How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

The Low- to Moderate-Income (LMI) New York State (NYS) Census Population Analysis dataset is resultant from the LMI market database designed by APPRISE as part of the NYSERDA LMI Market Characterization Study (https://www.nyserda.ny.gov/lmi-tool). All data are derived from the U.S. Census Bureau’s American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS) files for 2013, 2014, and 2015.

Each row in the LMI dataset is an individual record for a household that responded to the survey and each column is a variable of interest for analyzing the low- to moderate-income population.

The LMI dataset includes: county/county group, households with elderly, households with children, economic development region, income groups, percent of poverty level, low- to moderate-income groups, household type, non-elderly disabled indicator, race/ethnicity, linguistic isolation, housing unit type, owner-renter status, main heating fuel type, home energy payment method, housing vintage, LMI study region, LMI population segment, mortgage indicator, time in home, head of household education level, head of household age, and household weight.

The LMI NYS Census Population Analysis dataset is intended for users who want to explore the underlying data that supports the LMI Analysis Tool. The majority of those interested in LMI statistics and generating custom charts should use the interactive LMI Analysis Tool at https://www.nyserda.ny.gov/lmi-tool. This underlying LMI dataset is intended for users with experience working with survey data files and producing weighted survey estimates using statistical software packages (such as SAS, SPSS, or Stata).

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

Some college, associate's degree Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Pittsford, New York by age, education, race, gender, work experience and more.

Some college, associate's degree Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Riverhead, New York by age, education, race, gender, work experience and more.

Some other race Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Newark, New York by age, education, race, gender, work experience and more.

Some other race Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Marcellus, New York by age, education, race, gender, work experience and more.

Some college, associate's degree Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in Dutchess County, New York by age, education, race, gender, work experience and more.

Some college, associate's degree Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in Warren County, New York by age, education, race, gender, work experience and more.

Some college, associate's degree Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Goshen, New York by age, education, race, gender, work experience and more.

Some other race Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Washingtonville, New York by age, education, race, gender, work experience and more.

Some college, associate's degree Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Yorktown Heights, New York by age, education, race, gender, work experience and more.

Some college, associate's degree Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Mount Ivy, New York by age, education, race, gender, work experience and more.

Some other race Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Greene, New York by age, education, race, gender, work experience and more.

Some college, associate's degree Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Hewlett Harbor, New York by age, education, race, gender, work experience and more.

Worked full-time, year-round in the past 12 months Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Hillcrest, New York by age, education, race, gender, work experience and more.

Some college, associate's degree Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Victor, New York by age, education, race, gender, work experience and more.

Some college, associate's degree Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Pleasantville, New York by age, education, race, gender, work experience and more.

High school graduate (includes equivalency) Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in New York, New York by age, education, race, gender, work experience and more.

Some college, associate's degree Poverty Rate Statistics for 2022. This is part of a larger dataset covering poverty in Marcellus, New York by age, education, race, gender, work experience and more.

Less than high school graduate Poverty Rate Statistics for 2023. This is part of a larger dataset covering poverty in Suffolk County, New York by age, education, race, gender, work experience and more.