This week, health informatics became a hot topic in the US as the responsibility for collecting COVID-19 case data shifted from the CDC to the US Department of Health and Human Services.

本周，健康信息学成为美国的热门话题，因为收集COVID-19病例数据的责任从CDC转移到了美国卫生与公共服务部 。

I have worked on health information system strengthening projects in other countries. In the past, I’ve been met with blank stares when talking about the importance of robust, interoperable information systems with friends (it’s not exactly cocktail party banter), but perhaps the focus on COVID-19 data can kick off these conversations around the range of processes and systems used to collect health information.

我曾在其他国家从事过加强健康信息系统的项目 。 过去，在与朋友谈论健壮的，可互操作的信息系统的重要性时，我一直茫然无措(这并不是鸡尾酒会上的开玩笑)，但也许对COVID-19数据的关注可以引发围绕这些话题的对话。用于收集健康信息的过程和系统的范围。

Despite the wide demand for daily case-count updates shared across hundreds of global, country, and local dashboards, the results you see today in some of the best-case scenarios are cases that were infected (and potentially infectious to others) days or even more than a week prior. When analyzing COVID-19 case data, we can better make sense of the noise in daily case counts or how new cases lag behind tests administered by understanding how the data is collected.

尽管对数百个全球，国家和本地仪表板共享每日病例计数更新有广泛的需求，但您今天在某些最佳情况下看到的结果仍是被感染(并可能对其他人感染)的病例，甚至是一个多星期前。 在分析COVID-19案例数据时，通过了解数据的收集方式，我们可以更好地理解日常案例计数中的噪音或新案例如何落后于所管理的测试。

In this essay, we’ll look at the data collection timeline and processes through a patient’s perspective and in journey maps from three testing sites around the world in the United States, Canada, and South Africa.

在本文中，我们将通过患者的角度以及来自美国，加拿大和南非的三个测试站点的旅程图，查看数据收集的时间表和过程。

从患者的角度 (From a Patient’s Perspective)

Let’s look at an illustrative timeline from a COVID-19 exposure to receiving a test result in Washington, DC in mid-June.

让我们看一下从COVID-19暴露到6月中旬在华盛顿特区接受测试结果的示例性时间表。

In late May, two different kinds of gatherings were widely discussed: (1) Memorial Day picnics brought together people in environments where wearing a mask and maintaining distance may be challenging, and (2) Black Lives Matter protests advocating for racial justice and equity grew in scope and scale by early June in the wake of the murder of George Floyd.

5月下旬，对两种不同类型的聚会进行了广泛讨论：(1)阵亡将士纪念日的野餐使人们聚集在戴着口罩和保持距离可能具有挑战性的环境中；(2) 提倡种族正义和公平的“黑人生活”抗议活动日渐增多乔治·弗洛伊德(George Floyd)被谋杀后，范围和规模在6月初开始。

Those who attended such gatherings were advised to seek a COVID-19 viral test 5–7 days after the event, after which they would wait for 3–5 days for results. DC significantly scaled up testing sites to meet demand, but even with those efforts many waited in long lines to be tested.

建议参加此类聚会的人在活动后5-7天进行COVID-19病毒检测，然后等待3-5天以获得结果。 DC极大地扩展了测试站点，以满足需求，但是即使做出了这些努力，许多人仍在排队等待测试。

New confirmed cases were logged on the day results were received — which, in this best case without further delays, meant test results logged on day 11 after initial exposure. This timeline leaves a window for further community spread unless the patient has been diligent about self quarantine.

在收到结果的当天就记录了新的确诊病例-在最好的情况下，没有进一步的延迟，这意味着测试结果在初次暴露后的第11天记录下来。 该时间线为社区进一步传播留出了一个窗口，除非患者对自我隔离进行了认真的检查。

In March, NPR wrote about why it takes so long to get COVID results back. While innovations like pooled sample testing can address issues of lab capacity, in many cases our fragmented information systems further complicate the speed of sharing information.

3月，NPR撰写了为何花这么长时间才能获得COVID结果的信息 。 虽然诸如合并样本测试之类的创新可以解决实验室容量的问题，但在许多情况下，我们分散的信息系统使共享信息的速度更加复杂。

As reports in the U.S. emerge of test results taking days or even more than a week, today’s “real-time” case counts represent tests from days past. With tests recommended 5–7 days after exposure, the patient is uninformed about their status in the critical 4–6 day window after exposure when viral load may peak. Staying home during that window is highly recommended to prevent possible community spread, even without a confirmed positive test result.

随着美国报告的测试结果需要花费几天甚至一周以上的时间，今天的“实时”病例数代表了过去几天的测试结果。 建议在暴露后5-7天进行测试，如果病毒载量可能达到峰值，则患者在暴露后4-6天的关键窗口中将不会了解自己的状态。 强烈建议您在该时段内呆在家里，以防止可能的社区传播，即使没有经过确认的阳性测试结果。

These testing timelines and information system nuances may feel overly technical, but any time we work with a data set as data visualization professionals, we should spend time interrogating and understanding how the data was collected.

这些测试时间轴和信息系统的细微差别可能会感觉过于技术化，但是任何时候我们作为数据可视化专业人员使用数据集时，都应该花时间询问和理解 如何收集数据 。

Data about COVID-19 is no exception — and even if we’re not creating charts and dashboards with this date, understanding how the data is collected can help us be more informed readers of charts and graphs about the pandemic.

关于COVID-19的数据也不例外-即使我们没有在这个日期之前创建图表和仪表板，了解数据的收集方式也可以帮助我们更全面地了解有关流行病的图表和图形。

如何收集COVID-19病例数据？ (How is COVID-19 case data collected?)

To understand how case data is collected, we need to understand what steps happen from the time when someone arrives for a viral test and when their result appears in a database. Who is involved? How many different systems does testing data touch? How many different opportunities are there for delays?

要了解如何收集病例数据，我们需要了解从有人到达进行病毒检测的时间以及他们的结果出现在数据库中之后的步骤。 谁参与其中？ 测试数据涉及多少个不同的系统？ 有多少种不同的延误机会？

To answer these questions, I interviewed three public health experts involved in COVID-19 testing and reporting to learn about the data collection process in early May. I spoke to experts in locations across three different countries to learn about the differences in how the process works in countries with highly decentralized public health information systems (the United States), primarily provincial public health information systems (Canada), and national health information systems (South Africa).

为了回答这些问题，我采访了三名参与COVID-19测试和报告的公共卫生专家，以了解五月初的数据收集过程。 我与三个不同国家/地区的专家进行了交谈，以了解该流程在高度分散的公共卫生信息系统(美国)，主要是省级公共卫生信息系统(加拿大)和国家卫生信息系统的国家/地区中的工作方式的差异。 (南非)。

The information gathered represents illustrative information flows for each location based on one key informant interview, and should not be generalized as representing all sites throughout the given country, state, or province. Many people, policies, and technology innovations can impact the processes and timelines. Even from the time of these conversations two months ago to the current state of affairs today, processes and timelines have likely changed.

所收集的信息表示基于一次关键信息提供者访谈的每个位置的说明性信息流，并且不应被概括为代表整个给定国家，州或省的所有站点。 许多人员，政策和技术创新都会影响流程和时间表。 即使从两个月前进行这些对话时到今天的当前状态，流程和时间表也可能已经改变。

Instead of providing generalizable processes, these journey maps give us a glimpse into the work that public health, medical, and laboratory professionals do daily to track the spread of COVID-19, and a better understanding of why the COVID-19 case data can be so messy.

这些历程图没有提供一般化的过程，而是让我们瞥见了公共卫生，医学和实验室专业人员每天在跟踪COVID-19的传播情况下所做的工作，并更好地理解了为什么可以使用COVID-19病例数据好乱

关于旅程地图 (About the Journey Maps)

The phases of collecting COVID-19 case data are similar across locations: (1) test swab taken, (2) laboratory processes run, and (3) data making its way into a central database that reports into national systems.

跨位置收集COVID-19病例数据的阶段是相似的：(1)进行了拭子采集，(2)运行了实验室流程，(3)数据进入了向国家系统报告的中央数据库。

Within those phases, the complexity of the process and the number of people and platforms involved varies across counties, states/provinces, and countries.

在这些阶段中，流程的复杂性以及涉及的人员和平台的数量在各县，州/省和国家之间有所不同。

You may be surprised to see words like “spreadsheet” and “fax,” but the reality is that many public health information systems still rely on these technologies and have significant reliance on public health, laboratory, and medical professionals for data entry and transmission.

您可能会惊讶地看到诸如“电子表格”和“传真”之类的词，但现实情况是，许多公共卫生信息系统仍依赖这些技术，并且非常依赖公共卫生，实验室和医疗专业人员进行数据输入和传输。

The journey maps reflect the process for late April and early May, approximately three months after the first cases were confirmed in the U.S. and Canada and less than two months from the first case in South Africa.

旅程图反映了4月下旬和5月初的过程，大约在美国和加拿大确诊第一例病例后三个月，而距南非第一例病例不到两个月。

Interviews were conducted through a convenience sample, focused on individuals I knew who were working on the response. Note that in the early days and weeks, these processes were far less efficient as testing and data capture processes were put into place, and over the last two months since the interviews were conducted, the processes and timelines may have evolved.

访谈是通过方便样本进行的，重点是我认识的从事响应工作的人员。 请注意，在开始的几天和几周里，这些过程的效率远不如测试和数据捕获过程到位，并且自进行访谈以来的最后两个月中，过程和时间表可能有所变化。

The number of days to render lab results or notify a patient can vary significantly based on test volume, so timing estimates are presented in the illustrations only when the duration was somewhat consistent at the end of April.

呈现实验室结果或通知患者的天数可能会因测试量的不同而有很大差异，因此，只有在4月底持续时间一定程度上保持一致的情况下，插图中才会显示时间估计。

美国伊利诺伊州罗克福德 (Rockford, Illinois, United States of America)

Population: 282,572 (2019 estimate, US Census Bureau)

人口 ：282,572(2019年估计， 美国人口普查局 )

Key attributes: Rockford, IL is located in Winnebago County, on the border of Illinois and Wisconsin, and had two drive through testing sites as of early May. The city is around 90 miles northwest of Chicago.

主要属性 ：伊利诺伊州罗克福德位于伊利诺伊州和威斯康星州的边界的温尼巴哥县，截至5月初，有两次开车经过测试地点。 该市位于芝加哥西北约90英里处。

Background: In the U.S., the health information systems are highly decentralized, managed at the county and state level. The decentralized systems are one reason compiling and comparing data across US states can be challenging. While the U.S. has a robust system for influenza surveillance, a National Notifiable Disease Surveillance System that is undergoing a multi-year modernization, and has seen widespread adoption of electronic medical records, we still operate with many information silos.

背景：在美国，健康信息系统高度分散，在县和州一级进行管理。 分散系统是在美国各州进行数据汇编和比较可能具有挑战性的原因之一。 尽管美国拥有强大的流感监测系统，但美国国家法定疾病监视系统正在经历多年的现代化，并已广泛采用电子病历，但我们仍在处理许多信息孤岛。

The Auburn High School drive-through testing site operated by Crusader Clinic was set up under the direction of the state governor. A second testing site, at the UIC School of Medicine, was the first in Rockford, and is staffed by the National Guard. The journey map here represents the Auburn High School drive through site.

在州长的领导下，建立了由Crusader诊所运营的Auburn高中直通测试站点。 UIC医学院的第二个测试站点是洛克福德的第一个测试站点，由国民警卫队负责。 此处的旅程图代表了奥本高中的整个站点行驶。

Notable nuances: In May, approximately half of the patients being tested at the testing site were residents from other states. Many came from Wisconsin, who cross the state border daily for work and would come on their lunch break for testing. For patients with an out of state address, the test results need to be manually shared with the county of residence for the purpose of contact tracing and follow up, which adds additional steps to the data collection and reporting process.

值得注意的细微差别： 5月，在测试地点接受测试的患者中约有一半是来自其他州的居民。 许多人来自威斯康星州，威斯康星州每天都越过边界从事工作，他们会在午休时间进行测试。 对于州外地址的患者，需要与居住县手动共享测试结果，以进行联系人追踪和跟进，这为数据收集和报告过程增加了其他步骤。

As of early May 2020, the team was conducting 1,100 tests per week. As noted in the journey map, samples are not tested locally and instead are sent to a lab in Springfield daily. Samples include label with unique patient identifiers but are not barcoded. When the site first opened, it took 10 days to get a result from the state lab. By early May, the time had been reduced to two to three days, but can vary depending on lab capacity.

截至2020年5月，该团队每周进行1100次测试。 正如旅程地图中指出的那样，样品不会在本地进行测试，而是每天发送到位于斯普林菲尔德的实验室。 样品包括带有唯一患者识别符的标签，但没有条形码。 该站点首次打开时，花了10天时间从状态实验室获得结果。 到五月初，时间已减少到两到三天，但可以根据实验室的容量而有所不同。

加拿大安大略省金斯敦 (Kingston, Ontario, Canada)

Population: 117,660 (2016 Census, Statistics Canada)

人口 ：117,660(2016年人口普查， 加拿大统计局 )

Key attributes: Kingston has one of the largest prison populations in the province, but at the time of the interview had not had a large outbreak within the prison. In late June, two correctional officers tested positive, but rapid contact tracing and isolation helped minimize the risk to the wider prison population. In addition, the city has a large university.

重要属性 ：金斯敦(Kingston)是该省监狱人口最多的监狱之一，但在接受采访时，监狱内并未发生大的疫情。 6月下旬， 两名惩教人员测试为阳性 ，但是快速的接触者追踪和隔离帮助最大程度地降低了更多囚犯的风险。 此外，城市还有一所大型大学。

Background: In Canada, COVID-19 was added as a reportable disease in January 2020 and added to iPHIS, a health information reporting system created after the SARS outbreak in 2003.

背景：在加拿大，COVID-19于2020年1月被添加为可报告的疾病，并被添加到iPHIS中，iPHIS是在2003年SARS爆发后创建的健康信息报告系统。

“SARS fundamentally changed how we do public health in Canada,” said Allison Maier MPH. Toronto had the one of the largest SARS case counts in the world outside of Hong Kong. Following the SARS outbreak, the Public Health Agency of Canada was created, including the PHAC National Laboratory in Winnipeg, concentrating public health leadership at the provincial level.

“ SARS从根本上改变了我们在加拿大进行公共卫生的方式，”艾里森·迈尔(Allison Maier)MPH说。 多伦多是香港以外全球最大的SARS病例数之一。 SARS爆发后 ，加拿大公共卫生局成立，包括温尼伯的PHAC国家实验室，将公共卫生领导力集中在省一级。

As a result, Canada operates with 13 separate health care systems, one for each province. The Federal government leads care related to the Military and Indigenous populations. The iPHIS platform is used as the infectious disease information system for all reportable diseases across provinces, and works well for case management and as a centralized source of all cases and exposures, but not for contact tracing, which remains a primarily paper based exercise.

结果，加拿大运营着13个独立的卫生保健系统，每个省一个。 联邦政府领导与军事和原住民有关的护理。 iPHIS平台可以用作跨省所有可报告疾病的传染病信息系统，并且可以很好地用于病例管理，并且可以作为所有病例和暴露的集中来源，但不适用于接触者追踪，后者仍然主要是基于纸张的练习。

At the beginning of the COVID-19 response, from January to March, all samples were tested at the National Laboratory in Winnipeg. Ontario and then British Columbia were the first allowed to run the tests at the provincial level, increasing laboratory capacity.

从一月到三月的COVID-19响应开始时，所有样品都在温尼伯国家实验室进行了测试。 安大略省，然后是不列颠哥伦比亚省，首先被允许在省一级进行测试，从而提高了实验室的能力。

Notable nuances: In Kingston, a key to their success in collecting quality data was a training nurse who has used iPHIS for over a decade and is passionate about data quality. People, not technology, were critical to early success in collecting and reporting timely, accurate, complete data. The public health officials also partnered closely with the paramedics, and worked to manage personal protective equipment consistently.

值得注意的细微差别：在金斯敦，成功收集质量数据的关键是一名培训护士，他使用iPHIS已有十多年，并对数据质量充满热情。 对于早期成功收集和报告及时，准确，完整的数据至关重要的是人员而不是技术。 公共卫生官员还与医护人员紧密合作，并致力于统一管理个人防护设备。

Testing criteria in Canada limited who could be tested from January to March in the early days of the pandemic. This same challenge is felt across countries looking to understand the initial spread of infection, as availability of test kits was limited. In early April, Canada expanded the criteria for who could be tested to include behavioral exposures, including health care workers, long term care facility or similar, close contact with a case, travel risk.

加拿大的检测标准限制了在大流行初期从一月到三月可以接受检测的人员。 各国都希望了解感染的最初传播情况，因此面临同样的挑战，因为检测试剂盒的可用性有限。 在4月初，加拿大扩大了对谁可以接受测试的标准，包括行为暴露，包括医护人员，长期护理机构或类似人员，与案件密切接触，旅行风险。

南非豪登省 (Gauteng Province, South Africa)

Population: 15.2 million (2019 estimates, Statistics South Africa)

人口 ：1520万(2019年估计， 南非统计数据 )

Key attributes: Gauteng is the most populous province in South Africa, home to both Johannesburg, the commercial hub, and Pretoria, the national capital.

关键属性 ： 豪登省是南非人口最多的省份，既是约翰内斯堡(商业中心)和国家首都比勒陀利亚的故乡。

Background: In South Africa, COVID-19 case data is collected and managed through a mobile application integrated with the national health information system. The timeline from a community health worker arriving on your doorstep to having a test result in a national database was reported to be less than 48 hours. In countries like the US with more fragmented, siloed systems, information moves through more manual flows.

背景 ：在南非，通过与国家卫生信息系统集成的移动应用程序收集和管理COVID-19病例数据。 据报道，从社区卫生工作人员到您家门口到在国家数据库中获得测试结果的时间不到48小时。 在像美国这样具有零散，孤立的系统的国家，信息通过更多的手动流程传播。

The mobile data collection application is built on top of the DHIS2 COVID-19 Surveillance Digital Data package, which has also been adapted and deployed in 27 other countries (with 22 other countries in development). DHIS2 is also the open source information system platform used for managing routine health information and has been adapted for other disease specific purposes.

该移动数据收集应用程序建立在DHIS2 COVID-19监视数字数据包的基础上 ，该包也已在其他27个国家(正在开发的22个国家中)进行了改编和部署。 DHIS2还是用于管理常规健康信息的开源信息系统平台，并已针对其他疾病特定目的进行了调整。

Notable nuances: Investments in the National Health Information System support rapid response through technology. Having a DHIS2 system in place before COVID-19 created an enabling environment for digital data capture.

值得注意的细微差别：对国家卫生信息系统的投资支持通过技术进行快速响应。 在COVID-19之前安装DHIS2系统为数字数据捕获创造了一个有利的环境。

In South Africa, the COVID-19 response focuses on testing in hotspots across the country and community outreach. Gauteng had done more tests than any other province at the time of the interview, but the largest hotspots as of early May were in the Western Cape Province, where Cape Town is located. As of July 17, Gauteng province — the commercial and government center of the country — has the highest case count, recently surpassing Western Cape.

在南非，COVID-19响应的重点是在全国各地的热点和社区范围内进行测试。 采访时，豪登省比其他任何省份都进行了更多的测试，但是截至5月初，最大的热点是开普敦所在的西开普省。 截至7月17日，豪登省-该国的商业和政府中心- 案件数量最高 ，最近超过了西开普省。

The response relies heavily on outreach through community health workers, who are a critical part of the health systems in many countries. In the face of COVID-19, community health worker corps can help countries with less resilient health systems rapidly test and trace infected persons’ contacts. You can learn more about the response in South Africa in the DVS Viz Responsibly interview with Yazabantu Soldati.

应对措施在很大程度上取决于通过社区卫生工作者进行的外联活动，这是许多国家卫生系统的重要组成部分。 面对COVID-19， 社区卫生工作者团队可以帮助卫生系统缺乏弹性的国家快速测试和追踪感染者的联系。 您可以在DVS Viz负责任的Yazabantu Soldati访谈中了解有关南非的回应的更多信息。

从映射这些数据收集过程中我们可以学到什么？ (What can we learn from mapping these data collection processes?)

The variance in information systems even across these three examples is striking. In 2006, Larry Brilliant — who had been on the front lines of the small pox eradication — stepped onto the TED stage and shared a vision for how timely reporting of case data about a new disease could stop a pandemic.

即使在这三个示例中，信息系统的差异也是惊人的。 2006年，曾在根除天花的第一线的拉里·布里里安蒂(Larry Brilliant )登上TED舞台 ，并对如何及时报告有关新疾病的病例数据可以阻止大流行病抱有共同的愿景。

Some of that dream has been realized where there are centralized digital public health information systems: South Africa deployed a mobile application for case management in less than two months. Global disease surveillance systems have been built by WHO. But when the United States — the country with the leading case count globally — has major data delays and information silos, that hampers the timeliness and completeness of information about the pandemic.

实现集中数字公共卫生信息系统的梦想已经实现：南非在不到两个月的时间内部署了用于案件管理的移动应用程序。 世卫组织已经建立了全球疾病监测系统 。 但是，当美国(全球病例数最多的国家)发生重大数据延迟和信息孤岛时，就会影响有关大流行的信息的及时性和完整性。

Three journey maps from a convenience sample don’t define a generalizable process, which would require many more interviews and follow-ups over time. But the illustrations can help us better understand how COVID-19 case data is collected, with a glimpse into the many people and information systems are involved.

三个旅程从便利样本映射没有定义普及的过程，这将需要更多的采访和后续一段时间。 但是这些插图可以帮助我们更好地了解如何收集COVID-19案例数据，并可以一窥涉及的许多人员和信息系统。

Understanding who is involved hopefully engenders greater empathy and understanding for the people — the community health workers, public health professionals, lab workers, transporters, and others — who facilitate the process of gathering this information.

了解谁参与其中有望为人们带来更多的同情和谅解，他们促进了收集信息的过程，这些人是社区卫生工作者，公共卫生专业人员，实验室工作人员，运输人员和其他人员。

当您监视有关COVID-19案例的仪表板和新闻时，请记住： (As you monitor dashboards and news about COVID-19 cases, remember:)

• Real time case counts lag behind the current number of infected persons, due to the delays between exposure, onset of symptoms (if any), being tested, and receiving test results. This lag is in addition to the reality that case counts are a function of how many tests are done, which is why metrics like test positivity give us important information on if we’re testing enough people. Minimizing those gaps where possible and creating efficiencies gets us closer to real time information. The best thing to do as an individual is to continue to take preventive measures after any exposure risk: stay home, practice physical distancing if out of the house, washing your hands, and wearing a mask.

  由于暴露，症状发作(如果有)，被测试与接收测试结果之间的延迟，实时病例计数落后于当前感染人数 。 这种滞后是对事实的补充，即案例计数是完成多少测试的函数，这就是为什么诸如测试阳性之类的指标为我们提供了有关是否测试足够人的重要信息的原因。 尽可能缩小这些差距并提高效率，使我们更接近实时信息。 作为个人，最好的做法是在有任何暴露风险后继续采取预防措施：呆在家里，离开家时要与身体保持距离，洗手并戴口罩。

• Differences in how data is collected can create challenges when comparing outbreaks in different locations, including across states or provinces within a country. In the US, at the time of writing this article, self-reported lag times between having a sample taken varied from less than 24 hours to 14 days. Quest Diagnostics, a leading provider of COVID-19 tests, reported a 7+ day wait for test results unless the person is considered a priority patient. This is one reason why rolling 7 day averages may give more comparable trajectories of COVID-19 than daily case counts.

  在比较不同地区 (包括一个国家的州或省)的疫情爆发时，数据收集方式的差异可能会带来挑战 。 在美国，在撰写本文时， 自我报告的采样间隔时间从不到24小时到14天不等。 领先于COVID-19测试的提供商Quest Diagnostics 报告称，除非该人被视为优先患者，否则等待7天以上才能获得测试结果 。 这就是为什么连续7天平均计算的COVID-19轨迹比每日病例数更可比的原因之一。

• Many public health informatics systems rely on a range of different platforms and tools, as illustrated in these journey maps. How people use the tools and manage the processes impacts the timeliness of the data. Manual data capture and transfer processes also introduce opportunities for data quality issues.Understanding what happens before the case counts appear on COVID Act Now or in the New York Times repository can help us ask better questions of the data.

  如这些旅程图所示，许多公共卫生信息系统依赖于各种不同的平台和工具。 人们如何使用工具和管理流程会影响数据的及时性。 手动数据捕获和传输过程也带来了数据质量问题的机会。了解在案件计数出现在COVID Act Now或《纽约时报》存储库中之前发生的情况，可以帮助我们提出更好的数据问题。

The data is still valuable — lagging data is certainly better than no data at all as we work to combat this pandemic. COVID-19 and the need for rapid information is one of the greatest cases we could make for investments in robust health informatics systems to remove many of the manual steps in sharing data on reportable diseases in many countries, including the United States.

数据仍然很有价值-在我们努力应对这种大流行的过程中，滞后数据肯定比没有数据要好。 COVID-19和对快速信息的需求是我们可以投资于强大的健康信息系统的最大案例之一，从而消除了许多国家(包括美国)共享可报告疾病数据的许多手动步骤。

Amanda Makulec is the Senior Data Visualization Lead at Excella and holds a Masters of Public Health from the Boston University School of Public Health. She worked with data in global health programs for eight years before joining Excella, where she leads teams and develops user-centered data visualization products for federal, non-profit, and private sector clients. Amanda volunteers as the Operations Director for the Data Visualization Society and is a co-organizer for Data Visualization DC. Find her on Twitter at @abmakulec

Amanda Makulec 是 Excella 的高级数据可视化负责 人 ，拥有波士顿大学公共卫生学院的公共卫生硕士学位。 在加入Excella之前，她曾在全球卫生计划中处理数据八年，在那里她领导团队并为联邦，非营利和私营部门客户开发以用户为中心的数据可视化产品。 Amanda自愿担任数据可视化协会的运营总监，并且是 数据可视化DC 的联合组织者 。 在 @abmakulec的 Twitter上找到她

Katherine Haugh is an evaluator and graphic recorder based in Washington, DC.

凯瑟琳·哈夫 ( Katherine Haugh) 是华盛顿特区的评估员和图形记录员。