Objective: 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. Methods: 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. Results: 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. Conclusions: 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.
目的: 为应对新型冠状病毒肺炎(COVID-19)的大规模流行,依托有资质、有能力的检测机构,建立了每日万人份的应急核酸检测及千人份高通量测序实验室(武汉"火眼"实验室)。运用数学模型分析武汉"关闭离汉通道"后检测能力快速扩大对于疫情防控效果的影响。 方法: 在2020年1月23日武汉"关闭离汉通道"后,依据湖北省卫健委通报的疑似病例数据,以及"火眼"实验室每日检测数据,通过建立非线性、竞争性微分方程模型,模拟检测能力对实现疑似病例"清零"和"日清日结"的影响。 结果: 在万人级病原检测实验室没有建成的情况下,疑似患者高峰数量将从23 000例上升到33 700例(增长47%),疑似患者数量下降的转折点将延后6 d,实现"日清日结"将延迟11 d,疑似患者隔离成本将增加124%;万人级病原检测实验室饱和运转的情况下,疑似患者例数高峰将减少56%,超过22 800例疑似患者能够提前获得诊断和收治,疑似患者数量下降转折点将提前1周到来,实现"日清日结"可提前约12 d,隔离成本可减少72%;理想情况下,若"关闭离汉通道"时立即将日检测能力超过10 500例的规模化检测平台投入使用,则可始终保证疑似病例"日清日结"。为让"关闭离汉通道"持续时间和隔离成本最小化,需将规模化、标准化检测平台建设与"关闭离汉通道"、床位扩容、加强救治能力等措施同步执行,并向检测平台持续送样,保证饱和运行。 结论: 建设"平战结合"的精准检测平台是新发传感染病防控的关键一环,应作为重要基础设施统筹配置加以保障。.
Keywords: 2019-nCoV; Numerical simulation; Testing capacity.