The population density of West Laurel, MD was 1,982 in 2011.

Population Density

Population Density is computed by dividing the total population by Land Area Per Square Mile.

Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API - Notes:

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Geographic and Population Datasets Involving West Laurel, MD

  • API

    Choose Maryland: Compare Counties - Demographics

    opendata.maryland.gov | Last Updated 2024-07-09T17:43:22.000Z

    Population profile - total, rate of change, age, and density.

  • API

    ICC Vehicle Volume Data

    opendata.maryland.gov | Last Updated 2023-04-12T13:23:47.000Z

    This dataset shows the number of vehicles that have passed under a gantry on that particular day. This dataset does not show trips, it only shows segments. Segments are compiled to make trips. There are 10 gantries on the InterCounty Connector (ICC) and 5 interchanges. The eastbound gantries are 101, 105, 107, 109, 113, and the westbound gantries are 102, 106, 108, 110, 114. The dataset has a column for each gantry going east and west, then a total for each gantry. The ICC is an all electronic tolling road which opened February 2011. The first opening was a partial opening, with only the first interchange being available for use.There was a free period from February 23, 2011 through March 6, 2011. The rest of the ICC opened in November 2011, and there was another free period from November 22, 2011 through December 4, 2011. There are a few days where a low number of traffic passed under gantries (rows 196,198, 269,271...), these were either testing periods or construction vehicles.

  • API

    Choose Maryland: Compare States - Demographics

    opendata.maryland.gov | Last Updated 2024-07-09T17:45:48.000Z

    Population profile - total, rate of change, age, and density.

  • API

    Maryland Resident Population Per Square Mile: 2010-2020

    opendata.maryland.gov | Last Updated 2024-03-11T18:51:03.000Z

    Resident population density for Maryland and Jurisdictions per square mile from 2010 to 2020. Source: U.S. Bureau of Census

  • API

    MD COVID-19 - Cases per 100K population, by jurisdiction

    opendata.maryland.gov | Last Updated 2024-10-01T15:24:18.000Z

    <b>Note:</b> Starting April 27, 2023 updates change from daily to weekly. <b>Summary</b> The rate of confirmed COVID-19 cases among Marylanders per 100,000 people in each Maryland jurisdiction. <b>Description</b> The MD COVID-19 cases per 100K population, by jurisdiction layer is the rate of confirmed daily COVID-19 cases among Marylanders per 100,000 people in each Maryland jurisdiction. This rate is a 7-day average, calculated using the CasesByCounty layer and the 2019 estimated county populations (Maryland Department of Planning). Any negative value may be attributed to changes in reporting by jurisdiction. <b>Terms of Use</b> The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

  • API

    MD COVID-19 - Cases per 100K population, statewide

    opendata.maryland.gov | Last Updated 2024-10-01T15:23:56.000Z

    <b>Note:</b> Starting April 27, 2023 updates change from daily to weekly. <b>Summary</b> The rate of confirmed COVID-19 cases among Marylanders per 100,000 people statewide. <b>Description</b> The MD COVID-19 cases per 100K population, statewide layer is the rate of confirmed daily COVID-19 cases among Marylanders per 100,000 people statewide. This rate is a 7-day average, calculated using the sum of the CasesByCounty layer and the 2019 estimated county populations (Maryland Department of Planning). <b>Terms of Use</b> The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

  • API

    MD COVID-19 - Vaccination Percent Age Group Population

    opendata.maryland.gov | Last Updated 2023-04-27T15:26:50.000Z

    Regarding all Vaccination Data The date of Last Update is 4/21/2023. Additionally on 4/27/2023 several COVID-19 datasets were retired and no longer included in public COVID-19 data dissemination. See this link for more information https://imap.maryland.gov/pages/covid-data <b>Summary</b> The cumulative number of COVID-19 vaccinations percent age group population: 16-17; 18-49; 50-64; 65 Plus. <b>Description</b> COVID-19 - Vaccination Percent Age Group Population data layer is a collection of COVID-19 vaccinations that have been reported each day into ImmuNet. COVID-19 is a disease caused by a respiratory virus first identified in Wuhan, Hubei Province, China in December 2019. COVID-19 is a new virus that hasn't caused illness in humans before. Worldwide, COVID-19 has resulted in thousands of infections, causing illness and in some cases death. Cases have spread to countries throughout the world, with more cases reported daily. The Maryland Department of Health reports daily on COVID-19 cases by county. <b>Terms of Use</b> The Spatial Data, and the information therein, (collectively the Data) is provided as is without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata. This map is for planning purposes only. MEMA does not guarantee the accuracy of any forecast or predictive elements.

  • API

    MD COVID-19 - Total Population Tested by County

    opendata.maryland.gov | Last Updated 2022-08-23T10:34:42.000Z

    <b>Summary</b> This layer is deprecated (Last updated 3/14/2022). The total number of residents who have been administered at least one COVID-19 test in each Maryland jurisdiction. <b>Description</b> Data represent the number of Maryland residents, both in number and by percent of the population, who have been tested for COVID-19 at least once each Maryland jurisdiction. <b>Terms of Use</b> The Spatial Data, and the information therein, (collectively the "Data") is provided "as is" without warranty of any kind, either expressed, implied, or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted, nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct, indirect, incidental, consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data, nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

  • API

    NYCHA Development Data Book

    data.cityofnewyork.us | Last Updated 2024-05-13T15:53:04.000Z

    Contains the main body of the "Development Data Book". The Development Data Book lists all of the Authority's Developments alphabetically and includes information on the development identification numbers, program and construction type, number of apartments and rental rooms, population, number of buildings and stories, street boundaries, and political districts.

  • API

    NCHS - Drug Poisoning Mortality by County: United States

    data.cdc.gov | Last Updated 2022-03-29T21:27:25.000Z

    This dataset contains model-based county estimates for drug-poisoning mortality. Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are defined as having ICD–10 underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent). Estimates are based on the National Vital Statistics System multiple cause-of-death mortality files (1). Age-adjusted death rates (deaths per 100,000 U.S. standard population for 2000) are calculated using the direct method. Populations used for computing death rates for 2011–2016 are postcensal estimates based on the 2010 U.S. census. Rates for census years are based on populations enumerated in the corresponding censuses. Rates for noncensus years before 2010 are revised using updated intercensal population estimates and may differ from rates previously published. Death rates for some states and years may be low due to a high number of unresolved pending cases or misclassification of ICD–10 codes for unintentional poisoning as R99, “Other ill-defined and unspecified causes of mortality” (2). For example, this issue is known to affect New Jersey in 2009 and West Virginia in 2005 and 2009 but also may affect other years and other states. Drug poisoning death rates may be underestimated in those instances. Smoothed county age-adjusted death rates (deaths per 100,000 population) were obtained according to methods described elsewhere (3–5). Briefly, two-stage hierarchical models were used to generate empirical Bayes estimates of county age-adjusted death rates due to drug poisoning for each year. These annual county-level estimates “borrow strength” across counties to generate stable estimates of death rates where data are sparse due to small population size (3,5). Estimates for 1999-2015 have been updated, and may differ slightly from previously published estimates. Differences are expected to be minimal, and may result from different county boundaries used in this release (see below) and from the inclusion of an additional year of data. Previously published estimates can be found here for comparison.(6) Estimates are unavailable for Broomfield County, Colorado, and Denali County, Alaska, before 2003 (7,8). Additionally, Clifton Forge County, Virginia only appears on the mortality files prior to 2003, while Bedford City, Virginia was added to Bedford County in 2015 and no longer appears in the mortality file in 2015. These counties were therefore merged with adjacent counties where necessary to create a consistent set of geographic units across the time period. County boundaries are largely consistent with the vintage 2005-2007 bridged-race population file geographies, with the modifications noted previously (7,8). REFERENCES 1. National Center for Health Statistics. National Vital Statistics System: Mortality data. Available from: http://www.cdc.gov/nchs/deaths.htm. 2. CDC. CDC Wonder: Underlying cause of death 1999–2016. Available from: http://wonder.cdc.gov/wonder/help/ucd.html. 3. Rossen LM, Khan D, Warner M. Trends and geographic patterns in drug-poisoning death rates in the U.S., 1999–2009. Am J Prev Med 45(6):e19–25. 2013. 4. Rossen LM, Khan D, Warner M. Hot spots in mortality from drug poisoning in the United States, 2007–2009. Health Place 26:14–20. 2014. 5. Rossen LM, Khan D, Hamilton B, Warner M. Spatiotemporal variation in selected health outcomes from the National Vital Statistics System. Presented at: 2015 National Conference on Health Statistics, August 25, 2015, Bethesda, MD. Available from: http://www.cdc.gov/nchs/ppt/nchs2015/Rossen_Tuesday_WhiteOak_BB3.pdf. 6. Rossen LM, Bastian B, Warner M, and Khan D. NCHS – Drug Poisoning Mortality by County: United States, 1999-2015. Available from: https://data.cdc.gov/NCHS/NCHS-Drug-Poisoning-Mortality-by-County-United-Sta/pbkm-d27e. 7. National Center for Health Statistics. County geog