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Calibrating orphanhood: Calibrating orphanhood: the number of orphans according to recent the number of orphans according to recent censuses and health surveys censuses and health surveys already exceedalready exceed

UNAIDS estimates for 2010 for UNAIDS estimates for 2010 for Kenya and Benin, and 4/5Kenya and Benin, and 4/5thth for South Africa for South Africa

* * ** * * Robert McCAA,Robert McCAA,

Félicien Donat Edgar T. ACCROMBESSY,Félicien Donat Edgar T. ACCROMBESSY,Khassoum DIALLOKhassoum DIALLO

contact: [email protected]: [email protected]


Total orphans: maternal, paternal, double combinedSources: unadjusted census microdata, UNICEF 2004:32

Census counts of orphans exceed UNAIDS estimatesNote: DNK or NR = dead; except NR+NR = missing data

orph

ans

(milli

ons)

South Africayear

0

.5

1

1.5

2

2.5

3

3.5

zaunaids zacensus

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

orph

ans

(milli

ons)

Kenyayear

0

.5

1

1.5

2

2.5

3

3.5

knunaids kncensus

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

orph

ans

(milli

ons)

Beninyear

0

.5

1

1.5

2

bnunaids bncensus

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

The 2002 census of Benin reveals as many orphans as The 2002 census of Benin reveals as many orphans as predicted for 2010predicted for 2010

The UNAIDS estimates show a progressive rise, 1990-2010The UNAIDS estimates show a progressive rise, 1990-2010Note: the 1990 census of Benin did not contain a question on orphanhood.Note: the 1990 census of Benin did not contain a question on orphanhood.

UNAIDS UNAIDS (2004)(2004)estimatesestimatesfor 1990,for 1990,1995,1995,2000,2000,2003, and2003, and20102010




orph

ans

(milli

ons)

South Africayear

0

.5

1

1.5

2

2.5

3

3.5

zaunaids zacensus

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

orph

ans

(milli

ons)

Kenyayear

0

.5

1

1.5

2

2.5

3

3.5

knunaids kncensus

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

orph

ans

(milli

ons)

Beninyear

0

.5

1

1.5

2

bnunaids bncensus

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

Kenya, orphanhood statistics: UNAIDS estimates 1990-2010Kenya, orphanhood statistics: UNAIDS estimates 1990-2010compared with 1989 and 1999 census datacompared with 1989 and 1999 census data

age 0-17: orphans of any conditionage 0-17: orphans of any condition

SourcesSources:: Kenya: CBS-Kenya census sample from Kenya: CBS-Kenya census sample from www.ipums.org/internationalUNAIDS/UNICEF/USAID, Children on the BrinkChildren on the Brink, 2004:32. , 2004:32. NoteNote:: Results depend upon interpretation of Do not know and No reply. Results depend upon interpretation of Do not know and No reply. We use UNAIDS rule: DNK or NR = dead .We use UNAIDS rule: DNK or NR = dead .

Kenya Kenya 1999 censused orphans > 2010 est1999 censused orphans > 2010 est

1999 census1999 census



http://www.ipums.org/international


1.1. Compare orphanhood estimates from Demographic and Compare orphanhood estimates from Demographic and Health Surveys (DHS) with census microdata (CMD) to find Health Surveys (DHS) with census microdata (CMD) to find that the two sources are in close agreement by age pattern that the two sources are in close agreement by age pattern and type (maternal, paternal and double)and type (maternal, paternal and double)

2.2. Reveal that CMD figures are higher than UNAIDS estimates Reveal that CMD figures are higher than UNAIDS estimates of orphanhood, in some cases higher than the 2010 estimates. of orphanhood, in some cases higher than the 2010 estimates.

3.3. Show that census microdata can be used (Show that census microdata can be used (but are not used by but are not used by UNAIDSUNAIDS) to ) to (omitted for lack of time)(omitted for lack of time)

a.a. Study the condition of orphans in householdsStudy the condition of orphans in households

b.b. Compare trends over time, between and within countriesCompare trends over time, between and within countries

4.4. Conclude that the 2010 round of censuses may provide Conclude that the 2010 round of censuses may provide important benchmarks for the UNAIDS estimates—if the important benchmarks for the UNAIDS estimates—if the orphanhood, relation to hourseholder and associated orphanhood, relation to hourseholder and associated questions are retained (and if researchers analyze them). questions are retained (and if researchers analyze them).

What is original about this paper:What is original about this paper:


1.1. The orphan problem: numbers and consequences The orphan problem: numbers and consequences

2.2. Statistics and sources: UNAIDS vs. microdataStatistics and sources: UNAIDS vs. microdataa.a. UNAIDS estimated projectionsUNAIDS estimated projections

(based on demographic-epidemiological models)(based on demographic-epidemiological models) b.b. Surveys (Demographic & Health)Surveys (Demographic & Health)c.c. Censuses and census microdata (example of S. Africa): Censuses and census microdata (example of S. Africa):

Is your mother/father alive?Is your mother/father alive?Why not use these data to estimate/study orphans?Why not use these data to estimate/study orphans?

3.3. Insights from census microdata: Insights from census microdata: a.a. More orphans now than projected for 2010More orphans now than projected for 2010b.b. Yet, the extended family still shelters orphansYet, the extended family still shelters orphans

4.4. Policy implications: aid/assist Policy implications: aid/assist allall children children

Outline: the number of orphans, in recent censuses and Outline: the number of orphans, in recent censuses and health surveys, already exceed UNAIDS estimates for health surveys, already exceed UNAIDS estimates for 2010 for Kenya and Benin, & 4/52010 for Kenya and Benin, & 4/5thth for South Africa for South Africa


The orphan problem caused by AIDS: The orphan problem caused by AIDS: how many and how will they be cared forhow many and how will they be cared for

1.1. UNAIDS (1990-2010) projects a tripling of the number of UNAIDS (1990-2010) projects a tripling of the number of orphans, even with reduced fertility due to a) demographic orphans, even with reduced fertility due to a) demographic transformation & b) AIDS as well as c) increased mortality of transformation & b) AIDS as well as c) increased mortality of childrenchildren

2.2. Given the low life expectancy in many African countries, the Given the low life expectancy in many African countries, the extended family, particularly the grandmother, has long extended family, particularly the grandmother, has long cared for orphans.cared for orphans.

3.3. With the surge in the number of orphans and life expectancy With the surge in the number of orphans and life expectancy contracting, will the extended family continue to shelter contracting, will the extended family continue to shelter orphans?orphans?


Deconstructing “orphan”Deconstructing “orphan”““In African culture, we do not make the same distinctions among In African culture, we do not make the same distinctions among

relations practised by whites. We have no half-brothers or half-relations practised by whites. We have no half-brothers or half-sisters. My mother’s sister is my mother; my uncle’s son is my sisters. My mother’s sister is my mother; my uncle’s son is my brother; my brother’s child is my son, my daughter.”brother; my brother’s child is my son, my daughter.”

--Nelson Mandela (1994)--Nelson Mandela (1994) What is an orphan? --a social construct on a biological baseWhat is an orphan? --a social construct on a biological base

Mandela or models: kin terms and relations--the “adoption effect”Mandela or models: kin terms and relations--the “adoption effect”

Sociological (may include foster/step/etc.) vs. bio/demographic Sociological (may include foster/step/etc.) vs. bio/demographic

UNAIDS definition: child < 18 years with at least 1 parent is deadUNAIDS definition: child < 18 years with at least 1 parent is dead What are the implications?What are the implications?

Demography: mortality requires biological definition (Brass 1971)Demography: mortality requires biological definition (Brass 1971)

Policy, to promote child welfare: is a sociological definition ok?Policy, to promote child welfare: is a sociological definition ok?

Sources: fuzziness of the census may be an advantage for policy Sources: fuzziness of the census may be an advantage for policy making, although a disadvantage for estimating mortalitymaking, although a disadvantage for estimating mortality


Personal anecdotesPersonal anecdotes

Low number of orphans due to AIDS (2003): Low number of orphans due to AIDS (2003): 23-48,000 (5-10%)23-48,000 (5-10%)


3 Sources on orphans3 Sources on orphans1.1. UNAIDS method (2004:209): demographic-epidemiological model UNAIDS method (2004:209): demographic-epidemiological model

developed by UNAIDS Reference Group on HIV/AIDS Estimates, developed by UNAIDS Reference Group on HIV/AIDS Estimates, Modeling and Projections, with plausibility boundsModeling and Projections, with plausibility bounds Fertility, mortality, AIDS mortalityFertility, mortality, AIDS mortality Estimate maternal orphans, followed by estimates of paternal Estimate maternal orphans, followed by estimates of paternal

orphans using male fertility patterns for ages 0-17 yearsorphans using male fertility patterns for ages 0-17 years Concordance with DH Surveys (Grassly et al, 2005:373) Concordance with DH Surveys (Grassly et al, 2005:373)

2.2. DHS, the “gold standard” – Periodic, finely tuned, comprehensive DHS, the “gold standard” – Periodic, finely tuned, comprehensive instruments, skilled interviewers; many countries; ages 0-14 only.instruments, skilled interviewers; many countries; ages 0-14 only.

3.3. Census Census –– National in scope, snapshot of basic demographic and National in scope, snapshot of basic demographic and social characteristics, of individuals (all ages), families/households.social characteristics, of individuals (all ages), families/households. Poorly trained interviewers, simple questions, nothing on Poorly trained interviewers, simple questions, nothing on

AIDS, mortality estimates are contentiousAIDS, mortality estimates are contentious Microdata are difficult to obtain: ACAP (few 2000 round Microdata are difficult to obtain: ACAP (few 2000 round

censuses), IPUMS (1 African country), census agencies censuses), IPUMS (1 African country), census agencies


Benin, a West African example of low Benin, a West African example of low prevalence of AIDS, yet number of orphans in prevalence of AIDS, yet number of orphans in 2002 2002 already exceedsalready exceeds UNAIDS 2010 estimate UNAIDS 2010 estimate

Low number of orphans due to AIDS (2003): Low number of orphans due to AIDS (2003): 23-48,000 (5-10%)23-48,000 (5-10%)

HIV positive in capital city: 60% of sex workers; only 2% of HIV positive in capital city: 60% of sex workers; only 2% of young pregnant women.young pregnant women.

Yet, the total number of orphans in 2002 (385,000) exceeds Yet, the total number of orphans in 2002 (385,000) exceeds the number projected for 2010 (370,000)the number projected for 2010 (370,000)


Kenya 1999 census questionnaireKenya 1999 census questionnaire


Kenya 1989 census: instructions Kenya 1989 census: instructions to enumerators regarding to enumerators regarding

orphanhoodorphanhood““[Kenya, 1989:] Columns P17 and P18 - Orphanhood[Kenya, 1989:] Columns P17 and P18 - Orphanhood

117 117 ‘Is this person’s father/mother alive ?’‘Is this person’s father/mother alive ?’

118 118 Code 1 or 2 in respect of the person’s biological father and mother. Code 1 or 2 in respect of the person’s biological father and mother. Foster parents or other relatives who may have adopted the person should not Foster parents or other relatives who may have adopted the person should not be considered as the father or mother of the person be considered as the father or mother of the person [emphasis added].[emphasis added].

119 119 In some cases, child’s father may not be married or living with the In some cases, child’s father may not be married or living with the mother. In this case the mother might report that she does not know whether mother. In this case the mother might report that she does not know whether the father of her child is alive or dead. In this case code 3 for ‘Not-Known’.”the father of her child is alive or dead. In this case code 3 for ‘Not-Known’.”Source: www.ipums.org/international/enumforms/ken/ken1989_enuminstruct.pdf frame 12.

• Note: the instructions clearly emphasize “biological” Note: the instructions clearly emphasize “biological” parentage, but did enumerators pay attention? parentage, but did enumerators pay attention?• Better would be to include “biological” on questionnaireBetter would be to include “biological” on questionnaire

http://www.ipums.org/international/enumforms/ken/ken1989_enuminstruct.pdf


1999 instructions to census 1999 instructions to census enumerators regarding enumerators regarding

orphanhoodorphanhood““[Kenya, 1989:] Columns P17 and P18 - Orphanhood[Kenya, 1989:] Columns P17 and P18 - Orphanhood

117 117 ‘Is this person’s father/mother alive ?’‘Is this person’s father/mother alive ?’

118 118 Code 1 or 2 in respect of the person’s biological father and mother. Code 1 or 2 in respect of the person’s biological father and mother. Foster parents or other relatives who may have adopted the person should not Foster parents or other relatives who may have adopted the person should not be considered as the father or mother of the person be considered as the father or mother of the person [emphasis added].[emphasis added].

119 119 In some cases, child’s father may not be married or living with the In some cases, child’s father may not be married or living with the mother. In this case the mother might report that she does not know whether mother. In this case the mother might report that she does not know whether the father of her child is alive or dead. In this case code 3 for ‘Not-Known’.”the father of her child is alive or dead. In this case code 3 for ‘Not-Known’.”Source: www.ipums.org/international/enumforms/ken/ken1989_enuminstruct.pdf frame 12.

““[Kenya, 1999:] Columns P20-21: Orphanhood[Kenya, 1999:] Columns P20-21: Orphanhood

79. 79. "Is this person's father/mother alive?" "Is this person's father/mother alive?"

(a) (a) Tick the box under the appropriate column in respect of the survival Tick the box under the appropriate column in respect of the survival status of the respondent's biological father and mother. status of the respondent's biological father and mother. Note that at times Note that at times destitute children are brought up or adopted at a very young age by relatives. destitute children are brought up or adopted at a very young age by relatives. Such foster parents should not be considered as the biological parents of the Such foster parents should not be considered as the biological parents of the respondent. Please always probe to establish the reality of the situation respondent. Please always probe to establish the reality of the situation [emphasis added].[emphasis added].

(b) (b) In some cases, a child's father/mother may not be married or living In some cases, a child's father/mother may not be married or living with the mother/father. In this case the mother/father might report that she/he with the mother/father. In this case the mother/father might report that she/he does not know whether the father/mother of her child is alive or dead. In this does not know whether the father/mother of her child is alive or dead. In this case mark an "X" in the box for, 'don't know'. You must always probe to ensure case mark an "X" in the box for, 'don't know'. You must always probe to ensure you obtain the most satisfactory answer.you obtain the most satisfactory answer.

Source: www.ipums.org/international/enumforms/ken/ken1999_enuminstruct.pdf frame 31.




Sources: Demographic and Health Survey (DHS) Kenya 1998 Table 2.4; 1999 census microdatata Sources: Demographic and Health Survey (DHS) Kenya 1998 Table 2.4; 1999 census microdatata “imputed” come from a custom, non-circulating, edited sample supplied by the Central Bureau “imputed” come from a custom, non-circulating, edited sample supplied by the Central Bureau of Statistics of Kenya; 1999 and 1989 are from harmonized extracts from of Statistics of Kenya; 1999 and 1989 are from harmonized extracts from https://www.ipums.org/international https://www.ipums.org/international

Calibrating Orphanhood: Calibrating Orphanhood: Kenyan Survey and Census Microdata Are Remarkably CoherentKenyan Survey and Census Microdata Are Remarkably Coherent

Percent (Children aged 0-14 years)Percent (Children aged 0-14 years) NumberNumber

Status of parents:Status of parents:Both Both alivealive

DeadDead

NN D/KD/KFatherFather MotherMother BothBoth

DH Survey 1998DH Survey 1998 15,91715,917 493493

Don’t know = deadDon’t know = dead 87.787.7 8.78.7 2.42.4 1.21.2

Don’t know=imputed Don’t know=imputed 90.4 90.4 6.8 6.8 1.9 1.9 0.9 0.9

Census microdata, 1999Census microdata, 1999 717,317717,317 16,27516,275

Don’t know = deadDon’t know = dead 88.3 88.3 8.3 8.3 1.9 1.9 1.5 1.5

Don’t know = aliveDon’t know = alive 90.5 90.5 6.8 6.8 1.7 1.7 1.0 1.0

Don’t know=imputedDon’t know=imputed 90.6 90.6 6.9 6.9 1.6 1.6 0.9 0.9

Census microdata, 1989Census microdata, 1989 514,312514,312 12,60412,604

Don’t know = deadDon’t know = dead 91.3 91.3 6.8 6.8 1.2 1.2 0.7 0.7

Don’t know = aliveDon’t know = alive 93.7 93.7 4.9 4.9 1.0 1.0 0.3 0.3

3.1%3.1%

2.2%2.2%

2.5%2.5%


Table 5: Estimates of Orphaned Children: census microdata and UNAIDS, Table 5: Estimates of Orphaned Children: census microdata and UNAIDS, Kenya 1989-2003 (millions)—Kenya 1989-2003 (millions)—there are some puzzling inconsistenciesthere are some puzzling inconsistencies

NotNot OrphanedOrphaned

YearYear SourceSourceTotal Total

ChildrenChildren OrphanedOrphaned PaternalPaternal MaternalMaternal DoubleDouble Tot.Tot.

Children agedChildren aged 0-14 0-14 years (UNAIDS 2002 definition)years (UNAIDS 2002 definition)

19891989 census microdatacensus microdata 10.310.3 9.49.4 0.70.7 0.10.1 0.10.1 0.90.9

19901990 UNAIDS 2002:16UNAIDS 2002:16 11.711.7 10.710.7 0.60.6 0.30.3 0.10.1 1.01.0


20012001 UNAIDS: 2002:22UNAIDS: 2002:22 13.413.4 11.811.8 0.80.8 0.60.6 0.30.3 1.71.7

Children aged Children aged 0-170-17 years (UNAIDS 2004 definition) years (UNAIDS 2004 definition)


19901990 UNAIDS 2004:30UNAIDS 2004:30 11.811.8 nana nana nana nana 1.31.3



20032003 UNAIDS 2004:26UNAIDS 2004:26 15.015.0 13.213.2 0.60.6 0.60.6 0.40.4 1.71.7

??

??

Sources: UNAIDS, Sources: UNAIDS, Children on the Brink 2002Children on the Brink 2002 (p. 16, 22) and (p. 16, 22) and 20042004 (p. 26, 30); 1999 census microdatata with “imputed” come from (p. 26, 30); 1999 census microdatata with “imputed” come from a custom, non-circulating, edited sample supplied by the Central Bureau of Statistics of Kenya; 1989 and 1999 figures are a custom, non-circulating, edited sample supplied by the Central Bureau of Statistics of Kenya; 1989 and 1999 figures are from a harmonized extract obtained from from a harmonized extract obtained from www.ipums.org/international . In both instances “do not know”s are recoded to . In both instances “do not know”s are recoded to “dead”, that is, orphanhood is maximized. UNAIDS convention is: total orphans = paternal + maternal “dead”, that is, orphanhood is maximized. UNAIDS convention is: total orphans = paternal + maternal –– double. double. We have converted such figures, thus: total orphans = paternal + maternal We have converted such figures, thus: total orphans = paternal + maternal + + double.double.



Estimates of Orphaned Children: census microdata and UNAIDS, Estimates of Orphaned Children: census microdata and UNAIDS,

Kenya 1989-2003 (millions)Kenya 1989-2003 (millions)——there are some puzzling inconsistenciesthere are some puzzling inconsistencies

NotNot OrphanedOrphaned

YearYear SourceSourceTotal Total

ChildrenChildren OrphanedOrphaned PaternalPaternal MaternalMaternal DoubleDouble Tot.Tot.

Children agedChildren aged 0-14 0-14 years (UNAIDS 2002 definition)years (UNAIDS 2002 definition)


19901990 UNAIDS 2002:16UNAIDS 2002:16 11.711.7 10.710.7 0.60.6 0.30.3 0.10.1 1.01.0


20012001 UNAIDS: 2002:22UNAIDS: 2002:22 13.413.4 11.811.8 0.80.8 0.60.6 0.30.3 1.71.7

Children aged Children aged 0-170-17 years (UNAIDS 2004 definition) years (UNAIDS 2004 definition)





20032003 UNAIDS 2004:26UNAIDS 2004:26 15.015.0 13.213.2 0.60.6 0.60.6 0.40.4 1.71.7

Sources: UNAIDS, Sources: UNAIDS, Children on the Brink 2002Children on the Brink 2002 (p. 16, 22) and (p. 16, 22) and 20042004 (p. 26, 30); 1999 census microdatata with “imputed” come from (p. 26, 30); 1999 census microdatata with “imputed” come from a custom, non-circulating, edited sample supplied by the Central Bureau of Statistics of Kenya; 1989 and 1999 figures are a custom, non-circulating, edited sample supplied by the Central Bureau of Statistics of Kenya; 1989 and 1999 figures are from a harmonized extract obtained from from a harmonized extract obtained from www.ipums.org/international . In both instances “do not know”s are recoded to . In both instances “do not know”s are recoded to “dead”, that is, orphanhood is maximized. UNAIDS convention is: total orphans = paternal + maternal “dead”, that is, orphanhood is maximized. UNAIDS convention is: total orphans = paternal + maternal –– double. double. We have converted such figures, thus: total orphans = paternal + maternal We have converted such figures, thus: total orphans = paternal + maternal + + double.double.

?? ?? ??





orph

ans

(milli

ons)

South Africayear

0

.5

1

1.5

2

2.5

3

3.5

zaunaids zacensus

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

orph

ans

(milli

ons)

Kenyayear

0

.5

1

1.5

2

2.5

3

3.5

knunaids kncensus

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

orph

ans

(milli

ons)

Beninyear

0

.5

1

1.5

2

bnunaids bncensus

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

Recall Kenya, orphanhood statistics: Recall Kenya, orphanhood statistics: UNAIDS estimates 1990-2010UNAIDS estimates 1990-2010

compared with 1989 and 1999 census datacompared with 1989 and 1999 census dataage 0-17: orphans of any conditionage 0-17: orphans of any condition

SourcesSources:: Kenya: CBS-Kenya census sample from Kenya: CBS-Kenya census sample from www.ipums.org/internationalUNAIDS/UNICEF/USAID, Children on the BrinkChildren on the Brink, 2004:32. , 2004:32. NoteNote:: Results depend upon interpretation of Do not know and No reply. Results depend upon interpretation of Do not know and No reply. We use UNAIDS rule: DNK or NR = dead .We use UNAIDS rule: DNK or NR = dead .

Kenya Kenya 1999 censused orphans > 2010 est1999 censused orphans > 2010 est






orp

ha

ns

(mill

ion

s)

South Africayear

0

.5

1

1.5

2

2.5

3

3.5

zaunaids zacensus

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009

2001 census is four-fifths of estimate for 20102001 census is four-fifths of estimate for 2010

South Africa, orphanhood: UNAIDS estimates 1990-2010South Africa, orphanhood: UNAIDS estimates 1990-2010compared with 1996 and 2001 census microdatacompared with 1996 and 2001 census microdata

age 0-17: orphans of any conditionage 0-17: orphans of any condition

Anomaly? Or history?Anomaly? Or history?1996 census1996 census




South African census microdata:South African census microdata:1996 and 2001 compared1996 and 2001 compared

1.1. 1996: “maternal orphanhood data are good” (Bah 1999:36 -- 1996: “maternal orphanhood data are good” (Bah 1999:36 -- does not examine paternal). does not examine paternal).

2.2. For 1996 & 2001: low rates of “Do Not Know” and “No For 1996 & 2001: low rates of “Do Not Know” and “No Reply”Reply”

3.3. Increase in total orphans is less than expected, but both are Increase in total orphans is less than expected, but both are higher than UNAIDS estimates (millions): higher than UNAIDS estimates (millions): 2.2 (’96 vs. 1.5 for ‘95) and 2.5 (’01 vs. 2.2 for ’03) 2.2 (’96 vs. 1.5 for ‘95) and 2.5 (’01 vs. 2.2 for ’03)

4.4. High concordance with DHS (see next slides); similar by:High concordance with DHS (see next slides); similar by:age pattern: 0, 1, …17age pattern: 0, 1, …17by type: maternal, paternal, doubleby type: maternal, paternal, double


Double, Maternal, and Paternal Excludes children where both mother and father = no reply

% o

rph

an

ed

South Africa: orphanhood rates DHS 1998age of child

0 2 4 6 8 10 12 14 16

0

2

4

6

8

10

12

14

16

18

20

mDHS1998

pDHS1998

dDHS1998

A ‘gold standard’: DHS Survey (1998)A ‘gold standard’: DHS Survey (1998)

Are census microdata useful/reliable?Are census microdata useful/reliable?Compare orphanhood microdata by age of orphan Compare orphanhood microdata by age of orphan

and type (paternal, maternal, double) for South Africaand type (paternal, maternal, double) for South Africa


Paterns are consistent by age and typeExcludes children where both mother and father = no reply

% o

rph

an

ed

Orphanhood in South Africa: 1996 census and 1998 DHS comparedage of child

0 2 4 6 8 10 12 14 16

0

2

4

6

8

10

12

14

16

18

20

m1996

p1996

d1996mDHS1998

pDHS1998

dDHS1998

1996 census microdata closely track the 1998 DHS1996 census microdata closely track the 1998 DHS

Compare DHS ’98 with Census Microdata 1996:Compare DHS ’98 with Census Microdata 1996:Amazing agreement! Census figures are more regular!Amazing agreement! Census figures are more regular!


Patterns are remarkably consistent50% increase in Maternal Orphans in 5 years; 20% in Doubles

% o

rph

an

ed

South Africa: orphanhood rates 1996, 1998 and 2001age of child

0 2 4 6 8 10 12 14 16

0

2

4

6

8

10

12

14

16

18

20

m2001

p2001

d2001m1996

p1996

d1996mDHS1998

pDHS1998

dDHS1998

2001 census microdata are predictably higher2001 census microdata are predictably higher

Add Census Microdata for 2001:Add Census Microdata for 2001:Amazing agreement! 2001 rates are indeed higher!Amazing agreement! 2001 rates are indeed higher!


Why aren’t census microdata being used to Why aren’t census microdata being used to calibrate UNAIDS estimates calibrate UNAIDS estimates

1.1. For Africa, census microdata are difficult to obtain:For Africa, census microdata are difficult to obtain:

a.a. No recent census (Angola, Cameroon, DR Congo, Liberia, No recent census (Angola, Cameroon, DR Congo, Liberia, Nigeria, etc.)Nigeria, etc.)

b.b. Dissemination of 2000 round microdata limited to 3 Dissemination of 2000 round microdata limited to 3 countries, so far: Kenya, Mauritius, and South Africa countries, so far: Kenya, Mauritius, and South Africa (Benin made available to co-author).(Benin made available to co-author).

c.c. ACAP (Penn) and IPUMS-Interntational (Minnesota) ACAP (Penn) and IPUMS-Interntational (Minnesota) seek to provide access to researchers seek to provide access to researchers

2.2. Perhaps, too, researchers consider census data as less reliablePerhaps, too, researchers consider census data as less reliable

3.3. Or perhaps, they are not familiar with them.Or perhaps, they are not familiar with them.


Conclusions: Conclusions: 1.1. For the 2000 round of censuses…For the 2000 round of censuses…

» Microdata should be used as they become availableMicrodata should be used as they become available» Commercial: Commercial: www.ipums.org/international offers Kenyan offers Kenyan

census microdata (plus other countries) to researchers w/o census microdata (plus other countries) to researchers w/o cost; South Africa coming soon. cost; South Africa coming soon.

2.2. For the 2010 round of censuses…For the 2010 round of censuses…the microdata will be a valuable benchmarkthe microdata will be a valuable benchmark» If the censuses are conductedIf the censuses are conducted» If they include questions on orphanhoodIf they include questions on orphanhood» If researchers use the census microdataIf researchers use the census microdata

3.3. Policy implications: measure, manage (Paris21!)Policy implications: measure, manage (Paris21!)a.a. There will be There will be moremore orphans than UNAIDS estimates orphans than UNAIDS estimatesb.b. Currently, families shelter orphans (at some cost, and not Currently, families shelter orphans (at some cost, and not

entirely satisfactorily) but can they in 2010?entirely satisfactorily) but can they in 2010?** Thank you **** Thank you **


https:// calibrating orphanhood: the number of orphans according to recent censuses and health...

Documents

census unaids

unaids estimates of

number of orphans

condition of orphans

orphanhood estimates

unaids estimatesif

unaids rule

census of benin