Modelling HIV/AIDS in Southern Africa Centre for Actuarial Research (CARe) A Research Unit of the...
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Transcript of Modelling HIV/AIDS in Southern Africa Centre for Actuarial Research (CARe) A Research Unit of the...
Modelling HIV/AIDS in Southern Africa
Centre for Actuarial Research (CARe)A Research Unit of the University of Cape Town
History of the ASSA AIDS and Demographic model Doyle-Metropolitan model (c1990) ASSA500 (c1995) ASSA600 (c1998) ASSA2000 suite (2001): lite, full, provincial
(beta 2002) ASSA2002 lite and full (2004) ASSA2003 suite (2005): lite, full, provincial Other models (www.assa.org.za/aidsmodel.asp)
Orphans, select populations, other countries
Methodology: ASSA model
Antenatal data(by age)
Adult death data
Adjust for bias (public anc vs all
women)
Demographic parameters (base population, fertility, non-
AIDS mortality and migration)Cohort component projection model
Calibration
Epi and behavioural parameters(e.g. % in risk groups, amount of sex,
probability of transmission, probability a condom used, etc)
Epidemiological, behavioural,
intervention model
Interventions (IEC, VCT, STI, PMTCT, ART)
Detailed output including:No. infectedNo. new infectionsNo. AIDS deaths, etc
Features of the ASSA lite model
Heterosexual behavioural cohort component projection model (individual ages/years)
Population divided by risk by: Age (young, adult, old) ‘Behaviour’ (PRO, STD, RSK, NOT) ‘Previous socio-economic disadvantage’ (racial groups) Geographic region (province)
Sex activity Risk group of partner, probability of transmission, number
of new partners p.a., number of contacts per partner, condom usage,
No sex between racial groups or provinces
Diagram 1: A schematic diagram of the ASSA600 Aids Model
Adu
lt (1
4 -
59)
Old
(60+
)
HIV- Young HIV+ Young
NOT RSK STD PRO
Increasing sexual mobility
Increasing risk of HIV infection
HIV- Old HIV+ Old
Dea
ths
Normal Deaths AIDS Deaths
Imported HIV
Migrants (0-59)
Migrants (Aged 60+)
HIV- Births HIV+ Births
You
ng (0
-
13)
Modelling prevention and treatment
Five interventions: Social marketing, information and
education campaigns (IEC) Improved treatment for sexually
transmitted diseases (STDs) Voluntary counselling and testing (VCT) Prevention of mother-to-child
transmission (PMTCT) Antiretroviral treatment (ART)
The fitting process - calibration
Set as many of the parameters/assumptions from independent estimates (% STD, probability of transmission, condom usage, age of (male) partners, the median term to survival of adults and children, impact of HIV on fertility and bias in ANC data, all non-HIV demographic assumptions)
Set some other assumptions (which are not particularly important) by reasonable guesses (e.g. relative fertility, and risk groups of migrants)
The remaining assumptions are set in order to produce known data of the prevalence or impact of the epidemic such as the antenatal prevalence and the mortality figures - calibration (e.g. size of the RSK group, the mixing of risk groups, sex activity by age, no. of partners, number of contacts per partner)
Calibration targets
Prevalence levels Antenatal – overall prevalence Antenatal – prevalence by age over time Ratio of antenatal to national by age HSRC prevalence by sex and age
Deaths Population or vital registration – overall by sex, age
and over time Cause of Death – proportion AIDS in adults by sex
and age Cause of Death – proportion AIDS in children by age Cause of Death – ratio of male to female by age over
time
Calibration targets(cont’d)
Census Numbers by sex and age nationally and provincially Mortality rates by age and sex
Orphanhood CEB/CS Deaths in household
Other Numbers on treatment (private and public)
Antenatal prevalence: South Africa
Confidence intervals prior to 1998 were incorrectly calculated – should be wider
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%1
99
0
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
20
08
20
10
Pe
rce
nta
ge
Model
anc prevalence
adjusted for bias
Number of deaths - men
0
5000
10000
15000
20000
25000
30000
35000
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85+
Proj2002
1996
1997
1998
1999
2000
2001
2002
Number of deaths - women
0
5000
10000
15000
20000
25000
30000
35000
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85+
Proj2002
1996
1997
1998
1999
2000
2001
2002
Uncertainty
Demography (Base population, Fertility, Mortality & Migration)
Epidemiological assumptions (% in risk groups, mixing of the risk groups, probabilities of transmission, infectivity and infectiousness by stage, etc)
Interventions (in particular treatment) Roll-out Effectiveness
Behaviour Future developments (e.g. vaccine)
Selected results
Comparison with HSRC05: South Africa (Prevalence: males and females)
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
2-14
15-1
9
20-2
4
25-2
9
30-3
4
35-3
9
40-4
4
45-4
9
50-5
4
55-5
9
60+
ASSA2003
HSRC05
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
2-1
4
15
-19
20
-24
25
-29
30
-34
35
-39
40
-44
45
-49
50
-54
55
-59
60
+ASSA2003
HSRC05
Prevalence: adults 20-64: South Africa
0%
5%
10%
15%
20%
25%
30%
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
EasternCapeFree State
Gauteng
KwaZulu-NatalLimpopo
Mpumalanga
NorthernCapeNorth West
WesternCapeSouth Africa
Numbers infected by province: South Africa
0.00
1.00
2.00
3.00
4.00
5.00
6.00
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
Mil
lio
ns
Western Cape
North West
Northern Cape
Mpumalanga
Limpopo
KwaZulu-Natal
Gauteng
Free State
Eastern Cape
Numbers on HAART by province: South Africa
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,0002
00
0
20
02
20
04
20
06
20
08
20
10
20
12
20
14
Western Cape
North West
Northern Cape
Mpumalanga
Limpopo
KwaZulu-Natal
Gauteng
Free State
Eastern Cape
Prevalence 15-49 by sub-district: Botswana
0%
5%
10%
15%
20%
25%
30%
35%
40%
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
Barolong Bobonong C.Kgalagadi.G.R Central-Boteti Chobe Francistown
Gaborone Ghanzi Jwaneng Kgalagadi-North Kgalagadi-South Kgatleng
Kweneng-East Kweneng-West Lobatse Mahalapye Ngamiland-Delta Ngamiland-East
Ngamiland-West Ngwaketse-West North-East Orapa Selebi-Phikwe Serowe-Palapye
South-East Southern Sowa-Pan Tutme Sum NATIONAL
Numbers infected by stage by year: Botswana
0
50 000
100 000
150 000
200 000
250 000
300 000
350 000
400 00019
80
1984
1988
1992
1996
2000
2004
2008
2012
2016
2020
AIDS-off ART
ART
AIDS-pre ART
Pre-AIDS
Numbers of deaths by year: Botswana
0
5 000
10 000
15 000
20 000
25 000
30 000
35 000
1981
1984
1987
1990
1993
1996
1999
2002
2005
2008
2011
2014
2017
2020
AIDS
Non-AIDS
Future developments
Circumcision Vaccine Age-specific interventions Pregnancy and transmission? Risk group migration? Better demographic estimation Uncertainty Education? Household impact? Fitting to other (SADC) countries