{"id":1436,"date":"2020-07-22T01:57:40","date_gmt":"2020-07-22T01:57:40","guid":{"rendered":"http:\/\/council.nyc.gov\/data\/?page_id=1436"},"modified":"2022-05-19T18:42:04","modified_gmt":"2022-05-19T18:42:04","slug":"covid19-demographics","status":"publish","type":"page","link":"https:\/\/council.nyc.gov\/data\/covid19-demographics\/","title":{"rendered":"COVID19 Demographics"},"content":{"rendered":"

Characteristics of COVID-19 Death Rates<\/h2>\n
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\n Some zip codes have experienced very high levels of COVID-19 deaths while others have experienced very few COVID-19 deaths.<\/p>\n

To understand potential reasons for why these differences exist, we look at the connection between the characteristics of a zip code and its death rate.<\/p>\n

Income and previous health conditions have the highest correlation with COVID-19 death rates, but all of the zip code characteristics together play a role.<\/p>\n<\/div>\n

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Zip Code Characteristics<\/h2>\n

Previous Health Conditions
\nIncome
\nRace
\nInsurance Coverage
\nHousing Overcrowding
\nAge
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Download the Data <\/i><\/a><\/p>\n<\/div>\n

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Highest COVID-19 Death Rates<\/h2>\n

East New York (11239)
\nEdgemere \/ Far Rockaway (11691)
\nFlushing \/ Murray Hill (11354)
\nAllerton \/ Baychester \/ Pelham Gardens (10469)
\nAirport \/ East Elmhurst (10469)<\/small><\/p>\n<\/div>\n<\/div>\n

Data Team Home <\/i><\/a><\/p>\n<\/div>\n<\/div>\n

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Demographics<\/h2>\n

Severe previous health conditions in a zip code (Comorbidity Severity Index) is most strongly correlated with high zip code death rates due to COVID-19. (See: Comorbidity Analysis [link])<\/p>\n

Median income, race\/ethnicity, lack of health insurance, and household crowding are moderately correlated to high COVID-19 death rates by zip code.<\/p>\n

Percentage of people over 65 is weakly correlated to high COVID-19 death rates in neighborhoods.<\/p>\n<\/div>\n

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Correlation to COVID-19 Death Rate<\/h2>\n
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\nComorbidity Severity Index<\/strong>: Strong (0.67)<\/small><\/p>\n
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Moderate
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\nMedian Income<\/strong>: Moderate (-0.54)
\nNon-Hispanic White (%)<\/strong>: Moderate (-0.51)
\nLack of Health Insurance Rate (%)<\/strong>: Moderate (0.46)
\nHousehold Crowding<\/strong>: Moderate (0.44)
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Weak
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\nAge 65+ (%)<\/strong>: Weak (0.25)*<\/a><\/small><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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*Data Details<\/h3>\n
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The fact that age is only weakly correlated emphasizes two things about the analysis:<\/p>\n

(1) The data is at the zip code level, not the individual level.<\/p>\n

While older individuals have a higher death rate<\/a>, we do not find a strong connection between the proportion of people in a zip code over the age of 65 and the COVID-19 death rate in that area.<\/p>\n

(2) These factors do not exist in isolation, but rather together at once.<\/p>\n

For example, East Midtown (10022) and East New York (11239) have the highest proportion of people above the age of 65, 29%, but very different covid outcomes.<\/p>\n<\/div>\n

\n East Midtown\u2019s death rate is relatively low (102 deaths per 100,000), while East New York\u2019s is the highest in the city (717 deaths per 100,000). Unlike East Midtown, East New York has very low income and very severe comorbidities.<\/p>\n

The difference in the death rate between these two zip codes shows that all of the characteristics, not just one, are important in understanding the death rate of a zip code– they work in combination, not isolation.<\/p>\n

In addition, there are at least two pieces of information that are important but unavailable: data on where more people fled the city during quarantine and data on where more people worked from home.<\/p>\n<\/div>\n<\/div>\n

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Correlations: Characteristics & COVID-19 Death Rate<\/h2>\n
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\n Scatterplots illustrate visually the relationship between the zip code characteristics and COVID-19 death rate. Each data point represents a zip code.<\/p>\n<\/div>\n
\n The top five zip codes for the highest COVID-19 death rate are seen in red over the six characteristics.<\/p>\n<\/div>\n<\/div>\n
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Comorbidity Severity Index<\/h3>\n
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