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Generalized trapezoidal ogive curves for fatality rate modeling
The construction of a continuous family of distributions on a compact set is demonstrated by concatenating, in a continuous manner, three probability density functions with bounded support using a modified mixture technique. The construction technique is similar to that of generalized trapezoidal (G...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Ltd.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7402242/ http://dx.doi.org/10.1016/j.csfx.2020.100043 |
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author | Dorp, Johan René van Shittu, Ekundayo Mazzuchi, Thomas A. |
author_facet | Dorp, Johan René van Shittu, Ekundayo Mazzuchi, Thomas A. |
author_sort | Dorp, Johan René van |
collection | PubMed |
description | The construction of a continuous family of distributions on a compact set is demonstrated by concatenating, in a continuous manner, three probability density functions with bounded support using a modified mixture technique. The construction technique is similar to that of generalized trapezoidal (GT) distributions, but contrary to GT distributions, the resulting density function is smooth within its bounded domain. The construction of Generalized Trapezoidal Ogive (GTO) distributions was motivated by the COVID-19 epidemic, where smoothness of an infection rate curve may be a desirable property combined with the ability to separately model three stages and their durations as the epidemic progresses, being: (1) an increasing infection rate stage, (2) an infection rate stage of some stability and (3) a decreasing infection rate stage. The resulting model allows for asymmetry of the infection rate curve opposite to, for example, the Gaussian Error Infection (GEI) rate curve utilized early on for COVID-19 epidemic projections by the Institute for Health Metrics and Evaluation (IHME). While other asymmetric distributions too allow for the modeling of asymmetry, the ability to separately model the above three stages of an epidemic’s progression is a distinct feature of the model proposed. The latter avoids unrealistic projections of an epidemic’s right-tail in the absence of right tail data, which is an artifact of any fatality rate model where a left-tail fit determines its right-tail behavior. |
format | Online Article Text |
id | pubmed-7402242 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Authors. Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74022422020-08-05 Generalized trapezoidal ogive curves for fatality rate modeling Dorp, Johan René van Shittu, Ekundayo Mazzuchi, Thomas A. Chaos, Solitons & Fractals: X Article The construction of a continuous family of distributions on a compact set is demonstrated by concatenating, in a continuous manner, three probability density functions with bounded support using a modified mixture technique. The construction technique is similar to that of generalized trapezoidal (GT) distributions, but contrary to GT distributions, the resulting density function is smooth within its bounded domain. The construction of Generalized Trapezoidal Ogive (GTO) distributions was motivated by the COVID-19 epidemic, where smoothness of an infection rate curve may be a desirable property combined with the ability to separately model three stages and their durations as the epidemic progresses, being: (1) an increasing infection rate stage, (2) an infection rate stage of some stability and (3) a decreasing infection rate stage. The resulting model allows for asymmetry of the infection rate curve opposite to, for example, the Gaussian Error Infection (GEI) rate curve utilized early on for COVID-19 epidemic projections by the Institute for Health Metrics and Evaluation (IHME). While other asymmetric distributions too allow for the modeling of asymmetry, the ability to separately model the above three stages of an epidemic’s progression is a distinct feature of the model proposed. The latter avoids unrealistic projections of an epidemic’s right-tail in the absence of right tail data, which is an artifact of any fatality rate model where a left-tail fit determines its right-tail behavior. The Authors. Published by Elsevier Ltd. 2020-03 2020-08-04 /pmc/articles/PMC7402242/ http://dx.doi.org/10.1016/j.csfx.2020.100043 Text en © 2020 The Authors. Published by Elsevier Ltd. 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 Dorp, Johan René van Shittu, Ekundayo Mazzuchi, Thomas A. Generalized trapezoidal ogive curves for fatality rate modeling |
title | Generalized trapezoidal ogive curves for fatality rate modeling |
title_full | Generalized trapezoidal ogive curves for fatality rate modeling |
title_fullStr | Generalized trapezoidal ogive curves for fatality rate modeling |
title_full_unstemmed | Generalized trapezoidal ogive curves for fatality rate modeling |
title_short | Generalized trapezoidal ogive curves for fatality rate modeling |
title_sort | generalized trapezoidal ogive curves for fatality rate modeling |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7402242/ http://dx.doi.org/10.1016/j.csfx.2020.100043 |
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