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1. Predictors of HIV Molecular Cluster Membership and Implications for Partner Services

Author

Hallmark, Camden J, Luswata, Charles, Del Vecchio, Natascha, Hayford, Christina, Mora, Ricardo, Carr, Michelle, McNeese, Marlene, Benbow, Nanette, Schneider, John A, Wertheim, Joel O, and Fujimoto, Kayo

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Sexually Transmitted Infections, Infectious Diseases, HIV/AIDS, Genetics, Health Disparities, Infection, Good Health and Well Being, Humans, Coinfection, Retrospective Studies, HIV Infections, Cluster Analysis, Genes, Viral, Syphilis, HIV, cluster detection and response, partner services, molecular surveillance, syphilis coinfection, Virology, Clinical sciences
Abstract

Public health surveillance data used in HIV molecular cluster analyses lack contextual information that is available from partner services (PS) data. Integrating these data sources in retrospective analyses can enrich understanding of the risk profile of people in clusters. In this study, HIV molecular clusters were identified and matched to information on partners and other information gleaned at the time of diagnosis, including coinfection with syphilis. We aimed to produce a more complete understanding of molecular cluster membership in Houston, Texas, a city ranking ninth nationally in rate of new HIV diagnoses that may benefit from retrospective matched analyses between molecular and PS data to inform future intervention. Data from PS were matched to molecular HIV records of people newly diagnosed from 2012 to 2018. By conducting analyses in HIV-TRACE (TRAnsmission Cluster Engine) using viral genetic sequences, molecular clusters were detected. Multivariable logistic regression models were used to estimate the association between molecular cluster membership and completion of a PS interview, number of named partners, and syphilis coinfection. Using data from 4,035 people who had a viral genetic sequence and matched PS records, molecular cluster membership was not significantly associated with completion of a PS interview. Among those with sequences who completed a PS interview (n = 3,869), 45.3% (n = 1,753) clustered. Molecular cluster membership was significantly associated with naming 1 or 3+ partners compared with not naming any partners [adjusted odds ratio, aOR: 1.27 (95% confidence interval, CI: 1.08-1.50), p = .003 and aOR: 1.38 (95% CI: 1.06-1.81), p = .02]. Alone, coinfection with syphilis was not significantly associated with molecular cluster membership. Syphilis coinfection was associated with molecular cluster membership when coupled with incarceration [aOR: 1.91 (95% CI: 1.08-3.38), p = .03], a risk for treatment interruption. Enhanced intervention among those with similar profiles, such as people coinfected with other risks, may be warranted.

Published
2023

2. Expanding Medicaid to Reduce Human Immunodeficiency Virus Transmission in Houston, Texas

Author

Lee, Francis, Khanna, Aditya S, Hallmark, Camden J, Lavingia, Richa, McNeese, Marlene, Zhao, Jing, McNeese, Melanie L, Khuwaja, Salma, Ardestani, Babak M, Collier, Nicholson, Ozik, Jonathan, Hotton, Anna L, Harawa, Nina T, Schneider, John A, and Fujimoto, Kayo

Subjects
Applied Economics, Economics, Health Services and Systems, Health Sciences, Human Society, Policy and Administration, Sexual and Gender Minorities (SGM/LGBT*), Infectious Diseases, Prevention, HIV/AIDS, Health Disparities, Sexually Transmitted Infections, Infection, Good Health and Well Being, Humans, Male, HIV, HIV Infections, Homosexuality, Male, Sexual and Gender Minorities, Texas, pre-exposure prophylaxis, computer simulation, data mining, sexual and gender minorities, preventive medicine, Public Health and Health Services, Health Policy & Services, Applied economics, Health services and systems, Policy and administration
Abstract

ContextMedicaid expansion has been nationally shown to improve engagement in the human immunodeficiency virus (HIV) treatment and prevention continua, which are vital steps to stopping the HIV epidemic. New HIV infections in the United States are disproportionately concentrated among young Black men who have sex with men (YBMSM). Houston, TX, is the most populous city in the Southern United States with a racially/ethnically diverse population that is located in 1 of 11 US states that have not yet expanded Medicaid coverage as of 2021.MethodsAn agent-based model that incorporated the sexual networks of YBMSM was used to simulate improved antiretroviral treatment and pre-exposure prophylaxis (PrEP) engagement through Medicaid expansion in Houston, TX. Analyses considered the HIV incidence (number of new infections and as a rate metric) among YBMSM over the next 10 years under Medicaid expansion as the primary outcome. Additional scenarios, involving viral suppression and PrEP uptake above the projected levels achieved under Medicaid expansion, were also simulated.ResultsThe baseline model projected an HIV incidence rate of 4.96 per 100 person years (py) and about 368 new annual HIV infections in the 10th year. Improved HIV treatment and prevention continua engagement under Medicaid expansion resulted in a 14.9% decline in the number of annual new HIV infections in the 10th year. Increasing viral suppression by an additional 15% and PrEP uptake by 30% resulted in a 44.0% decline in new HIV infections in the 10th year, and a 27.1% decline in cumulative infections across the 10 years of the simulated intervention.FindingsSimulation results indicate that Medicaid expansion has the potential to reduce HIV incidence among YBMSM in Houston. Achieving HIV elimination objectives, however, might require additional effective measures to increase antiretroviral treatment and PrEP uptake beyond the projected improvements under expanded Medicaid.

Published
2023

3. Impact of molecular sequence data completeness on HIV cluster detection and a network science approach to enhance detection

Author

Mazrouee, Sepideh, Hallmark, Camden J, Mora, Ricardo, Del Vecchio, Natascha, Carrasco Hernandez, Rocio, Carr, Michelle, McNeese, Marlene, Fujimoto, Kayo, and Wertheim, Joel O

Subjects
Data Management and Data Science, Information and Computing Sciences, Biomedical and Clinical Sciences, HIV/AIDS, Infectious Diseases, Sexually Transmitted Infections, Prevention, 2.2 Factors relating to the physical environment, Infection, Good Health and Well Being, Humans, HIV Infections, Cluster Analysis, Molecular Epidemiology, Molecular Sequence Data, Epidemics, Phylogeny
Abstract

Detection of viral transmission clusters using molecular epidemiology is critical to the response pillar of the Ending the HIV Epidemic initiative. Here, we studied whether inference with an incomplete dataset would influence the accuracy of the reconstructed molecular transmission network. We analyzed viral sequence data available from ~ 13,000 individuals with diagnosed HIV (2012-2019) from Houston Health Department surveillance data with 53% completeness (n = 6852 individuals with sequences). We extracted random subsamples and compared the resulting reconstructed networks versus the full-size network. Increasing simulated completeness was associated with an increase in the number of detected clusters. We also subsampled based on the network node influence in the transmission of the virus where we measured Expected Force (ExF) for each node in the network. We simulated the removal of nodes with the highest and then lowest ExF from the full dataset and discovered that 4.7% and 60% of priority clusters were detected respectively. These results highlight the non-uniform impact of capturing high influence nodes in identifying transmission clusters. Although increasing sequence reporting completeness is the way to fully detect HIV transmission patterns, reaching high completeness has remained challenging in the real world. Hence, we suggest taking a network science approach to enhance performance of molecular cluster detection, augmented by node influence information.

Published
2022

4. Methodological synthesis of Bayesian phylodynamics, HIV-TRACE, and GEE: HIV-1 transmission epidemiology in a racially/ethnically diverse Southern U.S. context

Author

Fujimoto, Kayo, Bahl, Justin, Wertheim, Joel O, Del Vecchio, Natascha, Hicks, Joseph T, Damodaran, Lambodhar, Hallmark, Camden J, Lavingia, Richa, Mora, Ricardo, Carr, Michelle, Yang, Biru, Schneider, John A, Hwang, Lu-Yu, and McNeese, Marlene

Subjects
Biomedical and Clinical Sciences, Public Health, Health Sciences, Infectious Diseases, Women's Health, Minority Health, HIV/AIDS, Prevention, Behavioral and Social Science, Social Determinants of Health, Health Disparities, Sexually Transmitted Infections, 2.5 Research design and methodologies (aetiology), Infection, Good Health and Well Being, Adult, Ethnicity, HIV Infections, HIV-1, Humans, Male, Racial Groups, Texas
Abstract

This study introduces an innovative methodological approach to identify potential drivers of structuring HIV-1 transmission clustering patterns between different subpopulations in the culturally and racially/ethnically diverse context of Houston, TX, the largest city in the Southern United States. Using 6332 HIV-1 pol sequences from persons newly diagnosed with HIV during the period 2010-2018, we reconstructed HIV-1 transmission clusters, using the HIV-TRAnsmission Cluster Engine (HIV-TRACE); inferred demographic and risk parameters on HIV-1 transmission dynamics by jointly estimating viral transmission rates across racial/ethnic, age, and transmission risk groups; and modeled the degree of network connectivity by using generalized estimating equations (GEE). Our results indicate that Hispanics/Latinos are most vulnerable to the structure of transmission clusters and serve as a bridge population, acting as recipients of transmissions from Whites (3.0 state changes/year) and from Blacks (2.6 state changes/year) as well as sources of transmissions to Whites (1.8 state changes/year) and to Blacks (1.2 state changes/year). There were high rates of transmission and high network connectivity between younger and older Hispanics/Latinos as well as between younger and older Blacks. Prevention and intervention efforts are needed for transmission clusters that involve younger racial/ethnic minorities, in particular Hispanic/Latino youth, to reduce onward transmission of HIV in Houston.

Published
2021

9. Expanding Medicaid to Reduce Human Immunodeficiency Virus Transmission in Houston, Texas: Insights From a Modeling Study.

Author

Lee, Francis, Lee, Francis, Khanna, Aditya S, Hallmark, Camden J, Lavingia, Richa, McNeese, Marlene, Zhao, Jing, McNeese, Melanie L, Khuwaja, Salma, Ardestani, Babak M, Collier, Nicholson, Ozik, Jonathan, Hotton, Anna L, Harawa, Nina T, Schneider, John A, Fujimoto, Kayo, Lee, Francis, Lee, Francis, Khanna, Aditya S, Hallmark, Camden J, Lavingia, Richa, McNeese, Marlene, Zhao, Jing, McNeese, Melanie L, Khuwaja, Salma, Ardestani, Babak M, Collier, Nicholson, Ozik, Jonathan, Hotton, Anna L, Harawa, Nina T, Schneider, John A, and Fujimoto, Kayo

Abstract

ContextMedicaid expansion has been nationally shown to improve engagement in the human immunodeficiency virus (HIV) treatment and prevention continua, which are vital steps to stopping the HIV epidemic. New HIV infections in the United States are disproportionately concentrated among young Black men who have sex with men (YBMSM). Houston, TX, is the most populous city in the Southern United States with a racially/ethnically diverse population that is located in 1 of 11 US states that have not yet expanded Medicaid coverage as of 2021.MethodsAn agent-based model that incorporated the sexual networks of YBMSM was used to simulate improved antiretroviral treatment and pre-exposure prophylaxis (PrEP) engagement through Medicaid expansion in Houston, TX. Analyses considered the HIV incidence (number of new infections and as a rate metric) among YBMSM over the next 10 years under Medicaid expansion as the primary outcome. Additional scenarios, involving viral suppression and PrEP uptake above the projected levels achieved under Medicaid expansion, were also simulated.ResultsThe baseline model projected an HIV incidence rate of 4.96 per 100 person years (py) and about 368 new annual HIV infections in the 10th year. Improved HIV treatment and prevention continua engagement under Medicaid expansion resulted in a 14.9% decline in the number of annual new HIV infections in the 10th year. Increasing viral suppression by an additional 15% and PrEP uptake by 30% resulted in a 44.0% decline in new HIV infections in the 10th year, and a 27.1% decline in cumulative infections across the 10 years of the simulated intervention.FindingsSimulation results indicate that Medicaid expansion has the potential to reduce HIV incidence among YBMSM in Houston. Achieving HIV elimination objectives, however, might require additional effective measures to increase antiretroviral treatment and PrEP uptake beyond the projected improvements under expanded Medicaid.

Published
2023

10. Expanding Medicaid to Reduce Human Immunodeficiency Virus Transmission in Houston, Texas

Author

Lee, Francis, primary, Khanna, Aditya S., additional, Hallmark, Camden J., additional, Lavingia, Richa, additional, McNeese, Marlene, additional, Zhao, Jing, additional, McNeese, Melanie L., additional, Khuwaja, Salma, additional, Ardestani, Babak M., additional, Collier, Nicholson, additional, Ozik, Jonathan, additional, Hotton, Anna L., additional, Harawa, Nina T., additional, Schneider, John A., additional, and Fujimoto, Kayo, additional

Published
2022
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11. HIP HOP for HIV Awareness: Using Hip Hop Culture to Promote Community-Level HIV Prevention

Author

Hill, Mandy J., Hallmark, Camden J., McNeese, Marlene, Blue, Nike, and Ross, Michael W.

Abstract

The goal of this paper was to determine the effectiveness of the HIP HOP for HIV Awareness intervention, an innovative model utilising an exchange of an HIV test for a hip hop concert ticket, in a metropolitan city among African American youth and young adults. A subset of intervention participants participated in standardised testing, sex education and pre/post test administration. Data were analysed to identify changes in knowledge and attitudes with respect to HIV and sexually transmitted infections pre/post the educational session. An analysis of knowledge revealed variance in the pre- and post-assessment findings among participants receiving the intervention. Level of education and gender significantly influenced the variance in knowledge discerned from the pre- and post-assessment among participants. Two three-level significant interactions emerged from the analysis of variance: knowledge, education and gender; and knowledge, education and race/ethnicity. Programme findings suggest that an increase in knowledge and improved self-perceptions related to attitudes are the result of a brief, HIV-focused community-based intervention among young adults.

Published
2014
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13. Fourth Annual Summer Research Summit on Health Equity Organized by the Center of Excellence in Health Equity, Training and Research, Baylor College of Medicine, Houston, Texas 77030, USA on May 20, 2021

Author

Naik, Aanand, primary, Rajagopal, Abbhirami, additional, Floyd, Adam, additional, Gil, Adriana, additional, Tepede, Aisha, additional, Koroma, Aisha, additional, Deslandes, Aisha, additional, Graf, Akua, additional, Ruiz-Velasco, Alejandra, additional, Reyna-Carrillo, Alexa, additional, Alvarenga, Alexandra, additional, Awoseyi, Alexia, additional, Hernandez, Alexis, additional, Lawrence, Alexis, additional, Asghar-Ali, Ali, additional, Abacan, Allyssa, additional, Adams, Alyce, additional, Khan, Alyna, additional, McGregor, Alyson, additional, Hansen, Alyssa, additional, Johnson, Amari, additional, Coj, Andrea, additional, Vick, Andrea, additional, Tatem, Andria, additional, Aggarwal, Anjali, additional, Deendyal, Anjali, additional, Blake, Ann, additional, Awazi, Annabella, additional, VanHorn, Anne, additional, Marathe, Anuj, additional, Jayaram, Anusha, additional, Adams, April, additional, Hall, Arabella, additional, Heredia, Ariana, additional, Chavarria, Ariana, additional, Morrow, Asha, additional, Butler, Ashley, additional, Hodges, Asia, additional, Mejia, Aura, additional, Patel, Avani, additional, Hernandez, Ayleen, additional, Akande, Benjamin, additional, Felix-Okoroji, Blessing, additional, Garcia, Brisa, additional, Jenna, Buckleitner, additional, Fischer, Callie, additional, Hallmark, Camden, additional, Coren, Cara, additional, Ramos, Carlos, additional, Gambala, Cecilia, additional, Guillory, Charleta, additional, Livingston, Chelsea, additional, Onyejiaka, Chioma, additional, Callender, Chishinga, additional, Aldrich, Christina, additional, Largaespada, Christopher, additional, Bocchini, Claire, additional, Cochran, Craig, additional, Sherman, Danielle, additional, Gonzales, Danielle, additional, Venzon, David, additional, Wittkower, David, additional, Thompson, Debbe, additional, Thompson, Deborah, additional, Eseonu, Debra, additional, Dongarwar, Deepa, additional, Rospigliosi, Delia, additional, Smart, Denise, additional, Velazquez, Denisse, additional, Lockett, Derek, additional, Nwogu-Onyemkpa, Eberechi, additional, Byrne, Elizabeth, additional, Lopez, Elyse, additional, Dybbro, Eric, additional, Storch, Eric, additional, Onwuegbuchu, Erica, additional, Valdes, Erica, additional, Donovan, Erin, additional, Williams, Eunique, additional, Keil, Evan, additional, Ihekweazu, Faith, additional, Rosiji, Felicia, additional, Espinoza-Candelaria, Gabriela, additional, Chmaitelli, Gabriella, additional, Tavera, Gabriella, additional, Oneal, Gail, additional, Barbut, Gal, additional, Tonpouwo, Gauvain, additional, Carrum, George, additional, DeFelice, Gina, additional, Salihu, Hamisu, additional, Haq, Heather, additional, Heslop, Helen, additional, Lester, Houston, additional, Ezenwabachili, Ifeoma, additional, Gautham, Ila, additional, Powell, Jacquelin, additional, Alleyn, Jaime, additional, King, Jasmine, additional, Rivero, Jaydira, additional, Chung, Jayer, additional, Dave, Jayna, additional, Raphael, Jean, additional, Bryan, Jen, additional, Haug, Jendi, additional, Bryan, Jennifer, additional, Blau, Jenny, additional, Bellamy, Jerry, additional, Medrano, Jessica, additional, Ramirez, Jessica, additional, Greely, Jocelyn, additional, Atkinson, Jonnae, additional, Miranda, Jorge, additional, Dominguez, Jose, additional, Roca, Jose, additional, Mills, Joseph, additional, Hamer, Joshua, additional, Muñiz, Joshua, additional, Ogu, Julliet, additional, Gibbs, Karen, additional, Johnson, Karen, additional, Riggins, Karen, additional, Fredricks, Karla, additional, Lopez, Keila, additional, Williams, Kellie, additional, Peters, Keyishi, additional, Hyein, Kil, additional, Hill, LaQuisa, additional, Weinstein, Lee, additional, Shay, Lena, additional, Lefevre, Lentz, additional, Ross, Lindy, additional, Noll, Lisa, additional, Akpati, Lois, additional, Crear, Lorin, additional, Puryear, Lucy, additional, Coleman, Maame, additional, Vasudevan, Madhuri, additional, Miller, Malachi, additional, Vigil-Mallette, Maria, additional, Jaramillo, Maria, additional, Chacko, Mariam, additional, Baroni, Mariana, additional, Murillo, Mariana, additional, Marroquin, Maricarmen, additional, Masciale, Marina, additional, McNeese, Marlene, additional, Austin, Martinez, additional, Koller, Matthew, additional, Lee, Maya, additional, Nourian, Maziar, additional, Abadom, Megan, additional, Sebastian, Meghna, additional, Adera, Meheret, additional, Laracuente, Mei-Lei, additional, Lopez, Michelle, additional, Wright, Michelle, additional, Montero-Baker, Miguel, additional, Gonzalez, Monica, additional, Adelene, Morrow, additional, Adeyeye, Mosope, additional, Qazilbash, Muzaffar, additional, Walia, Namrata, additional, Shenoi, Nancy, additional, Rodriguez, Natalia, additional, Mukdadi, Naya, additional, Saini, Neeraj, additional, Olvera, Norma, additional, Chris-Rotimi, Ololade, additional, Hoyer, Paige, additional, Fallah, Parisa, additional, Smith, Peggy, additional, Lulla, Premal, additional, Ehieze, Priscilla, additional, Murali, Priyanka, additional, Head, Rachel, additional, Nwaneri, Rachel, additional, Wanser, Rachelle, additional, Lyn, Racquel, additional, Kamble, Rammurti, additional, Gilani, Ramyar, additional, Martinez, Raquel, additional, Asaithambi, Rathi, additional, Hatter, Reginald, additional, Wilson, Rhanna, additional, Brown, Ria, additional, Shulman, Robert, additional, Mbilinyi, Robert, additional, Levine, Robert, additional, Avery, Roe, additional, Patel, Romil, additional, Aduhene-Opoku, Roslyn, additional, Mizu, Ruth, additional, Usmani, Saad, additional, Usmani, Sadia, additional, Ahmed, Saeed, additional, Moore, Samantha, additional, Hadidi, Samer, additional, Erabti, Sana, additional, Javed, Sana, additional, Younus, Sana, additional, Mar’Quenda, Sanders, additional, Samaan, Sandy, additional, Alam, Sara, additional, Welty, Sara, additional, Navarro, Sergio, additional, Deering, Shad, additional, Morris, Shaine, additional, Alford, Shana, additional, Siddique, Shangir, additional, Walton, Shantyka, additional, Bhathena, Shayan, additional, O’Bryant, Shelease, additional, Patel, Shital, additional, Idicula, Sindhu, additional, Banu, Sophia, additional, Albert, Sophie, additional, McCullum, Sophie, additional, Lin, Sophie, additional, Okolie, Star, additional, Agarwal, Sunita, additional, Gillespie, Susan, additional, Hussaini, Syed, additional, Hysong, Sylvia, additional, Kang, Tammy, additional, Everett, Tara, additional, Ottesen, Taylor, additional, DiMasi, Tiana, additional, Nguyen, Tien, additional, Harris, Toi, additional, Chen, Tzu-An, additional, Mercado, Vicki, additional, Michael, Victoria, additional, Xie, Victoria, additional, Simonds, William, additional, Gonzalez, Yesenya, additional, Aviles, Yicenia, additional, Thomas, Ynhi, additional, and Pallister, Zachary, additional

Published
2021
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15. Author Correction: Methodological synthesis of Bayesian phylodynamics, HIV-TRACE, and GEE: HIV-1 transmission epidemiology in a racially/ethnically diverse Southern U.S. context

Author

Fujimoto, Kayo, primary, Bahl, Justin, additional, Wertheim, Joel O., additional, Del Vecchio, Natascha, additional, Hicks, Joseph T., additional, Damodaran, Lambodhar, additional, Hallmark, Camden J., additional, Lavingia, Richa, additional, Mora, Ricardo, additional, Carr, Michelle, additional, Yang, Biru, additional, Schneider, John A., additional, Hwang, Lu-Yu, additional, and McNeese, Marlene, additional

Published
2021
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16. Third Annual Summer Research Summit on Health Equity Organized by the Center of Excellence in Health Equity, Training and Research, Baylor College of Medicine, Houston, Texas 77030, USA on June 9, 2020

Author

Rajagopal, Abbhirami, primary, Oluyomi, Abiodun, additional, Turner, Acara E., additional, Johnson, Adedoyin, additional, Flores, Alfred, additional, Echeverria, Alfredo, additional, Asghar-Ali, Ali Abbas, additional, Eason, Alyssa, additional, Orange, Amy, additional, Dube, Andile, additional, Bryan, Andres, additional, Arvizu, Andrew, additional, Mangla, Anil T., additional, Deendyal, Anjali, additional, Ramoutar, Anjali, additional, Jilla, Anna M., additional, Wilson, Annise, additional, Jimenez, Antonio, additional, Green, Ardawna Jael, additional, Patel, Avani, additional, Itani, Aya, additional, Hurley, Ayrea, additional, Biscocho, Bess, additional, Anaele, Beverly I., additional, Felix-Okoroj, Blessing, additional, Adams, Brittany, additional, Wagen, Brooke, additional, Hallmark, Camden J., additional, Johnson, Carole E., additional, Park, Charles, additional, Prasad, Chaya, additional, Lavy, Chris, additional, Ulack, Chris, additional, Maxey, Christina, additional, Nemeh, Christopher, additional, Rodgers, Dakota, additional, Gonzales, Danielle, additional, Whitman, Danielle, additional, Dawson, Darius B., additional, Latini, David, additional, Canales, Debra, additional, Murray, Debra Dianne, additional, Dongarwar, Deepa, additional, Karri, Deepu, additional, Lockett, Derek L., additional, Ratnapradipa, Dhitinut, additional, Maria, Dr. Emma Santa, additional, Ordonez, Edgardo, additional, Acosta, Elisha, additional, Lopez, Elyse, additional, Oduguwa, Emmanuella, additional, Chow, Erica, additional, Williams, Eunique L., additional, Haffizulla, Farzanna S., additional, Cuascut, Fernando X., additional, Salihu, Hamisu M., additional, Caceres, Ibeth, additional, Athanassaki, Ionna D., additional, Atkins, Jacob, additional, Rodriguez, Jacquelin, additional, Perez, Jairo Barrantes, additional, Taylor, Jalyce, additional, Joy, Jeffery, additional, Chang, Jennifer, additional, Lopez, Jennifer, additional, Gaertner-Otto, Jennifer R., additional, Spinler, Jennifer, additional, Norman, Jensine’, additional, Suarez, Joel, additional, Jones, Jordan, additional, Gober, Joslyn, additional, Washington, Jqar, additional, Magrat, Justin, additional, Armknecht, Karen, additional, Dowdell, Katherine, additional, McDeavitt, Kathleen, additional, Kirk, Katie, additional, Tran, Kaylinda, additional, Snook, Kaylyn, additional, Fitzhugh, Kelsey, additional, Jarrett, Kelsey, additional, Hirschi, Kendal D., additional, Ratnapradipa, Kendra, additional, Wiafe, Kobby A., additional, Fisher, Kristen, additional, Carter, Krystal, additional, Rosen, Laura, additional, Garner, Lauren D., additional, Ross, Lindy, additional, Ochoa, Lyssa, additional, Castellanos, Maria I., additional, Vigil, Maria, additional, Marroquin, Maricarmen, additional, Masciale, Marina, additional, Palma, Mario Zuniga, additional, McNeese, Marlene, additional, Bennett, Mary Beth, additional, Morones, Matthew, additional, Abadom, Megan, additional, Sebastian, Meghna, additional, Furgurson, Mia, additional, Vento, Mia, additional, Hole, Michael K., additional, Kauth, Michael R., additional, Ludwig, Michelle, additional, Castelbuono, Morgan, additional, Mvula, Mwamba, additional, Sherif, Nadia, additional, Trinh, Nancy, additional, Rodriguez, Natalia, additional, Guerrero, Natalie, additional, Navejar, Natasha M., additional, Pithia, Neema, additional, Christian, Nick, additional, Huntington-Klein, Nick, additional, Gras, Nicole, additional, Truong, Nina, additional, Perez, Norma, additional, Bakare, Olusegun, additional, Hoyer, Paige, additional, Costello, Patrick, additional, Hardigan, Patrick, additional, Nakata, Paul, additional, McCommon, Rachel, additional, Wanser, Rachelle, additional, Parker, Ramona, additional, Lastrapes, Renee, additional, Brown, Ria, additional, Goin-Kochel, Robin P., additional, McIntire, Russell, additional, Janfaza, Samantha, additional, Willis, Samuel E., additional, Erbati, Sana, additional, Pak, Sang (Sam), additional, Grisales, Sara L., additional, Gustafson, Sarah, additional, Liu, Sean, additional, Navarro, Sergio M., additional, Johnson, Shelby, additional, Pinkstaff, Sherry, additional, Amin, Shetal, additional, Patel, Shital M., additional, Thomas, Sruthi, additional, Farrow, Taelor, additional, Everett, Tara, additional, Fletcher, Terri L., additional, Fasipe, Titilope, additional, Harris, Toi B., additional, Tran, Torrence, additional, Nguyen, Trung, additional, Walker, Valencia P., additional, Mercado, Vicki, additional, Cheuy, Victor, additional, Iwinski, Victoria, additional, Williams, Whitney, additional, Lagor, William, additional, Robinson, William, additional, and Xie, Yue, additional

Published
2020
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22. Brief Report: Discrepancies Between Self-Reported Adherence and a Biomarker of Adherence in Real-World Settings.

Author

Hebel S, Kahn-Woods E, Malone-Thomas S, McNeese M, Thornton L, Sukhija-Cohen A, Patani H, Engeran W, and Daughtridge G

Subjects
Adult, Biomarkers urine, Female, Humans, Male, Middle Aged, Young Adult, Anti-HIV Agents administration & dosage, Anti-HIV Agents blood, HIV Infections drug therapy, HIV-1, Medication Adherence, Self Report
Abstract

Background: Pre-exposure prophylaxis (PrEP) is only effective in preventing new HIV infections when taken consistently. In clinical practice, asking a patient about their adherence (self-report) is the predominant method of assessing adherence to PrEP. Although inexpensive and noninvasive, self-report is subject to social desirability and recall biases. Several clinical trials demonstrate a discrepancy between self-reported adherence and biomarker-based recent adherence. Less is known about the accuracy of self-report in real-world clinical settings. This brief report addresses this knowledge gap and describes the concordance between self-reported adherence and biomarker-based adherence in real-world clinical settings., Methods: A liquid chromatography-mass spectrometry urine test for tenofovir was developed and used clinically to detect recent nonadherence (no dose in at least 48 hours) for each individual. Two clinics' standard operating procedures recommend utilization of the urine-based adherence test for patients who self-report that they are not struggling with adherence. Those who self-report struggling with adherence receive enhanced adherence support without the need for additional testing. The number of results indicating recent nonadherence from these 2 clinics were analyzed to assess the concordance between self-reported adherence and biomarker-based adherence., Results: Across 2 clinics, 3987 tests were conducted from patients self-reporting as "adherent," and 564 [14.1%; 95% confidence interval (CI): 13.1% to 15.2%] demonstrated recent nonadherence with the liquid chromatography-mass spectrometry test. At clinic #1 in Florida, 3200 tests were conducted, and 465 (14.5%; 95% CI: 13.3% to 15.8%) demonstrated recent nonadherence. At clinic #2 in Texas, 787 tests were conducted, and 99 (12.6%; 95% CI: 10.4% to 14.9%) demonstrated recent nonadherence., Conclusions: Utilization of biomarker-based adherence monitoring at these 2 clinics resulted in 564 additional patients receiving enhanced adherence support who otherwise would not have been identified as nonadherent to their prescribed PrEP regimen. These findings suggest that objective adherence monitoring can be used clinically to enable providers to identify nonadherent patients and allocate support services accordingly.

Published
2020
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23. Re-engagement in HIV Care: A Clinical and Public Health Priority.

Author

Grimes RM, Hallmark CJ, Watkins KL, Agarwal S, and McNeese ML

Abstract

As many as 40-50% of persons living with HIV (PLWH) who once were in HIV care are no longer in care. It is estimated that these individuals account for over 60% of HIV transmissions. So, preventing the leaving of care and re-engaging PLWH with care are crucial if the HIV epidemic is to be brought under control. Clinicians can improve retention by keeping in close contact with patients. Governmental public health agencies have great expertise in finding and engaging in care persons with sexually transmitted infections. This expertise can be used to re-engage PLWH with HIV care, but it can only be utilized if the agencies know that someone is out of care. Data on who has left care are in the hands of HIV providers. This requires a close working relationship between HIV providers and public health agencies.

Published
2016
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