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ModInterv COVID-19: An online platform to monitor the evolution of epidemic curves
We present the software ModInterv as an informatics tool to monitor, in an automated and user-friendly manner, the evolution and trend of COVID-19 epidemic curves, both for cases and deaths. The ModInterv software uses parametric generalized growth models, together with LOWESS regression analysis, t...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969754/ https://www.ncbi.nlm.nih.gov/pubmed/36874079 http://dx.doi.org/10.1016/j.asoc.2023.110159 |
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author | Brum, Arthur A. Vasconcelos, Giovani L. Duarte-Filho, Gerson C. Ospina, Raydonal Almeida, Francisco A.G. Macêdo, Antônio M.S. |
author_facet | Brum, Arthur A. Vasconcelos, Giovani L. Duarte-Filho, Gerson C. Ospina, Raydonal Almeida, Francisco A.G. Macêdo, Antônio M.S. |
author_sort | Brum, Arthur A. |
collection | PubMed |
description | We present the software ModInterv as an informatics tool to monitor, in an automated and user-friendly manner, the evolution and trend of COVID-19 epidemic curves, both for cases and deaths. The ModInterv software uses parametric generalized growth models, together with LOWESS regression analysis, to fit epidemic curves with multiple waves of infections for countries around the world as well as for states and cities in Brazil and the USA. The software automatically accesses publicly available COVID-19 databases maintained by the Johns Hopkins University (for countries as well as states and cities in the USA) and the Federal University of Viçosa (for states and cities in Brazil). The richness of the implemented models lies in the possibility of quantitatively and reliably detecting the distinct acceleration regimes of the disease. We describe the backend structure of software as well as its practical use. The software helps the user not only to understand the current stage of the epidemic in a chosen location but also to make short term predictions as to how the curves may evolve. The app is freely available on the internet (http://fisica.ufpr.br/modinterv), thus making a sophisticated mathematical analysis of epidemic data readily accessible to any interested user. |
format | Online Article Text |
id | pubmed-9969754 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99697542023-02-27 ModInterv COVID-19: An online platform to monitor the evolution of epidemic curves Brum, Arthur A. Vasconcelos, Giovani L. Duarte-Filho, Gerson C. Ospina, Raydonal Almeida, Francisco A.G. Macêdo, Antônio M.S. Appl Soft Comput Article We present the software ModInterv as an informatics tool to monitor, in an automated and user-friendly manner, the evolution and trend of COVID-19 epidemic curves, both for cases and deaths. The ModInterv software uses parametric generalized growth models, together with LOWESS regression analysis, to fit epidemic curves with multiple waves of infections for countries around the world as well as for states and cities in Brazil and the USA. The software automatically accesses publicly available COVID-19 databases maintained by the Johns Hopkins University (for countries as well as states and cities in the USA) and the Federal University of Viçosa (for states and cities in Brazil). The richness of the implemented models lies in the possibility of quantitatively and reliably detecting the distinct acceleration regimes of the disease. We describe the backend structure of software as well as its practical use. The software helps the user not only to understand the current stage of the epidemic in a chosen location but also to make short term predictions as to how the curves may evolve. The app is freely available on the internet (http://fisica.ufpr.br/modinterv), thus making a sophisticated mathematical analysis of epidemic data readily accessible to any interested user. Elsevier B.V. 2023-04 2023-02-27 /pmc/articles/PMC9969754/ /pubmed/36874079 http://dx.doi.org/10.1016/j.asoc.2023.110159 Text en © 2023 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 Brum, Arthur A. Vasconcelos, Giovani L. Duarte-Filho, Gerson C. Ospina, Raydonal Almeida, Francisco A.G. Macêdo, Antônio M.S. ModInterv COVID-19: An online platform to monitor the evolution of epidemic curves |
title | ModInterv COVID-19: An online platform to monitor the evolution of epidemic curves |
title_full | ModInterv COVID-19: An online platform to monitor the evolution of epidemic curves |
title_fullStr | ModInterv COVID-19: An online platform to monitor the evolution of epidemic curves |
title_full_unstemmed | ModInterv COVID-19: An online platform to monitor the evolution of epidemic curves |
title_short | ModInterv COVID-19: An online platform to monitor the evolution of epidemic curves |
title_sort | modinterv covid-19: an online platform to monitor the evolution of epidemic curves |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969754/ https://www.ncbi.nlm.nih.gov/pubmed/36874079 http://dx.doi.org/10.1016/j.asoc.2023.110159 |
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