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Modelling HIV/AIDS in Southern Africa Centre for Actuarial Research (CARe) A Research Unit of the University of Cape Town.

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Presentation on theme: "Modelling HIV/AIDS in Southern Africa Centre for Actuarial Research (CARe) A Research Unit of the University of Cape Town."— Presentation transcript:

1 Modelling HIV/AIDS in Southern Africa Centre for Actuarial Research (CARe) A Research Unit of the University of Cape Town

2 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)www.assa.org.za/aidsmodel.asp Orphans, select populations, other countries

3 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. infected  No. new infections  No. AIDS deaths, etc

4 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

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6 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)

7 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)

8 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

9 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)

10 Antenatal prevalence: South Africa Confidence intervals prior to 1998 were incorrectly calculated – should be wider

11 Number of deaths - men

12 Number of deaths - women

13 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)

14 Selected results

15 Comparison with HSRC05: South Africa (Prevalence: males and females)

16 Prevalence: adults 20-64: South Africa

17 Numbers infected by province: South Africa

18 Numbers on HAART by province: South Africa

19 Prevalence by sub-district: Botswana

20 Numbers infected by stage by year: Botswana

21 Numbers of deaths by year: Botswana

22 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


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