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Scaling-up HCV prevention and treatment interventions in rural United States-model projections for tackling an increasing epidemic.

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Title: Scaling-up HCV prevention and treatment interventions in rural United States-model projections for tackling an increasing epidemic.
Authors: Fraser, Hannah, Zibbell, Jon, Hoerger, Thomas, Hariri, Susan, Vellozzi, Claudia, Martin, Natasha K., Kral, Alex H., Hickman, Matthew, Ward, John W., Vickerman, Peter
Source: Addiction. Jan2018, Vol. 113 Issue 1, p173-182. 10p. 1 Chart, 3 Graphs.
Subjects: Hepatitis C prevention, Hepatitis C treatment, Rural Americans, Epidemics, Infection prevention, Disease prevalence, Preventive medicine, Health, Mathematical models, Probability theory, Rural conditions, Theory, Data analysis software, Descriptive statistics, Chronic hepatitis C, Prevention, Infectious disease transmission
Geographic Terms: Scott County (Ind.), United States, Indiana
Abstract: Background and aims Effective strategies are needed to address dramatic increases in hepatitis C virus (HCV) infection among people who inject drugs (PWID) in rural settings of the United States. We determined the required scale-up of HCV treatment with or without scale-up of HCV prevention interventions to achieve a 90% reduction in HCV chronic prevalence or incidence by 2025 and 2030 in a rural US setting. Design An ordinary differential equation model of HCV transmission calibrated to HCV epidemiological data obtained primarily from an HIV outbreak investigation in Indiana. Setting Scott County, Indiana (population 24 181), USA, a rural setting with negligible baseline interventions, increasing HCV epidemic since 2010, and 55.3% chronic HCV prevalence among PWID in 2015. Participants PWID. Measurements Required annual HCV treatments per 1000 PWID (and initial annual percentage of infections treated) to achieve a 90% reduction in HCV chronic prevalence or incidence by 2025/30, either with or without scaling-up syringe service programmes (SSPs) and medication-assisted treatment (MAT) to 50% coverage. Sensitivity analyses considered whether this impact could be achieved without re-treatment of re-infections, and whether greater intervention scale-up was required due to the increasing epidemic in this setting. Findings To achieve a 90% reduction in incidence and prevalence by 2030, without MAT and SSP scale-up, 159 per 1000 PWID (initially 24.9% of infected PWID) need to be HCV-treated annually. However, with MAT and SSP scaled-up, treatment rates are halved (89 per 1000 annually or 14.5%). To reach the same target by 2025 with MAT and SSP scaled-up, 121 per 1000 PWID (19.9%) need treatment annually. These treatment requirements are threefold higher than if the epidemic was stable, and the impact targets are unattainable without retreatment. Conclusions Combined scale-up of hepatitis C virus treatment and prevention interventions is needed to decrease the increasing burden of hepatitis C virus incidence and prevalence in rural Indiana, USA, by 90% by 2025/30. [ABSTRACT FROM AUTHOR]
Copyright of Addiction is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Scaling-up HCV prevention and treatment interventions in rural United States-model projections for tackling an increasing epidemic.
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  Data: <searchLink fieldCode="AR" term="%22Fraser%2C+Hannah%22">Fraser, Hannah</searchLink><br /><searchLink fieldCode="AR" term="%22Zibbell%2C+Jon%22">Zibbell, Jon</searchLink><br /><searchLink fieldCode="AR" term="%22Hoerger%2C+Thomas%22">Hoerger, Thomas</searchLink><br /><searchLink fieldCode="AR" term="%22Hariri%2C+Susan%22">Hariri, Susan</searchLink><br /><searchLink fieldCode="AR" term="%22Vellozzi%2C+Claudia%22">Vellozzi, Claudia</searchLink><br /><searchLink fieldCode="AR" term="%22Martin%2C+Natasha+K%2E%22">Martin, Natasha K.</searchLink><br /><searchLink fieldCode="AR" term="%22Kral%2C+Alex+H%2E%22">Kral, Alex H.</searchLink><br /><searchLink fieldCode="AR" term="%22Hickman%2C+Matthew%22">Hickman, Matthew</searchLink><br /><searchLink fieldCode="AR" term="%22Ward%2C+John+W%2E%22">Ward, John W.</searchLink><br /><searchLink fieldCode="AR" term="%22Vickerman%2C+Peter%22">Vickerman, Peter</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Addiction%22">Addiction</searchLink>. Jan2018, Vol. 113 Issue 1, p173-182. 10p. 1 Chart, 3 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Hepatitis+C+prevention%22">Hepatitis C prevention</searchLink><br /><searchLink fieldCode="DE" term="%22Hepatitis+C+treatment%22">Hepatitis C treatment</searchLink><br /><searchLink fieldCode="DE" term="%22Rural+Americans%22">Rural Americans</searchLink><br /><searchLink fieldCode="DE" term="%22Epidemics%22">Epidemics</searchLink><br /><searchLink fieldCode="DE" term="%22Infection+prevention%22">Infection prevention</searchLink><br /><searchLink fieldCode="DE" term="%22Disease+prevalence%22">Disease prevalence</searchLink><br /><searchLink fieldCode="DE" term="%22Preventive+medicine%22">Preventive medicine</searchLink><br /><searchLink fieldCode="DE" term="%22Health%22">Health</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Probability+theory%22">Probability theory</searchLink><br /><searchLink fieldCode="DE" term="%22Rural+conditions%22">Rural conditions</searchLink><br /><searchLink fieldCode="DE" term="%22Theory%22">Theory</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis+software%22">Data analysis software</searchLink><br /><searchLink fieldCode="DE" term="%22Descriptive+statistics%22">Descriptive statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Chronic+hepatitis+C%22">Chronic hepatitis C</searchLink><br /><searchLink fieldCode="DE" term="%22Prevention%22">Prevention</searchLink><br /><searchLink fieldCode="DE" term="%22Infectious+disease+transmission%22">Infectious disease transmission</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Scott+County+%28Ind%2E%29%22">Scott County (Ind.)</searchLink><br /><searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink><br /><searchLink fieldCode="DE" term="%22Indiana%22">Indiana</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Background and aims Effective strategies are needed to address dramatic increases in hepatitis C virus (HCV) infection among people who inject drugs (PWID) in rural settings of the United States. We determined the required scale-up of HCV treatment with or without scale-up of HCV prevention interventions to achieve a 90% reduction in HCV chronic prevalence or incidence by 2025 and 2030 in a rural US setting. Design An ordinary differential equation model of HCV transmission calibrated to HCV epidemiological data obtained primarily from an HIV outbreak investigation in Indiana. Setting Scott County, Indiana (population 24 181), USA, a rural setting with negligible baseline interventions, increasing HCV epidemic since 2010, and 55.3% chronic HCV prevalence among PWID in 2015. Participants PWID. Measurements Required annual HCV treatments per 1000 PWID (and initial annual percentage of infections treated) to achieve a 90% reduction in HCV chronic prevalence or incidence by 2025/30, either with or without scaling-up syringe service programmes (SSPs) and medication-assisted treatment (MAT) to 50% coverage. Sensitivity analyses considered whether this impact could be achieved without re-treatment of re-infections, and whether greater intervention scale-up was required due to the increasing epidemic in this setting. Findings To achieve a 90% reduction in incidence and prevalence by 2030, without MAT and SSP scale-up, 159 per 1000 PWID (initially 24.9% of infected PWID) need to be HCV-treated annually. However, with MAT and SSP scaled-up, treatment rates are halved (89 per 1000 annually or 14.5%). To reach the same target by 2025 with MAT and SSP scaled-up, 121 per 1000 PWID (19.9%) need treatment annually. These treatment requirements are threefold higher than if the epidemic was stable, and the impact targets are unattainable without retreatment. Conclusions Combined scale-up of hepatitis C virus treatment and prevention interventions is needed to decrease the increasing burden of hepatitis C virus incidence and prevalence in rural Indiana, USA, by 90% by 2025/30. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Addiction is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1111/add.13948
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        Text: English
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      – SubjectFull: Hepatitis C prevention
        Type: general
      – SubjectFull: Hepatitis C treatment
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      – SubjectFull: Rural Americans
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      – SubjectFull: Epidemics
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      – SubjectFull: Infection prevention
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      – SubjectFull: Disease prevalence
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      – SubjectFull: Chronic hepatitis C
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      – SubjectFull: Scott County (Ind.)
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              Text: Jan2018
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