The World Bank Global HIV/AIDS Program (GHAP) Definitions and Measures of Multiple and Concurrent Partnerships Masauso Nzima UNAIDS RST-ESA Johannesburg

The World Bank Global HIV/AIDS Program (GHAP)


Definitions and Measures of Multiple and Concurrent Partnerships

Masauso NzimaUNAIDS RST-ESA

JohannesburgMay 2009

UNAIDS RST-ESA Johannesburg



Presentation Outline• Changes that we want to see with MCP efforts• Indicators to measure the changes• Measurement methods• Where to next? Future developments



Some Background

• Multiple and concurrent sexual partnerships facilitate rapid HIV spread (particularly in Southern Africa);

• Discussions and research on specific role in the spread of HIV impeded by lack of clear definition and indicators of concurrency;

• Hence focus of the 20-21 April meeting in Nairobi



Concurrency – What is it?

1

2

3

4

5

1

2

3

4

5


time

Same contact rate (5 partners/yr), but sequence of start and end dates is different

Serially monogamous partnerships

Concurrent partnerships


Definition of concurrency

Defined as:

“overlapping sexual partnerships where sexual intercourse with one partner occurs between two acts of intercourse with another partner”

REFER TO ILLUSTRATION



Changes we want to measure


• We need more MCP programmes and so we should see changes in the HIV community’s priorities and strategies.

• Changing sexual practices in the context of MCP means that the sexual networks need to be broken, therefore we should see changes in individual behaviours towards fewer multiple and concurrent partnerships (i.e. reduction in prevalence of concurrency), or increased harm reduction practices if concurrency is practiced.

• Decreasing the acceptability of MCP in communities and families – changes in social norms.

• Changes in how societies, communities, families and couples act towards each other



More MCP programmes, skills to deliver and funding for them

Improved relationships

Changed social norms and society ‘rules and regulations’ about

relationships

Fewer MCPs – lower prevalence of multiple partners, and lower

prevalence of concurrent parnters

Fewer new HIV infections

More people reached with MCP programmes

INPUTS

OUTPUTSOUTCOMES

OUTCOMES

IMPACTS

More harm reduction during MCP

OUTCOMES


Indicators with which to measure the changes: INPUTS


• percent of HIV funding spent on prevention (all prevention efforts, as opposed to treatment, care, impact mitigation and response management) [NASA]

• percent of HIV prevention funding spent on behaviour and social change communication programmes [NASA]

• number of policies and strategies relating to HIV that specifically address MCP as a key focus area for the HIV prevention response in the country [National composite policy index section of the UNGASS reporting processes]

• percent of HIV implementers trained to implement programmes addressing MCP [Programme monitoring data]

• percent of existing prevention intervention guidelines (VCT, PMTCT, STI, life skills, workplace programmes) that have incorporated MCP [Programme monitoring data]

• number of research activities that address MCP programmes [Programme monitoring data]



• number of mass media spots that address MCP• percent of members of cabinet that have addressed MCP in public

speeches of national interest • number of people reached with mass media activities focusing on MCP • percent of community-based organisations with programmes that

address MCP behaviour for couples in relationships• number and percent of community leaders trained in MCP• number and percent of communities in which inter-personal

communication (IPC) programmes relating to MCP (including family unit strengthening programmes) have been implemented

• number and percent of people who have been reached with behaviour change communication programmes relating to MCP through interpersonal communications (disaggregated by sex and age group)

Indicators with which to measure the changes: OUTPUTS



Changes in individual knowledge: • percent of men and women who can correctly identify the increased risks

associated with MCP• percent of men and women who can correctly identify the behavioral changes that

would minimise risk associated with MCP Changes in individual attitudes• percentage of men and women who think that MCP is acceptable• percentage of men and women who think that men/women who are not married

and are having sex should have sex with only one partner• percentage of men and women who think that men/women should only have sex

with their wives/husbands• percentage of men and women who intend to have multiple partners• percentage of men and women who discuss MCP with others

Indicators with which to measure the changes: OUTCOMES AT INDIVIDUAL & COUPLE LEVEL



Changes in individual behaviour:• percent of men and women having multiple partnerships - PREVALENCE OF

MULTIPLE PARTNERSHIPS• percent of men and women whose partners have multiple partnerships• percent of men and women having concurrent partnerships – PREVALENCE OF

CONCURRENT PARTNERSHIPS• percent of men and women whose partners have concurrent partnerships • percent of young women 15 – 19 who had a first sexual partner who was 5 years or more

older, and 10 years or more older• percent of men and women with multiple partners who have reported consistently using a

condom during last sex with non-marital, non-cohabiting partner




Changes in how couples relate to each other and in relationships• percent of men and women in steady relationships who report that they have discussed

their relationship values and agreed on safe sexual practices such as mutual monogamy or consistent condom use

• percent of men and women who have a spouse/partner who works away from home and is not co-resident for more than 6 months of the year

• percent of young men and women who are married




• percent of men and women who believe that a woman is justified in insisting on condom use if she knows her partner has another sexual partner

• percentage of men and women who believe a woman is justified in refusing to have sex with her husband/partner when she knows that he has had sex with another woman (or woman other than his wives, in the case of polygamy)

• percentage of men and women who believe it is acceptable in the community for a man to have multiple sexual partners

• percentage of men and women who believe it is acceptable in the community for a woman to have multiple sexual partners

• percentage of men and women who believe that MCP is common in the community

Indicators with which to measure the changes: OUTCOMES AT COMMUNITY & SOCIETY LEVEL



• Reduced HIV incidence

Indicators with which to measure the changes: IMPACTS


Main uncertainty about indicators for concurrency, is how to define the prevalence of concurrency

THEREFORE, the rest of the presentation will focus on this aspect of MCP measurement



Measurement of the Prevalence of Concurrency

Two main indicators agreed on at meeting in Nairobi:

1. Primary indicator – Point prevalence of concurrency

“The proportion of adults aged 15 to 49 reporting more than one on-going sexual partnerships at an instant in time”

• This is to be used as the main indicator of concurrent partnerships in a population;

• It also best distinguishes between concurrency and rapid serial monogamy



Measurement of the Prevalence of Concurrency2. Secondary indicator - cumulative prevalence of concurrency:

“The proportion of adults aged 15 to 49 reporting overlapping partnerships over time (typically 12 months)”

• It measures the intensity of exposure• Focuses on and can determine the duration of overlap• Provide data about the frequency of sex with each partner • Does not measure the rate of partner change (partner change rates

that resemble ABABABABAB is epidemiologically more risky than partner change that resemble AAAABBBBBBBB (maybe due to migration and temporary separation))



To measure these two indicators, need to ask 3 questions (about each partner)

When was the first time you had sex with this person? (cumulative prevalence and intensity)

When was the last time you had sex with this person? (cumulative prevalence and intensity)

Are you still having sex with this person? (momentary degree distribution, which is the point prevalence)



Measurement Methods



Measurement Methods

Now that we know what to measure, the next question is, how do we measure it?

• Proxy measure• Direct question method• Date method• Coital diaries• Partner’s concurrency




Using the Date Method - ‘Typical’ Sexual Behaviour QuestionnaireHave you ever had sex?General behaviour questions:

Age at first sex Marriage

Counts of partners Lifetime, past year, past month New partners

‘Name Generator’ (Morris 2004) Last X partners in Y duration Stratified by partner type?

‘Name Interpreters’ (Questions about each partner) Dates/duration of first and last sex Partnership type (Marriage, steady, casual, one-time etc.) Condom usage & coital frequency Partner characteristics: age, location, sexual behaviour (other partners) Partnership characteristics: type (spouse, casual, one-time, etc.),

transactional, coerced, alcohol/drug use

21



Identifying Concurrent Partnerships (1)• Proportion of individuals where start and end dates of previous

X partners overlap [in last Y duration] Name generator + Date (MM/YYYY) of first and last sex

with each partner Name generator + duration since last sex (in

days/weeks/months) + duration since partnership began (weeks/months/years)

Gives detailed network data Sensitive to recall bias for dates/durations

22



Identifying Concurrent Partnerships (2)Number of current ongoing partnerships > 1

Single question: How many sexual partnerships do you consider yourself to currently be in?

Name generator + “Is this partnership ongoing?” or “Do you plan to have sex with this person again”

Measures presence of stable partnerships Misses once-off & short partnerships (is this

“concurrency”?) Identifies momentary degree distribution, less indicative of

individual risk behaviour? Reduces gender differences in # of partners?

23



Identifying Concurrent Partnerships (3)Proportion ever had another sex partner during current/most recent

partnership [in the last Y duration] Are you currently in a relationship? + Have you had sex

with any other person since you began this relationship? Name generator + “During this relationship did you

have sex with any other person” or “During the past year within this relationship did you have sex with any other person”

More exposure to “concurrency” in longer relationships Does not distinguish once-off encounters from long-term

overlapping partnerships

24



Identifying Concurrent Partnerships (4)• Proportion reporting > 1 partner in last month

How many people have you had sex with in the past month?

Name generator + “How many times have you had sex with this person in past month?”

Does not guarantee strict concurrency Alternate estimate of degree distribution Compared to (2) more likely to include short or once-off

partnerships

25


Novel interview methods↑Privacy & confidentiality

Self-administered questionnaire (SAQ) Feels more confidential

Issues: Literacy, skip patterns, patience! Assisted self-completion questionnaire (ASCQ)

Interviewer only reads questions/answers but don’t record them Computerised

Audio/Computer assisted self interviewing (A/CASI) Palm top assisted self interviewing (PASI, PDA)

Confidentiality, reduce entry errors Issues: new technologies,

Non computerised methods Tape recorder ICVI PBS

No gold standard



Illustration

Clipboard with enclosed PDA

ICVI voting box PBS polling box

Self reported coital diaries



Importance of Interviewing Technique: Swaziland

1 2 3

Male 42.2 32.9 11.8

Female 36.3 58.8 2.9

Percent reporting 1, 2, 3 partners in the last 3 months – 2006 (Ngudzeni ADP)

Sources: James, V. and R. Matikanya (2006). Protective Factors: A Case Study for Ngudzeni ADP (Swaziland), World Vision Australia/Swaziland.; Central Statistical Office [Swaziland] and ORC Macro (Unpublished). Swaziland Demographic and Health Survey, 2006-2007. Calverton, Maryland, Central Statistical Office and ORC Macro.

2006-07 Swaziland DHS (nationally)

• Females reporting more than one partner in the last 12 months: 2.3%


Some breakthroughs at Nairobi Meeting• Concurrency reporting, in some cases,

increases threefold, when using different data collection methods (voting boxes vs FTFIs);

• HIV is higher among migrant populations, as well as those that report having concurrent partners (or whose partners report having concurrent partners);

• A study in northern Tanzania (Kisesa) is showing some behaviour change;



Where to next?• A community randomised trial (‘break the

network’ BCC interventions vs. standard HIV messaging) planned for 2010

• PSI and others are currently planning evaluations on MCP (Botswana & Mozambique); Namibia too



Additional areas of research• Further research into methods of measuring concurrency and

sexual behavior, relationship between concurrency and HIV transmission and social norms and concurrent partnerships;

• The need to continue measuring these behavioral aspects through population-based surveys*

• These are also very useful to collect self-reported behavior on a large enough scale;

• Need for more in-depth data gathering and that these should be triangulated with each other and with survey data



end


Documents

The World Bank Global HIV/AIDS Program (GHAP) Definitions and Measures of Multiple and Concurrent Partnerships Masauso Nzima UNAIDS RST-ESA Johannesburg