Confronting the challenge of climate change &
infectious diseases in eastern Africa:
The HEALTHY FUTURES project
David Taylor
Professor of Geography
Chair, Trinity International Development Initiative
Trinity College, University of Dublin, Ireland
HEALTHY FUTURES aims to provide decision support tools that have
their base in good scientific evidence/procedures to improve the
efficacy of future investments in public health that target waterrelated vector-borne infectious diseases in eastern Africa
Two major research-based challenges:
(1) Better understanding of links between environment (including
climate) and infectious diseases
(2) Using this improved understanding to better anticipate future
changes in these diseases as a result of environmental
variability, including changes in climate & seasonality
Assumption 1: Disease outcomes are susceptible inter alia to environment
Almost 25% of global
disease burden is explained
by environment:
Figure below shows diseases with largest environmental
component.
94% diarrheal
42% malaria
41% lower respiratory
The young are particularly
vulnerable – children under
age 14 are 44% more likely
to die as a result of
environment-related
illnesses than general
population
Information from Prüss-Üstün and Corvalán (2007). Data are for 2002
Assumption 2: Environments (including climate) in the region are changing
Wetland development
for rice in Rwanda
Thomson et al.,
(2011) Africa
needs climate
data to fight
disease Nature
Many vector-borne diseases have a strong seasonality component – e.g. malaria
Weekly malaria incidence in Niamey, Niger, 2001-2003 and GPCP ave monthly
precipitation data (from Gianotti et al. 2009)
Malaria prevalence data for also show a distinct relationship with
altitude (presumably proxy for temperature)
80
5 year moving average of survey points
70
60
50
40
Lake Bunyoni, Kigezi
30
?
20
10
0
900
1100
1300
Altitude (m)
y = -0.1082x + 175.67
(R2 = 0.5247, 900-1600 m, untransformed
data)
1500
1700
1900
2100
Data for Kigezi, southwestern Uganda
(collated and presented by Menno Bouma)
Better understanding of disease-environment relationships can itself
contribute to improved efficacy in delivery of health services
Madeleine C. Thomson,
IRI, Earth Institute,
Columbia University, New York
Ceccato et al., (2006) Am. Soc Trop Med & Hyg
e.g.
Seasonality
of malaria in
Eritrea
Major challenges remain
•Quality of data available
•Silos of knowledge
•Fixation on treatment rather than prevention
•Socio-economic confounding factors in environment-disease
relationships
but the risks of doing nothing are potentially enormous
Population between 1000 and 2500 m in eastern Africa. Shift of the prevalence
curve based on the central African lapse rate ( ca. -1 oC per +150 m)
80
1200
population x 1000
Prevalence x Population = “Cases”
Increasing
prevalence
70
60
+ 2 0C
1000
800
50
40
+ 1 0C
600
30
Geographic
extension
400
200
prevalence (% )
1400
20
+ 1 0C
10
+2
0C
0
0
2500
2400
2300
2200
2100
2000
1900
1800
1700
1600
1500
1400
1300
1200
1100
1000
altitude (m)
+ 1o C increase in ambient temperature = >100% increase disease burden
+ 2oC increase = > 250% increase in disease burden
Baseline prevalence (survey data, 1960s-1980s)
Climate change - the greatest challenge to global health
in the current century?
Costello et al. (2009) Lancet/UCL Global Health Commission
but: ‘health professionals have barely begun to engage with an
issue that should be a major focal point for their research,
preparedness planning and advocacy’.
Costello et al. (2009: 1659) Lancet/UCL Global Health Commission
And: though UN Framework Convention Climate Change (UNFCCC)
mentions health, COP meetings have barely considered health as an
issue until COP-16 (even then health was a focus of one side event
and Cancún agreements only mention health once - under
adaptation)
In other words – largely ignored by the international community!
EU FP7 funded research project
aims to provide the scientific basis
for better prediction of future
outbreaks of three water-related
Vector-Borne Diseases (VBDs) - as
a result of environmental changes in the East African Community
region of eastern Africa
Three target VBDs: malaria,
schistosomiasis & Rift Valley Fever
One outcome of the research will
be the delivery of improved
Decision Support Tools
Proposed field site for highland malaria and schistosomiasis:
Lake Burera, Rwanda
http://www.healthyfutures.eu/
Disease information and
associated socioeconomic,
historical and environmental
data
Downscaled climate,
surface hydrology and
landcover modelling
Disease transmission and
dynamic modelling
Vulnerability
assessment &
mapping
Developing and promoting
adaptive capability
Decision support
HEALTHY FUTURES researchers: a bridge between data providers and
users of information aimed at improving adaptation
e.g. Human host component of dynamic malaria model that does
not include socio-economic confounding factors ....
Parasite ratio from new HEALTHY FUTURES (ICTP, Trieste, Italy) VECTRI
model using simple pond model (2000-2010)
•Rates are too low in
eastern Rwanda due to
coarse temperature
resolution
•No immunity in model
yet, PR very high in
some endemic regions
Further development underway