a populationbased formative study using a discrete choice experiment Arianna Zanolini American Institutes for Research and Centre for Infectious Disease Research in Zambia Joint work with Jenala Chipungu Samuel ID: 547164
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Acceptability and preferences for HIV self-testing in Zambia: a population-based formative study using a discrete choice experiment
Arianna ZanoliniAmerican Institutes for Research and Centre for Infectious Disease Research in ZambiaJoint work with Jenala Chipungu, Samuel Bosomprah, Charles Holmes, Mazuba Mafwenko, Michael Vinikoor, Harsha ThirumurthySlide2
BackgroundIn Zambia,
only 37% of men and 46% of women tested in the past 12 months. Similar rates in other countries in SSA.HIV self-testing (HIVST) is gaining consideration in many countries in SSARecent research promising results and high acceptability of HIVSTMore evidence is needed on optimal delivery models for HIVST
In late 2014, Zambia’s Ministry of Health requested formative local research around acceptability and preferences for HIVSTSlide3
MethodsWe conducted a mixed methods study in Zambia’s most populated province to assess preferences for HIVST
Quantitative part of the study Structured questionnaires were administered to a representative sample of households in Lusaka ProvinceTwo-step sampling procedure was chosen to include urban and peri-urban districtsWe selected with probability proportional to size 17 CSA, and in each CSA targeted approximately 100 households randomly. In each household selected, we randomly chose one household member from the household roster.Questionnaire included assessment around acceptability, preferences, understanding of instructions, linkage to careRespondents received basic explanation of what Self-testing isSlide4
Discrete choice experiment A section of the questionnaire included a discrete choice experiment (DCE) to understand preferences for various ways of delivering HIV
self-testsDCE: series of questions where we ask participants to choose between modelsDCEs can help us eliciting preferences when we can’t observe the demand curve from real-life choicesBased on revealed preferences: when we choose A over B we “reveal” that we prefer A to BSlide5
DCE- An example question
OPD Pharmacy
Chemist
VCT/ART
No Counseling
Counseling Counseling 10 Kwacha 25 Kwacha Free A B C-regularSlide6
ResultsSlide7
Participant characteristics
All (N=1617)
Female
(N=970)
Male
(N=647)
Age (mean)
28.9
28.5
29.5
Employment
status
Employed for wages
23%
14%
37%Self-employed with business or farm28%28%29%Unemployed/not looking for work49%59%33%
Income level
<70US$/month
21%
28%
14%
70-15 US$/month
28%
33%
23%
150-600US$/month
44%
34%
55%
>600US$/month
7%
5%
8%
Education
No secondary school
20%
24%
16%
Jr Secondary school
32%
31%
29%
Sr. Secondary
or higher
47%
44%
55%
Rural setting
23%
20%
27%
Positive HIV Status, self-reported
12%
12%
11%
Perceived high
or moderate HIV risk
41%
42%
41%Slide8
HIV testing history of participantsSlide9
Acceptability of HIV self-testingSlide10
Acceptability-concerns
Any concerns at all with HIV Self-test?35%
If yes, which one?
Suicide
8%
Lack of post-counseling
and mental health
6%
Lack of linkage to
care
4%
Validity of the test
4%
Lack of behavioral
post-counseling advice
4%Partners’ violence3%Forcing people to test2%Cost1%Other3%How severe is this concern?No concerns65%Relatively minor8%Important but can be addressed25%Very severe. No self-testing in Zambia2%Slide11
DCE main results
Coefficient represent a marginal change in utility of, for example, moving from a scenario with no counseling to an equal scenario with counseling, everything else constant. Slide12
Willingness to pay for HIVST
Marginal willingness to pay= -1.65/-0.07 = 24 Kwacha =
3 USD
5 USDSlide13
ConclusionsHIV Self-testing highly acceptable in Lusaka Province, Zambia, across different demographics
Promising for non-testers, 75% of whom report willingness to test and who reveal stronger preferences for self-testing than testersStrong, positive preference for counseling. In our simple model, we estimated a willingness to pay of 3US$ for regular testers and 5 US$ for non-regular testers. Ideal to complement these data from other WTP-based on real buying choices to estimate demand