Xie Q, Wang J, You J L, Zhu S D, Zhou R, Tian Z J, Wu H, Lin Y, Chen W, Xiao L, Li J J, Dong J, Wu H L, Zhang W, Li J, Mu F, Xu X, Yin Y, Chen W J, Wang J
BGI-Shenzhen, Shenzhen 518083, China.
BGI-Wuhan, Wuhan 430075, China.
Zhonghua Yi Xue Za Zhi. 2020 Aug 25;100(32):2532-2536. doi: 10.3760/cma.j.cn112137-20200320-00860.
China adopted an unprecedented province-scale quarantine since January 23rd 2020, after the novel coronavirus (COVID-19) broke out in Wuhan in December 2019. Responding to the challenge of limited testing capacity, large-scale (>20 000 tests per day) standardized and fully-automated laboratory (Huo-Yan) was built as an ad-hoc measure. There is so far no empirical data or mathematical model to reveal the impact of the testing capacity improvement since quarantine. Based on the suspected case data released by the Health Commission of Hubei Province and the daily testing data of Huo-Yan Laboratory, the impact of detection capabilities on the realization of "clearing" and "clearing the day" of supected cases was simulated by establishing a novel non-linear and competitive compartments differential model. Without the establishment of Huo-Yan, the suspected cases would increase by 47% to 33 700, the corresponding cost of quarantine would be doubled, the turning point of the increment of suspected cases and the achievement of "daily settlement" (all newly discovered suspected cases are diagnosed according to the nucleic acid testing result) would be delayed for a whole week and 11 days. If the Huo-Yan Laboratory could ran at its full capacity, the number of suspected cases could start to decrease at least a week earlier, the peak of suspected cases would be reduced by at least 44%, and the quarantine cost could be reduced by more than 72%. Ideally, if a daily testing capacity of 10 500 tests was achieved immediately after the Hubei lockdown, "daily settlement" for all suspected cases could be achieved. Large-scale, standardized clinical testing platform, with nucleic acid testing, high-throughput sequencing, and immunoprotein assessment capabilities, need to be implemented simultaneously in order to maximize the effect of quarantine and minimize the duration and cost of the quarantine. Such infrastructure, for both common times and emergencies, is of great significance for the early prevention and control of infectious diseases.
自2019年12月新型冠状病毒（COVID-19）在武汉爆发后，中国于2020年1月23日采取了史无前例的省级规模隔离措施。为应对检测能力有限的挑战，作为一项临时措施，建立了大规模（每天超过20000次检测）标准化全自动实验室（火眼）。到目前为止，尚无实证数据或数学模型来揭示隔离后检测能力提升所带来的影响。基于湖北省卫生健康委员会公布的疑似病例数据和火眼实验室的每日检测数据，通过建立一个新的非线性竞争 compartment 微分模型，模拟了检测能力对疑似病例“清零”和“日清”实现情况的影响。若未建立火眼实验室，疑似病例将增加47%，达到33700例，相应的隔离成本将翻倍，疑似病例增量的转折点和“日清”（所有新发现的疑似病例均根据核酸检测结果确诊）的实现将推迟整整一周和11天。如果火眼实验室能够满负荷运行，疑似病例数量至少可提前一周开始下降，疑似病例峰值至少降低44%，隔离成本可降低72%以上。理想情况下，若湖北封城后立即实现每日10500次检测能力，所有疑似病例均可实现“日清”。为使隔离效果最大化并尽量缩短隔离时间和降低隔离成本，需同时实施具备核酸检测、高通量测序和免疫蛋白评估能力的大规模标准化临床检测平台。这样的基础设施，无论平时还是紧急情况下，对于传染病的早期防控都具有重要意义。
