MN EPHT Brownbag Series
April 12, 2010
Development of Environmental Health
Indicators of Climate Change
Road Map

Background

Building Capacity in MN

EPH Tracking & Indicators
• Example Indicators (heat & pollen)
• Indicators of Potential Interest to MN

Discussion & Questions
IPCC 4th Assessment
Changes in temperature, precipitation,
and other weather variables due to
climate change are “likely to affect the
health status of millions of people,
particularly those with low adaptive
capacity.” (IPCC, 2007)
Exposures & Effects
Climate
Change
Effects:
• Temperature
• Sea level
• Precipitation
Heat
Morbidity/mortality
Storms, coastal
flooding
Morbidity/mortality
Vector biology
Infectious diseases
Air pollutants,
allergens
Respiratory
diseases
Food supply
Malnutrition
Civil conflict
Morbidity/mortality/
displacement
Kittson
Roseau
Lake
of the
Woods
Koochiching
Marshall
St. Louis
Beltrami
Pennington
Polk
High-Risk Areas for
Tick-borne Diseases
in Minnesota
Cook
Clear
Water
Red Lake
Lake
Itasca
Mahnomen
Norman
Hubbard
Cass
Becker
Clay
Aitkin
Wadena
Crow Wing
Tick-borne disease risk in Minnesota is
highest in forested areas within the
shaded zones.
Carlton
Ottertail
Wilkin
Pine
Todd
Mille
Lacs
Grant
Douglas
Stevens
Pope
Kanabec
Morrison
Benton
Traverse
Stearns
Isanti
Big Stone
Sherburne
Swift
Chisago
Blacklegged ticks may also be found
at lower levels in some forested areas
outside this zone.
Anoka
Kandiyohi
Meeker
Wash ingRam - ton
sey
Wright
Chippewa
Hennepin
Lac Qui Parle
McLeod
Renville
Carver
Scott
Yellow Medicine
Dakota
Sibley
Lincoln
Lyon
Redwood
Rice
Le
Sueur
Nicollet
Goodhue
Wabasha
Known high risk areas for tick-borne diseases, before 2004
Brown
Pipestone
Murray
Cottonwood
Watonwan
Rock
Nobles
Jackson
Martin
Blue Earth
Faribault
Waseca
Steele
Freeborn
Dodge
Mower
Olmsted
Fillmore
Winona
Houston
Known high risk areas for tick-borne diseases, added in 2004
Rare or Emerging Tick-borne Diseases
(Minnesota)
Agent
Tick Vector
Ehrlichiosis
Ehrlichia spp.
Lone star tick
(Amblyomma
americanum)
Rocky Mountain
spotted fever
Rickettsia
rickettsii
Wood/dog tick
(Dermacentor sp.)
Powassan
encephalitis
Powassan virus
(prototype and
deer tick virus
lineages)
Blacklegged tick,
Woodchuck tick
(Ixodes spp.)
Building Capacity to Address
PH Impacts of Climate Change

Needs Assessment (survey)

Training (4 webinars)

Strategic Plan

Web Site
Training (4 modules)

Climate Change 101

Vector-Borne Disease

Extreme Heat

Vulnerable Populations
Ongoing Activities

Seeking Funding

Building Capacity (state & local levels)

Fostering Collaboration & Communication
• LPHA, UMN, MPCA, DNR, MDA, CDC, EPA…
What Are Indicators?

Indicators are quantitative summary measures
that may be used to track changes by population,
location, & time

Used to:



Evaluate trends over time
Identify areas for intervention & prevention
Evaluate effectiveness of programs & policies
State Environmental Health
Indicators Collaborative (SEHIC)

State-level epidemiologists

Voluntary (supported by CSTE & CDC)

Climate Change Workgroups




Morbidity & mortality
Population vulnerability
Air quality & respiratory morbidity
Vector-borne diseases
Environmental Health Perspectives
(November 2009)

Evaluated strengths & limitations of
data sources

Developed a suite of indicators of
climate change
Environmental Health Perspectives:
http://ehp03.niehs.nih.gov/home.action
EH Perspectives, 2009
EPHT Network

Congress first appropriated funding to the CDC to plan and
establish a national EPHT network in 2002.

The national EPHT program will…
Link health and environmental data systems
 Bring together existing and new sources of data
 Draw data and information from state networks and from
national data systems
 Provide data that are nationally
consistent
 Make information available
through a web-based, secure
electronic network

National EPHT Network (2009)
CDC currently funds 22 states, 1 city, and
4 academic partners to implement EPHT network.
Minnesota joined the network as a funded state in 2009.
National EPHT Network
Climate Change Team

Adopted climate change as a developmental
content area (Summer 2009)

Established Climate Change Team (Fall 2009)

Initial Focus:

Heat-related mortality & morbidity
Collaboration

National




SEHIC
National EPHT Network, CDC
NOAA, US EPA
State & Local



ASTHO Grantees (CA, MI, NH, FL, MN)
MPCA, DOC, DNR, MDH, UMN (ICAT)
Local health departments
Extreme Heat Events
 Heat
waves in MN (recent)
• 1983, 1995, 1999, 2001, 2005, 2006
 Consecutive
days of abnormally high
temps combined with humidity
 Heat
Index
Extreme Heat:
Health Effects


Primary

Heat stroke & heat exhaustion

Acute dehydration
Secondary

Cardiovascular disease & heart attacks

Kidney failure

Respiratory illness
Extreme Heat:
Indicator Development

Define extreme heat period
 Heat
Index > 105°F for 2 or more days
 Maximum
ambient temperature & relative
humidity

Define referent period

Equivalent number of days and distribution of
days of the week (exclude holidays)

Close to time period of heat event
Areas of Analysis
Climate Change Team
California
Louisiana
Maine
Massachusetts
Minnesota
Missouri
New Hampshire
New York City
Oregon
Utah
Washington
Wisconsin
Extreme Heat:
Mortality Indicator

Sum of daily counts of all-cause mortality
during heat wave & referent periods

Calculate rate ratio & confidence interval
•Deaths (Heat wave) / Deaths (Referent period)
•Assume population is constant over time
Extreme Heat:
Preliminary Results

Minnesota

July 20 – August 2, 2006 (2 weeks)

7 county metro area

Referent period
• June 24-31 and August 17-23

Deaths during heat wave: 547

Deaths during referent period: 509

Rate ratio: 1.07 (0.95, 1.21)
Preliminary Results
Rate Ratio (Confidence Interval)
California
Louisiana
Maine
Massachusetts
Minnesota
Missouri
New Hampshire
New York City
Oregon
Utah
Washington
Wisconsin
1.06 (1.03, 1.09)
3.40 (1.68, 6.88)
1.32 (0.88, 1.97)
--1.07 (0.95, 1.21)
----1.09 (1.01, 1.18)
1.00 (0.78, 1.28)
0.90 (0.57, 1.42)
-----
Extreme Heat:
Morbidity Indicator
 Sum
of daily counts of specific health
conditions
• Hospitalizations or ED visits during heat wave
period and referent period
• Primary & secondary diagnoses (Knowlton,
2009)

Calculate rate ratio & confidence interval
Data Issues

Heat Index


Some states rarely experience > 90° F or high
humidity
Daily maximum temp/humidity to
calculate Heat Index
May be better to calculate paired temp &
humidity
 Requires hourly data

Data Issues

May want to evaluate accounting for
low temps during heat waves


Night-time cooling off period is crucial
Referent period

Close to heat event so temps are still
relatively high
Data Issues


Mortality data

Not heat-specific

More easily obtained than hospitalization or
ED data
Difficult to create a national indicator that
is consistent and meaningful for all
geographic areas
Pollen & Climate Change
Increased pollen production
 Change in pollen species observed at
particular location
 Longer pollen season

Proposed Pollen Indicator
Measures
Pollen load:
Percentage of days with pollen
levels higher than the action
level per population in a
calendar year
Pollen type:
Pollen species measured in a
calendar year
Length of pollen season: Number of days
National Allergy Bureau
Monitoring Stations - Midwest
Source: http://www.aaaai.org/nab/index.cfm
Next Steps:
Pollen Indicator
Develop template and how-to guide
 Pilot-test using NAB data
 Present results at conference
roundtable in June
 Pilot-test measures (other states)
 Post final documents on CSTE
website

Indicators of Potential
Interest in MN

Extreme weather events (e.g., heat waves, floods)

Population vulnerability

Vector-borne diseases

Aero-allergens

Air quality (ozone, fine particles)

Others?
Tracking in Action
Public
Health
Action
Data
Dissemination
Data
Collection
Data
Analysis &
Integration
Tracking = public health surveillance
Next Steps

MDH
Strategic Plan
 CDC (funding opportunity)


National Tracking Network
Joint meeting w/SEHIC (April 29)
 Climate Change Team (ongoing)

Climate Change
Indicators & Tracking:
Collaborators:
University of MN Extension
Chuck Stroebel
Wendy Brunner
Paula Lindgren
Jean Johnson
MPCA
LPHA
Building Capacity:
Lynne Markus
Kristin Raab
Myrlah Olson
David Neitzel
Dan Symonik
Web Site:
www.health.state.mn.us/tracking/
….the most important question we
must ask ourselves is, “Are we
being good ancestors?”
Jonas Salk