The dirty business of :

Lessons from scaling-up TSSM in

Lisa Cameron, Paul Gertler and Manisha Shah August, 2012

1 Part of WSP Learning Agenda

• Evaluation of interventions in 7 countries – 4 TSSM & 3 Hand Washing – At scale

• Coordinated – Same outcomes – Rigorous causal methods

• Organization – Large team of IE experts & operational staff – BMGF funding

Total Sanitation and Sanitation Marketing in Indonesia (SToPs)

Demand side Supply side Demand side 1 Community-led 3 Social Marketing of Total Sanitation: Sanitation:  Stop OD by raising  Popularize improved awareness sanitation  “map” the village  Sanitation choice catalogue  “walk of shame”  Training masons  Triggers community action  Action plan & monitoring Behavior Change 2 Communications :  Social Marketing Events +  Communication Campaign

Basic IE Questions 1. What is the overall Impact of TSSM on: • Sanitation improvement and construction • Open Defecation • Health – Diarrhea – Parasites – Anemia – Height and weight Advanced IE Questions 2. Decomposition of overall OD effect into – Sanitation construction – Increased use of sanitation (behavioral)

3. Liquidity constraints

4. Effects of stronger implementation Today…. I. Theory of Change II. IE Design III. Triggering take-up IV. Results I. Sanitation II. Open Defecation III. Health Outcomes V. Policy Messages

Conceptual Framework

Decompose Open Defecation Rate into:

D = DTT + DNT (1-T)

D = Open Defecation Rate

T = Share of households that have sanitation

DT = Open Defecation Rate of HHs with Sanitation

DNT = Open Defecation Rate of HHs without Sanitation

TSSM Pathways To Reduce OD

1. Sanitation construction = TDT  DNT 

2.  in use of those who have san = DTT

3.  in use of those who do not have san = DNT 1T  Indonesia and East Java

http://education.yahoo.com/reference/factbook/id/map.html Sampling & Experimental East Java: 29 districts total Design 10 districts in TSSM Phase 2 8 of 10 districts participated in study

Randomly Sampled 160 communities (‘dusun’ or hamlet) Randomly Assigned to

Treatment Control 80 dusuns 80 dusuns Random Sample Random Sample 1046 HHs 1041 HHs

Sanitation Improvement/Construction 0.2

0.18

0.16

0.14

0.12

0.1 Treatment 0.08 Control

0.06

0.04

0.02

0 All Sanitation at No Sanitation at Baseline Baseline Sanitation Construction by SES 0.16

0.14

0.12

0.1

0.08 Treatment 0.06 Control

0.04

0.02

0 No Sanitation at No BL San No BL San Poor Baseline NonPoor Open Defecation 0.9

0.8

0.7

0.6

0.5 Treatment 0.4 Control 0.3

0.2

0.1

0 All No Sanitation at Sanitation at Baseline Baseline

Open Defecation Conditional on BL & EL Sanitation 1 0.9 0.8 0.7 0.6 0.5 Treatment 0.4 Control 0.3 0.2 0.1 0 San at BL & EL No San at & San at EL No San at Bl & No San at EL Decomposition of Δ in OD

• Total estimated effect of TSSM on OD = -.07 • Components: – Δ in sanitation .038*(.24-.83) = -0.038*0.61 = -0.02 – Δ in use of those that have sanitation -0.06*0.5 = -0.03 – Δ in use of those who do not have sanitation -0.4*0.5 = -.02 • Note that they add up to -0.07

Lessons So Far….

• TSSM reduced mostly through behavioral change  Explained 70% of the reduction in OD

• Less successful through sanitation construction

• Big potential gains from construction left on table  8% reduction in OD from 10% in sanitation • 6% from sanitation construction (.24-.83) • 2% from increased use of sanitation (0.6 – 0.2)  TSSM in Indonesia only increased sanitation by 3.8%  At baseline only 50% had sanitation

Why? Obstacles to Building Sanitation High Cost Space Other No Satisfied with current No materials available Soil Conditions No one to build Water not available Too Comples Permit Issues Tenancy Issues

0 10 20 30 40 50 60 70 80

Implementation: Share Triggered

Villages (Admin)

Villages (IE)

Households (IE)

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% Control Treatment What If All Villages Were Triggered? Results Summary

• TSSM was successful at – Reducing OD – Improving health outcomes • Mostly worked through behavioral change • Less successful at sanitation construction • Big potential gains through construction left on table – Cost and liquidity constraints biggest obstacles • Implementation matters • Repeating with India & Tanzania Data now Policy Messages

• TSSM (CLTS) model – Improves health primarily thru behavioral change – Less successful through sanitation construction

• Need to lower cost of sanitation construction – Subsidized prices – Credit – Community financing

• Need to Improve implementation Acknowledgements

Water and Sanitation Program, The The Bill and Melinda Gates Foundation University of California, Berkeley . Professor Paul Gertler, PhD . Jack Colford, MD, PhD, MPH . Ben Arnold, PhD . Tricia Kariger, PhD . Lia Fernald, PhD University of Maryland . Sebastian Galiani, PhD University of Buffalo . Pavani Ram, MD, PhD