Similarities between pandemics and cancer in growth and risk models

Detalhes bibliográficos
Autor(a) principal: Vandamme, Lode K J
Data de Publicação: 2021
Outros Autores: de Hingh, Ignace H J T, Fonseca, Jorge, Rocha, Paulo R. F.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/92633
https://doi.org/10.1038/s41598-020-79458-w
Resumo: 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.
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spelling Similarities between pandemics and cancer in growth and risk modelsCancer 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 Research2021-01-11info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/92633http://hdl.handle.net/10316/92633https://doi.org/10.1038/s41598-020-79458-weng2045-2322https://www.nature.com/articles/s41598-020-79458-wVandamme, Lode K Jde Hingh, Ignace H J TFonseca, JorgeRocha, Paulo R. F.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-05-25T06:02:02Zoai:estudogeral.uc.pt:10316/92633Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:11:41.189641Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Similarities between pandemics and cancer in growth and risk models
title Similarities between pandemics and cancer in growth and risk models
spellingShingle Similarities between pandemics and cancer in growth and risk models
Vandamme, Lode K J
title_short 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_sort Similarities between pandemics and cancer in growth and risk models
author Vandamme, Lode K J
author_facet Vandamme, Lode K J
de Hingh, Ignace H J T
Fonseca, Jorge
Rocha, Paulo R. F.
author_role author
author2 de Hingh, Ignace H J T
Fonseca, Jorge
Rocha, Paulo R. F.
author2_role author
author
author
dc.contributor.author.fl_str_mv Vandamme, Lode K J
de Hingh, Ignace H J T
Fonseca, Jorge
Rocha, Paulo R. F.
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.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-11
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/92633
http://hdl.handle.net/10316/92633
https://doi.org/10.1038/s41598-020-79458-w
url http://hdl.handle.net/10316/92633
https://doi.org/10.1038/s41598-020-79458-w
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2045-2322
https://www.nature.com/articles/s41598-020-79458-w
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dc.publisher.none.fl_str_mv Nature Research
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