Percent Live Births by Infant Sex and Mother’s Race/Ethnicity for New York City, 2007-2020

All NYC children are required to be tested for lead poisoning at around age 1 and age 2, and to be screened for risk of lead poisoning, and tested if at risk, up until age 6. These data are an indicator of the number and percentage of children turning 3 years old in a given year who were tested for lead poisoning.

About the Data
All NYC children are required to be tested for lead poisoning at around age 1 and age 2, and to be screened for risk of lead poisoning, and tested if at risk, up until age 6. These data are an indicator of the number and percentage of children turning 3 years old in a given year who were tested for lead poisoning.
How calculated: To identify children tested for lead poisoning, birth records for all children born in New York City to New York City resident mothers, and turning 3 years old in a given year were matched to children tested for lead poisoning before age 3.

Severe maternal morbidity (SMM) refers to life-threatening complications of labor and delivery that result in significant short- or long-term health consequences. SMM data are derived from linking NYC birth certificates for births occurring at NYC facilities with the mother's delivery hospitalization record from the New York Statewide Planning and Research Cooperative System. SMM is identified using an established algorithm developed by the Centers for Disease Control and Prevention that comprises 21 indicators that represent diagnoses of serious complications of pregnancy or delivery or procedures used to manage serious conditions. Each record represents the aggregated number and rate of SMM events in the population group specified for the year specified.

The Hepatitis category in NYC Health Map provides a list of facilities for the public and service providers looking for prevention services, testing, and treatment for hepatitis B and C. Due to shared risk factors, people living with HIV should get the Hep B vaccine, and should get tested for both Hep B and C. The programs listed have been verified by the NYC DOHMH.

The Viral Hepatitis Program in the Bureau of Hepatitis, HIV and STI contracts with organizations in the city to provide peer navigation and patient navigation for Hep B and C. These agencies and their hepatitis services are listed in the NYC Health Map for public use. The Hepatitis list also includes agencies contracted by the New York State Health Department to provide Hep C testing, care and treatment, and agencies participating in the Hep Free NYC network. This list is maintained in a database by Viral Hepatitis Program staff and is updated once a year. It does not capture all hepatitis B and C services available in New York City. The data is organized by service type, and each record represents a service offered at a single location. Hepatitis A vaccine information is kept separately in the Vaccines list managed by the Bureau of Immunizations.

This dataset consists of registrations for radiation producing equipment. The owner or operator of any radiation installation or of any radiation equipment in operable condition intended to be used for patient clinical diagnosis and/or treatment must obtain a current Radiation Producing Equipment - Certificate of Registration from the NYC Department of Health and Mental Hygiene (DOHMH) in order to establish (set up), maintain or operate such equipment. Registrations are categorized by facility and must be renewed every two years.

This dataset contains information on antibody testing for COVID-19: the number of people who received a test, the number of people with positive results, the percentage of people tested who tested positive, and the rate of testing per 100,000 people, stratified by ZIP Code Tabulation Area (ZCTA) neighborhood poverty group. These data can also be accessed here: https://github.com/nychealth/coronavirus-data/blob/master/totals/antibody-by-poverty.csv

Exposure to COVID-19 can be detected by measuring antibodies to the disease in a person’s blood, which can indicate that a person may have had an immune response to the virus. Antibodies are proteins produced by the body’s immune system that can be found in the blood. People can test positive for antibodies after they have been exposed, sometimes when they no longer test positive for the virus itself. It is important to note that the science around COVID-19 antibody tests is evolving rapidly and there is still much uncertainty about what individual antibody test results mean for a single person and what population-level antibody test results mean for understanding the epidemiology of COVID-19 at a population level.

These data only provide information on people tested. People receiving an antibody test do not reflect all people in New York City; therefore, these data may not reflect antibody prevalence among all New Yorkers. Increasing instances of screening programs further impact the generalizability of these data, as screening programs influence who and how many people are tested over time. Examples of screening programs in NYC include: employers screening their workers (e.g., hospitals), and long-term care facilities screening their residents.

In addition, there may be potential biases toward people receiving an antibody test who have a positive result because people who were previously ill are preferentially seeking testing, in addition to the testing of persons with higher exposure (e.g., health care workers, first responders.)

Neighborhood-level poverty groups were classified in a manner consistent with Health Department practices to describe and monitor disparities in health in NYC. Neighborhood poverty measures are defined as the percentage of people earning below the Federal Poverty Threshold (FPT) within a ZCTA. The standard cut-points for defining categories of neighborhood-level poverty in NYC are:
• Low: <10% of residents in ZCTA living below the FPT
• Medium: 10% to <20%
• High: 20% to <30%
• Very high: ≥30% residents living below the FPT
The ZCTAs used for classification reflect the first non-missing address within NYC for each person reported with an antibody test result.

Rates were calculated using interpolated intercensal population estimates updated in 2019. These rates differ from previously reported rates based on the 2000 Census or previous versions of population estimates. The Health Department produced these population estimates based on estimates from the U.S. Census Bureau and NYC Department of City Planning. Rates for poverty were calculated using direct standardization for age at diagnosis and weighting by the US 2000 standard population.
Antibody tests are categorized based on the date of specimen collection and are aggregated by full weeks starting each Sunday and ending on Saturday. For example, a person whose blood was collected for antibody testing on Wednesday, May 6 would be categorized as tested during the week ending May 9. A person tested twice in one week would only be counted once in that week. This dataset includes testing data beginning April 5, 2020.

Data are updated daily, and the dataset preserves historical records and source data changes, so each extract date reflects the current copy of the data as of that date. For example, an extract date of 11/04/2020 and extract date of 11/03/2020 will both contain all records as they were as of that extract date. Without filtering or grouping by extract date, an analysis will almost certain

This file contains person-level information on antibody testing: the number of people who received a test, the number of people with positive results, the percentage of people tested who tested positive, and the rate of testing per 100,000 people, stratified by age group.

This directory is for at-risk for HIV and eligible persons living with HIV in New York City seeking HIV medical and supportive services. The agencies and their listed programs receive CDC and Ryan White Part-A funding to provide: Targeted-Testing among Priority Populations, Food and Nutrition Services, Health Education and Risk Reduction Services, Harm Reduction Services, Legal Services, Mental Health Services, Case Management and Care Coordination Services, and Supportive Counseling Services. To be eligible to recieve these services, prospective clients must: 1)be HIV-positive; 2) have a total household income below 435% of the Federal Poverty Level (FPL) (this is the same as the income eligible guidelines for the New York State AIDS Drug Assistance Program (ADAP) and higher than the income eligiblity guidelines for Medicaid in New York State); and 3) reside in New York City or the counties of Westchester, Rockland, and Putnam. For providers, to make a referral, please contact the program directly using the information provided in the diretory (please be sure to call before directing clients to the program). When making a referral, you may also find it useful to talk to your client about executing a release of information form authorizing you to share confidential health and HIV-related information with another service provider in order to coordinate care (for more information, go to https://www.health.ny.gov/diseases/aids/providers/forms/informedconsent.htm).

This dataset contains information on antibody testing for COVID-19: the number of people who received a test, the number of people with positive results, the percentage of people tested who tested positive, and the rate of testing per 100,000 people, stratified by modified ZIP Code Tabulation Area (ZCTA) of residence. Modified ZCTA reflects the first non-missing address within NYC for each person reported with an antibody test result. This unit of geography is similar to ZIP codes but combines census blocks with smaller populations to allow more stable estimates of population size for rate calculation. It can be challenging to map data that are reported by ZIP Code. A ZIP Code doesn’t refer to an area, but rather a collection of points that make up a mail delivery route. Furthermore, there are some buildings that have their own ZIP Code, and some non-residential areas with ZIP Codes. To deal with the challenges of ZIP Codes, the Health Department uses ZCTAs which solidify ZIP codes into units of area. Often, data reported by ZIP code are actually mapped by ZCTA. The ZCTA geography was developed by the U.S. Census Bureau. These data can also be accessed here: https://github.com/nychealth/coronavirus-data/blob/master/totals/antibody-by-modzcta.csv Exposure to COVID-19 can be detected by measuring antibodies to the disease in a person’s blood, which can indicate that a person may have had an immune response to the virus. Antibodies are proteins produced by the body’s immune system that can be found in the blood. People can test positive for antibodies after they have been exposed, sometimes when they no longer test positive for the virus itself. It is important to note that the science around COVID-19 antibody tests is evolving rapidly and there is still much uncertainty about what individual antibody test results mean for a single person and what population-level antibody test results mean for understanding the epidemiology of COVID-19 at a population level.

These data only provide information on people tested. People receiving an antibody test do not reflect all people in New York City; therefore, these data may not reflect antibody prevalence among all New Yorkers. Increasing instances of screening programs further impact the generalizability of these data, as screening programs influence who and how many people are tested over time. Examples of screening programs in NYC include: employers screening their workers (e.g., hospitals), and long-term care facilities screening their residents.

In addition, there may be potential biases toward people receiving an antibody test who have a positive result because people who were previously ill are preferentially seeking testing, in addition to the testing of persons with higher exposure (e.g., health care workers, first responders)

Rates were calculated using interpolated intercensal population estimates updated in 2019. These rates differ from previously reported rates based on the 2000 Census or previous versions of population estimates. The Health Department produced these population estimates based on estimates from the U.S. Census Bureau and NYC Department of City Planning.

Antibody tests are categorized based on the date of specimen collection and are aggregated by full weeks starting each Sunday and ending on Saturday. For example, a person whose blood was collected for antibody testing on Wednesday, May 6 would be categorized as tested during the week ending May 9. A person tested twice in one week would only be counted once in that week. This dataset includes testing data beginning April 5, 2020.

Data are updated daily, and the dataset preserves historical records and source data changes, so each extract date reflects the current copy of the data as of that date. For example, an extract date of 11/04/2020 and extract date of 11/03/2020 will both contain all records as they were as of that extract date. Without filtering or grouping by extract date, an analysis wi

The New York City Health Opinion Poll (HOP) is a periodic rapid online poll conducted by New York City Department of Health and Mental Hygiene. The goals of the poll are to measure adult New Yorkers’ awareness, acceptance and use — or barriers to use — of our programs; knowledge, opinions and attitudes about health care and practices; and opinions about public events that are related to health. The data collected through public health polling are rapidly analyzed and disseminated. This real-time community input informs programming and policy development at the Health Department to better meet the needs of New Yorkers.

This dataset shows daily confirmed and probable cases of COVID-19 in New York City by date of specimen collection. Total cases has been calculated as the sum of daily confirmed and probable cases. Seven-day averages of confirmed, probable, and total cases are also included in the dataset.
A person is classified as a confirmed COVID-19 case if they test positive with a nucleic acid amplification test (NAAT, also known as a molecular test; e.g. a PCR test). A probable case is a person who meets the following criteria with no positive molecular test on record: a) test positive with an antigen test, b) have symptoms and an exposure to a confirmed COVID-19 case, or c) died and their cause of death is listed as COVID-19 or similar.
As of June 9, 2021, people who meet the definition of a confirmed or probable COVID-19 case >90 days after a previous positive test (date of first positive test) or probable COVID-19 onset date will be counted as a new case. Prior to June 9, 2021, new cases were counted ≥365 days after the first date of specimen collection or clinical diagnosis.
Any person with a residence outside of NYC is not included in counts.
Data is sourced from electronic laboratory reporting from the New York State Electronic Clinical Laboratory Reporting System to the NYC Health Department.
All identifying health information is excluded from the dataset.

These data are used to evaluate the overall number of confirmed and probable cases by day (seven day average) to track the trajectory of the pandemic. Cases are classified by the date that the case occurred. NYC COVID-19 data include people who live in NYC. Any person with a residence outside of NYC is not included.

The NYC Middle School Youth Risk Behavior Survey (MS YRBS) is conducted through an ongoing collaboration between the New York City Department of Health and Mental Hygiene (DOHMH), the Department of Education (DOE), and the National Centers for Disease Control and Prevention (CDC). The New York City's YRBS is part of the CDC's National Youth Risk Behavior Surveillance System (YRBSS). The survey's primary purpose is to monitor priority health risk behaviors that contribute to the leading causes of mortality, morbidity, and social problems among youth in New York City. For more information, visit https://www1.nyc.gov/site/doh/data/data-sets/nyc-youth-risk-behavior-survey.page

The NYC KIDS Survey is a population-based telephone survey conducted by the Health Department. The survey provides robust data on the health of children aged 13 years or younger (2017: children aged 0-13 years; 2019: children aged 1-13 years) in New York City, including citywide and borough estimates, on a broad range of topics including physical and mental health, health care access, and school and childcare enrollment and learning. For more information, visit https://www1.nyc.gov/site/doh/data/data-sets/child-chs.page

1. Counts and rates of referrals, children receiving general services, children receiving any services by borough.
2. Counts and rates of referrals, children receiving general services, children receiving any services by race/ethnicity
3. Progression of children referred though the EI stages, by, race citywide and by borough.
4. Current insurance status of children receiving general services.

Tuberculosis cases and rates by select characteristics table from the Tuberculosis Control Annual Summary

The Heat Vulnerability Index (HVI) shows neighborhoods whose residents are more at risk for dying during and immediately following extreme heat. It uses a statistical model to summarize the most important social and environmental factors that contribute to neighborhood heat risk. The factors included in the HVI are surface temperature, green space, access to home air conditioning, and the percentage of residents who are low-income or non-Latinx Black. Differences in these risk factors across neighborhoods are rooted in past and present racism. Neighborhoods are scored from 1 (lowest risk) to 5 (highest risk) by summing the following factors and assigning them into 5 groups (quintiles):

Median Household Income (American Community Survey 5 year estimate, 2016-2020)
Percent vegetative cover (trees, shrubs or grass) (2017 LiDAR, NYC DOITT)
Percent of population reported as Non-Hispanic Black on Census 2020
Average surface temperature Fahrenheit from ECOSSTRESS thermal imaging, August 27,2020
Percent of households reporting Air Conditioning access, Housing ad Vacancy Survey, 2017

This dataset shows the number of hospital admissions for influenza-like illness, pneumonia, or include ICD-10-CM code (U07.1) for 2019 novel coronavirus. Influenza-like illness is defined as a mention of either: fever and cough, fever and sore throat, fever and shortness of breath or difficulty breathing, or influenza. Patients whose ICD-10-CM code was subsequently assigned with only an ICD-10-CM code for influenza are excluded. Pneumonia is defined as mention or diagnosis of pneumonia.
Baseline data represents the average number of people with COVID-19-like illness who are admitted to the hospital during this time of year based on historical counts. The average is based on the daily avg from the rolling same week (same day +/- 3 days) from the prior 3 years. Percent change data represents the change in count of people admitted compared to the previous day.
Data sources include all hospital admissions from emergency department visits in NYC. Data are collected electronically and transmitted to the NYC Health Department hourly. This dataset is updated daily.
All identifying health information is excluded from the dataset.

This dataset shows daily citywide counts of persons tested by nucleic acid amplification tests (NAAT, also known as a molecular test; e.g. a PCR test) for SARS-CoV-2 , counts of persons with positive tests, and the percent positivity. Also included is a calculation of the average percent positivity over a 7-day period.

NAAT tests work through direct detection of the virus’s genetic material, and typically involve collecting a nasal swab. These tests are highly accurate and recommended for diagnosing current COVID-19 infection. After specimen collection, molecular tests are processed in a laboratory, and results are electronically reported to the New York State (NYS) Electronic Clinical Laboratory Results System (ECLRS). Test results for NYC residents are then sent electronically to NYC DOHMH. There is typically a lag of a few days between when a specimen is collected and when a result is reported to NYC DOHMH.
Data is sourced from electronic laboratory reporting from NYS ECLRS.
All identifying health information is excluded from the dataset.

This dataset contains information on antibody testing for COVID-19: the number of people who received a test, the number of people with positive results, the percentage of people tested who tested positive, and the rate of testing per 100,000 people, stratified by week of testing. These data can also be accessed here: https://github.com/nychealth/coronavirus-data/blob/master/trends/antibody-by-week.csv

Exposure to COVID-19 can be detected by measuring antibodies to the disease in a person’s blood, which can indicate that a person may have had an immune response to the virus. Antibodies are proteins produced by the body’s immune system that can be found in the blood. People can test positive for antibodies after they have been exposed, sometimes when they no longer test positive for the virus itself. It is important to note that the science around COVID-19 antibody tests is evolving rapidly and there is still much uncertainty about what individual antibody test results mean for a single person and what population-level antibody test results mean for understanding the epidemiology of COVID-19 at a population level. These data only provide information on people tested. People receiving an antibody test do not reflect all people in New York City; therefore, these data may not reflect antibody prevalence among all New Yorkers. Increasing instances of screening programs further impact the generalizability of these data, as screening programs influence who and how many people are tested over time. Examples of screening programs in NYC include: employers screening their workers (e.g., hospitals), and long-term care facilities screening their residents.

In addition, there may be potential biases toward people receiving an antibody test who have a positive result because people who were previously ill are preferentially seeking testing, in addition to the testing of persons with higher exposure (e.g., health care workers, first responders.)

Rates were calculated using interpolated intercensal population estimates updated in 2019. These rates differ from previously reported rates based on the 2000 Census or previous versions of population estimates. The Health Department produced these population estimates based on estimates from the U.S. Census Bureau and NYC Department of City Planning.

Antibody tests are categorized based on the date of specimen collection and are aggregated by full weeks starting each Sunday and ending on Saturday. For example, a person whose blood was collected for antibody testing on Wednesday, May 6 would be categorized as tested during the week ending May 9. A person tested twice in one week would only be counted once in that week. This dataset includes testing data beginning April 5, 2020.

Data are updated daily, and the dataset preserves historical records and source data changes, so each extract date reflects the current copy of the data as of that date. For example, an extract date of 11/04/2020 and extract date of 11/03/2020 will both contain all records as they were as of that extract date. Without filtering or grouping by extract date, an analysis will almost certainly be miscalculating or counting the same values multiple times. To analyze the most current data, only use the latest extract date. Antibody tests that are missing dates are not included in the dataset; as dates are identified, these events are added. Lags between occurrence and report of cases and tests can be assessed by comparing counts and rates across multiple data extract dates.

For further details, visit:
• https://www1.nyc.gov/site/doh/covid/covid-19-data.page
• https://github.com/nychealth/coronavirus-data

This dataset shows the mosquito spraying events in NYC.

The Health Department monitors mosquito populations and applies pesticides when appropriate throughout the summer to reduce the number of mosquitoes and to minimize the risk of mosquito-borne diseases such as the West Nile Virus and the Zika Virus.

This dataset contains information about when and where mosquito spraying events occur in NYC. DOHMH sprays pesticides from trucks to kill adult mosquitoes (adulticiding) or to kill mosquito larvae (larviciding) in areas that have an increased risk of mosquito spreading disease. These events – in residential and non-residential areas – are carefully planned by DOHMH to minimize human exposure to the pesticides. DOHMH creates the spray event boundaries and stores them in a GIS. Each record represent the extent/boundaries of a spray treatment area. The spray events are not fixed, each year the locations, boundaries and extents are determined by a variety of factors throughout the mosquito season.

For the historical data, please visit this page.

This dataset contains information on antibody testing for COVID-19: the number of people who received a test, the number of people with positive results, the percentage of people tested who tested positive, and the rate of testing per 100,000 people, stratified by sex. These data can also be accessed here: https://github.com/nychealth/coronavirus-data/blob/master/totals/antibody-by-sex.csv Exposure to COVID-19 can be detected by measuring antibodies to the disease in a person’s blood, which can indicate that a person may have had an immune response to the virus. Antibodies are proteins produced by the body’s immune system that can be found in the blood. People can test positive for antibodies after they have been exposed, sometimes when they no longer test positive for the virus itself. It is important to note that the science around COVID-19 antibody tests is evolving rapidly and there is still much uncertainty about what individual antibody test results mean for a single person and what population-level antibody test results mean for understanding the epidemiology of COVID-19 at a population level.

These data only provide information on people tested. People receiving an antibody test do not reflect all people in New York City; therefore, these data may not reflect antibody prevalence among all New Yorkers. Increasing instances of screening programs further impact the generalizability of these data, as screening programs influence who and how many people are tested over time. Examples of screening programs in NYC include: employers screening their workers (e.g., hospitals), and long-term care facilities screening their residents.

In addition, there may be potential biases toward people receiving an antibody test who have a positive result because people who were previously ill are preferentially seeking testing, in addition to the testing of persons with higher exposure (e.g., health care workers, first responders.)

Rates were calculated using interpolated intercensal population estimates updated in 2019. These rates differ from previously reported rates based on the 2000 Census or previous versions of population estimates. The Health Department produced these population estimates based on estimates from the U.S. Census Bureau and NYC Department of City Planning.

Antibody tests are categorized based on the date of specimen collection and are aggregated by full weeks starting each Sunday and ending on Saturday. For example, a person whose blood was collected for antibody testing on Wednesday, May 6 would be categorized as tested during the week ending May 9. A person tested twice in one week would only be counted once in that week. This dataset includes testing data beginning April 5, 2020.

Data are updated daily, and the dataset preserves historical records and source data changes, so each extract date reflects the current copy of the data as of that date. For example, an extract date of 11/04/2020 and extract date of 11/03/2020 will both contain all records as they were as of that extract date. Without filtering or grouping by extract date, an analysis will almost certainly be miscalculating or counting the same values multiple times. To analyze the most current data, only use the latest extract date. Antibody tests that are missing dates are not included in the dataset; as dates are identified, these events are added. Lags between occurrence and report of cases and tests can be assessed by comparing counts and rates across multiple data extract dates.

For further details, visit:
• https://www1.nyc.gov/site/doh/covid/covid-19-data.page
• https://github.com/nychealth/coronavirus-data

Percentage of interviewed cryptosporidiosis case-patients by type of tap water exposure before disease onset, by Immune Status, New York City, 1995 - 2016

*Note: Determination of an association between exposure to possible risk factors for cryptosporidiosis and acquisition of cryptosporidiosis cannot be made without reference to a suitable control population (i.e., non-Cryptosporidium-infected controls).

Format of case interview form changed on 1/1/1997, 5/11/2001, 8/21/2002, and 4/26/2010.
From 1/1/1995 to 4/25/2010, case-patients were asked about Tap Water Exposure during the month before onset. Starting 04/26/2010, case-patients were asked about Tap Water Exposure during the 14 days before onset.

Year 2000 percentage of interviewed cryptosporidiosis cases does not include 14 cases associated with a point source exposure at a swimming pool in Florida.

For more information on Waterborne Disease Risk Assessment Annual reports, please visit http://www.nyc.gov/html/dep/html/drinking_water/wdrap.shtml

This dataset includes cooling tower regulatory inspection results from the NYC Health Department’s Office of Building Water Systems Oversight (BWSO).

The dataset includes results from two inspection types: cycle or non-cycle. Cycle inspections are regular compliance inspections conducted by BWSO to confirm adherence with cooling tower regulations. Non-cycle may include follow-up inspections or other regulatory inspections to evaluate public health risks.Cooling tower systems that are compliant at the time of inspection have the inspection date with blank values for the violation and citation columns. Building owners that are subject to financial penalties for a cited violation receive a notice of violation with a summons number, as shown in the dataset. The Office of Administrative Trial and Hearings (OATH) adjudicates the summons.

Hearing status and adjudication result are shown separately in the Cooling Tower Hearings dataset (a subset of the OATH Hearings Division Case Status dataset). The summons number in this dataset corresponds with the ticket number field in the Cooling Towers Hearings dataset.

The 2015 Child Health, Emotional Wellness, and Development Survey (CHEWDS) was a population-based telephone survey conducted by the Health Department. The survey provided robust data on the health of children aged 0 to 12 years in New York City, including citywide and borough estimates, on a broad range of topics from health care access to nutrition.
For more information see EpiQuery, https://a816-health.nyc.gov/hdi/epiquery/visualizations?PageType=ts&PopulationSource=CCHS&Topic=5&Subtopic=26

Annual requests for telephonic interpretation. In accordance with local and state laws and federal regulations, the New York City Health Department provides access to language services, free of charge and upon request, to all New Yorkers and collects this data accordingly.