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新型冠状病毒感染的肺炎疫情紧急研究议程:传播和非药物缓疫策略

2020-02-06

  一、背景 

  20191229日,武汉市某医院报告了一起不明原因重症肺炎聚集性病例事件,中国政府核实后通报了世界卫生组织(WHO[1]202018日,此次暴发的病原被确认为新型冠状病毒,即2019新型冠状病毒(2019-nCoV),其基因序列被迅速提交WHO130日,WHO宣布将新型冠状病毒感染的肺炎疫情列为“国际关注的突发公共卫生事件” [2]。病原确认后的1个月中,科学家们通过研究已经阐明了诸多重要问题,给疫情的理解、预测和防控带来很多帮助[1,3-7]。尽管我们对2019-nCoV的认识已逐步深入,但很多问题仍然缺乏答案或不够精确,亟待解决。 

  本研究议程仅列出了四个领域中的优先研究问题,包括疾病传播特征、临床特征、流行轨迹和医疗卫生服务需求预测,以及防控策略的监测和评估。因此,本研究议程涉及的仅为中短期内需要解决和可望解决的防控决策相关的重要问题,不涉及2019-nCoV起源、新工具(如快速诊断工具)开发、疫苗和药物使用等问题。我们相信,这些问题的答案将有助于完善防控策略,遏制或缓解新型冠状病毒感染的肺炎流行。 

  二、研究方法 

  通过回顾2019-nCoVSARSMERS和流感研究文献,以及与学术及公共卫生机构的专家们讨论制定。在每一个研究领域中,我们简述了已知信息、优先研究问题以及研究建议。 

  三、结果 

  对照每个领域的研究问题列表,我们对四个领域分别进行描述。 

  领域1疾病传播特征 

  问题1病毒传播广度 

  •   病毒在人群中的传播程度,包括在疫情开始前的扩散程度如何? 

  问题2    传播能力 

  •  基本再生数(R0)、有效再生数(Re)、代际间隔时间(Tg)及倍增时间是多少? 
  •  是否发现了“超级传播者”,以及“超级传播者”引起的事件特征是什么?是否有可能判定哪些高风险人群可成为“超级传播者”? 
  •  温度和湿度影响传播能力吗,以何种方式影响? 

  问题3    传染期和感染力 

  •  病例排毒时间持续多久?发病之前是否排毒?如果是,发病多久前排毒?病愈后是否持续排毒?如果是,持续多久? 
  •  轻症和重症病例相比,排毒期是否存在差异?不同临床表现(呼吸道症状与非呼吸道症状)与传染性的相关性如何? 
  •  感染者能否在潜伏期传播病毒?效率如何? 
  •  轻症(未发热)感染者可以传播病毒吗?效率如何? 
  •  无症状感染者可以传播病毒吗?效率如何? 

  问题4    传播途径 

  •  哪些呼吸道、胃肠道或其他体液分泌物/排泄物具有传染性?它们的传染性如何? 
  •  在感染者尸体的哪些部位、哪种体液中可以发现有传染性的病毒? 
  •  血液中有病毒吗?这可能对血液供应的安全具有意义。血液中的病毒是否可以通过常规血液制备方法灭活? 
  •  PCR检测到的病毒RNA与其传染性有何关系? 
  •  病毒是否会残留在物体表面?如果是,可以残留多长时间? 

  问题5    高风险职业和行为 

  •  哪些职业人群感染风险更高? 
  •  哪些行为感染风险更高? 

  问题6    免疫力 

  •  新型冠状病毒感染后会产生免疫力,并预防再次感染该病毒吗?免疫力可持续多长时间? 
  •  某些人群(例如儿童)是否已有抗感染免疫力,或者具有感染后不发病的保护力? 

  谁在传播病毒,谁被感染,以及病毒传播是如何发生的。这些信息有助于增加病例筛查和识别的敏感性、模拟流行轨迹、完善隔离和检疫策略、以及帮助制定未来的疫苗接种策略。目前认为2019-nCoV主要通过呼吸道飞沫传播,但其他来源可能也很重要[8];无症状和轻症感染者的传播能力、“超级传播者”在流行延续中的可能作用尚不完全清楚;武汉、湖北和其他省市的新型冠状病毒感染范围尚不清楚,但血清学研究可以提供线索。对201912月及之前的临床实验室常规检测的剩余血液进行血清学检测,可能有助于确定疫情暴发前是否已存在社区传播。整体而言,该领域的研究方法包括流行病学研究、接触者追踪、在密切接触者中进行病毒监测、通过人群抽样或利用实验室检测的剩余血液开展血清学调查,以及对流感哨点监测网络的样本进行RT-PCR检测。 

    

  领域 2. 疾病临床特征 

  问题1    疾病的临床谱和病程 

  •  感染者中无症状、轻症(无肺炎)、无发热、普通肺炎、重症、危重症、死亡的比例如何? 
  •  在不同特征人群中(如儿童、成年人、老年人、基础疾病患者、孕妇等)自然史、临床特征和疾病谱是否不同? 
  •  发病到诊断的间隔、发病到住院的间隔、发病到死亡的间隔如何?在不同疾病严重程度和不同地区,上述间隔是否不同? 
  •  2019-nCoV单独感染的人群,与该病毒和其他呼吸道病原共同感染的人群相比,疾病的临床表现和结局是否存在差异? 
  •  2019-nCoV感染死亡的病例中,其导致死亡的原因是什么? 

  问题2    严重性和预后因素 

  •  不同临床特征和社会人口学特征的感染者中,疾病严重性和死亡风险是否存在差异? 
  •  不同症状和疾病所需要的医学支持措施(例如住院、呼吸支持、ICU)有何不同? 
  •  重症和危重症病例恢复的比例如何?需要呼吸支持的患者恢复的比例如何? 
  •  在既往健康的个体中发生死亡的比例如何? 
  •  是否有儿童和孕妇发展为严重疾病,如果有,感染的孕妇怀孕结局如何? 
  •  在伴有HIV感染的人中是否有病例发生,如果有,他们是否发展为严重病例? 

  问题3    病例发现 

  •  感染后具有哪些临床特征的人会寻求实验室检测以确定感染? 
  •  感染者就诊的比例? 
  •  是否有方法可以发现那些感染但没有就诊的人? 

  正如Munster[4]描述,掌握完整疾病谱以及疾病监测金字塔与暴发遏制之间的关系,对疫情应对和疫情发展预测至关重要。阐明临床和社会人口特征与疾病严重程度和死亡之间的关联,有助于预测医疗卫生服务需求,改进病例识别和筛查策略,并为未来的疫苗接种策略提供证据支持。整体而言,该领域的研究方法包括病例流行病学调查、血清学检测、病例密切接触者病毒监测、临床管理和疾病结局研究。 

    

  领域3. 流行轨迹和医疗卫生服务需求预测 

  问题1 模型假设和参数 

  •  对重要的模型预测结果(流行的高峰什么时候到达?什么时候结束?对卫生系统的影响?对经济的影响?)最为敏感的模型假设和参数有哪些? 
  •  模型的哪些假设和参数是高度优先需要通过流行病学和其他研究来获得的? 

  模型参数和假设可能包括: 

  1.感染后的免疫力。 

  2.病程。 

  3.病毒的动物来源以及持续向人类溢出病毒的储存宿主。 

  4.人群易感性。 

  5.不同临床阶段的传染性。 

  6.传播导致的感染、临床病例、住院病例和死亡。 

  问题2 模型预测 

  •  若未采取防控干预措施,本次疫情的情况会如何? 

  1.总感染数、病例数、需检疫人数、需隔离人数、住院数、需要呼吸支持的患者数、需要重症监护的患者数、死亡数。 

  2.在不同地区,流行的最高峰能达到多高? 

  3.在不同地区,达到流行高峰需要多长时间? 

  4.对医疗卫生服务能力有哪些影响? 

  •  各种干预措施的组合会发挥什么影响?(隔离、检疫、增加人际距离、限制人群流动、个人防护、筛查) 

  1.在不同地区,流行的最高峰将达到多高? 

  2.在不同地区,达到流行高峰需要多长时间? 

  3.不同的公共卫生控制措施的效果如何?在某些地区,是否有某项控制措施比其他措施更为合适?例如针对城市地区、农村地区等。 

  4.公共卫生措施实施的最佳时机?(开始时间、终止时间) 

  问题3. 模型评估 

  •  如何评估数学模型的准确性? 
  •  有什么可靠的和及时的信号,提示某数学模型可提供正确的预测? 

  关于本次疫情,各方研究者已建立了若干数学模型来洞悉流行轨迹[3,9-13]。可通过评估已发表的多个模型和预测结果的异同,进一步开展敏感性分析,确定哪些模型最有用。高质量的数据对于模型预测也很重要,因此,有必要不断评估并提高基础数据的质量。需要用模型预测的重要结果,包括基本和有效再生数、代际间隔、流行曲线、隔离检疫的负担、医疗卫生服务需求和经济影响等。这些重要结果对各种模型假设和参数的敏感性可能不同。相关研究有助于减小模型预测结果的不确定性。模型预测研究对评估疫情控制措施(如病例筛查、隔离和检疫、增加人际距离的策略和人口流动限制措施等)的潜在影响具有很大的实用价值。在疫情应对期间,持续监控模型的预测结果,有助于评价模型的有效性及其对决策后果的预测能力。 

    

  领域4. 疾病防控策略的监测和评估 

  问题1 针对本次疫情需要建立或加强哪些监测手段,在哪些层级建立? 

  •  感染 

  1.病例接触者的追踪(包括评估接触者的监测措施是否有效,并确定接触者发病的比例)。 

  2.利用常规实验室剩余的血标本进行血清学监测,以识别在人群中的感染情况,并对检测阳性者开展调查,确定感染来源。 

  3.利用门急诊流感样病例(ILI)、急性呼吸道感染(ARI)、住院严重急性呼吸道感染(SARI)监测系统开展2019-nCoV监测。 

  4.常规、定期对分离到的病毒进行测序,确定病毒进化情况,据此更新PCR和其他检测方法。 

  •  策略措施的依从性 

  1.隔离措施的依从性。 

  2.现有筛查措施的依从性。 

  3.个人防护措施的依从性。 

  •  疫情控制措施的社会可接受度:社会对围堵和缓疫策略的疲劳程度。 

  问题2 防控策略效果评估 

  •  围堵策略是否有效?何时需要转为缓疫策略? 
  •  缓疫策略是否有效?何时缓疫策略可以降级? 
  •  哪项对策最有效?经济成本最小? 

  新型冠状病毒感染的肺炎属于我国法定报告的乙类传染病,目前按甲类管理[14]。当前已实施了若干减少传播和感染风险,以及降低疫情影响的防控策略,包括围堵和缓疫。围堵(containment)是在新发传染病疫情早期,在限定的地理范围内,采用医学和非医学(区域封锁、停学和停工等)干预策略和措施,以迅速阻断疫情传播。缓疫(mitigation)是为了减轻疫情对医疗服务和社会运行的冲击和压力,采用医学和非医学干预策略和措施,延缓疫情增长速度,推迟流行高峰到来时间,压低峰值的策略。因此,我们需要建立评估平台,以监测病毒及其传播和进化,以及在不同地区实施的围堵和缓疫策略的依从情况和有效性。除病例接触者的追踪外,可以考虑的新平台包括重点人群的血清学监测、在门急诊流感样病例监测、急性呼吸道感染监测及住院严重急性呼吸道感染监测项目中检测2019-nCoV,在农贸市场寻找病毒,不断对新分离的病毒进行测序以确定冠状病毒的进化情况,并据此更新诊断试验。监测围堵和缓疫策略的依从情况和公众参与情况,可以帮助确定当前策略措施(包括检疫、隔离、筛查、个人防护和增加人际距离)的社会可接受性,这对于疫情应对的有效性和持续性很重要。 

    

  四、讨论 

  目前武汉市的新型冠状病毒疫情仍处于早期阶段,中国正实施多种策略以遏制病毒传播,减轻疫情影响。鉴于对2019-nCoV的传播动力学和疾病谱的现有研究数据仍然有限,迫切需要新的证据来支持疫情应对工作,降低疫情的健康和经济损失。有关传播特征、疾病谱、疫情重要影响的模型预测、围堵和缓疫策略的实施情况以及潜在影响的评估等将有助于改进疫情应对。 

  本研究议程简要描述了中国疾病预防控制中心为填补中短期知识缺口优先考虑的问题,且仅限于4个领域。议程撰写时预期2019-nCoV的血清学检测工具很快将可获得。其他研究领域,例如研发治疗药物、疫苗和其他预防措施、开发新的诊断工具、寻找病毒来源和动物宿主,也非常重要,但未列入本议程的范围内。 

  我们期望我国学术机构、各级疾控机构、其他研究组织和国际社会开展或参与这些研究。我们还期望研究机构和国际合作伙伴帮助完善和改进这一研究议程,并随新知识的产生和新证据的出现而不断更新[15]。作为国家级疾病预防控制机构,中国疾病预防控制中心将跟踪研究进展,促进与国内外科学界、政府和关键利益相关者分享研究结果。 

  当前,医疗机构掌握着一手的病人资料和样本,疾控机构掌握着疫情报告数据、病例和接触者调查资料,学术机构、非营利性组织和企业拥有强大的研究资源和能力。各方真诚、开放、协调、高效的合作,对研究工作的快速、有序推进至关重要。中国疾控中心愿推动建立新型冠状病毒疫情应对应急研究联盟中心,尽快制定并发布高质量、统一的研究方案和研究工具,促进向合作者开放不涉及隐私和敏感数据的资料和病患标本,联合各方力量开展快速调查和研究,为优化疫情应对策略和病人管理提供有力支持。 

    

    

  作者:中国疾病预防控制中心新型冠状病毒感染的肺炎疫情防控技术组 

  议程编写专家组: 

  中国疾病预防控制中心:冯子健 

  中国疾病预防控制中心传染病管理处:陈秋兰、冯录召、李中杰、秦颖、王晴、杨孝坤、殷文武、张慕丽 

  中国疾病预防控制中心卫生应急中心:张婷 

  中国疾病预防控制中心免疫规划中心:安志杰、李媛秋、吴丹、尹遵栋 

  中国疾病预防控制中心性病艾滋病预防控制中心:俞海亮 

  中国疾病预防控制中心结核病预防控制中心:陈伟、夏愔愔 

  中国疾病预防控制中心传染病预防控制所:张若尘 

  中国疾病预防控制中心高级顾问:Lance Rodewald 

  通讯作者:冯子健,邮箱:fengzj@chinacdc.cn 

    

  致谢感谢Ben Cowling教授,Alexander James Millman博士,Chin-Kei Lee博士、吴尊友研究员、王华庆研究员和赖圣杰博士在议程起草中给予的宝贵建议,杜珩博士对本文翻译工作给予的支持,以及苏琪茹博士提供参考资料。 

    

  本文已在《中华流行病学》杂志刊出。(中华流行病学杂志,2020412):135-138.  

  DOI:10.3760/cma.j.issn.0254-6450.2020.02.001 

    

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  [7]        Paules CI, Marston HD, Fauci AS. Coronavirus Infections-More Than Just the Common Cold[J]. Jama, 2020. 

  [8]        Holshue ML, DeBolt C, Lindquist S, et al. First Case of 2019 Novel Coronavirus in the United States[J]. N Engl J Med, 2020. 

  [9]        Wu JT, Leung K, Leung GM. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study[J]. The Lancet, 2020. 

  [10]      Riou J, Althaus CL. Pattern of early human-to-human transmission of Wuhan 2019-nCoV[J]. bioRxiv, 2020: 2020.2001.2023.917351. 

  [11]      Zhao S, Lin Q, Ran J, et al. Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak[J]. bioRxiv, 2020: 2020.2001.2023.916395. 

  [12]      Liu T, Hu J, Kang M, et al. Transmission dynamics of 2019 novel coronavirus (2019-nCoV)[J]. bioRxiv, 2020: 2020.2001.2025.919787. 

  [13]      Read JM, Bridgen JRE, Cummings DAT, et al. Novel coronavirus 2019-nCoV—early estimation of epidemiological parameters and epidemic predictions[J]. medRxiv, 2020. 

  [14]      National Health Committee. Announcement of the National Health Committee of the People's Republic of China; http://www.nhc.gov.cn/jkj/s7916/202001/44a3b8245e8049d2837a4f27529cd386.shtml.  

  [15]      Heymann DL. Data sharing and outbreaks: best practice exemplified[J]. Lancet, 2020. 

    

    

    

    

    

    

    

    

    

    

    

  Urgent research agenda for the novel coronavirus epidemic: transmission and non-pharmaceutical mitigation strategies 

    

  Author: Strategy and policy working group for NCIP epidemic response, Chinese Center for Disease Control and Prevention (China CDC). 

  Corresponding author: Zijian Feng, fengzj@chinacdc.cn 

  Member of the working group participating in the work: 

  Chinese Center for Disease Control and Prevention (China CDC): Zijian Feng. 

  Division of Infectious Diseases, China CDC: Qiulan Chen, Luzhao Feng, Zhongjie Li, Shu Li, Ying Qin, Qing Wang, Xiaokun Yang, Wenwu Yin, Muli Zhang. 

  Public Health Emergency Center, China CDC: Ting Zhang. 

  National Immunization Programme, China CDC: ZhijieAn, Yuanqiu Li, Dan Wu, Zundong Yin. 

  National Center for AIDS/STD Control and Prevention, China CDC: Hailiang Yu. 

  Chinese Center for Tuberculosis Control and Prevention (TB center), China CDC: Chen Wei, Yinyin Xia. 

  National Institute for Communicable Disease Control and Prevention, China CDC: Ruochen Zhang. 

  China CDC Senior Consultant: Lance Rodewald. 

    

  Background 

  On December 29, 2019, a cluster of cases of severe pneumonia of unknown etiology was identified by hospital clinicians in Wuhan and reported to health authorities who in turn reported the cluster to the World Health Organization (WHO) [1]. On January 8, 2020, the cause of the pneumonia was determined to be a novel coronavirus, 2019-nCoV, and its genetic sequence was provided to WHO. The illness likely to have been caused by this Cov was named “novel coronavirus-infected pneumonia” (NCIP). On January 30, WHO declared the epidemic started by the novel coronavirus to be a Public Health Emergency of International Concern [2]. In the first month since identification of the coronavirus, many scientists have described important research questions that can help understand, predict, and mitigate the epidemic [1,3-7]. Considerable new knowledge about this coronavirus has been generated, but evidence is lacking or not sufficiently precise to address some research questions. 

  We report a limited research agenda of questions in four domains: transmission, clinical features, prediction on epidemic trajectory and health care capacity needed, and monitoring and evaluation of strategies. The scope of the agenda is short- to medium-term and aims to support epidemic control decision making processes. It does not include research on the origin of the coronavirus, development of new tools such as rapid point-of-care diagnostics, or the use of vaccines and other pharmaceutical strategies. We believe that answers to questions in the four domains can help refine strategies to contain or mitigate the 2019-nCoV epidemic. 

    

  Methods 

  This agenda was developed through review of scientific literature on 2019-nCoV, SARS, MERS, and influenza and discussion with experts at academic and public health institutions. For each of the four domains, we describe briefly what is known, priority research questions, and suggestions of methods to address the questions. 

    

  Results 

  Each of the domains is described in this section, with reference to the lists of research questions for each domain in the boxes. 

  Box 1. The first domain concerns transmission of the novel coronavirus – who is transmitting the virus, who is getting infected, and how is transmission occurring. This information will help inform efforts to screen for the virus, model the epidemic, refine isolation and quarantine, and inform vaccination strategies. The coronavirus is known to be transmitted primarily through respiratory droplets, but other sources may be significant [8]; the degree to which asymptomatic and mild infections can transmit is not fully understood, nor is the potential role of “super-spreaders” in sustaining the epidemic; and the breadth of infection in Wuhan, Hubei and other provinces is not known but can be informed by serological studies. Serological testing of residual blood from routine clinical laboratory testing obtained in December 2019 and earlier may help determine the extent, if any, of earlier community spread. Methods of study for this domain include epidemiological studies, contact tracing, virological monitoring of close contacts, serological surveys using population-based sampling or residual blood from laboratory testing, and virus detection with RT-PCR of samples from the influenza sentinel surveillance network. 

  Box 2. The second domain concerns the clinical features associated with 2019-nCoV infection. As described by Munster and colleagues [4], knowledge of the full spectrum of disease and the relation between the surveillance pyramid and outbreak containment is of critical importance for responding to the epidemic and predicting its trajectory. Knowledge of the association of clinical and sociodemographic factors with illness severity and mortality can help predict health care needs, improve screening strategies, and provide evidence for future vaccine deployment. Methods for this domain include epidemiological investigation of cases, serological testing, virological monitoring of quarantined close contacts of cases, and studies of clinical management and illness outcomes. 

  Box 3. The third domain concerns prediction of epidemic trajectories and health care capacity needs. Several mathematical models of this epidemic have been developed that provide insight to the epidemic [3,9-13]. It is important to have multiple models and multiple forecasts to evaluate consensus and divergence of models, perform additional sensitivity analyses, and determine which ones appear to be useful for various predictions. High quality data are also important for modeling, necessitating continuous evaluation of data quality. Important model outputs, including the basic and effective reproduction numbers, generation time, epidemic curve shape, burden of isolation, quarantine, healthcare use and economic impact will vary in their sensitivity to model assumptions and parameters. This knowledge can help inform research studies to narrow the range of uncertainty in important model outputs. Modelling has great utility in evaluating the potential impact of countermeasures, such as screening, isolation and quarantine, social distancing strategies, and population movement restrictions. Monitoring model predictions during the epidemic response may be able to help evaluate the validity of models and their ability to predict outcomes of importance to policy makers. 

  Box 4. The fourth domain concerns establishing or strengthening epidemic response strategies through monitoring and evaluation. The novel coronavirus is a Category B infectious disease that is being managed as a Category A (most severe) infectious disease [14]. To date, several strategies to reduce transmission and risk of infection, and mitigate epidemic impact have been implemented. Evaluation platforms will need to be established to monitor the virus and its spread and evolution, and to monitoring compliance and effectiveness of containment and mitigation strategies under different scenarios. In addition to contact tracing of cases, new platforms to consider include serological monitoring of key population groups, linking 2019-nCoV surveillance into influenza-like illness (ILI), acute respiratory infections (ARI) and hospitalized severe acute respiratory infections (SARI) surveillance, searching for the virus in wet markets, and routine sequencing of isolated viruses to determine the evolution of the coronavirus and update diagnostic tests. Monitoring compliancewith containment and mitigation strategiesand public engagement for determining the societal acceptability of strategies will be important for effective and sustained response.  

    

  Discussion 

  The 2019-nCoV epidemic is in an early stage following its detection in Wuhan, and many strategies are being implemented to contain this virus and mitigate epidemic impact. Given limitations in the available data on the transmission dynamics and spectrum of disease of 2019-nCoV, new evidence is urgently needed to guide the response effort and minimize the health and economic costs of the epidemic. New knowledge regarding transmission, the spectrum of disease caused by the virus, modeling key outcomes, and evaluating implementation and potential impact of containment and mitigation strategies will help improve the response to the epidemic. 

  The research agenda described in this brief article describes questions considered by China CDC to fill priority knowledge gaps in the short- and medium-term. The agenda is limited to the four domains. One assumption that we make is the impending availability of serology tests of evidence of infection. Other research domains – for example, development of treatments, vaccines and other preventive measures, development of new diagnostic tools, and searching for the origin and animal reservoir of the virus – are critically important, but not in the scope of this agenda. 

  We anticipate that academic institutions, centers for disease control and prevention at all levels, and other research organizations in China and the global public health community will conduct or participate inthese research efforts. We also anticipate that research organizations and international partners will help refine and improve this research agenda and update it as new knowledge is generated, and new evidence emerges [15]. As the national level CDC, China CDC is in a position to track research progress and facilitate sharing of results with the domestic and international scientific community, government, and key stakeholders in the 2019-nCoV response. 

  At this point, hospitalshavefirst-hand patient data and samples, CDCs havedisease reporting data and case and contact investigation data, and many academic institutions, NGOs, and other institutions have strong research capabilities and resources. Sincere, open, coordinated, and efficient collaborationamong all parties is essential to rapid and orderly advancement of research. The Chinese Center for Disease Control and Prevention is willing to promote the establishment of anurgent research consortium for nCoVepidemic response, to formulate and release high-quality, timely unified research protocols and research tools and promote opening to research partners materials and patient specimens that do not compromise privacy ordata sensitivity. Collaboratively, we can join forces to conduct rapid investigations and research and provide strong support for optimizing epidemic response strategies and patient management. 

    

  Acknowledgements   

     We thank Prof. Ben Cowling, Dr. Alexander James Millman, Dr. Chin-Kei Lee, Prof. Zunyou Wu, Prof. Huaqing Wang and Dr. Shengjie Laifor their valuable opinions in drafting this agenda. We thank Dr. Anna Du for her support in translation. We thank Dr. Qiru Su for providing her summary about modelling studies. 

    

  The Chinese version of this article has been published in the Chinese Journal of Epidemiology:  Chinese Journal of Epidemiology, 2020, 41(2)135-138. DOI:10.3760/cma.j.issn.0254-6450.2020.02.001 

    

  References 

  [1]        Tu W, Tang H, Chen F, et al. Epidemic Update and Risk Assessment of 2019 Novel Coronavirus — China, January 28, 2020[J]. China CDC Weekly, 2020: 1-4. 

  [2]        World Health Organizaiton.. Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus (2019-nCoV); https://www.who.int/news-room/detail/30-01-2020-statement-on-the-second-meeting-of-the-international-health-regulations-(2005)-emergency-committee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov). In, 2020. 

  [3]        Li Q, Guan X, Wu P, et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia[J]. N Engl J Med, 2020. 

  [4]        Munster VJ, Koopmans M, van Doremalen N, et al. A Novel Coronavirus Emerging in China - Key Questions for Impact Assessment[J]. N Engl J Med, 2020. 

  [5]        Wang C, Horby PW, Hayden FG, et al. A novel coronavirus outbreak of global health concern[J]. Lancet, 2020. 

  [6]        World Health Organizaiton. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/advice-for-public/myth-busters.  

  [7]        Paules CI, Marston HD, Fauci AS. Coronavirus Infections-More Than Just the Common Cold[J]. Jama, 2020. 

  [8]        Holshue ML, DeBolt C, Lindquist S, et al. First Case of 2019 Novel Coronavirus in the United States[J]. N Engl J Med, 2020. 

  [9]        Wu JT, Leung K, Leung GM. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study[J]. The Lancet, 2020. 

  [10]      Riou J, Althaus CL. Pattern of early human-to-human transmission of Wuhan 2019-nCoV[J]. bioRxiv, 2020: 2020.2001.2023.917351. 

  [11]      Zhao S, Lin Q, Ran J, et al. Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak[J]. bioRxiv, 2020: 2020.2001.2023.916395. 

  [12]      Liu T, Hu J, Kang M, et al. Transmission dynamics of 2019 novel coronavirus (2019-nCoV)[J]. bioRxiv, 2020: 2020.2001.2025.919787. 

  [13]      Read JM, Bridgen JRE, Cummings DAT, et al. Novel coronavirus 2019-nCoV—early estimation of epidemiological parameters and epidemic predictions[J]. medRxiv, 2020. 

  [14]      National Health Committee. Announcement of the National Health Committee of the People's Republic of China; http://www.nhc.gov.cn/jkj/s7916/202001/44a3b8245e8049d2837a4f27529cd386.shtml.  

  [15]      Heymann DL. Data sharing and outbreaks: best practice exemplified[J]. Lancet, 2020. 

 

 

  

  Box 1. Transmission 

  Q1    Breadth of virus spread 

  •  How far has the virus spread in human populations, including spread prior to the start of epidemic monitoring? 

  Q2    Transmissibility 

  •  What is the basic reproductive number (R0), effective reproductive ratio (Re), serial interval, generation time (Tg), and doubling time?  
  •  Have superspreaders been identified and what are the characteristics of superspreading events? Is it possible to identify those at high risk of being superspreaders? 
  •  Do temperature and humidity affect transmissibility? In what way? 

  Q3    Duration of infection and infectivity 

  •  How long does virus shedding last?  Does shedding precede onset of symptoms? If yes, how long before? Does shedding continue after recovery? If yes, for how long? 
  •  Are there differences in the duration of virus shedding in those with mild disease versus those with severe disease? How does clinical presentation (respiratory vs non-respiratory) relate to contagiousness? 
  •  Can infected person transmit virus during the incubation period transmit? How efficiently? 
  •  Can persons with mild (afebrile) infectiontransmit virus? How efficiently? 
  •  Can persons with asymptomatic infectiontransmit virus? How efficiently? 

  Q4    Routes of transmission 

  •  What are the types of respiratory, gastrointestinal, other body fluid secretions/excretions that are infectious? How infectious are they? 
  •  Where in the body and in what body fluids can infectious virus be found in infected people? 
  •  Is virus in blood? This would have implications for the safety of the blood supply. Is virus in blood inactivated by standard methods for blood preparation?  
  •  How does viral RNA detected by PCR correlate with infectious virus? 
  •  Does virus persist on surfaces? If yes, how long? 

  Q5    High risk occupations and behaviors 

  •  What occupations place people at higher risk of becoming infected? 
  •  What behaviors place people at higher risk of becoming infected? 

  Q6    Immunity 

  •   Does novel coronavirus infection lead to immunity and prevention of future infection? 
  •   Do some groups of individuals (e.g. children) have pre-existing immunity to infection, or protection against disease if infected? 

    

    

  Box 2. Clinical features 

  Q1    Clinical spectrum and course of disease 

  •  What proportion of infected individuals remain asymptomatic, have mild illness, have no fever, have serious illness, or die? 
  •  How does the spectrum of disease vary by population characteristics (for example, among children, adult, elderly, individuals with comorbid conditions, and pregnant women)? 
  •  What are the time intervals between symptom onset and testing, symptom onset and hospitalization, and symptom onset and death?  Does this vary by disease severity and geography? 
  •  Are there differences in clinical disease and outcomes in people with 2019-nCoV monoinfections versus coinfections with 2019-nCoV and another respiratory pathogen? 
  •  What are the causes of death among those with 2019-nCoV infections? 

  Q2    Severity and prognostic factors 

  •  How does risk of serious illness and death vary by clinical and sociodemographic characteristics of infected individuals? 
  •  How does the level of required medical support (e.g., hospitalization, respiratory support, intensive care) vary by syndrome and clinical condition?  
  •  What proportion of severe and critically ill patients have recovered? What proportion of patients requiring mechanical ventilation have recovered? 
  •  What proportion of deaths have occurred in previously healthy individuals?   
  •  Have any children or pregnant women developed severe disease?  If yes, what were the pregnancy outcomes of infected pregnant women? 
  •  Have any cases occurred in people living with HIV?  If yes, did they develop severe disease? 

  Q3    Case identification 

  •  What clinical features associated with infection lead to seeking testing for infection? 
  •  What proportion of infected individuals seek medical care? 
  •  Are there ways to identify some infected individuals who do not seek medical care? 

    

  Box 3. Prediction of epidemic trajectories and health care capacity needs 

  Q1    Model assumptions and parameters 

  •  What are model assumptions and parameters to which important model predictions (when will the epidemic peak, when will it be over, impact on healthcare system, and economic impact) are most sensitive?  
  •  Which model assumptions and parameters are high priorities for measuring with epidemiological and other studies? 

  Model parameters and assumptions may include: 

  1.Immunity resulting from infection 

  2.Duration of illness 

  3.Zoonotic source and reservoir that ongoing spillover to humans 

  4.Human population susceptibility 

  5.Transmissibility in various clinical states 

  6.Transmissionleading to infections, clinical cases, hospitalizations, deaths 

  Q2    Model prediction 

  •  What are counterfactual (no intervention) predictions for this epidemic?  

  1.What is the total number of infections, cases, quarantine need, isolation need, hospital admissions, patients need respiratory support, patients need intensive care, and deaths? 

  2.How high will the peak of the epidemic be in different locations?  

  3.How much time will it take to reach the peak in different locations? 

  4.What are the impacts on healthcare capacity? 

  •  What are the impacts of combinations of countermeasures (isolation, quarantine, social distancing strategies, population movement restriction strategies, personal protection, and screening)?  

  1.How high will the peak of the epidemic be in different locations?  

  2.How much time will it take to reach the peak in different locations?  

  3.What is the effectiveness of various public health control measures? Are certain control measures more suitable in some locations than others, for example urban areas versus rural areas?  

  4.What is the best timing (start time, stop time) of public health measures? 

  Q3    Model evaluation 

  •   How should mathematical models be evaluated for accuracy while they are being used? 
  •   What are reliable and timely signs that a mathematical model can provide valid predictions? 

    

  Box4. Monitoring and evaluation of strategies 

  Q1    What monitoring should be established or strengthened for this epidemic, and at what jurisdiction level?  

  •   Infection 

  1.Contact tracing of cases (including assessing how effectively contacts are being monitored and determine how many contacts become cases) 

  2.Serological monitoring of residual blood from routine laboratory testing to identify evidence of infection in the population, followed by investigation of positives to determine source 

  3.ILI, ARI and SARI surveillance for novel coronavirus infection monitoring 

  4.Routine, periodic sequencing of isolated viruses to determine evolution of virus, update PCR and other diagnostics 

  •   Compliance with strategies 

  1.Compliance with quarantine 

  2.Compliance with exit screening 

  3.Compliance with personal protection 

  •  Societal acceptability of interventions – degree of fatigue from mitigation strategies including quarantine, screening, person protection, social distancing interventions 

  Q2    Effectiveness evaluation 

  •  Is the containment strategy effective? When should we shift to mitigation strategy? 
  •  Is the mitigation strategy effective?  When can mitigation strategies be de-escalated? 
  •  Which countermeasure is most effective and with minimum economic cost? 

    

  附件1新型冠状病毒感染的肺炎疫情紧急研究议程:传播和非药物缓疫策略_中文版 

  附件2Urgent research agenda for the novel coronavirus epidemic transmission and non-pharmaceutical mitigation strategies_英文版 

    

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