Ending the HIV Epidemic: Identifying Barriers and Facilitators to Implement Molecular HIV Surveillance to Develop Real-Time Cluster Detection and Response Interventions for Local Communities
Abstract
:1. Introduction
2. Materials and Methods
2.1. Sampling
2.2. Interview Guide and Data Collection
2.3. Data Analysis
3. Results
3.1. Themes
3.1.1. Strengths and Limitations in Utilizing HIV Surveillance Data for Real-Time CDR
So, the data is analyzed by our HIV surveillance and epidemiology team. They run this data and whenever a new cluster is identified then that’s sent to my team to follow up with those individuals who break the cycle of transmission. When we identify a cluster, those individuals they’re sent to the HIV partner services team that we would assign for field investigations and we’ve worked with those clients to understand their partners and notify their partners in that cluster.
So, the biggest challenge is that different systems are housed in different bureaucratic areas, different systems that necessarily share unique identifying variables. So, for example, I don’t have actual access to eHARS and there is no variable in the counseling and testing system that matches a variable in eHARS. So, we have to do kind of a fuzzy match based on name and date of birth to try to connect testing data to surveillance data.
3.1.2. Limitations of MHS Data Due to Medical Provider and Staff Concerns Related to CDR
The CDC has requirements for the number of genetic sequences that you’re supposed to be receiving in your area. Towards the end of last year, we noticed that there was a decrease. And this was even before COVID. I think a large part has to do with providers not ordering as many genetic sequences. Because in the past, they would use that information to kind of tailor their treatment protocols. But now with the treatments for HIV being improved, they don’t need that information from the genetic sequences.(Participant 16-South)
I mean it’s probably been a consistent message that just timeliness of data is getting providers to report. Labs have automated reporting for the most part, that’s pretty quick and timely and that’s really improved in the past few years and made a world of difference. And then you put COVID on top of all of that and it’s a challenge.(Participant 18-Midwest)
3.1.3. Divergent Perspectives on the Effectiveness of Partner Services
We use the [partner service] data to identify the molecular clusters and then, the underlying transmission clusters, so, then we can develop high impact interventions or prevention services. We can get individuals linked or re-linked into care. Offer... people that test negative, connected with PrEP services. The goal is to stop the disease transmission.(Participant 16-South)
…I think there is [epidemiological] data that partner services is uniquely able to collect. I talked about that at the beginning: risk information, substance use, psychosocial. They also can connect because partner services in almost every jurisdiction does try to touch or connect with every person who has got an HIV diagnosis or a new syphilis diagnosis and other jurisdictions might do other things like a gonorrhea, etcetera.(Participant 18-Midwest)
…it’s more often than not, the HIV cases that are generated for partner services interview are too old. There have been times when a nine-month-old case is assigned to a disease intervention specialist to conduct an interview. And this is a person that was diagnosed with HIV nine months ago has done whatever he/she or they did after learning status hopefully got into care, has made peace, and is living life and then the government calls saying, “We want to talk to you and we want you to give us your sexual partners’ names”. It kills our credibility and doesn’t provide us really good data. So, the timeliness between an actual positive test result and the partner services interview is really critical.(Participant 19-Midwest)
3.1.4. Optimism But Reluctance about SNS
I think it’s a great tool [SNS], and that I’m absolutely optimistic and want to continue to see if it brings in, or if we find new positives. I mean, we were happy to see that people who’ve never tested before. Our population, of course it was the Latino population. So, we assumed that there were a lot of undocumented people who maybe would have not had the opportunity to test or were afraid to go anywhere to test, so that was positive…I think that I’m hopeful and I’m waiting to find [newly diagnosed PLWH].(Participant 15-South)
So, there’s quite a bit of upfront commitment for SNS. I’m guessing…a cluster looks different each time. Your planning has to change every [time], you know, if it looks drastically different, like I can’t do the same things or say the same things if it’s a predominantly Hispanic, Latino, you know cluster versus a diverse younger cluster, right? So, there’s quite a bit of upfront commitment. So, you do need staff who are already trained on it that you could pull from.
3.1.5. Enhancing Partnerships with Community Stakeholders to Address MHS-Related Concerns
I think that if we were able to take on a more peer-to-peer centered approach, I think that would help in people being more receptive to speaking with the health department if they see themselves and the people who are reaching out to them. Building that out would be important. I think just having the resources and capacity to offer real services within the field would help build trust and also acceptable at this type of program within the community and having more community members and providers just talk about the interventions and be clear about what the interventions are and how they can benefit their clients, their communities, their peers would be helpful and building that trust.
It’s [CDR] created a lot of concern for advocates and activists in many other jurisdictions… there are concerns about the abilities or the perception that cluster analysis can determine directionality of infection and people’s concern that they may be sort of identified as a person that infected someone else and are there legal implications and criminalization implications that are associated with data that might be able to tell that I was the person that infected that person. The data don’t do that. They don’t determine directionality, so that is just a perception. But that is the perception of what MHS could do and the danger that it could potentially cause is something that folks are worried about.
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Oster, A.M.; Lyss, S.B.; McClung, R.P.; Watson, M.; Panneer, N.; Hernandez, A.L.; Buchacz, K.; Robilotto, S.E.; Curran, K.G.; Hassan, R.; et al. HIV cluster and outbreak detection and response: The science and experience. Am. J. Prev. Med. 2021, 61, S130–S142. [Google Scholar] [CrossRef] [PubMed]
- CDC. Funding Opportunity Announcement (FOA) PS18-1802: Integrated Human Immunodeficiency Virus (HIV) Surveillance and Prevention Programs for Health Departments; Centers for Disease Control and Prevention: Atlanta, GA, USA, 2018. [Google Scholar]
- CDC. Detecting and Responding to HIV Transmission Clusters: A Guide for Health Departments; Centers for Disease Control and Prevention: Atlanta, GA, USA, 2018. [Google Scholar]
- Han, X.; Zhao, B.; An, M.; Zhong, P.; Shang, H. Molecular network-based intervention brings us closer to ending the HIV pandemic. Front. Med. 2020, 14, 136–148. [Google Scholar] [CrossRef] [PubMed]
- France, A.M.; Oster, A.M. The promise and complexities of detecting and monitoring HIV transmission clusters. J. Infect. Dis. 2020, 221, 1223–1225. [Google Scholar] [CrossRef] [PubMed]
- Health and Human Services. Ending the HIV Epidemic: A Plan for America. February 2019. Available online: https://www.hiv.gov/ending-hiv-epidemic (accessed on 15 February 2019).
- Oster, A.M.; Panneer, N.; Lyss, S.B.; McClung, R.P.; Watson, M.; Saduvala, N.; Ocfemia, M.C.B.; Linley, L.; Switzer, W.M.; Wertheim, J.O.; et al. Increasing capacity to detect clusters of rapid HIV transmission in varied populations—United States. Viruses 2021, 13, 577. [Google Scholar] [CrossRef] [PubMed]
- Mehta, S.R.; Schairer, C.; Little, S. Ethical issues in HIV phylogenetics and molecular epidemiology. Curr. Opin. HIV AIDS 2019, 14, 221–226. [Google Scholar] [CrossRef] [PubMed]
- Cranston, K. Molecular HIV Surveillance: Balancing Outbreak Detection and Control and the Rights of Persons Living With HIV. Am. J. Public Health 2020, 110, 276–278. [Google Scholar] [CrossRef] [PubMed]
- The Center for HIV Law and Policy. Is Molecular HIV Surveillance Worth the Risk? 2019. Available online: https://www.hivlawandpolicy.org/resources/hiv-molecular-surveillance-worth-risk-center-hiv-law-and-policy-september-2019 (accessed on 15 December 2020).
- Molldrem, S.; Smith, A.K. Reassessing the ethics of molecular HIV surveillance in the era of cluster detection and response: Toward HIV data justice. Am. J. Bioeth. 2020, 20, 10–23. [Google Scholar] [CrossRef] [PubMed]
- Dawson, L.; Benbow, N.; Fletcher, F.E.; Kassaye, S.; Killelea, A.; Latham, S.R.; Lee, L.M.; Leitner, T.; Little, S.J.; Mehta, S.R.; et al. Addressing Ethical Challenges in US-Based HIV Phylogenetic Research. J. Infect. Dis. 2020, 222, 1997–2006. [Google Scholar] [CrossRef] [PubMed]
- Schairer, C.E.; Mehta, S.R.; Vinterbo, S.A.; Hoenigl, M.; Kalichman, M.; Little, S.J. Trust and Expectations of Researchers and Public Health Departments for the Use of HIV Molecular Epidemiology. AJOB Empir. Bioeth. 2019, 10, 201–213. [Google Scholar] [CrossRef] [PubMed]
- Poon, A.F.Y. Near real-time monitoring of HIV transmission hotspots from routine HIV genotyping: An implementation case study. Lancet HIV 2016, 3, e231–e238. [Google Scholar] [CrossRef] [Green Version]
- Gore, D.J.; Schueler, K.; Ramani, S.; Uvin, A.; Phillips, G.; McNulty, M.; Fujimoto, K.; Schneider, J. HIV Response Interventions that Integrate HIV Molecular Cluster and Social Network Analysis: A Systematic Review. AIDS Behav. 2022, 26, 1750–1792. [Google Scholar] [CrossRef]
- Rich, S.N.; Richards, V.L.; Mavian, C.N.; Switzer, W.M.; Rife Magalis, B.; Poschman, K.; Geary, S.; Broadway, S.E.; Bennett, S.B.; Blanton, J.; et al. Employing molecular phylodynamic methods to identify and forecast HIV transmission clusters in public health settings: A qualitative study. Viruses 2020, 12, 921. [Google Scholar] [CrossRef] [PubMed]
- Shook, A.G.; Buskin, S.E.; Golden, M.; Dombrowski, J.C.; Herbeck, J.; Lechtenberg, R.J.; Kerani, R. Community and Provider Perspectives on Molecular HIV Surveillance and Cluster Detection and Response for HIV Prevention: Qualitative Findings From King County, Washington. J. Assoc. Nurses AIDS Care 2022, 33, 270–282. [Google Scholar] [CrossRef]
- Morgan, E.; Skaathun, B.; Nikolopoulos, G.K.; Paraskevis, D.; Williams, L.D.; Smyrnov, P.; Friedman, S.R.; Schneider, J.A. A Network Intervention to Locate Newly HIV Infected Persons Within MSM Networks in Chicago. AIDS Behav. 2019, 23, 15–20. [Google Scholar] [CrossRef]
- Smyrnov, P.; Williams, L.D.; Korobchuk, A.; Sazonova, Y.; Nikolopoulos, G.K.; Skaathun, B.; Morgan, E.; Schneider, J.; Vasylyeva, T.I.; Friedman, S.R. Risk network approaches to locating undiagnosed HIV cases in Odessa, Ukraine. J. Int. AIDS Soc. 2018, 21, e25040. [Google Scholar] [CrossRef] [PubMed]
- Morgan, E.; Skaathun, B.; Schneider, J.A. Sexual, Social, and Genetic Network Overlap: A Socio-Molecular Approach Toward Public Health Intervention of HIV. Am. J. Public Health 2018, 108, 1528–1534. [Google Scholar] [CrossRef] [PubMed]
- Fusch, P.I.; Ness, L.R. Are we there yet? Data saturation in qualitative research. Qual. Rep. 2015, 20, 1408. [Google Scholar] [CrossRef]
- Braun, V.; Clarke, V. Using thematic analysis in psychology. Qual. Res. Psychol. 2006, 3, 77–101. [Google Scholar] [CrossRef]
- NVivo. 2022. Available online: http://www.qsrinternational.com/product/nvivo-mac (accessed on 15 January 2022).
- Health Resources & Services Administration: Ryan White Ending the HIV Epidemic in the U.S. Initiative 2021 Community Engagement Listening Sessions. Available online: https://ryanwhite.hrsa.gov/sites/default/files/ryanwhite/resources/hrsa-ehe-exec-summary-2021.pdf (accessed on 15 January 2022).
- Oster, A.M.; France, A.M.; Panneer, N.; Ocfemia, M.C.B.; Campbell, E.; Dasgupta, S.; Switzer, W.M.; Wertheim, J.O.; Hernandez, A.L. Identifying clusters of recent and rapid HIV transmission through analysis of molecular surveillance data. J. Acquir. Immune Defic. Syndr. 2018, 79, 543. [Google Scholar] [CrossRef] [PubMed]
- Commonwealth Fund. Meeting America’s Public Health Challenge: Recommendations for Building A National Public Health System that Addresses Ongoing and Future Health Crises, Advances Equity, and Earns Trust; The Commonwealth Fund: New York, NY, USA, 2022; Volume 21. [Google Scholar]
- Wallace, M.; Sharfstein, J.M. The patchwork US public health system. New Engl. J. Med. 2022, 386, 1–4. [Google Scholar] [CrossRef] [PubMed]
- Evans, D.; Benbow, N. Ethical Considerations for A Public Health Response Using Molecular HIV Surveillance Data: A Multi-Stakeholder Approach; Project Inform and Northwestern University: Chicago, IL, USA, 2018. [Google Scholar]
- Spieldenner, A.; French, M.; Ray, V.; Minalga, B.; Sardina, C.; Suttle, R.; Castro-Bojorquez, M.; Lewis, O.; Sprague, L. The Meaningful Involvement of People with HIV/AIDS (MIPA): The Participatory Praxis Approach to Community Engagement on HIV Surveillance. J. Community Engagem. Scholarsh. 2022, 14, 1. [Google Scholar] [CrossRef]
- Garcia, M. This Is America: Systemic Racism and Health Inequities Amidst the COVID-19 Pandemic. Soc. Work. Public Health 2021, 37, 105–121. [Google Scholar] [CrossRef]
- Tordoff, D.M.; Minalga, B.; Trejo, A.; Shook, A.; Kerani, R.P.; Herbeck, J.T. Lessons Learned from Community Engagement Regarding Phylodynamic Research with Molecular HIV Surveillance Data. SocArXiv 2022. [Google Scholar] [CrossRef]
- German, D.; Grabowski, M.K.; Beyrer, C. Enhanced use of phylogenetic data to inform public health approaches to HIV among men who have sex with men. Sex. Health 2017, 14, 89–96. [Google Scholar] [CrossRef]
- Lee, L.M.; Heilig, C.M.; White, A. Ethical justification for conducting public health surveillance without patient consent. Am. J. Public Health 2012, 102, 38–44. [Google Scholar] [CrossRef]
- Poon, A.F.; Joy, J.B.; Woods, C.K.; Shurgold, S.; Colley, G.; Brumme, C.J.; Hogg, R.S.; Montaner, J.S.; Harrigan, P.R. The impact of clinical, demographic and risk factors on rates of HIV transmission: A population-based phylogenetic analysis in British Columbia, Canada. J. Infect. Dis. 2015, 211, 926–935. [Google Scholar] [CrossRef] [Green Version]
Variable | n (%) |
---|---|
Region | |
South | 8 (53.3) |
Midwest | 7 (46.7) |
Years of Experience | |
0–4 years | 6 (40.0) |
≥5 years | 9 (60.0) |
Age | |
18–29 | 2 (13.3) |
30–39 | 5 (33.4) |
40–49 | 3 (20.0) |
50–59 | 3 (20.0) |
≥60 | 2 (13.3) |
Race/Ethnicity | |
White, Non-Hispanic | 11 (73.3) |
Hispanic | 3 (20.0) |
Other | 1 (6.7) |
Gender | |
Cisgender Female | 7 (46.7) |
Cisgender Male | 7 (46.7) |
Other | 1 (6.7) |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Garcia, M.; Devlin, S.; Kerman, J.; Fujimoto, K.; Hirschhorn, L.R.; Phillips, G., II; Schneider, J.; McNulty, M.C. Ending the HIV Epidemic: Identifying Barriers and Facilitators to Implement Molecular HIV Surveillance to Develop Real-Time Cluster Detection and Response Interventions for Local Communities. Int. J. Environ. Res. Public Health 2023, 20, 3269. https://doi.org/10.3390/ijerph20043269
Garcia M, Devlin S, Kerman J, Fujimoto K, Hirschhorn LR, Phillips G II, Schneider J, McNulty MC. Ending the HIV Epidemic: Identifying Barriers and Facilitators to Implement Molecular HIV Surveillance to Develop Real-Time Cluster Detection and Response Interventions for Local Communities. International Journal of Environmental Research and Public Health. 2023; 20(4):3269. https://doi.org/10.3390/ijerph20043269
Chicago/Turabian StyleGarcia, Moctezuma, Samantha Devlin, Jared Kerman, Kayo Fujimoto, Lisa R. Hirschhorn, Gregory Phillips, II, John Schneider, and Moira C. McNulty. 2023. "Ending the HIV Epidemic: Identifying Barriers and Facilitators to Implement Molecular HIV Surveillance to Develop Real-Time Cluster Detection and Response Interventions for Local Communities" International Journal of Environmental Research and Public Health 20, no. 4: 3269. https://doi.org/10.3390/ijerph20043269