Tag: census

Correcting the census: Household sizes in Maptitude 2019
Household size distributions are critical inputs to many business analyses, but may not be correctly derived from U.S. Census data, according to Caliper.

The Census counts people at their geographic locations, and when several unrelated people live at the same address, they are reported as one household with a number of residents.

A confusing array of data is reported. In both the Census SF1 2010 file and in 2017 ACS, the following tabulations are provided down to the Census tract level:
- People in Family Households
- 2 person Family Households
- 3 person Family Households
- 4 person Family Households
- 5 person Family Households
- 6 person Family Households
- 7+ person Family Households
- Non-relatives in Family Households
  - Unmarried Partners (including same-sex couples) in Family Households
- People in Non-Family Households
  - Unmarried Partners (including same-sex couples) in Non-Family Households
There is also extensive information on people residing in group quarters in the 2010 Census, which has the tabulations below:
- People in Group Quarters: College
- People in Group Quarters: Military
- People in Group Quarters: Navy Ships
- People in Group Quarters: Other
  - People in Group Quarters: Homeless
  - People in Group Quarters: Group Homes
  - People in Group Quarters: Residential Treatment
  - People in Group Quarters: Merchant Ships
  - People in Group Quarters: Workers’ Group Living Quarters
  - People in Group Quarters: Other Other
- People in Group Quarters: Institutionalized
Using this information, Maptitude 2019 includes a corrected data set of household size distributions for Census Tracts and Block Groups to account for the under-representation of one-person households in the Census data.

Census tracts with Caliper derived households. (Image: Caliper)

Census tracts with Census household count. (Image: Caliper)
April 17, 2019
GIS fundamental in battle against Zika virus

Florida is home to more than 3.6 million women aged 15 to 44 years. With more than 400 Zika virus cases reported in Florida to date, the state has become a top focus in the public health battle to curb the spread of Zika infections in the U.S.

Gathering and mapping such data using GIS software from Esri is part of the U.S. Department of Health & Human Services (HHS) Office of the Assistant Secretary for Preparedness and Response’s (ASPR) effort to combat this growing health risk domestically and internationally.

The health impacts of the Zika virus are greatest on developing fetuses. Drawing on U.S. Census data, Esri is showing experts at the ASPR and other agencies within HHS where best to target information and reach women of child-bearing age and their partners.

To plan for the domestic assistance that states may need, ASPR also is using Esri software to monitor the spread of the Zika virus across the U.S. and in 34 other countries where infections have been found.

Using Esri software, ASPR created a publicly available interactive map that shows the number of cases in each state. The information is automatically updated each week.

The Zika virus is spread to people primarily through the bites of infected Aedes aegypti mosquitoes; however, the virus has also been found to be transmitted sexually. The virus can cause Guillain-Barré syndrome in adults and children and can cause a serious birth defect called microcephaly.

“Prevention is the first course of action in protecting public health, but people need information to make decisions about what preventive actions to take,” said Este Geraghty, chief medical officer and health solutions director, Esri. “Using GIS technology to locate the most vulnerable populations is a first step in educating people on the risks of the Zika virus and about actions that can protect health and curb the spread of disease.”

For more information on Esri and using GIS for vector-borne disease surveillance and control, visit go.esri.com/pr-zika.

August 23, 2016
CartoDB unveils tech to extract Deep Insights from location data

CartoDB, a world leading company for location intelligence, data analysis, and visualization, has launched Deep Insights, a technology layer that enables the visualization, dynamic filtering, and exploration of large location datasets at unprecedented scale and scope.

With CartoDB’s Deep Insights technology, datasets can be enriched or augmented by existing geospatial data from various sources with a diverse number of fields, such as census information or administrative boundaries. Once data is processed by Deep Insights, users can further filter, pan, zoom and granularly narrow in on data to view trends and patterns that, in traditional reports, would otherwise go unnoticed.

Deep Insights is also equipped with a suite of interactive widgets and command controls so users can tailor the interface for the best experience. It can be implemented to stand-alone or configured and integrated with users’ own application workflow.

“The launch of Deep Insights involves a redefinition of the role of geospatial data visualization and analysis in maps, empowering the way people analyze and interact with massive amounts of existing data. For CartoDB it was the next logical step to follow,” said Sergio Álvarez Leiva, CPO, CartoDB. “The creation of a new visualization technology capable of identifying trends and patterns with big data, literally making the invisible visible.”

CartoDB is launching Deep Insights at Mobile World Congress, being held Feb. 22-25 in Barcelona, Spain. The company is demonstrating the technology in partnership with Mobile World Capital, an organization dedicated to bringing mobile transformation to the city of Barcelona. Deep Insights will be used to analyze the influx of tourism in Barcelona and identify opportunities for increased revenue through tourism per location. The collaborative project will leverage three sets of data, including data on key touristic spots, social media activity, and payments from BBVA bank.

Deep Insights is made available through a single, user-friendly interface that allows users to explore location-related insights visually on a map. It has a fixed pricing structure to allow for unlimited scale with no cap on usage, starting at $100 for 1GB in memory data.

February 23, 2016