COVID-19, the infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has put to the test many sectors such as health, education, socioeconomic development, transport, trade and finance. Millions of people have been infected, hundreds of thousands have died, and the toll continues to soar. The international scientific community has found itself in a race against time to contain the spread of the disease, with an urgent need to devise fast screening and triage systems for early detection and isolation of affected patients. With advanced health-care technologies and prior experiences with many epidemics in the past, people were confident that the scientific community will lead them out of this crisis. However, what has become apparent is a sense of panic and amateurism of some healthcare authorities, and a lack of agreement among scientists and experts with sometimes conflicting recommendations from trusted research institutions. This will not be the last pandemic; the international scientific community must learn valuable lessons from it to be able to combat future disease outbreaks that could be more infectious and lethal than COVID-19. Over the past few months, we heard the voice of many key players in the global fight against this pandemic, including health professionals, crisis counselors, epidemiologists, medical scientists and immunologists. In this editorial, we aim to cast light on the crucial contribution of other players, working behind the scenes, including bioengineers, computer scientists and big data specialists. Their contribution is shaping the way the international community is going to stop this outbreak. This concerns promoting innovative solutions to the following four areas that are of paramount importance to current global interventions: (a) develop portable imaging systems that are fast and accurate for diagnostic and prognostic purposes, (b) create bespoke databases with robust and secure data-sharing protocols of patient-level COVID-19 metadata, (c) devise AI-powered tools that can process complex data and can make accurate and useful individualized data-driven predictions and (d) derive accurate models about the spread of pandemics, with the ultimate aim to generate useful forecasts about the effects of interventions. 1 | DEVELOP PORTABLE IMAGING SYSTEMS

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Covid-19 大流行：生物工程师、计算机科学家和大数据专家可以带来什么

COVID-19 是由严重急性呼吸系统综合症冠状病毒 2 (SARS-CoV-2) 引起的传染病，已对卫生、教育、社会经济发展、交通、贸易和金融等许多部门进行了考验。数百万人被感染，数十万人死亡，而且死亡人数继续飙升。国际科学界发现自己正在与时间赛跑以遏制疾病的传播，迫切需要设计快速筛查和分诊系统，以便及早发现和隔离受影响的患者。凭借先进的医疗保健技术和过去许多流行病的经验，人们相信科学界将带领他们走出这场危机。然而，显而易见的是一些医疗保健当局的恐慌和业余主义，科学家和专家之间缺乏共识，有时值得信赖的研究机构提出的建议相互矛盾。这不会是最后一次大流行；国际科学界必须从中吸取宝贵的经验教训，才能应对未来可能比 COVID-19 更具传染性和致命性的疾病爆发。在过去的几个月里，我们听到了全球抗击这一流行病的许多关键角色的声音，包括卫生专业人员、危机顾问、流行病学家、医学科学家和免疫学家。在这篇社论中，我们旨在阐明在幕后工作的其他参与者的重要贡献，包括生物工程师、计算机科学家和大数据专家。他们的贡献正在塑造国际社会阻止这次疫情爆发的方式。这涉及促进以下四个领域的创新解决方案，这些领域对当前的全球干预至关重要：（a）开发用于诊断和预后目的的快速准确的便携式成像系统，（b）创建具有强大和安全数据的定制数据库 -共享患者级 COVID-19 元数据的协议，(c) 设计人工智能驱动的工具，可以处理复杂的数据，并可以做出准确和有用的个性化数据驱动预测，以及 (d) 得出关于流行病传播的准确模型，最终目标是生成有关干预效果的有用预测。1 | 开发便携式成像系统 (a) 开发用于诊断和预后目的的快速、准确的便携式成像系统，(b) 创建具有强大且安全的患者级 COVID-19 元数据数据共享协议的定制数据库，(c) 设计人工智能驱动的工具，可以处理复杂的数据，并可以做出准确和有用的个性化数据驱动预测，并且 (d) 得出有关流行病传播的准确模型，最终目标是生成有关干预措施效果的有用预测。1 | 开发便携式成像系统 (a) 开发用于诊断和预后目的的快速、准确的便携式成像系统，(b) 创建具有强大且安全的患者级 COVID-19 元数据数据共享协议的定制数据库，(c) 设计人工智能驱动的工具，可以处理复杂的数据，并可以做出准确和有用的个性化数据驱动预测，并且 (d) 得出有关流行病传播的准确模型，最终目标是生成有关干预措施效果的有用预测。1 | 开发便携式成像系统 (c) 设计能够处理复杂数据并能够做出准确和有用的个性化数据驱动预测的人工智能工具；以及 (d) 推导出关于流行病传播的准确模型，最终目标是生成关于干预效果的有用预测. 1 | 开发便携式成像系统 (c) 设计能够处理复杂数据并能够做出准确和有用的个性化数据驱动预测的人工智能工具；以及 (d) 推导出关于流行病传播的准确模型，最终目标是生成关于干预效果的有用预测. 1 | 开发便携式成像系统