What to consider when developing a new molecular HIV surveillance tool: Perspectives of key stakeholders working in HIV prevention and treatment.

Shantrel S Canidate, Hannah R Gracy, Sean McIntosh, Yiyang Liu, Rebecca Fisk-Hoffman, Shannon Rich, Carla Mavian, Robert L Cook, Mattia Prosperi, Marco Salemi
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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.

在开发一种新的HIV分子监测工具时需要考虑什么:从事HIV预防和治疗工作的关键利益相关者的观点。
开发和验证新型艾滋病毒分子监测(MHS)工具,这些工具能够预测由特定传播集群驱动的局部暴发的增长和轨迹,这是“结束美国艾滋病毒流行”倡议的关键。本研究探讨了利益相关者对艾滋病预防和治疗的看法,涉及一个正在开发的深度学习框架,deepdynafforecast,及其预测艾滋病毒传播集群轨迹的能力,并为佛罗里达州艾滋病毒预防和治疗扩大方法的决策提供信息。我们与16名临床卫生专业人员以及州和地方公共卫生人员进行了5次虚拟焦点小组讨论。对焦点小组讨论进行录音,使用Zoom转录,并使用反思性主题分析方法进行手动编码。总体而言,参与者报告了使用MHS工具的高水平可接受性。然而,当探讨他们对使用DeepDynaForecast工具的看法时,参与者讨论了他们的接受标准,包括DeepDynaForecast工具应该具有的关键功能,以及确定工具应该生成的数据类型以满足他们的需求并被认为是可接受的。在实施之前,与会者认为该工具应该进行广泛的软件测试,然后由最终用户接受全面的培训,开发人员确定如何将deepdynafforecast工具与现有的MHS工具集成。同样,与会者讨论了如何利用deepdynafforecast生成的数据,在艾滋病毒诊断最多的社区加强艾滋病毒预防、教育、推广活动和动员工作,以及加强行为改变沟通工作。与会者还表达了对艾滋病毒相关污名的担忧,这是使用现有和新的妇幼保健工具的潜在危险的意外后果。目前MHS工具已经帮助告知和评估美国的艾滋病毒预防和治疗工作。一种新的MHS工具,如deepdynafforecast,可能对实现终结艾滋病毒流行(EHE)的目标和遏制艾滋病毒在佛罗里达州和美国的传播至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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