Project Management in the Time of Coronavirus

Peter Sun
1Point3Acres Worklog
8 min readApr 8, 2020


How a team that barely met before manages one of the first and most used real-time COVID-19 tracker in North America

Fig 1. Main page of the 1point3acres Coronavirus Tracker, as of 4/6/2020

Sometimes how smoothly a team works makes me forget how little we know each other outside work.

Two weeks into volunteering at one of the most used COVID-19 trackers in North America, I saw this Tweet that features an interview with someone apparently from our team. Not so apparent to me who this is, I screenshot the Tweet, threw it into our Slack and asked, “which of you champs is [name of the person interviewed]? I’ve never matched y’all’s real names and Slack profiles haha.”

Then the co-founder of the team, who I Slack on an hourly basis for data and social media replied, “yep it’s me.”

My jaw dropped. Apart from the fact that I became the entertainment of the day for the team (much needed when you monitor exponentially growing patient numbers), it really struck me just how far this team has gone solely on remote collaboration.

Apart from co-founders and several core team members, one of the most used non-government COVID-19 databases in North America is powered by a team of volunteers who have barely met each other in person, heard each other’s voices or seen each other’s faces. And this team of offline strangers continues to publish the latest numbers in real time, roll out new features responding to changing circumstances, and maintain a bilingual social media presence.

As many people are settling into working from home because of the outbreak, let me take you behind the scene to see the three key drivers of a team of remote volunteers passionate about fighting COVID-19.

Rules as a culture

When thinking of a distributed team of volunteers, many people imagine a loose organizational structure without much guidance and individual team members making independent and sometimes spontaneous decisions. Cases, fatalities, recoveries — series of numbers that change by the minute do require a high degree of self-determination in our team, but it might be surprising to some that this would not have been possible if not for the opposite: writing rules together, and sticking to them.

Imagine this. You were a new volunteer on the data team. You just made your second data entry.

Suddenly the total number of confirmed cases was shaved off by two digits. And case details went missing in all but one state. Before you could give yourself a pat on the back.

Oops. That’s what one volunteer on the data team recalled in the moment.

To her relief, the co-founders quickly stepped in with a blameless post-mortem approach: they not only helped her resolve the issue, but also encouraged her to share the take-aways from the hiccup with other teammates to prevent similar mistakes from happening again. From there, she and the fellow volunteers keyed in the first lines of what has become the several key guidelines that continue to help teammates new and old to help each other by replicating the best practices collective experience into individual workflows.

Pinned to the main Slack channels and Github, these guidelines were the first words I read when I joined in early March and continue to guide my work today. A new volunteer starts from the “beginner guide”, the onboarding doc where annotated screenshots, workflow charts and examples of common mistakes help him / her learn the basics of logging new cases. The volunteer then proceeds to a mini quiz to complete the smooth but rigorous onboarding process. After signing up for logging data for a specific state, the volunteer reads the corresponding section in the “difficult problem set” — a living runbooks co-edited by the team — and gets brought up to speed with the mini tutorials written by volunteers who were tasked with logging data for that state previously (“How not to panic when New York City, NY State and Governor Cuomo’s Twitter give you three different cases counts at three times during the same day?” would go here. With annotated screenshots).

Fig 2. A new volunteer is constantly engaged with the onboarding doc and living runbook, which consolidates the relevance of the guidelines and improves the experience of the volunteer

The key point — these documentations are not some long-forgotten rulebooks written by early members and left in the dust. Each of the three documentations evolves everyday with our understanding of the changing situation: a teammate added a section about spelling and punctuation when first released case information, another added a detailed guide on reconciling NY state data when the numbers exploded a few days back, and today a new section about responding on social media is added as our Twitter followers increased 10x in the past week. The relevance of these documents to everyone’s daily work makes people frequently refer to them to navigate hard problems, which in turn feeds a team culture where everyone understands and contributes to keeping documentations as updated as possible. The mutual ownership and respect from writing and adhering to these guidelines then grant each of us trust in dealing with the unknown together but independently.

Prototype as an approach

Volunteering at the COVID-19 tracker is also the first time I work in a team where the majority of my co-workers have a software development background. Apart from picking up GitHub basics, dare to throw out prototypes to questions no one has an answer for is the greatest lesson I thank my colleagues for.

What would be your first reaction if I asked you to manage the Twitter account of a real-time data service used by millions every day around the US? Your experience: do not even have a Twitter account.

That was me. I was scared. My second reaction: throw out questions to teammates who have (just a few weeks) more experience. And I waited for others to give me a full action plan to avoid making any mistakes on a public Twitter. Instead of giving it easy to me, this is what my teammates Slacked:

“@Peter none of us has experience managing a Twitter [account], or a public crisis. Might as well just throw out your ideas. Let’s do it together!”

This is a team of first times. For everybody in this team of young professionals and students, it’s our first time to deal with such intense real-world data that carries so much responsibility for communities near and far. For many of my Chinese teammates, it’s their first time to cram US geography (“county” is a different concept than “xian” in China so don’t call it that on the Chinese version of the site) and learn the levels of healthcare providers (so we don’t count them thrice when hospital, city and county report the same patients). Hanging out questions for others to answer before you attempt first would not have gotten us to the bottom of every data misalignment and every new Twitter strategy — because no one really knows from experience.

Fig 3. Prototyping earlier in our Twitter content generation process accelerates development by reducing less productive discussion in a more conventional process

That is not to say the team discourages questions. People ask questions — but they also throw a prototype solution to kick start the discussion. Take the first time we tweeted about emotional wellbeing. Instead of throwing articles and links and waiting for others to act on them, a teammate dropped a draft poster after a few rounds of trial and error in Canva and asked, “how does this look as a start?” Then conversation quickly advanced to specific designs and information on the poster. The tweet was out in less than two hours. This strategy drives the discussion by prototyping grounds suggestions in the final product, rather than scattering them around on the table — a prime excuse for everyone to talk much and do little.

Fig 4. One of our first emotional wellbeing Tweets, driven by the “prototype first” mentality

Transparency as the default

Those scrolling all the way here for a grand finale might be disappointed, but transparency is just like salt and sugar: everyone has them in the kitchen; few of us master either. Transparency is such a slogan in today’s project management toolkit that everyone nods at it, but it is easier said than done because often people regard it as additional efforts rather than a default mode of work.

At least that was my mindset when I first joined. I preferred direct messaging teammates, so I don’t bother others in the channels. I tried to be as aware of transparency as possible and did not hesitate to copy / paste or summarise the direct messages in channels whenever I see fit.

Then I got a call out in the #coronavirus_data.

“Make sure you use the public channels as much as possible instead of DMs. It helps everybody to see what comes out of your chats and saves time telling each other about it.”

Three weeks later I can’t agree more. In the time of coronavirus when circumstances move faster than we comprehend, the last thing this team needs is an artificial barrier of communication and decisions communicated after they have been made in private. As the team makes public channels the default place for all communications, I can trace a thread between two colleagues on Ingham, MI to determine the best format to explain the data inconsistency there on social media while feeling in the loop when I see there’s a thread with 20 messages before a new feature is launched. This transparency is not extra effort for the team as people are simply having the same conversations at a different place, but the mutual trust, honesty and lower cost of communication are immensely valuable in a rapidly evolving situation.

This mindset that defaults to transparency also helped us to gain public trust. Take the example when we first realised our approach to compile county-level numbers differed from Washington State authorities. We chose to clarify on both the website and on Twitter about how and why we compile the numbers before users even raised the question or even noticed. Our job is not just about having transparent results, but also transparent processes. As one of the co-founders put it, “we should link state official numbers in our tracker too, so users have visibility that we ARE making the comparisons.” While transparency is easy to be dismissed as a vague virtue, treating transparency as default is an actionable first step to take from here.

What’s next?

As the COVID-19 situation continues to evolve in North America, our team has expanded the focus from accurate state-level data to a variety of new resources. These new features are aimed to address diverse public needs from trends on the county level, hospitalization vs. healthcare capacity, to even a job board for those who are laid off.

Stay tuned for more insights, reflections and most importantly, up-to-date COVID-19 resources on one site at, and follow our Twitter at @1p3adev!

About the Author

Peter is a graduating senior at Duke University and an incoming associate consultant at Bain & Company in New York City. Peter is passionate about social impact work and has donated to charities fighting the COVID-19 outbreak since January. As the situation in the US escalated, Peter cancelled spring break plans to look for more hands-on opportunities to help doctors, nurses and patients. He joined the 1p3a Coronavirus Tracker and has been with the team since then. Peter now volunteers in the data team and Twitter operations, and is seeking new initiatives to bring value to the public in this challenging time.