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[#]: collector: (lujun9972)
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[#]: translator: (HankChow)
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[#]: reviewer: ( )
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[#]: publisher: ( )
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[#]: url: ( )
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[#]: subject: (How open source software is fighting COVID-19)
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[#]: via: (https://opensource.com/article/20/3/open-source-software-covid19)
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[#]: author: (Jeff Stern https://opensource.com/users/jeffstern)
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How open source software is fighting COVID-19
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======
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Learn about four of the thousands of open source projects combating the
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spread of coronavirus.
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![symbols showing healthcare][1]
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Work is hard right now. COVID-19 makes it a challenge to stay focused and motivated. But it was cathartic for me to do some research into how the open source community is responding to the global pandemic.
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Since the end of January, the community has contributed to [thousands of open source repositories][2] that mention coronavirus or COVID-19. These repositories consist of datasets, models, visualizations, web and mobile applications, and more, and the majority are written in JavaScript and Python.
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Previously, we shared information about several [open hardware makers helping][3] to stop the spread and suffering caused by the coronavirus. Here, we're sharing four (of many) examples of how the open source software community is responding to coronavirus and COVID-19, with the goal of celebrating the creators and the overall impact the open source community is making on the world right now.
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### 1\. CHIME by PennSignals
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![CHIME by PennSignals][4]
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COVID-19 Hospital Impact Model for Epidemics ([CHIME][5]) is an open source application built by data scientists at Penn Medicine at the University of Pennsylvania. The online tool allows hospitals to better understand the impact the virus will have on hospital demand.
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Hospital leaders can use CHIME to "get more informed estimates of how many patients will need hospitalization, ICU beds, and mechanical ventilation over the coming days and weeks." A user can input how many patients are currently hospitalized and see, based on other variables, how demand might increase over the coming days.
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CHIME is primarily built with Python and uses the [pandas][6] open source dependency for much of the underlying data-transformation number-crunching to generate the estimates. Pandas has a relatively robust team and is one of the most commonly used Python libraries for data analysis and, like all open source projects, is highly dependent on [users' support][7] for income.
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### 2\. Real-time COVID-19 visualization by Locale.ai
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![Locale.ai COVID-19 visualization][8]
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Maps that track the number of cases help us visualize the relative scale and spread of COVID-19. [Locale.ai created an open source, interactive visualization][9] of all known cases of COVID-19. The map provides live updates with new data as it becomes available.
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I find this project especially interesting because the data is retrieved via [an open source API][9] created by GitHub user ExpDev07 that queries [an open source dataset][10] from John Hopkins University. The John Hopkins dataset (an aggregate of more than a dozen other sources) is currently the most popular COVID19-related project on GitHub. This is the branching nature of open source at its finest!
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Locale.ai built the visualization website using [Vue.js][11], a popular framework that allows web developers to create modern web apps. Vue.js was created and continues to be maintained by [Evan You][12], one of the few people who have made a full-time career as an open source maintainer.
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### 3\. DXY-COVID-19-Crawler by BlankerL
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![BlankerL DXY-COVID-19-Crawler][13]
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[DXY-COVID-19-Crawler][14] was created in January and is one of the earliest responses from the open source community to COVID-19. When the virus was spreading primarily in China, the Chinese medical community was using a site called [DXY.cn][15] to report and track cases. To make the information more readily available and usable by others, GitHub user BlankerL wrote a web crawler to systematically collect data from the DXY.cn site and make it available via an API and data warehouse. That data has been used by academic researchers and others to examine trends and visualize the spread of the virus. So far, DXY-COVID-19-Crawler has been starred more than 1,300 times and forked nearly 300 times.
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BlankerL wrote the web crawler using Python and a package called [Beautiful Soup][16]. Beautiful Soup is an application that allows Python developers to easily scrape information from websites. Beautiful Soup is maintained by Leonard Richardson, who also works full-time as a software architect.
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### 4\. City of Tokyo's COVID-19 task force website
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![City of Tokyo's COVID-19 Task Force site][17]
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Many cities around the world have updated their websites with information for their residents about COVID-19. The Tokyo Metropolitan Government created a [comprehensive website][18] that "aims to allow Tokyo residents, companies with offices in Tokyo, and visitors to Tokyo to grasp the current situation and take measures and precautions accordingly."
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Unlike many other cities, Tokyo decided to [open source its site][19]. The project boasts contributions by more than 180 different users, and [at least three other cities][20] in Japan (Nagano, Chiba, and Fukuoka City) remixed the site. The project is an example of how cities can better serve their citizens by building openly.
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There's an incredible amount of open source technology powering Tokyo's open source website. Using the [Tidelift][21] application, I identified 1,365 dependencies used in the project. All of this complexity happens because 38 direct dependencies (i.e., dependencies the developers explicitly decided to use) have dependencies of their own. That said, maintainers of more than a thousand different open source dependencies (including [Nuxt.js][22], [Prettier][23], [Babel][24], [Ajv][25], and more) are in a small way responsible for helping Tokyo share information with their citizens.
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![Dependencies in Tokyo's COVID-19 Task Force site][26]
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### Other projects
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There are [many other important projects][27] being built in the open in response to COVID-19. I am inspired by how the open source community is responding to this pandemic and leveraging other open source technologies to work quickly. The weeks ahead will be difficult, but I know we can continue to find motivation in the open source community.
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If you are working on an open source project related to COVID-19, please share it in the comments so we can help spread the word.
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--------------------------------------------------------------------------------
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via: https://opensource.com/article/20/3/open-source-software-covid19
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作者：[Jeff Stern][a]
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选题：[lujun9972][b]
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译者：[译者ID](https://github.com/译者ID)
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校对：[校对者ID](https://github.com/校对者ID)
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本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
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[a]: https://opensource.com/users/jeffstern
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[b]: https://github.com/lujun9972
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[1]: https://opensource.com/sites/default/files/styles/image-full-size/public/lead-images/Medical%20costs.jpg?itok=ke57j6cs (symbols showing healthcare)
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[2]: https://github.com/search?q=coronavirus+OR+covid19
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[3]: https://opensource.com/article/20/3/open-hardware-covid19
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[4]: https://opensource.com/sites/default/files/uploads/chime_pennsignals.png (CHIME by PennSignals)
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[5]: http://penn-chime.phl.io/
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[6]: https://tidelift.com/subscription/pkg/pypi-pandas
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[7]: https://pandas.pydata.org/about/sponsors.html
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[8]: https://opensource.com/sites/default/files/uploads/locale-ai-visualization.png (Locale.ai COVID-19 visualization)
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[9]: https://github.com/localeai/covid19-live-visualization
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[10]: https://github.com/CSSEGISandData/COVID-19
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[11]: https://tidelift.com/subscription/pkg/npm-vue
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[12]: https://blog.tidelift.com/vuejs-evan-you-javascript-framework
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[13]: https://opensource.com/sites/default/files/uploads/dxy-covid-19-crawler.png (BlankerL DXY-COVID-19-Crawler)
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[14]: https://github.com/BlankerL/DXY-COVID-19-Crawler
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[15]: https://dxy.cn
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[16]: https://blog.tidelift.com/beautiful-soup-is-now-part-of-the-tidelift-subscription
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[17]: https://opensource.com/sites/default/files/uploads/tokyo-covid19-task-force.png (City of Tokyo's COVID-19 Task Force site)
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[18]: https://stopcovid19.metro.tokyo.lg.jp/en/
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[19]: https://github.com/tokyo-metropolitan-gov/covid19
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[20]: https://github.com/tokyo-metropolitan-gov/covid19/issues/1802
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[21]: https://tidelift.com/
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[22]: https://tidelift.com/subscription/pkg/npm-nuxt
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[23]: https://blog.tidelift.com/prettier-is-now-part-of-the-tidelift-subscriptions
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[24]: https://tidelift.com/subscription/pkg/npm-babel
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[25]: https://blog.tidelift.com/ajv-is-now-part-of-the-tidelift-subscription
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[26]: https://opensource.com/sites/default/files/uploads/tokyo-dependencies.png (Dependencies in Tokyo's COVID-19 Task Force site)
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[27]: https://github.com/soroushchehresa/awesome-coronavirus
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[#]: collector: (lujun9972)
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[#]: translator: (HankChow)
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[#]: reviewer: ( )
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[#]: publisher: ( )
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[#]: url: ( )
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[#]: subject: (How open source software is fighting COVID-19)
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[#]: via: (https://opensource.com/article/20/3/open-source-software-covid19)
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[#]: author: (Jeff Stern https://opensource.com/users/jeffstern)
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开源软件在应对 COVID-19 中的贡献
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======
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> 在新冠疫情爆发之际，涌现了数以千计的开源项目，今天我们来了解其中四个。
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![symbols showing healthcare][1]
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在当前紧张的疫情环境下，保持专注和积极性是一个很大的挑战。而研究开源社区如何应对这一次疫情爆发，对于我来说却成为了一种宣泄。
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从今年一月底开始，整个开源社区已经贡献了数以千计关于冠状病毒或 COVID-19 的[开源软件库][2]，其中涉及的内容包括但不限于数据集、模型、可视化、Web 应用、移动应用，且大多数都使用了 JavaScript 和 Python 编写。
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之前我们分享过一些关于开源硬件厂商在帮助遏制冠状病毒传播方面做的[贡献][3]，现在将继续分享四个由开源社区作出的应对冠状病毒和 COVID-19 的项目，这体现了开发者们和整个开源社区在当下对整个世界的影响力。
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### 1. PennSignals：CHIME
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![CHIME by PennSignals][4]
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<ruby>COVID-19 流行病医院影响模型<rt>COVID-19 Hospital Impact Model for Epidemics</rt></ruby>（[CHIME][5]）是由宾夕法尼亚大学 Penn Medicine 机构的数据科学家们建立的开源在线应用，它可以让医院更好地了解本次新型冠状病毒对医院需求的影响。
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医院的管理人员可以通过 CHIME 来大致预测未来几天和几周内将会有多少患者需要住院治疗，并推算 ICU 和呼吸机的需求量。只需要输入当前住院患者数以及一些相关的变量，就可以看到未来几天内需求的变化情况。
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CHIME 主要使用 Python 开发，并通过 [pandas][6] 这个开源库实现了大部分的数据转换和数值计算，最终得出相关的估计值。pandas 的背后有一个强大的团队进行支持，因此它是在数据分析方面被广泛使用的 Python 库之一。和很多其它的开源项目一样，pandas 团队的收入大部分来源于[用户的资金支持][7]。
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### 2. Locale.ai：Real-time COVID-19 visualization
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![Locale.ai COVID-19 visualization][8]
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实时显示世界各地病例数量分布的地图可以让我们直观了解 COVID-19 的规模和扩散程度。Locale.ai 就开发了这样一个开源、可交互的 [COVID-19 已知病例可视化分布图][9]，这个图会根据最新的可靠数据实时进行更新。
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这个项目有趣的地方在于，它的数据是是通过 GitHub 用户 ExpDev07 创建的[开源 API][10] 进行检索的，这个 API 的数据来源是[约翰·霍普金斯大学的开源数据集][11]，而约翰·霍普金斯大学这份聚合了多个来源的数据集则是 GitHub 上 COVID-19 相关的最受欢迎的项目。这就是开源项领域中分支带来的一大好处。
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Locale.ai 的这个图表通过 [Vue.js][11] 开发。Vue.js 是一个在 Web 应用开发方面非常流行的框架，它是由[尤雨溪][12]创造并维护的。值得一提的是，尤雨溪是全职参与开源项目维护的少数人之一。
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### 3. BlankerL：DXY-COVID-19-Crawler
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![BlankerL DXY-COVID-19-Crawler][13]
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[DXY-COVID-19-Crawler][14] 建立于今年 1 月份，是开源社区对 COVID-19 最早发起响应的项目之一。当时 COVID-19 主要在中国范围内传播，中国医学界通过[丁香园][15]网站来进行病例的报告和跟踪。为了使这些疫情信息具有更高的可读性和易用性，GitHub 用户 BlankerL 开发了一个爬虫，系统地从丁香园网站获取数据，并通过 API 和数据仓库的方式对外公开。这些数据也被学术研究人员用于研究病毒传播趋势和制作相关的可视化图表。到目前为止，DXY-COVID-19-Crawler 这个项目已经获得了超过 1300 个星标和近 300 次的复刻。
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BlankerL 使用 Python 和 [Beautiful Soup][16] 库开发了这个爬虫。Beautiful Soup 是 Python 开发者用于从页面 HTML DOM 中提取信息的库，它由 Leonard Richardson 维护，这位作者i你另外还全职担任软件架构师。
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### 4. 东京 COVID-19 工作组网站
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![City of Tokyo's COVID-19 Task Force site][17]
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世界各地很多城市都在网络上持续更新当地的 COVID-19 信息。东京都政府则为此创建了一个[综合性的网站][18]，让东京当地居民、在东京设有办事处的公司以及到东京的游客了解最新情况，并采取相应的预防措施。
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这个网站的不同之处在于它是由东京都政府[开源][19]的。这个项目受到了来自 180 多名用户的贡献，日本的[长野市、千叶市、福冈市][20]还对这个网站进行了改造。这个项目是城市公共建设更好地服务大众的有力示范。
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这个开源网站也使用了很多开源技术。通过 [Tidelift][21]，我留意到项目中存在了 1365 个依赖项，其中 38 个是由开发者直接使用的依赖项。也就是说，超过一千多个开源项目（包括 [Nuxt.js][22]、[Prettier][23]、[Babel][24]、[Ajv][25] 等等）都为东京向市民共享信息提供了帮助。
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![Dependencies in Tokyo's COVID-19 Task Force site][26]
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### 其它项目
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除此以外，还有很多[响应 COVID-19 的重要项目][27]正在公开进行当中。在这次研究中，开源社区应对流行病以及利用开源技术开展工作的方式让我深受启发。接下来的一段时间都是应对疫情的关键时期，我们也可以继续在开源社区中寻找到更大的动力。
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如果你也参与到了 COVID-19 相关的开源项目当中，欢迎在评论区分享。
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--------------------------------------------------------------------------------
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via: https://opensource.com/article/20/3/open-source-software-covid19
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作者：[Jeff Stern][a]
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选题：[lujun9972][b]
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译者：[HankChow](https://github.com/HankChow)
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校对：[校对者ID](https://github.com/校对者ID)
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本文由 [LCTT](https://github.com/LCTT/TranslateProject) 原创编译，[Linux中国](https://linux.cn/) 荣誉推出
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[a]: https://opensource.com/users/jeffstern
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[b]: https://github.com/lujun9972
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[1]: https://opensource.com/sites/default/files/styles/image-full-size/public/lead-images/Medical%20costs.jpg?itok=ke57j6cs (symbols showing healthcare)
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[2]: https://github.com/search?q=coronavirus+OR+covid19
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[3]: https://opensource.com/article/20/3/open-hardware-covid19
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[4]: https://opensource.com/sites/default/files/uploads/chime_pennsignals.png (CHIME by PennSignals)
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[5]: http://penn-chime.phl.io/
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[6]: https://tidelift.com/subscription/pkg/pypi-pandas
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[7]: https://pandas.pydata.org/about/sponsors.html
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[8]: https://opensource.com/sites/default/files/uploads/locale-ai-visualization.png (Locale.ai COVID-19 visualization)
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[9]: https://github.com/localeai/covid19-live-visualization
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[10]: https://github.com/CSSEGISandData/COVID-19
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[11]: https://tidelift.com/subscription/pkg/npm-vue
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[12]: https://blog.tidelift.com/vuejs-evan-you-javascript-framework
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[13]: https://opensource.com/sites/default/files/uploads/dxy-covid-19-crawler.png (BlankerL DXY-COVID-19-Crawler)
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[14]: https://github.com/BlankerL/DXY-COVID-19-Crawler
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[15]: https://dxy.cn
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[16]: https://blog.tidelift.com/beautiful-soup-is-now-part-of-the-tidelift-subscription
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[17]: https://opensource.com/sites/default/files/uploads/tokyo-covid19-task-force.png (City of Tokyo's COVID-19 Task Force site)
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[18]: https://stopcovid19.metro.tokyo.lg.jp/en/
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[19]: https://github.com/tokyo-metropolitan-gov/covid19
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[20]: https://github.com/tokyo-metropolitan-gov/covid19/issues/1802
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[21]: https://tidelift.com/
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[22]: https://tidelift.com/subscription/pkg/npm-nuxt
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[23]: https://blog.tidelift.com/prettier-is-now-part-of-the-tidelift-subscriptions
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[24]: https://tidelift.com/subscription/pkg/npm-babel
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[25]: https://blog.tidelift.com/ajv-is-now-part-of-the-tidelift-subscription
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[26]: https://opensource.com/sites/default/files/uploads/tokyo-dependencies.png (Dependencies in Tokyo's COVID-19 Task Force site)
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[27]: https://github.com/soroushchehresa/awesome-coronavirus
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