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结合简约的数学模型和定制实验中的感染数据来理解环境传播。

Combining a parsimonious mathematical model with infection data from tailor-made experiments to understand environmental transmission.

机构信息

Quantitative Veterinary Epidemiology, Wageningen University and Research, 6708 PB, Wageningen, The Netherlands.

Wageningen Bioveterinary Research, Wageningen University and Research, 8221 RA, Lelystad, The Netherlands.

出版信息

Sci Rep. 2023 Aug 10;13(1):12986. doi: 10.1038/s41598-023-38817-z.

DOI:10.1038/s41598-023-38817-z
PMID:37563156
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10415373/
Abstract

Although most infections are transmitted through the environment, the processes underlying the environmental stage of transmission are still poorly understood for most systems. Improved understanding of the environmental transmission dynamics is important for effective non-pharmaceutical intervention strategies. To study the mechanisms underlying environmental transmission we formulated a parsimonious modelling framework including hypothesised mechanisms of pathogen dispersion and decay. To calibrate and validate the model, we conducted a series of experiments studying distance-dependent transmission of Campylobacter jejuni in broilers. We obtained informative simultaneous estimates for all three model parameters: the parameter of C. jejuni inactivation, the diffusion coefficient describing pathogen dispersion, and the transmission rate parameter. The time and distance dependence of transmission in the fitted model is quantitatively consistent with marked spatiotemporal patterns in the experimental observations. These results, for C. jejuni in broilers, show that the application of our modelling framework to suitable transmission data can provide mechanistic insight in environmental pathogen transmission.

摘要

虽然大多数感染是通过环境传播的,但对于大多数系统来说,环境传播阶段背后的过程仍然知之甚少。更好地了解环境传播动力学对于有效的非药物干预策略很重要。为了研究环境传播的机制,我们制定了一个简洁的建模框架,包括假设的病原体扩散和衰减机制。为了校准和验证模型,我们进行了一系列实验,研究空肠弯曲杆菌在肉鸡中的距离依赖性传播。我们同时获得了所有三个模型参数的信息性估计:空肠弯曲杆菌失活参数、描述病原体扩散的扩散系数以及传播率参数。拟合模型中的时间和距离依赖性与实验观察中标记的时空模式定量一致。这些结果表明,我们的建模框架应用于合适的传播数据可以为环境病原体传播提供机制上的见解。

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