The cost of living index of Philadelphia Metro Area (PA-NJ-DE-MD) was 106 for other in 2016.

Cost of Living

Overall Cost of Living

Cost of Goods

Cost of Rents

Other Costs

The cost of living index measures the difference in the price levels of goods and services across regions. The average cost of living index in the U.S. is 100, with higher values corresponding to costlier goods and services. Data is available for U.S. states and metropolitan areas.

Above charts are based on data from the U.S. Bureau of Economic Analysis | Data Source | ODN Dataset | API - Notes:

1. ODN datasets and APIs are subject to change and may differ in format from the original source data in order to provide a user-friendly experience on this site.

2. To build your own apps using this data, see the ODN Dataset and API links.

3. If you use this derived data in an app, we ask that you provide a link somewhere in your applications to the Open Data Network with a citation that states: "Data for this application was provided by the Open Data Network" where "Open Data Network" links to Where an application has a region specific module, we ask that you add an additional line that states: "Data about REGIONX was provided by the Open Data Network." where REGIONX is an HREF with a name for a geographical region like "Seattle, WA" and the link points to this page URL, e.g.

Economy and Cost of Living Datasets Involving Philadelphia Metro Area (PA-NJ-DE-MD)

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    Park and Ride Locations Current Transportation | Last Updated 2019-01-17T14:36:56.000Z

    PennDOT Official Park and Ride information that is currently available. This is not all inclusive.

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    Newly Identified Confirmed Chronic Hepatitis C Age 15-34 Year 2007-2016 Health | Last Updated 2018-09-20T14:30:44.000Z

    This data set provides an estimate of the number of people aged 15-34 years with newly identified confirmed chronic (or past/present) hepatitis C infection, by county and by year. The dataset is limited to persons aged 15 to 34 because hepatitis C infection is usually asymptomatic for decades after infection occurs. Cases are usually identified because they have finally become symptomatic, or they were screened. Until very recently, screening for hepatitis C was not routinely performed. This makes it very challenging to identify persons with recent infection. Limiting the age of newly identified patients to 15-34 years makes it more likely that the cases included in the dashboard were infected fairly recently. It is not meant to imply that the opioid crisis’ effect on hepatitis C transmission is limited to younger people. The process by which case counts are determined is as follows: Case reports, which include lab test results and address data, are sent to Pennsylvania’s electronic disease surveillance system (PA-NEDSS). Confirmation status is determined by public health investigators who evaluate test results against the CDC case definition for hepatitis C in place for the year in which the patient was first reported ( Reportable disease data, including hepatitis C, is extracted from PA-NEDSS, combined with similar data sent by the Philadelphia Department of Public Health (PDPH, which uses a separate surveillance system), and sent to CDC. Case data sent to CDC (from PA-NEDSS and PDPH combined) are used to create a statewide reportable disease dataset. This statewide file was used to generate the dashboard dataset. Note that the term that CDC has used to denote persons with hepatitis C infection that is not known to be acute has switched back and forth between “Hepatitis C, past or present” and “Hepatitis C, chronic” over the past several years. The CDC case definition for hepatitis C, chronic (or past or present) changed in 2005, 2010, 2011, 2012, and 2016. Persons reported as confirmed in one year may not have been considered confirmed in another year. For example, patients with a positive radioimmunoblot assay (RIBA) or elevated enzyme immunoassay (EIA) signal-to-cutoff level were counted as confirmed in 2012, but not counted as confirmed in 2016. Data sent to CDC’s National Notifiable Disease Surveillance System use a measure for aggregating cases by year called the MMWR year. The MMWR, or the Morbidity and Mortality Weekly Report, is an official publication by CDC and the means by which CDC has historically presented aggregated case count data. Since data in the MMWR are presented by week, the MMWR year always starts on the Sunday closest to Jan 1 and ends on the Saturday closest to Dec 31. The most recent year for which case counts are finalized is 2016. Annual case counts are finalized in May of the following year. The patient zip code, as submitted to PA-NEDSS, is used to determine the case’s county of residence at the time of initial case report. In some instances, the patient zip code is unavailable. In those circumstances, the zip code of the provider that ordered the lab test is used as a proxy for patient zip code. Users should note that the state prison system routinely screens all incoming inmates for hepatitis C. If these inmates are determined to be confirmed cases, they are assigned to the county in which they were incarcerated when their confirmed hepatitis C was first identified. Hepatitis C case counts in counties with state prisons should be interpreted cautiously in light of this enhanced screening activity.

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    Safe Schools Drug and Alcohol Use SY 2012 - Current County Education | Last Updated 2019-03-07T16:27:32.000Z

    This dataset contains summary information by county on Incidents involving Drug and Alcohol reported use in Schools. School categories are Public School, Charter, Intermediate, Vo-Tech, Non-Public and other. The data count fields are suppressed when less than 11. The data and more information is also published and searchable online on the website under School Safety. Here are the infraction codes and definitions that are utilized within this report as found within appendix Z of the PIMS manual:

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    Estimated Prevalence and New Diagnoses of HIV and HIV among Injection Drug Users by County (2012-2016) Health | Last Updated 2018-09-20T14:31:56.000Z

    This data set provides an estimate of the number of people living with Human Immunodeficiency Virus (HIV) Disease at the end of each year for 2012 through 2016 and the number of these persons who have injection drug use identified as the primary risk for having acquired the infection. The data sets also provides the number of new diagnoses of HIV Disease by county among all persons and among those with injection drug identified as the primary risk. These data are derived through HIV surveillance activities of the Pennsylvania Department of Health. Laboratories and providers are required to report HIV test results for all individuals with a result that indicates the presence of HIV infection. These include detectable viral load results and CD4 results below 200 cells. These data are reported electronically to the Pennsylvania National Electronic Disease Surveillance System. The most recent patient address information obtained from all reports (both HIV and non-HIV reports) is used to identify last known county of residence in 2016. Cases are also matched to lists that identify individuals who have been reported to be living outside of Pennsylvania by the US Centers for Disease Control and Prevention (CDC) to remove cases that are presumed to have moved from Pennsylvania. Address data for Philadelphia County cases are extracted from the Pennsylvania enhanced HIV/AIDS Reporting System. IDU: use of non-prescribed injection drugs (e.g., heroin, fentanyl, cocaine, etc.) HIV Disease: Confirmed infection with the Human Immunodeficiency Virus (HIV). Acquired Immunodeficiency Syndrome (AIDS) is a stage of HIV Disease marked by a low CD4 count and/or certain co-morbid conditions.

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    Naloxone First Responders Program 2017 - Current County Commission on Crime and Delinquency | Last Updated 2019-04-03T12:29:20.000Z

    This data contains information regarding Naloxone distributed statewide through the Naloxone for First Responders program. The dataset includes the number of doses of naloxone that have been distributed to each county, the number of doses used, the number of individuals on whom naloxone was used and the number of overdose reversals. In addition, those same datapoints are separated out by the type of first responders who have received and/or used naloxone.