1. Creating an information system for the Global Polio Eradication Initiative
IDM 2018 Symposium
Paul Chenoweth, WHO (presented by Arie Voorman, BMGF)

2. Programmatic implications
Outline
Introduction
Context to the Global Polio Eradication Initiative
System Objectives
Delivering a system
Key milestones
Challenges
Outcome
Programmatic implications

3. Global Polio Eradication Initiative (GPEI)
Introduction (1)
Global Polio Eradication Initiative (GPEI)
Is a public-private partnership led by national governments with five partners – WHO, Rotary International, CDC, UNICEF and BMGF
Goal: to complete the eradication and containment of all wild, vaccine-related and Sabin polioviruses, such that no child ever again suffers paralytic poliomyelitis

4. Global Polio Eradication Initiative (GPEI)
Introduction (2)
Global Polio Eradication Initiative (GPEI)
4 part strategy
Surveillance
Disease and Laboratory
In 2017, 22 wild poliovirus were reported from nearly 100,000 cases which exhibited the non-specific symptoms of poliomyelitis
Routine Immunization
Supplementary Immunization (over 160 campaigns in 2017 – see below)
Targeted mop-up campaigns

5. Global Wild Poliovirus & cVDPV Cases1, Previous 12 Months2
Introduction (3)
22/06/2019
Global Wild Poliovirus & cVDPV Cases1, Previous 12 Months2
1988: 125 endemic countries with approximately 350,000 cases
Wild poliovirus type 1
cVDPV type 2
Endemic country
1Excludes viruses detected from environmental surveillance 2Onset of paralysis 11 April 2017 – 10 April 2018
Data in WHO HQ as of 10 Apr. 2018
Data in WHO HQ as of 30 Nov 2010

6. Global Polio Eradication Initiative (GPEI)
Introduction (4)
Global Polio Eradication Initiative (GPEI)
Factors influencing the quantity and quality of the data
Multi part strategy
Global program
All WHO member states (194)
Eradication program with deadlines
Weekly reporting from all member states
Established program
Launched in 1988
Well funded
Over US$15 billion between 1988 and 2017
The GPEI is “data driven”
WHO generates extensive weekly analysis – used to inform daily operations
Partners provide in-depth analysis – used to inform policy and strategy
Quantity of data is unrivaled by any other disease program

7. Harmonize and consolidate data from various sources
PolIS Objectives
Harmonize and consolidate data from various sources
Simplify data management through automation
Quality checks at all levels
Standard set of outputs
Facilitate data and information sharing, plus in depth analyses in a variety of tools by a variety of users of different skill levels

9. PolIS Objectives - automation
Before
After *
Scattered data spread over multiple file repositories
Harmonized data in a centralized data platform
Manual “prone to errors” collection process
Automated collection processes with quality checks
No standardized geographic reference data
“Geo-database” used to capture and display standardized geography
No standard list of indicators and definitions
Standardized list of indicators, definitions, and calculations
Inefficient data analysis
More efficient use of staff’s time
Analysis capability limited to data managers
Analysis tools and information readily accessible by all
Data management process provided little valued added to the WHO regions and countries
Cleaned, harmonized data and standardized reports are readily available after data submission
Poorly defined flow of some information
System designed to facilitate new streams of data flow
Highlighted arrows – ones where there are challenges
* Varying degrees of completeness

10. Delivering the system Key events: Defining the need
System designed to manage incoming data rather then enforcing new processes
Procuring the funds
Partner driven
Development started in late 2012
Multiple applications
Data sharing policy in 2013

11. Huge milestone achieved
Data sharing
Huge milestone achieved
Permission to securely share polio data with GPEI partners
February 2013 Polio Data Sharing Agreement
“Each Core GPEI Partner is authorized by WHO to share the AFP data and WHO geo-data for the purpose of analyses, mathematical modeling and risk assessments, with a collaborating institution which is agreed by WHO and which has agreed to be bound by the same terms and conditions as those under which the data were provided to the Core GPEI Partner “
“The primary purpose of data sharing is to advance public health by permitting analyses that allow for the fullest possible understanding of health challenges, to help develop new solutions, and to ensure that decisions are based on the best available evidence” (from: WHO’s 2017 policy on use and sharing of data)
Consultation with DG and 194 member states to share their country’s data.

12. Challenges
Two of the more challenging issues which complicated the deliver of the previously stated objectives are:
Defining processes for some information work flows
Autonomous nature of regional offices
Different needs across countries
Multiple concurrent data / information projects
Rapidly evolving program
Establishing a global reference data (focus on geography)
Most data are reported by geo-place name
~ 40,000 geo-places need to be managed in POLIS
Geo-places can have multiple spellings
“Geography” (names and boundaries) is not static
Putting a global system together is not necessarily challenging from a technical standpoint, but is extremely hard from a process.
Rapidly evolving – program continues to push countries to measure and provide new types of information
Much more important are establishing common geographic reference data

13. Challenges - geography
Geographic reference data is at the heart of POLIS
Common dimension across all datasets
POLIS is standardized at the Admin-2 (district) level
Strong geographic reference data is required in order to harmonize and consolidate the GPEI’s data
Approach
Harmonize and merge data into a global layer based on the official UN approved country borders
Unique identifiers are assigned
Geometry repair
Maintaining validity of administrative units
Annual review and defined standard operating procedures
Time aware geo-database with end-dating
Create synonyms for unmatched geo-place names

14. Outcome (1)
Data
Multiple data sets including: disease surveillance, laboratory, vaccination campaigns, campaign performance, environmental surveillance, routine immunization..
All datasets are harmonized and consolidated at the admin-2 level
Raw or summarized data can be queried, visualized, or downloaded (export or API)
POLIS facts and figures as of 16 April 2018
Cumulative over all data in POLIS – not neccessarily on the same time frame
Jan 2010 for AFP, earlier for confirmed cases.
SIAs to 2000

15. Information Outcome (2)
Dashboard allows an easy visual to get up-to-date on situational awareness

16. Dashboard pages: Outcome (3) Country page Case page
Both pages demonstrate the value of having harmonized and consolidate data in one location as the following datasets are combined for one consolidate view: surveillance, laboratory, vaccination campaigns, campaign quality, routine immunization, geographic and population reference data.

17. Dashboard pages: Outcome (4)
Vaccination activity page Environmental site page
Both pages demonstrate the value of having harmonized and consolidate data in one location

18. Interactive pages: Outcome (5)
Search page (example campaigns in the last 6 months)
Search Results can be shared by:
Hyperlink
Data export
Table view (default – shown above)
Calendar view
Map view

19. Programmatic Implications
Prior to POLIS the partnership had little to
no access to program data
Prior to POLIS, WHO set the narrative for how well the program was doing

20. Programmatic Implications
POLIS facilitates information sharing
WHO’s weekly automated epidemiologic analysis
WHO’s weekly global update
Morbidity and Mortality Weekly Reports (MMWR) publications
Weekly Epidemiologic Record (WER) publications
Weekly Sabin2 monitoring
Countless risk assessments
Countless in-depth surveillance reviews
Estimated 30+ peer review journal articles
See next page

21. Example: Ad-hoc risk assessment
WPV/cVDPV cases WPV cVDPV2
Notification last week of an isolate of cVDPV2 in sewage in Nairobi, genetically related to recent isolates in Somalia
SoPs call for <24hrs for preliminary risk assessment and immunization response planning
An immediate need to contextualize isolate with historical epidemiology in the region
Requires coordination of data across countries, regions, and agencies
© Bill & Melinda Gates Foundation

22. Example: Surveillance performance

23. Example: Evaluation of vaccination campaign effects
Matching timing of virus isolates in sewage with vaccination campaigns allows evaluation of effectiveness of campaigns
© Bill & Melinda Gates Foundation

24. Example: surveillance data quality
Linking surveillance data and vaccination program data can give insight into data quality and data collection

25. Programmatic Implications
POLIS facilitates knowledge generation (subset)
Informing policy decisions
Assessing role of vaccinating older age children
Modelling strategies to increase population immunity
Assessing choice of vaccine on viral transmission
Including the costs and benefits
Modeling poliovirus transmission to inform vaccination strategies in under vaccinated subpopulations
Estimating serotype specific population immunity to inform outbreak response strategies following the detection of cVDPV2
Modelling the chances of undetected viral circulation
Spatial model for risk prediction and sub-national prioritization to aid poliovirus eradication
The risk of type 2 oral polio vaccine use in post-cessation outbreak response

26. Conclusion
The quantity of data that are collected by the Global Polio Eradication Initiative is unlikely to be matched by any other public health program
POLIS facilitates the sharing of data, information, and knowledge that is driving the GPEI toward a polio free world

27. Thank you very much
Paul Chenoweth