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

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Presentation Transcript
presentation overview from data collection to analysis and effective decision making
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
introduction
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.
gims why another system
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
gims to reduce burden on data collection
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.)
scenario 2020 climate change resilience to increased rainfall
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

gims who is it for
GIMS:Who is it for?
  • Country authorities
  • Global bodies who provides policy relevant information
  • Researchers
  • Policy makers
  • Etc.
gims components
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
slide13

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

slide14

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

the public health landscape

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
crowded with problems new and old
… 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)

compounded by
… 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

need for tools methodologies standards
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

slide20

And that can analyse and communicate information rapidly and in meaningful ways as to assist in guiding effective response

Need for tools, methodologies & standards

challenges in information management
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
who strategy on health information
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
who s health information strategy
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

gho vision
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

what will gho not do
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.
connectivity accessing health data
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
slide35

ConnectivityLinks to partner databases

  • Poverty (world Bank)
  • Financial (OECD)
  • UN-Water "federated" database
  • Climate change (WMO, UNEP, FAO, universities,..)
interoperability links to country databases health services
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.)
connectivity links to country databases health services
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
slide40

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
gims in the context of w s monitoring
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

gims for jmp
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

benefits of gims
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
next steps
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
thank you
THANK YOU

For further information:

hossainr@who.int