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Updated: Feb 17, 2026
A Protocol for Analyzing Hepatitis C Virus Replication
Published on: June 26, 2014
Development and Validation of Surveillance-Based Algorithms to Estimate Hepatitis C Treatment and Cure in New York
Miranda S Moore1, Angelica Bocour, Lizeyka Jordan
1Viral Hepatitis Program (Mss Moore, Bocour, and Jordan and Drs Winters and Laraque), New York City Department of Health and Mental Hygiene, Division of Disease Control (Dr Varma), Bureau of Communicable Diseases (Ms McGibbon), Queens, New York. Dr Varma is now with the Africa CDC, Centers for Disease Control and Prevention, National Center for Emerging and Zoonotic Infectious Diseases, Atlanta, Georgia. Dr Laraque is now with the New York City Department of Homeless Services, New York, New York.
Context:
Treatment options for chronic hepatitis C virus (HCV) have improved in recent years. The burden of HCV in New York City (NYC) is high. Measuring treatment and cure among NYC residents with HCV infection will allow the NYC Department of Health and Mental Hygiene (DOHMH) to appropriately plan interventions, allocate resources, and identify disparities to combat the hepatitis C epidemic in NYC.
Objective:
To validate algorithms designed to estimate treatment and cure of HCV using RNA test results reported through routine surveillance.
Design:
Investigation by NYC DOHMH to determine the true treatment and cure status of HCV-infected individuals using chart review and HCV test data. Treatment and cure status as determined by investigation are compared with the status determined by the algorithms.
Setting:
New York City health care facilities.
Participants:
A total of 250 individuals with HCV reported to the New York City Department of Health and Mental Hygiene (NYC DOHMH) prior to March 2016 randomly selected from 15 health care facilities.
Main Outcome Measures:
The sensitivity and specificity of the algorithms.
Results:
Of 235 individuals successfully investigated, 161 (69%) initiated treatment and 96 (41%) achieved cure since the beginning of 2014. The treatment algorithm had a sensitivity of 93.2% (95% confidence interval [CI], 89.2%-97.1%) and a specificity of 83.8% (95% CI, 75.3%-92.2%). The cure algorithm had a sensitivity of 93.8% (95% CI, 88.9%-98.6%) and a specificity of 89.4% (95% CI, 83.5%-95.4%). Applying the algorithms to 68 088 individuals with HCV reported to DOHMH between July 1, 2014, and December 31, 2016, 28 392 (41.7%) received treatment and 16 921 (24.9%) were cured.
Conclusions:
The algorithms developed by DOHMH are able to accurately identify HCV treatment and cure using only routinely reported surveillance data. Such algorithms can be used to measure treatment and cure jurisdiction-wide and will be vital for monitoring and addressing HCV. NYC DOHMH will apply these algorithms to surveillance data to monitor treatment and cure rates at city-wide and programmatic levels, and use the algorithms to measure progress towards defined treatment and cure targets for the city.
