Xiao Zang1, Emanuel Krebs2, Siyuan Chen3, Micah Piske2, Wendy S Armstrong4, Czarina N Behrends5, Carlos Del Rio4, Daniel J Feaster6, Brandon D L Marshall1, Shruti H Mehta7, Jonathan Mermin8, Lisa R Metsch9, Bruce R Schackman5, Steffanie A Strathdee10, Bohdan Nosyk2,3. 1. Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island, USA. 2. British Columbia Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada. 3. Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada. 4. Division of Infectious Diseases, Department of Medicine, Emory University, Atlanta, Georgia, USA. 5. Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, New York, USA. 6. Department of Public Health Sciences, Leonard M. Miller School of Medicine, University of Miami, Miami, Florida, USA. 7. Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA. 8. National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA. 9. Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA. 10. School of Medicine, University of California San Diego, La Jolla, California, USA.
Abstract
BACKGROUND: Widespread viral and serological testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may present a unique opportunity to also test for human immunodeficiency virus (HIV) infection. We estimated the potential impact of adding linked, opt-out HIV testing alongside SARS-CoV-2 testing on the HIV incidence and the cost-effectiveness of this strategy in 6 US cities. METHODS: Using a previously calibrated dynamic HIV transmission model, we constructed 3 sets of scenarios for each city: (1) sustained current levels of HIV-related treatment and prevention services (status quo); (2) temporary disruptions in health services and changes in sexual and injection risk behaviors at discrete levels between 0%-50%; and (3) linked HIV and SARS-CoV-2 testing offered to 10%-90% of the adult population in addition to Scenario 2. We estimated the cumulative number of HIV infections between 2020-2025 and the incremental cost-effectiveness ratios of linked HIV testing over 20 years. RESULTS: In the absence of linked, opt-out HIV testing, we estimated a total of a 16.5% decrease in HIV infections between 2020-2025 in the best-case scenario (50% reduction in risk behaviors and no service disruptions), and a 9.0% increase in the worst-case scenario (no behavioral change and 50% reduction in service access). We estimated that HIV testing (offered at 10%-90% levels) could avert a total of 576-7225 (1.6%-17.2%) new infections. The intervention would require an initial investment of $20.6M-$220.7M across cities; however, the intervention would ultimately result in savings in health-care costs in each city. CONCLUSIONS: A campaign in which HIV testing is linked with SARS-CoV-2 testing could substantially reduce the HIV incidence and reduce direct and indirect health care costs attributable to HIV.
BACKGROUND: Widespread viral and serological testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may present a unique opportunity to also test for human immunodeficiency virus (HIV) infection. We estimated the potential impact of adding linked, opt-out HIV testing alongside SARS-CoV-2 testing on the HIV incidence and the cost-effectiveness of this strategy in 6 US cities. METHODS: Using a previously calibrated dynamic HIV transmission model, we constructed 3 sets of scenarios for each city: (1) sustained current levels of HIV-related treatment and prevention services (status quo); (2) temporary disruptions in health services and changes in sexual and injection risk behaviors at discrete levels between 0%-50%; and (3) linked HIV and SARS-CoV-2 testing offered to 10%-90% of the adult population in addition to Scenario 2. We estimated the cumulative number of HIV infections between 2020-2025 and the incremental cost-effectiveness ratios of linked HIV testing over 20 years. RESULTS: In the absence of linked, opt-out HIV testing, we estimated a total of a 16.5% decrease in HIV infections between 2020-2025 in the best-case scenario (50% reduction in risk behaviors and no service disruptions), and a 9.0% increase in the worst-case scenario (no behavioral change and 50% reduction in service access). We estimated that HIV testing (offered at 10%-90% levels) could avert a total of 576-7225 (1.6%-17.2%) new infections. The intervention would require an initial investment of $20.6M-$220.7M across cities; however, the intervention would ultimately result in savings in health-care costs in each city. CONCLUSIONS: A campaign in which HIV testing is linked with SARS-CoV-2 testing could substantially reduce the HIV incidence and reduce direct and indirect health care costs attributable to HIV.
Authors: Anthony Todd Fojo; Melissa Schnure; Parastu Kasaie; David W Dowdy; Maunank Shah Journal: Ann Intern Med Date: 2021-09-21 Impact factor: 25.391
Authors: Xiao Zang; Cassandra Mah; Amanda My Linh Quan; Jeong Eun Min; Wendy S Armstrong; Czarina N Behrends; Carlos Del Rio; Julia C Dombrowski; Daniel J Feaster; Gregory D Kirk; Brandon D L Marshall; Shruti H Mehta; Lisa R Metsch; Ankur Pandya; Bruce R Schackman; Steven Shoptaw; Steffanie A Strathdee; Emanuel Krebs; Bohdan Nosyk Journal: J Acquir Immune Defic Syndr Date: 2022-02-01 Impact factor: 3.771
Authors: James M Tesoriero; Carol-Ann E Swain; Jennifer L Pierce; Lucila Zamboni; Meng Wu; David R Holtgrave; Charles J Gonzalez; Tomoko Udo; Johanne E Morne; Rachel Hart-Malloy; Deepa T Rajulu; Shu-Yin John Leung; Eli S Rosenberg Journal: JAMA Netw Open Date: 2021-02-01
Authors: Kate M Mitchell; Dobromir Dimitrov; Romain Silhol; Lily Geidelberg; Mia Moore; Albert Liu; Chris Beyrer; Kenneth H Mayer; Stefan Baral; Marie-Claude Boily Journal: Lancet HIV Date: 2021-02-19 Impact factor: 16.070
Authors: Kate M Mitchell; Dobromir Dimitrov; Romain Silhol; Lily Geidelberg; Mia Moore; Albert Liu; Chris Beyrer; Kenneth H Mayer; Stefan Baral; Marie-Claude Boily Journal: medRxiv Date: 2020-11-03
Authors: Steffanie A Strathdee; Natasha K Martin; Eileen V Pitpitan; Jamila K Stockman; Davey M Smith Journal: J Acquir Immune Defic Syndr Date: 2021-01-01 Impact factor: 3.731