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裂谷热病毒传播的机制模型:系统评价。

Mechanistic models of Rift Valley fever virus transmission: A systematic review.

机构信息

Oniris, INRAE, BIOEPAR, Nantes, France.

ASTRE, University of Montpellier, CIRAD, INRAE, Montpellier, France.

出版信息

PLoS Negl Trop Dis. 2022 Nov 18;16(11):e0010339. doi: 10.1371/journal.pntd.0010339. eCollection 2022 Nov.

Abstract

Rift Valley fever (RVF) is a zoonotic arbovirosis which has been reported across Africa including the northernmost edge, South West Indian Ocean islands, and the Arabian Peninsula. The virus is responsible for high abortion rates and mortality in young ruminants, with economic impacts in affected countries. To date, RVF epidemiological mechanisms are not fully understood, due to the multiplicity of implicated vertebrate hosts, vectors, and ecosystems. In this context, mathematical models are useful tools to develop our understanding of complex systems, and mechanistic models are particularly suited to data-scarce settings. Here, we performed a systematic review of mechanistic models studying RVF, to explore their diversity and their contribution to the understanding of this disease epidemiology. Researching Pubmed and Scopus databases (October 2021), we eventually selected 48 papers, presenting overall 49 different models with numerical application to RVF. We categorized models as theoretical, applied, or grey, depending on whether they represented a specific geographical context or not, and whether they relied on an extensive use of data. We discussed their contributions to the understanding of RVF epidemiology, and highlighted that theoretical and applied models are used differently yet meet common objectives. Through the examination of model features, we identified research questions left unexplored across scales, such as the role of animal mobility, as well as the relative contributions of host and vector species to transmission. Importantly, we noted a substantial lack of justification when choosing a functional form for the force of infection. Overall, we showed a great diversity in RVF models, leading to important progress in our comprehension of epidemiological mechanisms. To go further, data gaps must be filled, and modelers need to improve their code accessibility.

摘要

裂谷热(RVF)是一种动物源性虫媒病毒病,已在非洲各地报告,包括最北部边缘、西南印度洋岛屿和阿拉伯半岛。该病毒可导致幼反刍动物流产率和死亡率升高,对受影响国家造成经济影响。迄今为止,由于涉及的脊椎动物宿主、媒介和生态系统的多样性,RVF 的流行病学机制尚未完全了解。在这种情况下,数学模型是深入了解复杂系统的有用工具,而机制模型特别适合数据稀缺的环境。在这里,我们对研究 RVF 的机制模型进行了系统回顾,以探讨它们的多样性及其对该疾病流行病学理解的贡献。我们研究了 Pubmed 和 Scopus 数据库(2021 年 10 月),最终选择了 48 篇论文,这些论文总共提出了 49 种不同的模型,并用 RVF 进行了数值应用。我们根据它们是否代表特定的地理背景以及是否依赖于广泛的数据使用,将模型分为理论、应用或灰色模型。我们讨论了它们对 RVF 流行病学理解的贡献,并强调了理论和应用模型的使用方式不同,但具有共同的目标。通过检查模型特征,我们确定了在不同尺度上仍未探讨的研究问题,例如动物流动性的作用,以及宿主和媒介物种对传播的相对贡献。重要的是,我们注意到在选择感染力的函数形式时缺乏充分的理由。总的来说,我们展示了 RVF 模型的多样性,这使得我们对流行病学机制的理解取得了重要进展。为了更进一步,必须填补数据空白,模型制作者需要提高他们的代码可访问性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3114/9718419/025eb422f5e5/pntd.0010339.g001.jpg

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