Transcript Document

Vulnerability and Adaptation
Assessments Hands-On
Training Workshop
HUMAN HEALTH SECTOR
1A.1
Outline




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


Pathways for weather to affect health
Potential health impacts of climate change

Extreme weather events





Temperature
Floods
Vector-borne diseases
Diseases related to air pollution
Diarrheal diseases
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)
Pathways from Driving Forces
to Potential Health Impacts
Corvalan et al., 2003
Drivers of Health Issues






Population density
Urbanization
Public health infrastructure
Economic and technologic development
Environmental conditions
Populations at risk




Poor
Children
Increasing population of elderly residents
Immunocompromised
Climate Change
May Entail
Changes in
Variance, as Well
as Changes in
Mean
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.
2000 Flood in Mozambique

Heavy rains from Cyclones Connie and Eline in
February 2000 caused large-scale flooding of the
Limpopo, Incomati, Save, and Umbeluzi rivers


Environmental degradation and poor river system
management and protection contributed to the crisis
700 people died, 250,000 people were displaced,
and 950,000 required humanitarian assistance (of
which 190,000 were children under the age of 5)

14,800 people were rescued by helicopter
Health Impacts of Floods
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
Proportion of malaria cases and
anomalies in maximum temperture: Kenya
70
4
60
3
50
2
1
40
0
30
-1
20
Jan 97May SepJan 98May SepJan 99May Sep
Temperature anomalies
Percent of malaria cases in hospital
5
-2
Time
Malaria cases
A. Githeko,
communication
Dr.
Githeko,personal
personal
communication
Maximu m tempMi nimu m Temp
Climate Change and Malaria
under Different Scenarios (2080)


Increase: East Africa, Central Asia, Russian Federation
Decrease: Central America, Amazon [within current vector limits]
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
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
2001
2002
2003
Resources

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.


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.

Pdf available at
http://www.who.dk/document/E81923.pdf
Health Data to Determine the
Current Burden of ClimateSensitive Diseases
1A.19
Questions to be Addressed

What climate-sensitive diseases are
important in the country or region?


What factors other than climate should be
considered?



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

World Health Report provides regional-level data for
all major diseases



WHO databases



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_health/datab
ase/en
Ministry of Health

Disease surveillance/reporting
branch
Health Data Sources – Other


UNICEF at http://www.unicef.org
CRED-EMDAT provides data on disasters



http://www.em-dat.net
Mission hospitals
Government district hospitals
Mozambique




Total population = 18,863,000
Annual population growth rate = 2.4%
Life expectancy at birth = 45 years
Under age 5 mortality rate = 158/1,000


WHO, 2005
72% of 1-year-olds immunized with 3 doses
of DTP
5.8% of gross domestic product spent on
health
Seychelles National
Communication
Methods and Tools for
V&A Assessment in the
Health Sector
1A.25
Methods and Tools




Qualitative assessments
Methods of assessing human health
vulnerability to climate change
MARA/ARMA – climate suitability for stable
malaria transmission
WHO Global Burden of Disease Comparative
Risk Assessment


Environmental Burden of Disease
Other models
Qualitative Assessments


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.28
Methods for:



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


Requires using climate scenarios
Can use top-down or bottom-up approaches



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 VectorBorne Diseases in Portugal

Four qualitative scenarios developed of
changes in climate and in vector populations





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
Kovats et al., 2003
Sources of Uncertainty

Data


Models



Missing data or errors in data
Uncertainty regarding predictability of the system
Uncertainty introduced by simplifying relationships
Other



Inappropriate spatial or temporal data
Inappropriate assumptions
Uncertainty about predictive ability of scenarios
Kovats et al., 2003
Estimating the Global Health
Impacts of Climate Change

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)?
Campbell-Lendrum et al., 2003 (pdf available)
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
Campbell-Lendrum et al., 2003
2020s
2050s
2080s
Criteria for Selection of
Health Outcomes



Sensitive to climate variation
Important global health burden
Quantitative model available at the global scale





Malnutrition (prevalence)
Diarrhoeal disease (incidence)
Vector-borne diseases – dengue and falciparum
malaria
Inland and coastal floods (mortality)
Heat and cold related CVD mortality
Campbell-Lendrum et al., 2003
Exposure: Alternative Future
Projections of GHG Emissions




Unmitigated current GHG emissions trends
Stabilization at 750 ppm CO2-equivalent
Stabilization at 550 ppm CO2-equivalent
1961-1990 levels of GHGs with associated
climate

Campbell-Lendrum et al., 2003
Source: UK Hadley Centre models
8
Relative Risk of Deaths and Injuries in Inland
Floods in 2030, by Region
7
s550
s750
UE
5
4
3
2
1
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
Afr D
Relative Risk
6
Relative Risk of Diarrheoa in 2030, by Region
1.1
Climate
s550
scenarios,
ass750
function
of GHG
UE
emissions
1.08
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
Estimated Death and DALYs
Attributable to Climate Change
2000
Floods
2020
Malaria
Diarrhea
Malnutrition
120 100 80
60
40
20
Deaths (thousands)
Campbell-Lendrum et al., 2003
0
2
4
6
8
DALYs (millions)
10
Conclusions



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
 Largest impacts from diarrhea, malnutrition, and
vector-borne diseases
Uncertainties include:
 Uncertainties in projections
 Effectiveness of interventions
 Changes in nonclimatic factors
Campbell-Lendrum et al., 2003
Environmental Burden
of Disease


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
The website [http://www.mara.org.za] contains prevalence and population data,
and regional and country-level maps
Climate and Stable Malaria
Transmission



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)

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.
MARA/ARMA Model


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
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
Mozambique – Endemic Malaria
Season Length
Mozambique – Endemic Malaria
Prevalence
Mozambique – Endemic Malaria
Prevalence by Age
Climate Suitability for Stable Malaria
Transmission in Zimbabwe Under
Different Climate Change Scenarios
Ebi et al., In press
Objective: to look at the range of responses in the climatic
suitability for stable falciparum malaria transmission under
different climate change scenarios in Zimbabwe
1A.58
Malaria in Zimbabwe
Cases by Month


Source:
South African Malaria Research Programme
Ebi et al., In press

Patterns of stable
transmission follow
pattern of precipitation
and elevation (which in
turn influences
temperature)
> 9,500 deaths and
6.4 million cases
between 1989 and 1996
Recent high-altitude
outbreaks
Methods



Baseline climatology determined
COSMIC was used to generate Zimbabwespecific scenarios of climate change;
changes were added to baseline climatology
Outputs from COSMIC were used as inputs
for the MARA/ARMA (Mapping Malaria Risk
in Africa) model of climate suitability for
stable Plasmodium falciparum malaria
transmission
Ebi et al., In press
Data Inputs

Climate data



Mean 60 year climatology of Zimbabwe on a
0.05° lat/long grid (1920-1980)
Monthly minimum and maximum temperature
and total precipitation
COSMIC output

Ebi et al., In press
Projected mean monthly temperature and
precipitation (1990-2100)
Climate in Zimbabwe






Rainy warm austral summer October-April
Dry and cold May-September
Heterogeneous elevation-dictated
temperature range
Strong interannual and decadal variability in
precipitation
Decrease in precipitation in the last 100
years (about 1% per decade)
Temperature changes 1933-1993


Ebi et al., In press
Increase in maximum temperatures +0.6°C
Decrease in minimum temperatures -0.2 °C
GCMs




Canadian Centre for Climate Research
(CCC)
United Kingdom Meteorological Office
(UKMO)
Goddard Institute for Space Studies (GISS)
Henderson-Sellers model using the CCM1 at
NCAR (HEND)
Ebi et al., In press
Scenarios

Climate sensitivity



High = 4.5°C
Low = 1.4°C
Equivalent carbon dioxide (ECD) analogues
to the 350 ppmv and 750 ppmv GHG
emission stabilization scenarios of the IPCC
SAR
Ebi et al., In press
Assumptions



No change in the monthly range in minimum
and maximum temperatures
Permanent water bodies do not meet the
precipitation requirements
Climate did not change between the baseline
(1920-1980) and 1990
Ebi et al., In press
Fuzzy Logic Value



Fuzzy logic boundaries established for
minimum, mean temperature, and
precipitation
0 = unsuitable
1 = suitable for seasonal endemic malaria
Ebi et al., In press
Assignment of Fuzzy Logic
Values to Climate Variables
Fuzzy Logic Value for Mean Temperature
1.2
Fuzzy Value
1
0.8
0.6
0.4
0.2
39.5
37.5
35.5
33.5
31.5
29.5
27.5
25.5
23.5
21.5
19.5
17.5
0
Mean Temperature (°C)
Fuzzy Logic Value for Minimum Temperature
1.2
1.2
1
1
Precipitation (mm)
Minimum Temperature (°C)
6.5
6.3
6.1
5.9
5.7
5.5
5.3
5.1
4.9
4.7
4.5
4.3
84
80
76
72
68
64
60
56
52
48
44
40
36
32
28
24
20
16
0
8
0
12
0.2
4
0.2
4.1
0.4
3.9
0.4
0.6
3.7
0.6
0.8
3.5
Fuzzy Value
0.8
0
Fuzzy Value
Fuzzy Logic Value for Precipitation
Climate Suitability Criteria

Fuzzy values assigned to each grid




For each month, determined the lowest fuzzy
value for precipitation and mean temperature
Determined moving 5-month minimum fuzzy
values
Compared these with the fuzzy value for the
lowest monthly average of daily minimum
temperature
Assigned the lowest fuzzy value
Ebi et al., In press
UKMO


S750 ECD stabilization scenario with
4.5°C climate sensitivity
Model output

Precipitation


Temperature

Ebi et al., In press
Rainy season (ONDJFMA) increase in
precipitation of 8.5% from 1990 to 2100
Annual mean temperature increase by 3.5°C
from 1990 to 2100, with October temperatures
increasing more than July temperatures.
Baseline
Ebi et al., In press
2025
Ebi et al., In press
2050
Ebi et al., In press
2075
Ebi et al., In press
2100
Ebi et al., In press
Conclusions




Assuming no future human-imposed
constraints on malaria transmission, changes
in temperature and precipitation could alter
the geographic distribution of stable malaria
transmission in Zimbabwe
Among all scenarios, the highlands become
more suitable for transmission
The lowveld and areas currently limited by
precipitation show varying degrees of
change
The results illustrate the importance of using
several climate scenarios
Ebi et al., In press
Other Models

MIASMA


Global malaria model
CiMSiM and DENSim for dengue


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
Sudan National Communication


Using an Excel spreadsheet, modeled
malaria based on relationships described in
MIASMA
Calculated monthly changes in transmission
potential for the Kordofan Region for the
years 2030-2060, relative to the period 19611990 using the IPCC IS92A scenario,
simulation results of HADCM2, GFDL, and
BMRC, and MAGICC/SCENGEN
Sudan – Projected Increase in
Transmission Potential of Malaria in 2030
Sudan – Projected Increase in
Transmission Potential of Malaria in 2060
Sudan – Malaria Projections

Malaria in Kordofan Region could increase
significantly during the winter months in the
absence of effective adaptation measures



The transmission potential during these
months is 75% higher than without climate
change
Under HADCM2, the transmission potential
in 2060 is more than double baseline
Transmission potential is projected to
decrease during May-August due to
increased temperature
Methods for Determining a
Health Adaptation Baseline
1A.81
Questions for Designing Adaptation
Policies and Measures



Adaptation to what?
Is additional intervention needed?
What are the future projections for the
outcome? Who is vulnerable?




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



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?

Kovats et al., 2003
Identify strengths and weaknesses, as well as
threats and opportunities to implementation
Public Health Adaptation to
Climate Change

Existing risks




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