Environmental Public Health Tracking: Climate Change

Climate change data can give context to climate-related health data.

Public health professionals study both heat and heat-related illness data and precipitation and flooding data in order to prepare for future heat or precipitation events and warn the public when they are at risk.

The sections below present answers to frequently asked questions about heat and heat-related illness data and precipitation and flooding data.

Heat and Heat-related Illness

High temperatures can cause many health problems, such as heat rash, swelling, cramps, fainting, and heat stroke. Public health professionals track extreme heat and heat-related illness in order to prepare for future heat events and warn the public when they are at risk. The section below presents answers to frequently asked questions about heat and heat-related illness.

What is heat-related illness?

Heat-related illness occurs when the body’s temperature and control system becomes overloaded. Normally, the body cools itself by sweating, but this cooling mechanism can become ineffective if the body’s temperature rises too fast. There are several forms of heat-related illness, including heat stroke, heat exhaustion, rhabdomyolysis, heat syncope, heat cramps, and heat rash.

What are some risk factors for heat-related illness?

Old age, youth ages 0-4, obesity, fever, dehydration, heart disease, mental illness, poor circulation, sunburn, prescription medication use, and alcohol use are factors that impact the body’s ability to regulate temperature. Workers whose jobs require them to work outside in hot weather are also at risk of heat-related illness.

How is heat-related illness related to environment?

As a result of climate change, events like heat waves happen more often. The frequency of heat waves may impact how often people suffer from heat-related illness. 

How can tracking heat and heat-related illness improve public health?

  • Tracking extreme heat events and heat-related injury gives public health professionals a better understanding of the health consequences of extreme heat across the country. We can monitor the impact of our warnings and preparedness efforts.
  • Projecting extreme heat events can help certain areas prepare for these events in advance.

What is the data source?

All of the heat and heat-related illness measures are from CDC’s National Environmental Public Health Tracking portal. See below for details about the original data sources.

  • The original source of the emergency department and hospitalization data as displayed on the Wisconsin Tracking Portal is the Wisconsin Hospital Association Information Center, Inc. 
  • Heat-related mortality data are from the CDC’s National Center for Health Statistics.
  • The North American Land Data Assimilation System from the National Aeronautics and Space Administration is the original source of the historical temperature data.
  • Modeled temperature data obtained from 1/8 degree-CONUS Daily Downscaled Climate Projections by Katharine Hayhoe is the source for projected heat data.
  • The vulnerability and preparedness data are from the Wisconsin Hospital Association Information Center, Inc. the U.S. Census Bureau, CDC’s Behavioral Risk Factor Surveillance System, American Hospital Association Annual Survey, and National Land Cover Database.

What measures does Wisconsin Tracking have for heat and heat-related illness?

  • Historical Temperature & Heat Index
    • Number of extreme heat days
  • Temperature & Heat Projections
    • Projected number of future extreme heat days
    • Projected number of future extreme heat nights
  • Heat-Related Illness
    • Heat-related Emergency Department Visits
      • Age-adjusted rate of emergency department visits per 100,000 population
      • Crude rate of emergency department visits for heat stress per 100,000 population
      • Number of emergency department visits for heat stress
    • Heat-Related Hospitalizations
      • Age-adjusted rate of hospitalizations for heat stress per 100,000 population
      • Crude rate of hospitalizations for heat stress per 100,000 population
      • Number of hospitalizations for heat stress
    • Heat-Related Mortality
      • Number of summertime (May-September) heat-related deaths, by year
  • Vulnerability & Preparedness: Heat
    • Age-adjusted rate of hospitalization for heart attack per 10,000 population
    • Median household income
    • Number and percent of people living in poverty
    • Number and percent of people without health insurance

What are some considerations for interpreting the data?

  • Heat index data takes both humidity and temperature into account.
  • Hospital admission and emergency department visit data do not include people who experience symptoms but are not seen in the emergency room or admitted to the hospital.
  • These data do not include inpatient admissions or emergency department visits at hospitals owned by the federal government, such as Veterans Administration hospitals.
  • The death certificate dataset may be missing a small number of cases where the decedent is a Wisconsin resident but died in another state.
  • Data users should keep in mind that many factors contribute to illness. These factors should be considered when interpreting the data. Factors include the following:
    • Demographics (race, gender, age)
    • Socioeconomic status (income level, education)
    • Geography (rural, urban)
    • Changes in the medical field (diagnosis patterns, reporting requirements)
    • Individual behavior (diet, smoking)

Where can I learn more about heat and heat-related illness?

Precipitation and Flooding

Precipitation and flooding data can give context to related health data. Public health professionals study both historical and projected precipitation data in order to prepare for future flooding events and warn the public when they are at risk. The section below presents answers to frequently asked questions about precipitation and flooding data.

What does precipitation and flooding refer to?

The precipitation and flooding topic refers to the measure of precipitation falling as rain or snow in a given year. The precipitation and flooding data on the Wisconsin Tracking portal include measures from previous years and projections for future years.

How are precipitation and flooding related to environmental health?

Serious weather events such as floods can cause a variety of public health impacts, including waterborne disease and drowning.

How can tracking precipitation and flooding improve public health?

These data allow us to understand how changing weather patterns could impact populations in terms of precipitation, flooding, or drought. Understanding precipitation and flooding patterns can also help at-risk areas, emergency response services, and healthcare systems prepare for flooding events.

What is the data source?

  • The North American Land Data Assimilation System from the National Aeronautics and Space Administration is the source of the historical precipitation data.
  • Modeled precipitation data were obtained from 1/8th degree CONUS Daily Downscaled Climate Projections by Katherine Hayhoe.
  • Hospital information was obtained from the 2016 American Hospital Association (AHA) survey.
  • Calculations of special flood hazard areas were determined from 2011 National Flood Layer data from the Federal Emergency Management Agency (FEMA).
  • 2010 U.S. census block group data were used for population data.
  • The two emissions scenarios used for precipitation projections were developed by the Intergovernmental Panel for Climate Change (IPCC).

What measures does Wisconsin Tracking have for precipitation and flooding?

  • Historical Precipitation
    • Number of extreme precipitation days
  • Precipitation and Flooding Projections
    • Projected annual precipitation intensity
    • Projected number of future extreme precipitation days
    • Projected ratio of precipitation falling as rain to that falling as snow
  • Vulnerability and Preparedness
    • Number of housing units within FEMA designated flood hazard area
    • Number of people within FEMA designated flood hazard area
    • Number and percent of square miles within FEMA designated flood hazard area
    • Percent of hospital beds within flood hazard area
    • Percent of hospitals within flood hazard area

What are some considerations for interpreting the data?

Statistical downscaling drastically improves the spatial distribution of climate parameters. Also, modeled meteorological data may not accurately reflect the true precipitation values in each county.

Where can I learn more about precipitation and flooding?

Last Revised: July 8, 2021