Modeling Influenza Virus Infection: A Roadmap for Influenza Research

Viruses

Alessandro Boianelli²  Van Kinh Nguyen²  Thomas Ebensen¹  Kai Schulze¹  Esther Wilk³  Niharika Sharma⁴  Sabine Stegemann-Koniszewski⁴  Dunja Bruder⁴  Franklin R. Toapanta⁵  Carlos A. Guzmán¹  Michael Meyer-Hermann⁶  Esteban A. Hernandez-Vargas² 

[1] Department of Vaccinology and Applied Microbiology, Helmholtz Centre for Infection Research, Braunschweig 38124, Germany;Systems Medicine of Infectious Diseases, Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Braunschweig 38124, Germany;Department of Infection Genetics, Helmholtz Centre for Infection Research, Braunschweig 38124, Germany;Immune Regulation, Helmholtz Centre for Infection Research, Braunschweig 38124, Germany;Center for Vaccine Development, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA;Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Braunschweig 38124, Germany;

关键词: mathematical models;    parameters estimation;    influenza;    coinfection;    aging;    vaccinology;    host genetic factors;   

DOI  :  10.3390/v7102875

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.