Educational Resource Hub
This crowd-sourced database of educational resources is meant to encompass any tools relevant to people working in the climate and health space. This might include submissions by the content authors themselves, or simply recommendations from community members for resources they have found helpful. This collection includes only links directing users to existing resources - it is not meant to house or archive content.
Keep in mind, this is a crowd-sourced database. CAFE does not verify the quality nor endorse the use of any materials included in this database. Make sure to follow the terms of use and attribution requirements specific to each resource. If you have created or used sources that would be relevant to the community of practice, please add it to the database by entering it in the submission form below.
Speaker: Antonio Gasparrini, PhD
Professor of Biostatistics and Epidemiology
Department of Social & Environmental Health Research
London School of Hygiene & Tropical Medicine
Speaker: Saria Hassan, MD
Assistant Professor of Medicine
Emory School of Medicine
Using the Python cdsapi package, ERA5-Land hourly temperature measures are downloaded from the Copernicus Climate Data Store (CDS). Heat index and humidex metrics are derived from ERA5-Land hourly 2-meter temperature and 2-meter dew point temperature. Daily mean, maximum, and minimum measures are assessed across administrative boundaries for 2-meter temperature, 2-meter dew point temperature, skin temperature, heat index and humidex. Kenya is used as a demonstration area for the Copernicus CDS API query and spatial aggregation, using administrative boundaries from the Database of Global Administrative Areas.
Following the Basic GitHub Introduction, you will be able to upload your code without needing to install any software on your machine or use the command line. For those interested in using the command line interface, refer to the Cloning Repositories and Pushing Code section for basic Git commands.
Finding the most appropriate environmental dataset for a given health analysis can be one of the most challenging steps in a climate and health project. This handbook does not provide a comprehensive encyclopedia of datasets with instructions on what to use, when to use it, and why. Instead, key principles are outlined that should be carefully considered when selecting a dataset. CAFE is engaged in several efforts that aim to ensure that public health professionals can find different data that might meet their needs across climate change exposures and geographic regions.
This repository includes code for the derivation sum road length at the census tract-level using TIGER/Line roads data. Total road length is measured, as well as road length within each of several MTFCC classes.
This repository provides tutorial scripts in R and Python for spatializing and mapping tabular temperature data at the county level.
Crowd-Sourced Climate Change and Health Educational Resources Collection Submission Form
Do you have a resource you’d like to share with the community in this educational resource collection? Please fill out the submission form below.
Your entry will be checked to ensure the content is appropriate, but will not be assessed for accuracy or completeness, and no other quality checks will be done.
If you have a dataset you’d like to share with the community, think about posting it to the CAFE collection on Dataverse!
Please fill out the form to add a resource you think might be helpful for the climate change and health community of practice.
The type of resources that should be shared here are one of the following:
- Book or reference text (e.g. textbook or guidebook on best practices or other essential knowledge)
- Code repository (e.g. a GitHub code bank of an existing analysis)
- Online code tutorial or vignette (e.g. a walkthrough of specific code or methods with examples and explanations)
- Online course (e.g. a series of learning objectives with content and assessment)
- Video or recorded webinar (e.g. educational resources presented in video format)
