a Biostatistics, Biomathematics, Pharmacoepidemiology, and Infectious Diseases (B2PHI) Unit , Institut Pasteur, Inserm U1181, University of Versailles St-Quentin-en-Yvelines.
b Department of Ecology and Evolutionary Biology , University of Michigan , Ann Arbor , MI , USA.
Hum Vaccin Immunother. 2019;15(3):683-686. doi: 10.1080/21645515.2018.1549432. Epub 2018 Dec 20.
The epidemiology of pertussis-a vaccine-preventable respiratory infection typically caused by the bacterium Bordetella pertussis-remains puzzling. Indeed, the disease seems nowhere close to eradication and has even re-emerged in certain countries-such as the US-that have maintained high vaccination coverage. Because the dynamics of pertussis are shaped by past vaccination and natural infection rates, with the relevant timescale spanning decades, the interpretation of such unexpected trends is not straightforward. In this commentary, we propose that mathematical transmission models play an essential role in helping to interpret the data and in closing knowledge gaps in pertussis epidemiology. We submit that recent advances in statistical inference methods now allow us to estimate key parameters, such as the nature and duration of vaccinal immunity, which have to date been difficult to quantify. We illustrate these points with the results of a recent study based on data from Massachusetts (Domenech de Cellès, Magpantay, King, and Rohani, Sci. Transl. Med. 2018;10: eaaj1748. doi:10.1126/scitranslmed.aaj1748), in which we used such methods to elucidate the mechanisms underlying the ongoing resurgence of pertussis. In addition, we list a number of safety checks that can be used to critically assess mathematical models. Finally, we discuss the remaining uncertainties surrounding pertussis vaccines, in particular the acellular vaccines used for teenage booster immunizations.
百日咳的流行病学——一种由百日咳鲍特菌引起的可通过疫苗预防的呼吸道感染——仍然令人费解。事实上，这种疾病似乎远未被根除，甚至在一些保持高疫苗接种率的国家（如美国）再次出现。由于百日咳的动态受过去疫苗接种和自然感染率的影响，相关时间跨度跨越几十年，因此解释这种出乎意料的趋势并不简单。在这篇评论中，我们提出数学传播模型在帮助解释数据和弥合百日咳流行病学中的知识空白方面发挥着至关重要的作用。我们认为，最近统计推断方法的进展现在使我们能够估计关键参数，例如疫苗免疫的性质和持续时间，这些参数迄今为止一直难以量化。我们用最近来自马萨诸塞州的数据的研究结果来说明这些观点（Domenech de Cellès、Magpantay、King 和 Rohani，Sci. Transl. Med. 2018；10：eaaj1748. doi：10.1126/scitranslmed.aaj1748），我们使用这些方法阐明了百日咳持续复苏的机制。此外，我们列出了一些可用于严格评估数学模型的安全检查。最后，我们讨论了围绕百日咳疫苗的剩余不确定性，特别是用于青少年加强免疫的无细胞疫苗。
