3.Panel6 Estro Dariatno The Analysis of Funds Efficiency on Tuberculosis High Burden Countries

THE ANALYSIS OF FUNDS
EFFICIENCY
ON TUBERCULOSIS HIGH
BURDEN COUNTRIES
ESTRO DARIATNO SIHALOHO
ADIATMA YM SIREGAR

TB BURDEN COUNTRIES

INTRODUCTION

From 19 TB
Burden Countries
Total Asia :
11 Countries

DATA AND METHODS
RESULT

Total Africa :
7 Countries

Total America :
1 Countries

CONCLUSION

Source : Global
TB Report 2014

WHO in TB Global Report show that there are 22 countries become
TB Burden Countries. But this paper just review 19 countries . There
are
:
Afganista
Cambodi
Ethiopia
Kenya
Nigeria
Thailan
Zimbab
n


a

d

Banglades
h

China

India

Mozambiqu
e

Pakistan

Tanzania

Brazil


Congo

Indonesia

Myanmar

Philippin
es

Viet Nam

1

we

TB BURDEN COUNTRIES
Rank

INTRODUCTION

DATA AND METHODS
RESULT
CONCLUSION

Number
Rank Country
of
Prevalent
1
India
2500000
2
Indonesia 1600000
3
China
1200000
4 Bangladesh 640000
5
Pakistan 630000
6

Nigeria
590000
7 Philippines 410000
8
Tanzania 270000
9
Myanmar 240000
10
Ethiopia
190000
11 Viet Nam 180000
12
Thailand 160000
Mozambiqu
13
e
150000
14
Kenya
120000

Afghanista
15
n
110000
16
Brazil
110000
17 Cambodia 100000
18 Zimbabwe 44000
19
Congo
21000

1
2
3
4
5
6
7

8
9
10
11
12
13
14
15
16
17
18
19

Number
of death
India
220000
Nigeria
170000
Indonesia 100000

Bangladesh 81000
Pakistan
48000
China
38000
Ethiopia
32000
Tanzania
30000
Myanmar 28000
Mozambiqu
e
18000
Viet Nam 17000
Afghanista
n
14000
Philippines 10000
Kenya
9400

Cambodia
8900
Thailand
7400
Brazil
5300
Zimbabwe 2300
Congo
2100
Country

Source : Global
TB Report 2014

Rank

Country

1
2

3
4
5
6
7
8
9
10
11
12
13
14
15
16
17

China
India
Brazil
Nigeria

Philippines
Indonesia
Ethiopia
Pakistan
Myanmar
Kenya
Bangladesh
Viet Nam
Tanzania
Congo
Thailand
Zimbabwe
Cambodia
Afghanista
n
Mozambiqu
e

18
19

1

2

Total
Fundin
g
282
251
69.2
65
61
55
34.5
34
23.5
22.6
21.9
19.6
19.1
16.1
13.8
13.7
11
6.2
4.3

TB BURDEN COUNTRIES

INTRODUCTION
DATA AND METHODS
RESULT
CONCLUSION

No

Country

1
India
2
Indonesia
3
Brazil
4
Ethiopia
5
China
6
Philippines
7
Kenya
8
Nigeria
9
Congo
10
Pakistan
11 Bangladesh
12 Zimbabwe
13
Tanzania
14
Thailand
15 Afghanistan
16
Myanmar
17 Mozambique
18
Viet Nam
19 Cambodia

Number of
Smear Lab
13583
5689
3382
2972
2952
2561
1920
1765
1604
1483
1104
989
945
908
720
492
336
325
215

No

Country

1
2
3

Kenya
Ethiopia
Philippines
Afghanista
n
Indonesia
Tanzania
Brazil
Cambodia
Zimbabwe
Thailand
Mozambiqu
e
Viet Nam
India
Nigeria
Myanmar
Pakistan
Bangladesh
Congo
China

4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19

1

Number Smear
Lab/100.000
Population
4.3
3.1
2.6
2.3
2.2
1.8
1.6
1.4
1.4
1.3
1.2
1.1
1
1
0.9
0.8
0.7
0.7
0.2

Source : Global TB Report
2014

2

3

TB BURDEN COUNTRIES

INTRODUCTION
DATA AND METHODS
RESULT
CONCLUSION

Source
of
Fundin
g

Country

Local Funding
(US$ Million)

Afghanistan
Bangladesh
Brazil
Cambodia
China
Congo
Ethiopia
India
Indonesia
Kenya
Mozambique
Myanmar
Nigeria
Pakistan
Philippines
Thailand
Tanzania
Viet Nam
Zimbabwe

0.8
2.9
68
1.2
271
2.1
6.5
165
17
13
0
5.5
12
0
32
8.6
8.1
6.6
0.7

International
Funding (US$
Million)
5.4
19
1.2
9.8
11
14
28
86
38
9.6
4.3
18
53
34
29
5.2
11
13
13

Source : Global TB Report
2014

1

2

3

4

DATA

INTRODUCTION
DATA AND METHODS
RESULT

This research used secondary data
from Global TB Report 2010-2015.
This Research focus on measuring the
TB funds efficiency and analyze
environmental factors that can
increase technical efficiency scores in
19 TB high burden countries. This
study uses the period of 2011-2014

CONCLUSION

1

2

3

4

5

METHODS

INTRODUCTION
DATA AND METHODS
RESULT
CONCLUSION

Data Envelopment
Analysis (DEA) is one form of
measurement analysis is used to
evaluate the relative efficiency of a
set of decision making unit (DMU) in
managing resources (inputs) to be
the maximum result (output).
OUPUT
INPUT
DEA

• Number of death
decreasing of TB
• Number of
prevalent
decreasing of TB
• Number of new
SMEAR laboratory
for efficiency
measurement

• Domestic funding
• International
funding

6

METHODS
Tobit analysis
INTRODUCTION
DATA AND METHODS
RESULT
CONCLUSION

is one form of measurement analysis
is used to evaluate the importance of
environmental or non-discretionary
inputs by regressing the output
efficiency scores on a set of possible
explanatory variables
Environmental
Eff Score
Factor

• Tax of Cigarette
• Budget of Tobacco
Control

T
O
B
I
T

6

7

DEA RESULT
DMU
1
2
3
4
5
6
7
8
9
10
11
LOWEST12
13
14
15
16
17
18
19

Country
Afghanistan
Bangladesh
Brazil
Cambodia
China
Congo
Ethiopia
India
Indonesia
Kenya
Mozambique
Myanmar
Nigeria
Pakistan
Philippines
Thailand
Tanzania
Viet Nam
Zimbabwe

2011
1.000000
0.202522
0.240130
0.758476
1.000000
1.000000
0.884933
1.000000
1.000000
1.000000
0.684028
0.150414
1.000000
0.783960
1.000000
1.000000
1.000000
0.921031
1.000000

Source : STATA
11, Global TB
Report 2013 &
2014

INTRODUCTION
DATA AND METHODS
DMU
1
2
3
4
5
6
7
8
9
10
11
LOWEST
12
13
14
15
16
17
18
19

Country
Afghanistan
Bangladesh
Brazil
Cambodia
China
Congo
Ethiopia
India
Indonesia
Kenya
Mozambique
Myanmar
Nigeria
Pakistan
Philippines
Thailand
Tanzania
Viet Nam
Zimbabwe

2012
0.567222
0.777778
0.231114
0.311111
0.110517
1.000000
1.000000
1.000000
0.841246
0.821310
0.019896
0.240000
0.163226
1.000000
1.000000
0.172585
0.273156
1.000000
1.000000

RESULT

CONCLUSION

6

7

8

DEA RESULT
DMU
1
2
LOWEST3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19

Country
Afghanistan
Bangladesh
Brazil
Cambodia
China
Congo
Ethiopia
India
Indonesia
Kenya
Mozambique
Myanmar
Nigeria
Pakistan
Philippines
Thailand
Tanzania
Viet Nam
Zimbabwe

2013
1.000000
1.000000
0.395277
1.000000
1.000000
DMU
1.000000
1
1.000000
2
1.000000
3
1.000000
4
0.411875
5
0.520886
6
0.797536
7
1.000000
8
1.000000
9
1.000000
10
1.000000
11
1.000000
12
1.000000
13
LOWEST
0.718432
14
15
Source : STATA
16
11, Global TB
17
Report 2011 &
18
2012
19

INTRODUCTION
DATA AND METHODS
Country
Afghanistan
Bangladesh
Brazil
Cambodia
China
Congo
Ethiopia
India
Indonesia
Kenya
Mozambique
Myanmar
Nigeria
Pakistan
Philippines
Thailand
Tanzania
Viet Nam
Zimbabwe

2014
0.871871
0.227533
1.000000
0.436340
1.000000
0.359559
1.000000
1.000000
0.140362
1.000000
1.000000
0.235607
0.129667
1.000000
1.000000
0.768948
0.378213
0.323287
1.000000

RESULT

CONCLUSION

6

7

8

9

Eff Score 20112014
INTRODUCTION
DATA AND METHODS
RESULT

CONCLUSION

Source : STATA 11, Global TB Report 2011-2014

6

7

8

9

10

DEA RESULT
DMU
1
2
3
4
5
6
7
HIGHEST
8
9
10
11
LOWEST

12
13
14
HIGHEST
15
16
17
18
19

Country
Afghanistan
Bangladesh
Brazil
Cambodia
China
Congo
Ethiopia
India
Indonesia
Kenya
Mozambiqu
e
Myanmar
Nigeria
Pakistan
Philippines
Thailand
Tanzania
Viet Nam
Zimbabwe

Average Eff 20112014
0.859773
0.551958
0.466630
0.626482
0.777629
0.839890
0.971233
1.000000
0.745402
0.808296

INTRODUCTION
DATA AND METHODS
RESULT

CONCLUSION

0.556203
0.355889
0.573223
0.945990
1.000000
0.735383
0.662842
0.811080
0.929608

The efficiency score of India and
Philippines show that the two countries
was more efficient and more optimum
than other burden countries to manage all
the TB funding in every year

11

TOBIT RESULT
 

dy/dx

Std. Err.

z

P>|z|

Tax_Cig

0.0032515

0.0085583

0.38

0.708

Tob_Con_B
ud

0.00000001
87

0.0000000
51

0.37

0.718

INTRODUCTION
DATA AND METHODS
RESULT

The cigarettes
tax has a
positive
marginal effect
about
0,0032515 but
not significant
The budget on
tobacco control
has positive
marginal effect
about
0,0000000187
but also not
significant

CONCLUSION

Source : STATA
11, Global TB
Report 2011 2014

11

12

CONCLUSION

INTRODUCTION
DATA AND METHODS
RESULT
CONCLUSION

1. DEA process shows that there were
countries not optimal to used the
existing budget to reduce the level of TB
prevalent and TB death rate.
2. This can influenced by very small
allocation from the government
budget. So the burden countries
become
very
dependent
on
International
funding
for
prevention
program,
diagnosis
3. Tobit programs,
process shows and
that the
treatment
marginal
effects
of
taxes
on
programs.
cigarettes and budget of tobacco
control is still not significant.
These results indicate that the
government in TB high-burden
countries
have
to
increase
cigarette taxes by a very high
level. This would make the price
of cigarettes would 11
be 12
very
13
expensive and would affect the