Selected article for: "dynamic model and potential impact"

Author: Zang, Xiao; Krebs, Emanuel; Chen, Siyuan; Piske, Micah; Armstrong, Wendy S; Behrends, Czarina N; Del Rio, Carlos; Feaster, Daniel J; Marshall, Brandon D L; Mehta, Shruti H; Mermin, Jonathan; Metsch, Lisa R; Schackman, Bruce R; Strathdee, Steffanie A; Nosyk, Bohdan
Title: The potential epidemiological impact of COVID-19 on the HIV/AIDS epidemic and the cost-effectiveness of linked, opt-out HIV testing: A modeling study in six US cities
  • Cord-id: biv9roks
  • Document date: 2020_10_12
  • ID: biv9roks
    Snippet: BACKGROUND: Widespread viral and serological testing for SARS-CoV-2 may present a unique opportunity to also test for HIV infection. We estimated the potential impact of adding linked, opt-out HIV testing alongside SARS-CoV-2 testing on HIV incidence and the cost-effectiveness of this strategy in six US cities. METHODS: Using a previously-calibrated dynamic HIV transmission model, we constructed three sets of scenarios for each city: (1) sustained current levels of HIV-related treatment and prev
    Document: BACKGROUND: Widespread viral and serological testing for SARS-CoV-2 may present a unique opportunity to also test for HIV infection. We estimated the potential impact of adding linked, opt-out HIV testing alongside SARS-CoV-2 testing on HIV incidence and the cost-effectiveness of this strategy in six US cities. METHODS: Using a previously-calibrated dynamic HIV transmission model, we constructed three 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 behaviours 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 cumulative HIV infections between 2020-2025 and 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 16.5% decrease in HIV infections between 2020-2025 in the best-case scenario (50% reduction in risk behaviours and no service disruptions), and 9.0% increase in the worst-case scenario (no behavioural change and 50% reduction in service access). We estimated that HIV testing (offered at 10%-90% levels) could avert a total of 576-7,225 (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 HIV incidence and reduce direct and indirect health care costs attributable to HIV.

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