Post on 18-Dec-2015
AHSPPR FY 2013/14 highlights
Population denominators
• NBS has not yet published official projections• However, we have Census 2012 data for:– Regions and LGAs– Specific age groups (U1, U5, WRA)
• We also have official inter-censal growth rates for all regions (Census 2012, p2)
• We therefore used these to provide “best estimate” denominators pending the publication of official projections
HEALTH STATUS INDICATORS
Indicator Baseline (2008)
Latest data (source)
Target (2015)
Life expectancy at birth (yrs) F52 M 51 F62 M60 F62 M59
Neonatal mortality rate (per 1,000 live births)
32 26 (TDHS 2010)21.4 (UN 2012)
19
Infant mortality rate (per 1,000 live births)
58 45 (Census 2012) 50
U5 mortality rate (per 1,000 live births)
94 81 (TDHS 2010)54 (UN 2012)
48
Health status indicators
5
529
578
454 432
265
0
100
200
300
400
500
600
700
TDHS 1996 TDHS 2005 TDHS 2010 Census 2012 HSSP III Target2015
The trend in the Maternal Mortality per 100,000 Live Births
Indicator Baseline (2008)
Latest data (source) Target (2015)
% U5 severely underweight 3.70% TBD 2.00%
% U5 severely stunted 38% 42% (TDHS 2010)35% (NPS 2011)
20%
Total Fertility Rate 5.7 5.2 (Census 2012) Trend
Health status indicators
HEALTH SERVICE INDICATORS
Malaria ARI Pneumonia Diarrhoeal Diseases
Urinary tract Infection
05
10152025303540
Year 2011 Year 2012 Year 2013Malaria ARI Pneumonia Diarrhoeal
Diseases Urinary tract
Infection
05
101520253035404550
Year 2011 Year 2012 Year 2013
Malaria ARI Diarrheal Diseases
Pneumonia Intestinal worms
0
5
10
15
20
25
30
35
Year 2011 Year 2012 Year 2013
. Malaria ARI Diarrheal Diseases
Pneumonia Intestinal worms
0
5
10
15
20
25
30
35
40
Year 2011 Year 2012 Year 2013
Top five outpatient (OPD) diagnoses trends 2011 to 2013 using HMIS and SPDs
<5 Years 5 and Above
Health Management Information System (HMIS)
<5 Years 5 and Above
Sentinel panel Districts (SPDs)
Malaria ARI Pneumonia Diarrheal Diseases
Anaemia0
5
10
15
20
25
30
35
40
45
Year 2011 Year 2012 Year 2013
Malaria ARI Pneumonia Diarrheal Diseases
Anaemia0
5
10
15
20
25
30
35
40
45
50
Year 2011 Year 2012 Year 2013
Top five causes of admission (IPD diagnoses); HMIS and SPDs 2011 to 2013
<5 Years 5 and Above
<5 Years 5 and Above
Health Management Information System (HMIS)
Sentinel panel Districts (SPDs)
Malaria ARI Diarrheal Diseases
Pneumonia Anaemia0
5
10
15
20
25
30
35
40
Year 2011 Year 2012 Year 2013
Malaria ARI Diarrheal Diseases
Pneumonia Anaemia0
5
10
15
20
25
30
35
40
45
Year 2011 Year 2012 Year 2013
Malaria, severe HIV-AIDS Anaemia Pneumonia TB0
5
10
15
20
25
Year 2011 Year 2012 Year 2013
Malaria, severe HIV-AIDS Anaemia Pneumonia TB0
5
10
15
20
25
30
35
40
Year 2011 Year 2012 Year 2013
Top FIVE causes of deaths for persons aged under five and 5 years and above, HMIS (and SPD)
<5 Years 5 and Above Health Management Information
System (HMIS)
Sentinel Panel Districts (SPDs)
<5 Years 5 and Above
Malaria Pneumonia Anaemia Perinatal conditions
Diarrheal Diseases
0
5
10
15
20
25
30
35
40
Year 2011 Year 2012 Year 2013
Malaria Pneumonia Anaemia Perinatal conditions
Diarrheal Diseases
0
5
10
15
20
25
30
35
40
45
Year 2011 Year 2012 Year 2013
Conclusion
• No significant change in the proportions for the top three OPD diagnosis in three consecutive years. SPD data suggest reduction in the proportion of diagnosis of malaria in both under fives and five and years and above
• Malaria was consistently the leading cause of admission over the last three years, and by a great margin. Proportion of malaria among U5 decreased in 2013 compared with 2012 and 2011 (HMIS).
• Malaria, pneumonia and anaemia accounted for two thirds of reported U5 deaths in 2013 while HIV/AIDS, Malaria and TB account for 45% of deaths among 5 years and above
Per capita OP attendances, 2011 - 13
Target = 1.0
Mwanza 0.70 Geita 3.6 Simiyu 0.29
Shinyanga 0.57
Tabora 0.45
Singida 0.76
Dodoma 0.42
Iringa 0.71 =
Morogoro 0.91
Manyara 0.27
DDSM
0.66
Pwani 0.86
Lindi 0.74
Mtwara 0.66Ruvuma 0.43
Njombe 0.66
Mbeya 0.50
Rukwa 0.62
Katavi 0.74
Kigoma 1.54
Kilimanjaro 0.70
Arusha 0.54
Mara 0.76
Kagera 0.48
Tanga 0.90
DSM 0.69
Regional Per Capita OP attendances, all ages,
2013
National Average 0.65
0 – 0.39
0.4 – 0. 59
0.6 – 0.79
0.8 – 1.0
> 1.0
Key
Year 2008 Year 2011 Year 2012 Year 2013 Target 20150
20
40
60
80
100
120
91
98 99
84 85
92
101104
92
858588
9289
85
DPT3 Measles TT2
DTP3, Measles and TT2 vaccination coverage, 2011-13
Mwanza 81% Geita 68 Simiyu 107%
Shinyanga 96%
Tabora 87%
Singida 70%
Dodoma 59%
Iringa 77% =
Morogoro 98%
Manyara 71%
DDSM
0.66
Pwani 80%
Lindi 49%
Mtwara 52%Ruvuma 86%
Njombe 166%
Mbeya 97%
Rukwa 105%
Katavi 53%
Kigoma 73%
Kilimanjaro 51%
Arusha 78%
Mara 108%
Kagera 103%
Tanga 86%
DSM 74%
Regional TT2 vaccination
coverage, 2013
National Average 89%
40 – 59%
60 – 89%
90 – 100%
> 100%
Key0 – 39%
ANC early booking, 2011-13
Baseline (2008) 2011 2012 2013 Target (2015)0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
14%
45% 42%
35%
80%
Note: 2011 < 16 weeks; 2012 and 2013 < 12 weeks
Mwanza 40% Geita 34 Simiyu 29%
Shinyanga 17%
Tabora 23%
Singida 33%
Dodoma 11%
Iringa 74% =
Morogoro 107%
Manyara 24%
DDSM
0.66
Pwani 16%
Lindi 15%
Mtwara 22%Ruvuma 56%
Njombe 38%
Mbeya 49%
Rukwa 60%
Katavi 68%
Kigoma 45%
Kilimanjaro 22%
Arusha 23%
Mara 37%
Kagera 24%
Tanga 40%
DSM 13%
Regional ANC 1st visit before 12 weeks,
2013
National Average 35%
0 – 39%
40 – 49%
50 – 78%
80 – 100%
> 100%
Key
Health facility deliveries, 2011-13
Baseline (TDHS 2004/05)
2011 2012 2013 Target (2015)0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
47%
62% 63% 61%
80%
Mwanza 75% Geita 57% Simiyu 46%
Shinyanga 66%
Tabora 71%
Singida 60%
Dodoma 59%
Iringa 74% =
Morogoro 66%
Manyara 32%
DDSM
0.66
Pwani 85%
Lindi 59%
Mtwara 48%Ruvuma 78%
Njombe 68%
Mbeya 68%
Rukwa 100%
Katavi 73%
Kigoma 57%
Kilimanjaro 55%
Arusha 57%
Mara 56%
Kagera 45%
Tanga 46%
DSM 55%
Regional facility deliveries, 2013
National Average 61%
0 – 39%
40 – 59%
60 – 79%
80 – 100%
> 100%
Key
Family planning coverage, 2011-13
Baseline (TDHS 2004/05)
2011 2012 2013 Target (2015)0%
10%
20%
30%
40%
50%
60%
70%
20%
44% 42% 43%
60%
Mwanza 31% Geita 18% Simiyu 21%
Shinyanga 32%
Tabora 21%
Singida 57%
Dodoma 82%
Iringa 44% =
Morogoro 37%
Manyara 31%
DDSM
0.66
Pwani 69%
Lindi 71%
Mtwara 69%Ruvuma 78%
Njombe 68%
Mbeya 41%
Rukwa 43%
Katavi 40%
Kigoma 48%
Kilimanjaro 54%
Arusha 40%
Mara 41%
Kagera 38%
Tanga 61%
DSM 38%
Regional FP coverage, 2013
National Average 43%
0 – 39%
40 – 59%
60 – 79%
80 – 100%
Key
ART coverage, 2011-13
2011 2012 20130%
10%
20%
30%
40%
50%
60%
70%
80%72%
63%67%
13%
23%29%
15+ <15
2003/04 2007/08 2011/120.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
7
5.85.3
Survey Year
HIV
Pre
vale
nce
(%)
HIV prevalence.
TB and leprosy indicators Indicator Baseline
(2008) 2011 2012 2013 Target
(2015) TB notification rate per 100,000 population 163 140 142 142 no Tuberculosis treatment success rate (%) 84.7 89 88 89 no The proportion of leprosy cases diagnosed and successful completed treatment pauci-bacillary (cohort registered receding yea) -%
95 93 95 96 97
The proportion of leprosy cases diagnosed and successful completed treatment multi-bacillary (cohort registered preceding 2 year) -%
92 95 94 93 95
HEALTH SYSTEMS INDICATORS
Per capita public spending, 2011/12 – 2013/14
2010/11
2011/12
2012/13
2013/14
2014/15
-
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
29,722 28,086 28,738
32,743 34,660
14,741 12,658 11,639 12,363 12,509
Per capita budget, TZS
nominal real
2010/11 2011/12 2012/13 2013/14 -
5,000
10,000
15,000
20,000
25,000
30,000
22,414 24,416 23,660
28,523
11,116 11,004 9,582
10,770
Per capita actual, TZS
nominal real
Mwanza 1.8% Geita 1.6% Simiyu 1.5%
Shinyanga 2.4%
Tabora 13.2% Singida
29.8%Dodoma 12.6%
Iringa 9.3% =
Morogoro 9.7%
Manyara 3.3%
DDSM
0.66
Pwani 15.8%
Lindi 4.7%
Mtwara 3%Ruvuma 9.9%
Njombe 9.7%
Mbeya 26.4%
Rukwa 12.2%
Katavi 13.8%
Kigoma 8.1%
Kilimanjaro
20.1%
Arusha 5.2%
Mara 2.7%
Kagera 1.3%
Tanga 14.1%
DSM 0%
Regional CHF coverage, 2013
National Average 8.7%
0 – 19%
20 – 39%
40 – 79%
80 – 100%
> 100%
Key
Mwanza7 Geita 3.1% Simiyu 2.5%
Shinyanga 4,9%
Tabora 2.9%
Singida 5.5
Dodoma 6.9
Iringa 11.3 =
Morogoro 7.9
Manyara 7.3%
DDSM
0.66
Pwani 9.6
Lindi 8.3%
Mtwara 6.5Ruvuma 7.2%
Njombe 10.9%
Mbeya 10.1
Rukwa 4.7%
Katavi 2.5%
Kigoma 3.3%
Kilimanjaro
14.8
Arusha 8.6
Mara 6
Kagera 5.2
Tanga 6.7
DSM 13
Human Resource (AMO, MO, Nurses/Nurse Midwife Laboratory staff) Per 10,000
Population by Region 2013
National Average 7.4
0 – 4.9%
5.0 – 6.9%
7.0 - 9.9%
>10
Key
Percentage of facilities with continuous availability of Tracer medicines, Jan-June 2014
Albendazo
le
Amoxycil
lin
Artemeth
er/Lu
merfan
trine o
ral
Depo-prove
ra
Disposab
le syr
inge
Ergometr
ineMRDT
Normal
saline
Oral re
hydrati
on
Pentav
alent v
accin
e0.65
0.7
0.75
0.8
0.85
0.9
83.1%
80.4%
84.4%82.6%
77.7%
80.7%
75.3%
82.7%
76.5%
88.4%
Mwanza 7.1 Geita 5.8 Simiyu 6.6
Shinyanga 6.7
Tabora 8.1
Singida 8.1
Dodoma 7.2
Iringa 8,1
Morogoro 8.5
Manyara 8.1
DDSM
0.66
Pwani 6.8
Lindi 8.1
Mtwara 7.2Ruvuma 7.8
Njombe 8.4
Mbeya 8.1
Rukwa 8.5
Katavi 8.2
Kigoma 7.1
Kilimanjaro
7.8
Arusha 8
Mara 7.8
Kagera 8
Tanga 8.4
DSM 7.4
Mean number of tracers available
January – June 2013
National Average 7.7
Challenges • Unsatisfactory quality of HMIS data– under-reporting and delayed reporting from
health facilities– Insufficient capacity for data
analysis/summarization at health facility level• Lack of reliable population denominators • Duplication of data collection through use of
parallel reporting systems• Inadequate data dissemination and use
Way forward• Strengthening of supportive supervision and mentoring of regions
and councils• Quarterly analysis of HMIS data and review by the M&E TWG to
identify data problems/issues and find out solution• Implement data quality audit activities• Establish a way for regular communication with regions to feed
back and discuss the identified data quality issues• Harmonization of reporting systems for all programmes to prevent
duplications and improve quality• Implement activities that will improve data dissemination and use• Strengthen capacity for data collection, compilation at HF level
and use of DHIS database