Story page with maps, charts explaining the Vaccine Rates by PA State Senate, PA State House and U.S. Congressional Districts.

EDDIE is an interactive health statistics dissemination web tool where you can create customized data tables for various health related data.

The EDDIE system was developed to empower public health professionals by enhancing and expanding upon their ability to use data and statistics to drive public health policy and program decisions. Users of the EDDIE system must agree to make no attempt to identify an individual, and must agree to notify the Pennsylvania Department of Health, Division of Health Informatics immediately if an individual is inadvertently identified along with an explanation on how this occurred.

The following datasets are available:
•Air Quality
•Behavioral Risk Factor Surveillance System (BRFSS)
•Birth Defects
•Births
•Cancer Incidence
•Carbon Monoxide Poisoning Mortality
•Childhood Cancer Incidence
•Childhood Lead Poisoning
•Children Less Than Age 5 Living in Poverty
•Communicable Diseases (other than STDs)
•Deaths
•Drinking Water Quality
•Hospitalizations
•Housing by Year Built
•Infant Deaths
•Population
•Reported Pregnancies
•Reproductive Health Outcomes
•Sexually Transmitted Diseases (STDs)

EDDIE is the Pennsylvania Department of Health's primary tool for data dissemination. This is also the replacement for our legacy EpiQMS system, which has been disabled. We are working to add additional functionality to the EDDIE system in the future, including charts, county assessments, and additional maps. We are also planning to add new datasets in the coming years.

​DISCLAIMER: If you use any of the data provided, please include the following statement in any publication or release:
These data were provided by the Division of Health Informatics, Pennsylvania Department of Health. The Department specifically disclaims responsibility for any analyses, interpretations, or conclusions. Users of this data agree to make no attempt to identify an individual, and agree to notify the Division of Health Informatics, Pennsylvania Department of Health immediately if an individual is inadvertently identified along with an explanation of how this occurred.

This View is created to group Death counts by County and by Month.
This dataset contains aggregate death data at the state and county level for Pennsylvania residents. The data are displayed by county, date, death counts, averages, rates based on population. Pennsylvania statewide numbers are listed with Pennsylvania named as the county for the statewide totals. Do not add up the entire file (all rows) or counts will be duplicated.
Data will be updated between 9-11 am every day.

This dataset contains aggregate death data at the state and county level for Pennsylvania residents. The data are displayed by year, race/ethnicity, gender, age group and cause of death.

This dataset contains aggregate COVID-19 case counts and rates by date of first report for all counties in Pennsylvania and for the state as a whole. Counts include both confirmed and probable cases as defined by the Council of State and Territorial Epidemiologists (CSTE). At present, a person is counted as a case only once. Note that case counts by date of report are influenced by a variety of factors, including but not limited to testing availability, test ordering patterns (such as day of week patterns), labs reporting backlogged test results, and mass screenings in nursing homes, workplaces, schools, etc. Case reports received without a patient address are assigned to the county of the ordering provider or facility based on provider zip code. Cases reported with a residential address that does not match to a known postal address per the commonwealth geocoding service are assigned to a county based on the zip code of residence. Many zip codes cross county boundaries so there is some degree of misclassification of county. All counts may change on a daily basis due to reassignment of jurisdiction, removal of duplicate case reports, correction of errors, and other daily data cleaning activities. Downloaded data represents the best information available as of the previous day.

Data will be updated between 9-11 am every day.

A federal government website managed and paid for by the U.S. Centers for Medicare & Medicaid Services.
7500 Security Boulevard, Baltimore, MD 21244

The intent of the data is to provide an overview of cumulative state and federal expenditures dedicated to COVID-19 preparedness and response. Where applicable, detail information is provided at the agency/fund/commitment-item level. Scope of data includes expenditures attributed to federal funding provided through the Coronavirus Aid, Relief, and Economic Security Act (“CARES Act”) (PL 116-136), the Coronavirus Preparedness and Response Supplemental Appropriations Act (PL 116-123), the Families First Coronavirus Response Act (PL 116-127), and the Robert T. Stafford Disaster Relief and Emergency Assistance Act (“Stafford Act”)(PL 100-707); state expenditures attributed to the Governor’s disaster proclamation; and all other state expenditures incurred in response to the COVID-19 pandemic. Due to non-applicability and/or immateriality, state expenditures uniquely assigned as matching funds for federal awards are not included within the detail. In most circumstances, federal matching requirements were waived in response to COVID-19.

Expenditure data contained within the dataset is extracted from the Funds Management (FM) module of the Commonwealth’s accounting system (SAP). Expenditures, reported as cumulative through the end of the defined reporting period, are generally recognized and recorded when a liability to make a payment is incurred, regardless of when the cash disbursement is to be made. Unique account assignments have been established and utilized independently by each Commonwealth agency/program to distinguish expenditures attributed to the COVID-19 pandemic.

Please note that the data reported may not reconcile directly to spending reported to the federal government for the same period due to differences in how spending is grouped or classified, or due to specific data submission requirements.

The CDC is one of the major operating components of the Department of Health and Human Services. View CDC’s Official Mission Statements/Organizational Charts to learn more about CDC′s organizational structure.

CDC works 24/7 to protect America from health, safety and security threats, both foreign and in the U.S. Whether diseases start at home or abroad, are chronic or acute, curable or preventable, human error or deliberate attack, CDC fights disease and supports communities and citizens to do the same.

CDC increases the health security of our nation. As the nation’s health protection agency, CDC saves lives and protects people from health threats. To accomplish our mission, CDC conducts critical science and provides health information that protects our nation against expensive and dangerous health threats, and responds when these arise.

The home of Medicaid and CHIP open data provided by the Federal Government.
Conduct research and design data visualizations using open data from Medicaid and the Children's' Health Insurance Program (CHIP)

The American Community Survey (ACS) helps local officials, community leaders, and businesses understand the changes taking place in their communities. It is the premier source for detailed population and housing information about our nation. This dataset provides estimates by county for Health Insurance Coverage and is summarized from summary table S2701: SELECTED CHARACTERISTICS OF HEALTH INSURANCE COVERAGE IN THE UNITED STATES. The 5-year estimates are used to provide detail on every county in Pennsylvania and includes breakouts by Age, Gender, Race, Ethnicity, Household Income, and the Ratio of Income to Poverty.

An blank cell within the dataset indicates that either no sample observations or too few sample observations were available to compute the statistic for that area.

Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level.

While an ACS 1-year estimate includes information collected over a 12-month period, an ACS 5-year estimate includes data collected over a 60-month period. In the case of ACS 1-year estimates, the period is the calendar year (e.g., the 2015 ACS covers the period from January 2015 through December 2015).

In the case of ACS multiyear estimates, the period is 5 calendar years (e.g., the 2011–2015 ACS estimates cover the period from January 2011 through December 2015). Therefore, ACS estimates based on data collected from 2011–2015 should not be labeled “2013,” even though that is the midpoint of the 5-year period.

Multiyear estimates should be labeled to indicate clearly the full period of time (e.g., “The child poverty rate in 2011–2015 was X percent.”). They do not describe any specific day, month, or year within that time period.