March 4 at 4 p.m. ET | 3 p.m. CT| 2 p.m. MT/1 p.m. PT Virtual Event

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. 

Research on disasters and health has increasingly leveraged linked administrative claims data and detailed spatial information on natural disaster events in order to move beyond single-case descriptions toward quasi-experimental designs. Such linkages aim to improve knowledge about the proximate mechanism (such as health care utilization) that link the consequence of disasters to health outcomes. 

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.

The Health and Retirement Study (HRS) is an ongoing longitudinal study of middle-aged and older adults. It is designed to be nationally-representative of the U.S. population over age 50 and it adds a new cohort every six years. The HRS presents an excellent opportunity to study life course exposures and health outcomes in older adults. Many researchers have used the HRS to investigate the impacts of environmental exposures, including disasters, heat, air pollution, and greenspace.

February 5, 2026

In collaboration with our partners at UC Santa Barbara’s Climate Hazards Center. Led by Dr. Shraddhanand Shukla, Associate Researcher at the Department of Geography at UCSB. An overview of the Climate Hazards Center’s (CHC) flagship climate monitoring resources: the CHIRPS (Precipitation) and CHIRTS (Temperature) datasets. 

This code aims to show 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.

A new report from Winkler & Mockrin (2025) entitled “Aging and wildfire risk to communities” explores the exposure of older populations to wildfires. A main findings is that “Nearly all (87 percent) of the population growth in higher wildfire risk locations between 2010 and 2020 was among people over the age of 60, many of whom had been living in higher risk places for years and are growing older (i.e., aging in place).”

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. 

The purpose of this code is to analyze the questions regarding displacement due to disasters in US Census Bureau’s Household Pulse Survey. The code is applied to a single dataset.

A recent article in The Conversation, written by CACHE Co-Director Lori Hunter, explores how older adults in rural areas are especially vulnerable in the aftermath of disasters like floods and hurricances. Here’s how families and neighbors can help.