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Mathematical modeling of postcoinfection with influenza A virus and Streptococcus pneumoniae, with implications for pneumonia and COPD-risk assessment

BACKGROUND: The interaction between influenza and pneumococcus is important for understanding how coinfection may exacerbate pneumonia. Secondary pneumococcal pneumonia associated with influenza infection is more likely to increase respiratory morbidity and mortality. This study aimed to assess exac...

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Autores principales: Cheng, Yi-Hsien, You, Shu-Han, Lin, Yi-Jun, Chen, Szu-Chieh, Chen, Wei-Yu, Chou, Wei-Chun, Hsieh, Nan-Hung, Liao, Chung-Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5505164/
https://www.ncbi.nlm.nih.gov/pubmed/28740377
http://dx.doi.org/10.2147/COPD.S138295
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author Cheng, Yi-Hsien
You, Shu-Han
Lin, Yi-Jun
Chen, Szu-Chieh
Chen, Wei-Yu
Chou, Wei-Chun
Hsieh, Nan-Hung
Liao, Chung-Min
author_facet Cheng, Yi-Hsien
You, Shu-Han
Lin, Yi-Jun
Chen, Szu-Chieh
Chen, Wei-Yu
Chou, Wei-Chun
Hsieh, Nan-Hung
Liao, Chung-Min
author_sort Cheng, Yi-Hsien
collection PubMed
description BACKGROUND: The interaction between influenza and pneumococcus is important for understanding how coinfection may exacerbate pneumonia. Secondary pneumococcal pneumonia associated with influenza infection is more likely to increase respiratory morbidity and mortality. This study aimed to assess exacerbated inflammatory effects posed by secondary pneumococcal pneumonia, given prior influenza infection. MATERIALS AND METHODS: A well-derived mathematical within-host dynamic model of coinfection with influenza A virus and Streptococcus pneumoniae (SP) integrated with dose–response relationships composed of previously published mouse experimental data and clinical studies was implemented to study potentially exacerbated inflammatory responses in pneumonia based on a probabilistic approach. RESULTS: We found that TNFα is likely to be the most sensitive biomarker reflecting inflammatory response during coinfection among three explored cytokines. We showed that the worst inflammatory effects would occur at day 7 SP coinfection, with risk probability of 50% (likely) to develop severe inflammatory responses. Our model also showed that the day of secondary SP infection had much more impact on the severity of inflammatory responses in pneumonia compared to the effects caused by initial virus titers and bacteria loads. CONCLUSION: People and health care workers should be wary of secondary SP infection on day 7 post-influenza infection for prompt and proper control-measure implementation. Our quantitative risk-assessment framework can provide new insights into improvements in respiratory health especially, predominantly due to chronic obstructive pulmonary disease (COPD).
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spelling pubmed-55051642017-07-24 Mathematical modeling of postcoinfection with influenza A virus and Streptococcus pneumoniae, with implications for pneumonia and COPD-risk assessment Cheng, Yi-Hsien You, Shu-Han Lin, Yi-Jun Chen, Szu-Chieh Chen, Wei-Yu Chou, Wei-Chun Hsieh, Nan-Hung Liao, Chung-Min Int J Chron Obstruct Pulmon Dis Original Research BACKGROUND: The interaction between influenza and pneumococcus is important for understanding how coinfection may exacerbate pneumonia. Secondary pneumococcal pneumonia associated with influenza infection is more likely to increase respiratory morbidity and mortality. This study aimed to assess exacerbated inflammatory effects posed by secondary pneumococcal pneumonia, given prior influenza infection. MATERIALS AND METHODS: A well-derived mathematical within-host dynamic model of coinfection with influenza A virus and Streptococcus pneumoniae (SP) integrated with dose–response relationships composed of previously published mouse experimental data and clinical studies was implemented to study potentially exacerbated inflammatory responses in pneumonia based on a probabilistic approach. RESULTS: We found that TNFα is likely to be the most sensitive biomarker reflecting inflammatory response during coinfection among three explored cytokines. We showed that the worst inflammatory effects would occur at day 7 SP coinfection, with risk probability of 50% (likely) to develop severe inflammatory responses. Our model also showed that the day of secondary SP infection had much more impact on the severity of inflammatory responses in pneumonia compared to the effects caused by initial virus titers and bacteria loads. CONCLUSION: People and health care workers should be wary of secondary SP infection on day 7 post-influenza infection for prompt and proper control-measure implementation. Our quantitative risk-assessment framework can provide new insights into improvements in respiratory health especially, predominantly due to chronic obstructive pulmonary disease (COPD). Dove Medical Press 2017-07-05 /pmc/articles/PMC5505164/ /pubmed/28740377 http://dx.doi.org/10.2147/COPD.S138295 Text en © 2017 Cheng et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Cheng, Yi-Hsien
You, Shu-Han
Lin, Yi-Jun
Chen, Szu-Chieh
Chen, Wei-Yu
Chou, Wei-Chun
Hsieh, Nan-Hung
Liao, Chung-Min
Mathematical modeling of postcoinfection with influenza A virus and Streptococcus pneumoniae, with implications for pneumonia and COPD-risk assessment
title Mathematical modeling of postcoinfection with influenza A virus and Streptococcus pneumoniae, with implications for pneumonia and COPD-risk assessment
title_full Mathematical modeling of postcoinfection with influenza A virus and Streptococcus pneumoniae, with implications for pneumonia and COPD-risk assessment
title_fullStr Mathematical modeling of postcoinfection with influenza A virus and Streptococcus pneumoniae, with implications for pneumonia and COPD-risk assessment
title_full_unstemmed Mathematical modeling of postcoinfection with influenza A virus and Streptococcus pneumoniae, with implications for pneumonia and COPD-risk assessment
title_short Mathematical modeling of postcoinfection with influenza A virus and Streptococcus pneumoniae, with implications for pneumonia and COPD-risk assessment
title_sort mathematical modeling of postcoinfection with influenza a virus and streptococcus pneumoniae, with implications for pneumonia and copd-risk assessment
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5505164/
https://www.ncbi.nlm.nih.gov/pubmed/28740377
http://dx.doi.org/10.2147/COPD.S138295
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