Last updated: 9/18/2020.

Data Geek Alert!
The data presented here should NOT be your sole metric for making decisions about your personal health and safety. Always listen to advice and directives made by Federal, State, and Local health experts!

Read more about how we collected and presented this data:

To compile this information, we utilized NYC Department of Health’s public COVID-19 github data accessible via NYC Open Data. Please refer to the readme for this dataset for complete caveats and qualifiers. For compiling Bay Ridge’s COVID history, we used the daily GIT commits for zip code 11209, utilizing the data-by-modzcta.csv dataset.

Please note that this data contains occasional “null” entries, reflecting dates where the city data was not updated.

Additionally, the datasets are always continually cleaned and updated resulting in seemingly odd day-to-day data changes. These instances often reflect hospitals and health agencies updating their data to reflect new information, such as a case being assigned to the wrong zip-code.

Thus, it is important to note that this data is not exact. The data provided should be used to infer general trends only, as represented by our moving 7-day averages.

The data for this visualization is freely downloadable on the Tableau website.

Interpreting This Data…

You’ll notice two elements to each graph: a bar graph, and a line graph. The bars show the daily totals for each statistic. The line shows the 7-day average. Hovering over a specific date will show more details and exact numbers.

In our Daily New Cases graph, the line graph color changes based on whether the average is rising or falling: red for rising, blue for falling.

In our Daily Tests graph, the color of the line becomes warmer the more positive tests were found on that day. This helps to highlight if an increase in testing has been prompted by an increase in positive tests, or another external factor.

Why are there gaps?

This data is collected from the NYC Department of Health, and some days did not see an update to zip-code level data. Other days had data retroactively adjusted for accuracy. The moving 7-day average (line graph) is thus a more accurate indicator of overall trends since it smooths these errors out.

Additionally, individual numbers for testing were not available at a zip-code level before June 10th.

What’s that big spike in Mid-August?

The mid-August spike, that nearly exceeded a 5% average positivity rate, corresponds to a Sunset Park localized outbreak. City officials later determined that the outbreak was not widespread but centered on specific households and illegal large-gatherings in Sunset Park. However, the city didn’t publicly confirm through contact tracing that any of the large-gathering Karaoke parties (which were raided and shut down) were the source of the outbreak.

Considering that Bay Ridge experienced a COVID-19 spike, it’s doubtful that the August outbreak was solely due to isolated events and households within Sunset Park, as was widely reported.

These spikes should also serve as a strong reminder that localized outbreaks and community spread is a very real possibility, even when overall city numbers appear to be going down.

Why is the Percent Positive trend going slightly up?

On our bottom-most graph, you can see the dotted line indicating the overall trend number of tests returned positive going slightly upward.

This is because fewer people have been getting test as time goes on. However, the number of cases has been staying roughly the same. This is probably due to fewer people getting tested as a precaution, which leaves more people getting tested who are displaying symptoms. As schools reopen and indoor dining resuming, we expect testing numbers to go up (as employees get tested before returning to work). This may push the percent positive trend downward.

As restaurants and schools reopen, we expect the testing numbers to go up, and the percent positive to go down….

Is this data useful in determining if local schools are safe?


Our schools are attended by staff and students from many different zip-codes, which this data does not capture. Zip-code level data cannot and should not be used to prove classrooms are safe.