Vickers David M, Osgood Nathaniel D
Interdisciplinary Studies, College of Graduate Studies and Research, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
Theor Biol Med Model. 2007 Dec 20;4:49. doi: 10.1186/1742-4682-4-49.
The desire to better understand the immuno-biology of infectious diseases as a broader ecological system has motivated the explicit representation of epidemiological processes as a function of immune system dynamics. While several recent and innovative contributions have explored unified models across cellular and organismal domains, and appear well-suited to describing particular aspects of intracellular pathogen infections, these existing immuno-epidemiological models lack representation of certain cellular components and immunological processes needed to adequately characterize the dynamics of some important epidemiological contexts. Here, we complement existing models by presenting an alternate framework of anti-viral immune responses within individual hosts and infection spread across a simple network-based population.
Our compartmental formulation parsimoniously demonstrates a correlation between immune responsiveness, network connectivity, and the natural history of infection in a population. It suggests that an increased disparity between people's ability to respond to an infection, while maintaining an average immune responsiveness rate, may worsen the overall impact of an outbreak within a population. Additionally, varying an individual's network connectivity affects the rate with which the population-wide viral load accumulates, but has little impact on the asymptotic limit in which it approaches. Whilst the clearance of a pathogen in a population will lower viral loads in the short-term, the longer the time until re-infection, the more severe an outbreak is likely to be. Given the eventual likelihood of reinfection, the resulting long-run viral burden after elimination of an infection is negligible compared to the situation in which infection is persistent.
Future infectious disease research would benefit by striving to not only continue to understand the properties of an invading microbe, or the body's response to infections, but how these properties, jointly, affect the propagation of an infection throughout a population. These initial results offer a refinement to current immuno-epidemiological modelling methodology, and reinforce how coupling principles of immunology with epidemiology can provide insight into a multi-scaled description of an ecological system. Overall, we anticipate these results to as a further step towards articulating an integrated, more refined epidemiological theory of the reciprocal influences between host-pathogen interactions, epidemiological mixing, and disease spread.
将传染病的免疫生物学作为一个更广泛的生态系统来更好地理解的愿望，促使人们将流行病学过程明确表示为免疫系统动态的函数。虽然最近有几项创新性的研究探索了跨细胞和机体领域的统一模型，并且似乎非常适合描述细胞内病原体感染的特定方面，但这些现有的免疫流行病学模型缺乏对某些细胞成分和免疫过程的描述，而这些成分和过程是充分表征某些重要流行病学背景下动态变化所必需的。在此，我们通过提出一个个体宿主内抗病毒免疫反应以及感染在一个基于简单网络的群体中传播的替代框架，对现有模型进行补充。
我们的房室模型简洁地展示了免疫反应性、网络连通性与群体感染自然史之间的相关性。这表明，在保持平均免疫反应率的同时，人们对感染的反应能力差异增大，可能会加剧疫情在群体中的总体影响。此外，改变个体的网络连通性会影响群体范围内病毒载量的积累速度，但对其趋近的渐近极限影响不大。虽然群体中病原体的清除会在短期内降低病毒载量，但再次感染前的时间越长，疫情可能就越严重。考虑到最终再次感染的可能性，与感染持续存在的情况相比，感染消除后产生的长期病毒负担可以忽略不计。
未来的传染病研究不仅应继续努力了解入侵微生物的特性或机体对感染的反应，还应了解这些特性如何共同影响感染在群体中的传播，这样才能从中受益。这些初步结果对当前的免疫流行病学建模方法进行了完善，并强化了将免疫学原理与流行病学相结合如何能够为生态系统的多尺度描述提供见解。总体而言，我们预计这些结果将朝着阐明一个综合的、更精细的流行病学理论迈出进一步的步伐，该理论涉及宿主 - 病原体相互作用、流行病学混合和疾病传播之间的相互影响。
