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A co-infection model on TB - COVID-19 with optimal control and sensitivity analysis
COVID-19 had been declared a public health emergency by the World Health Organization in the early 2020. Since then, this deadly virus has claimed millions of lives worldwide. Amidst its chaotic spread, several other diseases have faced negligence in terms of treatment and care, of which one such ch...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013278/ https://www.ncbi.nlm.nih.gov/pubmed/35462786 http://dx.doi.org/10.1016/j.matcom.2022.04.001 |
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author | Bandekar, Shraddha Ramdas Ghosh, Mini |
author_facet | Bandekar, Shraddha Ramdas Ghosh, Mini |
author_sort | Bandekar, Shraddha Ramdas |
collection | PubMed |
description | COVID-19 had been declared a public health emergency by the World Health Organization in the early 2020. Since then, this deadly virus has claimed millions of lives worldwide. Amidst its chaotic spread, several other diseases have faced negligence in terms of treatment and care, of which one such chronic disease is Tuberculosis. Due to huge rise in COVID-19 cases, there had been a drastic decrease in notification of TB cases which resulted in reversal of global TB target progress. Apart from these due to the earlier co-infections of TB with SARS and MERS-CoV viruses, the TB-COVID-19 co-infection posed a severe threat in the spread of the disease. All these factors backed to be major motivation factor in development of this model. Leading with this concern, a TB - COVID-19 co-infection model is developed in this study, considering possibility of waning immunity of both diseases. Considering different epidemiological traits, an epidemiological model with 11 compartments is developed and the co-dynamics is analysed. A detailed stability and bifurcation analysis is performed for the TB only sub-model, COVID-19 only sub-model and the complete TB - COVID-19 model. Impact of key parameters namely, infection rate, waning immunity, and face mask efficacy on disease prevalence is discussed in detail. Sensitivity analysis by means of normalized forward sensitivity index of the basic reproduction number and LHS-PRCC approach is carried to provide a thorough understanding of significance of various parameters in accelerating as well as controlling the disease spread. Optimal control analysis is presented extensively, incorporating controls related to timely and improved TB treatment, and enhanced COVID-19 tests and isolation facilities to curb the spread of these infectious diseases. The simulation results obtained from each of these analyses stress on the importance of different control measures in mitigation of the diseases and are illustrated accordingly. The study suggests that in the times of a pandemic, other disease treatment and care must not be neglected, and adequate care must be taken so that mortality due to co-infection and unavailability of timely treatment can be avoided. |
format | Online Article Text |
id | pubmed-9013278 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90132782022-04-18 A co-infection model on TB - COVID-19 with optimal control and sensitivity analysis Bandekar, Shraddha Ramdas Ghosh, Mini Math Comput Simul Original Articles COVID-19 had been declared a public health emergency by the World Health Organization in the early 2020. Since then, this deadly virus has claimed millions of lives worldwide. Amidst its chaotic spread, several other diseases have faced negligence in terms of treatment and care, of which one such chronic disease is Tuberculosis. Due to huge rise in COVID-19 cases, there had been a drastic decrease in notification of TB cases which resulted in reversal of global TB target progress. Apart from these due to the earlier co-infections of TB with SARS and MERS-CoV viruses, the TB-COVID-19 co-infection posed a severe threat in the spread of the disease. All these factors backed to be major motivation factor in development of this model. Leading with this concern, a TB - COVID-19 co-infection model is developed in this study, considering possibility of waning immunity of both diseases. Considering different epidemiological traits, an epidemiological model with 11 compartments is developed and the co-dynamics is analysed. A detailed stability and bifurcation analysis is performed for the TB only sub-model, COVID-19 only sub-model and the complete TB - COVID-19 model. Impact of key parameters namely, infection rate, waning immunity, and face mask efficacy on disease prevalence is discussed in detail. Sensitivity analysis by means of normalized forward sensitivity index of the basic reproduction number and LHS-PRCC approach is carried to provide a thorough understanding of significance of various parameters in accelerating as well as controlling the disease spread. Optimal control analysis is presented extensively, incorporating controls related to timely and improved TB treatment, and enhanced COVID-19 tests and isolation facilities to curb the spread of these infectious diseases. The simulation results obtained from each of these analyses stress on the importance of different control measures in mitigation of the diseases and are illustrated accordingly. The study suggests that in the times of a pandemic, other disease treatment and care must not be neglected, and adequate care must be taken so that mortality due to co-infection and unavailability of timely treatment can be avoided. International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. 2022-10 2022-04-16 /pmc/articles/PMC9013278/ /pubmed/35462786 http://dx.doi.org/10.1016/j.matcom.2022.04.001 Text en © 2022 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Original Articles Bandekar, Shraddha Ramdas Ghosh, Mini A co-infection model on TB - COVID-19 with optimal control and sensitivity analysis |
title | A co-infection model on TB - COVID-19 with optimal control and sensitivity analysis |
title_full | A co-infection model on TB - COVID-19 with optimal control and sensitivity analysis |
title_fullStr | A co-infection model on TB - COVID-19 with optimal control and sensitivity analysis |
title_full_unstemmed | A co-infection model on TB - COVID-19 with optimal control and sensitivity analysis |
title_short | A co-infection model on TB - COVID-19 with optimal control and sensitivity analysis |
title_sort | co-infection model on tb - covid-19 with optimal control and sensitivity analysis |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013278/ https://www.ncbi.nlm.nih.gov/pubmed/35462786 http://dx.doi.org/10.1016/j.matcom.2022.04.001 |
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