Data Collection and Analysis in WASH - webinar

deck from Aquaya's ICT webinar

Transcript

1. Data Collection and Analysis in WASH October 2, 2012 Matt Ball – matt@aquaya.org Aquaya
2. Outline • Aquaya's work • What constitutes ICT in WASH? • Examples • Aquaya's approach • Technical options and a demo of Aquaya's Pipeline • Questions (live and at the end)
3. Aquaya's work in the sector • Aquatest and the Water Quality Reporter o feature phone application with a supporting website • Consulting and research o working with NGOs, suppliers and surveillance programs • Monitoring for Safe Water o improving the data management capabilities of African water suppliers and surveillance agencies
4. Components of ICT in WASH • Data collection o operational o surveillance o sales o crowdsourcing
5. Components of ICT in WASH (cont.) • Data analysis o periodic reporting and sharing of analyses o aggregation o live analysis o integration with other systems and data sources o staff management
6. Expected benefits • better coverage and increased sustainability • real-time data o no longer physically transporting information • operational awareness o physical and temporal coverage of data • digitization and compilation o error-reduction o data “liquidity”
7. Example use-cases: Teuk Saat • NGO in Battambang, Cambodia o operating ~50 small-scale treatment sites o operators have many duties
8. Example use-cases: Teuk Saat • Water Quality Reporter app o microbiological data o aggregated by central managers o not available in Khmer • organization saw a shift in its need for real-time data
9. Example use-cases: HueWACO • Mid-sized utility in Hue, Vietnam o operates ~10 rural treatment plants
10. Example use-cases: HueWACO • WQR used for physiochemical data o transitioned to CommCare o added chemical inventory data o aggregated by central managers • organization needed an expandable system and backup methods
11. Example use-cases: MISAU-DNA • traveling surveillance personnel o operating in 3 Mozambican provinces o coordinated with UNICEF • WQR used for physiochemical, inspection and follow-up data o weekly and monthly analysis sent to Mozambican officials • organization needed backup methods and managerial guidelines • needed improved institutional buy-in at certain levels
12. Overall lessons learned • consider backups for storage and transmission • find systems that can evolve as user needs evolve • delineate management plans
13. Aquaya's approach • separate collection and analysis • aggressively leverage Open Source • need-finding • development of management and training procedures • pilot deployments • scale-up and handover
14. Technical options for data collection • IVRHub (Aquaya) o Voice-based; OSS and SAAS • CommCare (Dimagi) o Android and feature phones; OSS and SAAS • FormHub (Columbia Univ.) o Android; OSS and SAAS • EpiSurveyor (Datadyne) o all platforms; SAAS • FrontlineForms (Kiwanja) o SMS-based; OSS OSS: Open source software SAAS: software as a service
15. Technical options for data analysis • Pipeline (Aquaya) o general analysis and reporting • CommCare o enumerator efficiency and reporting • FormHub o mapping • EpiSurveyor o response graphing • Excel/SPSS o general analysis and reporting
17. Demo of Aquaya's Pipeline
18. Thanks! • Questions? ▫ Matt Ball – matt@aquaya.org • UNC’s Water and Health Conference, Nov 2 • ICT in WASH paper soon