Module 5:
Thermal extremes
Key messages in Module 5
• Extreme thermal events cause excess
morbidity & mortality
– All adverse health outcomes are preventable
– Worker productivity likely to be adversely affected
• Climate change is projected to increase health
risks with more, more severe, & longer
heatwaves
– Larger & older populations could increase the risk for
additional adverse health impacts
• Adaptation can reduce current & future risks in
morbidity & mortality due to temp extremes
2
Module 5 outline
Thermal
Identifying
extremes
thermal
Who is
Assessing
vulnerable to
risks &
extremes
impacts
extremes
5
Potential
impacts
3
Understanding
thermal
extremes
4
Key concepts
Events vs. seasons
Thermal extremes focus on relatively short lived
weather conditions (generally days) that are in the
‘tails’ in distributions summarizing annual or
seasonal weather
Excess health outcomes
Defined as the difference in the number/rate of
outcomes during thermal extremes compared
with what would be expected if the event had not
occurred. This is assumed to reflect the health
impact of the extreme temperatures.
5
Climate change: temperature
distribution shifts to more heat
Source: IPCC (2007)
6
The 2003 heatwave in India
• Temperature climbed as high as 500C, some
100 degrees higher than normal
• Heat waves claimed more than 1,900 lives
across India, 70 in Pakistan & 40 in
Bangladesh in three weeks
• Of the 1,900 in India, Andhra Pradesh alone
saw over 1,300 deaths
• Women, children & the elderly were among
the most who died
7
The 2003 heatwave in Andhra Pradesh
Temperatures
in Andhra
Pradesh India
soared to 54oC
& took a toll of
at least 3,000
lives
Photo: Refugee Study Centre
8
Impacts of thermal extremes
The health impacts of
thermal extremes are not
limited to mortality. There
are significant adverse
social impacts with reduced
worker productivity.
It's too hot to work for
cart pullers in New Delhi
Photo: CBS News (2002)
Photo: BBC News (2000)
9
What thermal extremes are
you observing in your
country?
Have you noticed any
health impacts from
thermal extremes?
10
Daily excess mortality associated with daily
maximum temperature in China
Source: Li et al. (2014)
11
Mortality impacts of thermal extremes:
vulnerable countries
Source: EM-DAT (2008) 12
Chiang Mai,
Thailand:
Estimated
cold & hot
effects of
mean
temperature
on causespecific
mortality
Source: Guo et al. (2012)
13
How to identify
thermal extremes
14
Identifying extreme thermal
conditions
• Evaluating meteorological data against
established criteria (e.g. threshold
temperatures, comfort indices, historical
distributions)
• Analyzing observed health impacts
• Combining meteorological & health impact
assessment
15
Meteorological options to identify
extreme thermal conditions
Fixed threshold criteria
Extreme thermal conditions exist when criteria are
exceeded at any point in time, for example:
•
•
•
•
Extreme heat if temperature is > 40ºC
Extreme cold if temperature is < -10 ºC
Temperatures exceed a seasonal distribution value (e.g. 5th
or 95th percentile)
A temperature threshold is associated with increased
adverse health outcomes
16
Meteorological options to identify
extreme thermal conditions
Relative threshold criteria
Criteria for extreme thermal conditions vary by
location and/or time of season
•
Recognize that perceptions of what is exceptionally “hot”
& “cold” vary across locations
17
Identifying thermal extremes using
fixed & relative thresholds
Source: US EPA (2006)
18
Extreme heat & relative thresholds:
India, May 2005
Upper image
shows the start
of an Indian heat
wave in May
2005 when
compared with
the same area at
the same time in
2004.
Note the
expanded yellow
areas in 2005.
Source: NASA (2008)
19
Extreme heat & fixed thresholds: India
in 2003
India in 2003
had the
same
temperature
signal as the
Sahara
desert: >50ºC
Source: NASA (2008)
Identifying thermal extremes
based on health impacts
• Significant increases in health outcomes can
be used to identify thresholds for extreme
thermal conditions
• Increases should be evaluated vs. localized
norms that account for the time of year
• Evaluate the historical relationship between
weather & health outcomes (e.g. daily
mortality) to establish criteria for extreme
conditions
21
Identifying thermal extremes using
weather & health data
Maximum temperature & daily
summer mortality 1980 - 89
Maximum Temperature and Daily Summer Mortality
Shanghai, China 1980-89
Scatter plot of
daily maximum
temperature &
total mortality
Shanghai, China
250
200
Daily Mortality
(to help identify
possible
summertime
threshold
temperatures for
extreme heat) in
300
150
100
50
0
15
20
25
30
35
Maximum Temperature (C)
Source: Kalkstein (2002)
40
Options for identifying extreme
thermal conditions: Using observed health
Strengths:
outcomes
• Certain: if you observe ‘significant’ impacts you know extreme
thermal conditions exist
Weaknesses:
• Reactive: need to rely on real-time data to identify dangerous
conditions
• Requires accurate, comprehensive & timely health outcome
reporting systems
• Lagged notification & response: outcomes a result of
exposure so dangerous conditions already experienced before
warning is provided
• Short term resource commitment to monitoring vs response
might be better balanced
23
Options for identifying extreme thermal
conditions: Using combined meteorological
& health impact data
Strengths:
•
•
•
Accurate: any criteria will be based on periods of interest
where weather significantly increased health impacts
Flexible: various assessment methods can be used
depending on available data (visual evaluation,
regression)
Proactive: with criteria established, it is possible to
evaluate weather forecasts for dangerous conditions
Weaknesses:
•
•
Approach can be difficult to explain
Outreach & education messaging can be complicated
24
Who is
vulnerable to
thermal
extremes?
25
Factors associated with increased
vulnerability
•
•
•
•
•
•
•
•
•
Extreme age: older & younger individuals
Poverty
Lack of technology/adaptability
Low level of fitness
Physical or mental impairment
Social isolation
Chronic conditions
Use of specific medications
Extended direct exposure to ambient heat/cold
26
Managing the risks of thermal
extremes
Risk factor
Risk management /
adaptation
Lack of access to
cooling
• Cooling in public facilities
• Changes in urban
infrastructure
• Heatwave early warning
systems
• Social care networks
Age
Pre-existing health
conditions
Poverty & isolation • Urban green spaces
27
Factors increasing risk of thermal
extremes in a changing climate
• Larger populations
• Larger elevated risk groups (old, young,
poor)
• Expect more & more severe extreme heat
events
• May reach exposure thresholds without
adaptation
28
Factors reducing the risk of thermal
extremes in a changing climate
•
•
•
•
Anticipated increase in standard of living
Early warning & response systems
Urban green spaces
Infrastructure better designed for higher
temperatures
• Cooling in public facilities
• Social care networks
29
Assessing the
health risks &
impacts of thermal
extremes
30
Quantifying the health impacts of
thermal extremes
• Develop & use estimates of ‘excess’ outcomes
instead of counts based on listed medical
condition codes for thermal exposure
• Generate odds ratios or relative risk estimates
for changes in thermal measures or
combinations of meteorological conditions
• Conditional results can be generated (e.g. risk
by age of persons affected, by thermal
threshold)
31
Quantifying health impacts in air
mass-based studies
• Air masses capture distinctions in weather
considering multiple meteorological variables (e.g.
temperature, humidity, wind speed)
• Map the air masses over the time period of interest
• Compare health outcomes, by air mass, with longer
term averages
• Air masses with elevated outcome rates may identify
extreme thermal conditions
• Regression analysis can be used to predict health
outcomes given conditions in an air mass
32
Mortality displacement distributed
lag
model
Example
reflects
extreme
thermal
conditions that
result in excess
mortality (A)
followed by
reduced
mortality (B),
indicating
‘mortality
displacement’
33
5
Potential impacts
of thermal
extremes
34
Projected occurrence of max. temperatures
Source: Diffenbaugh & Giorgi (2012)
(% of years in each period)
35
Projected changes in heatwaves in India
Source: Murari et al. (2014)
36
Source: Dunne et al. (2013)
Population-weighted individual labor capacity (%)
during annual minimum (upper lines) & maximum
(lower lines ) heat stress months
37
Elements of successful early
warning & response systems for
thermal stress
• Strong collaboration between health &
meteorological services & implementing
organizations
• Provide clear advice of actions to take & avoid
• Know who & where the most vulnerable are
located
• Help provide relief from the heat
38
Elements of successful early
warning & response systems for
thermal stress
• Provide opportunities to request assistance or
evaluation
• Be creative in use of available resources
• Short term assignment changes for some public
sector staff
• Review response to events to identify successes &
areas for improvement
• Revise program as needs/opportunities change
39
What we covered in Module 5
Thermal
extremes
Identifying
Who is
Assessing
thermal
vulnerable to
risks &
extremes
extremes
impacts
5
Potential
impacts
40
Learning from Module 5
• Extreme thermal events cause excess morbidity
& mortality
– All adverse health outcomes are preventable
– Worker productivity likely to be adversely affected
• Climate change is projected to increase health
risks with more, more severe, & longer
heatwaves
– Larger & older populations could increase the risk for
additional adverse health impacts
• Adaptation can reduce current & future risks in
morbidity & mortality due to temp extremes
41
What action will you
take in your work,
given what you learnt
in Module 5?
42
Coming up next…
Module 6:
Extreme weather events
43