TY - JOUR
T1 - The Potential Epidemiological Impact of Coronavirus Disease 2019 (COVID-19) on the Human Immunodeficiency Virus (HIV) Epidemic and the Cost-effectiveness of Linked, Opt-out HIV Testing
T2 - A Modeling Study in 6 US Cities
AU - Localized HIV Modeling Study
AU - Zang, Xiao
AU - Krebs, Emanuel
AU - Chen, Siyuan
AU - Piske, Micah
AU - Armstrong, Wendy S.
AU - Behrends, Czarina N.
AU - Del Rio, Carlos
AU - Feaster, Daniel J.
AU - Marshall, Brandon D.L.
AU - Mehta, Shruti H.
AU - Mermin, Jonathan
AU - Metsch, Lisa R.
AU - Schackman, Bruce R.
AU - Strathdee, Steffanie A.
AU - Nosyk, Bohdan
AU - Dombrowski, Julia C.
AU - Gebo, Kelly A.
AU - Kirk, Gregory
AU - Montaner, Julio
AU - Pandya, Ankur
AU - Shoptaw, Steven
N1 - Funding Information:
This work was supported by the US National Institutes of Health, National Institutes on Drug Abuse (grant number R01-DA041747).
Publisher Copyright:
© 2020 The Author(s). Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved.
PY - 2021/6/1
Y1 - 2021/6/1
N2 - 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.
AB - 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.
KW - COVID-19
KW - HIV
KW - cost-effectiveness
KW - dynamic HIV transmission model
KW - linked opt-out HIV testing
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U2 - 10.1093/cid/ciaa1547
DO - 10.1093/cid/ciaa1547
M3 - Article
C2 - 33045723
AN - SCOPUS:85107390559
VL - 72
SP - E828-E834
JO - Clinical Infectious Diseases
JF - Clinical Infectious Diseases
SN - 1058-4838
IS - 11
ER -