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

ed & H

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