Mobile data tools for improving information flow in WASH

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  • Why should you be interested in cell phone based reporting in the context of water management? I think there are at least two compelling reasons for exploring ICT tools in this sector– There are real data gaps in the water sector which electronic data transmission can help address given advantages over paper based reporting. Go into more detail what kind of data is collected and how it can be used to ensure water safety. Many researchers have identified ‘institutional support’ as critical for the sustainability of rural water supplies. This can include technical, managerial and financial assistance. Challenging to provide this kind of support when gov agencies and local have limited resources. Tools for increasing information flow between dispersed supply managers and support staff is a concrete means of promoting institutional linkages and support. Photo: District technician in Laos who monitors rural water supplies and the national ministry office in Vientiane that theoretically should be looking at national trends and providing support and guidance to their field staff, but in reality quite disconected.
  • Provincial water suppier for Hue Province – they serve the city of hue and surrounding towns. with 17 satellite treatment plants serving small towns in the province – GO TO MAP Operators of satellite treatment plants conduct on-site water quality testing for a number of physical and chemical parameters. Operators are supported by Area managers and by the head water quality manager at the central laboratory. Currently they log test results in paper log books and they call in to the central laboratory once a week to report a summary of test results for the week. The operators use the WQR to submit a form with dat afrom 8 water quality tests Application translated into VietnameseImages – you two operators doing their testing at the treatment plant. And the on the right is noting results in a log book and then submitted them with WQR on the phone.
  • NGO supporting small scale water treatment and sales in rural areas – hybrid entrepreneurial model, where the NGO provides a lot of upfront support but eventually each operator/each site becomes self sustaining and pays for ongoing technical support from the NGO. Support the development of new sites and training operatorsUnder the Teuk Saat model, the operators carry out a simple presence/absence test for bacterial contamiation, once a week. They report this test result, along with sales data and operations and maintence logs to Teuk Saat. Currently, facilitators from Teuk Saat travel to the operator’s sites and collect paper forms. Data from WQ testing on site by operators submited via WQR to NGO support center wq managerLooking into options for new forms on billing, operations and maintenance etc.
  • Notice a big increase which I’ll come back to. Go back to other data slide. 6 months. After a period of technical troubleshooting and changes to the form type – consistent data submission over the past 2 ½ months. 17 water treatment plants, submitting data for multiple water types. - The 6 sites that consistently report and then the remainder varies. Take home message is that a lot of data is coming in, but due to both technical issues and motivational issues not all sites report each week.
  • Cambodia and Vietnam data was being collected and aggregated: Time savings and increased accuracyLeap frogging effect, bypass Formal data collection/management - Real time identification of risks – only able to look at this in Cambodia. Leakhena call operators right away (instead of once a month) and remind them to clean system etc. Value will depend on role of managers vs operators in water quality management decisions. Still paralell to previous methods in EA pilots. Vietnam and Cambodia the managers already consistently receive the data – but in Mozambique – even though we haven’t gotten to see this really play out yet, in our initial scoping we found that very little data comes from the districts ot the provinces
  • Mobile data tools for improving information flow in WASH

    1. 1. Mobile Data Tools for Improving Information Flow in WASH Lessons from Three Field PilotsMatt Ball1, Zarah Rahman1, Michael Champanis2, Ulrike Rivett2 & Ranjiv Khush1 1The Aquaya Institute, San Francisco, USA2iCOMMS, Department of Civil Engineering, University of Cape Town, South Africa
    2. 2. Aquaya How can local governments and water suppliers improve water quality testing in poor and remote areas? How can they best use water quality data to guide management policies and practices?
    3. 3. Aquatest Monitoring for Safe WaterE. Coli Test & Evaluating constraintsPortable Incubator to microbial testing
    4. 4. Mobile Data Solutions
    5. 5. Mobile data in professional settings Reduce gaps in data transmission? • Better response times • Greater accountability Strengthen institutional links by improving information flow? • Financial and technical support
    6. 6. Hue Water Company, Vietnam
    7. 7. Teuk Saat 1001, Cambodia
    8. 8. District Health Offices, Mozambique
    9. 9. Reporting Formats WaterDate Area Site name Operator Comments Turbidity pH Chlorine Iron pressure 14-Mar-11 Huong Thuy Loc Bon nguyen huu chuong Source: Reservoir 0.2 2 7 0.5 0.005 14-Mar-11 Huong Thuy Loc Bon nguyen huu chuong Source: Distribution 0.25 1.3 7.1 0.4 0.005 14-Mar-11 Huong Tra Binh Thanh Cao Trong Thang No equipment for Mn, Fe, TDS 0.11 1.5 7.14 0.4 0 14-Mar-11 Phong Dien O Lau River nguyen van tin Source: Reservoir 0.12 3.5 7.1 0.65 0 14-Mar-11 Huong Tra Thuan Hoa B ho anh tuan 0.184 3.5 7.13 0.4 0.03 14-Mar-11 Phong Dien O Lau River nguyen van tin Source: Distribution 0.17 2.8 7.35 0.35 0 14-Mar-11 Phu Loc Cu Du Tran Binh Phuong Source: Distribution 0.35 1 6.87 0.35 14-Mar-11 Phu Loc Cu Du Tran Binh Phuong Source: Reservoir 0.32 0.6 6.88 0.45 14-Mar-11 Phu Loc Cu Du Tran Binh Phuong Source: Raw Water 1.25 1.2 6.67 0 14-Mar-11 Nam Dong Nam Dong nguyen huu son Source: Reservoir 0.2 2 7.1 0.6 0 14-Mar-11 Nam Dong Nam Dong nguyen huu son Source: Distribution 0.25 2.3 7 0.4 0 14-Mar-11 Tu Ha Town Tu Ha le hiep 0.1 4.4 7.26 0.4 0.02 15-Mar-11 Phu Loc Song Nong ton thai ha March 8th to 14th 0.2 2 7.15 0.55 0.02 15-Mar-11 Quang Dien Quang Ngan hoang ngoc ha 0.22 0 7.18 0.4 0.05 16-Mar-11 Phu Loc Chan May pham hong khanh Source: Reservoir 0.17 2.25 6.705 0.5 0.045 19-Mar-11 Huong Tra Thuan Hoa B ho anh tuan 0.18 3.6 7.2 0.46 0.03 19-Mar-11 Huong Thuy Loc Bon nguyen huu chuong Source: Reservoir 0.25 2 7.2 0.5 0 19-Mar-11 Huong Thuy Loc Bon nguyen huu chuong Source: Distribution 0.32 1.8 7.23 0.4 0 20-Mar-11 Nam Dong Nam Dong nguyen huu son Source: Reservoir 0.18 1.6 7 0.65 0.005 20-Mar-11 Nam Dong Nam Dong nguyen huu son Source: Distribution 0.016 1.9 7.1 0.4 0.005 21-Mar-11 Quang Dien Quang An nguyen van phuoc Source: Reservoir 0.1 2.5 6.7 0.6 0 21-Mar-11 Quang Dien Quang An nguyen van phuoc Source: Distribution 0.25 0.8 6.7 0.2 0 21-Mar-11 Phong Dien O Lau River nguyen van tin Source: Reservoir 0.12 3.2 7.1 0.6 0 21-Mar-11 Phong Dien O Lau River nguyen van tin Source: Distribution 0.17 3.1 7.3 0.3 0 21-Mar-11 Phu Loc Song Nong ton thai ha March 15th to 21st 0.19 2 7.1 0.55 0.025 21-Mar-11 Phu Loc Cu Du Tran Binh Phuong Source: Raw Water 2.15 1.2 6.82 0 21-Mar-11 Phu Loc Cu Du Tran Binh Phuong Source: Reservoir 0.44 0.5 6.89 0.4 22-Mar-11 Huong Tra Binh Thanh Cao Trong Thang No equipment for Mn, Fe, TDS 0.1 1.3 7 0.4 0 22-Mar-11 Phu Loc Chan May pham hong khanh Source: Reservoir 0.155 2.9 6.94 0.5 0.03 26-Mar-11 Huong Tra Thuan Hoa B ho anh tuan 0.18 2.4 7.2 0.45 0.03 26-Mar-11 Nam Dong Nam Dong nguyen huu son Source: Reservoir 0.2 1.6 7 0.55 1.5 26-Mar-11 Nam Dong Nam Dong nguyen huu son 0.18 1.6 7.1 4 0.01 26-Mar-11 Huong Thuy Loc Bon nguyen huu chuong Source: Reservoir 0.22 2 7.2 0.5 0.015 27-Mar-11 Huong Thuy Loc Bon nguyen huu chuong Source: Distribution 0.27 1.5 7.2 0.4 0.005
    10. 10. Data submission: Vietnam 14 12 10 Sites Reporting 8 6 4 2 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 Week • 8 months - 15 WTPs, 3 Rivers - 608 Forms Total • Average 9 out of 17 sites reporting
    11. 11. Data submission: Mozambique Submissions by District, Mozambique
    12. 12. Challenges Technical • Unreliable cellular network • Unstable phone settings Managerial • Phone credit • Personal use
    13. 13. Benefits Data gaps? • Only in where reporting was minimal, (Mozambique) Information flows/institutional support? • Rapid identification of risks • Awareness at higher administrative levels • More discussion of responsibilities and use of data
    14. 14. Long-term use Dedicated service providers vs local hosting Integration with full range of user activities Integration with existing data systems
    15. 15. Thank you iComms group, University of Cape Town: Ulrike Rivett & Michael Champanis Teuk Saat 1001: Chay Lo, Leakhana Phuong and Marie Yen UNICEF Mozambique: Sam Godfrey & Matteus Van der Velden, UNICEF Mozambique HueWaco: Tran Thi Minh Tam Aquaya: Matt Ball & Zarah Rahman

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