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Modelling the potential prevention benefits of a treat-all hepatitis C treatment strategy at global, regional, and country levels: a modelling study

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Modelling the potential prevention benefits of a treat-all hepatitis C treatment strategy at global, regional, and country levels : a modelling study. / Trickey, Adam; Fraser, Hannah; Lim, Aaron; Walker, Josephine; Peacock, Amy; Colledge, Samantha; Leung, Janni; Grebely, Jason; Larney, Sarah; Martin, Natasha; Degenhardt, Louisa; Hickman, Matthew; May, Margaret; Vickerman, Peter.

In: Journal of Viral Hepatitis, 07.08.2019.

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@article{b05e79433c4d43c482b723439b6caf07,
title = "Modelling the potential prevention benefits of a treat-all hepatitis C treatment strategy at global, regional, and country levels: a modelling study",
abstract = "The World Health Organization (WHO) recently produced guidelines advising a treat-all policy for HCV to encourage widespread treatment scale-up for achieving HCV elimination. We modelled the prevention impact achieved (HCV infections averted [IA]) from initiating this policy compared with treating different subgroups at country, regional, and global-levels. We assessed what country-level factors affect impact. A dynamic, deterministic HCV transmission model was calibrated to data from global systematic reviews and UN datasets to simulate country-level HCV epidemics with ongoing levels of treatment. For each country, the model projected the prevention impact (in HCV IA per treatment undertaken) of initiating four treatment strategies; either selected randomly (treat-all) or targeted among people who inject drugs (PWID), people aged ≥35, or those with cirrhosis. The IA was assessed over 20-years. Linear regression identified associations between IA per treatment and demographic factors. Eighty-eight countries (85{\%} of the global population) were modelled. Globally, the model estimated 0.35 (95{\%} credibility interval [95{\%}CrI]: 0.16-0.61) IA over 20-years for every randomly allocated treatment, 0.30 (95{\%}CrI: 0.12-0.53) from treating those aged ≥35, and 0.28 (95{\%}CrI: 0.12-0.49) for those with cirrhosis. Globally, treating PWID achieved 1.27 (95{\%}CrI: 0.68-2.04) IA per treatment. The IA per randomly allocated treatment was positively associated with a country’s population growth-rate, and negatively associated with higher HCV prevalence among PWID. In conclusion, appreciable prevention benefits could be achieved from WHO’s treat-all strategy, although greater benefits per treatment can be achieved through targeting PWID. Higher impact will be achieved in countries with high population growth.",
keywords = "DAA, treat, averted, infections, HCV",
author = "Adam Trickey and Hannah Fraser and Aaron Lim and Josephine Walker and Amy Peacock and Samantha Colledge and Janni Leung and Jason Grebely and Sarah Larney and Natasha Martin and Louisa Degenhardt and Matthew Hickman and Margaret May and Peter Vickerman",
year = "2019",
month = "8",
day = "7",
doi = "10.1111/jvh.13187",
language = "English",
journal = "Journal of Viral Hepatitis",
issn = "1352-0504",
publisher = "Wiley",

}

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TY - JOUR

T1 - Modelling the potential prevention benefits of a treat-all hepatitis C treatment strategy at global, regional, and country levels

T2 - a modelling study

AU - Trickey, Adam

AU - Fraser, Hannah

AU - Lim, Aaron

AU - Walker, Josephine

AU - Peacock, Amy

AU - Colledge, Samantha

AU - Leung, Janni

AU - Grebely, Jason

AU - Larney, Sarah

AU - Martin, Natasha

AU - Degenhardt, Louisa

AU - Hickman, Matthew

AU - May, Margaret

AU - Vickerman, Peter

PY - 2019/8/7

Y1 - 2019/8/7

N2 - The World Health Organization (WHO) recently produced guidelines advising a treat-all policy for HCV to encourage widespread treatment scale-up for achieving HCV elimination. We modelled the prevention impact achieved (HCV infections averted [IA]) from initiating this policy compared with treating different subgroups at country, regional, and global-levels. We assessed what country-level factors affect impact. A dynamic, deterministic HCV transmission model was calibrated to data from global systematic reviews and UN datasets to simulate country-level HCV epidemics with ongoing levels of treatment. For each country, the model projected the prevention impact (in HCV IA per treatment undertaken) of initiating four treatment strategies; either selected randomly (treat-all) or targeted among people who inject drugs (PWID), people aged ≥35, or those with cirrhosis. The IA was assessed over 20-years. Linear regression identified associations between IA per treatment and demographic factors. Eighty-eight countries (85% of the global population) were modelled. Globally, the model estimated 0.35 (95% credibility interval [95%CrI]: 0.16-0.61) IA over 20-years for every randomly allocated treatment, 0.30 (95%CrI: 0.12-0.53) from treating those aged ≥35, and 0.28 (95%CrI: 0.12-0.49) for those with cirrhosis. Globally, treating PWID achieved 1.27 (95%CrI: 0.68-2.04) IA per treatment. The IA per randomly allocated treatment was positively associated with a country’s population growth-rate, and negatively associated with higher HCV prevalence among PWID. In conclusion, appreciable prevention benefits could be achieved from WHO’s treat-all strategy, although greater benefits per treatment can be achieved through targeting PWID. Higher impact will be achieved in countries with high population growth.

AB - The World Health Organization (WHO) recently produced guidelines advising a treat-all policy for HCV to encourage widespread treatment scale-up for achieving HCV elimination. We modelled the prevention impact achieved (HCV infections averted [IA]) from initiating this policy compared with treating different subgroups at country, regional, and global-levels. We assessed what country-level factors affect impact. A dynamic, deterministic HCV transmission model was calibrated to data from global systematic reviews and UN datasets to simulate country-level HCV epidemics with ongoing levels of treatment. For each country, the model projected the prevention impact (in HCV IA per treatment undertaken) of initiating four treatment strategies; either selected randomly (treat-all) or targeted among people who inject drugs (PWID), people aged ≥35, or those with cirrhosis. The IA was assessed over 20-years. Linear regression identified associations between IA per treatment and demographic factors. Eighty-eight countries (85% of the global population) were modelled. Globally, the model estimated 0.35 (95% credibility interval [95%CrI]: 0.16-0.61) IA over 20-years for every randomly allocated treatment, 0.30 (95%CrI: 0.12-0.53) from treating those aged ≥35, and 0.28 (95%CrI: 0.12-0.49) for those with cirrhosis. Globally, treating PWID achieved 1.27 (95%CrI: 0.68-2.04) IA per treatment. The IA per randomly allocated treatment was positively associated with a country’s population growth-rate, and negatively associated with higher HCV prevalence among PWID. In conclusion, appreciable prevention benefits could be achieved from WHO’s treat-all strategy, although greater benefits per treatment can be achieved through targeting PWID. Higher impact will be achieved in countries with high population growth.

KW - DAA

KW - treat

KW - averted

KW - infections

KW - HCV

U2 - 10.1111/jvh.13187

DO - 10.1111/jvh.13187

M3 - Article

JO - Journal of Viral Hepatitis

JF - Journal of Viral Hepatitis

SN - 1352-0504

ER -