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HIV research in the era of ART: changing priorities in Tanzania. Basia Zaba SOAS 3 rd March 2011. Overview. Introduction – data sources & measurement strategies Monitoring the epidemic at a national level Evaluating prevention and treatment responses

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Hiv research in the era of art changing priorities in tanzania

HIV research in the era of ART: changing priorities in Tanzania

Basia Zaba

SOAS

3rd March 2011


Overview
Overview Tanzania

  • Introduction – data sources & measurement strategies

    • Monitoring the epidemic at a national level

    • Evaluating prevention and treatment responses

    • What difference does ART availability make?

  • Results from observational studies of HIV in Tanzania

    • Ante-natal Clinic Surveillance: historical trends

    • Nationally representative X-section sample surveys

    • Clinical cohorts for studying ART patients

    • Community-based cohort studies

    • Combining data from different sources

  • Tanzania compared to other African countries


Monitoring the epidemic at a national level
Monitoring the epidemic Tanzaniaat a national level

  • Need for a representative population sample

    • men and women, all ages

    • rural and urban

    • not just sick people

  • Convenience and cost

    • accessibility of health facilities

    • build on routine record keeping

    • locate in interested institution

Nationally representative household survey with HIV testing (e.g. DHS)

Ante-Natal clinic surveillance


Evaluating prevention and treatment response
Evaluating prevention and treatment response Tanzania

  • Prevention: need individual follow-up data to measure

    • rate of new infections

    • prior behavioural risks

    • influence of campaigns

  • Treatment questions:

    • do people know they are infected?

    • what proportion accesses treatment?

    • how do those on treatment fare?

Community cohort studies (e.g. Kisesa)

Household surveys e.g. DHS

Referral studies

Clinical cohort studies


Hiv observational study designs
HIV observational study designs Tanzania

simple & cheap complex & costly

Cross-sectional studies may be repeated several times to get overall trends, they are only called longitudinal if individuals are linked from round to round


What difference does art availability make
What difference does ART availability make? Tanzania

  • Greater willingness to learn HIV status

    • HIV is no longer a death sentence

    • stigma is still a big issue

  • Ethical obligation of researchers to encourage people to learn status, and if necessary access treatment

    • study design allows for diagnosis as well as measurement

    • protocols must include “realistic” referral procedures

  • Facility data analysis has to account for possible biases due to treatment seeking or test avoidance

  • Need to link individual’s clinic and community records to study certain impacts – e.g. treatment drop out, partner infections


Ante natal clinic surveillance
Ante-natal clinic surveillance Tanzania

  • Testing of pregnant women coming to ANC is still main source of national estimates of HIV trends world wide

    • Before ~2005 based on unlinked anonymous tests of residue of blood sample used for syphilis testing (no feedback)

    • Since ~2005, usually based on results of PMTCT testing (mothers get test feedback)

  • Representative samples of Tanzanian clinics began to be selected after 2000, prior trend estimates must take account of changing clinic selection

  • Clinic samples may be biased if women who think they are infected seek out clinics that do PMTCT testing



Deriving prevalence trends when reporting clinics vary over time
Deriving prevalence trends when reporting clinics vary over time

Method developed by UNAIDS

  • Only use data from clinics that report more than once

  • Do a separate trend analysis for urban and rural clinics, then weight results by size of urban and rural populations

  • Use median clinic prevalence rather than mean to give less weight to extremes


Fitting unaids model to median prevalence in anc clinics
Fitting UNAIDS model to median prevalence in ANC clinics time

Peak in early 90’s

Projected to level out at under 10%


Demographic health surveys
Demographic & Health Surveys time

  • DHS: nationally representative sample surveys with an international standard questionnaire

  • May include additional modules on special topics such as malaria prevention

  • Recent studies have added collection of bio-markers, including anonymous HIV tests

  • Tanzania has done more DHS surveys than any other country, including two with HIV testing (2004, 2007)



Adjusting unaids model to observed dhs prevalence
Adjusting UNAIDS model to observed DHS prevalence time

Projected to level out at under 9%


Putting together results of two dhs surveys
Putting together results of two DHS surveys time

Most regions experienced a significant prevalence decline between 2004-07


The unaids prevalence trend model needs re adjusting
The UNAIDS prevalence trend model needs re-adjusting time

Decline has been much steeper than UNAIDS prediction

2010


Treatment and care interpreting data from different sources
Treatment and care: interpreting data from different sources time

  • Community-based data on HIV diagnostic testing (but no direct questions about results or treatment)

  • Referral data: what do HIV+ people do after learning they are infected

  • Care and Treatment Clinic (CTC) follow-up data: what happens to people referred to clinics for care (monitoring) and treatment


whole community time

Attend VCT

HIV negative

HIV positive – no ART need

Referred ART

HIV positive - needs ART

Attend ART

eligible ART

start ART

Access to ART

clinic data only tell us this part of the story


Trend in knowledge of hiv status
Trend in knowledge of HIV status, % time

Know their HIV status


Estimated of hiv infected in care art or pre treatment monitoring by region 2010
Estimated % of HIV infected in care (ART or time pre-treatment monitoring), by region, 2010.

  • Varies by region from 14% to 55% of HIV infected in care

  • Overall estimate: 255,000 to 367,000 HIV +ve in care in Tanzania = 21%-30% of those infected (aim is 100%)


Access to hiv preventative treatment for mothers and newborn children in magu district 2009
Access to HIV preventative treatment for mothers and newborn children in Magu district, 2009

Of the 168 HIV-positive women who had a live birth:

  • 110 (66%) did not receive any PMTCT drug treatment at all

  • 2 (1%) reported obtaining drugs only for the child;

  • 15 (9%) only received drugs for herself;

  • 41 (24%) received full PMTCT drug treatment for self and her child


Hiv care treatment clinic ctc record follow up
HIV Care & Treatment Clinic (CTC) record follow-up children in Magu district, 2009

  • Studies done as part of monitoring and evaluation of national Anti Retroviral Treatment (ART) programme

  • In Tanzania, 666 out of 909 CTC facilities reported current and/or new numbers of patients receiving care

  • 101 facilities have computerised patient record databases, can even trace patients moving between facilities (unique patient IDs)

  • Can use the computerised data to construct a clinic cohort to study patient welfare and clinic attendance



Death rates following art initiation
Death rates following ART initiation children in Magu district, 2009

high death rates at start of treatment due to late initiation and drug toxicity


Median cd4 count following art
Median CD4 count following ART children in Magu district, 2009

CD4 counts improve due to drugs and because of deaths of those with very low initial counts

threshold for treatment initiation

most people initiate treatment too late


Hiv community cohort studies
HIV community cohort studies children in Magu district, 2009

  • Whole communities are followed over long periods of time, with frequent (at least yearly) household censuses (demographic surveillance)

  • Adults in the communities have HIV status measured at regular intervals (at least once every 3 years) and HIV status is individually linked to demographic data

  • Also do periodic surveys of known HIV risk factors (e.g. sexual partnerships, condom use, blood transfusions) and possible consequences (e.g. infant mortality) and people’s knowledge and attitudes


Kisesa cohort study components
Kisesa children in Magu district, 2009 cohort study components


Hiv status life histories collected in cohort study
HIV status life-histories collected in cohort study children in Magu district, 2009

new infection

at risk of infection

HIV+ death

at risk of death


Describing incidence rate of new infections
Describing incidence (rate of new infections) children in Magu district, 2009

  • Crude measures (and trends):

  • Specific patterns – incidence classified by:

    • age and sex

    • place of residence

    • marital status

  • Comparing different populations: life time risk


Incidence trends by age sex and residence
Incidence trends by age, sex and residence children in Magu district, 2009


Incidence age pattern kisesa 1994 2004
Incidence age pattern, Kisesa 1994-2004 children in Magu district, 2009

Mode 30 yrs

Peak 1.5 %

Mode 27 yrs

Peak 1.2 %


Incidence level measure life time risk cumulated risk to age 65
Incidence LEVEL measure: life time risk = cumulated risk to age 65

Kisesa, 1994-2004

Life time risk of HIV infection = 40%

Kisesa, 1994-2004

Average HIV prevalence = 9.3%


Mortality and survival after hiv infection
Mortality and survival after HIV infection age 65

  • Most common way of comparing severity of HIV mortality across sites is to look at how long infected people survive without treatment

  • Not ethical to try to measure this in the era of ART treatment, but community cohort studies like Kisesa have survival data collected over many years before treatment was available

  • In Kisesa as in other sites we found that people infected at older ages have much worse survival patterns – this is not just because older people have higher mortality

  • We can also study age-specific mortality patterns and compare infected and uninfected, and mortality among HIV infected persons before and after ART became available



Hiv mortality and art need
HIV mortality and ART need 1994-2005

  • In CTC clinics, individual ART need is assessed using CD4 count and clinical staging of HIV disease

  • For the population as a whole, we can define the need for ART in an age group as the proportion who would die within the next 3 years if they didn’t get treatment

  • Cohort data on age-specific HIV mortality in the pre-treatment era allow us to estimate proportions of HIV infected persons by age who would be expected to die within 3 years – this is the base-year treatment need for an ART program at start-up

  • We can also determine the build up of treatment need in a successful program, with suitable assumptions about mortality of those on treatment



Initial art need in 2005 kisesa
Initial ART need in 2005, Kisesa 1994-2005

Total need, both sexes: 123

Total on treatment: 27


Cumulated art need by 2008 kisesa
Cumulated ART need by 2008, Kisesa 1994-2005

Total need, both sexes: 193

Total on treatment: 207


Tanzania compared to other african countries
Tanzania compared to other African countries 1994-2005

(data from other cohort studies in the ALPHA network)


Results incidence level pattern comparison across sites
Results: Incidence level & pattern comparison across sites 1994-2005

* 40 x peak incidence for Hlabisa

Males have a higher life time risk of HIV infection ...

… an older age distribution of risk …

… peak rates are broadly similar …

… pattern is slightly less concentrated


Graphical results smoothed age specific incidence rates by sex and study site
Graphical results: smoothed age-specific incidence rates by sex and study site

To compare incidence patterns in the South African cohort with the others demands some re-scaling


Non-African studies sex and study site


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