TARGETS  

HCV elimination targets in New York State (NYS) are based on World Health Organization goals to achieve HCV elimination worldwide by 2030. Through implementation of public health measures undertaken through the HCV Elimination plan, NYS aims to meet the following five targets by 2030:

INCREASE
DIAGNOSES

INCREASE
TREATMENT

REDUCE NEW INFECTIONS

REDUCE
PREVALENCE

DECREASE
DEATHS

  METRICS  

To monitor progress on elimination targets, including reducing prevalence,Elimination is defined as a 90% reduction in HCV prevalence. Read more about the methods used to calculate prevalence.X the HCV Dashboard tracks three primary metrics: diagnoses, treatment, and new infections.

As the HCV Elimination plan and Dashboard evolve, various secondary metrics that highlight disparities in HCV risk and care will be developed and tracked.

Metric: Number of individuals newly diagnosed with HCV infection, per year.
 
Definition: Number of individuals with a positive HCV RNA test (quantitative or qualitative) or genotype test. The diagnosis of HCV infection typically includes an HCV antibody test and an HCV RNA test. However, because antibody tests do not confirm current infection, the Diagnoses metric uses positive HCV RNA and genotype tests as its key measure of diagnosis.
 
Data Source: Hepatitis Elimination and Epidemiology Dataset (HEED), using HCV case reporting to the NYS Department of Health (DOH) and the NYC Department of Health and Mental Hygiene (DOHMH). 
Metric: Number of individuals diagnosed with HCV with evidence of treatment for, or clearance of, hepatitis C infection, per year.
 
Definition: Number of individuals with a positive HCV RNA test or genotype test, followed by a subsequent HCV RNA negative test or treatment indicated by another data source, without any additional positive HCV RNA test or genotype tests. 
 
Data Source: NYS Hepatitis Elimination and Epidemiology Dataset (HEED), augmented by treatment information from other data sources. 
Metric: Rate of new HCV infections among persons aged 18-40 per year, as a proxy for the rate of new HCV infections among people who inject drugs (PWID) per year.
 
Definition: Rates are calculated using the number of acute HCV cases among individuals aged 18-40 and census-based population estimates.
 
Data Source: NYS Hepatitis Elimination and Epidemiology Dataset (HEED) and National Center for Health Statistics bridged-race population estimates.

  OUTCOMES  

The Center for Disease Analysis Foundation’s Polaris Observatory, in collaboration with the NYS HCV Elimination Task Force’s Surveillance, Data and Metrics Workgroup, worked to calibrate a mathematical disease progression model using New York State specific epidemiologic data. New infections among PWID were modeled using a separate model of HCV transmission. The models were combined to estimate projected cumulative HCV outcomes during the 2020-2030 period, if public health measures detailed in the HCV Elimination plan are implemented.

  screening  

10.0 – 10.6 mil.

New Yorkers screened for HCV

  diagnoses  

33,200 – 75,000

New Yorkers diagnosed with HCV

treatment

75,600 – 143,000

New Yorkers treated or cleared of infection

new infections

37,000 – 46,400

New HCV infections among New Yorkers who inject drugs

liver-related deaths

2,900 – 9,100

Liver-related deaths among New Yorkers

  MEASURING PREVALENCE  

A vital step in designing and monitoring the success of the HCV Elimination plan is understanding the current burden of HCV infection in NYS — also known as the prevalence of current HCV infection in NYS. Annual prevalence estimates are adjusted in conjunction with the three primary metrics tracked annually — diagnoses, treatment, and new infections among PWID.

Estimating prevalence: Due to undiagnosed cases and missing data, among other factors, prevalence of HCV in NYS cannot be directly measured. Instead, a mathematical model developed by UAlbany School of Public Health (SPH) and the NYS Department of Health (DOH) AIDS Institute is used to estimate prevalence. This model integrates National Health and Nutrition Examination (NHANES) data with HCV case surveillance and mortality data from NYS and NYC and incorporates state-specific HCV testing data among persons in jails and prisons. This model provided a primary estimate of 114,000 (0.74%) adults infected with HCV infection throughout NYS in 2015. Using this primary estimate, the Center for Disease Analysis Foundation’s Polaris Observatory’s dynamic model of the HCV epidemic, described above in “Outcomes”, calculated a lower bound of 116,000 persons of all ages living with HCV in NYS in 2015.

Another model developed by Bocour et al. (2018) estimated the prevalence of HCV infection in NYC alone. To be scalable to all of NYS, this method requires data and assumptions that are currently unavailable. Nonetheless, using assumptions from earlier work conducted by NYS DOH, the UAlbany SPH model approximated this technique for all of NYS, yielding an estimate of between 168,000 – 200,000 HCV-infected adults. This estimate was used to choose 189,000 as an upper-bound prevalence among persons of all ages in NYS in 2015. These upper and lower bounds (116,000 – 189,000) of NYS HCV prevalence in 2015 inform NYS elimination planning, including the creation of the five elimination targets and the simulation model used for the cumulative outcomes, as detailed above.

  NYS HCV ELIMINATION DATA AND METRICS ADVISORY COMMITTEE  

The Advisory Committee was appointed to ensure scientific validity, clinical accuracy, cultural appropriateness, and feasibility of the approaches developed by the Surveillance, Data and Metrics Workgroup. The Committee also provides feedback on implementation plans, summary data, and the HCV Dashboard. The initial Advisory Committee included the following members:

Meredith Barranco
Debra Blog
Angelica Bocour
Don Des Jarlais
Elizabeth Dufort
Eliana Duncan
Colleen Flanigan

John Fuller
Annette Gaudino
Holly Hagan
Ingrid Hahn
David Holtgrave
Christine Kerr
John Leung

Wendy Levey
Denis Nash
Monica Parker
Daniel Raymond
Barbara Rogler
Eli Rosenberg
Elizabeth Rosenthal

Bruce Schackman
Sarah Shufelt
Patrick Sullivan
Tomoko Udo
Ronald Valdiserri
Larissa Wilberschied
Ann Winters
Lucila Zamboni