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Similarities between pandemics and cancer in growth and risk models
Cancer and pandemics are leading causes of death globally, with severe socioeconomic repercussions. To better understand these repercussions, we investigate similarities between pandemics and cancer and describe the limited growth in number of infections or cancer cells, using mathematical models. F...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801496/ https://www.ncbi.nlm.nih.gov/pubmed/33431944 http://dx.doi.org/10.1038/s41598-020-79458-w |
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author | Vandamme, Lode K. J. de Hingh, Ignace H. J. T. Fonseca, Jorge Rocha, Paulo R. F. |
author_facet | Vandamme, Lode K. J. de Hingh, Ignace H. J. T. Fonseca, Jorge Rocha, Paulo R. F. |
author_sort | Vandamme, Lode K. J. |
collection | PubMed |
description | Cancer and pandemics are leading causes of death globally, with severe socioeconomic repercussions. To better understand these repercussions, we investigate similarities between pandemics and cancer and describe the limited growth in number of infections or cancer cells, using mathematical models. For a pandemic, the analysis shows that in most cases, the initial fast growth is followed by a slower decay in the recovery phase. The risk of infection increases due to the airborne virus contact crossing a risk-threshold. For cancers caused by carcinogens, the increasing risk with age and absorbed dose of toxins that cross a risk-threshold, may lead to the disease onset. The time scales are different for both causes of death: years for cancer development and days to weeks for contact with airborne viruses. Contamination by viruses is on a time scale of seconds or minutes. The risk-threshold to get ill and the number-threshold in cancer cells or viruses, may explain the large variability in the outcome. The number of infected persons per day is better represented in log–lin plots instead of the conventional lin–lin plots. Differences in therapies are discussed. Our mathematical investigation between cancer and pandemics reveals a multifactorial correlation between both fragilities and brings us one step closer to understand, timely predict and ultimately diminish the socioeconomic hurdle of both cancer and pandemics. |
format | Online Article Text |
id | pubmed-7801496 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78014962021-01-12 Similarities between pandemics and cancer in growth and risk models Vandamme, Lode K. J. de Hingh, Ignace H. J. T. Fonseca, Jorge Rocha, Paulo R. F. Sci Rep Article Cancer and pandemics are leading causes of death globally, with severe socioeconomic repercussions. To better understand these repercussions, we investigate similarities between pandemics and cancer and describe the limited growth in number of infections or cancer cells, using mathematical models. For a pandemic, the analysis shows that in most cases, the initial fast growth is followed by a slower decay in the recovery phase. The risk of infection increases due to the airborne virus contact crossing a risk-threshold. For cancers caused by carcinogens, the increasing risk with age and absorbed dose of toxins that cross a risk-threshold, may lead to the disease onset. The time scales are different for both causes of death: years for cancer development and days to weeks for contact with airborne viruses. Contamination by viruses is on a time scale of seconds or minutes. The risk-threshold to get ill and the number-threshold in cancer cells or viruses, may explain the large variability in the outcome. The number of infected persons per day is better represented in log–lin plots instead of the conventional lin–lin plots. Differences in therapies are discussed. Our mathematical investigation between cancer and pandemics reveals a multifactorial correlation between both fragilities and brings us one step closer to understand, timely predict and ultimately diminish the socioeconomic hurdle of both cancer and pandemics. Nature Publishing Group UK 2021-01-11 /pmc/articles/PMC7801496/ /pubmed/33431944 http://dx.doi.org/10.1038/s41598-020-79458-w Text en © Crown 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Vandamme, Lode K. J. de Hingh, Ignace H. J. T. Fonseca, Jorge Rocha, Paulo R. F. Similarities between pandemics and cancer in growth and risk models |
title | Similarities between pandemics and cancer in growth and risk models |
title_full | Similarities between pandemics and cancer in growth and risk models |
title_fullStr | Similarities between pandemics and cancer in growth and risk models |
title_full_unstemmed | Similarities between pandemics and cancer in growth and risk models |
title_short | Similarities between pandemics and cancer in growth and risk models |
title_sort | similarities between pandemics and cancer in growth and risk models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7801496/ https://www.ncbi.nlm.nih.gov/pubmed/33431944 http://dx.doi.org/10.1038/s41598-020-79458-w |
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