David Taylor Professor of Geography Chair, Trinity International Development Initiative Trinity 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, and GPCP ave monthly precipitation data (from Gianotti et al. 2009) Many vector-borne diseases have a strong seasonality component – e.g. malaria

Altitude (m) Prevalence (spleenrate) Data for Kigezi, southwestern Uganda (collated and presented by Menno Bouma) 5 year moving average of survey points y = x (R 2 = , m, untransformed data) Malaria prevalence data for also show a distinct relationship with altitude (presumably proxy for temperature) ? Lake Bunyoni, Kigezi

Ceccato et al., (2006) Am. Soc Trop Med & Hyg Better 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

+ 1 o C increase in ambient temperature = >100% increase disease burden + 2 o C 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 o C per +150 m) Baseline prevalence (survey data, 1960s-1980s) Increasing prevalence Geographic extension C C C C 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

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 ( ) Further development underway