Transcript Comparing national and international monitoring WHO/UNICEF Joint Monitoring Programme

WHO/UNICEF
Joint Monitoring Programme
for Water Supply and Sanitation (JMP)
Comparing national and international monitoring
of the MDG drinking water and sanitation target
Rolf Luyendijk,UNICEF
UNSD/UN-ESCAP Workshop
Bangkok, Thailand, 14-16 January, 2009
This presentation
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5.
Introduction
Data sources
JMP Methodology
Definitions
Comparing national and
international monitoring
WHO/UNICEF Joint Monitoring Program
(JMP)
 Established
in 1990
 Secretariat:

World Health Organization & UNICEF
WHO-UNICEF
Joint Monitoring Program (JMP)
 Responsible
for monitoring
progress towards MDG 7 Target 7c

Global accountability and advocacy
 Biennial
updates of coverage
estimates

Water supply & sanitation
• urban, rural, and total
• by country, region and at global level
Sanitation in Asia: Urban and rural disparities 2006
Improved sanitation
coverage, 2006
Less than 50%
Urban
51% - 75%
76% - 90%
91% - 100%
No or insufficient data
WHO/UNICEF JMP, 2008
Rural
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2.
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5.
Introduction
Data sources
JMP Methodology
Definitions
Comparing national and
international monitoring
Data sources on access to
drinking water and sanitation

1980 – 1997 Reported data from Governments
1997 – data from household surveys and censuses

JMP data sources are primary sources:



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National household sample surveys (DHS, MICS, LSMS,
CWIQ, WHS, HBS, H&N, RHS, PAPFAM etc)
National censuses
Note: JMP is not involved in primary data
collection
How does the JMP obtain national
census and household survey data?



DHS surveys - directly from MACRO-International
MICS surveys from UNICEF
WHS surveys from WHO
Other surveys and census data:
 UNICEF country offices - annual data compilation
 International Household Survey Network
 Internet searches of NSO websites
Question:
What would be an appropriate mechanism for NSOs to
submit new survey and census data on water and
sanitation to the WHO/UNICEF JMP?
Use of “user-based” data vs.
“provider-based” data

Standardized definitions among surveys

Objective “snapshot” of the situation


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Nett picture of new facilities constructed and those
fallen in disrepair
Avoid double counting of upgraded improved facilities
(e.g. hand pump to piped house connection)
Allows for analyses

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Disaggregated into wealth quintiles
Comparable across countries
Monitor trends over time
100
WHO90
Coverage
90
distribution
80
% Coverage
70
JMP93
60
JMP96
50
JMP99
40
Reported data
30
Survey data
20
DHS99
DHS94
WHO88
EMP85
EMP86
10
0
1980
MICS00
1982
1984
1986
1988
1990
1992
1994
Year
1996
1998
2000
2002
2004
2006
JMP – data base (2008)
 Data
for +/- 170 countries
 600+ results of HH surveys + Censuses
from 1985 – 2006
 Bulk of surveys for LDCs, SSA, larger
developing countries
 30 - 35 new survey results per year
 Frequency for most developing countries
one survey every three years
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3.
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Introduction
Data sources
JMP Methodology
Definitions
Comparing national and
international monitoring
Monitoring MDG drinking water and
sanitation targets
A country’s responsibility
 At global level: JMP

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Challenges:

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Track progress over time
Ensure comparability over time
Track progress towards the MDG target vs.
baseline year 1990
Ensure comparability of data among
countries (JMP specific challenge)
Viet Nam - rural Proportion using an improved sanitation facility
100
Latest data point DHS 2002 :51%
90
80
70
60
DHS02
50
DHS97
40
M ICS00
LSS93
CEN98
M ICS96
30
% Coverage
20
10
0
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
Year
Hallo
Total improved access
Sew erage connections (SC)
2010
Viet Nam - rural Proportion using an improved sanitation facility
100
Estimates Coverage
90
Latest data point DHS 2002 :51%
2004 = 50%
80
70
60
DHS02
50
DHS97
40
M ICS00
LSS93
CEN98
M ICS96
30
% Coverage
20
10
0
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
Year
Hallo
Total improved access
Sew erage connections (SC)
2010
Viet Nam - rural Proportion using an improved sanitation facility
100
Estimates Coverage
90
80
Added Fictive data point 2005 :58%
2004 = 50% = 54%
2006 = 57%
70
60
FIctive 05
DHS02
50
DHS97
40
M ICS00
LSS93
CEN98
M ICS96
30
% Coverage
20
10
0
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
Year
Hallo
Total improved access
Sew erage connections (SC)
2010
Viet Nam - rural Proportion using an improved sanitation facility
100
Estimated Coverage
90
80
Added Fictive data point 2008 :65%
2004 = 50% = 54%= 54%
2006 = 57% = 59%
2008 = 63%
70
Fictive 08
60
FIctive 05
DHS02
50
DHS97
40
M ICS00
LSS93
CEN98
M ICS96
30
% Coverage
20
10
0
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
Year
Hallo
Total improved access
Sew erage connections (SC)
2010
Viet Nam - rural Access to improved sanitation coverage
100
Estimated Coverage
90
Latest data point DHS 2002 :51%
2004 estimate = 50%
80
70
60
DHS02
50
DHS97
40
M ICS00
LSS93
CEN98
M ICS96
30
% Coverage
20
10
0
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
Year
Total improved access
Sew erage connections (SC)
2010
Viet Nam - rural 100
90
80
Proportion using an improved sanitation facility
Proportion using an improved sanitation facility
2004 = 50%Coverage
Estimated
= 54%
Added Fictive data point 2005 :49%
:58%
2006 = 57%
2004
50% = 49%
2006 = 52%
70
60
DHS02
50
DHS97
FIctive 05
40
M ICS00
LSS93
CEN98
M ICS96
30
% Coverage
20
10
0
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
Year
Hallo
Total improved access
Sew erage connections (SC)
2010
JMP Methodology - Summary

Primarily based on user data derived from
household surveys and censuses rather than
data reported by governments
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Adjustments made to full historical series to
ensure comparability over time and between
countries
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Use linear regression to extrapolate and
interpolate reference years instead of using the
latest household survey data
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Introduction
Data sources
JMP Methodology
Definitions
Comparing national and
international monitoring
Core question on water and sanitation for
household surveys - What is measured?
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What is the main source of drinking water for
members of your household?
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What kind of toilet facility do members of your
household usually use?
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http://www.wssinfo.org/pdf/WHO_2008_Core_Q
uestions.pdf


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Standard set of only eight questions used by DHS
and MICS
Detailed descriptions and definitions of technologies
Indicator tabulation plans
MDG target + Indicators
MDG 7 Target 10:
 Halve, by 2015, the proportion of people
without sustainable access to safe drinking
water and basic sanitation
Indicators (based on information collected):
 Proportion of population that uses an improved
drinking water source, urban and rural
 Proportion of population that uses an improved
sanitation facility, urban and rural
“Improved” means….
An improved drinking water source is:
“a source that by nature of its construction is
adequately protected from outside
contamination in particular with fecal matter”
An improved sanitation facility:
“ a facility that hygienically separates human
waste from human contact”
JMP definitions of improved/unimproved
Drinking Water
Sanitation
Piped into dwelling, plot or yard
Tube well/borehole
Protected dug well
Protected spring
Rainwater collection
 piped sewer system
IMPROVED
Public tap/standpipe
Flush/pour flush to:
Tanker truck
 Surface water (river, dam, lake, pond,
stream, canal, irrigation canal)
 Bottled water
Ventilated improved pit (VIP) latrine
 Pit latrine with slab
 Flush/Pour flush to elsewhere
UN-IMPROVED
Cart with small tank/drum
 pit latrine
 Composting toilet
Unprotected dug well
Unprotected spring
septic tank
 Pit latrine without slab/open pit
 Bucket
 Hanging toilet/hanging latrine
Shared sanitation of any type
 No facilities, bush or field
What HH Surveys tell us:

-
-
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Disaggregation by:
Facility types / access levels (e.g. piped connections
into dwelling, borehole with hand pump, open
defecation, pour flush latrines, etc)
Urban and Rural areas
Time to source (go to, get water and come back)
Wealth quintiles (access of the 20% poorest and 20% richest)
Sometimes disaggregation possible by region or
province
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4.
5.
Introduction
Data sources
JMP Methodology
Definitions
Comparing national and
international monitoring
Most common discrepancies between national
and international coverage estimates
(in order of most frequent occurrence)
1.Use of different definitions of access or poorly defined
categories


Indonesia: ‘Pit’ or ‘Hole’ is acceptable (?)
MDG definition: shared sanitation facilities are ‘unimproved’
2.Use of latest survey or census data instead of a
computed estimate
3.Use of different population estimates
4.Use of old estimates, instead of latest available data
5.Use of reported (provider-based) data rather than
household survey or census data
Often there are discrepancies within a country or
between surveys about what constitutes coverage….
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Use of different definitions by different national authorities
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Use of different response categories among different surveys
describing the same facility
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Tanzania, Kazakhstan, etc. traditional pit latrine, latrine, pit latrine, pit,
pit latrine with slab
Poor or incomplete disaggregation of response categories
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China National Health Systems Survey : ‘Harmless sanitary latrines’
China Ministry of Health: ‘Sanitary latrines’
Drinking water category: Indonesia: ‘Piped’
No listing of unimproved categories e.g. open defecation
Substitute of responses
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Thailand, Indonesia, Philippines: ‘bottled water’ for piped water
supply into dwelling
Adjustments made to survey or
census data set (1)
Example:
 HBS ‘86: Latrine: 58%
 DHS ‘89: Pit: 62%
 Census ‘92: Open pit: 59%
 MICS ‘95: Traditional latrine: 60%
Improved
Improved ?
Not improved
Improved?
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How to interpret these categories?
Adjustment: half of the facilities are considered improved
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Suggested re-classification:
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Pit latrine with a slab
Pit latrine without a slab/open pit
Adjustments made to survey or
census data set (2)
Example:
 DHS ‘98: Well: 22%
 Census ‘00: Protected dug well: 14%
 Census ’00: Unprotected dug well: 6%
Improved?
Improved
Not Improved
Did coverage drop by 22 -14 = 8% over the period 19902000?

Adjustment:
Improved dug well DHS ’98: 14/(14+6) x 22% = 15.4%
Why is a good disaggregation of
response categories so important?
South Asia
Sanitation
Eastern Asia &
Pacific
11
7
Tracking of progress
20
Advocacy
7
Accountability
49
35
Open defecation
8
Coverage (%)
Coverage (%)
66
Programming
5
Learning
10
66
Not improved
10
49
Shared
6
33
Improved
18
1990
2006 1990
2006
Example Uganda: Monitoring for Learning
Urban and rural disparities
Use of an unimproved drinking water source
The majority of the population without access
to safe drinking water lives in rural areas
1990: 61% = 9.7 million people
2006: 40% = 10.3 million people
30
30
25
25
People (millions)
People (millions)
Trend of population with and without access to an
improved drinking water source 1990 - 2006
20
15
10
5
20
15
10
5
0
1990
Piped on premises
Urban
Other improved
Source: Special tabulation, 2007
2006
Unimproved
0
1990
Piped on premises
Rural
Other improved
2006
Unimproved
Example Philippines: Monitoring for Programming
60
The urban population w ith access to basic
sanitation in the Philippines m ore than
doubled over the period 1990 - 2006
Population (millions)
Population (millions)
Trend of population with and without access to sanitation
1990 - 2006
50
40
30
20
10
0
1990
2006
Urban population w ithout access to sanitation
Urban population w ith access to sanitation
Source: Special tabulation, 2007
60
Rural sanitation coverage in the
Philippines, slow ly catches up; 3.6 m illion
rural people gained access since 1990
50
40
30
20
10
0
1990
2006
Rural population w ithout access to sanitation
Rural population w ith access to sanitation
Example: Monitoring for Advocacy
Wealth quintile analysis: The richest 20% are more than
five times as likely to use an improved sanitation
facility as the poorest 20%
100
Improved drinking water coverage by
wealth quintiles; Indonesia 2003
100
3
13
80
41
89
percentage (%)
60
74
55
50
55
Coverage (%)
81
80
66
19
40
34
52
60
35
15
12
40
14
47
20
20
15
30
34
21
9
2 nd
Ho useho ld co nnectio n
3 rd
B o ttled water
4th
R ic he s t
Other impro ved
Source: Indonesia DHS 2003 special tabulation
Improved
Shared
4th
3rd
Unimproved
Open defecation
Uganda DHS 2005 special tabulation
Richest
P o o re s t
Poorest
0
2nd
0
Example Viet Nam: Monitoring for Accountability
Progress towards the MDG drinking water and
sanitation target
Viet Nam has met its MDG drinking
water target and will meet its
sanitation target ahead of time
100
94
84
84
82
65
68
80
Coverage (%)
67
60
40
35
20
0
1990
Water
Sanitatio n
Source: Special tabulation, 2007
2006
2015
JMP Website: www.wssinfo.org
 JMP


country files
Four graphs with regressions line
All HHS + census data per country
 Regional
and global coverage estimates
 Core questions on WSS for household
surveys incl:

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Standard indicators
Definitions of service categories
Thank You!
JMP Challenges ahead (1)
Global and National
 2007 – 2010: regional and country
workshops, comparing UN - with national
coverage estimates and MDG monitoring
to exchange experiences for mutual
learning and understanding
 Facilitate
the development and roll-out of
standard protocols for water quality
monitoring
Challenges ahead (2)
Methodological Challenges
 Continue to develop and validate tools and instruments
to measure:
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Sustainable access
Safe drinking water – water quality
Access to basic sanitation
Appropriate hygiene - and hand washing behaviour
Disparities (pro-poor focus)
Access in peri-urban and urban slum areas
Disaggregate urban data between cities and small towns
Challenges for wider sector monitoring
 Strengthen sub-national monitoring
 Invest in sector monitoring of the enabling environment

E.g. policies, HR capacity, financing mechanisms and
investments, sustainable operation & maintenance,
decentralization of authority, quality management etc.
Monitoring challenges at national level

Regularly collect, use, analyze and disseminate existing
and new monitoring data and information for ACTION:
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Advocacy
Programming
Accountability
Learning
To accelerate progress towards the MDGs
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Use standard definitions of access and consistently
monitor those over time
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Set “own” MDG drinking water and sanitation target