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2016年至2019年尼日利亚大规模拉沙热疫情的机制建模

Mechanistic modelling of the large-scale Lassa fever epidemics in Nigeria from 2016 to 2019.

作者信息

Musa Salihu S, Zhao Shi, Gao Daozhou, Lin Qianying, Chowell Gerardo, He Daihai

机构信息

Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong; Department of Mathematics, Kano University of Science and Technology, Wudil, Nigeria.

School of Nursing, The Hong Kong Polytechnic University, Hong Kong; JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong; Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China.

出版信息

J Theor Biol. 2020 May 21;493:110209. doi: 10.1016/j.jtbi.2020.110209. Epub 2020 Feb 22.

Abstract

Lassa fever, also known as Lassa hemorrhagic fever, is a virus that has generated recurrent outbreaks in West Africa. We use mechanistic modelling to study the Lassa fever epidemics in Nigeria from 2016-19. Our model describes the interaction between human and rodent populations with the consideration of quarantine, isolation and hospitalization processes. Our model supports the phenomenon of forward bifurcation where the stability between disease-free equilibrium and endemic equilibrium exchanges. Moreover, our model captures well the incidence curves from surveillance data. In particular, our model is able to reconstruct the periodic rodent and human forces of infection. Furthermore, we suggest that the three major epidemics from 2016-19 can be modelled by properly characterizing the rodent (or human) force of infection while the estimated human force of infection also present similar patterns across outbreaks. Our results suggest that the initial susceptibility likely increased across the three outbreaks from 2016-19. Our results highlight the similarity of the transmission dynamics driving three major Lassa fever outbreaks in the endemic areas.

摘要

拉沙热,又称拉沙出血热,是一种在西非反复引发疫情的病毒。我们使用机理模型研究了2016年至2019年尼日利亚的拉沙热疫情。我们的模型在考虑隔离、检疫和住院过程的情况下,描述了人类与啮齿动物种群之间的相互作用。我们的模型支持前向分岔现象,即无病平衡和地方病平衡之间的稳定性发生交换。此外,我们的模型很好地捕捉了监测数据中的发病率曲线。特别是,我们的模型能够重建周期性的啮齿动物和人类感染力。此外,我们建议,通过适当表征啮齿动物(或人类)感染力,可以对2016年至2019年的三次主要疫情进行建模,而估计的人类感染力在各次疫情中也呈现出相似的模式。我们的结果表明,在2016年至2019年的三次疫情中,初始易感性可能有所增加。我们的结果突出了在流行地区推动三次主要拉沙热疫情的传播动态的相似性。

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