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Modeling the impact of combined use of COVID Alert SA app and vaccination to curb COVID-19 infections in South Africa

The unanticipated continued deep-rooted trend of the Severe Acute Respiratory Syndrome Corona-virus-2 the originator pathogen of the COVID-19 persists posing concurrent anxiety globally. More effort is affixed in the scientific arena via continuous investigations in a prolific effort to understand t...

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Autores principales: Kinyili, Musyoka, Munyakazi, Justin B., Mukhtar, Abdulaziz Y. A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9897588/
https://www.ncbi.nlm.nih.gov/pubmed/36735664
http://dx.doi.org/10.1371/journal.pone.0264863
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author Kinyili, Musyoka
Munyakazi, Justin B.
Mukhtar, Abdulaziz Y. A.
author_facet Kinyili, Musyoka
Munyakazi, Justin B.
Mukhtar, Abdulaziz Y. A.
author_sort Kinyili, Musyoka
collection PubMed
description The unanticipated continued deep-rooted trend of the Severe Acute Respiratory Syndrome Corona-virus-2 the originator pathogen of the COVID-19 persists posing concurrent anxiety globally. More effort is affixed in the scientific arena via continuous investigations in a prolific effort to understand the transmission dynamics and control measures in eradication of the epidemic. Both pharmaceutical and non-pharmaceutical containment measure protocols have been assimilated in this effort. In this study, we develop a modified SEIR deterministic model that factors in alternative-amalgamation of use of COVID Alert SA app and vaccination against the COVID-19 to the Republic of South Africa’s general public in an endeavor to discontinue the chain of spread for the pandemic. We analyze the key properties of the model not limited to positivity, boundedness, and stability. We authenticate the model by fitting it to the Republic of South Africa’s cumulative COVID-19 cases reported data utilizing the Maximum Likelihood Estimation algorithm implemented in fitR package. Sensitivity analysis and simulations for the model reveal that simultaneously-gradually increased implementation of the COVID Alert SA app use and vaccination against COVID-19 to the public substantially accelerate reduction in the plateau number of COVID-19 infections across all the observed vaccine efficacy scenarios. More fundamentally, it is discovered that implementing at least 12% app use (mainly for the susceptible population not vaccinated) with simultaneous vaccination of over 12% of the susceptible population majorly not using the app using a vaccine of at least 50% efficacy would be sufficient in eradicating the pandemic over relatively shorter time span.
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spelling pubmed-98975882023-02-04 Modeling the impact of combined use of COVID Alert SA app and vaccination to curb COVID-19 infections in South Africa Kinyili, Musyoka Munyakazi, Justin B. Mukhtar, Abdulaziz Y. A. PLoS One Research Article The unanticipated continued deep-rooted trend of the Severe Acute Respiratory Syndrome Corona-virus-2 the originator pathogen of the COVID-19 persists posing concurrent anxiety globally. More effort is affixed in the scientific arena via continuous investigations in a prolific effort to understand the transmission dynamics and control measures in eradication of the epidemic. Both pharmaceutical and non-pharmaceutical containment measure protocols have been assimilated in this effort. In this study, we develop a modified SEIR deterministic model that factors in alternative-amalgamation of use of COVID Alert SA app and vaccination against the COVID-19 to the Republic of South Africa’s general public in an endeavor to discontinue the chain of spread for the pandemic. We analyze the key properties of the model not limited to positivity, boundedness, and stability. We authenticate the model by fitting it to the Republic of South Africa’s cumulative COVID-19 cases reported data utilizing the Maximum Likelihood Estimation algorithm implemented in fitR package. Sensitivity analysis and simulations for the model reveal that simultaneously-gradually increased implementation of the COVID Alert SA app use and vaccination against COVID-19 to the public substantially accelerate reduction in the plateau number of COVID-19 infections across all the observed vaccine efficacy scenarios. More fundamentally, it is discovered that implementing at least 12% app use (mainly for the susceptible population not vaccinated) with simultaneous vaccination of over 12% of the susceptible population majorly not using the app using a vaccine of at least 50% efficacy would be sufficient in eradicating the pandemic over relatively shorter time span. Public Library of Science 2023-02-03 /pmc/articles/PMC9897588/ /pubmed/36735664 http://dx.doi.org/10.1371/journal.pone.0264863 Text en © 2023 Kinyili et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Kinyili, Musyoka
Munyakazi, Justin B.
Mukhtar, Abdulaziz Y. A.
Modeling the impact of combined use of COVID Alert SA app and vaccination to curb COVID-19 infections in South Africa
title Modeling the impact of combined use of COVID Alert SA app and vaccination to curb COVID-19 infections in South Africa
title_full Modeling the impact of combined use of COVID Alert SA app and vaccination to curb COVID-19 infections in South Africa
title_fullStr Modeling the impact of combined use of COVID Alert SA app and vaccination to curb COVID-19 infections in South Africa
title_full_unstemmed Modeling the impact of combined use of COVID Alert SA app and vaccination to curb COVID-19 infections in South Africa
title_short Modeling the impact of combined use of COVID Alert SA app and vaccination to curb COVID-19 infections in South Africa
title_sort modeling the impact of combined use of covid alert sa app and vaccination to curb covid-19 infections in south africa
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9897588/
https://www.ncbi.nlm.nih.gov/pubmed/36735664
http://dx.doi.org/10.1371/journal.pone.0264863
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