2.50
Hdl Handle:
http://hdl.handle.net/10033/580115
Title:
Ebola virus infection modeling and identifiability problems.
Authors:
Nguyen, Van Kinh; Binder, Sebastian C ( 0000-0003-1169-1786 ) ; Boianelli, Alessandro; Meyer-Hermann, Michael ( 0000-0002-4300-2474 ) ; Hernandez-Vargas, Esteban A ( 0000-0002-3645-435X )
Abstract:
The recent outbreaks of Ebola virus (EBOV) infections have underlined the impact of the virus as a major threat for human health. Due to the high biosafety classification of EBOV (level 4), basic research is very limited. Therefore, the development of new avenues of thinking to advance quantitative comprehension of the virus and its interaction with the host cells is urgently needed to tackle this lethal disease. Mathematical modeling of the EBOV dynamics can be instrumental to interpret Ebola infection kinetics on quantitative grounds. To the best of our knowledge, a mathematical modeling approach to unravel the interaction between EBOV and the host cells is still missing. In this paper, a mathematical model based on differential equations is used to represent the basic interactions between EBOV and wild-type Vero cells in vitro. Parameter sets that represent infectivity of pathogens are estimated for EBOV infection and compared with influenza virus infection kinetics. The average infecting time of wild-type Vero cells by EBOV is slower than in influenza infection. Simulation results suggest that the slow infecting time of EBOV could be compensated by its efficient replication. This study reveals several identifiability problems and what kind of experiments are necessary to advance the quantification of EBOV infection. A first mathematical approach of EBOV dynamics and the estimation of standard parameters in viral infections kinetics is the key contribution of this work, paving the way for future modeling works on EBOV infection.
Affiliation:
Helmholtz Center for Infection Research
Citation:
Ebola virus infection modeling and identifiability problems. 2015, 6:257 Front Microbiol
Journal:
Frontiers in microbiology
Issue Date:
2015
URI:
http://hdl.handle.net/10033/580115
DOI:
10.3389/fmicb.2015.00257
PubMed ID:
25914675
Type:
Article
Language:
en
ISSN:
1664-302X
Appears in Collections:
publications of the research group system immunology ([BRICS]SIMM)

Full metadata record

DC FieldValue Language
dc.contributor.authorNguyen, Van Kinhen
dc.contributor.authorBinder, Sebastian Cen
dc.contributor.authorBoianelli, Alessandroen
dc.contributor.authorMeyer-Hermann, Michaelen
dc.contributor.authorHernandez-Vargas, Esteban Aen
dc.date.accessioned2015-10-22T11:44:55Zen
dc.date.available2015-10-22T11:44:55Zen
dc.date.issued2015en
dc.identifier.citationEbola virus infection modeling and identifiability problems. 2015, 6:257 Front Microbiolen
dc.identifier.issn1664-302Xen
dc.identifier.pmid25914675en
dc.identifier.doi10.3389/fmicb.2015.00257en
dc.identifier.urihttp://hdl.handle.net/10033/580115en
dc.description.abstractThe recent outbreaks of Ebola virus (EBOV) infections have underlined the impact of the virus as a major threat for human health. Due to the high biosafety classification of EBOV (level 4), basic research is very limited. Therefore, the development of new avenues of thinking to advance quantitative comprehension of the virus and its interaction with the host cells is urgently needed to tackle this lethal disease. Mathematical modeling of the EBOV dynamics can be instrumental to interpret Ebola infection kinetics on quantitative grounds. To the best of our knowledge, a mathematical modeling approach to unravel the interaction between EBOV and the host cells is still missing. In this paper, a mathematical model based on differential equations is used to represent the basic interactions between EBOV and wild-type Vero cells in vitro. Parameter sets that represent infectivity of pathogens are estimated for EBOV infection and compared with influenza virus infection kinetics. The average infecting time of wild-type Vero cells by EBOV is slower than in influenza infection. Simulation results suggest that the slow infecting time of EBOV could be compensated by its efficient replication. This study reveals several identifiability problems and what kind of experiments are necessary to advance the quantification of EBOV infection. A first mathematical approach of EBOV dynamics and the estimation of standard parameters in viral infections kinetics is the key contribution of this work, paving the way for future modeling works on EBOV infection.en
dc.language.isoenen
dc.titleEbola virus infection modeling and identifiability problems.en
dc.typeArticleen
dc.contributor.departmentHelmholtz Center for Infection Researchen
dc.identifier.journalFrontiers in microbiologyen

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