This dataset was developed by the Research & Analytics Group at the Atlanta Regional Commission using data from the U.S. Census Bureau across all standard and custom geographies at statewide summary level where applicable. For a deep dive into the data model including every specific metric, see the ACS 2017-2021 Data Manifest. The manifest details ARC-defined naming conventions, field names/descriptions and topics, summary levels; source tables; notes and so forth for all metrics. Find naming convention prefixes/suffixes, geography definitions and user notes below.Prefixes:NoneCountpPercentrRatemMedianaMean (average)tAggregate (total)chChange in absolute terms (value in t2 - value in t1)pchPercent change ((value in t2 - value in t1) / value in t1)chpChange in percent (percent in t2 - percent in t1)sSignificance flag for change: 1 = statistically significant with a 90% CI, 0 = not statistically significant, blank = cannot be computedSuffixes:_e21Estimate from 2017-21 ACS_m21Margin of Error from 2017-21 ACS_e102006-10 ACS, re-estimated to 2020 geography_m10Margin of Error from 2006-10 ACS, re-estimated to 2020 geography_e10_21Change, 2010-21 (holding constant at 2020 geography)GeographiesAAA = Area Agency on Aging (12 geographic units formed from counties providing statewide coverage)ARC21 = Atlanta Regional Commission modeling area (21 counties merged to a single geographic unit)ARWDB7 = Atlanta Regional Workforce Development Board (7 counties merged to a single geographic unit)BeltLine (buffer)BeltLine Study (subareas)Census Tract (statewide)CFGA23 = Community Foundation for Greater Atlanta (23 counties merged to a single geographic unit)City (statewide)City of Atlanta Council Districts (City of Atlanta)City of Atlanta Neighborhood Planning Unit (City of Atlanta)City of Atlanta Neighborhood Planning Unit STV (3 NPUs merged to a single geographic unit within City of Atlanta)City of Atlanta Neighborhood Statistical Areas (City of Atlanta)City of Atlanta Neighborhood Statistical Areas E02E06 (2 NSAs merged to single geographic unit within City of Atlanta)County (statewide)Georgia House (statewide)Georgia Senate (statewide)MetroWater15 = Atlanta Metropolitan Water District (15 counties merged to a single geographic unit)Regional Commissions (statewide)SPARCC = Strong, Prosperous And Resilient Communities ChallengeState of Georgia (single geographic unit)Superdistrict (ARC region)US Congress (statewide)UWGA13 = United Way of Greater Atlanta (13 counties merged to a single geographic unit)WFF = Westside Future Fund (subarea of City of Atlanta)ZIP Code Tabulation Areas (statewide)The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent. The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2017-2021). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available. For further explanation of ACS estimates and margin of error, visit Census ACS website.Source: U.S. Census Bureau, Atlanta Regional CommissionDate: 2017-2021Data License: Creative Commons Attribution 4.0 International (CC by 4.0)Link to the data manifest: https://garc.maps.arcgis.com/sharing/rest/content/items/34b9adfdcc294788ba9c70bf433bd4c1/data

This layer was developed by the Research & Analytics Group of the Atlanta Regional Commission, using data from the U.S. Census Bureau’s American Community Survey 5-year estimates for 2013-2017, to show total population and change by ARC 20 County in the Atlanta region.

The user should note that American Community Survey data represent estimates derived from a surveyed sample of the population, which creates some level of uncertainty, as opposed to an exact measure of the entire population (the full census count is only conducted once every 10 years and does not cover as many detailed characteristics of the population). Therefore, any measure reported by ACS should not be taken as an exact number – this is why a corresponding margin of error (MOE) is also given for ACS measures. The size of the MOE relative to its corresponding estimate value provides an indication of confidence in the accuracy of each estimate. Each MOE is expressed in the same units as its corresponding measure; for example, if the estimate value is expressed as a number, then its MOE will also be a number; if the estimate value is expressed as a percent, then its MOE will also be a percent.

The user should also note that for relatively small geographic areas, such as census tracts shown here, ACS only releases combined 5-year estimates, meaning these estimates represent rolling averages of survey results that were collected over a 5-year span (in this case 2013-2017). Therefore, these data do not represent any one specific point in time or even one specific year. For geographic areas with larger populations, 3-year and 1-year estimates are also available.

For further explanation of ACS estimates and margin of error, visit Census ACS website.

Naming conventions:

Prefixes:

None

Count

p

Percent

r

Rate

m

Median

a

Mean (average)

t

Aggregate (total)

ch

Change in absolute terms (value in t2 - value in t1)

pch

Percent change ((value in t2 - value in t1) / value in t1)

chp

Change in percent (percent in t2 - percent in t1)

Suffixes:

None

Change over two periods

_e

Estimate from most recent ACS

_m

Margin of Error from most recent ACS

_00

Decennial 2000

Attributes:

SumLevel

Summary level of geographic unit (e.g., County, Tract, NSA, NPU, DSNI, SuperDistrict, etc)

GEOID

Census tract Federal Information Processing Series (FIPS) code

NAME

Name of geographic unit

Planning_Region

Planning region designation for ARC purposes

Acres

# Area, Acres, 2017

SqMi

# Area, square miles, 2017

County

County identifier (combination of Federal Information Processing Series (FIPS) codes for state and county)

CountyName

County Name

TotPop_e

# Total population, 2017

TotPop_m

# Total population, 2017 (MOE)

rPopDensity

Population density (people per square mile), 2017

last_edited_date

Last date the feature was edited by ARC

Source: U.S. Census Bureau, Atlanta Regional Commission

Date: 2013-2017

For additional information, please visit the Census ACS website.

The 2020 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the urban footprint. There are 2,644 Urban Areas (UAs) in this data release with either a minimum population of 5,000 or a housing unit count of 2,000 units. Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. This file includes revisions made to the 2020 Census New Orleans, LA Urban Area where the territory originally delineated as the 2020 Census Laplace--Lutcher--Gramercy, LA Urban Area was combined with the 2020 Census New Orleans, LA Urban Area to form the current New Orleans, LA Urban Area. This file includes revisions made to the 2020 Census Atlanta, GA Urban Area and Gainesville, GA Urban Area, where some urban territory originally designated to the Gainesville, GA Urban Area was reassigned to the Atlanta, GA Urban Area.

Abstract (en): The Atlanta Household Travel Survey sampled 8,069 households in the thirteen-county metropolitan Atlanta region. The survey relied on the willingness of area residents to complete diary records of all travel for a 48-hour period. Household recruitment for the study was conducted through the use of a recruitment interview, in which respondents were informed of the survey, its purpose, and the obligation of all household members to complete the survey. The 8,069 participating households, when weighted, represent 21,323 persons, 14,449 vehicles, and 126,127 places visited during the 48-hour travel period. Data were collected on trip generation, trip distribution, modal choice, transit use, neighborhood preferences, and trip activities. Household data includes demographic information such as household size, household vehicles, dwelling type, home ownership status, tenure, and computer ownership. Also included are summary statistics regarding the number of workers, students, and trips made during the 48-hour travel period. Person data includes demographic information about the household members, student data, employment data for first and second jobs, and health related information. The objective of the household travel survey was to collect information on work and non-work travel behavior. This includes trip generation, trip distribution, and modal choice data as well as data on transit use, neighborhood preferences, health and activity. The Atlanta Household Travel Survey utilizes both weighting and expansion factors to (1) adjust the sample data to match population parameters, and (2) expand trip information to all households in the survey area. This includes the counties of Cherokee, Clayton, Cobb, Coweta, Dekalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Henry, Paulding, and Rockdale. For additional information on weights, please see the "Weighting and Expansion" section of the Final Report. Response Rates: The response rate was calculated for recruitment, and for retrieval. The overall response rate was determined by multiplying the two resultant rates. The recruitment rate for this study was 44.8 percent, the retrieval rate was 67.8 percent, and the overall response rate was 30.4 percent. All households within the 13-county region of metropolitan Atlanta, Georgia. Smallest Geographic Unit: county The sample for the Atlanta Household Travel Survey is intended to optimize the production of data with sufficient observations for all relevant levels in three variables: net residential density level (NRDL), household size, and household income. The survey employed a list assisted random digit dial design with a probability sample selection process that selected households for inclusion in the study. The major requirement for probability samples was that the relative probability (or chance) of any given household in the universe being included in the sample was known. Once the sampling procedure was determined, the selection of specific households for inclusion in the sample was left entirely to chance. The sample included both listed and unlisted households. The definition of a completed household was one in which travel and activity data were collected from all household members age five and older. A total of 8,069 households met this criterion. The type of probability sampling employed was stratified sampling in which the sample goal was to have 20 percent of the sample in each of the five preset NRDL categories. Current income data was unknown at the time of the study and the relationship between NRDL and household size was unknown, hence these two variables were not used to stratify the sample. Overall sample goals for the Atlanta Household Travel Survey include the following: (1) Inclusion of high density areas; (2) County level representation; (3) Low income representation; and (4) Minority representation. computer-assisted telephone interview (CATI), mail questionnaireThis collection has not been processed by ICPSR. The deposited files are being released as they were received from the Principal Investigator. For additional information regarding the Atlanta Household Travel Survey, please visit the Metropolitan Travel Survey Archive Web site.

Population characteristics (patient level- and area level variables).

Dataset of species (MRSA v. MSSA), stratified by early and late periods, along with associated location coordinates (latitude and longitude) used to create MaxEnt maps. (CSV)

Urban streams and rivers have chronic bacteria contamination in the United States, coming from multiple sources, following a variety of flowpaths to the waterway, and with differing downstream fates. Bacteria from human sewage, estimated through measures of Escherichia coli, pose the highest risk to human health. We analyzed four years of E. coli monitoring by community science groups to look for spatial and temporal drivers of E. coli densities in watersheds in the urban core of metro Atlanta, GA, with a wide range of racial and economic diversity as well as persistent patterns of segregation and racialized inequality. These watersheds are spaces of environmental injustice, with disproportionate impacts for lower-wealth and predominantly Black communities from flooding, soil contamination, and air pollution. While there were minimal differences in E. coli between watersheds with different Black and white populations, individual sites could be identified as hot and cold spots of contamination. Storm events increased E. coli at most sites, indicating a combination of runoff and sediment-sorbed E. coli explains about 50% of the temporal variability in E. coli densities. Long-term median E. coli levels were not strongly correlated to land cover or socio-demographic characteristics of the contributing watershed, but E. coli variability was lower in less densely urbanized areas. Temporal and spatial distributions of E. coli are controlled by complex interactions between sources and hydrologic transport that vary across watersheds. While direct correlations to racial demographics were not observed, the interactions between sewage as one environmental harm and the many others (air quality, soil quality, prison-industrial complex, etc.) present in minority and low-income urban communities emphasize the oversized burden environmental justice communities carry.

Anonymized and limited dataset of patients enrolled in the study, stratified by the type of Staphylococcus aureus infection (CO-MRSA and CO-MSSA) and date (year) of infection. (XLSX)

Percent contribution of variables for 2002–2005 CO-MRSA, 2002–2005 CO-MSSA, 2006–16 CO-MRSA, and 2006–16 CO-MSSA.

Patient level characteristics, early (2002–2005) and late (2006–2016) periods.

Multilevel model to assess risks for CO-MRSA compared to CO-MSSA.