Global Information Management System on Sanitation and Drinking-water (GIMS)

1. GlobalInformation Management System on Sanitation and Drinking-water(GIMS) Rifat Hossain

2. Presentation overview: from data collection, to analysis and effective decision making • What is GIMS? • GIMS and the bigger picture • Global health situation • WHO strategy for health information • GIMS functionality and connectivity • GIMS clients • JMP • GLASS • Benefits and next steps

3. What is GIMS?

4. Introduction • 2.5 billion people without improved sanitation, around 900 million people without improved drinking-water • No surprise: diarrhoeal disease is the 2nd leading cause of death from infectious diseases, even before HIV/AIDS - mostly children • Such deaths could be prevented, with good evidence based policies • It is difficult to make pro-poor evidence-based policy decisions: • Difficult to relate improvements in service levels to the drivers of the sector • Missing links between service levels to other socio-economic indicators, burden of water-borne diseases, climate resilience etc.

5. What do users want from WHO? Total count: 7999

6. What improvements are needed? Total count: 5598

7. GIMS:Why another system? • To strengthen the evidence base: filling gaps and links • Robust access estimates (use for JMP etc.) • Links between sanitation, drinking-water and health (disease burden etc.) • Links between WatSan and other environmental issues • To measure progress of societies; link between service levels to poverty, BoD, climate resilience etc. • Build national capacity through • Cost-effective dynamic online data reconciliation • An integrated country/regional coordination mechanism and its interactive and dynamic support to populate GIMS

8. GIMS…for a more robust estimate!

9. GIMS: to reduce burden on data collection • Integrated into Global Health Observatory • A WHO data management portal • Connectivity to country data management tool • DevInfo automatic connectivity • Other data management system (WSP, World Bank, OECD etc.)

10. Scenario 2020: climate changeResilience to increased rainfall High Improved pit latrines Sewers Vulnerability Medium Community managed piped water Protected wells (shallow) Low Utility managed piped water Septic tanks Protected wells (deep) Protected springs Rainwater collection High Medium Low Adaptability

11. GIMS:Who is it for? • Country authorities • Global bodies who provides policy relevant information • Researchers • Policy makers • Etc.

12. GIMS: components • A comprehensive data management system • Data collection • Data analysis • Data dissemination • A dynamic data linking system • Data to be shared with interested parties • Dynamic, web-enabled (Web2.0) • As opposed to static Web1.0 architecture

13. Information flow between data source to GIMS (1) OH SDMX Registry users GIMS Internet Agency A Agency B Agency C International Internet Internet Internet National Region B2 Region A2 Region C2 Region A3 Region A1 Region B3 Region B1 Region C3 Region C1

14. Information flow between data source to GIMS (2) OH SDMX Registry users International (GIMS) Internet National Region B2 Region A2 Region C2 Region A3 Region A1 Region B3 Region B1 Region C3 Region C1

15. GIMS and the bigger picture:

16. A changing world: complex and crowded Everything is intimately interconnected Globalization has flattened the world and speeded up trade leading to: increased movements of people expansion of international trade social and environmental changes Microbes are on the move… Health security is at stake The public health landscape

17. … crowded with problems – new and old Rapidly evolving threats posed by emerging pandemic and epidemic prone diseases (e.g. H1N1 2009, SARS 2003 & Avian Flu 2003-2008 ) Epidemic-prone diseases that are known risks (HIVAIDS, cholera, meningitis, yellow fever) Unexpected outbreaks of new or previously rare diseases (eg. Ebola, West Nile fever in US) Accidental or intentional release of biological, chemical and/or nuclear agents Older problems that keep on getting bigger (e.g tuberculosis) Endemic diseases that have been with us for thousands of years (malaria, leprosy, guinea worm, lymphatic filariasis, polio, onchocerciasis)

18. … compounded by Collapse of public health infrastructure Ineffective vector control programmes (Chikungunya) Development of antimicrobial resistance (XDR-TB) Increasing burden of chronic diseases due to our changing lifestyles Environment and climate change

19. Need for tools, methodologies & standards Multi source:integrate data from different sources using different data collection methodologies Multi sector:consolidate vital data from different sectors Multi level:disseminate data across different geographic levels Country level Health Remote field level Education Environment Global level Regional level Water that can define, collect and assemble data from: Community surveys Population surveys Laboratory results

20. And that can analyse and communicate information rapidly and in meaningful ways as to assist in guiding effective response Need for tools, methodologies & standards

21. Challenges in Information Management • Fragmentation and duplication • Lack of use of standards (case definitions, identifiers, geo-coding, data exchange) • Lack of interoperability between database systems • Uncoordinated approaches to data collection • Data quality assessment and transparency: often weak • Major data gaps remain • Duplication of efforts/resources • Data portability, use and decision making is hampered

22. WHO Strategy on Health Information Dr Margaret Chan Opening remarks at the Fourth Global Meeting of Heads of WHO Country Offices Geneva, 12 November 2007 "Without fundamental health data, we are working in the dark. We may also be shooting in the dark. ……" • To improve the availability, quality and use of data and statistics on key health priorities • To address data gaps: availability and quality of data used for decision making • To strengthen country capacity to support better health systems surveillance

23. WHO's Health Information Strategy Improve access to WHO's data Improve quality of data Leverage and connecting to existing database Address data gaps Build country capacity Global Health Observatory Monitoring the health situation and trends in the world Disease PHC/health Equity Health Outbreak Africa systems Gauge MDGs Monitoring performance Conflicts & NCD & Mortality GIMS Other Emergencies risk & disease regions Tracking factors burden World Health Statistics Integrated Country Health Profiles

24. GHO Vision Functions Data warehouse Data production/ decentralised activities Health Systems NCDs and Risk Factors WHO Programmes XML Dashboard Agency partners XML Disease Outbreak Monitoring Environmentand GIMS XML Countries Analysis XML Surveys Mortality & GBD MDGs Charts Metadata standardsDDI, Dublin Core, SDMX… Data exchange standardsIXF3, SDMX, XLS, CSV Maps

25. What will GHO not do • Centralize all data production and dissemination. • Control individual data producers: • statistical techniques for validating data • imputation of missing values • correction for bias, heterogeneity in the values of quantities of interest • Over-ride existing legacy systems and databases Instead • preserve the independence of data producers while making data and metadata part of a coherent and seamless corporate system • A constellation or federation of databases.

26. GIMS functionality and connectivity

32. Country sheets through GIMS/GHO

33. Real time data entry

34. ConnectivityAccessing health data • Core health statistics • Epidemic and Outbreaks (cholera, Rift valley fever etc • Neglected diseases of poverty (e.g guinea worm, schistosomiasis, trachoma.. • Health systems • Global burden of diseases • Environmental risk factors

35. ConnectivityLinks to partner databases • Poverty (world Bank) • Financial (OECD) • UN-Water "federated" database • Climate change (WMO, UNEP, FAO, universities,..)

36. ConnectivityLinks to country databases: eg health services

37. % Districts with improved access to water

38. InteroperabilityLinks to country databases: health services • Overlaying public health facilities, laboratories, stockpiles, schools, workplaces, to support response .. ( targeting of drugs, equipment, surge capacity.) • Infrastructures (roads, schools, airports, etc.)

39. ConnectivityLinks to country databases: health services • Overlaying public health facilities, laboratories, stockpiles, schools, workplaces, to support response .. ( targeting of drugs, equipment, surge capacity.) • Infrastructures (roads, schools, airports, etc.) • Water point mapping

40. Integrating remotely sensed data for GIS analysis • Data collection from earth observation satellites (10-35m2 resolution) • Water quality data • Hydrological data • Land use • Risk assessment (catchment) • Risk assessment (water-related disease) • Trends • Potential use of high resolution images (2m2 resolution) • Validation of coverage data • Validation of access data

41. GIMS clients

42. GIMS in the context of W&S Monitoring The tool The use of the tool Impact Disease prevention, gender equity, poverty reduction, economic growth WHO/UNICEF Joint Monitoring Programme (JMP)  Global Information Management System (GIMS) MDG monitoring Increased service and coverage levels Evidence base UN-Water Global Annual Assessment (GLAAS)  Increased sector and aid effectiveness Transparency, mutual accountability, aid prioritization and targeting

43. GIMS for JMP Compare, understand, align data Link between Access / Health Access figures (use) Nat. Sector Agencies Infrastructure / service provision + other indicators(quality, sustainability…) Data Cholera outbreaks, diarrhoeal diseases Household Surveys, Censuses Nat. Statistics Offices Nat. Health Statistics Data reconciliation process Data collection to reduce data gaps Analysis of outcome of access to WATSAN

44. What is GLAASAt a glance…

45. Benefits and next steps

46. Benefits of GIMS • Comprehensive picture of the situation • Dynamic linking of service levels to other indicators of progress • Assessing problems, resources and gaps • Guiding rational allocation of resources • Building country capacity for strengthening evidence base • Provide standards-based platform for integrating, analysing and using country data • Participatory data gathering and analysis • Local ownership and institutional capacity building • Fostering a collaborative /open approach • Collaborative community of practice (involving public ,private, NGOs, civil society) • Accessible, shareable, transparent data • Open source tools • Leveraging collective investments and resources

47. Next steps • Incremental data uploads • MDGs, World health statistics, Global Burden of Disease, outbreaks • Water and sanitation country survey data • Water service provider data (2010) • Incremental functionality enhancements -leveraging efforts/tools of partners (World Bank, OECD, UN………) • Open source data architecture and platform under development • UI and customizable analyses tools • 1st launch of data dissemination system: end 2009 • Closer links to regional and country databases/observatories • Expanding the partner network • Project plan, roadmap and resource mobilisation

48. THANK YOU For further information: hossainr@who.int