Modeling Influenza Virus Infection: A Roadmap for Influenza Research.
Modeling Influenza Virus Infection: A Roadmap for Influenza Research.
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DOI：
10.3390/v7102875
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发表时间：
2015-10-12
期刊：
影响因子：
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通讯作者：
Hernandez-Vargas EA
中科院分区：
文献类型：
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作者：
Boianelli A;Nguyen VK;Ebensen T;Schulze K;Wilk E;Sharma N;Stegemann-Koniszewski S;Bruder D;Toapanta FR;Guzmán CA;Meyer-Hermann M;Hernandez-Vargas EA
甲型流感病毒 (IAV) 感染是导致季节性爆发和流行病的全球威胁。此外，主要由肺炎链球菌引起的继发细菌感染是主要并发症之一，也是 IAV 感染相关发病率和死亡率增加的原因。尽管我们对 IAV 感染的了解取得了重大进展，但对 IAV 与宿主免疫反应 (IR) 之间相互作用的整体理解仍然很分散。在过去的十年中，数学模型在解释和量化 IAV 动态方面发挥了重要作用。在本文中，我们不仅回顾了 IAV 感染数学模型的最新技术，还回顾了用于参数估计的方法。我们重点关注 IAV 感染的适应性 IR 控制以及促进继发细菌合并感染的可能机制。为了举例说明 IAV 动力学和可识别性问题，考虑了解释适应性 IR 和 IAV 感染之间相互作用的数学模型。此外，在本文中，我们提出了未来流感研究的路线图。开发具有继发性细菌共感染、免疫衰老、宿主遗传因素和疫苗接种反应的数学模型框架对于推进 IAV 感染理解和治疗优化至关重要。
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.