WEBVTT

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<v ->People join.</v>

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We can just let them in.

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So I just wanna say good afternoon.

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My name is Christine Simon.

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I am an associate research scientist

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in the Department of Social and Behavioral Sciences,

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and at the Center for Methods in Implementation

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and Prevention Science here at Yale School of Public Health.

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I am delighted to introduce our Ready Hub

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webinar presentation and presenter, Dr. LaRon Nelson.

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But before I do that, I just wanted give you

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a little bit more information about our hub.

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Leveraging the expertise of Yale Center for Methods

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in Implementation and Prevention Science

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and Center for Interdisciplinary Research on AIDS,

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Ready, R3EDI, the Rigorous, Rapid and Relevant

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Evidence Adaptation and Implementation

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to Ending the HIV Epidemic.

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Implementation Science Hub provides technical assistance

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to more than 10 Ending the HIV Epidemic projects

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from around the country.

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Ready, we have so many acronyms. (chuckles)

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Ready does this in collaboration

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with the Implementation Science Coordination,

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Consultation and Collaboration Initiative,

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also called ISC3I,

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creating opportunities to translate local knowledge

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into generalizable knowledge whenever possible.

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Ready offers comprehensive expertise

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in implementation science methods, frameworks

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and outcomes in HIV AIDS research.

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I just also wanna let everyone know that this event

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is co-sponsored by the Yale Center for Methods

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in Implementation and Prevention Science,

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also known as CMIPS, and Yale Center

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for Interdisciplinary Research on AIDS,

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CIRA and ISC3I.

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So if you would like to know more

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about future Ready Hub webinar events,

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please notify Dr. Debbie Humphries in the chat,

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and she'll make sure that you're added to our email list.

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So today's presentation is titled "No Black Men Left Behind:

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Conundrums and Considerations for Designing

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a Multi-Level Hybrid HIV Implementation/Efficacy Trial."

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And it is being presented by Dr. LaRon Nelson,

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who is the Associate Dean for Global Affairs

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and Planetary Health and Independence Foundation

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Associate Professor of Nursing.

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I just wanted do a quick background on Dr. Nelson.

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He has so many accomplishments,

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but just to highlight a few.

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Dr. Nelson's domestic and international research

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investigates the implementation and effectiveness

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of multi-level intervention strategies

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to reduce race and sexuality-based disparities

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in HIV outcomes.

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He's recognized as the world's leading authority

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on the application of self-determination theory

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for HIV prevention and care.

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His research also involves identifying interventions

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to address intersectional stigma at the organizational level

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and treating the traumatic effects of intersectional stigma

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that manifests at the individual level.

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His work in research and implementation science

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spans multiple countries.

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He co-founded the Central and West Africa

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Implementation Science Alliance,

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a collaboration of implementation scientists

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in implementing agencies from Cameroon, Congo,

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Ghana and Nigeria, aimed to improve HIV-related outcomes

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among adolescents in the region.

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He is also leading implementation science efforts

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to reduce racial disparities in HIV incidence,

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treatments and viral suppression

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among African, Caribbean and black communities in Canada.

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His work in the US focuses on the, excuse me,

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his work in the US focuses on the use of multilevel

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social, structural, behavioral and clinical interventions

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to reduce HIV infections among black MSM.

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He's also currently part of a multiple EEG supplement

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addressing rapid PrEP and HIV prevention.

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It is with great pleasure that I turn this presentation

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over to Dr. Nelson.

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Thank you so much for doing this.

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<v ->Thank you, Chris, for that introduction.</v>

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Welcome, everyone.

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Thank you for making time with this presentation.

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What I'm gonna do today is perhaps a little bit different

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because I won't be presenting on outcomes of research,

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but this is essentially a presentation

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and discussion about research and progress.

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Slides are loading in progress.

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Let's see if we can get 'em up here.

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And so this is the title,

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"No Black Man Left Behind."

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Really thinking about what were some of the conundrums

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and things we should be thinking about for designing

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a multi-level hybrid HIV implementation/efficacy trial.

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And hopefully some of what we're learning,

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what we've learned, and what we are learning can help

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those of you out there who are thinking

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about similar types of work and the opportunities it offers,

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but also the challenges that are involved.

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The work today I'll talk about was done in collaboration

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with a lot of people, but principally with Chris Beyrer

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who's at Duke University.

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He's the director of Duke Institute for Global Health,

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and Bob Remien.

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They're not here today presenting today,

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but because this webinar we'll talk exclusively

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about HPTN 096, it's important for you to know

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that three of us are leading that together.

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So right now there's still a marked racial disparity

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in the coverage of PrEP.

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If we look at the most recent data from the CDC,

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this is what the slide is showing.

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And this is from 2019.

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Overall, the nation is still at about a quarter

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of people who are eligible for PrEP

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have been prescribed PrEP.

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So that's about halfway towards the EHE goal

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of getting to 50% by 2030.

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However, that 23% really is driven principally

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by the high degree of PrEP prescription among whites.

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So that is 63%.

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If you look at Hispanic and Latino, is 14%,

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and blacks including African-Americans

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are not even 1/10.

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And so the large number among whites

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mask the disparity that exists,

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black folks who are eligible for PrEP

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are not being prescribed PrEP and thus black not using PrEP.

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We see similar, although not as stark source of patterns

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with viral suppression, there are still racial gaps.

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You see overall the rate is about,

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the proportion is about 66% of people with HIV

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being virally suppressed in 2019.

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But if you look across three racial groups,

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just social groups, mind you,

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that blacks and African-Americans represent 61%.

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Only 61% of those with HIV are virally suppressed

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compared to Hispanics and Latino, which is slightly higher

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and then highest among people who are white.

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And then the HV epidemic itself is also,

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there are disparities geographically.

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We know that the epidemic really is concentrated

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in southern US states.

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Ton of social, structural and behavioral reasons

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for that also, but what you see on the map on the left

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is the HIV prevalence.

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And you can see that it really does pool

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along the South Atlantic seaboard,

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even Atlantic Coast more generally,

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across the Gulf of Mexico states.

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The map on the right shows you a similar pattern.

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These are HIV diagnoses by US county.

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And again, along the southeastern Atlantic coastline

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across the Gulf of Mexico,

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you see that those where we're having the most cases.

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And then if we look more specifically

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at black MSM in the South,

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you find that they are highly overrepresented

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in new HIV cases.

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So what you see on this slide are cases of HIV,

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new diagnoses of HIV among men who have sex with men,

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grouped by region: Northeast, Midwest, South and West.

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So you can see clearly that most of the new diagnoses

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are happening in the South among MSM.

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That accounts for more than all the diagnoses

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in other regions put together is in the South.

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And if you look specifically in the South among MSM,

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black MSM represent the vast majority of the cases

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among MSM in that region.

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And then this is perhaps one of the most important slides

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I'll show you in terms of background,

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is that there have been several innovations,

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biomedical innovations that should have an impact

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on HIV incidence.

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There's some things that are done in HPTN,

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the HIV Prevention Trials Network.

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So in a 052 study, they establish U=U,

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that if a person is virally suppressed and undetectable,

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they cannot transmit the virus.

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There was discovery of the efficacy of oral Truvada for PrEP

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and then the introduction of rapid HIV test cases

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that could be taken at home.

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All very important innovations.

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And what you see that between 2010 and 2019,

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that those innovations, you know,

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we can't say that it was a direct link to it,

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but if you just look at how the graph along that timeline,

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that you see that the HIV incidence among white MSM declined

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over time pretty much corresponding with introduction

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of these new innovations.

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And that's not unusual, that's not unexpected.

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That's the reason why we do,

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scientists do this type of research

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to have an observable impact.

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So you've seen that among white MSM.

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But at the same time,

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that trend among black MSM from 2010 to 2019

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is relatively unchanged.

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Even with the evidence of U=U,

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even with the introduction of Truvada for PrEP,

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even with the introduction of rapid home test kits

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that those, the introduction of those innovations

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into the health system or the healthcare marketplace

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has not seemed to have any impact

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on the the HIV incidence among black MSM

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in that 10-year time period.

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And so there are reasons for that.

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And I think in the HIV prevention world,

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many of the reasons that we've investigated for many years

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have been behavioral reasons

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'cause they must be have more sex than the white MSM,

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or that's probably the principle reason

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that we've investigated and ways to sort of minimize

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people's exposure to HIV through sexual behavior.

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But through a lot of work,

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including some work that's happened at Yale,

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we know that there are other factors

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that are structural factors and social factors.

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I won't even give an examples of them right now,

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but, or maybe I will give an example.

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So even more recently in the US District Court

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out of Tarrant County, Texas, that's Fort Worth,

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there was a recent ruling that employers

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were no longer obligated to provide coverage

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for PrEP as part of their insurance plans.

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And so if they're black men, white men, black women,

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Hispanic women who wanted to take PrEP,

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there will be barriers to taking it

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if their employer didn't cover it, right?

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That's not a behavioral factor.

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That's a structural factor that can impede

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the ability for communities to achieve prevention goals.

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And so that's just one very recent example.

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But there are a number of examples that,

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over time, we've come to understand that

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the situation is much more complex than getting a person

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to do a thing, that the way systems and social norms,

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stigmas confront and constrain people's ability

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to enact the behavioral goals has an impact

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on this epidemic.

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And we contend that this is, more than contend,

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we understand that this is part of what is happening

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with why we can have the development of these types

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of innovations and not have an impact on black MSM

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in terms of what we see with the viral suppression data

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or the incidence data is because there are

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structural factors that are making that

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very difficult to attain.

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So what we decided to do with HPTN 096

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was to develop and test an integrated strategy

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that dealt both with behavioral factors,

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that dealt with social factors,

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and that dealt with structural factors.

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And so we identified interventions that address

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all of those things.

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And we're testing this, well,

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there are four components of that intervention.

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The first is social media influencers.

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So I thought was that we have to tackle

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this at multiple levels.

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We can't just have another study where we enroll a cohort

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of black men and zero in an intervention on them

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and follow them over time.

268
00:14:37.170 --> 00:14:38.520
Because that that essentially

269
00:14:38.520 --> 00:14:41.190
is a behavioral-focused intervention.

270
00:14:41.190 --> 00:14:43.020
They needed something that addressed these issues

271
00:14:43.020 --> 00:14:44.190
at multiple levels.

272
00:14:44.190 --> 00:14:45.690
And so the first component was to use

273
00:14:45.690 --> 00:14:49.500
social media influencers who could really have an impact

274
00:14:49.500 --> 00:14:52.740
on norms, norms around stigma,

275
00:14:52.740 --> 00:14:56.103
norms around HIV prevention and HIV treatment.

276
00:14:57.180 --> 00:15:01.050
A second component to that was a culturally-responsive

277
00:15:01.050 --> 00:15:04.652
intersectional stigma prevention, or CRISP for short.

278
00:15:04.652 --> 00:15:06.600
That is an intervention that is targeted specifically

279
00:15:06.600 --> 00:15:08.223
at healthcare facilities.

280
00:15:09.780 --> 00:15:14.040
Because the experience that black men have

281
00:15:14.040 --> 00:15:16.530
when they're going to facilities can either optimize

282
00:15:16.530 --> 00:15:19.080
their prevention goals or treatment outcomes

283
00:15:19.080 --> 00:15:20.520
or can undermine it.

284
00:15:20.520 --> 00:15:23.490
And so we thought, beyond doing something

285
00:15:23.490 --> 00:15:26.340
that was at the community level,

286
00:15:26.340 --> 00:15:27.840
that it needed to be something that was focused

287
00:15:27.840 --> 00:15:30.660
at transforming healthcare environments,

288
00:15:30.660 --> 00:15:33.030
so intervention focused at the organizational

289
00:15:33.030 --> 00:15:34.383
or institution level.

290
00:15:35.580 --> 00:15:37.020
There's a peer support component

291
00:15:37.020 --> 00:15:39.900
which is a behavioral-focused intervention

292
00:15:39.900 --> 00:15:42.660
that is targeted towards black men,

293
00:15:42.660 --> 00:15:45.123
black MSM specifically in this study,

294
00:15:46.230 --> 00:15:48.750
that's designed to offer them access to peer support

295
00:15:48.750 --> 00:15:53.750
that's not, doesn't require them to have to meet in person,

296
00:15:54.450 --> 00:15:57.843
which is de facto disclosing people's sexual identity,

297
00:15:58.890 --> 00:16:01.380
which may not be acceptable in some of the places

298
00:16:01.380 --> 00:16:02.640
where the study is happening.

299
00:16:02.640 --> 00:16:04.530
And then the last one is the health equity-focused

300
00:16:04.530 --> 00:16:07.140
intervention, which is the structural intervention.

301
00:16:07.140 --> 00:16:12.140
This is a coalition model where people are coming together,

302
00:16:12.810 --> 00:16:15.630
people, organizations are coming together

303
00:16:15.630 --> 00:16:19.350
and finding different ways to cooperate, right?

304
00:16:19.350 --> 00:16:21.720
The system is the design a particular way,

305
00:16:21.720 --> 00:16:24.630
but we're saying the system's not serving black men,

306
00:16:24.630 --> 00:16:27.450
they're not serving black MSM in particular.

307
00:16:27.450 --> 00:16:31.678
And so how might you cooperate, the church,

308
00:16:31.678 --> 00:16:34.440
the employment agency, the immigration office,

309
00:16:34.440 --> 00:16:38.430
the health department, the police department,

310
00:16:38.430 --> 00:16:42.480
the rape trauma center, how might you, the food bank?

311
00:16:42.480 --> 00:16:45.000
Is there a way to restructure how you work together

312
00:16:45.000 --> 00:16:48.150
that's gonna help bridge these gaps that the men

313
00:16:48.150 --> 00:16:51.060
are falling through and it's contributing to the reason

314
00:16:51.060 --> 00:16:54.210
that we're not seeing incidence decrease

315
00:16:54.210 --> 00:16:57.123
and viral suppression rates increase?

316
00:16:58.050 --> 00:17:00.780
So those are the four components of the intervention.

317
00:17:00.780 --> 00:17:03.060
CRISP, peer support, social media influence

318
00:17:03.060 --> 00:17:03.893
and health equity.

319
00:17:03.893 --> 00:17:07.470
So we said, "Okay, if we do these four things together,"

320
00:17:07.470 --> 00:17:09.750
right, if we do this multi-level strategy

321
00:17:09.750 --> 00:17:13.800
that are addressing issues that we know are complicating us

322
00:17:13.800 --> 00:17:16.920
achieving this goal with black MSM,

323
00:17:16.920 --> 00:17:18.810
we can increase rates for HIV testing.

324
00:17:18.810 --> 00:17:21.270
And then among those who don't have HIV

325
00:17:21.270 --> 00:17:23.850
increased the use of PrEP.

326
00:17:23.850 --> 00:17:24.987
At the time we only had oral PrEP,

327
00:17:24.987 --> 00:17:26.880
but even with injectable PrEP.

328
00:17:26.880 --> 00:17:29.130
We can increase that and then increase the proportion

329
00:17:29.130 --> 00:17:32.760
of black MSM who are protected from acquiring

330
00:17:32.760 --> 00:17:35.880
an HIV infection if they're exposed.

331
00:17:35.880 --> 00:17:37.440
And then among those who are diagnosed,

332
00:17:37.440 --> 00:17:39.870
we can increase the uptake in adherence to ART

333
00:17:39.870 --> 00:17:42.510
and increase the proportion of those black MSM

334
00:17:42.510 --> 00:17:43.890
who are virally suppressed.

335
00:17:43.890 --> 00:17:46.260
And if we can do these things,

336
00:17:46.260 --> 00:17:48.337
which is consistent with the EHE strategy,

337
00:17:48.337 --> 00:17:50.790
these are three parts of the pillar,

338
00:17:50.790 --> 00:17:53.990
that we can reduce HIV incidence among black MSM

339
00:17:53.990 --> 00:17:56.850
in the South, because that's personally

340
00:17:56.850 --> 00:17:58.050
where it's concentrated.

341
00:18:00.000 --> 00:18:04.200
So we're testing this, the things I described to you.

342
00:18:04.200 --> 00:18:06.450
We don't know that it will work.

343
00:18:06.450 --> 00:18:09.690
We hypothesize that it will work, but we don't know.

344
00:18:09.690 --> 00:18:11.670
How we plan to know what's do testing it

345
00:18:11.670 --> 00:18:14.523
in this cluster randomized controlled trial.

346
00:18:15.420 --> 00:18:17.253
It involves 16 communities.

347
00:18:18.090 --> 00:18:22.222
It involves delivering the integrated strategy

348
00:18:22.222 --> 00:18:23.880
and the intervention communities.

349
00:18:23.880 --> 00:18:26.820
And the communities who are randomized to standard of care

350
00:18:26.820 --> 00:18:28.800
will continue to do whatever it is

351
00:18:28.800 --> 00:18:30.150
that they're doing in their communities

352
00:18:30.150 --> 00:18:33.063
to advance their EEG goals, but without the added,

353
00:18:33.900 --> 00:18:36.093
the addition of the integrated strategy.

354
00:18:37.110 --> 00:18:40.050
And then we're measuring our out points at,

355
00:18:40.050 --> 00:18:43.560
we're measuring out our endpoints in two ways.

356
00:18:43.560 --> 00:18:45.840
The first is we're looking at viral suppression

357
00:18:45.840 --> 00:18:48.330
through partnership with the Centers for Disease Control.

358
00:18:48.330 --> 00:18:51.240
So we'll look at surveillance data to see whether or not

359
00:18:51.240 --> 00:18:53.760
our intervention, the way that is applied,

360
00:18:53.760 --> 00:18:56.070
if can have an impact on CDC surveillance

361
00:18:56.070 --> 00:18:58.800
of HIV viral suppression among black MSM.

362
00:18:58.800 --> 00:19:02.400
And then we are doing an assessment,

363
00:19:02.400 --> 00:19:05.610
a cross-sectional assessment of black MSM sampled

364
00:19:05.610 --> 00:19:08.280
from each community to determine the prevalence

365
00:19:08.280 --> 00:19:10.323
of PrEP uptake in those communities.

366
00:19:11.940 --> 00:19:15.000
So these are the 16 communities.

367
00:19:15.000 --> 00:19:17.100
We group them into pairs,

368
00:19:17.100 --> 00:19:19.443
and we randomized within each pair.

369
00:19:21.990 --> 00:19:23.070
May not be able to see it well,

370
00:19:23.070 --> 00:19:26.400
but the communities that have the stars next to it

371
00:19:26.400 --> 00:19:28.650
are the ones who are randomized

372
00:19:28.650 --> 00:19:32.493
to the intervention community.

373
00:19:34.380 --> 00:19:36.240
And we started this in a pilot.

374
00:19:36.240 --> 00:19:41.240
So we started a pilot maybe earlier 2022,

375
00:19:41.730 --> 00:19:44.040
seems like longer than that.

376
00:19:44.040 --> 00:19:46.680
So we're piloting it and two pairs,

377
00:19:46.680 --> 00:19:49.380
which is about coming to an end of that phase.

378
00:19:49.380 --> 00:19:51.900
That's Dallas and Houston, Texas being one pair,

379
00:19:51.900 --> 00:19:53.697
with Dallas as the intervention community.

380
00:19:53.697 --> 00:19:56.070
And then Montgomery, Alabama and Greenville

381
00:19:56.070 --> 00:19:59.100
being the second pair in Montgomery was the,

382
00:19:59.100 --> 00:20:00.750
or is the intervention community.

383
00:20:01.950 --> 00:20:06.300
I think we developed this beautiful logic model.

384
00:20:06.300 --> 00:20:09.450
This is based on the implementation research logic model

385
00:20:09.450 --> 00:20:12.420
that I think came out of the team at Northwestern,

386
00:20:12.420 --> 00:20:14.400
which is also part of ISC3I.

387
00:20:14.400 --> 00:20:18.363
So we use this to think about how would we implement these,

388
00:20:19.290 --> 00:20:23.250
this intervention strategy given that's gonna be implemented

389
00:20:23.250 --> 00:20:27.630
in places where it requires people who work

390
00:20:27.630 --> 00:20:31.170
in organizations to take the intervention and use it.

391
00:20:31.170 --> 00:20:33.337
So it's not a sort of classic drug trial

392
00:20:33.337 --> 00:20:37.200
where you enroll people, you give them an intervention

393
00:20:37.200 --> 00:20:40.560
or a pill and you see the outcome.

394
00:20:40.560 --> 00:20:44.070
These organizations have some role

395
00:20:44.070 --> 00:20:47.160
in taking these strategies and improving their practice

396
00:20:47.160 --> 00:20:48.240
for us to see the outcomes.

397
00:20:48.240 --> 00:20:49.830
So we need to think about what are the things

398
00:20:49.830 --> 00:20:52.530
that are gonna influence that, what are the determinants?

399
00:20:52.530 --> 00:20:54.270
How might we influence that?

400
00:20:54.270 --> 00:20:56.280
And that's the implementation strategies.

401
00:20:56.280 --> 00:20:58.470
That's what our integrated strategy is,

402
00:20:58.470 --> 00:21:00.393
an integrated implementation strategy.

403
00:21:01.320 --> 00:21:03.630
And then we map the outcomes based on what we think

404
00:21:03.630 --> 00:21:06.300
the mechanism of action will be.

405
00:21:06.300 --> 00:21:07.890
And so again, in this study,

406
00:21:07.890 --> 00:21:10.350
we're not testing the efficacy

407
00:21:10.350 --> 00:21:14.460
of the biomedical innovation.

408
00:21:14.460 --> 00:21:16.260
These clinical interventions exist.

409
00:21:16.260 --> 00:21:19.263
What we're trying to do, in a sense,

410
00:21:20.430 --> 00:21:23.100
is test how can we get them scaled,

411
00:21:23.100 --> 00:21:24.600
taking the scale in these communities,

412
00:21:24.600 --> 00:21:27.780
and can we also observe the impact of scaling

413
00:21:27.780 --> 00:21:30.030
in these communities in our final outcomes

414
00:21:30.030 --> 00:21:33.603
which are viral suppression and PrEP uptake.

415
00:21:34.770 --> 00:21:38.430
So these are the considerations

416
00:21:38.430 --> 00:21:39.630
that I wanted to sort of get into.

417
00:21:39.630 --> 00:21:44.100
So the first thing in doing something complex as this

418
00:21:44.100 --> 00:21:48.093
is community engagement is very important.

419
00:21:49.920 --> 00:21:54.810
Neither Bob or Chris or I live,

420
00:21:54.810 --> 00:21:57.900
Chris lives there now, but live in this place

421
00:21:57.900 --> 00:22:00.300
where we're gonna do this study.

422
00:22:00.300 --> 00:22:03.663
And even if we did, we didn't live in all the places that,

423
00:22:05.280 --> 00:22:06.720
we didn't live in every neighborhood.

424
00:22:06.720 --> 00:22:09.330
We weren't familiar with every place in this region.

425
00:22:09.330 --> 00:22:11.700
And so community engagement was gonna be key.

426
00:22:11.700 --> 00:22:15.960
We needed people who knew what it was to live in the South,

427
00:22:15.960 --> 00:22:20.280
who knew what it was to live the black social experience

428
00:22:20.280 --> 00:22:24.390
in the South, who knew what it was to be a man

429
00:22:24.390 --> 00:22:26.100
who has such desired for other men,

430
00:22:26.100 --> 00:22:28.110
or who engaged in sex with other men,

431
00:22:28.110 --> 00:22:29.760
or who identifies as gay bisexual

432
00:22:29.760 --> 00:22:31.803
in that geographic context.

433
00:22:32.880 --> 00:22:36.060
So we spent a lot of time designing a strategy

434
00:22:36.060 --> 00:22:38.490
that would really infuse community engagement

435
00:22:38.490 --> 00:22:40.946
throughout everything that we did.

436
00:22:40.946 --> 00:22:43.203
It was really a three-level strategy.

437
00:22:44.580 --> 00:22:47.700
The first was helping to raise general awareness

438
00:22:47.700 --> 00:22:50.670
about the study through local stakeholders

439
00:22:50.670 --> 00:22:52.140
and through national stakeholders

440
00:22:52.140 --> 00:22:55.020
who were recognized members of the community.

441
00:22:55.020 --> 00:22:57.723
Then we had a community specific-engagement component,

442
00:23:02.940 --> 00:23:05.090
which is really designed to make sure folks

443
00:23:06.240 --> 00:23:07.680
understood these different elements

444
00:23:07.680 --> 00:23:09.183
of the integrated strategy,

445
00:23:10.530 --> 00:23:13.260
but also that community members could inform

446
00:23:13.260 --> 00:23:15.390
our development of these elements

447
00:23:15.390 --> 00:23:16.920
of the integrated strategy.

448
00:23:16.920 --> 00:23:19.680
And then the third was making sure we could identify people

449
00:23:19.680 --> 00:23:23.130
who could participate in the cross-sectional assessment,

450
00:23:23.130 --> 00:23:25.263
or baseline survey and sampling.

451
00:23:26.490 --> 00:23:31.490
And, initially, we had three types of groups

452
00:23:31.590 --> 00:23:33.990
that we identified or assembled:

453
00:23:33.990 --> 00:23:37.650
a community strategies group which was really a group

454
00:23:37.650 --> 00:23:40.410
that provided strategic guidance to us.

455
00:23:40.410 --> 00:23:44.880
These were folks who were involved in healthcare

456
00:23:44.880 --> 00:23:47.820
and policy and research in different parts of the country,

457
00:23:47.820 --> 00:23:50.470
mostly in the South but not exclusively in the South.

458
00:23:51.330 --> 00:23:53.700
It helped us think about how we were designing this study,

459
00:23:53.700 --> 00:23:57.063
what we should be pursuing, what pitfalls we should avoid.

460
00:23:58.620 --> 00:24:00.000
A community advisory group,

461
00:24:00.000 --> 00:24:03.300
which was our primary advisory body for the study.

462
00:24:03.300 --> 00:24:06.033
These were made up of people who really,

463
00:24:07.080 --> 00:24:08.430
they had to live in the community.

464
00:24:08.430 --> 00:24:11.343
So we had at least two individuals,

465
00:24:12.420 --> 00:24:15.960
not all black men, but mostly black men

466
00:24:15.960 --> 00:24:18.420
who were from each of the 16 communities

467
00:24:18.420 --> 00:24:20.100
where the study was being conducted.

468
00:24:20.100 --> 00:24:21.930
It didn't matter whether it was the intervention community

469
00:24:21.930 --> 00:24:23.250
or standard of care.

470
00:24:23.250 --> 00:24:25.110
We needed people from there who could really help us

471
00:24:25.110 --> 00:24:27.120
understand what we needed to be doing

472
00:24:27.120 --> 00:24:29.610
or be aware of in these communities.

473
00:24:29.610 --> 00:24:32.880
And then finally, we had community liaisons

474
00:24:32.880 --> 00:24:34.140
who really were our gatekeepers.

475
00:24:34.140 --> 00:24:36.360
These were the people, you see them across the bottom

476
00:24:36.360 --> 00:24:41.360
of the screen, who were our connection to the communities,

477
00:24:42.330 --> 00:24:44.670
both me as one of the protocol chairs

478
00:24:44.670 --> 00:24:46.230
and also our senior research managers.

479
00:24:46.230 --> 00:24:48.900
They helped us understand what was going on

480
00:24:48.900 --> 00:24:51.420
and were really the ambassadors, if you will,

481
00:24:51.420 --> 00:24:53.940
for the study in their communities.

482
00:24:53.940 --> 00:24:57.960
These represent Dallas, Texas, Montgomery,

483
00:24:57.960 --> 00:25:00.210
Greenville and Houston, Texas,

484
00:25:00.210 --> 00:25:02.510
Greenville, South Carolina and Houston, Texas.

485
00:25:04.260 --> 00:25:08.340
And we obviously had to do a lot of communications.

486
00:25:08.340 --> 00:25:12.300
And so this is just showing a couple things,

487
00:25:12.300 --> 00:25:14.400
a website was developed to make sure people

488
00:25:14.400 --> 00:25:17.733
could go to it and understand aspects of the study.

489
00:25:18.720 --> 00:25:22.710
We presented at multiple conferences at community events.

490
00:25:22.710 --> 00:25:25.030
And then we had to also in some ways

491
00:25:25.980 --> 00:25:28.260
sponsored community events.

492
00:25:28.260 --> 00:25:32.520
I mean, I think typically,

493
00:25:32.520 --> 00:25:35.400
and I think we suffer from this also in this study,

494
00:25:35.400 --> 00:25:39.630
is we see the community component

495
00:25:39.630 --> 00:25:44.630
as a bit of a added benefit or a luxury.

496
00:25:45.510 --> 00:25:48.840
And what it means is that when we allocate budget,

497
00:25:48.840 --> 00:25:52.380
we allocate it towards the things that are key or important.

498
00:25:52.380 --> 00:25:55.980
And if there's money left over to do the nice-to-have things

499
00:25:55.980 --> 00:25:58.391
but not essential things, then you might sprinkle,

500
00:25:58.391 --> 00:26:01.563
(chuckles) you might put some money in those areas.

501
00:26:02.880 --> 00:26:04.350
But I think that's a mistake.

502
00:26:04.350 --> 00:26:08.160
The community engagement part is essential.

503
00:26:08.160 --> 00:26:11.430
There's no way we could even get to these places

504
00:26:11.430 --> 00:26:13.920
and try to implement half of what we've done

505
00:26:13.920 --> 00:26:15.810
were it not been for our engagement.

506
00:26:15.810 --> 00:26:18.663
And it also can't just be transactional.

507
00:26:20.460 --> 00:26:22.680
And I mentioned this because I mentioned a few moments ago

508
00:26:22.680 --> 00:26:25.530
about the need to sponsor events.

509
00:26:25.530 --> 00:26:29.190
So the trials and investment in the community

510
00:26:29.190 --> 00:26:33.360
had to be more than you being able to bring us participants.

511
00:26:33.360 --> 00:26:36.330
So we had to be there and also show interesting things

512
00:26:36.330 --> 00:26:37.680
that they were doing,

513
00:26:37.680 --> 00:26:40.770
even if it was not directly tied to the study,

514
00:26:40.770 --> 00:26:42.600
that they can be constrained to that,

515
00:26:42.600 --> 00:26:44.340
if your grant funder doesn't approve for you

516
00:26:44.340 --> 00:26:47.580
to do certain things with the fund that promote this.

517
00:26:47.580 --> 00:26:49.200
But had we not done these things,

518
00:26:49.200 --> 00:26:50.920
I think it's quite likely that

519
00:26:52.530 --> 00:26:54.750
we would not have been welcomed or not seen

520
00:26:54.750 --> 00:26:58.830
as serious partners in some of these community areas

521
00:26:58.830 --> 00:26:59.663
where we were.

522
00:26:59.663 --> 00:27:03.720
And so the community investment is a key consideration,

523
00:27:03.720 --> 00:27:08.070
I think is also a common pitfall

524
00:27:08.070 --> 00:27:09.720
that happens when you're designing studies

525
00:27:09.720 --> 00:27:12.783
and particularly how you're resourcing trials.

526
00:27:18.330 --> 00:27:21.630
So we did the baseline cross-sectional assessment

527
00:27:21.630 --> 00:27:23.097
in four communities.

528
00:27:23.097 --> 00:27:25.897
And three of the four, we've already reached our target.

529
00:27:27.090 --> 00:27:30.780
So we did this because the intervention is being applied

530
00:27:30.780 --> 00:27:33.115
at the community level, as I mentioned before,

531
00:27:33.115 --> 00:27:35.433
we're not following a cohort.

532
00:27:36.600 --> 00:27:37.920
So because we're not doing that,

533
00:27:37.920 --> 00:27:40.830
we needed to use a sampling method that we thought

534
00:27:40.830 --> 00:27:42.030
could give us (sneezes),

535
00:27:44.610 --> 00:27:47.530
that we thought could give us a population estimate

536
00:27:48.510 --> 00:27:52.140
that we could sample this way and have a pretty good sense

537
00:27:52.140 --> 00:27:53.820
that this is what's happening in the community,

538
00:27:53.820 --> 00:27:57.570
both that baseline and when we do our follow-up assessment.

539
00:27:57.570 --> 00:28:00.543
And so we use this Starfish sampling method.

540
00:28:02.130 --> 00:28:06.750
And what you'll see, this is data as of Monday

541
00:28:06.750 --> 00:28:08.550
that we've reached our target.

542
00:28:08.550 --> 00:28:11.515
The target is 100 people per community

543
00:28:11.515 --> 00:28:13.590
in the four that were in the pilot.

544
00:28:13.590 --> 00:28:17.763
So we reached our target three of the four communities,

545
00:28:18.600 --> 00:28:20.313
in some ways exceeded the target.

546
00:28:21.510 --> 00:28:22.770
Are there reasons that we had to always (indistinct)

547
00:28:22.770 --> 00:28:24.840
some places, but at least in three,

548
00:28:24.840 --> 00:28:27.840
we have reached at least 100 people that were enrolled.

549
00:28:27.840 --> 00:28:30.690
And in one community we're a little bit ways away

550
00:28:30.690 --> 00:28:34.143
from reaching the 100 'cause we're currently at about 80.

551
00:28:35.730 --> 00:28:37.683
So here is the challenge.

552
00:28:39.240 --> 00:28:44.240
We think there are some assumptions about Starfish sampling

553
00:28:45.420 --> 00:28:48.280
that, not even some assumptions

554
00:28:49.740 --> 00:28:52.140
about that might be cultural that might not really reflect

555
00:28:52.140 --> 00:28:54.930
the way that black communities operate

556
00:28:54.930 --> 00:28:56.940
or move about in the South.

557
00:28:56.940 --> 00:28:58.740
And there are also some constraints.

558
00:28:58.740 --> 00:29:02.430
So for example, in order to try to reach

559
00:29:02.430 --> 00:29:07.410
a representative sample, you can't just go to a party

560
00:29:07.410 --> 00:29:12.180
or event and talk to every person that you encounter, right?

561
00:29:12.180 --> 00:29:15.003
In some sense, that becomes a convenient sample.

562
00:29:16.470 --> 00:29:20.880
And so they've had to space out how many people

563
00:29:20.880 --> 00:29:22.830
they could when they would count a person.

564
00:29:22.830 --> 00:29:25.110
So every third person could be recruited,

565
00:29:25.110 --> 00:29:28.080
and then up to 10 people per event.

566
00:29:28.080 --> 00:29:29.610
And then you would stop recruiting,

567
00:29:29.610 --> 00:29:30.900
and you wait for another event.

568
00:29:30.900 --> 00:29:32.250
You'd approach every third person,

569
00:29:32.250 --> 00:29:35.520
up to a certain number of people at a time.

570
00:29:35.520 --> 00:29:38.910
And so, from a statistical standpoint,

571
00:29:38.910 --> 00:29:41.070
you can understand why that would be important to do

572
00:29:41.070 --> 00:29:43.320
if you're trying to achieve what Starfish

573
00:29:43.320 --> 00:29:46.020
is supposed to provide in terms of representativeness.

574
00:29:47.250 --> 00:29:51.033
But it does create challenges because it does not,

575
00:29:52.689 --> 00:29:55.980
it imposes constraints.

576
00:29:55.980 --> 00:30:00.980
So for example, it takes much longer to recruit people

577
00:30:00.990 --> 00:30:03.540
in these contexts using Starfish

578
00:30:03.540 --> 00:30:05.580
because, especially in COVID,

579
00:30:05.580 --> 00:30:08.580
there are not sort of regular normal places

580
00:30:08.580 --> 00:30:11.310
where black gay men or black MSM

581
00:30:11.310 --> 00:30:15.000
can gather in a place like Montgomery, Alabama

582
00:30:15.000 --> 00:30:17.340
or a place like Greenville, South Carolina,

583
00:30:17.340 --> 00:30:19.533
or even some parts of Texas.

584
00:30:20.469 --> 00:30:23.970
And so the opportunities to recruit become smaller

585
00:30:23.970 --> 00:30:26.460
in places where you don't have an infrastructure

586
00:30:26.460 --> 00:30:29.130
that's set up where there's normal gathering places

587
00:30:29.130 --> 00:30:31.650
for black sexual minority men, right?

588
00:30:31.650 --> 00:30:33.240
So this was a conundrum.

589
00:30:33.240 --> 00:30:35.790
We want to use this strategy because we wanna have

590
00:30:35.790 --> 00:30:38.640
some rigor and understanding that the sample that we got

591
00:30:38.640 --> 00:30:40.773
represents the community overall.

592
00:30:41.760 --> 00:30:43.650
But it's hard to implement this (chuckles)

593
00:30:43.650 --> 00:30:46.050
because of the parameters of how you have to operate it,

594
00:30:46.050 --> 00:30:48.750
which means it's gonna take us a much longer time to do it,

595
00:30:48.750 --> 00:30:50.370
and the studies already started.

596
00:30:50.370 --> 00:30:54.690
And so we don't wanna still be recruiting a baseline sample

597
00:30:54.690 --> 00:30:56.490
at the point that we already had to,

598
00:30:56.490 --> 00:30:59.940
we don't wanna be recruiting the baseline sample

599
00:30:59.940 --> 00:31:01.740
at the point where we've already had to start

600
00:31:01.740 --> 00:31:04.770
implementing the study because it's taking so long

601
00:31:04.770 --> 00:31:07.290
and we can't wait to get the sample

602
00:31:07.290 --> 00:31:09.450
before we can start because of timelines.

603
00:31:09.450 --> 00:31:13.203
So that was a conundrum but something to consider.

604
00:31:14.460 --> 00:31:16.410
For social media influencers,

605
00:31:16.410 --> 00:31:20.280
we had influencers

606
00:31:20.280 --> 00:31:23.163
from at least each community.

607
00:31:24.600 --> 00:31:28.890
This was also very exciting for us

608
00:31:28.890 --> 00:31:31.290
because of the potential impact

609
00:31:31.290 --> 00:31:33.213
and reach of social media influencers.

610
00:31:34.530 --> 00:31:38.610
But it also had some conundrums for us, some challenges.

611
00:31:38.610 --> 00:31:42.180
So the first is that because we are testing this

612
00:31:42.180 --> 00:31:44.853
in a randomized controlled trial,

613
00:31:46.170 --> 00:31:48.810
we were very concerned about contamination,

614
00:31:48.810 --> 00:31:53.810
that we have to find social media influencers

615
00:31:54.780 --> 00:31:58.800
whose influence is really isolated

616
00:31:58.800 --> 00:32:01.140
to the intervention communities,

617
00:32:01.140 --> 00:32:02.910
because we didn't want them influencing people

618
00:32:02.910 --> 00:32:04.710
in our standard of care communities,

619
00:32:05.820 --> 00:32:08.130
not for the intervention component.

620
00:32:08.130 --> 00:32:11.130
And so the first is that is hard to do.

621
00:32:11.130 --> 00:32:14.370
The people that have the most influence,

622
00:32:14.370 --> 00:32:16.290
their influence is not isolated. (chuckles)

623
00:32:16.290 --> 00:32:18.930
Their influence is broad,

624
00:32:18.930 --> 00:32:22.560
and having people like that violates

625
00:32:22.560 --> 00:32:25.680
one of the principles of conducting

626
00:32:25.680 --> 00:32:27.180
a randomized controlled trial.

627
00:32:28.110 --> 00:32:31.740
But if you can identify influencers

628
00:32:31.740 --> 00:32:34.023
who have very limited reach,

629
00:32:34.950 --> 00:32:37.560
which can allow you to have a social media influencer

630
00:32:37.560 --> 00:32:39.720
that will not have such a broad reach

631
00:32:39.720 --> 00:32:42.510
that they would contaminate other communities,

632
00:32:42.510 --> 00:32:44.910
it doesn't really allow you to, (chuckles)

633
00:32:44.910 --> 00:32:47.010
it doesn't really meet the intent

634
00:32:47.010 --> 00:32:49.500
of the social media influence because you need somebody

635
00:32:49.500 --> 00:32:51.900
with limited influence in order to conform

636
00:32:51.900 --> 00:32:53.850
the parameters of a trial.

637
00:32:53.850 --> 00:32:57.240
And if you got influencers who really have broad influence

638
00:32:57.240 --> 00:32:58.623
and people would listen to,

639
00:32:59.580 --> 00:33:01.350
that that would quite easily violate

640
00:33:01.350 --> 00:33:02.790
the parameters of conducting

641
00:33:02.790 --> 00:33:04.500
a randomized controlled problem.

642
00:33:04.500 --> 00:33:07.050
So we've had to learn from this.

643
00:33:07.050 --> 00:33:08.900
One of the ways that we thought about

644
00:33:09.870 --> 00:33:13.510
is that we might have to relax that

645
00:33:16.200 --> 00:33:18.480
and think about, you know, what we would lose

646
00:33:18.480 --> 00:33:21.990
by having a broad influencer who might have influence

647
00:33:21.990 --> 00:33:24.270
in some of the other communities

648
00:33:24.270 --> 00:33:26.910
compared to what we would gain by having an influencer

649
00:33:26.910 --> 00:33:28.680
that could really represent

650
00:33:28.680 --> 00:33:30.730
what this intervention is supposed to be.

651
00:33:32.490 --> 00:33:35.250
For peer support, these are,

652
00:33:35.250 --> 00:33:38.130
the pictures that you're seeing are the people on the team.

653
00:33:38.130 --> 00:33:40.680
And so these are our six peer supporters,

654
00:33:40.680 --> 00:33:44.163
and Antoine Jackson who is their clinical supervisor.

655
00:33:45.424 --> 00:33:48.870
As I mentioned, the peer support is designed for,

656
00:33:48.870 --> 00:33:52.170
it's online, and you don't have to be signed up

657
00:33:52.170 --> 00:33:54.670
with any particular agency to receive the support.

658
00:33:57.180 --> 00:34:01.770
We train them, we train them intensely,

659
00:34:01.770 --> 00:34:03.810
over 40 hours of training.

660
00:34:03.810 --> 00:34:08.810
And we develop a comprehensive promotional program

661
00:34:09.690 --> 00:34:11.643
to get people to participate.

662
00:34:13.200 --> 00:34:14.850
And we didn't have, at least right now,

663
00:34:14.850 --> 00:34:16.353
robust participation.

664
00:34:17.460 --> 00:34:19.770
And we try to understand mostly with the help

665
00:34:19.770 --> 00:34:22.720
of our community advisory group why that might be the case.

666
00:34:25.710 --> 00:34:29.703
And partly because peer support requires trust,

667
00:34:30.900 --> 00:34:33.390
and trust takes time to build.

668
00:34:33.390 --> 00:34:37.770
And that this trust building really was not

669
00:34:37.770 --> 00:34:39.753
aligned with the study timeline.

670
00:34:41.250 --> 00:34:43.680
In some of these places where there's high degrees

671
00:34:43.680 --> 00:34:47.010
of stigma where living as an out black gay man,

672
00:34:47.010 --> 00:34:49.050
or even if you're not out, people finding out

673
00:34:49.050 --> 00:34:52.680
about your sexuality if it's a minoritized sexuality,

674
00:34:52.680 --> 00:34:54.720
can have very serious consequences for people.

675
00:34:54.720 --> 00:34:57.240
And so for folks to access these things,

676
00:34:57.240 --> 00:35:00.360
for even show on their phone as an app,

677
00:35:00.360 --> 00:35:02.670
folks have to trust that it's not gonna get them

678
00:35:02.670 --> 00:35:05.970
in some type of trouble or situation

679
00:35:05.970 --> 00:35:07.227
they don't want to be in.

680
00:35:07.227 --> 00:35:10.263
And that building that type of trust takes time,

681
00:35:11.100 --> 00:35:15.393
and more time than we had (chuckles) for the study timeline.

682
00:35:16.380 --> 00:35:18.270
And so we didn't have great uptake

683
00:35:18.270 --> 00:35:21.150
in this particular component in the timeframe

684
00:35:21.150 --> 00:35:22.200
that we were trying to look for,

685
00:35:22.200 --> 00:35:24.510
which I think it was probably too narrow.

686
00:35:24.510 --> 00:35:26.010
And so one of the things that we considered

687
00:35:26.010 --> 00:35:29.550
is that we probably don't need a centralized

688
00:35:29.550 --> 00:35:32.553
peer support program not connected to an agency.

689
00:35:34.260 --> 00:35:37.410
The reason we had a centralized program

690
00:35:37.410 --> 00:35:40.060
is because people were concerned that in order to get

691
00:35:41.940 --> 00:35:44.310
peer support you had to go to the Spiegelman clinic.

692
00:35:44.310 --> 00:35:45.960
And if you're not a patient at the Spiegelman clinic,

693
00:35:45.960 --> 00:35:49.030
you don't have to become a patient just to get peer support

694
00:35:50.040 --> 00:35:52.080
or go to the Nelson Health Center to get peer support

695
00:35:52.080 --> 00:35:53.130
if you wanted a patient there

696
00:35:53.130 --> 00:35:54.810
or if you didn't like going there.

697
00:35:54.810 --> 00:35:58.710
And so we had that information from the community early on.

698
00:35:58.710 --> 00:36:00.960
So we said we shouldn't anchor it to a clinic

699
00:36:00.960 --> 00:36:03.060
because then that will serve as a barrier.

700
00:36:04.080 --> 00:36:06.630
But, in thinking about that,

701
00:36:06.630 --> 00:36:09.420
we think it may be better to not anchor it

702
00:36:09.420 --> 00:36:12.600
into a particular clinic but to offer the program

703
00:36:12.600 --> 00:36:15.960
to resource multiple organizations in the community

704
00:36:15.960 --> 00:36:18.720
so that people had options so that the peer support program

705
00:36:18.720 --> 00:36:22.590
was not tied to the identity of any one particular clinic.

706
00:36:22.590 --> 00:36:25.920
But because those clinics and organizations were trusted,

707
00:36:25.920 --> 00:36:27.900
hopefully trusted organizations,

708
00:36:27.900 --> 00:36:30.990
that this could facilitate the implementation in ways

709
00:36:30.990 --> 00:36:33.990
that trying to do it centrally from a research site

710
00:36:33.990 --> 00:36:35.460
cannot accomplish in the timeframe

711
00:36:35.460 --> 00:36:38.103
that we needed to accomplish for the trial.

712
00:36:39.810 --> 00:36:43.500
And then this next one is really the CRISP.

713
00:36:43.500 --> 00:36:47.370
And this is the component I spent quite a bit of time on.

714
00:36:47.370 --> 00:36:50.250
Again, CRISP is focused on healthcare facilities,

715
00:36:50.250 --> 00:36:55.250
really to reduce the amount of stigma

716
00:36:56.340 --> 00:36:58.260
that people experience when they go there,

717
00:36:58.260 --> 00:37:00.390
both in interpersonal interactions

718
00:37:00.390 --> 00:37:02.733
but also in how services might be delivered.

719
00:37:03.930 --> 00:37:05.943
And CRISP has these five components:

720
00:37:07.320 --> 00:37:08.490
client observation visits,

721
00:37:08.490 --> 00:37:11.520
which are simulated clients that we train

722
00:37:11.520 --> 00:37:14.520
who go in as patients, simulated patients,

723
00:37:14.520 --> 00:37:16.140
and have an experience in that clinic

724
00:37:16.140 --> 00:37:18.420
and then have the ability to offer feedback

725
00:37:18.420 --> 00:37:21.240
about what it was like to be a black gay man

726
00:37:21.240 --> 00:37:24.810
and playing that character in that clinic space,

727
00:37:24.810 --> 00:37:27.453
or CBO space, but mostly these have been clinics.

728
00:37:28.710 --> 00:37:31.110
Or providing a foundational training

729
00:37:31.110 --> 00:37:34.270
which is basically 12 contact hours of stigma reduction

730
00:37:35.400 --> 00:37:37.110
intervention workshop.

731
00:37:37.110 --> 00:37:39.480
And then quality improvement, which is how we take

732
00:37:39.480 --> 00:37:43.953
what we've learned and translate that into service changes.

733
00:37:46.470 --> 00:37:51.470
So we worked, we tried this with four facilities.

734
00:37:51.870 --> 00:37:53.250
One is Parkland Hospital,

735
00:37:53.250 --> 00:37:57.990
which is a large public safety hospital in Dallas, Texas,

736
00:37:57.990 --> 00:38:01.380
and Abounding Prosperity, which is a community-based clinic,

737
00:38:01.380 --> 00:38:04.320
organization with the clinic in Dallas, Texas,

738
00:38:04.320 --> 00:38:08.100
and then MAO, which is in Montgomery, Alabama.

739
00:38:08.100 --> 00:38:11.400
They have a treatment facility and a prevention facility.

740
00:38:11.400 --> 00:38:14.160
So we were able to, this green that you see is showing

741
00:38:14.160 --> 00:38:16.023
that we completed surveys,

742
00:38:17.070 --> 00:38:18.960
we had simulated client instructors,

743
00:38:18.960 --> 00:38:20.883
observers go in and make those visits.

744
00:38:21.840 --> 00:38:23.490
And we met all our training goals,

745
00:38:23.490 --> 00:38:26.670
which really was that we could get 75% of people

746
00:38:26.670 --> 00:38:30.090
in those facilities who do HIV prevention work

747
00:38:30.090 --> 00:38:33.240
or are along that HIV prevention or treatment pathway,

748
00:38:33.240 --> 00:38:36.690
that we could get at least 75% of those people trained.

749
00:38:36.690 --> 00:38:41.460
And we had as much as 99% coverage in some places.

750
00:38:41.460 --> 00:38:46.460
Parkland was at 77%, and Abounding Prosperity at 83%.

751
00:38:48.180 --> 00:38:50.490
But those are great successes,

752
00:38:50.490 --> 00:38:52.680
but they're also challenges to it.

753
00:38:52.680 --> 00:38:54.580
The first is that

754
00:38:58.950 --> 00:39:03.650
we have to have a pretty strong business case for doing this

755
00:39:03.650 --> 00:39:08.340
in healthcare facilities or a pretty substantial incentive

756
00:39:08.340 --> 00:39:11.100
because the time that the facilities take out

757
00:39:11.100 --> 00:39:14.940
to participate in this, the stigma reduction intervention,

758
00:39:14.940 --> 00:39:18.810
which is important, but it is time that they're not spending

759
00:39:18.810 --> 00:39:21.360
doing things that they could be billing for

760
00:39:21.360 --> 00:39:25.000
and generating revenue, which is not trivial.

761
00:39:27.210 --> 00:39:30.600
So it's something we have to think about to do.

762
00:39:30.600 --> 00:39:35.103
We did provide an intended, which we thought was fair,

763
00:39:36.240 --> 00:39:38.250
in the design.

764
00:39:38.250 --> 00:39:41.100
But in the implementation, it is becoming clear to us

765
00:39:41.100 --> 00:39:44.520
that sites are feeling that they're giving up a bit more

766
00:39:44.520 --> 00:39:48.270
to participate in this than is covered

767
00:39:48.270 --> 00:39:51.270
by the compensation that we provided them for participating.

768
00:39:52.320 --> 00:39:53.970
So it's something to think about because we couldn't do,

769
00:39:53.970 --> 00:39:58.050
we can't force the clinics to do it, to participate in this,

770
00:39:58.050 --> 00:40:03.050
but in order for us to reach black men and black MSM,

771
00:40:03.210 --> 00:40:05.040
we really have to be working in clinics

772
00:40:05.040 --> 00:40:06.570
where we know they'll go,

773
00:40:06.570 --> 00:40:09.453
they'll likely have to pass through to get care.

774
00:40:10.740 --> 00:40:14.280
Related to that is (chuckles)

775
00:40:14.280 --> 00:40:18.543
one of the things that we thought about is how can we,

776
00:40:19.950 --> 00:40:23.020
what number of clinics do we need to target

777
00:40:24.699 --> 00:40:28.020
to maximize the reach that it will get to black MSM?

778
00:40:28.020 --> 00:40:30.753
Is it 10, is it 20, is it 100?

779
00:40:32.010 --> 00:40:33.963
We can't afford 100 in each city,

780
00:40:34.890 --> 00:40:37.200
but we need some way of figuring out how we do that.

781
00:40:37.200 --> 00:40:39.420
For HIV primary care, that's a bit easier

782
00:40:39.420 --> 00:40:43.653
because those sites are relatively few in each city.

783
00:40:44.790 --> 00:40:46.740
So we could essentially target all

784
00:40:46.740 --> 00:40:48.543
HIV primary care facilities.

785
00:40:49.625 --> 00:40:51.960
And this chart here is showing you what we would do.

786
00:40:51.960 --> 00:40:56.960
So there are four facilities, that if we targeted them

787
00:40:57.157 --> 00:40:59.280
and check (indistinct) stigma reduction,

788
00:40:59.280 --> 00:41:02.580
we would be in facilities that had patient volume

789
00:41:02.580 --> 00:41:06.870
that accounted for 65% of the black MSM living with HIV.

790
00:41:06.870 --> 00:41:09.510
This is in Shelby County, Memphis, Tennessee.

791
00:41:09.510 --> 00:41:12.540
So for four clinics we could get 65%.

792
00:41:12.540 --> 00:41:15.750
Those clinics would cover 65% of black MSM.

793
00:41:15.750 --> 00:41:18.227
And then if we get additional four clinics,

794
00:41:18.227 --> 00:41:20.730
we can get as high as 80%.

795
00:41:20.730 --> 00:41:24.690
But then after eight clinics, the additional yield,

796
00:41:24.690 --> 00:41:26.040
the additional coverage we would get

797
00:41:26.040 --> 00:41:27.903
gets smaller and smaller and smaller.

798
00:41:29.430 --> 00:41:31.233
So that's something to think about is how we,

799
00:41:31.233 --> 00:41:35.170
that we're thinking about, is how do we get coverage

800
00:41:36.450 --> 00:41:39.390
in terms of population coverage of black MSM,

801
00:41:39.390 --> 00:41:41.280
but we don't have a lot of time

802
00:41:41.280 --> 00:41:43.770
and we don't have an infinite amount of money to do it.

803
00:41:43.770 --> 00:41:46.740
But we could at least accomplish quite a big yield

804
00:41:46.740 --> 00:41:48.780
in HIV primary care.

805
00:41:48.780 --> 00:41:52.120
The larger challenge for us though is in trying to find

806
00:41:53.550 --> 00:41:57.660
the right coverage, the maximum coverage for facilities

807
00:41:57.660 --> 00:42:01.890
who provide PrEP or who could provide PrEP.

808
00:42:01.890 --> 00:42:05.710
Because essentially that's any primary care facility

809
00:42:06.870 --> 00:42:11.310
anywhere should have the capacity to provide PrEP.

810
00:42:11.310 --> 00:42:15.330
And so we're trying to figure out what that is.

811
00:42:15.330 --> 00:42:18.480
The other challenge in trying to figure out that number,

812
00:42:18.480 --> 00:42:20.493
the imperative, I guess I would say,

813
00:42:21.740 --> 00:42:25.140
is that we can't end up with an intervention strategy

814
00:42:25.140 --> 00:42:29.070
or healthcare facility strategy that can only be done

815
00:42:29.070 --> 00:42:31.293
in the context of a trial like this,

816
00:42:32.130 --> 00:42:33.870
that could never be done.

817
00:42:33.870 --> 00:42:37.530
But the CDC would say there's no way we could support this

818
00:42:37.530 --> 00:42:40.500
in our budget, or that agencies in these communities

819
00:42:40.500 --> 00:42:42.720
across the country with this or get

820
00:42:42.720 --> 00:42:44.370
taken up by the CDC would say,

821
00:42:44.370 --> 00:42:45.930
"How could we ever lift this up?"

822
00:42:45.930 --> 00:42:49.440
'Cause you have the sample 100, no 100,

823
00:42:49.440 --> 00:42:52.020
let's say 20 facilities in a small community.

824
00:42:52.020 --> 00:42:54.300
There's no way we could do that.

825
00:42:54.300 --> 00:42:57.600
So what we're thinking about now is taking an epi-focused

826
00:42:57.600 --> 00:43:00.840
approach to selecting the healthcare facilities

827
00:43:00.840 --> 00:43:03.483
for the stigma reduction.

828
00:43:04.320 --> 00:43:09.320
That is looking at global information systems data,

829
00:43:10.440 --> 00:43:13.530
or GIS data that should be available

830
00:43:13.530 --> 00:43:15.090
from health departments.

831
00:43:15.090 --> 00:43:20.090
Understanding what are the high STI burden census tracts

832
00:43:20.460 --> 00:43:23.853
in these areas and what clinics are in those areas.

833
00:43:25.140 --> 00:43:28.830
Because the HIV risk, as we saw earlier,

834
00:43:28.830 --> 00:43:32.310
is not evenly distributed, even probably across communities.

835
00:43:32.310 --> 00:43:34.590
There are probably certain communities where STI

836
00:43:34.590 --> 00:43:39.590
as an indicator of risk of acquiring HIV

837
00:43:39.600 --> 00:43:42.810
are more concentrated or more prevalent than other parts.

838
00:43:42.810 --> 00:43:47.310
So we are thinking we should find out where those places are

839
00:43:47.310 --> 00:43:49.710
and what clinics are in those places,

840
00:43:49.710 --> 00:43:54.060
and in what proportion of that census

841
00:43:54.060 --> 00:43:56.370
in those clinics or the patient role

842
00:43:56.370 --> 00:43:58.140
are black men represented?

843
00:43:58.140 --> 00:44:00.900
And I say black men because in many of these places,

844
00:44:00.900 --> 00:44:03.810
we don't have a denominator for black MSM

845
00:44:03.810 --> 00:44:05.100
for a lot of reasons.

846
00:44:05.100 --> 00:44:07.980
Why it doesn't ask question, or they ask the question

847
00:44:07.980 --> 00:44:09.990
and the person is, the man is not comfortable

848
00:44:09.990 --> 00:44:12.900
telling the provider about that aspect of their behavior

849
00:44:12.900 --> 00:44:14.760
for a variety of reasons.

850
00:44:14.760 --> 00:44:17.940
And so we don't have reliable estimates of black MSM

851
00:44:17.940 --> 00:44:22.050
from a prevention side in many of these places

852
00:44:22.050 --> 00:44:23.643
in almost all of these places.

853
00:44:24.762 --> 00:44:28.140
And so, but we do know the number of black men.

854
00:44:28.140 --> 00:44:33.140
And so if we can identify the places,

855
00:44:33.750 --> 00:44:37.020
the highest number of cases of STIs among black men,

856
00:44:37.020 --> 00:44:38.820
if we can reach those black men,

857
00:44:38.820 --> 00:44:41.040
black MSM are a part of that group.

858
00:44:41.040 --> 00:44:44.440
And so we're trying to figure out ways to determine

859
00:44:45.781 --> 00:44:47.720
how can we figure out where the highest need is,

860
00:44:47.720 --> 00:44:51.930
or the biggest impact that does not require us

861
00:44:51.930 --> 00:44:54.960
to try to sample all the clinics, which we cannot do.

862
00:44:54.960 --> 00:44:56.610
And even if we could do it,

863
00:44:56.610 --> 00:44:59.280
it is not a sound public health strategy

864
00:44:59.280 --> 00:45:01.740
because it probably could not be implemented

865
00:45:01.740 --> 00:45:03.690
in most places in the United States

866
00:45:03.690 --> 00:45:07.050
because of the heavy lift and the cost.

867
00:45:07.050 --> 00:45:10.830
And then we also thought about this idea of spillover.

868
00:45:10.830 --> 00:45:14.190
So if we can identify, let's say, index clinics

869
00:45:14.190 --> 00:45:17.103
that are in these places of high STI burden,

870
00:45:18.330 --> 00:45:20.970
then might there be a way to, if we reach those,

871
00:45:20.970 --> 00:45:22.980
that there will be some spillover effect

872
00:45:22.980 --> 00:45:25.230
in other parts of the community which can also help us

873
00:45:25.230 --> 00:45:27.033
reach that coverage.

874
00:45:27.960 --> 00:45:31.710
This is a paper by some of our colleagues at Yale,

875
00:45:31.710 --> 00:45:34.890
including my friend Donna Spiegelman and Sten Vermund

876
00:45:34.890 --> 00:45:37.530
that looked at that in one particular study.

877
00:45:37.530 --> 00:45:39.300
So it is something that we're trying to think about,

878
00:45:39.300 --> 00:45:44.300
is can we look at, can we use a targeted strategy,

879
00:45:45.300 --> 00:45:47.640
identify index healthcare facilities

880
00:45:47.640 --> 00:45:49.470
and then estimate some spillover effect

881
00:45:49.470 --> 00:45:51.870
to other parts of the community,

882
00:45:51.870 --> 00:45:54.750
which I think is likely impossible.

883
00:45:54.750 --> 00:45:58.950
And then the last component is the health equity component.

884
00:45:58.950 --> 00:46:02.013
Again, these are local community coalitions.

885
00:46:03.330 --> 00:46:05.193
They're both local and regional.

886
00:46:06.630 --> 00:46:08.340
In Dallas, we have Abounding Prosperity

887
00:46:08.340 --> 00:46:10.863
as the lead organization.

888
00:46:11.880 --> 00:46:14.760
And in Montgomery with the Medical Advocacy &amp; Outreach,

889
00:46:14.760 --> 00:46:15.593
or MAO.

890
00:46:16.710 --> 00:46:19.080
And then the regional organizing agency,

891
00:46:19.080 --> 00:46:21.703
a coordinating agency is the Southern Black Policy

892
00:46:21.703 --> 00:46:26.100
&amp; Advocacy Network, which is led by a black

893
00:46:26.100 --> 00:46:28.803
openly gay man, open living with HIV.

894
00:46:29.910 --> 00:46:33.000
And next week he might be the first openly black gay man

895
00:46:33.000 --> 00:46:36.450
with HIV serving in the Texas State House.

896
00:46:36.450 --> 00:46:38.600
He's on the ballot, I think he's gonna win.

897
00:46:39.930 --> 00:46:44.790
So this was also not without challenges.

898
00:46:44.790 --> 00:46:47.283
The first is that when we started this,

899
00:46:48.270 --> 00:46:50.010
we used a centralized model,

900
00:46:50.010 --> 00:46:52.410
which was with the Black AIDS Institute,

901
00:46:52.410 --> 00:46:54.210
which is, many of you may know it.

902
00:46:54.210 --> 00:46:58.290
It is a vitally important, famed institution

903
00:46:58.290 --> 00:47:00.453
in the black community and for the country.

904
00:47:01.740 --> 00:47:03.570
That partnership did not work out.

905
00:47:03.570 --> 00:47:08.570
And so the challenge with the centralized model

906
00:47:08.630 --> 00:47:10.710
is that, if the partnership doesn't work out,

907
00:47:10.710 --> 00:47:12.300
you have to start all over

908
00:47:12.300 --> 00:47:14.400
because if you only had one partner.

909
00:47:14.400 --> 00:47:17.040
So we thought that introduced too much instability,

910
00:47:17.040 --> 00:47:22.040
but we thought that made us

911
00:47:22.290 --> 00:47:26.160
too vulnerable to have one implementing partner.

912
00:47:26.160 --> 00:47:27.960
And so we decided to go to a local model,

913
00:47:27.960 --> 00:47:30.900
which I think was more culturally appropriate

914
00:47:30.900 --> 00:47:33.100
in many of these places to do a local model.

915
00:47:34.680 --> 00:47:38.310
So that has worked out well so far.

916
00:47:38.310 --> 00:47:41.610
Another challenge is that Medical Advocacy &amp; Outreach,

917
00:47:41.610 --> 00:47:45.660
they filed for bankruptcy, I don't know,

918
00:47:45.660 --> 00:47:47.463
a week ago, two weeks ago.

919
00:47:48.360 --> 00:47:53.360
And so, we'd already learned from our experience

920
00:47:53.730 --> 00:47:57.930
with having our health equity component

921
00:47:57.930 --> 00:47:59.520
focused in one agency.

922
00:47:59.520 --> 00:48:03.300
And so we expect that for many of these agencies

923
00:48:03.300 --> 00:48:06.240
and many of these areas that we will have

924
00:48:06.240 --> 00:48:10.950
some that struggle and that might cease operations

925
00:48:10.950 --> 00:48:14.490
or change management or change ownership.

926
00:48:14.490 --> 00:48:17.310
So we don't treat this as an isolated incident.

927
00:48:17.310 --> 00:48:19.860
This is one of the structural factors

928
00:48:19.860 --> 00:48:22.980
that impacts HIV prevention goals among black MSM.

929
00:48:22.980 --> 00:48:25.110
What we had to do was figure out how do we build

930
00:48:25.110 --> 00:48:27.420
in some resilience in this model

931
00:48:27.420 --> 00:48:29.460
so that when those changes occur,

932
00:48:29.460 --> 00:48:31.500
which we expect will continue to occur

933
00:48:31.500 --> 00:48:33.783
as we do this in the other cities,

934
00:48:36.959 --> 00:48:38.280
that we don't become so unstable

935
00:48:38.280 --> 00:48:41.130
that we can't complete this intervention in.

936
00:48:41.130 --> 00:48:43.470
So what we did was the coalition

937
00:48:43.470 --> 00:48:46.200
happened to already be built in Montgomery.

938
00:48:46.200 --> 00:48:49.290
MAO had already designed a coalition.

939
00:48:49.290 --> 00:48:52.020
And so we tried to center the intervention

940
00:48:52.020 --> 00:48:55.980
as part of a co-owned community coalition,

941
00:48:55.980 --> 00:48:58.740
that it didn't belong to the organizing agency.

942
00:48:58.740 --> 00:49:01.290
So that if the organizing agency changed hands

943
00:49:01.290 --> 00:49:03.792
or for some reason they decided they didn't want to do it

944
00:49:03.792 --> 00:49:06.570
or they didn't meet grant contract deliverables,

945
00:49:06.570 --> 00:49:10.030
that the coalition could still function

946
00:49:11.310 --> 00:49:13.860
for a time till we found another agency to lead

947
00:49:13.860 --> 00:49:16.953
to serve as the lead organizing agency.

948
00:49:19.500 --> 00:49:22.050
And so just things that consider,

949
00:49:22.050 --> 00:49:24.213
as having gone through all these things.

950
00:49:25.620 --> 00:49:27.030
One thing that we realized,

951
00:49:27.030 --> 00:49:29.880
even though we're conducting a randomized control trial,

952
00:49:29.880 --> 00:49:34.413
that we have to figure out ways to adapt.

953
00:49:35.790 --> 00:49:39.210
We say sometimes, "We have to bend or we're gonna break."

954
00:49:39.210 --> 00:49:40.893
And I think we've seen that,

955
00:49:42.184 --> 00:49:44.640
that we try to figure out how we're gonna sort of

956
00:49:44.640 --> 00:49:46.500
adjust as we go along.

957
00:49:46.500 --> 00:49:48.840
So I would consider using a design that will allow you

958
00:49:48.840 --> 00:49:50.793
to adjust as you implement.

959
00:49:51.750 --> 00:49:56.160
What you see on the screen, this is a slide from a talk

960
00:49:56.160 --> 00:50:00.000
I saw Donna Spiegelman give about this approach

961
00:50:00.000 --> 00:50:01.590
that her and her team have come up with

962
00:50:01.590 --> 00:50:03.120
called Learn as You Go.

963
00:50:03.120 --> 00:50:05.640
And so we are looking at how do we implement

964
00:50:05.640 --> 00:50:07.740
this Learn As You Go into the study

965
00:50:07.740 --> 00:50:09.990
that's already been designed.

966
00:50:09.990 --> 00:50:13.170
It would be best to have thought about this to incorporate

967
00:50:13.170 --> 00:50:15.240
this from the beginning when we're designing the study,

968
00:50:15.240 --> 00:50:16.833
but we didn't have that luxury.

969
00:50:17.670 --> 00:50:19.530
We didn't have that foresight, I should say.

970
00:50:19.530 --> 00:50:21.840
So we're looking at how do we do this now

971
00:50:21.840 --> 00:50:25.140
so that we're not just sort of making changes here and there

972
00:50:25.140 --> 00:50:26.820
based on our subjective experience,

973
00:50:26.820 --> 00:50:30.720
but that that we have some data-driven estimates

974
00:50:30.720 --> 00:50:33.120
about where we need to make changes and how much.

975
00:50:33.120 --> 00:50:34.710
So I think this offers great promise

976
00:50:34.710 --> 00:50:36.510
to the work that we're doing.

977
00:50:36.510 --> 00:50:39.300
Community engagement is key, and has to be integrated

978
00:50:39.300 --> 00:50:41.130
with scientific considerations.

979
00:50:41.130 --> 00:50:43.500
You can't do it with just scientific model.

980
00:50:43.500 --> 00:50:46.080
You can't do it with just listening to the community voices

981
00:50:46.080 --> 00:50:48.730
without considering the science, you have to do both.

982
00:50:49.590 --> 00:50:51.600
There really is a need for more implementation

983
00:50:51.600 --> 00:50:53.400
and prevention science methods

984
00:50:53.400 --> 00:50:57.810
that respond to the realities of life for black communities.

985
00:50:57.810 --> 00:51:01.230
I mentioned the challenges of doing Starfish sampling

986
00:51:01.230 --> 00:51:03.980
in some of these places, the challenges of peer support

987
00:51:05.003 --> 00:51:06.720
and social media influence in some of these places.

988
00:51:06.720 --> 00:51:09.780
So our methods need to really be able to respond

989
00:51:09.780 --> 00:51:12.750
to the realities in some of these communities

990
00:51:12.750 --> 00:51:14.790
'cause they're not always designed with

991
00:51:14.790 --> 00:51:17.430
that cultural logic in mind.

992
00:51:17.430 --> 00:51:19.110
And again, it's not trivial.

993
00:51:19.110 --> 00:51:20.370
Might seem so.

994
00:51:20.370 --> 00:51:22.710
When you're trying to do it, you see where it comes out.

995
00:51:22.710 --> 00:51:25.650
And then the last consideration is that we need

996
00:51:25.650 --> 00:51:30.270
more rigorous design options that are not limited

997
00:51:30.270 --> 00:51:33.600
to the RCT or that can at least enhance the RCT.

998
00:51:33.600 --> 00:51:37.650
And I think LAGO might be one thing that could enhance

999
00:51:37.650 --> 00:51:39.870
what we're trying to do with RCTs.

1000
00:51:39.870 --> 00:51:42.750
But if RCTs and some are the only things we have,

1001
00:51:42.750 --> 00:51:45.860
it really is hard for us to test some of these interventions

1002
00:51:45.860 --> 00:51:48.390
in some of these places, given the constraints

1003
00:51:48.390 --> 00:51:50.583
that are already embedded within them.

1004
00:51:51.960 --> 00:51:55.320
So I wanna just acknowledge a lot of people

1005
00:51:55.320 --> 00:51:57.360
involved in this, including the people

1006
00:51:57.360 --> 00:51:58.950
who support this through funding.

1007
00:51:58.950 --> 00:52:00.330
And that's what you see on your screen,

1008
00:52:00.330 --> 00:52:04.083
HPTN and many NIH institutes.

1009
00:52:05.580 --> 00:52:07.600
And then I did want to just say

1010
00:52:08.700 --> 00:52:13.050
sort of in a way of dedication to Dr. Dawn Smith

1011
00:52:13.050 --> 00:52:16.080
who was a very key part of this study

1012
00:52:16.080 --> 00:52:17.130
from the very beginning.

1013
00:52:17.130 --> 00:52:19.860
She is scienced at the CDC.

1014
00:52:19.860 --> 00:52:24.860
She led the development of the PrEP guidelines for the US.

1015
00:52:25.080 --> 00:52:30.030
She died a few days ago, and I will miss her immensely.

1016
00:52:30.030 --> 00:52:31.800
But the work that you see here and the things

1017
00:52:31.800 --> 00:52:35.190
that we're doing really is part of her contribution

1018
00:52:35.190 --> 00:52:39.840
to HIV prevention, practice, but also prevention science.

1019
00:52:39.840 --> 00:52:41.253
And thank you.

1020
00:52:47.400 --> 00:52:49.863
<v ->Thank you so much, Dr. Nelson.</v>

1021
00:52:51.647 --> 00:52:53.400
This is such a great presentation.

1022
00:52:53.400 --> 00:52:57.630
We only have two minutes left, and so I do wanna make sure

1023
00:52:57.630 --> 00:53:01.803
that there are any questions that you're able to answer.

1024
00:53:06.810 --> 00:53:09.760
<v ->Yep, I can stick around and see if there's any questions.</v>

1025
00:53:11.190 --> 00:53:14.519
<v ->Yeah, we're hitting on. Anyone have any questions in that?</v>

1026
00:53:14.519 --> 00:53:17.403
I'm looking. Okay, anyone has any hands up?

1027
00:53:20.490 --> 00:53:23.877
Okay, we are like right at the three o'clock mark,

1028
00:53:23.877 --> 00:53:27.510
but if there are any questions or anything comes up,

1029
00:53:27.510 --> 00:53:31.290
please feel free to email me or, you know,

1030
00:53:31.290 --> 00:53:33.090
and I can pass along to Dr. Nelson

1031
00:53:33.090 --> 00:53:37.020
or email Dr. Nelson directly.

1032
00:53:37.020 --> 00:53:40.893
Just wanna just thank you again so much.

1033
00:53:42.210 --> 00:53:43.680
<v ->Yeah, it's my pleasure.</v>

1034
00:53:43.680 --> 00:53:45.600
It's always a pleasure working with Ready,

1035
00:53:45.600 --> 00:53:47.700
and I appreciate all the work that y'all are doing,

1036
00:53:47.700 --> 00:53:49.140
including helping us.

1037
00:53:49.140 --> 00:53:52.230
I didn't say that we had a Ready consultation,

1038
00:53:52.230 --> 00:53:53.430
and it's been very helpful,

1039
00:53:53.430 --> 00:53:55.650
so thank you again for the opportunity.

1040
00:53:55.650 --> 00:53:57.630
<v ->Yeah, great talk. Great work.</v>

1041
00:53:57.630 --> 00:53:59.553
Really important work, LaRon.