How Can Progress Toward Ending the Human Immunodeficiency Virus Epidemic in the United States Be Monitored?

Author:

Mitchell Kate M12,Maheu-Giroux Mathieu3,Dimitrov Dobromir4,Moore Mia4,Hughes James P45,Donnell Deborah4,Beyrer Chris6,El-Sadr Wafaa M7,Cohen Myron S8,Boily Marie-Claude12

Affiliation:

1. Medical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom

2. HIV Prevention Trials Network Modelling Centre, Imperial College London, London, United Kingdom

3. Department of Epidemiology, Biostatistics, and Occupational Health, School of Population and Global Health, McGill University, Montréal, Canada

4. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA

5. Department of Biostatistics, University of Washington, Seattle, Washington, USA

6. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA

7. International Center for AIDS Care and Treatment Programs at Columbia University, Mailman School of Public Health, New York, New York, USAand

8. Institute for Global Health and Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

Abstract

Abstract The plan for Ending the HIV (human immunodeficiency virus) Epidemic (EHE) in the United States aims to reduce new infections by 75% by 2025 and by 90% by 2030. For EHE to be successful, it is important to accurately measure changes in numbers of new HIV infections after 5 and 10 years (to determine whether the EHE goals have been achieved) but also over shorter timescales (to monitor progress and intensify prevention efforts if required). In this viewpoint, we aim to demonstrate why the method used to monitor progress toward the EHE goals must be carefully considered. We briefly describe and discuss different methods to estimate numbers of new HIV infections based on longitudinal cohort studies, cross-sectional incidence surveys, and routine surveillance data. We particularly focus on identifying conditions under which unadjusted and adjusted estimates based on routine surveillance data can be used to estimate changes in new HIV infections.

Funder

National Institutes of Health

Medical Research Council

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Microbiology (medical)

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