In New York City Reopening Splits Along Lines of Wealth and Race Bloomberg has analyzed the mobile phone location data of hundreds of thousands of New Yorkers to show how the city is gradually returning to normal after lock-down. Over the last year travel between New York neighborhoods has been much lower than usual as people have stayed close to home.
Using mobile phone location data Bloomberg has created a series of animated flow maps which visualize travel in New York. These animated flow maps clearly show how the coronavirus pandemic dramatically reduced the amount of travel between New York's different neighborhoods.For example the screenshot above shows a snapshot of travel in March 2019 compared to March 2020. Other flow maps, from later in 2020, show how travel began to pick-up as the city began to reopen.
Of course not everybody was able to work from home. Bloomberg has also used this phone location data and subway ridership data to show how low-income, Black and Hispanic communities were less able to stay at home during the pandemic. The data clearly shows that social distancing was a privilege that many sections of society could not afford.
In May of last year Gothamist also explored subway data to analyze how the pandemic was effecting travel in New York. The Gothamist came to very similar conclusions to those reached by Bloomberg on the sections of society which were least able to stop traveling during lock-down.
The interactive map in Which Parts Of NYC Are Relying On The Subway Most During Coronavirus uses scaled markers to show the total number of turnstile entries at each New York subway station. The color of the markers on this map visualize the number of turnstile entries as a percentage of the historical average. In other words the bluest stations saw the smallest drop in traffic compared to normal.
The map also includes a choropleth layer visualizing the levels of poverty and the numbers of residents working in healthcare in each New York borough. If you turn on the poverty rate layer you can see that there seems to be a correlation between the stations with the least reductions in traffic and the local poverty rate. The map also seems to show that the areas with the most healthcare workers are also the areas where subway use remains relatively high.
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