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Online Short Course: Overview of Data Science Tools for Climate & Health
As a pedagogy fellow during AY 2022-2023, I developed this short course for the new online master's in public health program at HSPH.
Summary: Climate change is one of the most (if not the most) pressing challenges of our time. Meanwhile, data science is a rapidly expanding field; references to the power of “machine learning” are ubiquitous. But what does “machine learning” really mean in the context of public health and climate change? In what situations might a really nice map make advanced statistical analysis gratuitous? This module will help you build a mental framework for distinguishing different aspects of data science and gain intuition for when these tools have the most potential to help us study and fuel action at the intersection of climate and health.
Learning Objectives:
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Differentiate between major categories of statistical / data science tools
- Data visualization / mapping
- Traditional statistical modeling / parametric regression
- Machine learning -
Identify areas of climate & health research and/or policy work for which the different types of tools are best suited, possibly in combination or to complement one another
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Gain familiarity with common critiques / drawbacks of these types of tools, specifically at the intersection of climate and health
A list of additional resources can be found at the bottom of this page.
Trailer
Part 1: Intro to Climate & Health Data Science
Part 2: Statistical Analysis for Climate & Health
Part 3: Machine Learning for Climate & Health
Additional Resources
Climate & Health References:
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Lancet Countdown on Health and Climate Change, 2022 (includes interactive data visualizations)
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Extreme Weather and Climate Change: Population Health and Health System Implications – Annual Review of Public Health, 2021
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“Breathing Data” blog on air pollution, health, and data science by Ellen Considine, 2021 (blogs 6,7,8 explore connections with climate change and 9 focuses on wildfires)
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“Extreme Heat Will Change Us” – NY Times, 2022
Accessible Data Science References:
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Public Health Disparities Geocoding Project 2.0 (2022)
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Introduction to Data Science: Data Analysis and Prediction Algorithms with R by Rafael Irizarry
Interesting Dashboards to Explore:
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What will my city’s climate look like in 60 years? Interactive app
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Climate Mapping for Resilience and Adaptation
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Climate Solutions – interactive viz from the Environmental Defense Fund (EDF)
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Featured Tools from Heat.gov
- Heat & Health Tracker
- Climate Explorer -
US Climate and Economic Justice Screening Tool (CEJST)
- Methodology: “A community is highlighted as disadvantaged on the CEJST map if it is in a census tract that is (1) at or above the threshold for one or more environmental, climate, or other burdens, and (2) at or above the threshold for an associated socioeconomic burden.”
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