Analyzing Patterns of COVID-19

.. as COVID-19 impacts our demographics, economy and way of life, we look for answers about where we are and what lies ahead.  Here we review data on COVID-19 incidence and tools to analyze those data. In the coming days, weeks, we plan to augment these tools and data. See more below.  See related Web section for more detail.

Use new resources to examine/analyze patterns of COVID-19 incidence in context of related demographic-economic characteristics. Resources include the narrative/interpretative portion, interactive table and GIS tools and project/files. Data and tools are updated daily. There is no fee to use any of these resources.

COVID-19 Incidence by County in the Atlanta Metro Area
The following graphic shows patterns of COVID-19 incidence (number of cases per 1,000 population) by county. See color patterns in the inset legend. This view shows counties labeled with name and number of confirmed COVID-19 cases. Use the GIS project described below to create variations of this view and develop similar views for any metro.

.. view developed with ProximityOne CV XE GIS and related GIS project.

The GIS resources and interactive table below makes use of the COVID-19 confirmed cases data updated daily by the New York Times. See more about the New York Times U.S. tracking page.

COVID-19 Incidence — U.S. by County
Similar to the above view, the following graphic shows patterns of COVID-19 incidence (number of cases per 1,000 population) by county for the U.S. See color patterns in the inset legend. This view shows counties labeled with name and number of confirmed COVID-19 cases. Use the GIS project described below to create variations of this view and develop similar views for any metro. Click graphic for larger, more detailed view. Expand browser window for best quality view.

.. view developed with ProximityOne CV XE GIS and related GIS project.

Using GIS Tools & Resources
Use the Geographic Information System (GIS) CV XE GIS software and GIS project to view maps and geospatially analyze patterns COVID-19 cases in context of related demographic-economic data. The GIS project automatically opens with the following view:

.. see details about using the mapping/GIS resources.
.. create map views for your areas of interest.

COVID-19 Confirmed Cases by County Interactive Table
Use the interactive table to view, rank, query compare patterns of COVID-19 cases. See related demographic-economic interactive tables.

The following static graphic illustrates use of the table to view daily patterns of COVID-19 cases in Cobb County, GA.

Use the interactive table to examine counties of interest.

Situation & Outlook Web Sessions
Join me in a Situation & Outlook Web Session where we discuss topics relating to measuring and interpreting the where, what, when, how and how much demographic-economic change is occurring and it’s impact.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Examining Health Care Infrastructure by ZIP Code

.. small area data providing information on sub-county and sub-city/place geographies are challenging to locate and use — particularly in context of demand for healthcare services and demographic attributes of associated neighborhoods. Develop insights into the healthcare infrastructure by ZIP code using the two related resources reviewed here — 1) individual ZIP code demographic-economic profiles and 2) ZIP code demographic-economic interactive tables. One way to examine the healthcare infrastructure for an area is to view/analyze the number and attributes (employment, earnings) of healthcare establishments by types of business/industry (such as physicians office or hospitals). Data and tools reviewed here provide insights into characteristics and patterns of national scope ZIP code areas — examine your ZIP codes of interest.

Option 1 — ZIP Code Profiles
.. examining the healthcare infrastructure in context of the related demographic-economic situation … the following graphic shows ZIP code 10514 (Westchester County, NY) with a bold red boundary.  Census tracts are shown with black boundaries with tract codes as white labels. See more about ZIP-Tract relationships. Cities/places are shown with blue cross-hatch pattern.

– view created with CV XE GIS software and related GIS project.

The above map graphic is part of a ZIP Code 10514 profile (click link to view complete profile). Section 3.1. of the profile shows the number healthcare establishments in the ZIP Code as partly shown in this graphic:

The portion of the table shows the NAICS/type of business code at left, followed by type of business description and the number of establishments at the right.

Examine other characteristics of this ZIP code profile and in context of others via this related Web section. These profiles update in May 2018.

Option 2 — ZIP Code Health Care Sector comparative analysis
.. examining the healthcare infrastructure for a set of ZIP codes in a state, metro, county or peer group … use the interactive table located here to view/rank/compare health care business establishments by type of business for a selected set of ZIP codes. This table shows a query placed on the table to show the total number of offices of physicians for ZIP codes in the vicinity of ZIP 10514. It shows that there are 14 offices of physicians establishments and 13 have 1-4 employees.

About These and Related ZIP Code Data
Data used to develop the tools/resources described above are based in part on the Census Bureau County Business Patterns program. These establishment data update annually.

ZIP code demographic-economic interactive tables
Use the following tables to examine a wide range of ZIP code demographic-economic conditions:
  • General Demographics
  • Social Characteristics
  • Economic Chacteristics
  • Housing CHaracteristics

Data Analytics Web Sessions
Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Life Expectancy Change by County, 1980-2014

.. data and tools to examine changing life expectancy by county. Use the interactive table to examine life expectancy characteristics and related demographics for counties and regions of interest. Use the related GIS project and datasets to examine life expectancy contextually with other geography & subject matter. See details below. These data and tools are part of the ProximityOne health data analytics resources.

Life expectancy is rising overall in the United States, but in some areas, death rates are going in the other direction. These geographic disparities are widening.

Life Expectancy Change by County, 1980-2014
The following graphic shows patterns of the change in life expectancy change from 1980 to 2014. Click graphic for larger view. Expand browser window for best quality view.

– View developed using CV XE GIS and related GIS project.
– see below in this section about using this GIS project.

Life expectancy is greatest in the high country of central Colorado, but in many pockets of the U.S., life expectancy is more than 20 years lower. These data are based on research and analysis by the University of Washington Institute for Health Metrics and Evaluation.

Examining life expectancy by county allows for tracking geographic disparities over time and assessing factors related to these disparities. This information is potentially useful for policymakers, clinicians, and researchers seeking to reduce disparities and increase longevity.

Life Expectancy Change by County, 1980-2014 — drill-down view
— South Central Region
The following graphic shows patterns of the change in life expectancy change from 1980 to 2014. Click graphic for larger view. Expand browser window for best quality view. The larger graphic shows counties labeled with change in life expectancy from 1980-2014.

– View developed using CV XE GIS and related GIS project.
– see below in this section about using this GIS project.

Additional Views — use the GIS project to create your own views
.. click link to view
• Alaska
• Hawaii
• Minneapolis metro

Using the Interactive Table
Use the interactive table to view, rank, compare life expectancy characteristics. This graphic shows California counties ranked on life expectancy change 1980-2014 in descending order. Select states or metros of interest. Click graphic for larger view.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Tools to Analyze County Demographic-Economic Characteristics

.. demographic-economic characteristics of counties are essential for business development, market analysis, planning, economic development, program management and general awareness of patterns and trends. This section provides access to data and tools to examine these data for all counties in the U.S. This annual update includes geographic area characteristics based on ACS 2015 data.  The tools/data are organized into four related sections summarized below.

1. General Demographics
View interactive table at http://proximityone.com/us155dp1.htm
Patterns of School Age Population by County
Use GIS tools to visually examine county general demographics as illustrated below. The following view shows patterns of percent population ages 5 to 17 years of age by county — item D001-D004-D018 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

2. Social Characteristics
View interactive table at http://proximityone.com/us155dp2.htm 
Patterns of Educational Attainment by County
– percent college graduate
Use GIS tools to visually examine county social characteristics as illustrated below. The following view shows patterns of percent college graduate by county — item S067 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

3. Economic Characteristics
View interactive table at http://proximityone.com/us155dp3.htm 
Patterns of Median Household Income by County
Use GIS tools to visually examine county economic characteristics as illustrated below. The following view shows patterns median household income by county — item E062 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

4. Housing Characteristics
View interactive table at http://proximityone.com/us155dp4.htm 
Patterns of Median Housing Value by County
Use GIS tools to visually examine county housing characteristics as illustrated below. The following view shows patterns median housing value by county — item E062 in the interactive table. Create your own views.

… view developed using the CV XE GIS software.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

America’s Cities: Demographic-Economic Characteristics Annual Update

.. tools and data to interactively examine demographic-economic characteristics of America’s 29,321 cities/places .. understanding demographic-economic characteristics of cities and places is essential for business development, market analysis, planning, economic development, program management and general awareness of patterns and trends. This section provides access to data and tools to examine characteristics of all cities/places in the U.S. This annual update includes data for 29,321 cities/places based on ACS 2015 data.

Accessing the Data; Using Interactive Tables
Each of the four links below opens a new page providing access to U.S. by city/place interactive tables — by type of subject matter. Use tools and usage notes below table to select operations to perform queries, sort and select columns.
• General Demographics
• Social Characteristics
• Economic Characteristics
• Housing Characteristics

How the the Tables/Data Can be Used
The following table shows data derived from the Economic Characteristics table. The top 10 cities/places having the highest median household income ($MHI) are shown. The table also shows population, median family income ($MFI) and per capita income ($PCI). The $250,000 value is a cap; the actual value is $250,000 or higher. Use the interactive tables to create similar views for states of interest. Use the button below the table to select/view cities within a selected metro. Compare attributes of cities of interest to a peer group based on population size.

Visual Analysis of City/Place Population Patterns
Use GIS resources to visually examine city/place demographic-economic patterns. The following view shows patterns of population percent change by city in the Charlotte, NC-SC metro area.

… view developed using the CV XE GIS software.
… click map for larger view and details.

Related Data
• Cities/Places Main Section
• Citie Population Estimates & Trends, 2010-15

More About Using These Data
• Using ACS 1-year and 5-year data

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Personal Consumption Expenditures by State: Updates & Pattern Analysis

.. data and tools to develop insights into personal consumption patterns by state .. growth in state personal consumption expenditures (PCE) – the measure of goods and services purchased by or on behalf of households – decelerated to 3.6 percent on average in 2015 from 4.4 percent in 2014. In 2015, PCE growth ranged from 1.5 percent in Wyoming to 5.0 percent in Florida. PCE by state data for 16 expenditure categories are shown for the U.S. and by state in the interactive table. See related Web section for more detail.

Per Capita Personal Consumption Expenditures
  — Patterns & Characteristics by State
The following graphic shows patterns of percent change in total PCE 2010-2015 by state labeled with 2015 per capita total PCE. Use CVGIS project to examine PCE by types and different years. Integrate additional subject matter and types of geography. Click graphic for larger view with details.

– views developed with CVGIS and related GIS project & datasets.

In 2015, the fastest growing categories of expenditures across all states were food services and accommodations, health care and other nondurable goods. These categories along with housing and utilities were also the largest contributors to growth in total PCE by state.

Per capita PCE by state measures average PCE spending per person in a state. Across all states, per capita total PCE was $38,196. Per capita PCE by state ranged from a high of $49,717 in Massachusetts to a low of $29,330 in Mississippi.

Personal Consumption Expenditure by Category
PCE by state is the state counterpart of the Nation’s personal consumption expenditures (PCE). PCE by state measures the goods and services purchased by or on behalf of households and the net expenditures of nonprofit institutions serving households (NPISHs) by state of residence for all states and DC. PCE by state reflects spending on activities that are attributable to the residents of a state, even when those activities take place outside of the state. Per capita PCE by state measures average PCE spending per person in a state.

Interactive Analysis
The following two graphics illustrate use of the interactive PCE table. View 1 shows Texas by PCE type ranked in ascending order on percent change from 2010 to 2015 (ranked on far right column). View 2 shows Texas by PCE type ranked in descending order on percent change from 2010 to 2015 (ranked on far right column). Use the table to examine characteristics of states of interest. Click graphic for larger view.

Texas by PCE Type; Ranked Ascending on PCPCE Change 2010-15

Texas by PCE Type; Ranked Descending on PCPCE Change 2010-15

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.

Metropolitan Area Gross Domestic Product: Trends & Updates

… data and analytical tools to examine Metro GDP patterns and trends.  As a policy-maker, investor, business, advisor or stakeholder, it is important to know how and where the metro economy is changing … and how one or selected metros relate to the U.S. and other metros. Is metro X changing in a different direction than metro Y? By how much, why and is there a pattern? What does the healthcare sector, for example, contribute to a metro’s gross domestic product (GDP)? How does it compare to peer metros? How is the healthcare industry trending? Metro GDP data can provide insights and answers to these important questions. Developing insights using metro GDP data — an example. See related Web section for more detail.

Change in Per Capita Real GDP by Metro, 2010-2015
The following graphic shows patterns of change in per capita real GDP by metro from 2010 to 2015. The orange and red fill patterns show metros experiencing a decrease in per capita real GDP over the period. Click graphic for larger view that shows the 2015 rank of the metro among all 382 MSAs based on 2015 per capita real GDP.

— view created using CV XE GIS and associated MetroGDP GIS Project

282 metropolitan statistical areas, of the total 382, experienced an increase in real Gross Domestic Product (GDP) between 2010 and 2015. Growth was led by growth in professional and business services; wholesale and retail trade; and finance, insurance, real estate, rental and leasing, Collectively, real GDP for U. S. metropolitan areas increased 2.5 percent in 2015 after increasing 2.3 percent in 2014. Use the interactive table and GIS project/datasets described in this section to view/analyze patterns and characteristics in metros of interest.

Illustrative GDP by Sector Trend Profiles
Real GDP by sector profiles are available for the U.S. and each state and MSA. The Metro GDP data are part of the State & Regional Income & Product Accounts (SRIPA). The following profiles illustrate these data for metros, states and the U.S.

• Atlanta, GA MSA • Charlotte, NC-SC MSA • Chicago, IL MSA • Columbia, MO MSA • Houston, TX MSA • Phoenix, AZ MSA

• United States • Missouri • Texas

Metro Situation & Outlook Reports
View Metro GDP Characteristics section in the Metropolitan Area Situation & Outlook Reports, providing the same scope of data as in the table below integrated with other data. See example for the Dallas, TX MSA. GDP tells an important but small part of the broader metro demographic-economic characteristics. Most metros have sub-county areas experiencing growth or activity sometimes masked when looking at the entire metro. Click a metro (metro GDP estimated for MSAs only) link in the table at upper right to view the GDP estimate in context of related subject matter.

Interactive Analysis
The following graphic shows an illustrative view of the interactive MetroGDP table. This view shows California MSAs ranked in descending order on percent change in per capita real GDP from 2010 to 2015 (ranked on far right column). Use the table to examine characteristics of metros in regions of interest. Click graphic for larger view.

Join me in a Data Analytics Lab session to discuss more details about accessing and using wide-ranging demographic-economic data and data analytics. Learn more about using these data for areas and applications of interest.

About the Author
— Warren Glimpse is former senior Census Bureau statistician responsible for innovative data access and use operations. He is also the former associate director of the U.S. Office of Federal Statistical Policy and Standards for data access and use. He has more than 20 years of experience in the private sector developing data resources and tools for integration and analysis of geographic, demographic, economic and business data. Contact Warren. Join Warren on LinkedIn.