David Taylor Professor of Geography Chair, Trinity International Development Initiative Trinity College, University of Dublin, Confronting the challenge of climate change & infectious diseases in eastern Africa: The HEALTHY FUTURES project
Dec 19, 2015
David TaylorProfessor of Geography
Chair, Trinity International Development InitiativeTrinity College, University of Dublin, Ireland
Confronting the challenge of climate change & infectious diseases in eastern Africa:
The HEALTHY FUTURES project
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 water-related 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
Information from Prüss-Üstün and Corvalán (2007). Data are for 2002
Figure below shows diseases with largest environmental component.
Almost 25% of global disease burden is explained by environment:
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
Assumption 1: Disease outcomes are susceptible inter alia to environment
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
Weekly malaria incidence in Niamey, Niger, 2001-2003 and GPCP ave monthly precipitation data (from Gianotti et al. 2009)
Many vector-borne diseases have a strong seasonality component – e.g. malaria
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Data for Kigezi, southwestern Uganda (collated and presented by Menno Bouma)
5 year moving average of survey points
y = -0.1082x + 175.67(R2 = 0.5247, 900-1600 m, untransformed data)
Malaria prevalence data for also show a distinct relationship with altitude (presumably proxy for temperature)
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Lake Bunyoni, Kigezi
Ceccato et al., (2006) Am. Soc Trop M
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ygBetter understanding of disease-environment relationships can itself
contribute to improved efficacy in delivery of health services
e.g. Seasonality of malaria in Eritrea
Madeleine C. Thomson, IRI, Earth Institute,
Columbia University, New York
Major challenges remain
but the risks of doing nothing are potentially enormous
•Quality of data available
•Silos of knowledge
•Fixation on treatment rather than prevention
•Socio-economic confounding factors in environment-disease relationships
+ 1o C increase in ambient temperature = >100% increase disease burden
+ 2oC increase = > 250% increase in disease burden
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)
Baseline prevalence (survey data, 1960s-1980s)
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Prevalence x Population = “Cases”
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!
Climate change - the greatest challenge to global health in the current century?
Costello et al. (2009) Lancet/UCL Global Health Commission
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
Disease transmission and dynamic modelling
Vulnerability assessment &
mapping
Decision support
Downscaled climate, surface hydrology and landcover modelling
Developing and promoting adaptive capability
e.g. Human host component of dynamic malaria model that does not include socio-economic confounding factors ....
HEALTHY FUTURES researchers: a bridge between data providers and users of information aimed at improving adaptation
•Rates are too low in eastern Rwanda due to coarse temperature resolution
•No immunity in model yet, PR very high in some endemic regions
Parasite ratio from new HEALTHY FUTURES (ICTP, Trieste, Italy) VECTRI model using simple pond model (2000-2010)
Further development underway