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CSU 123/2010: SEASON'S GREETINGS/ USE OF EXISTING DATA FOR GEOGRAPHICAL TARGETING

Friday, 3rd of December 2010 Print

Dear All,

CSU 123/2010: SEASON'S GREETINGS/ USE OF EXISTING DATA  FOR GEOGRAPHICAL TARGETING

 SEASONS' GREETINGS

To those celebrating Hanukkah or Advent this month, best wishes of the season.

USE OF EXISTING DATA FOR GEOGRAPHICAL TARGETING

In the best of all possible worlds, abundant resources would be available for EPI, data would be of high quality, and external assistance could be made available everywhere.

On planet earth, other approaches are called for. Consider the table below.  It tells us that the BCG coverage in the first district listed was 89 percent, and measles was 75 percent. The dropout rate between the two was (89 – 75)/89 x 100, or 16 percent.

Doing the same exercise for each of the 100 districts, we soon get a rank ordering, from top to bottom, of dropout rates for all the districts of the country. Our work is not yet completed. We need to ask ourselves, 16 percen t of what? The column listed livebirths tells us that 16 percent of the 44,088 liveborn infants did not finish their vaccination series. So 6935 infants in this district got BCG, but did not finish the vaccination series.

When we complete this exercise for every district listed, we are likely to discover that 2/3 of the infants with incomplete vaccinations live in about 1/3 of the districts. Moreover, in most countries, the capital city, far from overperforming the country, includes a large share of the undervaccinated infants.

What do we do with this information? If we are a self-financed vaccination programme, we put our resources, or the bulk of them, where the problem is. If we are an international partner, we share these data with the government and ask them how best to proceed in the allocation of scarce resources.

Cheers, BD

 

Name of the district

Livebirths, 2009

 

 
     

BCG
%

MCV1*
%

 

ANTANANARIVO-RENIVOHITRA

44088

89%

75%

 

ANTANANARIVO-ATSIMONDRANO

11281

126%

121%

 

ANTANANARIVO-AVARADRANO

9582

100%

98%

 

AMBATOLAMPY

8163

89%

89%

 

AMBOHIDRATRIMO

9020

97%

106%

 

ANDRAMASINA

5644

96%

100%

 

ANJOZOROBE

6668

97%

95%

 

ANKAZOBE

5075

94%

87%

 

ANTANIFOTSY

11284

93%

86%

 

ANTSIRABE I

7767

84%

73%

 

ANTSIRABE II

13808

86%

80%

 

ARIVONIMAMO

10150

100%

97%

 

BETAFO

13381

106%

103%

 

FARATSIHO

6299

94%

85%

 

FENOARIVO-AFOVOANY

4859

99%

93%

 

MANJAKANDRIANA

8215

71%

77%

 

MIARINARIVO

9605

88%

75%

 

SOAVINANDRIANA

6892

110%

105%

 

TSIROANOMANDIDY

13467

115%

94%

 

ANTSIRANANA I

3517

85%

66%

 

ANTSIRANANA II

3416

50%

45%

 

AMBANJA

5912

91%

84%

 

AMBILOBE

6967

76%

76%

 

ANTALAHA

8622

111%

99%

 

ANDAPA

6930

94%

87%

 

NOSY-BE

2165

65%

60%

 

SAMBAVA

10933

92%

81%

 

VOHIMARINA (Vohémar)

7071

111%

95%

 

FIANARANTSOA I

5949

84%

75%

 

FIANARANTSOA II

16889

82%

73%

 

AMBALAVAO

7205

114%

98%

 

AMBATOFINANDRAHANA

4016

93%

82%

 

AMBOHIMAHASOA

7446

82%

83%

 

AMBOSITRA

9471

81%

70%

 

BEFOTAKA

1002

63%

62%

 

FANDRIANA

7639

85%

85%

 

FARAFANGANA

10955

60%

70%

 

IKONGO

9457

44%

52%

 

IAKORA

1288

90%

102%

 

IFANADIANA

5435

59%

86%

 

IHOSY

6314

85%

97%

 

IKALAMAVONY

2488

93%

85%

 

IVOHIBE

1756

74%

96%

 

MANAKARA-ATSIMO

12458

69%

76%

 

MANANJARY

13171

66%

68%

 

MIDONGY-ATSIMO

1242

93%

89%

 

NOSY-VARIKA

8180

80%

79%

 

VANGAINDRANO

8621

89%

85%

 

VOHIPENO

5482

44%

50%

 

VONDROZO

3343

104%

102%

 

MANANDRIANA

3593

89%

86%

 

MAHAJANGA I

6111

85%

72%

 

MAHAJANGA II

1776

65%

67%

 

AMBATO-BOINA

4771

61%

45%

 

AMBATOMAINTY

923

119%

121%

 

ANALALAVA

4500

75%

58%

 

ANTSALOVA

2220

85%

98%

 

ANTSOHIHY

5506

48%

54%

 

BEALANANA

4465

98%

89%

 

BEFANDRIANA-AVARATRA

6676

116%

102%

 

BESALAMPY

2047

58%

119%

 

KANDREHO

475

107%

119%

 

MAEVATANANA

4652

89%

82%

 

MAINTIRANO

2871

95%

106%

 

MAMPIKONY

3236

114%

92%

 

MANDRITSARA

8035

124%

105%

 

MAROVOAY

4701

83%

79%

 

MITSINJO

2228

149%

134%

 

MORAFENOBE

1375

87%

87%

 

BORIZINY (Port-Berger)

5163

104%

105%

 

SOALALA

1175

47%

58%

 

TSARATANANA

4035

106%

90%

 

TOAMASINA I

6805

106%

88%

 

TOAMASINA II

6814

89%

88%

 

AMBATONDRAZAKA

10991

88%

85%

 

AMPARAFARAVOLA

7993

101%

95%

 

ANDILAMENA

4277

69%

63%

 

ANOSIBE AN-ALA

4951

95%

85%

 

ANTANAMBAO-MANAMPOTSY

1785

89%

83%

 

VOHIBINANY (Brickaville)

6525

80%

73%

 

FENOARIVO-ATSINANANA

9470

118%

121%

 

MAHANORO

7790

83%

74%

 

MANANARA-AVARATRA

4820

103%

98%

 

MAROANTSETRA

7299

102%

96%

 

MAROLAMBO

4413

88%

88%

 

MORAMANGA

7432

118%

105%

 

NOSY-BORAHA (Sainte Marie)

881

69%

75%

 

SOANIERANA-IVONGO

5619

78%

82%

 

VATOMANDRY

5233

78%

79%

 

VAVATENINA

5948

81%

87%

 

TOLIARY I

4890

85%

87%

 

TOLIARY II

7275

81%

78%

 

AMBOASARY-ATSIMO

6354

59%

105%

 

AMBOVOMBE-ANDROY

8313

62%

113%

 

AMPANIHY

9167

64%

70%

 

ANKAZOABO-ATSIMO

2043

67%

61%

 

BEKILY

4987

103%

123%

 

BELO-TSIRIBIHINA

4432

78%

84%

 

BELOHA

2199

61%

156%

 

BENENITRA

1238

44%

44%

 

BEROROHA

1813

41%

56%

 

BETIOKY-ATSIMO

7252

70%

74%

 

BETROKA

6118

58%

51%

 

TAOLAGNARO

8847

81%

82%

 

MAHABO

4842

93%

78%

 

MANJA

2652

78%

69%

 

MIANDRIVAZO

3880

78%

67%

 

MOROMBE

4545

63%

59%

 

MORONDAVA

4640

82%

73%

 

SAKARAHA

2813

85%

88%

 

TSIHOMBE

3328

54%

93%

 

Total

701795

87%

85%

 

 



 



































































































































Good reading.

 BD

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