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National and subnational experience with estimating the extent and trend in completeness of registration of deaths in South Africa Rob Dorrington Centre for Actuarial Research University of Cape Town Analytical methods to evaluate the completeness and quality of birth registration Session 4 of the UN Expert Group Meeting on the methodology and lessons learner to evaluate the completeness and quality of vital statistics data from civil registration

National and subnational experience with estimating the ... · National and subnational experience with estimating the extent and trend in completeness of registration of deaths in

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National and subnational experience with estimating the extent and trend in

completeness of registration of deaths in South Africa

Rob Dorrington Centre for Actuarial Research

University of Cape Town

Analytical methods to evaluate the completeness and quality of birth registration

Session 4 of the UN Expert Group Meeting on the methodology and lessons learner to evaluate the completeness and quality of vital statistics data from civil

registration

Background

Population 51.8 million in 2011

VR data are incomplete – slightly more than 500,000 deaths in 2011

Significant HIV/AIDS epidemic + significant treatment from 2004/5

Surveys: DHS 1998 and 2003 (unsuccessful); GHS (limited information, Udjo 1997; 2005); 2007 Community Survey (not very reliable); HSRC 2012 (not publicly available)

3 post-apartheid censuses (1996, 2001 & 2011) not without problems (Moultrie & Dorrington 2004) – only 2001 and 2011 asked households to report on deaths

Most recent reliable estimates of IMR & U5MR from 1998 DHS and 1996 census

2

Rapid mortality surveillance (RMS)

Hiatus in processing VR data while rising AIDS epidemic

Population register (PR) comprising all registered births and adults with IDs

RMS originally set up to ‘prove’ that people were dying of AIDS, and track the impact on mortality

More recently tracking impact of interventions (ART)

Extrapolate trend in PR vs VR estimate future VR from PR

Completeness of VR deaths 15+ from a trend in estimates of completeness in intercensal periods

Completeness of VR deaths <5 was interpolated/extrapolated from estimates of infant and under-five mortality from census and survey data

3

PR deaths as a proportion of Stats SA deaths by age group, 2000-2014

4

Ratio of VR deaths to estimate of complete deaths (15+) by duration since year of death: 2008-2014

5

RMS NNR, IMR & U5MR vs other methods/data

6

0

10

20

30

40

50

60

70

80

90

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

De

ath

s p

er

1 0

00

live

bir

ths

NMR (VR) IMR (VR) U5MR (VR)

NMR (DHIS) IMR (RMS) U5MR (RMS)

IMR (direct) NMR (direct VR) NMR (direct DHIS)

Some observations about the assumption of constant completeness by age

7

Some observations about the assumption of constant completeness by age

Also, urban completeness > rural completeness and age distribution differs in the two areas violation of assumption

With deaths reported by households

Where there are many one or two-person households

under-reporting of deaths at the old ages (particularly for women?)

For young adults the opposite might happen – a death being reported by more than one household

8

Estimating of mortality of sub-national areal populations

A challenge since

VR data – lack of correspondence between place of death and place of usual residence (which is usually not captured) and need reliable estimates of sub-national migration

Household deaths – often violate the assumption of constant completeness by age and are for a short period creating uncertainty about the estimates

Thus Dorrington and Timaeus (2015) suggest combining the two sources, by

using VR to estimate the true numbers of deaths nationally by age for each sex (and possibly other divisions that could affect reporting of household data)

Assuming all households by sex (and other divisions) are equally likely to report the deaths at each age

9

SA: 45q15 vs projection model estimates

10

WC

EC

NC

FS

KZ

NW

GT

MP

LP

WC

ECNC

FSKZ

NW

GT

MP

LP

0%

10%

20%

30%

40%

50%

60%

70%

0% 10% 20% 30% 40% 50% 60% 70%

45q

15 f

rom

ho

useh

old

death

s

45q15 from model

2001

Males

Females

45o

NationalWC

EC

NC

FSKZ

NW

GT

MPLP

WC

EC

NC

FS

KZNW

GT

MP

LP

0%

10%

20%

30%

40%

50%

60%

70%

0% 10% 20% 30% 40% 50% 60% 70%

45q

15 f

rom

ho

useh

old

death

s

45q15 from model

2011

Males

Females

45o

National

Brazil: vs household deaths alone

11

N NE

SE

S

MW

NNE

SES

MW

0%

5%

10%

15%

20%

25%

30%

0% 5% 10% 15% 20% 25%

Qu

eiro

z

Dorrington&Timaeus

45q15

45o

Males

Females

N

NE

SE

S

MW

N

NE

SE

S

MW

75%

80%

85%

90%

95%

100%

105%

110%

75% 80% 85% 90% 95% 100% 105% 110%Q

uei

roz

Dorrington&Timaeus

Completeness

45o

Males

Females

Brazil: vs VR data alone

12

N NESE

S

MW

NNE SES MW

0%

5%

10%

15%

20%

25%

0% 5% 10% 15% 20% 25%

Qu

eiro

z

Dorrington&Timaeus

45q15

45o

Series2

Series3

N NE

SE SMW

N

NE

SE S

MW

70%

75%

80%

85%

90%

95%

100%

105%

70% 75% 80% 85% 90% 95% 100% 105%Q

uei

roz

Dorrington&Timaeus

Completeness

45o

Males

Females

Estimating mortality at advanced ages

13

NEG vs census: males 2011

14

Mortality by population group and vs HMD average and range

15

Discussion

RMS

Even an incomplete population register can be useful

Consistency of trend over time as important than attempting to increase completeness or release data more rapidly at the expense of seriously disrupting a well-established trend

When completeness high direct estimates of IMR are not too inaccurate

Assumption of constant completeness by age

Only true above age 30 in South Africa

Likely to be a problem in significantly heterogeneous populations (e.g. urban vs rural)

Household deaths likely to be problematic unless stable multigenerational families

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Discussion

Sub-national populations

Method is promising, but no gold standard to check

Works better if can identify factors linked to whether households report deaths

Mortality at old ages

Age problems (year of birth heaping) can be entrenched in the official data, limiting usefulness of NEG methods

NEG-GAM has potential but may not eliminate the age exaggeration in the death data (particularly if incentives to exaggerate age)

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