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Code & Data

Introducing the Temperature Extremes in Europe (TEE) Datasets

This GitHub repository contains a collection of scripts that generate datasets quantifying extreme temperature exposure in Europe using a variety of metrics at two sub-national spatial scales (NUTS 2 and NUTS 3) and three temporal scales (daily, extreme temperature wave, and yearly) from 1980-2024.

Triply robust approach to evaluate the health impacts of extreme weather events

This code was first designed to evaluate the mortality risk associated with flood in the contiguous United States. The code could be used with other “pulse” events (e.g., extreme weather events) or other health outcomes (e.g., hospital visits).

Mapping Flooding and Population Exposure: The Global Flood Database

The data combines satellite flood and human settlement data to identify population exposure to flooding and flood risk from 2000 onward. The data were created using NASA satellite imagery to identify and map flood events recorded by the Dartmouth Flood Observatory (DFO)…

Creating “bins” for extreme temperature data and adjusting for known bias

This Stata code and program take temperature data at fine temporal and spatial resolution (ie: tract-day) and transform it to an aggregated panel dataset with temperature binned to year-place or month-place specificity.

Code linking NCHS mortality data with GFD flood event data

This code links National Center for Health Statistics (NCHS) mortality data with Global Flood Database (GFD) flood event data from 2001 – 2018 by US county.

Processing NDVI and VIIRS vegetation data for use in population health research

These code resources offer a comprehensive outline for downloading, processing, aggregating, and integrating global vegetation coverage data for use in demographic and health research.

Resources and Data from the IPUMS DHS Spatial Analysis and Health Research Hub

The code and data resources in the hub use R scripting to demonstrate basic spatial data processing techniques for integrating numerous environmental and weather-related data with social and health data in the DHS.

Get to know the Health & Retirement Study (HRS)

Dr. Amanda Sonnega provides details on the Health and Retirement Study’s (HRS) history, study design, content, and information on access to the restricted data.

An overview of environmental data for the Health & Retirement Study (HRS)

Dr. Sara Adar provides details on measures useful for the HRS and sister studies of air pollution, green space, temperature, precipitation, disasters, drought, and more.

Code analyzing population pyramids for counties exposed to Low Elevation Coastal Zones (LECZs) in Puerto Rico

This code aims to integrate Python programming with ArcGIS API to access NASA SEDAC Low Elevation Coastal Zone (LECZ) data, IPUMS API to access U.S. Census Decennial Census data of Age and Sex groups at the Block Group and County levels, create interactive maps, find insights about the changes in population pyramid structures, and compare these changes between areas inside and outside of the Low Elevation Coastal Zone (LECZ) in Puerto Rico.

Daily Temperature Data Processing and Analysis: An Example for New York City

This code aims to provide a comprehensive guide to acquiring and cleaning daily temperature and precipitation data for New York City between 2015-2022 using two primary data sources: Global Historical Climatology Network daily (GHCNd) from the U.S. National Centers for Environmental Information and ERA5-Land Reanalysis from the European Union’s Copernicus Project.

Aging and disability in the Mexican Population

This code demonstrates how to construct disability measures using the international recommendation of the Washington Group. It also demonstrates how to evaluate age and sex composition of the population with disability and their territorial distribution.

Severe Heat Days using the Universal Thermal Comfort Index

This code demonstrates how to construct severe heat measures using the UTCI data (ERA5-HEAT ). It starts by showing data manipulation from raster (grid data) to a tabular dataset that obtains UTCI values for each municipality in Mexico.

Linking SVRGIS with FEMA Disaster Declarations and Census/ACS

This code provides examples of how to pull, filter, and merge data from the NOAA/NWS Severe Weather GIS Database (SVRGIS), OpenFEMA Disaster Declarations Summaries, and data from the Decennial Census and American Community Survey (ACS).

Joining ACAG Annual Estimates of PM2.5 with Social Determinants of Health (SDOH) data

This code aggregates gridded annual average PM2.5 concentration estimates produced by the Atmospheric Composition Analysis Group (ACAG) to the census tract level, producing a variable containing the average PM2.5 exposure for each tract. This is then combined with socioeconomic and demographic data available at the tract level from the social determinants of health (SDOH) database produced by the Agency for Healthcare Research and Quality (AHRQ).

US Census Bureau Household Pulse Survey – Disaster Displacement

This code analyzes the questions regarding displacement due to disasters in US Census Bureau’s Household Pulse Survey.

Code linking SHELDUS with ACS data

This code links the American Community Survey (ACS) microdata with the Spatial Hazards Events and Losses Database for the United States (SHELDUS).

R markdown for how to use SHELDUS data (Spatial Hazard Events and Losses Database for the United States) with US Census’ American Community Survey (ACS) micro data

This example demonstrates linkages and analysis applications for South Carolina. Click here to download the zip file that contains code and data for all users. The workshop agenda found here provides links to other materials (presentations, slide-deck, lab worksheet) that accompany it.

FEMA Disaster Declaration Summaries available at county scale

Disaster Declarations Summaries is a summarized dataset describing all federally declared disasters.

The multi-faceted, publicly-available disaster data platform from the Federal Emergency Management Agency (FEMA)

OpenFEMA is the “agency’s data delivery platform which provides datasets to the public in open, industry standard, machine-readable formats.

Call for Code

Have you recently finished a project or published a paper that integrates social and health science data with disaster, climate or environmental data? Would you like to share your code on CACHE?

How to apply to share your code & data on the CACHE website:

1. Review this form, then submit your brief proposal (linked in the form). Proposal to include code is accepted by an internal team or by an external team for CACHE demonstration or seed-funded projects.

2. If accepted, you will be asked to complete a template. Your code will be reviewed by a team member and verified that it performs as stated. We are offering a $250 stipened for those accepted and for those who meet elligibility.

Note: Science objectives and study result are not critically examined as it falls beyond the scope of the objective to make code openly available.

For questions, email cache@colorado.edu.

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