Transcript Methods of Assessing Human Health Vulnerability and Public

Vulnerability and Adaptation
Assessments Hands-On
Training Workshop
Human Health Sector
Kristie L. Ebi, Exponent Health Group
1A.1
Outline
1.
2.
3.
4.
Overview of the potential health impacts of
climate variability and change
Health data to determine the current burden
of climate-sensitive diseases
Methods and tools for V&A assessment in
the health sector
Methods for determining a health adaptation
baseline
Overview of the Potential
Health Impacts of Climate
Variability and Change
1A.3
Topics
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Pathways for weather to affect health
Potential health impacts of climate change
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Extreme weather events
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El Nino and disease
Temperature
Floods
Vector-borne diseases
Diseases related to air pollution
Diarrheal diseases
Pathways from Driving Forces
to Potential Health Impacts
Corvalan et al., 2003
Pathways for Weather to Affect
Health: Example = Diarrheal Disease
Distal Causes
Temperature
Humidity
Precipitation
Living conditions
(water supply and
sanitation)
Food sources and
hygiene practices
Proximal Causes
Infection Hazards
Survival/ replication
of pathogens in the
environment
Consumption of
contaminated water
Contamination of
water sources
Consumption of
contaminated food
Contamination of
food sources
Contact with
infected persons
Rate of person
to person contact
WHO
Health Outcome
Incidence of
mortality and
morbidity
attributable
to diarrhea
Vulnerability
(e.g. age and
nutrition)
IPCC TAR–Potential Health
Impacts of Climate Change
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Any increase in climate extremes (storms, floods, cyclones)
could increase the risk of infectious disease epidemics,
particularly in low-income countries
Increase in heatwaves, often exacerbated by increased
humidity & urban air pollution
Increase in the geographic range of potential transmission of
malaria & other vector-borne diseases
Increase in water- and food-borne diseases
The severity of impacts will depend on the capacity to adapt & its
effective deployment
Drivers of Health Issues
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Population density
Urbanization
Public health infrastructure
Economic and technologic development
Environmental conditions
Populations at risk
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Poor
Children
Increasing population of elderly residents
Immunocompromised
ENSO and Disease
Kovats et al., 2003
Exploring Linkages Between
ENSO and Human Health
Dengue Epidemics in South Pacific
1970-1999
Number of Cholera cases in Uganda 1997-2002
Number of cases
50000
40000
El Nino stops
El Nino starts
30000
20000
10000
0
1996
1997
1998
1999
2000
Time in years
Dr. Githeko, personal communication
2001
2002
2003
Climate Change
May Entail
Changes in
Variance, as Well
as Changes in
Mean
Folland et al., 2001
Temperature
Extremes in
the
Caribbean,
1955-2000
Climate Variability and Change
Impacts in the Caribbean
DATE
COUNTRY
EVENT
DEATH
ESTIMATED COSTS
(US$ million, 1998)
1974
Honduras
Hurricane Fifi
7,000
1,331
1982/3
Bolivia, Ecuador, Peru
El Niño
0
5,661
1997/98
Bolivia, Colombia, Ecuador,
Peru
El Niño
600
7,694
1998
Central America
Hurricane Mitch
9,214
6,008
1998
Dominican Republic
Hurricane Georges
235
2,193
Cuba
Hurricane Georges
6
N/A
Venezuela
Landslide
25,000
N/A
1999
Fuente: ECLAC, América Latina y El Caribe: El Impacto de los Desastres Naturales en el Desarrollo, 1972-1999,
LC/MEX/L.402; OFDA, Venezuela- Floods, Fact Sheet #10, 1/12/ 2000.
Mechanisms by Which Above Average
Rainfall Can Affect Health
Event
Description
Potential Health Impact
Heavy
precipitation
“Extreme event”
Increased or decreased
mosquito abundance
Flood
River/stream over Above plus contamination of
tops its banks
surface water
Property or crops
damaged
Flood
Catastrophic
flood/disaster
Kovats et al., 2003
Above plus increased risk of
respiratory and diarrhoeal
disease, injuries, etc.
Health Impacts of Floods
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Immediate deaths and
injuries
Nonspecific increases
in mortality
Infectious diseases –
leptospirosis, hepatitis,
diarrheal, respiratory,
and vector-borne
diseases
Exposure to toxic
substances
Mental health effects
Increased demands on
health systems
Philip Wijmans, LWF/ACT Mozambique, March 2000
Mechanisms by Which Drought Can Affect
Health
Description
Potential Health Impact
Soil moisture decreases
Changes in vector abundance
Decreased crop production Depends on socioeconomic factors
Reduction in food or water
supply and quality
Food shortage, illness, malnutrition,
increased risk of disease
Food shortage leading to
deaths
Death, starvation, risks associated with
population displacement
Kovats et al., 2003
Examples of Environmental Changes and
Possible Effects on Infectious Diseases
Environmental
Change
Example
Disease
Pathway of Effect
Dams, canals,
irrigation
Malaria
Increase breeding sites for
mosquitoes
Urbanization
Cholera
Decreased sanitation &
hygiene, increased water
contamination
Reforestation
Lyme
disease
Increase tick hosts, outdoor
exposure
Ocean warming
Red tide
Increase toxic algal blooms
Patz et al., 2003
Wilson 2001
Factors that Influence the Range and
Prevalence of Infectious Diseases
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Sociodemographic influences
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Human travel, trade, and migration
Disease control efforts
Drug resistance
Nutrition
Environmental influences
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Land-use, including deforestation, agricultural
development, and urbanization
Ecological influences
Temperature and Precipitation Effects on
Vector- and Rodent-Borne Diseases
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Survival and reproduction rate of the vector
Time of year and level of vector activity,
specifically the biting rate
Rate of development and reproduction of the
pathogen within the vector
Main Types of Transmission Cycles
for Infectious Disease
Patz et al., 2003
Potential Transmission of
Schistosomiasis, Jiangsu Province
Yang et al., 2005
Climate Change and Malaria
under Different Scenarios (2080)
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Increase: East Africa, Central Asia, Russian Federation
Decrease: Central America, Amazon [within current vector limits]
Van Lieshout et al. 2004
Change of consecutive months
A1
> +2
+2
A2
-2
< -2
B1
B2
Van Lieshout et al. 2004
China Haze 10 January 2003
NASA
Effect of Temperature Variation on
Diarrheal Incidence in Lima, Peru
Daily Diarrhea
Admissions
Daily
Temperature
Diarrhea increases by 8% for each 1ºC increase in temperature
Checkley et al., 2000
Resources
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McMichael, A.J., D.H. Campbell-Lendrum, C.F.
Corvalan, K.L. Ebi, A. Githeko, J.D. Scheraga, and A.
Woodward (eds.). 2003. Climate Change and Human
Health: Risks and Responses. WHO, Geneva.
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Summary pdf available at
http://www.who.int/globalchange/publications/cchhsum
mary/
Kovats, R.D., K.L Ebi, and B. Menne. 2003. Methods
of Assessing Human Health Vulnerability and Public
Health Adaptation to Climate Change. WHO/Health
Canada/UNEP.
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Pdf available at
http://www.who.dk/document/E81923.pdf
Health Data to Determine the
Current Burden of ClimateSensitive Diseases
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Questions to be Addressed
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What climate-sensitive diseases are
important in the country or region?
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What factors other than climate should be
considered?
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What is the current burden of these diseases?
Water, sanitation, etc.
Where are data available?
Are health services able to satisfy current
demands?
Health Data Sources
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World Health Report provides regional-level
data for all major diseases
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WHO databases
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http://www.who.int/whr/en
Annual data in Statistical Annex
Malnutrition http://www.who.int/nutgrowth/db
Water and sanitation
http://www.who.int/entity/water_sanitation_he
alth/database/en
Ministry of Health
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Disease surveillance/reporting
branch
Health Data Sources – Other
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UNICEF at http://www.unicef.org
CRED-EMDAT provides data on disasters
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http://www.em-dat.net
Mission hospitals
Government district hospitals
Indonesia
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Total population = 219,883,000
Annual population growth rate = 1.4%
Life expectancy at birth = 67 years
Under age 5 mortality rate = 41/1,000
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WHO, 2005
70% of 1-year-olds immunized with 3 doses
of DTP
3.2% of gross domestic product spent on
health
Methods and Tools for
V&A Assessment in the
Health Sector
1A.33
Methods and Tools
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Qualitative assessments
Methods of assessing human health
vulnerability to climate change
WHO Global Burden of Disease Comparative
Risk Assessment
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Environmental Burden of Disease
MIASMA
Other models
Qualitative Assessments
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Available data allow for qualitative
assessment of vulnerability
For example, given current burden of
diarrheal diseases and projected changes in
precipitation, will vulnerability remain the
same, increase, or decrease?
Methods of Assessing Human
Health Vulnerability and
Public Health Adaptation to
Climate Change
Kovats et al., 2003
1A.36
Methods for:
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Estimating the current distribution and
burden of climate-sensitive diseases
Estimating future health impacts attributable
to climate change
Identifying current and future adaptation
options to reduce the burden of disease
Kovats et al., 2003
Estimate Potential Future
Health Impacts
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Requires using climate scenarios
Can use top-down or bottom-up approaches
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Models can be complex spatial models or be
based on a simple exposure-response
relationship
Should include projections of how other
relevant factors may change
Uncertainty must be addressed explicitly
Kovats et al., 2003
Case Study: Risk of Vector-Borne
Diseases in Portugal
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Four qualitative scenarios developed of
changes in climate and in vector populations
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Vector not present
Focal distribution of vector
Widespread distribution of vector
Change from focal to potentially regional
distribution
Expert judgment determined likely risk under
each scenario for 5 vector-borne diseases
Casimiro et al., 2006
Portuguese National Assessment
Vector
Parasite
None Present
Imported
human cases
only
Low prevalence
in
vectors/hosts
High
prevalence
vectors/hosts
None
Present
Negligible
Risk
Negligible
Risk
Negligible
Risk
Negligible
Risk
Focal
Distribu
-tion
Negligible
Risk
Very low
Risk
Low
Risk
Low
Risk
Regional
Negligible
Risk
Very low
Risk
Low
Risk
Medium
Risk
Widespread
Negligible
Risk
Very low
Risk
Medium
Risk
High
Risk
Casimiro & Calheiros 2002
Sources of Uncertainty
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Data
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Models
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Missing data or errors in data
Uncertainty regarding predictability of the
system
Uncertainty introduced by simplifying
relationships
Other
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Kovats et al., 2003
Inappropriate spatial or temporal data
Inappropriate assumptions
Uncertainty about predictive ability of
scenarios
Estimating the Global Health
Impacts of Climate Change
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What will be the total potential health impact
caused by climate change (2000 to 2030)?
How much of this could be avoided by
reducing the risk factor (i.e. stabilizing
greenhouse gas (GHG) emissions)?
McMichael et al., 2004
Comparative Risk Assessment
Greenhouse gas
emissions scenarios
Time
2020s
2050s
Global climate modelling:
2080s
Generates series of maps
of predicted future climate
Health impact model:
Estimates the change in relative
risk of specific diseases
McMichael et al., 2004
2020s
2050s
2080s
Criteria for Selection of
Health Outcomes
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Sensitive to climate variation
Important global health burden
Quantitative model available at the global
scale
McMichael et al., 2004
Health Outcomes Considered
Outcome Class
Incidence /
prevalence
Outcome
Direct effects of heat and
cold
Incidence
Cardiovascular disease deaths
Foodborne & waterborne
diseases
Incidence
Diarrhea episodes
Vector-borne diseases
Incidence
Malaria cases
Natural disasters
Incidence
Incidence
Deaths due to unintentional injuries
Other unintentional injuries
Risk of malnutrition
Prevalence
Non-availability of recommended
daily calorie intake
McMichael et al., 2004
Exposure: Alternative Future
Projections of GHG Emissions
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Unmitigated current GHG emissions trends
Stabilization at 750 ppm CO2-equivalent by
the year 2210
Stabilization at 550 ppm CO2-equivalent by
the year 2170
Average climate conditions for 1961-1990
(WMO climate normal baseline)
Source: UK Hadley Centre models
McMichael et al., 2004
Estimated Mortality (000s) Attributable
to Climate Change, 2000
Malnutrition
Diarrhea
CVD
All
Causes
Deaths /
Million
SEARB
0
1
1
2
7.9
SEARD
52
22
7
80
65.8
McMichael et al., 2004
Relative Risk of Diarrheoa in 2030, by Region
1.1
Climate
scenarios,
s550
as function
of GHG
s750
emissions
1.08
UE
1.04
1.02
1
0.98
0.96
Wpr B
Wpr A
Sear D
Sear B
Eur C
Eur B
Eur A
Emr D
Emr B
Amr D
Amr B
Amr A
Afr E
0.94
Afr D
Relative Risk
1.06
Conclusions
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Climate change may already be causing a significant
burden in developing countries
Unmitigated climate change is likely to cause
significant public health impacts out to 2030
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Largest impacts from diarrhea, malnutrition, and malaria
Uncertainties include:
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McMichael et al., 2004
Uncertainties in projections
Effectiveness of interventions
Changes in nonclimatic factors
Environmental Burden of Disease
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A. Prüss-Üstün, C. Mathers, C. Corvalan,
and A. Woodward. 2003. Introduction and
Methods: Assessing the Environmental
Burden of Disease at National and Local
Levels [pdf available at
http://www.who.int/peh/burden/burdenindex.h
tml]
Climate change document will be published
soon
Climate and Stable Malaria
Transmission
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Climate suitability is a primary determinant of
whether the conditions in a particular location
are suitable for stable malaria transmission
A change in temperature may lengthen or
shorten the season in which mosquitoes or
parasites can survive
Changes in precipitation or temperature may
result in conditions during the season of
transmission that are conducive to increased
or decreased parasite and vector populations
Climate and Stable Malaria
Transmission
(continued)
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Changes in precipitation or temperature may
cause previously inhospitable altitudes or
ecosystems to become conducive to
transmission. Higher altitudes that were
formerly too cold or desert fringes that were
previously too dry for mosquito populations
to develop may be rendered hospitable by
small changes in temperature or
precipitation.
Mean Temperature (°C)
40
38
36
34
32
30
28
26
24
22
20
18
.1
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
16
Proportion of M osquitoes
Surviving One Day
Relationship between Temperature and
Daily Survivorship of Anopheles
Relationship between Temperature and
Time Required for Parasite Development
120
100
Days
80
60
40
20
0
17
19
21
23
25
27
29
31
Mean Temperature (°C )
33
35
37
39
Mean Temperature (°C)
39
37
35
33
31
29
27
25
23
21
19
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
0.00
17
Proportion Surviving
Proportion of Vectors Surviving Time
Required for Parasite Development
The website [http://www.mara.org.za] contains prevalence and population data,
and regional and country-level maps
MARA/ARMA Model
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Biological model that defines a set of
decision rules based on minimum and mean
temperature constraints on the development
of the Plasmodium falciparum parasite and
the Anopheles vector, and on precipitation
constraints on the survival and breeding
capacity of the mosquito
CD-ROM $5 for developing countries or can
download components from website:
www.mara.org.za
MIASMA
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Modeling Framework for the Health Impact
Assessment of Man-Induced Atmospheric
Changes
MIASA was written by Dr. Pim Martens
([email protected]). A fee of US$ 5
is required for a self-extracting CD
Includes modules for thermal stress, malaria,
dengue, and schistosomiasis
Select IPCC scenario and GCM
Other Models
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CiMSiM and DENSim for dengue
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Weather and habitat-driven entomological
simulation model that links with a simulation
model of human population dynamics to project
disease outbreaks
http://daac.gsfc.nasa.gov/IDP/models/index.html
India’s Initial National Communication: Goals
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To identify, analyze, and evaluate the impacts of
climate variability and change on natural
ecosystems, socioeconomic systems, and
human health
To assess the vulnerabilities, which also depend
on the institutional and financial capacities of the
affected communities
To assess the potential adaptation responses
To develop technical, institutional, and financial
strategies to reduce vulnerability
India’s Initial National Communication
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Temperature-related mortality
Vector-borne diseases
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Health effects of extreme weather
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Changing patterns of diseases – malaria, filaria, kala-azar,
Japanese encephalitis, dengue
Diarrhea, cholera, and poisoning caused by biological and
chemical contaminants in water
Damaged public health infrastructure due to cyclones/floods
Social and mental health stress due to disasters and
displacements
Health effects due to insecurity in food production
Malaria in India 1976-2001
Projected Changes in Number of Months
Malaria Can Be Transmitted
Factors Affecting Malaria Distribution and
Prevalence in India
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Climate
Urban settlements
Poverty
Irrigation
Agricultural practices
Land-use change
Methods for Determining a
Health Adaptation Baseline
1A.67
Questions for Designing Adaptation
Policies and Measures
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Adaptation to what?
Is additional intervention needed?
What are the future projections for the
outcome? Who is vulnerable?
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On scale relevant for adaptation
Who adapts? How does adaptation occur?
When should interventions be implemented?
How good or likely is the adaptation?
Current and Future
Adaptation Options
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What is being done now to reduce the
burden of disease? How effective are these
policies and measures?
What measures should begin to be
implemented to increase the range of
possible future interventions?
When and where should new policies be
implemented?
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Kovats et al., 2003
Identify strengths and weaknesses, as well as
threats and opportunities to implementation
Public Health Adaptation
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Existing risks
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Modifying existing prevention strategies
Reinstitute effective prevention programs that
have been neglected or abandoned
Apply win/win or no-regrets strategies
New risks
Options for Adaptations to Reduce
the Health Impacts of Climate Change
Health Outcome
Legislative
Technical
Educational-advisory
Cultural & Behavioral
Thermal stress
Building guidelines
Housing, public
buildings, urban
planning, air
conditioning
Early warning systems
Clothing, siesta
Extreme weather
events
Planning laws,
economic incentives
for building
Urban planning, storm
shelters
Early warning systems
Use of storm shelters
Vector control,
vaccination,
impregnated bednets,
sustainable
surveillance,
prevention & control
programmes
Health education
Water storage
practices
Screening for
pathogens, improved
water treatment &
sanitation
Boil water alerts
Washing hands and
other behavior, use of
pit latrines
Vector-borne diseases
Water-borne diseases
McMichael et al. 2001
Watershed protection
laws, water quality
regulation
Screening the Theoretical Range
of Response Options – Malaria
Theoretical
Range of
Choice
Technically
feasible?
Effective?
Environmentally
acceptable?
Financially
Feasible?
Socially and
Legally
Acceptable?
Closed/Open
(Practical Range
of Choice)
Improved public
health
infrastructure
Yes
Low
Yes
Sometimes
Yes
Open
Forecasting &
early warning
systems
Yes
Medium
Yes
Often
Yes
Open
Public
information &
education
Yes
Low
Yes
Yes
Yes
Open
Control of vector
breeding sites
Yes
Yes
Spraying - no
Yes
Sometimes
Open
Impregnated bed
nets
Yes
Yes
Yes
Yes
Yes
Open
Prophylaxis
Yes
Yes
Yes
Only for the
few
Yes
Closed for many
Vaccination
No
Ebi and Burton, submitted
Closed
Analysis of the Practical Range of
Response Options – Malaria
Theoretical
Range of
Choice
Technically
viable?
Financial
Human skills &
capability? institutional
capacity?
Compatible
with current
policies?
Target of
opportunity?
Improved public
health
infrastructure
Yes
Low
Low
Yes
Yes
Forecasting &
early warning
systems
Yes
Yes
Yes
Yes
Yes
Public
information &
education
Yes
Yes
Sometimes
Yes
Yes
Control of vector
breeding sites
Yes
Sometimes Sometimes
Yes
Yes
Impregnated bed
nets
Yes
Sometimes Yes
Yes
Yes
Prophylaxis
Yes
Sometimes Yes
Yes
Yes
Ebi and Burton, submitted
Thank you
1A.74