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Modeling the impact of the COVID-19 pandemic on achieving HCV elimination amongst young and unstably housed people who inject drugs in San Francisco.
Fraser, Hannah; Stone, Jack; Facente, Shelley N; Artenie, Adelina; Patel, Sheena; Wilson, Erin C; McFarland, Willi; Page, Kimberly; Vickerman, Peter; Morris, Meghan D.
Afiliação
  • Fraser H; Population Health Sciences, Bristol Medical School, University of Bristol, UK.
  • Stone J; Population Health Sciences, Bristol Medical School, University of Bristol, UK.
  • Facente SN; School of Public Health, Division of Epidemiology and Biostatistics, University of California Berkeley, Berkeley, USA; Facente Consulting, Richmond, USA.
  • Artenie A; Population Health Sciences, Bristol Medical School, University of Bristol, UK.
  • Patel S; Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, USA.
  • Wilson EC; San Francisco Department of Public Health, San Francisco, USA.
  • McFarland W; Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, USA; San Francisco Department of Public Health, San Francisco, USA.
  • Page K; Department of Internal Medicine, Division of Epidemiology, University of New Mexico, USA.
  • Vickerman P; Population Health Sciences, Bristol Medical School, University of Bristol, UK. Electronic address: peter.vickerman@bristol.ac.uk.
  • Morris MD; Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, USA.
Int J Drug Policy ; : 104452, 2024 Jun 11.
Article em En | MEDLINE | ID: mdl-38910096
ABSTRACT

BACKGROUND:

Young adult (18-30 years) people who inject drugs (PWID) face high hepatitis C virus (HCV) prevalence. In San Francisco, where >60% of PWID lack stable housing, barriers hinder HCV treatment access. We assessed progress towards the World Health Organization's (WHO) HCV elimination goal of an 80% reduction in incidence over 2015-2030, focusing on young (YPWID) and unstably housed PWID in San Francisco.

METHODS:

We developed a dynamic HCV transmission model among PWID, parameterized and calibrated using bio-behavioural survey datasets from San Francisco. This included 2018 estimates for the antibody-prevalence among PWID (77%) and care cascade estimates for HCV for YPWID (72% aware of their status and 33% ever initiating treatment). Based on programmatic data, we assumed a 53.8% reduction in testing and 40.7% decrease in treatment from 2020 due to the COVID-19 pandemic, which partially rebounded from April 2021 with testing rates then being 31.1% lower than pre-pandemic rates and treatment numbers being 19.5% lower. We simulated different scenarios of how services changed after the pandemic to project whether elimination goals would be met.

RESULTS:

Continuing post-pandemic rates of testing and treatment, the model projects an 83.3% (95% credibility interval [95% CrI]60.6-96.9%) decrease in incidence among PWID over 2015-2030 to 1.5/100pyrs (95% CrI0.3-4.4) in 2030. The probability of achieving the elimination goal by 2030 is 62.0%. Among YPWID and unstably housed PWID, the probability of achieving the elimination goal by 2030 is 54.8 and 67.6%, respectively. Importantly, further increasing testing and treatment rates to pre-pandemic levels by 2025 only results in a small increase in the probability (67.5%) of the elimination goal being achieved among all PWID by 2030, while increased coverage of medication for opioid use disorder among YPWID and/or housing interventions results in the probability of achieving elimination increasing to over 75%.

CONCLUSION:

The COVID-19 pandemic impeded progress toward achieving HCV elimination. Our findings indicate that existing partial rebounds in HCV testing and treatment may achieve the elimination goal by 2030, with an additional scale-up of interventions aimed at YPWID or unstably housed PWID ensuring San Francisco is likely to achieve elimination by 2030.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article