Mann Sarah C, Barocas Joshua A
Division of Infectious Diseases, University of Colorado School of Medicine, 12631 E. 17th Ave., Mailstop B180, Aurora, CO, 80045, USA.
Division of General Internal Medicine, University of Colorado School of Medicine, Aurora, CO, USA.
Curr HIV/AIDS Rep. 2024 Dec 17;22(1):11. doi: 10.1007/s11904-024-00720-1.
An accurate and comprehensive HIV surveillance system is critical to understanding the burden of HIV infection. Reliable estimates into the surveillance system serve as the cornerstone for HIV prevention and treatment programs. PURPOSE OF REVIEW: In this article, we review the current structure and function of the HIV surveillance system in the US, identify gaps in reporting, and propose multiple potential interventions to augment the HIV surveillance system. RECENT FINDINGS: Recent literature demonstrate that substantial gaps in reporting to health departments from clinical providers exist. These gaps include stigma, knowledge of HIV reporting requirements, inaccurate direct testing estimates, reporting errors, and lack of community engagement. All of these gaps place a substantial burden on health departments, hinder responses, and effect funding. Leveraging community partnerships, technologic advances, and emerging methodologies may fill some of these gaps. Advancements in HIV self-testing, broad community HIV testing, indirect statistical methods, and machine learning bolstered by broad community engagement and oversight could modernize the HIV surveillance system to achieve the Ending the HIV Epidemic goals.
一个准确且全面的艾滋病毒监测系统对于了解艾滋病毒感染负担至关重要。对监测系统的可靠估计是艾滋病毒预防和治疗计划的基石。综述目的:在本文中,我们回顾了美国艾滋病毒监测系统的当前结构和功能,确定报告中的差距,并提出多种潜在干预措施以加强艾滋病毒监测系统。最新发现:最近的文献表明,临床提供者向卫生部门报告存在重大差距。这些差距包括耻辱感、对艾滋病毒报告要求的了解、直接检测估计不准确、报告错误以及缺乏社区参与。所有这些差距给卫生部门带来了沉重负担,阻碍应对措施并影响资金。利用社区伙伴关系、技术进步和新兴方法可能会填补其中一些差距。艾滋病毒自我检测、广泛的社区艾滋病毒检测、间接统计方法以及在广泛社区参与和监督支持下的机器学习方面的进展,可以使艾滋病毒监测系统现代化,以实现终结艾滋病毒流行的目标。