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Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity [Population Biology]
Proceedings of the National Academy of Sciences of the United States of America ( IF 9.4 ) Pub Date : 2021-03-02 , DOI: 10.1073/pnas.2019716118
Rahul Subramanian 1 , Qixin He 1 , Mercedes Pascual 2, 3
Affiliation  

The contributions of asymptomatic infections to herd immunity and community transmission are key to the resurgence and control of COVID-19, but are difficult to estimate using current models that ignore changes in testing capacity. Using a model that incorporates daily testing information fit to the case and serology data from New York City, we show that the proportion of symptomatic cases is low, ranging from 13 to 18%, and that the reproductive number may be larger than often assumed. Asymptomatic infections contribute substantially to herd immunity, and to community transmission together with presymptomatic ones. If asymptomatic infections transmit at similar rates as symptomatic ones, the overall reproductive number across all classes is larger than often assumed, with estimates ranging from 3.2 to 4.4. If they transmit poorly, then symptomatic cases have a larger reproductive number ranging from 3.9 to 8.1. Even in this regime, presymptomatic and asymptomatic cases together comprise at least 50% of the force of infection at the outbreak peak. We find no regimes in which all infection subpopulations have reproductive numbers lower than three. These findings elucidate the uncertainty that current case and serology data cannot resolve, despite consideration of different model structures. They also emphasize how temporal data on testing can reduce and better define this uncertainty, as we move forward through longer surveillance and second epidemic waves. Complementary information is required to determine the transmissibility of asymptomatic cases, which we discuss. Regardless, current assumptions about the basic reproductive number of severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) should be reconsidered.



中文翻译:

使用观察到的病例、血清学和检测能力来量化纽约市的无症状感染和传播的 COVID-19 [群体生物学]

无症状感染对群体免疫和社区传播的贡献是 COVID-19 卷土重来和控制的关键,但很难使用忽略检测能力变化的当前模型来估计。使用包含适合病例的日常检测信息和来自纽约市的血清学数据的模型,我们发现有症状病例的比例较低,为 13% 至 18%,并且再生数可能比通常假设的要大。无症状感染极大地促进了群体免疫,并与症状前感染一起促进了社区传播。如果无症状感染者的传播率与有症状感染者相似,那么所有类别的总体传染数就会比通常假设的要大,估计范围为 3.2 至 4.4。如果传播不良,则有症状病例的繁殖数会更大,范围为 3.9 至 8.1。即使在这种情况下,在疫情高峰期,无症状病例和无症状病例合计至少占感染力的 50%。我们没有发现所有感染亚群的繁殖数都低于三的制度。这些发现阐明了尽管考虑了不同的模型结构,但当前病例和血清学数据无法解决的不确定性。他们还强调,随着我们继续进行更长时间的监测和第二波流行病,测试的时间数据如何能够减少并更好地定义这种不确定性。需要补充信息来确定我们讨论的无症状病例的传播性。无论如何,目前关于严重急性呼吸综合征冠状病毒 2 (SARS-Cov-2) 基本繁殖数的假设应该重新考虑。

更新日期:2021-02-11
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