Cargando…

Can infectious modelling be applicable globally – lessons from COVID 19

Contagious diseases are needed to be monitored to prevent spreading within communities. Timely advice and predictions are necessary to overcome the consequences of those epidemics. Currently, emphasis has been placed on computer modelling to achieve the needed forecasts, the best example being the C...

Descripción completa

Detalles Bibliográficos
Autores principales: Magana-Arachchi, Dhammika N., Wanigatunge, Rasika P., Vithanage, Meththika S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9612404/
https://www.ncbi.nlm.nih.gov/pubmed/36320817
http://dx.doi.org/10.1016/j.coesh.2022.100399
_version_ 1784819766759784448
author Magana-Arachchi, Dhammika N.
Wanigatunge, Rasika P.
Vithanage, Meththika S.
author_facet Magana-Arachchi, Dhammika N.
Wanigatunge, Rasika P.
Vithanage, Meththika S.
author_sort Magana-Arachchi, Dhammika N.
collection PubMed
description Contagious diseases are needed to be monitored to prevent spreading within communities. Timely advice and predictions are necessary to overcome the consequences of those epidemics. Currently, emphasis has been placed on computer modelling to achieve the needed forecasts, the best example being the COVID-19 pandemic. Scientists used various models to determine how diverse sociodemographic factors correlated and influenced COVID-19 Global transmission and demonstrated the utility of computer models as tools in disease management. However, as modelling is done with assumptions with set rules, calculating uncertainty quantification is essential in infectious modelling when reporting the results and trustfully describing the limitations. This article summarizes the infectious disease modelling strategies, challenges, and global applicability by focusing on the COVID-19 pandemic.
format Online
Article
Text
id pubmed-9612404
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Elsevier B.V.
record_format MEDLINE/PubMed
spelling pubmed-96124042022-10-28 Can infectious modelling be applicable globally – lessons from COVID 19 Magana-Arachchi, Dhammika N. Wanigatunge, Rasika P. Vithanage, Meththika S. Curr Opin Environ Sci Health Article Contagious diseases are needed to be monitored to prevent spreading within communities. Timely advice and predictions are necessary to overcome the consequences of those epidemics. Currently, emphasis has been placed on computer modelling to achieve the needed forecasts, the best example being the COVID-19 pandemic. Scientists used various models to determine how diverse sociodemographic factors correlated and influenced COVID-19 Global transmission and demonstrated the utility of computer models as tools in disease management. However, as modelling is done with assumptions with set rules, calculating uncertainty quantification is essential in infectious modelling when reporting the results and trustfully describing the limitations. This article summarizes the infectious disease modelling strategies, challenges, and global applicability by focusing on the COVID-19 pandemic. Elsevier B.V. 2022-10-22 /pmc/articles/PMC9612404/ /pubmed/36320817 http://dx.doi.org/10.1016/j.coesh.2022.100399 Text en © 2022 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 Article
Magana-Arachchi, Dhammika N.
Wanigatunge, Rasika P.
Vithanage, Meththika S.
Can infectious modelling be applicable globally – lessons from COVID 19
title Can infectious modelling be applicable globally – lessons from COVID 19
title_full Can infectious modelling be applicable globally – lessons from COVID 19
title_fullStr Can infectious modelling be applicable globally – lessons from COVID 19
title_full_unstemmed Can infectious modelling be applicable globally – lessons from COVID 19
title_short Can infectious modelling be applicable globally – lessons from COVID 19
title_sort can infectious modelling be applicable globally – lessons from covid 19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9612404/
https://www.ncbi.nlm.nih.gov/pubmed/36320817
http://dx.doi.org/10.1016/j.coesh.2022.100399
work_keys_str_mv AT maganaarachchidhammikan caninfectiousmodellingbeapplicablegloballylessonsfromcovid19
AT wanigatungerasikap caninfectiousmodellingbeapplicablegloballylessonsfromcovid19
AT vithanagemeththikas caninfectiousmodellingbeapplicablegloballylessonsfromcovid19