1. . COP-11 Development and Adaptation Days Montreal, 3-4th December 2005 Anticipation, adaptation and climate risk management for health Stephen Connor, International Research Institute for Climate & Society (IRI), The Earth Institute at Columbia University, New York PAHO/WHO Collaborating Centre on early warning systems for malaria and other climate sensitive diseases

2. International Development and Health: Targets/Timelines MDGs by 2015 - health related targets: indirect Water and Sanitation direct < Maternal Mortality direct < Childhood mortality direct < Malaria and other infectious diseases Roll Back Malaria by 2010/15: >access to treatment, epidemic detection and control Abuja Targets by 2005/10 – that 60% of epidemics will be detected within two weeks of inception and 60% responded to within two weeks of detection – need to know where and when they are likely to occur…

3. Climate-Sensitive Disease & EWS Using Climate to Predict Infectious Disease Epidemics. WHO 2005 Diseases include: Inter-annual variability: Sensitivity to climate # : Climate variables: Influenza* * * * ** (<T) Meningitis* * * * * >T, R) Leishmaniasis* * * * (>T,>R) R.V. Fever* * * >R (<T) Cholera* * * * * (>T) Malaria* * * * * (>R,T,H) Dengue* * * * * (>R,T,H).. bacterial, viral and protozoan....other candidates, e.g some respiratory diseases not included here…. … must remember socio economic factors very important…

4. Recognizing the impact of climate variability Rainfall in the Sahel 1930-2000 West Africa provides one of the most dramatic examples worldwide of climate variability that has been directly and quantitatively measured [Hulme, 2001]. Changes in malaria <endemicity (Faye et al 1995) >epidemicity (Mouchet et al 1996) Changes in meningitis >epidemic frequency >southward extension of ‘Meningitis Belt’ (Molesworth et al 2003) 30 year drought !! Very important consideration when establishing baselines !!

5. Managing risk associated with climate variability.. Integrated MEWS gathering cumulative evidence for early and focused epidemic preparedness and response (WHO 2004)…. Flag 1 – Flag 2 – Flag 3 >>> Planning & Response

6. Example of malaria in Botswana...inter year variability in malaria is related to variability in rainfall ………… 20+ years of confirmed incidence data Epidemics88 93 96/9799/00 Change in drug policy CQ - SP

7. Vulnerability monitoring Many factors may increase the vulnerability of a population to malaria epidemics: >drug resistance, <health service, food insecurity, migrations, co-infections, etc - increasing the severity of disease outcome should an epidemic occur Routine assessment of SP efficacy in three sentinel sites, susceptibility of the vector to insecticides, and coverage of IRS achieved each season Requests regular assessments of drought and food security status from the SADC Drought Monitoring Centre and disseminates the information to the epidemic prone DHTs Recognised need for extra vigilance in malaria control programme monitoring, and surveillance among its most vulnerable groups, including those co-infected with HIV, TB, etc. Example in practice: Botswana …

8. Seasonal Forecasting Seasonal climate forecasts offer the potential to predict the rainfall season many months in advance ….. But forecast information is uncertain …. What is the evidence that they may be useful for malaria early warning ? High malaria years predicted November – January DEMETER standardised ensemble mean and adjusted malaria incidence anomalies (Thomson, et al. in press: Nature) Example in Botswana ….. Low malaria years predicted Opportunities for planning and preparedness >>>>>>>>

9. Environmental monitoring Seasonal and inter year variability in malaria related to rainfall ….. But again how certain ? What is the evidence that it may be useful for malaria early warning? Opportunities for prevention and more localised preparedness >> Example in Botswana … (Thomson, et al 2005: AmJTropMed&Hyg) high malaria years predicted low malaria years predicted

10. Case surveillance There are currently few case surveillance systems in SSA that could warn of an epidemic with sufficient lead time to mount an effective response. However, they are essential to the early detection component of a MEWS. A number of indicators: 2 STD, Normal Channel, C-SUM, tested Example in Botswana.. Case thresholds defined for three levels of alert … Threshold 1- 600 unconfirmed cases/week >>> Action Plan 1. Threshold 2- 800 unconfirmed cases/week >>> Action Plan 2. Threshold 3- 3000 unconfirmed cases/week >>> Action Plan 3.

11. This example discussed at 1 st SA Regional Epidemic Malaria Outlook Forum, Harare, 2004 Improving epidemic malaria planning, preparedness and response in Southern Africa. (DaSilva, et al. 2004) http://www.malariajournal.com/content/3/1/37

12. And for application of the approach elsewhere ? World Bank GEF for INAP in Colombia (malaria and dengue) AfDB-WHO in East Africa (malaria and..) AfDB-WHO in West Africa/GEF ? (malaria and meningitis) ? in South East Asia ?

13. Our climate: a series of interacting systems Can we see patterns in those systems ? Can we use those patterns to understand climate impacts better? Can we use this knowledge to predict and monitor the climate and manage the risk associated with it?

14. Managing climate sensitive disease Many of the MDG goals and targets (health and non-health) are sensitive to climate variability (DFID 2003) Establish firm evidence base for linkage Anticipate impacts (who, where and when) Monitor key variables and indicators Adapt planning preparedness and response measures according to changes in risk Build responsive capacity……………. IPCC identified rebuilding public health infrastructure as “the most important, cost effective and urgently needed” adaptation strategy for climate change – in effect a no regrets adaptation strategy (WHO-UNEP-WMO 2003)

15. Thank you for your attention sjconnor@iri.columbia.edu PAHO/WHO Collaborating Centre on early warning systems for malaria and other climate sensitive diseases