Shantrel S Canidate, Hannah R Gracy, Sean McIntosh, Yiyang Liu, Rebecca Fisk-Hoffman, Shannon Rich, Carla Mavian, Robert L Cook, Mattia Prosperi, Marco Salemi
{"title":"What to consider when developing a new molecular HIV surveillance tool: Perspectives of key stakeholders working in HIV prevention and treatment.","authors":"Shantrel S Canidate, Hannah R Gracy, Sean McIntosh, Yiyang Liu, Rebecca Fisk-Hoffman, Shannon Rich, Carla Mavian, Robert L Cook, Mattia Prosperi, Marco Salemi","doi":"10.1109/ichi64645.2025.00072","DOIUrl":null,"url":null,"abstract":"<p><p>Developing and validating novel molecular HIV surveillance (MHS) tools capable of predicting the growth and trajectory of localized outbreaks driven by specific transmission clusters is key to the <i>Ending the HIV Epidemic in the United States initiative</i>. This study explored stakeholders' perspectives on HIV prevention and treatment regarding a developing deep-learning framework, <i>DeepDynaForecast,</i> and its ability to predict HIV transmission cluster trajectories and inform decision-making on HIV prevention and treatment scale-up approaches in Florida. We conducted five virtual focus group discussions with 16 clinical health professionals and state and local public health personnel. Focus group discussions were audio-recorded, transcribed using Zoom transcription, and manually coded using a reflexive thematic analysis approach. Overall, participants reported a high level of acceptability for using MHS tools. However, when exploring their perspectives on using the DeepDynaForecast tool,participants discussed their acceptance criteria, including key features that the DeepDynaForecast tool should have and the need to determine the data types the tool should generate to meet their needs and be deemed acceptable. Before implementation, participants felt the tool should undergo extensive software testing, followed by end-users receiving comprehensive training and the developers determining how the DeepDynaForecast tool could integrate with existing MHS tools. Likewise, participants discussed using the data generated by DeepDynaForecast to increase HIV prevention, education, outreach activities, and mobilization efforts in communities where the most HIV diagnoses occur, as well as increase behavioral change communication efforts. Participants also expressed concerns about HIV-related stigma, a potentially dangerous unintended consequence of using existing and new MHS tools. Current MHS tools have helped inform and evaluate HIV prevention and treatment efforts in the US. A novel MHS tool such as DeepDynaForecast may be critical to achieving the Ending the HIV Epidemic (EHE) goals and curbing the spread of HIV in Florida and in the US.</p>","PeriodicalId":73284,"journal":{"name":"IEEE International Conference on Healthcare Informatics. IEEE International Conference on Healthcare Informatics","volume":"2025 ","pages":"588-597"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12345360/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE International Conference on Healthcare Informatics. IEEE International Conference on Healthcare Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ichi64645.2025.00072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/22 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Developing and validating novel molecular HIV surveillance (MHS) tools capable of predicting the growth and trajectory of localized outbreaks driven by specific transmission clusters is key to the Ending the HIV Epidemic in the United States initiative. This study explored stakeholders' perspectives on HIV prevention and treatment regarding a developing deep-learning framework, DeepDynaForecast, and its ability to predict HIV transmission cluster trajectories and inform decision-making on HIV prevention and treatment scale-up approaches in Florida. We conducted five virtual focus group discussions with 16 clinical health professionals and state and local public health personnel. Focus group discussions were audio-recorded, transcribed using Zoom transcription, and manually coded using a reflexive thematic analysis approach. Overall, participants reported a high level of acceptability for using MHS tools. However, when exploring their perspectives on using the DeepDynaForecast tool,participants discussed their acceptance criteria, including key features that the DeepDynaForecast tool should have and the need to determine the data types the tool should generate to meet their needs and be deemed acceptable. Before implementation, participants felt the tool should undergo extensive software testing, followed by end-users receiving comprehensive training and the developers determining how the DeepDynaForecast tool could integrate with existing MHS tools. Likewise, participants discussed using the data generated by DeepDynaForecast to increase HIV prevention, education, outreach activities, and mobilization efforts in communities where the most HIV diagnoses occur, as well as increase behavioral change communication efforts. Participants also expressed concerns about HIV-related stigma, a potentially dangerous unintended consequence of using existing and new MHS tools. Current MHS tools have helped inform and evaluate HIV prevention and treatment efforts in the US. A novel MHS tool such as DeepDynaForecast may be critical to achieving the Ending the HIV Epidemic (EHE) goals and curbing the spread of HIV in Florida and in the US.