This folder contains files with daily or weekly data shown across time. Note that these trend data are published by date of event, not by date of report.
This file contains citywide and borough-specific daily counts of confirmed cases, hospitalizations, and deaths. To address variation in cases diagnosed per day, we have included a 7-day average (mean) of daily confirmed case counts. This is calculated as the average of number of confirmed cases diagnosed on that day and the previous 6 days. Counts are aggregated separately by the following dates of interest:
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Cases are by date of diagnosis
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Hospitalizations are by date of admission
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Deaths are by date of death
This file includes data since February 29, 2020 based on the date that the Health Department classifies as the start of the COVID-19 outbreak in NYC (date of the first laboratory-confirmed case).
Indicators include:
| Variable name | Definition | Timeframe |
|---|---|---|
| DATE_OF_INTEREST | Date of diagnosis (cases), date of admission (hospitalizations), date of death (deaths) | |
| CASE_COUNT | Count of confirmed cases citywide | Day |
| HOSPITALIZED_COUNT | Count of hospitalized cases citywide | Day |
| DEATH_COUNT | Count of confirmed deaths citywide | Day |
| DEATH_COUNT_PROBABLE | Count of probable deaths citywide | Day |
| CASE_COUNT_7DAY_AVG | 7-day average of count of confirmed cases citywide | Current day and previous 6 days |
| HOSP_COUNT_7DAY_AVG | 7-day average of count of hospitalized cases citywide | Current day and previous 6 days |
| DEATH_COUNT_7DAY_AVG | 7-day average of count of confirmed deaths citywide | Current day and previous 6 days |
| BX_CASE_COUNT | Count of confirmed cases in the Bronx | Day |
| BX_HOSPITALIZED_COUNT | Count of hospitalized cases in the Bronx | Day |
| BX_DEATH_COUNT | Count of confirmed deaths in the Bronx | Day |
| BX_CASE_COUNT_7DAY_AVG | 7-day average of count of confirmed cases in the Bronx | Current day and previous 6 days |
| BX_HOSPITALIZED_COUNT_7DAY_AVG | 7-day average of count of hospitalized cases in the Bronx | Current day and previous 6 days |
| BX_DEATH_COUNT_7DAY_AVG | 7-day average of count of confirmed deaths in the Bronx | Current day and previous 6 days |
| BK_CASE_COUNT | Count of confirmed cases in Brooklyn | Day |
| BK_HOSPITALIZED_COUNT | Count of hospitalized cases in Brooklyn | Day |
| BK_DEATH_COUNT | Count of confirmed deaths in Brooklyn | Day |
| BK_CASE_COUNT_7DAY_AVG | 7-day average of count of confirmed cases in Brooklyn | Current day and previous 6 days |
| BK_HOSPITALIZED_COUNT_7DAY_AVG | 7-day average of count of hospitalized cases in Brooklyn | Current day and previous 6 days |
| BK_DEATH_COUNT_7DAY_AVG | 7-day average of count of confirmed deaths in Brooklyn | Current day and previous 6 days |
| MN_CASE_COUNT | Count of confirmed cases in Manhattan | Day |
| MN_HOSPITALIZED_COUNT | Count of hospitalized cases in Manhattan | Day |
| MN_DEATH_COUNT | Count of confirmed deaths in Manhattan | Day |
| MN_CASE_COUNT_7DAY_AVG | 7-day average of count of confirmed cases in Manhattan | Current day and previous 6 days |
| MN_HOSPITALIZED_COUNT_7DAY_AVG | 7-day average of count of hospitalized cases in Manhattan | Current day and previous 6 days |
| MN_DEATH_COUNT_7DAY_AVG | 7-day average of count of confirmed deaths in Manhattan | Current day and previous 6 days |
| QN_CASE_COUNT | Count of confirmed cases in Queens | Day |
| QN_HOSPITALIZED_COUNT | Count of hospitalized cases in Queens | Day |
| QN_DEATH_COUNT | Count of confirmed deaths in Queens | Day |
| QN_CASE_COUNT_7DAY_AVG | 7-day average of count of confirmed cases in Queens | Current day and previous 6 days |
| QN_HOSPITALIZED_COUNT_7DAY_AVG | 7-day average of count of hospitalized cases in Queens | Current day and previous 6 days |
| QN_DEATH_COUNT_7DAY_AVG | 7-day average of count of confirmed deaths in Queens | Current day and previous 6 days |
| SI_CASE_COUNT | Count of confirmed cases in Staten Island | Day |
| SI_HOSPITALIZED_COUNT | Count of hospitalized cases in Staten Island | Day |
| SI_DEATH_COUNT | Count of confirmed deaths in Staten Island | Day |
| SI_CASE_COUNT_7DAY_AVG | 7-day average of count of confirmed cases in Staten Island | Current day and previous 6 days |
| SI_HOSPITALIZED_COUNT_7DAY_AVG | 7-day average of count of hospitalized cases in Staten Island | Current day and previous 6 days |
| SI_DEATH_COUNT_7DAY_AVG | 7-day average of count of confirmed deaths in Staten Island | Current day and previous 6 days |
| INCOMPLETE | Used for display purposes only |
Note that sum of counts in this file may not match values in citywide tables because of records with missing geographic information.
covid-like-illness.csv was previously called syndromic_data.csv.
This file includes the rate of visits to NYC emergency departments (ED) per 100,000 people, and rates of subsequent admissions to the hospital through the ED, for influenza-like illness or pneumonia, by date of visit for all ages and by age group (0-4, 5-12, 13-17, 18-24, 25-34, 35-44, 45-54, 55-64, 65-74, and 75+ years). Please see additional details about the Health Department's syndromic surveillance system in the technical notes section (Types of Surveillance: Syndromic Surveillance).
This file includes data based on the Health Department’s syndromic surveillance system. The data go back to February 1, 2020, to provide a view of the early days of the pandemic
Indicators include:
| Variable name | Definition | Timeframe |
|---|---|---|
| Date | Date of ED visit | |
| Admit 0-4 | Rate of hospital admissions among people aged 0-4 years per 100,000 people | Day |
| Admit 5-12 | Rate of hospital admissions among people aged 5-12 years per 100,000 people | Day |
| Admit 13-17 | Rate of hospital admissions among people aged 13-17 years per 100,000 people | Day |
| Admit 18-24 | Rate of hospital admissions among people aged 18-24 years per 100,000 people | Day |
| Admit 25-34 | Rate of hospital admissions among people aged 25-34 years per 100,000 people | Day |
| Admit 35-44 | Rate of hospital admissions among people aged 35-44 years per 100,000 people | Day |
| Admit 45-54 | Rate of hospital admissions among people aged 45-54 years per 100,000 people | Day |
| Admit 55-64 | Rate of hospital admissions among people aged 55-64 years per 100,000 people | Day |
| Admit 65-74 | Rate of hospital admissions among people aged 65-74 years per 100,000 people | Day |
| Admit 75+ | Rate of hospital admissions among people aged 75+ years per 100,000 people | Day |
| Admit All ages | Rate of hospital admissions among people of all ages per 100,000 people | Day |
| Visit 0-4 | Rate of ED visits among people aged 0-4 years per 100,000 people | Day |
| Visit 5-12 | Rate of ED visits among people aged 5-12 years per 100,000 people | Day |
| Visit 13-17 | Rate of ED visits among people aged 13-17 years per 100,000 people | Day |
| Visit 18-24 | Rate of ED visits among people aged 18-24 years per 100,000 people | Day |
| Visit 25-34 | Rate of ED visits among people aged 25-34 years per 100,000 people | Day |
| Visit 35-44 | Rate of ED visits among people aged 35-44 years per 100,000 people | Day |
| Visit 45-54 | Rate of ED visits among people aged 45-54 years per 100,000 people | Day |
| Visit 55-64 | Rate of ED visits among people aged 55-64 years per 100,000 people | Day |
| Visit 65-74 | Rate of ED visits among people aged 65-74 years per 100,000 people | Day |
| Visit 75+ | Rate of ED visits among people aged 75+ years per 100,000 people | Day |
| Visit All ages | Rate of ED visits among people of all ages per 100,000 people | Day |
This file contains the number of people who received a polymerase chain reaction (PCR) test, the number of people with positive results, and the percentage of people tested who tested positive, stratified by day. The dates shown in this table reflect the date of specimen collection (i.e., when someone went to a healthcare provider for a test). Please see description of the different categories of COVID-19 tests in the technical notes section (Types of Surveillance: Reportable Disease Surveillance).
To address wide variation in single day testing data, the file also includes 7-day averages (means) for the number of people tested and the number of people who were positive. These are calculated as the cumulative sum of both persons positive and persons tested of that day’s count and the previous 6 days.
This file includes data since March 3, 2020 based on when the Health Department started to receive a higher volume of PCR tests following the start of the COVID-19 outbreak in NYC.
Indicators include:
| Variable name | Definition | Timeframe |
|---|---|---|
| DATE | Date of specimen collection | |
| TOTAL_TESTS | Number of people who received a PCR test | Day |
| POSTITIVE_TESTS | Number of people with a positive result on a PCR test | Day |
| PERCENT_POSITIVE | Percentage of people tested with a PCR test who tested positive | Day |
| TOTAL_TESTS_7DAYS_AVG | 7-day average of number of people who received a PCR test | Current day and previous 6 days |
| POSITIVE_TESTS_7DAYS_AVG | 7-day average of number of people with positive results | Current day and previous 6 days |
| PERCENT_POSITIVE_7DAYS_AVG | 7-day average of percentage of people tested with a PCR test who tested positive | Current day and 6 previous days |
| INCOMPLETE | Used for display purposes only |
Note that one person can have more than one test on different days. Therefore, the number of positive persons every day will be different from the counts of confirmed cases, which will count people only on the first day they test positive.
This file contains the number of people who received a PCR test, the percentage of people tested who tested positive, and the rate of PCR testing per 100,000 people, stratified by week and age group. The dates shown in this table reflect the date of specimen collection (i.e., when someone went to a healthcare provider for a test). Please see description of the different categories of COVID-19 tests in the technical notes section (Types of Surveillance: Reportable Disease Surveillance).
People with a PCR test are aggregated by full-weeks starting each Sunday and ending on Saturday. For example, a person who had a nasal swab collected for PCR testing on Monday October 12 would be categorized as tested during the week ending October 17. A person tested twice in one week would only be counted once in that week.
This file includes data since March 3, 2020 based on when the Health Department started to receive a higher volume of PCR tests following the start of the COVID-19 outbreak in NYC.
Indicators include:
| Variable name | Definition | Timeframe |
|---|---|---|
| WEEK_ENDING | Week-ending date | |
| PERPOS_ALL_AGEG | Percentage of people tested with a PCR test who tested positive among people of all ages | Full week preceding the week-ending date |
| TESTRATE_ALL_AGEG | Rate of PCR testing per 100,000 among people of all ages | Full week preceding the week-ending date |
| NUMTEST_ALL_AGEG | Number of people who received a PCR test among people of all ages | Full week preceding the week-ending date |
| PERPOS_0_4 | Percentage of people aged 0-4 years tested with a PCR test who tested positive | Full week preceding the week-ending date |
| TESTRATE_0_4 | Rate of PCR testing per 100,000 people aged 0-4 years | Full week preceding the week-ending date |
| NUMTEST_0_4 | Number of people aged 0-4 years who received a PCR test | Full week preceding the week-ending date |
| PERPOS_5_12 | Percentage of people aged 5-12 years tested with a PCR test who tested positive | Full week preceding the week-ending date |
| TESTRATE_5_12 | Rate of PCR testing per 100,000 people aged 5-12 years | Full week preceding the week-ending date |
| NUMTEST_5_12 | Number of people aged 5-12 years who received a PCR test | Full week preceding the week-ending date |
| PERPOS_13_17 | Percentage of people aged 13-17 years tested with a PCR test who tested positive | Full week preceding the week-ending date |
| TESTRATE_13_17 | Rate of PCR testing per 100,000 people aged 13-17 years | Full week preceding the week-ending date |
| NUMTEST_13_17 | Number of people aged 13-17 years who received a PCR test | Full week preceding the week-ending date |
| PERPOS_18_24 | Percentage of people aged 18-24 years tested with a PCR test who tested positive | Full week preceding the week-ending date |
| TESTRATE_18_24 | Rate of PCR testing per 100,000 people aged 18-24 years | Full week preceding the week-ending date |
| NUMTEST_18_24 | Number of people aged 18-24 years who received a PCR test | Full week preceding the week-ending date |
| PERPOS_25_34 | Percentage of people aged 25-34 years tested with a PCR test who tested positive | Full week preceding the week-ending date |
| TESTRATE_25_34 | Rate of PCR testing per 100,000 people aged 25-34 years | Full week preceding the week-ending date |
| NUMTEST_25_34 | Number of people aged 25-34 years who received a PCR test | Full week preceding the week-ending date |
| PERPOS_35_44 | Percentage of people aged 35-44 years tested with a PCR test who tested positive | Full week preceding the week-ending date |
| TESTRATE_35_44 | Rate of PCR testing per 100,000 people aged 35-44 years | Full week preceding the week-ending date |
| NUMTEST_35_44 | Number of people aged 35-44 years who received a PCR test | Full week preceding the week-ending date |
| PERPOS_45_54 | Percentage of people aged 45-54 years tested with a PCR test who tested positive | Full week preceding the week-ending date |
| TESTRATE_45_54 | Rate of PCR testing per 100,000 people aged 45-54 years | Full week preceding the week-ending date |
| NUMTEST_45_54 | Number of people aged 45-54 years who received a PCR test | Full week preceding the week-ending date |
| PERPOS_55_64 | Percentage of people aged 55-64 years tested with a PCR test who tested positive | Full week preceding the week-ending date |
| TESTRATE_55_64 | Rate of PCR testing per 100,000 people aged 55-64 years | Full week preceding the week-ending date |
| NUMTEST_55_64 | Number of people aged 55-64 years who received a PCR test | Full week preceding the week-ending date |
| PERPOS_65_74 | Percentage of people aged 65-74 years tested with a PCR test who tested positive | Full week preceding the week-ending date |
| TESTRATE_65_74 | Rate of PCR testing per 100,000 people aged 65-74 years | Full week preceding the week-ending date |
| NUMTEST_65_74 | Number of people aged 65-74 years who received a PCR test | Full week preceding the week-ending date |
| PERPOS_75UP | Percentage of people aged 75+ years tested with a PCR test who tested positive | Full week preceding the week-ending date |
| TESTRATE_75UP | Rate of PCR testing per 100,000 people aged 75+ years | Full week preceding the week-ending date |
| NUMTEST_75UP4 | Number of people aged 75+ years who received a PCR test | Full week preceding the week-ending date |
Note that one person can have more than one test during different weeks. Therefore, the sum of counts across weeks may not match summary values.
This file contains the number of people who received an antibody test, the number of people with positive results, and the percentage of people tested who tested positive, stratified by week. The dates shown in this table reflect the date of specimen collection (i.e., when someone went to a healthcare provider for a test). Please see description of the different categories of COVID-19 tests in the technical notes section (Types of Surveillance: Reportable Disease Surveillance).
People with an antibody test are aggregated by full-weeks starting each Sunday and ending on Saturday. For example, a person whose blood was collected for antibody testing on Monday, October 12 would be categorized as tested during the week ending October 17. A person tested twice in one week would only be counted once in that week.
People are considered positive if they ever receive a positive antibody result, regardless of whether they have received negative results as well.
This file includes data since the week ending April 11, 2020 based on when the Health Department started to receive a higher volume of antibody tests following the start of the COVID-19 outbreak in NYC.
Indicators include:
| Variable Name | Definition | Timeframe |
|---|---|---|
| WEEKDATE | Week-ending date | |
| NUM_PEOP_TEST | Number of people who received an antibody test | Full week preceding the week-ending date |
| NUM_PEOP_POS | Number of people with a positive result on an antibody test | Full week preceding the week-ending date |
| PERCENT_POSITIVE | Percentage of people tested with an antibody test who tested positive | Full week preceding the week-ending date |
| INCOMPLETE | Used for display purposes only |
Note that one person can have more than one test during different weeks. Therefore, the sum of counts across weeks may not match summary values.
This file contains test-level information on PCR tests, stratified by week. The dates shown in this table reflect the date of specimen collection (i.e., when someone went to a healthcare provider for a test). Please see description of the different categories of COVID-19 tests in the technical notes section (Types of Surveillance: Reportable Disease Surveillance).
PCR tests are aggregated by full-weeks starting each Sunday and ending on Saturday. For example, a nasal swab collected for PCR testing on Monday October 12 would be categorized as tested during the week ending October 17.
This file includes data since the week ending March 7, 2020 based on when the Health Department started to receive a higher volume of PCR tests following the start of the COVID-19 outbreak in NYC.
| Variable Name | Definition | Timeframe |
|---|---|---|
| WEEK_END | Week-ending date | |
| TESTS | Number of PCR tests conducted | Week |
| PERCENT_24HR | Percent of PCR tests with results reported within 24 hours | Full week preceding the week-ending date |
| PERCENT_48HR | Percent of PCR tests with results reported within 48 hours | Full week preceding the week-ending date |
| LAG_MEDIAN | Median lag time (half of tests have results reported faster than this time), in days | Full week preceding the week-ending date |
| LAG_25TH_PERCENTILE | 25th percentile lag time (1 out of 4 tests have results reported faster than this time), in days | Full week preceding the week-ending date |
| LAG_75TH_PERCENTILE | 75th percentile lag time (1 out of 4 tests have results reported slower than this time), in days | Full week preceding the week-ending date |
Note that one person can have more than one test on different days. Therefore, the number of tests conducted in a week will differ from the number of people tested (as reported in other files) for the same week.
This file contains the rate of PCR testing per 100,000 people, stratified by week and three different geographies: citywide, borough, modified ZIP Code Tabulation Area geographies (MODZCTA). The level of geography is indicated following the underscore (_) in each column heading. Please see the technical notes section for a description of MODZCTA (Geography: Zip codes and ZCTAs), and the different categories of COVID-19 tests (Types of Surveillance: Reportable Disease Surveillance). The dates shown in this table reflect the date of specimen collection (i.e., when someone went to a healthcare provider for a test).
People with a PCR test are aggregated by full-weeks starting each Sunday and ending on Saturday. For example, a person who had a nasal swab collected for PCR testing on Monday October 12 would be categorized as tested during the week ending October 17. A person tested twice in one week would only be counted once in that week. Therefore, the number of tests conducted in a week will differ from the number of people tested (as reported in other files) for the same week.
This file contains the percentage of people tested for COVID-19 with a PCR test who tested positive, stratified by week and three different geographies: citywide, borough, MODZCTA. The level of geography is indicated following the underscore (_) in each column heading. Please see the technical notes section for a description of MODZCTA (Geography: Zip codes and ZCTAs), and the different categories of COVID-19 tests (Types of Surveillance: Reportable Disease Surveillance). The dates shown in this table reflect the date of specimen collection (i.e., when someone went to a healthcare provider for a test).
People with a PCR test are aggregated by full-weeks starting each Sunday and ending on Saturday. For example, a person who had a nasal swab collected for PCR testing on Monday October 12 would be categorized as tested during the week ending October 17. A person tested twice in one week would only be counted once in that week. Therefore, the number of tests conducted in a week will differ from the number of people tested (as reported in other files) for the same week.
This file contains the rate of confirmed cases per 100,000 people, stratified by week and three different geographies: citywide, borough, MODZCTA. The level of geography is indicated following the underscore (_) in each column heading. Please see the technical notes section for a description of MODZCTA (Geography: Zip codes and ZCTAs), and the different categories of COVID-19 tests (Types of Surveillance: Reportable Disease Surveillance). The dates shown in this table reflect the date of specimen collection (i.e., when someone went to a healthcare provider for a test).
People with confirmed COVID-19 are categorized based on the date of diagnosis, and are aggregated by full-weeks starting each Sunday and ending on Saturday. For example, a person who was diagnosed with COVID-19 on Monday October 12 would be categorized as diagnosed during the week ending October 17. Note that sum of counts in this file may not match values in citywide tables because of records with missing geographic information.