Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity
Quantifying asymptomatic infection and transmission of COVID-19 in New York City using observed cases, serology, and testing capacity
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DOI：
10.1101/2020.10.16.20214049
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发表时间：
2020-10
影响因子：
11.1
通讯作者：
R. Subramanian;Qixin He;Mercedes Pascual
中科院分区：
文献类型：
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作者：
R. Subramanian;Qixin He;Mercedes Pascual
意义
随着卫生官员面临又一波新冠疫情，他们需要对出现症状的感染病例比例以及有症状和无症状病例对社区传播的影响程度进行评估。近期的无症状检测指南含糊不清。利用一个包含检测能力的流行病学模型，我们表明许多感染是无症状的，但总体上对社区传播有重大影响。它们的个体传播性仍不确定。如果它们像有症状感染一样传播，疫情可能会以比当前模型通常假设的更快速度传播。如果不是这样，那么每个有症状病例平均产生的二次感染数量会比通常假设的要高。无论如何，控制传播都需要在广泛且记录详尽的无症状检测基础上进行社区层面的干预。无症状感染对群体免疫和社区传播的贡献是新冠疫情复发和控制的关键，但使用忽略检测能力变化的当前模型很难进行评估。利用一个结合每日检测信息并与纽约市的病例和血清学数据相匹配的模型，我们表明有症状病例的比例较低，在13%到18%之间，而且繁殖数可能比通常假设的要大。无症状感染对群体免疫有重大贡献，并与症状前病例一起对社区传播有重大影响。如果无症状感染以与有症状感染相似的速率传播，所有类别综合的总体繁殖数比通常假设的要大，估计值在3.2到4.4之间。如果它们传播能力弱，那么有症状病例的繁殖数在3.9到8.1之间。即使在这种情况下，症状前和无症状病例加起来在疫情爆发高峰期至少占感染力量的50%。我们没有发现所有感染亚群繁殖数都低于3的情况。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。它们还强调了随着我们经历更长时间的监测和第二波疫情，检测的时间序列数据如何能够减少并更好地界定这种不确定性。需要补充信息来确定无症状病例的传播性，我们对此进行了讨论。无论如何，应该重新考虑关于严重急性呼吸综合征冠状病毒2（SARS - Cov - 2）基本繁殖数的当前假设。
Significance As health officials face another wave of COVID-19, they require estimates of the proportion of infected cases that develop symptoms, and the extent to which symptomatic and asymptomatic cases contribute to community transmission. Recent asymptomatic testing guidelines are ambiguous. Using an epidemiological model that includes testing capacity, we show that many infections are nonsymptomatic but contribute substantially to community transmission in the aggregate. Their individual transmissibility remains uncertain. If they transmit as well as symptomatic infections, the epidemic may spread at faster rates than current models often assume. If they do not, then each symptomatic case generates, on average, a higher number of secondary infections than typically assumed. Regardless, controlling transmission requires community-wide interventions informed by extensive, well-documented asymptomatic testing. 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.