits and systems can augment the understanding of disease mechanisms. In this paper, we develop two electronic circuit models for realizing the dynamics of two compartmental models widely used in epidemiological studies. These models are important in the context of the current, rampant COVID-19 global pandemic. This innovative study will no doubt pave the way for developing electronic circuits and analog processing systems that can simulate the dynamics of more complex population models.
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spelling pubmed-88960712022-03-04 Electronic circuit implementation of the compartmental models for population dynamics of COVID-19 like epidemics THAFASAL IJYAS, V P MAYET, ABDULILAH MOHAMMAD Sādhanā Article Modelling of population dynamics of epidemic diseases is crucial in developing effective strategies for curbing the diseases. It helps us identify the various parameters that can help control the epidemic if the modelling is done carefully. Physical modelling of the dynamics in the form of circuits and systems can augment the understanding of disease mechanisms. In this paper, we develop two electronic circuit models for realizing the dynamics of two compartmental models widely used in epidemiological studies. These models are important in the context of the current, rampant COVID-19 global pandemic. This innovative study will no doubt pave the way for developing electronic circuits and analog processing systems that can simulate the dynamics of more complex population models. Springer India 2022-03-04 2022 /pmc/articles/PMC8896071/ http://dx.doi.org/10.1007/s12046-022-01821-6 Text en © Indian Academy of Sciences 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
THAFASAL IJYAS, V P
MAYET, ABDULILAH MOHAMMAD
Electronic circuit implementation of the compartmental models for population dynamics of COVID-19 like epidemics
title Electronic circuit implementation of the compartmental models for population dynamics of COVID-19 like epidemics
title_full Electronic circuit implementation of the compartmental models for population dynamics of COVID-19 like epidemics
title_fullStr Electronic circuit implementation of the compartmental models for population dynamics of COVID-19 like epidemics
title_full_unstemmed Electronic circuit implementation of the compartmental models for population dynamics of COVID-19 like epidemics
title_short Electronic circuit implementation of the compartmental models for population dynamics of COVID-19 like epidemics
title_sort electronic circuit implementation of the compartmental models for population dynamics of covid-19 like epidemics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896071/
http://dx.doi.org/10.1007/s12046-022-01821-6
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