Hepatitis C virus (HCV) infection is the most common blood-borne infection in the United States \[[@CIT0001]\]; untreated infection is a leading cause of cirrhosis and hepatocellular carcinoma, is the most frequent cause of liver failure requiring transplantation, and causes more deaths annually than human immunodeficiency virus (HIV) \[[@CIT0002]\]. About 70% of persons with untreated HCV infection remain infected for life. HCV infection may be asymptomatic and approximately half of persons are unaware of their infection \[[@CIT0006]\]. Within 30 years, 41% of infected persons progress to cirrhosis, leading to liver failure, hepatocellular carcinoma, and death from liver-related causes \[[@CIT0002]\].

The annual number of new HCV infections in the United States was highest before HCV was discovered to be the cause of "non-A non-B hepatitis" in 1989; incidence declined after prevention guidelines and blood donor screening were implemented in the 1990s. After years of level incidence, new HCV infections began to rise nationally in 2010, increasing \>2-fold by 2014. Incidence of acute HCV infections has risen among males, persons aged 20--29 years, and American Indians/Alaska Natives \[[@CIT0007]\]. The prevalence of HCV infection can be measured by a positive test for HCV antibody. Chronic HCV infection is associated with substantial morbidity and mortality, is highest among males and those born during 1945--1965, and has been associated with rising HCV-related mortality in recent years \[[@CIT0001], [@CIT0004], [@CIT0007]\].

Current US surveillance programs provide incomplete estimates of HCV infection prevalence. In 2014, the Centers For Disease Control and Prevention (CDC) National Notifiable Diseases Surveillance System (NNDSS) included passively collected laboratory reports from 40 states of acute HCV infection, and from 34 states reporting chronic HCV infection. US national and state-specific estimates of HCV infection prevalence cannot be ascertained from NNDSS data \[[@CIT0007], [@CIT0010]\].

National estimates of HCV prevalence have been produced using the US National Health and Nutrition Examination Survey (NHANES), which includes interviews and physical examinations of noninstitutionalized persons aged ≥6 years \[[@CIT0011]\]. NHANES data for 2003--2010 estimated that 3.6 million persons had antibodies to HCV (anti-HCV), indicative of past or current HCV infection, corresponding to a national prevalence of 1.3% \[[@CIT0008]\]. Subsequent systematic reviews estimate an additional 1 million HCV infections from populations excluded and underrepresented in NHANES, primarily homeless or incarcerated persons \[[@CIT0012], [@CIT0013]\].

State-level estimates of the prevalence of HCV infection are essential for guiding intervention programs, research, and federal assistance funding priorities among US states. In 2016, CDC funded 7 jurisdictions to conduct active case surveillance for HCV infection, and case counts of HCV diagnoses have been produced \[[@CIT0007]\]. However, these states have been conducting active surveillance for few years, and most states lack local resources to provide similar information regarding the number of persons diagnosed with HCV; surveillance data are limited by variability in testing of persons at risk for infection and reporting to public health authorities.

Some jurisdictions have created their own estimates of prevalence using various methods, most commonly by applying NHANES-derived HCV infection prevalence rates to state populations \[[@CIT0014]\]. The assumption that all states have the national NHANES prevalence of HCV infection might produce inaccurate state-specific estimates, because risk of HCV infection likely varies by state. Some researchers have attempted to improve upon this simple approach by standardizing the national NHANES estimate to local demographic profiles or creating models using case surveillance data (Supplementary Table 1). Despite these informative efforts, there is no complete set of state-specific estimates of HCV infection prevalence for all US states that is based on accurate and consistent methods.

Small-area estimation methods are statistical approaches that can be used for determining state-level HCV infection prevalence by allocating national prevalence estimates into state-specific components using data sources indicating state-level markers of HCV infection prevalence \[[@CIT0015]\]. State-level data sources include electronic medical records (EMRs), insurance claims, and laboratory and mortality data. Individual commercially available EMR, claims, and laboratory datasets are inconsistent in their geographic and demographic representation \[[@CIT0016]\]. Alternatively, mortality is systemically recorded for all decedents in the United States and is publicly available through the population-based National Vital Statistics System (NVSS) \[[@CIT0004]\]. NVSS mortality data provide detailed information regarding decedent age, sex, and race/ethnicity, which are covariates of state-specific HCV infection prevalence.

Here, we describe an application of small-area methodology to deconstruct national NHANES-estimated HCV infection prevalence into state-specific components using HCV-related mortality as a state-level data source. Sensitivity analyses consider the uncertainty of the estimates associated with state-specific variation in diagnosing and treating HCV infection and in recording HCV-related mortality. We present state-level estimates of anti-HCV prevalence and compare these to previously published state estimates.

METHODS {#s1}
=======

We employed a synthetic small-area estimation approach that combined indirect standardization of NHANES data with regression-based estimates of state-level HCV-related mortality. The data sources and approach are described below and in [Table 1](#T1){ref-type="table"} and [Figure 1](#F1){ref-type="fig"}.

###### 

Data Sources and Purposes for Primary and Sensitivity Analyses

  Data source                                        Years Represented   Purpose                                                                                           No. of Individuals Represented                                                     No. of Cases                                                                    Data Extraction Notes
  -------------------------------------------------- ------------------- ------------------------------------------------------------------------------------------------- ---------------------------------------------------------------------------------- ------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
  National Health and Nutrition Examination Survey   1999--2012          National HCV antibody prevalence overall and by strata of sex, race/ethnicity, and birth cohort   36726 with nonmissing HCV antibody test results                                    662 with positive anti- HCV test result                                         NHANES 2000, 2002, 2004, 2006, 2008, 2010, 2012 datasets
  US Census intercensal data                         1999--2012          Population structure for modeling 14-year average HCV-related mortality rate                      3125647447 person-years aged ≥18 y                                                 NA                                                                              US Vintage 2000, Vintage 2009, Vintage 2014 datasets
  US Census 2010                                     2010                Population structure for final estimates                                                          234564071 persons aged ≥18 y                                                       NA                                                                              US Census 2010 dataset
  National Vital Statistics System                   1999--2012          Hepatitis C--related mortality, for primary analysis                                              33540118 decedents age aged ≥18 y who resided in the 50 states or Washington, DC   185285 with HCV as underlying or multiple cause of death                        *ICD-10* codes included acute viral hepatitis C (B17.1), chronic viral hepatitis C (B18.2)
  National Vital Statistics System                   1999--2012          Cirrhosis-related mortality, for bias analysis                                                    33540118 decedents aged ≥18 y who resided in the 50 states or Washington, DC       427404 with cirrhosis as underlying or multiple cause of death                  *ICD-10* codes included hepatic fibrosis (K74.0); hepatic sclerosis (K74.1); hepatic fibrosis with hepatic sclerosis (K74.12); or other and unspecified cirrhosis of liver (K74.6)
  National Vital Statistics System                   1999--2012          Hepatocellular carcinoma-related mortality, for bias analysis                                     33540118 decedents aged ≥18 y who resided in the 50 states or Washington, DC       197976 with hepatocellular carcinoma as underlying or multiple cause of death   *ICD-10* codes included liver cell carcinoma (C22.0); primary malignant neoplasm of liver, type unspecified (C22.8); or malignant neoplasm of liver, not specified as primary or secondary (C22.9)

Abbreviations: HCV, hepatitis C virus; *ICD-10, International Classification of Diseases, Tenth Revision*; NHANES, National Health and Nutrition Examination Survey.

![Modeling equations. Abbreviations: anti-HCV, hepatitis C virus antibody; NVSS, National Vital Statistics System.](cix20201){#F1}

Data Sources {#s2}
------------

### NHANES 1999--2012 {#s3}

Annually, NHANES uses a complex, multistage sampling design to select approximately 5000 persons in 15 counties, representing the noninstitutionalized population of persons aged ≥6 years residing in the 50 states and Washington, District of Columbia \[[@CIT0011]\].

NHANES tests blood specimens for HCV antibody (anti-HCV), with RNA confirmatory testing \[[@CIT0008]\]. Persons who were anti-HCV positive were considered to have past or current HCV infection \[[@CIT0008]\].

Publicly available data from 7 NHANES release cycles were combined---a 14-year span (1999--2012) that included 36726 observations with anti-HCV test results (662 anti-HCV positive), and self-reported sex, race/ethnicity, and age. Race/ethnicity was categorized into Hispanic, non-Hispanic white, non-Hispanic black, and other (including multiracial) \[[@CIT0008]\]. NHANES respondents were classified into birth cohorts---before, during, and after 1945--1965 \[[@CIT0017], [@CIT0018]\]. Analyses were restricted to respondents aged ≥18 years; only 5 individuals aged \<18 years were anti-HCV positive. The primary analysis did not include RNA confirmatory testing because of missingness for 120 (15%) of tested persons in NHANES datasets.

### NVSS Multiple Cause of Death Mortality Data (1999--2012) {#s4}

Mortality Multiple Cause Microdata files (1999--2012) were obtained through the NVSS \[[@CIT0019], [@CIT0020]\]. Data were individual records for decedents who lived in a US state or Washington, District of Columbia and were aged ≥18 years at death. Records also contained *International Classification of Diseases, Tenth Revision* (*ICD-10*) codes for multiple underlying causes of death (N = 33540118). Demographic covariates included sex, race/ethnicity, and birth cohort. In the primary analysis, any records including the *ICD-10* code for acute viral hepatitis C (B17.1) or chronic viral hepatitis C (B18.2) as an underlying cause of death were considered to signal HCV-related mortality (n = 185285).

### US Census Intercensal Data (1999--2012) and 2010 US Census Data {#s5}

Intercensal population estimates from the US Vintage 2000, 2009, and 2014 datasets provided denominators for HCV-related mortality rates during 1999--2012 \[[@CIT0021]\]. Data were grouped into the same sex, race/ethnicity, and birth cohort categories as the NHANES and NVSS data. State-by-demographic group population totals from the 2010 US Census were used to calculate 2010 state HCV prevalence \[[@CIT0021]\].

Analysis {#s6}
--------

The number of persons in each state with anti-HCV was computed using the standardization-based estimator in [Figure 1](#F1){ref-type="fig"}, equation 1. First, we calculated direct weighted estimates of national HCV-antibody prevalence ${\hat{\mu}}_{j}$ for 24 strata (sex × race/ethnicity × birth cohort), using standard methodology ([Figure 1](#F1){ref-type="fig"}, equation 1) \[[@CIT0015]\]. We multiplied weighted estimates by state-by-demographic stratum 2010 population counts to generate crude state-level estimates. These were adjusted by the ratio of state-by-demographic stratum effects, based on the average HCV-related death rate ${\hat{\theta}}_{ij}$ in the 14-year period. We fit a high-order logistic regression model that approximated full stratification (several of 1224 strata had zero cells), permitting detection of heterogeneity among strata ([Figure 1](#F1){ref-type="fig"}, equation 3). We assessed collinearity and model fit by comparing observed state-level HCV-related mortality totals to model predictions \[[@CIT0015], [@CIT0022]\]. Mortality-adjusted HCV infection prevalence totals were summarized to yield estimated state-level totals ${\hat{T}}_{i}$ (rounded to nearest hundred persons), with prevalence rates ${\hat{\lambda}}_{i}$ ([Figure 1](#F1){ref-type="fig"}, equations 1 and 2). Supplementary analyses estimated state-level chronic HCV infection, defined as a positive or indeterminate anti-HCV test and a positive HCV RNA test, using the above approach but with a 12-stratum model (race/ethnicity considered white non-Hispanic or not), due to more sparse NHANES data.

Sensitivity Analyses {#s7}
--------------------

To account for the joint statistical uncertainty in the stratified NHANES estimates and model-based HCV-related mortality estimates, we conducted a Monte Carlo simulation that respectively sampled from logit-normal and normal distributions (*k* = 10000 runs), using the standard errors for the original estimates, to produce 95% confidence intervals (CIs) for state-level estimates.

There might be state-level variability in HCV diagnosis and treatment that produces state-level variability in HCV-related deaths or proper attribution (specific *ICD-10* codes) of deaths to an HCV cause, although likely limited \[[@CIT0005]\]. We repeated all analyses with a broader definition of HCV-related deaths that used a combination of the HCV-specific *ICD-10* codes and less-specific, more sensitive, *ICD-10* codes representing cirrhosis-related and hepatocellular carcinoma--related (HCC) causes of death ([Table 1](#T1){ref-type="table"}) \[[@CIT0005]\]. To increase specificity of these additional codes, we applied available estimates of the population attributable fraction (PAF) due to HCV infection (cirrhosis: 42%, HCC: 48%; [Figure 1](#F1){ref-type="fig"}, equation 4) \[[@CIT0023]\]. We secondarily considered other PAF estimates in less representative populations \[[@CIT0024], [@CIT0025]\].

We descriptively compared model findings to other publicly available reports of state estimates. Reports were excluded if HCV infection estimates solely involved applying national NHANES HCV infection prevalence estimates to total state population or if estimation was exclusively based on partial case surveillance data for HCV infection. Reports not describing the methodology used for prevalence estimation were included to facilitate more comparisons. Where possible, abstracted prevalence estimates were restricted to comparable noninstitutionalized populations.

RESULTS {#s8}
=======

The estimated national prevalence of anti-HCV in 2010 was 1.67% (95% CI, 1.53%--1.90%), corresponding to 3 911 800 (95% CI, 3589400--4447500) US adults with past or current HCV infection. Demographic stratum-specific estimates ranged from 0.26% for other race/ethnicity females born after 1965 to 8.02% for black males born 1945--1965 (Supplementary Table 2).

The prevalence of anti-HCV varied by state ([Table 2](#T2){ref-type="table"} and [Figure 2](#F2){ref-type="fig"}). State-specific prevalence rates ranged from 0.71% in Illinois to 3.34% in Oklahoma, with \>2.5% additionally in District of Columbia, New Mexico, Oregon, and Tennessee. By census region and division, the West contained the most high-prevalence states: 10 of 13 states were above the national average, and the region-specific prevalence was 2.14%. The Pacific West division was most affected (2.30% prevalence; 865400 persons who had been infected with HCV). The South had the second-highest anti-HCV prevalence (1.80%) and the largest number of persons with anti-HCV (n = 1561600). Within the South, the West South Central had the highest prevalence (2.19%), while the South Atlantic division had the most persons with anti-HCV (n = 712900). The Midwest (1.14%) and Northeast (1.43%) had relatively lower anti-HCV prevalence. Of the 21 states in these regions, only Rhode Island had prevalence above the national average (2.12%). Although having prevalence rates lower than the national average, Michigan, New York, Pennsylvania, and Ohio each had \>100000 persons with anti-HCV.

###### 

Estimated Total and Prevalence Rate of Persons With Hepatitis C Virus Antibody, US States and District of Columbia, by US Census Region and Division, 2010^a^

  Region/Division/State           2010 Census Population   Total Persons With Anti-HCV   Anti-HCV Prevalence Rate          
  ------------------------------- ------------------------ ----------------------------- -------------------------- ------ --------------
  NORTHEAST                       42984048                 614300                        (565700--693900)           1.43   (1.32--1.62)
  ** **New England                11293971                 157800                        (143400--182100)           1.40   (1.27--1.61)
  **  **Connecticut               2757082                  36800                         (33500--42400)             1.33   (1.21--1.54)
  **  **Maine                     1053828                  11200                         (9600--13900)              1.06   (0.91--1.32)
  **  **Massachusetts             5128706                  74100                         (66900--85600)             1.44   (1.30--1.67)
  **  **New Hampshire             1029236                  11000                         (9300--13700)              1.07   (0.91--1.33)
  **  **Rhode Island              828611                   17500                         (15600--21000)             2.12   (1.89--2.53)
  **  **Vermont                   496508                   7200                          (6100--9400)               1.45   (1.23--1.89)
   Middle Atlantic                31690077                 456500                        (421300--513200)           1.44   (1.33--1.62)
  **  **New Jersey                6726680                  90700                         (83000--103000)            1.35   (1.23--1.53)
  **  **New York                  15053173                 223700                        (207000--252700)           1.49   (1.38--1.68)
  **  **Pennsylvania              9910224                  142100                        (129200--160900)           1.43   (1.30--1.62)
  MIDWEST                         50798893                 578600                        (527700--659200)           1.14   (1.04--1.30)
   East North Central             35269776                 378800                        (345200--429200)           1.07   (0.98--1.22)
  **  **Indiana                   4875504                  59100                         (52600--68300)             1.21   (1.08--1.40)
  **  **Illinois                  9701453                  68400                         (62500--78000)             0.71   (0.64--0.80)
  **  **Michigan                  7539572                  101200                        (92000--114600)            1.34   (1.22--1.52)
  **  **Ohio                      8805753                  119000                        (107700--135000)           1.35   (1.22--1.53)
  **  **Wisconsin                 4347494                  31100                         (28000--36200)             0.71   (0.64--0.83)
   West North Central             15529117                 199800                        (181700--231100)           1.29   (1.17--1.49)
  **  **Iowa                      2318362                  24600                         (21700--29500)             1.06   (0.94--1.27)
  **  **Kansas                    2126179                  29900                         (26600--35200)             1.41   (1.25--1.66)
  **  **Minnesota                 4019862                  41500                         (37600--48500)             1.03   (0.94--1.21)
  **  **Missouri                  4563491                  76900                         (68900--88300)             1.69   (1.51--1.93)
  **  **Nebraska                  1367120                  16100                         (14300--19500)             1.18   (1.05--1.42)
  **  **North Dakota              522720                   4400                          (3700--6200)               0.83   (0.71--1.19)
  **  **South Dakota              611383                   6300                          (5400--8700)               1.03   (0.88--1.42)
  SOUTH                           86766987                 1561600                       (1427700--1768900)         1.80   (1.65--2.04)
   South Atlantic                 46020646                 712900                        (652100--805700)           1.55   (1.42--1.76)
  **  **Delaware                  692169                   13600                         (12200--16100)             1.97   (1.76--2.33)
  **  **District of Columbia      500908                   16400                         (14400--19500)             3.27   (2.87--3.90)
  **  **Florida                   14799219                 245600                        (221700--280700)           1.66   (1.50--1.90)
  **  **Georgia                   7196101                  84500                         (76800--96100)             1.17   (1.07--1.34)
  **  **Maryland                  4420588                  82000                         (74900--93100)             1.86   (1.69--2.11)
  **  **North Carolina            7253848                  117300                        (106600--133100)           1.62   (1.47--1.83)
  **  **South Carolina            3544890                  62300                         (56200--71400)             1.76   (1.58--2.01)
  **  **Virginia                  6147347                  66700                         (60800--76000)             1.09   (0.99--1.24)
  **  **West Virginia             1465576                  24400                         (21000--29500)             1.66   (1.43--2.01)
   East South Central             14025119                 264300                        (236500--303300)           1.88   (1.69--2.17)
  **  **Alabama                   3647277                  52400                         (47000--60400)             1.44   (1.29--1.66)
  **  **Kentucky                  3315996                  54200                         (47200--63800)             1.63   (1.42--1.92)
  **  **Mississippi               2211742                  35200                         (31300--40900)             1.59   (1.42--1.85)
  **  **Tennessee                 4850104                  122500                        (108900--141100)           2.53   (2.25--2.91)
   West South Central             26721222                 584400                        (536000--664500)           2.19   (2.01--2.49)
  **  **Arkansas                  2204443                  37500                         (33000--43900)             1.70   (1.50--1.99)
  **  **Louisiana                 3415357                  76200                         (69300--86400)             2.23   (2.03--2.53)
  **  **Oklahoma                  2821685                  94200                         (83800--112900)            3.34   (2.97--4.00)
  **  **Texas                     18279737                 376600                        (345900--428000)           2.06   (1.89--2.34)
  WEST                            54014143                 1157400                       (1060100--1341100)         2.14   (1.96--2.48)
   Mountain                       16368084                 291900                        (266100--339700)           1.78   (1.63--2.07)
  **  **Arizona                   4763003                  90000                         (81400--104600)            1.89   (1.71--2.20)
  **  **Colorado                  3803587                  66100                         (60000--76500)             1.74   (1.58--2.01)
  **  **Idaho                     1138510                  16400                         (14200--20200)             1.44   (1.25--1.77)
  **  **New Mexico                1540507                  42600                         (37900--51400)             2.76   (2.46--3.34)
  **  **Montana                   765852                   14900                         (12900--19300)             1.94   (1.69--2.52)
  **  **Utah                      1892858                  17600                         (15500--21300)             0.93   (0.82--1.13)
  **  **Nevada                    2035543                  36500                         (32800--42700)             1.80   (1.61--2.10)
  **  **Wyoming                   428224                   7800                          (6700--10200)              1.83   (1.56--2.39)
   Pacific                        37646059                 865400                        (792300--1002900)          2.30   (2.10--2.66)
  **  **Alaska                    522853                   11400                         (9700--16400)              2.19   (1.85--3.13)
  **  **California                27958916                 629600                        (578800--726100)           2.25   (2.07--2.60)
  **  **Hawaii                    1056483                  15700                         (13600--20300)             1.48   (1.29--1.92)
  **  **Oregon                    2964621                  90500                         (79800--106800)            3.05   (2.69--3.60)
  **  **Washington                5143186                  118300                        (105800--138800)           2.30   (2.06--2.70)
  50 US States & Washington, DC   234564071                3911800                       (3 589 400--4 447 500)     1.67   (1.53--1.90)

Abbreviations: CI, confidence interval; Anti-HCV, hepatitis C virus antibody.

^a^Defined as persons with HCV antibodies, indicating past or current hepatitis C infection.

![Estimated total persons with hepatitis C virus antibody (anti-HCV; indicating past or current HCV infection) (*A*) and anti-HCV prevalence rates (*B*), United States and District of Columbia, 2010.](cix20202){#F2}

In sensitivity analyses that considered the addition of 2 potential indicators of HCV-related deaths, the above patterns were preserved, generally yielding state-level estimates closer to the national average ([Figure 3](#F3){ref-type="fig"} and Supplementary Tables 3--4). Inclusion of cirrhosis-related mortality resulted in 39 of 51 state estimates within the 95% CI bounds for the primary estimates that used only HCV-specific mortality. The median absolute deviation of state estimates between these 2 estimation approaches was 8% (interquartile range \[IQR\], 5%--16%, multiplicative scale). Inclusion of HCC-related mortality resulted in 50 of 51 state estimates that were within the 95% CI bounds for the primary estimates using HCV-specific mortality. The median absolute deviation of state estimates between these 2 estimation approaches was 3% (IQR, 2%--6%). Results were similar when considering alternative, but less representative PAF estimates (Supplementary Tables 5--6). There was high agreement between the primary anti-HCV prevalence estimates and 11 external estimates of state-level HCV infection prevalence (Supplementary Table 1). The 2 external estimates that utilized state-level HCV testing data (Arkansas, Oregon) were closest to our primary estimates (5.5% and 4.8% higher, respectively). To facilitate comparisons, Supplementary Tables 7--8 display model-based chronic HCV infection and NHANES standardization--based anti-HCV estimates.

![Estimated hepatitis C virus antibody (anti-HCV) prevalence rates from sensitivity analyses using additional HCV-related mortality *International Classification of Diseases, Tenth Revision* codes. Abbreviations: anti-HCV, hepatitis C virus antibody; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; PAF, population attributable fraction.](cix20203){#F3}

DISCUSSION {#s9}
==========

We used a small-area estimation approach to synthesize data from 3 publicly available systematic, population-based data systems and provide the first comprehensive state estimates of the prevalence of anti-HCV in the United States. The estimates were robust to multiple approaches based on additional mortality data, and were comparable to independent state estimates. The method and its results can be applied by state and local health officials to guide program planning, set priorities for resource allocation, and evaluate interventions.

These state-specific estimates bring a new level of understanding to our prior knowledge about the epidemiology of HCV infection in the United States. States with high estimated anti-HCV prevalence also contain highly urban populations (eg, Rhode Island, District of Columbia) and high proportions of the population who inject drugs (eg, Vermont, Tennessee, West Virginia) or who are Native Americans (eg, Oklahoma, New Mexico; the model did not explicitly include Native American race) \[[@CIT0026], [@CIT0027]\]. The current anti-HCV prevalence estimates highlight states which, by their demographic structure alone, might be predicted to have lower prevalence. For example, simple NHANES standardization yields 44000 estimated cases in Oklahoma; incorporating additional data on HCV-related deaths in Oklahoma suggests an estimated prevalence more than twice that high.

Our approach has significant methodologic strengths, as the data sources are population-based and representative of the underlying populations. However, our analysis has important limitations. We aggregated data across multiple years of NHANES to achieve a sufficient sample for stable estimates. It is possible that there were secular trends over the NHANES period. The NHANES population samples noninstitutionalized adults and therefore excludes incarcerated persons, homeless persons, those in active military service, and persons on tribal lands. These populations are critical constituents of the US HCV epidemic, comprising up to a fifth of prevalent antibody- positive persons in the United States \[[@CIT0012]\]. Thus, our estimates apply only to noninstitutionalized US populations. Mortality data used to allocate the NHANES-based anti-HCV total included deaths from institutionalized populations. Complete laboratory data in NHANES were nearly universally available for the anti-HCV test, but were less complete for RNA testing. Thus, our primary estimates of persons with anti-HCV includes the 15%--25% of people infected by HCV who may have cleared their HCV infections but retained detectable antibodies \[[@CIT0028]\]. Antibody-based prevalence of individuals previously or currently infected with HCV provides a conservative overestimate of persons indicated for clinical evaluation and HCV-related medical services \[[@CIT0008]\]. The HCV RNA test more accurately indicates active infection needing treatment. Importantly, the proportion of anti-HCV positive persons with detectable HCV by polymerase chain reaction is also influenced by the number of persons successfully treated and cured of their HCV infection. Over time, this proportion should decline as more persons are identified, treated, and cured; however, the proportion will vary among populations with differential access to HCV-related care and treatment.

Finally, NHANES is likely less representative of populations of persons infected in recent years. Incidence of HCV infection has been increasing since 2010, and those infected in more recent epidemics are younger, more likely to live in rural areas, and likely to acquire HCV through needle-sharing behaviors associated with opioid use \[[@CIT0029]\]. Nationally, the number of recent new infections is small relative to the prevalent population, although some states with modest or low prevalence of infection have had larger increases than reflected in national trends \[[@CIT0007]\]. Methods that incorporate recent trends in incident HCV infection and in treatment can improve future iterations of this model.

There is some mismatch between the NHANES and mortality data: mortality data represent older trends in the epidemic. Also, HCV infection may not be consistently diagnosed or recorded on death certificates by state. However, this low sensitivity of identified HCV infection in death records should not cause bias in our estimates unless the likelihood of diagnosis or recording on death certificates varies across states. We posit that deficiencies in diagnosis or recording likely occur, but are at a facility level and do not vary systematically by state. The impact of varying sensitivities of our case definition in mortality data were explored in extensive sensitivity analyses, and did not result in substantial changes to our estimates.

CONCLUSIONS {#s10}
===========

Although national recommendations for HCV prevention, testing, and clinical management are developed by CDC and other authorities \[[@CIT0030]\], decisions regarding the capacity to deliver these services are made at the state level. State-level estimates can inform these decisions in multiple ways. First, these data can prompt reconsiderations of HCV disease burden. These modeled prevalence estimates are based on publicly available data, allowing local authorities to assess biases in data sources used in the model (ie, mortality data) and the representativeness of the modeled data in comparisons with other local data sources (ie, HCV surveillance). Second, these results, supported by local public health authorities, provide new information to engage stakeholders, resulting in agreed-upon state/local estimates of HCV infection prevalence. State-level prevalence estimates allow state and local health officials to consider more investments in surveillance and collection of other strategic data for refining our estimates. These data can also be used to revise HCV-related prevention plans and guide prevention initiatives. For example, these data can help state/local health officials estimate the number of HCV-infected persons who remain undiagnosed. The results may help state Medicaid programs to budget funds for HCV testing and treatment. More broadly, having state-level estimates calculated consistently across states will allow states to assess their standing in relation to other states and to the nation as a whole, and to adapt their prevention and control efforts to national or other state programs that have been shown to be effective.

The approach reported here can be routinely updated as new data become available. The same approach to estimation can also be extended to yield estimates for demographic strata, areas smaller than states, and excluded populations in each state. Modeling approaches can serve as a useful method to quantify the HCV epidemic in the absence of national case surveillance data. However, this should not minimize the imperative of continuing to enhance local surveillance efforts, especially in the context of curative HCV therapies. Surveillance data may provide more accurate and reliable estimates of the burden of HCV infection and serve as the basis for public health programs to diagnose persons living with hepatitis C and link them to appropriate clinical services and treatment.

Supplementary Data {#s11}
==================

Supplementary materials are available at *Clinical Infectious Diseases* online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.

Supplementary Material
======================

###### 

Click here for additional data file.

***Acknowledgments.*** We acknowledge Kevin Weiss for his assistance in compiling external state prevalence estimates for Supplementary Table 1 and Dr Jeremy Grey for his input on estimation methodology.

***Financial support.*** We acknowledge funding from the Centers for Disease Control and Prevention (CDC) National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention Epidemic and Economic Modeling Agreement (U38 PS004646).

***Potential conflicts of interest.*** E. S. R. has received grants from CDC and personal fees from Medidata Inc and Cengage Learning. P. S. S. has received grant support through the CDC, National Institutes of Health, MAC AIDS Fund, and Gilead Sciences. T. H. S.'s institution has a project funded by Gilead Sciences to develop and implement a website to help disseminate HCV surveillance and epidemiology information. All other authors report no potential conflicts. No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

[^1]: Correspondence: E. Rosenberg, Department of Epidemiology, Emory University Rollins School of Public Health, 1518 Clifton Rd NE, GCR 472, Atlanta, GA 30322 (<esrose2@emory.edu>).
