My volunteer core data entry shift was more challenging than I expected; there was definitely an adrenaline rush. I signed up for a shift two days after observing and being actually in the spreadsheet, gathering data, while making my way through the nuances and state specific caveats was profoundly different than simply watching the chats and checkers in the sheet. The shift started with intro check-in via ice breaker, general announcements and standard operational slackbot messaging. I was quite impressed with the logistics of the project, it is pretty systematic at this point with the slackbot sending its daily threads, separate state conversation threads, and team leads and mentors on the shift who know the work in and out and able to provide guidance and support with some of the quickest turn around I have ever seen.
There was a full volunteer list on my day, so I ended up working on 3 state/territories: Louisiana, American Samoa, and Vermont. Starting with Louisiana, I noticed an anomaly where the number of COVID patients currently hospitalized and number of covid patients currently on ventilator went down by just enough overnight to raise concerns. When flagged, I was assured by the team lead that current numbers often fluctuate even cumulatively as state’s look back. Separately, I was really challenged with presence and meticulousness. Despite being fully immersed in the spreadsheet, I still managed to miscalculate a formula cell by using the wrong “positive cases” number. The feedback was “the Negative number (cell AQ) should use the positive cases (PCR) num” which illuminated to me the importance of headers and really understanding what each cell/input is telling us about the virus.
I moved on to American Samoa, which was quite uneventful. The last date from the island was in May 2020, where a fourth amended declaration of continued health emergency was announced. This state’s notes advised the checker to ‘Be your best detective. Good luck. tip: this usually comes from press releases, news or official social media. but it is updated infrequently.’ After some google perusing online, I came across the NY Times article which examined AS and highlighted how “The territory moved swiftly to halt nearly all incoming flights, rapidly boosted testing ability and took advantage of social distancing strategies that had already been adopted in response to a measles outbreak at the end of last year.” Not to mention the territory has responded to the COVID-19 pandemic similarly to recent disease outbreaks such as zika, dengue, and the measles. They have an effective system for managing outbreaks.
Lastly, Vermont was straightforward, but I still managed to make some errors with the calculated cells and not calculating with the correct ‘positive cases’ number. Once again, headers here and expert precision meticulousness here is super crucial.
