Powerful engineering tools should help in the fight against nCoV-2109,

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【原文翻译】
Powerful engineering tools should help in the fight against CoV-2109, but we must start by acknowledging some limitations.
强大的工程工具应该有助于打击新冠肺炎，但我们必须首先承认一些限制。
The rest of this series will look at how digital technology applies to the the outbreak of a novel Coronavirus (nCoV-2019) in China. How is engineering being deployed to help medical professionals combat its spread there and in the rest of the world?
本系列的其余部分将介绍数字技术如何应用于在中国爆发的新冠肺炎。如何部署工程来帮助医疗专业人员对抗它在那里和世界其他地方的传播？
But as coverage and understandable public interest – and concern – about the outbreak has intensified, it seems wise first to look at how the event is exposing some of technology’s limitations both in and of itself and how we interpret what it can do for us.
但是，随着对疫情的报道和公众可理解的兴趣以及担忧的加剧，首先看看这一事件如何暴露了某些技术本身的局限性，以及我们如何解释它能为我们做些什么，似乎是明智的。
Three themes emerge.
出现了三个主题。
Technology is not immediate. There is a tendency to believe that the recent rapid advances in processing power, algorithmic development, machine learning and artificial intelligence can now deliver almost instant answers to everything. The digital landscape has changed massively since the SARS outbreak in 2003. But while we may be able to do things more efficiently, some things still take time and that is particularly true of a virus. There is no ‘one size fits all’ here and, indeed, there are real dangers in believing that one analytical strategy and its particular use can be applied universally.

技术不是立竿见影的。有一种趋势认为，最近在处理能力、算法开发、机器学习和人工智能等方面的快速发展，现在几乎可以为任何事情提供即时的答案。自2003年非典爆发以来，数字领域发生了巨大变化。但是，虽然我们可以更有效地做一些事情，但有些事情仍然需要时间，尤其是病毒。这里没有“一刀切”的说法，而且，事实上，相信一种分析战略及其特殊用途能够得到普遍应用确实存在危险。

Second, as viruses spread and evolve, so do the data sets around them. We are not dealing with a situation of simple ‘garbage in, garbage out’ but rather one where new information is emerging daily (and there is the further complication that there were delays in early reporting of the outbreak). That means that the results even the wisest medical experts can produce are also going to change. Also, as you might imagine, their methodologies vary.
其次，随着病毒的传播和进化，它们周围的数据集也会随之变化。我们处理的不是一个简单的“垃圾输入，垃圾输出”的情况，而是每天都有新的信息出现的情况（还有一个更复杂的问题，就是疫情的早期报告出现了延误）。这意味着，即使是最聪明的医学专家所能得出的结果也将发生变化。而且，正如您可能想象的那样，它们的方法也各不相同。

Third, a lot of data is being placed into the digital sphere, across social media, specialist sites and elsewhere. Here, the comparison with 17 years ago is especially profound. But the intentions behind various postings are many. Anyone might be able to access the data via a web browser – and its free availability is laudable – but its intended audiences can be very different. In some cases, experts are looking to inform the public but in others they are looking to contribute to and stimulate the debate taking place among themselves. These goals are laudable and necessary, but they do not always coexist harmoniously.
第三，大量数据正被放到数字领域，包括社交媒体、专业网站和其他领域。在这里，与17年前的对比尤其深刻。但各种帖子背后的意图是多方面的。任何人都可以通过网络浏览器访问数据，而且它的免费可用性是值得称赞的，但是它的目标受众可能会非常不同。在某些情况下，专家们希望向公众提供信息，但在另一些情况下，他们则希望为自己之间正在进行的辩论作出贡献和促进。这些目标是值得称赞和必要的，但它们并不总是和谐共存。