2.50
Hdl Handle:
http://hdl.handle.net/10033/618444
Title:
Modeling Influenza Virus Infection: A Roadmap for Influenza Research.
Authors:
Boianelli, Alessandro; Nguyen, Van Kinh; Ebensen, Thomas ( 0000-0001-8906-063X ) ; Schulze, Kai ( 0000-0003-2286-3416 ) ; Wilk, Esther ( 0000-0003-3446-5511 ) ; Sharma, Niharika; Stegemann-Koniszewski, Sabine; Bruder, Dunja ( 0000-0003-3066-189X ) ; Toapanta, Franklin R; Guzmán, Carlos A; Meyer-Hermann, Michael ( 0000-0002-4300-2474 ) ; Hernandez-Vargas, Esteban A ( 0000-0002-3645-435X )
Abstract:
Influenza A virus (IAV) infection represents a global threat causing seasonal outbreaks and pandemics. Additionally, secondary bacterial infections, caused mainly by Streptococcus pneumoniae, are one of the main complications and responsible for the enhanced morbidity and mortality associated with IAV infections. In spite of the significant advances in our knowledge of IAV infections, holistic comprehension of the interplay between IAV and the host immune response (IR) remains largely fragmented. During the last decade, mathematical modeling has been instrumental to explain and quantify IAV dynamics. In this paper, we review not only the state of the art of mathematical models of IAV infection but also the methodologies exploited for parameter estimation. We focus on the adaptive IR control of IAV infection and the possible mechanisms that could promote a secondary bacterial coinfection. To exemplify IAV dynamics and identifiability issues, a mathematical model to explain the interactions between adaptive IR and IAV infection is considered. Furthermore, in this paper we propose a roadmap for future influenza research. The development of a mathematical modeling framework with a secondary bacterial coinfection, immunosenescence, host genetic factors and responsiveness to vaccination will be pivotal to advance IAV infection understanding and treatment optimization.
Affiliation:
BRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.
Citation:
Modeling Influenza Virus Infection: A Roadmap for Influenza Research. 2015, 7 (10):5274-304 Viruses
Journal:
Viruses
Issue Date:
Oct-2015
URI:
http://hdl.handle.net/10033/618444
DOI:
10.3390/v7102875
PubMed ID:
26473911
Type:
Article
Language:
en
ISSN:
1999-4915
Appears in Collections:
publications of the research group systems medicine of infections([BRICS]SMID)

Full metadata record

DC FieldValue Language
dc.contributor.authorBoianelli, Alessandroen
dc.contributor.authorNguyen, Van Kinhen
dc.contributor.authorEbensen, Thomasen
dc.contributor.authorSchulze, Kaien
dc.contributor.authorWilk, Estheren
dc.contributor.authorSharma, Niharikaen
dc.contributor.authorStegemann-Koniszewski, Sabineen
dc.contributor.authorBruder, Dunjaen
dc.contributor.authorToapanta, Franklin Ren
dc.contributor.authorGuzmán, Carlos Aen
dc.contributor.authorMeyer-Hermann, Michaelen
dc.contributor.authorHernandez-Vargas, Esteban Aen
dc.date.accessioned2016-08-16T13:41:00Z-
dc.date.available2016-08-16T13:41:00Z-
dc.date.issued2015-10-
dc.identifier.citationModeling Influenza Virus Infection: A Roadmap for Influenza Research. 2015, 7 (10):5274-304 Virusesen
dc.identifier.issn1999-4915-
dc.identifier.pmid26473911-
dc.identifier.doi10.3390/v7102875-
dc.identifier.urihttp://hdl.handle.net/10033/618444-
dc.description.abstractInfluenza A virus (IAV) infection represents a global threat causing seasonal outbreaks and pandemics. Additionally, secondary bacterial infections, caused mainly by Streptococcus pneumoniae, are one of the main complications and responsible for the enhanced morbidity and mortality associated with IAV infections. In spite of the significant advances in our knowledge of IAV infections, holistic comprehension of the interplay between IAV and the host immune response (IR) remains largely fragmented. During the last decade, mathematical modeling has been instrumental to explain and quantify IAV dynamics. In this paper, we review not only the state of the art of mathematical models of IAV infection but also the methodologies exploited for parameter estimation. We focus on the adaptive IR control of IAV infection and the possible mechanisms that could promote a secondary bacterial coinfection. To exemplify IAV dynamics and identifiability issues, a mathematical model to explain the interactions between adaptive IR and IAV infection is considered. Furthermore, in this paper we propose a roadmap for future influenza research. The development of a mathematical modeling framework with a secondary bacterial coinfection, immunosenescence, host genetic factors and responsiveness to vaccination will be pivotal to advance IAV infection understanding and treatment optimization.en
dc.language.isoenen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subject.meshAdaptive Immunityen
dc.subject.meshAnimalsen
dc.subject.meshCoinfectionen
dc.subject.meshDisease Models, Animalen
dc.subject.meshHost-Pathogen Interactionsen
dc.subject.meshHumansen
dc.subject.meshInfluenza, Humanen
dc.subject.meshModels, Theoreticalen
dc.subject.meshOrthomyxoviridaeen
dc.subject.meshPneumonia, Pneumococcalen
dc.titleModeling Influenza Virus Infection: A Roadmap for Influenza Research.en
dc.typeArticleen
dc.contributor.departmentBRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56, 38106 Braunschweig, Germany.en
dc.identifier.journalVirusesen

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