Epidemiology of Hepatitis C virus infection among incarcerated populations in North Dakota

Liton Chandra Deb; Hannah Hove; Tracy K Miller; Kodi Pinks; Grace Njau; John J Hagan; Rick J Jansen

doi:10.1371/journal.pone.0266047

. 2022 Mar 29;17(3):e0266047. doi: 10.1371/journal.pone.0266047

Epidemiology of Hepatitis C virus infection among incarcerated populations in North Dakota

Liton Chandra Deb ^1,², Hannah Hove ^1,³, Tracy K Miller ⁴, Kodi Pinks ⁴, Grace Njau ⁴, John J Hagan ⁵, Rick J Jansen ^1,^6,^7,^8,^*

Editor: Jee-Fu Huang⁹

PMCID: PMC8963564 PMID: 35349606

Abstract

This retrospective cohort study was conducted to determine the prevalence of HCV infections among individuals incarcerated in a state prison system and identify potential contributing factors to HCV infection. North Dakota Department of Corrections and Rehabilitation (NDDOCR) data from 2009 to 2018 was used and period prevalence was calculated for this 10-year time period. The period prevalence of HCV infection was (15.13% (95% CI 14.39–15.90) with a marginally significant (p-value: 0.0542) increasing linear trend in annual prevalence over this period. Multivariate logistic regression analysis was used to identify risk factors associated with HCV infection. The main significant independent risk factors for HCV infection in this incarcerated population were age >40 years [OR: 1.78 (1.37–2.32)]; sex [OR: 1.21 (1.03–1.43)]; race/ethnicity [OR: 1.97 (1.69–2.29)]; history of intravenous drug use (IVDU) [OR: 7.36 (6.41–8.44)]; history of needle or syringe sharing [OR: 7.57 (6.62–8.67)]; and alcohol use [OR: 0.87 (0.77–0.99)]. Study limitations include uncollected information on sexual history, frequency or duration of injection drug use and blood transfusion history of the incarcerated population. Considering the high prevalence of HCV infection and its associated risk factors, it is important to implement prevention programs such as syringe/needle exchanges and counsel with imprisoned IVD users.

Introduction

Hepatitis C virus (HCV) infection is the most frequently reported blood borne infection in the United States in both general and incarcerated populations [1]. HCV causes both acute and chronic infection. Acute HCV infection mainly occurs within the first 6 months after a person is exposed. Although acute infection can be a short illness, in the majority cases it leads to a lifelong or chronic infection. HCV infection is also considered a major disease worldwide with a prevalence of almost 3%, which means that more than 170 million people suffer with chronic hepatitis C [2]. It is considered one of the world’s current significant health problems as HCV leads to severe liver complications and early mortality [3].

Based on a US study between 2003 and 2013 examining national multiple-cause-of-death (MCOD) data, the annual HCV related deaths were increasing since 2007 with an estimate that 19,368 people died due to HCV in 2013[4]. From 2003 to 2013 the number of deaths associated HCV surpassed the total number of deaths from 60 nationally notifiable infectious diseases combined [4]. In fact, in the US, a national health survey of data collected from 2003 to 2010 indicated that approximately 3.5 million people were infected with HCV with an overall incidence rate 1.0 cases per 100,000 population [5].

Previous studies have indicated that incarcerated populations have a disproportionately higher risk to HCV exposure and infection compared to the general US population. The existing studies on incarcerated populations have indicated that HCV antibody positivity rates range from 12 to 34%, which is over 20 times the national level [6–10]. As previously mentioned, HCV infection disproportionately affects those who have been in jail and prison [11]. Unfortunately, the data for chronic HCV infection in incarcerated populations is scarce and not current in the US. Still existing data indicates a high rate of infection and disease burden among the incarcerated population. For example, in 2002, Hammett et al. indicated that US correctional populations in 1997 accounted for 29.4% to 43.2% of total HCV infections [12]. Also, the CDC database for 2003 derived from HCV surveillance data from eight states reported that 16% to 41% of prison populations in those eight states had serological evidence of prior HCV exposure and the HCV cases among correctional population was responsible for 1.3 million (39%) of the HCV burden within those states[13]. Thus, based on published reports, HCV infection prevalence is much higher in prison populations than in general populations because of a much higher prevalence of risk-factors among the prison population [14].

Risk factors of HCV that are observed at a higher rate in incarcerated populations compared to the general population includes heavy alcohol drinking, IVDU, and needle sharing. Heavy alcohol drinking has been reported to increase the risk of HCV by 1.58 times [15], IVDU is reported in a meta-analysis study to increase the risk of HCV infection by 24 times [16], while needle sharing has been associated with an increased risk of 2.58–4.06 times [17, 18].

There is a lack of current data on HCV infections and risk factors in incarcerated people in the US. Therefore, this study was conducted from 2009 to 2018 in North Dakota Department of Corrections and Rehabilitation (NDDOCR) to update data on the prevalence of HCV infections in incarcerated people in the US and identify possible contributing risk factors.

Methodology

Study population

This is a retrospective cohort study of 8,836 incarcerated people in NDDOCR from 2009 to 2018. Of the total 8,836 justice involved individuals, 1,337 were chronic HCV virus and 7,499 were HCV virus negative when testing for antibodies to HCV (anti-HCV) in serum. Reflex testing with universal opt-out was completed upon arrival for HCV antibody and if positive, viral load and genotype identification was performed. All 8,836 incarcerated persons were unique individuals; repeated persons were entered in the database as a single incarcerated person and only counted once in this database. The study protocol, and materials were reviewed and approved by the ND Department of Health Institutional Review Board. As in the original study (Substance Use and early Death Among Justice Involved Individuals of the ND Dept of Corrections and Rehabilitation, 2010–2018 (ND-045-052019)), informed consent was not collected, due to minimal risk associated with this study. Data used for this study were the de-identified data set created from the original study.

Data collection

Demographic, medical, behavioural, and incarceration-related information was collected from NDDOCR with the help of North Dakota Department of Health (NDDoH). Medical information consisted of the history of intravenous drug use, abnormal liver test results, and screening results of HCV (testing for antibodies to HCV within asymptomatic incarcerated persons). Behavioural information included the history of alcohol consumption, drug use, and needle sharing. The needle sharing variable was assessed using the question, “Now or in the past, have you shared injection drugs or needles with anyone else? This includes needles, syringes, spoons, filters or rinse water?” The intention was to identify opportunities to transmit HCV during the injection process. Demographic information included birth date, sex, and race/ethnicity. Also, incarceration-related variables included length of total lifetime incarceration, number of times incarcerated, and the age at first incarceration. All behavioural, medical and incarceration related information was routinely collected for each individual at the time of their entry into the correctional facilities. In case of repeated offenders their first occurrence was only included in the study sample.

Statistical analysis

Collected demographic, medical, behavioural, and incarceration-related information were initially entered into Microsoft excel spreadsheet and coded for analysis. Statistical Analysis System (SAS) version 9.4 (SAS Institute Inc., Cary, NC, USA) and R statistical program version 4.1.2 were used to perform statistical analyses and generate tables and figures. Age was categorized into 3 groups: less than 20, 21 to 40 and more than 40 years old. Age was categorized into three groups based on the previous literature detailing that people born during 1945–1965 (i.e., baby boomers) are at higher risk of HCV as a group because of potential contaminated blood exposures. Race/ethnicity was coded into 5 groups: Black (black and African American), Caucasian, Native American, Hispanic and others. All the other variables were categorized based on yes or no response. Prevalence with 95% Confidence Intervals (CIs) were calculated on the basis of binomial distributions. Summary statistics included frequency tables, for categorical variables, medians and 95% CIs. Associations between HCV antibody status and demographic, risk exposure–related, and incarceration-related variables were conducted using the χ² test of association (or Fisher’s exact test, in cases for which the expected cell size was less than 5 events), and Odds ratio (ORs) and 95% CIs were calculated. Independent associations between the various exposures and HCV antibody were assessed using unconditional logistic regression analyses. Explanatory variables with p-values ≤ 0.10 on bivariate analysis, were included into a backward stepwise logistic regression analysis. Select interactions were also checked based on previously published observations and our study results. Confounding effect of an explanatory variable was also evaluated by assigning the change of parameter estimates before and after removal of a variable from the model. If the parameter estimates of a variable increased or decreased ≥ 10% after removing another variable from the model, then this one explanatory variable was considered to have a confounding effect on the outcome variable. Regression coefficients were converted into odds ratios (ORs; eβ) and their 95% confidence intervals (CIs). All tests were considered statistically significant at (P ≤ 0.05) unless otherwise noted above.

Results

Descriptive analysis of all variables was completed and presented in Table 1. Here, 1,337 individuals were diagnosed with HCV out of 8,836 who were housed by the NDDOCR during the study period, for a period prevalence of 15.13% (95% CI 14.39–15.90). HCV diagnosis was based on incoming blood tests and antibody test (genotype confirmatory tests) with acute versus chronic determined by persistence on 6 month recheck (approximately 100% chronic). Of the 8,836 incarcerated people, 1,553 individuals were excluded from the risk factors analysis due to lack of behavioral information such as their history of alcohol use, needle sharing and drug use. Finally, 7,283 individuals were used for further analysis: 1,256 individuals were HCV antibody (Ab) positive and 6,027 were HCV antibody (Ab) negative on screening. The annual HCV prevalence for the years 2009–2018 are presented in Table 1 and visualized in Fig 1. A marginally significant (p-value = 0.0542) increasing linear trend was observed over the study period (Fig 1). The prevalence of HCV was significantly higher in the older age category (21.03%) compared with younger age category (13.01%) (Table 1). Also, the prevalence was much higher in people who had a history of taking intravenous drugs (36.11%) compared with those without history of intravenous drugs (6.98%). Similarly, the prevalence was much higher for people with sharing needles (46.82%) compared with those that did not have any history of needle sharing (10.41%) (Table 1).

Table 1. Univariable analysis (chi-square test) of plausible determinants of HCV antibody (Ab) in Incarcerated population.

Variables	HCV antibody (Ab) Positive n (%)	HCV antibody (Ab) Negative n (%)	HCV Period Prevalence Over Study (%)	P^*-value
Age				< .0001
≤20 year	83 (6.61)	555 (9.21)	13.01
21 to 40 years	882 (70.22)	4379 (72.66)	16.76
>40 year	291 (23.17)	1093 (18.14)	21.03
Sex				< .0001
Female	281 (22.37)	937 (15.55)	23.07
Male	975 (77.63)	5090 (84.45)	16.08
Race/ethnicity				< .0001
Black	23 (1.83)	399 (6.62)	5.45
Caucasian	641 (51.04)	2537 (42.09)	20.17
HIS	45 (3.58)	229 (3.80)	16.42
NAT	360 (28.66)	724 (12.01)	33.21
Others	187 (14.89)	2138 (35.47)	8.04
Birth Category				< .0001
Before 1945	2 (0.16)	16 (0.27)	11.11
1945 to 1965	179 (14.25)	540 (8.96)	24.90
After 1965	1075 (85.59)	5471 (90.77)	16.42
Time spent in incarceration				0.4749
Less than 1 year	173 (13.77)	785 (13.02)	18.06
More than 1 year	1083 (86.23)	5242 (86.98)	17.12
Alcohol				0.0025
Yes	551 (43.87)	2926 (48.55)	15.85
No	705 (56.13)	3101 (51.45)	18.52
Drug Use				< .0001
Yes	1109 (88.30)	4608 (76.46)	19.40
No	147 (11.70)	1419 (23.54)	9.39
History of Intravenous Drug Use (IVDU)				< .0001
Yes	927 (73.81)	1640 (27.21)	36.11
No	329 (26.19)	4387 (72.79)	6.98
History of Needle Sharing				< .0001
Yes	640 (50.96)	727 (12.06)	46.82
No	616 (49.04)	5300 (87.94)	10.41
Year of Incarceration			HCV Annual Prevalence (%)	< .0001
2009	119 (10.40)	425 (7.69)	21.88
2010	100 (8.74)	539 (9.75)	15.65
2011	79 (6.91)	467 (8.45)	14.47
2012	83 (7.26)	580 (10.49)	12.52
2013	90 (7.87)	595 (10.77)	13.14
2014	133 (11.63)	679 (12.29)	16.38
2015	170 (14.86)	662 (11.98)	20.43
2016	169 (14.77)	690 (12.48)	19.67
2017	137 (11.98)	600 (10.86)	18.59
2018	64 (5.25)	290 (5.25)	18.08

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n, Number of people; %, percentage; HCV, Hepatitis C Virus; HIS, Hispanic; NAT, Native American

*p values were calculated using the Chi-squared test

Fig 1 — The blue line represents the line of best fit and the surrounding dark grey area represents the 95% confidence band.

Information on 7,283 incarcerated individuals was used in this analysis with 1,256 HCV antibody (Ab) positive individuals and 6,027 HCV antibody (Ab) negative individuals. Univariable analysis revealed that age, sex, race/ethnicity, birth category, alcohol use history, drug use history, history of taking intravenous drug and shared needle history were significantly associated with HCV active infection (Table 1). Hence, these eight variables were included in the multivariable analysis. In the final multivariable logistic regression model with backward elimination six variables namely age, sex, birth category, alcohol use history, history of taking intravenous drug and shared needle history are retained as significant and independent predictors of HCV status at a p<0.05. Results of the final multivariable logistic regression model were presented in (Table 2). Odds of HCV active infection was 1.78 (1.37–2.32) times higher in individuals >40 years old than in individuals ≤20 years old, 2.65 (0.6–11.65) times higher in individuals who born between 1945 to 1965, and 1.21 (1.03–1.43) times higher in incarcerated females than in incarcerated males. The odds of HCV active infection were 7.36 (6.41–8.44) times higher in incarcerated persons who had a history of taking intravenous drugs compared with non-intravenous drug users, and was 7.57 (6.62–8.67) times higher in those who had a history of shared drug injection or needle sharing. In this study, incarcerated persons with alcohol use history showed significantly lower odds of HCV active infection than those that did not have any alcohol use history after adjusting for the other five variables in the model (Table 2). Fig 1 in the supplement shows the percentage of cases which identified having a selected risk behaviour. It is observed that a majority cases had a history of taking intravenous drugs and needle sharing (S1 Fig). Potential interaction between IVDU and either sex or race/ethnicity was investigated. Although the distribution of IVDU across sex and race/ethnicity groups was different than expected using a chi-squared test (S1 Table), an interaction term in a logistic regression model (e.g., HCV ~ sex + IVDU + sex: IVDU) was not significant for either sex by IVDU or race/ethnicity by IVDU (not shown).

Table 2. Final model of multivariable logistic regression analysis of plausible determinants of HCV antibody (Ab) in incarcerated populations.

Variables	Odds ratio (95% Confidence interval)	P-value^*
Age		<0.0001
≤20 year	1
21 to 40 years	1.38 (1.08–1.76)
>40 year	1.78 (1.37–2.32)
Sex		0.02
Female	1.21 (1.03–1.43)
Male	1
Race/ethnicity		<0.0001
Caucasian	1
Black	0.23 (0.15–0.35)
HIS	0.78 (0.56–1.08)
NAT	1.97 (1.69–2.29)
Others	0.38 (0.32–0.45)
Birth category		0.002
Before 1945	1
1945 to 1965	2.65 (0.6–11.65)
After 1965	1.57 (0.36–6.85)
Alcohol		0.002
Yes	0.87 (0.77–0.99)
No	1
History of Intravenous Drug Use (IVDU)		<0.0001
Yes	7.36 (6.41–8.44)
No	1
History of Needle Sharing		<0.0001
Yes	7.57 (6.62–8.67)
No	1

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HCV, Hepatitis C Virus; HIS, Hispanic; NAT, Native American

*p values were calculated using the Chi-squared test

Discussion

The results of this study indicate that over a period of 10 years the prevalence of HCV among incarcerated populations in ND correctional facilities was 15.13%. As expected, the rate of HCV virus seropositivity among ND incarcerated populations from 2009 to 2018 is much higher than the seroprevalence of 1.7% (95% CI 1.4–2.0%) estimated by using National Health and Nutrition examination Survey (NHANES) for the non-institutional US population from 2013 to 2016 [19]. HCV prevalence estimates among incarcerated populations reported from the other studies such as California (34.3%) and Italy (10.4%) were also higher [6, 20]. Overall, available data suggests that HCV is highly prevalent among individuals incarcerated in prison settings [17, 21, 22]. This variation in the prevalence among the studies carried out in different regions is most likely attributed to the type of incarcerated populations surveyed on the basis of associated risk factors such as IVDU, history of imprisonment, high-risk sexual behaviours, or other high-risk behaviours. Also, as previously mentioned, HCV infection among the incarcerated population is largely attributed to their history of using IVDU. Thus, the prevalence of self-reported IVDU was higher (43%) among incarcerated populations in California as compared with the ND incarcerated population self-reported prevalence (36%) and may account for some of the difference between the HCV rates between these two states [6].

The findings of this study showed that the odds of HCV infection were 1.78 times higher among incarcerated individuals who were >40 years old compared with ≤20 years old. This finding is in line with other published investigations, including the California study that reported age independently correlated with HCV infection and that the prevalence increased with age [6]. Also, In terms of birth cohorts, the results of this study indicated that the odds of being HCV positive are 2.65 times higher in incarcerated individuals who were born between 1945 to 1965 than those born before 1945. Indeed, results from another study among US veterans are consistent this study’s findings [23].

The results of this current ND study showed that the risk of HCV infection was higher in incarcerated females than in incarcerated males. In this study, the odds of HCV infection among incarcerated females were 1.21 times higher than for incarcerated males. Other studies have also observed that HCV infection was observed more frequently in incarcerated females than in incarcerated males [23, 24], but other studies observed higher rates among males compared to females [25]. A probable explanation behind this higher rate in females was proposed in a California study, in which a higher prevalence of HCV infected women who reported that their sexual partners were injection drug users [6]. Also, it was worthy to pointing out that those female populations’ offenses more frequently related to drugs and prostitution. Unfortunately, due to the lack of data availability for ND, the sexual histories of either incarcerated males or females were not included.

We observed a significant association of HCV infection with the history of alcohol use by the incarcerated populations. Incarcerated persons with alcohol use history showed significantly lower odds of HCV infection than those that did not have any alcohol use history. This is in contrast to the National Institute on Alcohol Abuse and Alcoholism (NIAAA) report summarizing that heavy alcohol drinking increases the risk of HCV infection [26]. It is likely that our observed negative correlation was due to unmeasured confounding effects.

The results of this current study revealed that the risk of HCV infection was higher in incarcerated Native Americans (NAT). In this study, the odds of HCV infection among incarcerated NAT were 1.97 times higher than for incarcerated Caucasian. When looking at rates of IVDU for NAT and Caucasians, we also see a lower percentage of Caucasian IVDU (42.5) compared to NAT IVDU (49.1%) (S1 Table) which may partially explain the increased risk of HCV observed among NAT. Other studies observed that HCV infection was observed more frequently in incarcerated blacks [27, 28], however, we did not observe this in our study. This variation could be due to the self-reporting of race/ethnicity and the difference in minority populations across the US.

The findings of this study also showed that 73.80% of the HCV positive incarcerated populations in ND had a history of taking intravenous drugs. This finding is in line with other published investigations, including a meta-analysis study that found that male incarcerated individuals using injected drugs were 24 times more likely to be HCV positive compared with using non-injecting drugs [16]. The results from this ND study revealed that the odds of HCV infection among incarcerated populations with histories of intravenous drug use were 7.36 times higher compared with non-intravenous drug users.

The odds for HCV for incarcerated populations who had a history of shared drug injection or needle sharing was 7.57 times higher in comparison with those who had not a history of needle sharing. This association has also been reported in other studies, observing that the HCV infection is 2.58 and 4.06 times higher among those who had a history of needle sharing respectively in Brazil and Iran [21, 29].

Multiple strategies can be used to reduce the prevalence of HCV among incarcerated individuals. One approach, screen and treat, can be a cost-effective way to reduce ongoing HCV transmission before release into the community [30]. In a study conducted by He et al., universal opt-out HCV screening was a cost-effective way to reduce ongoing HCV disease and transmission benefiting both individuals and the community [30]. Screening has shown to be an effective first step in addressing HCV seropositivity and providing linkage to care but the practice has been under-utilized and inconsistent throughout incarcerated populations (Kronfli-International drug policy).

Another approach involves cross-collaboration among city, county and state public health departments to provide HCV positive incarcerated individuals proper linkage to care for treatment and education. This would involve making sure known IVDU (HCV positive and HCV negative) are released with the resources and education on where needle-exchange programs are located and how they can be utilized [31]. Needle exchange programs help reduce overall healthcare costs, reduce HCV transmission and reduce risky behaviours, such as needle sharing [32]. Currently, North Dakota has 4 needle exchange programs [33]. By increasing needle exchange programs throughout the state, more individuals (previous incarcerated and general population) can potentially benefit from these needle-exchange programs.

Currently all individuals admitted to the NDDOCR undergo screening, assessment and diagnosis for substance use disorders (SUD), HCV, and HVI. An individualized treatment plan is developed for SUD for each resident within 30 days of admission and treatment is offered to all individuals with chronic hepatitis C and an APRI of >0.5. The American Society of Addiction Medicine criteria are used to place each resident into the appropriate level of care for effective SUD treatment (https://www.asam.org/asam-criteria/about-the-asam-criteria). The NDDOCR utilizes evidence-based medication-assisted treatment for opioid use disorders and alcohol use disorders following the ACA-ASAM Joint Public Policy Correctional Policy on the Treatment of Opioid Use Disorders for Justice Involved Individuals (https://www.asam.org/docs/default-source/public-policy-statements/2018-joint-public-correctional-policy-on-the-treatment-of-opioid-use-disorders-for-justice-involved-individuals.pdf?sfvrsn=26de41c2_2). NDDOCR utilizes the University of Cincinnati College of Education, Criminal Justice, and Human Services Cognitive-Behavioral Interventions for Substance Abuse (CBI-SA) curriculum in treatment of SUD. Potential opportunities for the state of North Dakota and NDDOCR to improvement of these disorders include fostering local needle exchanges and provide HCV treatment to all identified HCV patients.

Direct antiviral agents (DAAs) are an effective yet underutilized tool to help treat incarcerated individuals with HCV. DAA therapy has a high cost and coupled with prison turnover rates and transfers, makes proper administration difficult [34]. However, modelling studies have shown that DAA therapy administered to chronic HCV incarcerated individuals who are known IVDU and have a sentence greater than 16 weeks could decrease future HCV transmission by 26–70% depending on length of stay and biological uptake of the drug [35]. A modelling study performed a cost-effective analysis of DAAs in an Australian prison system and has shown that DAAs fell below the willingness to pay threshold for Australia making DAAs a value in terms of total healthcare expenditure [35]. While these studies are just models, utilizing DAAs in IVDU who are incarcerated can benefit the community upon their release.

This study has limitations that should be mentioned. The major drawback was no information about the participants’ sexual histories, and there was a lack of behavioural information collected such as frequency or duration of injection drug use and their blood transfusion histories. Additionally, the crude categorization of alcohol consumption (yes/no) likely resulted in our observed results and an incomplete confounding adjustment. In this retrospective study, we had additional limitations related to the collection of some data. HCVRNA data is only available for a small fraction of our study population and was not incorporated into this study. Well-established risk factors such as receiving surgery, blood transfusion, family members with HCV infection were also not assessed in this population. Had this more detailed information been collected, we would have further adjusted our analyses, which may have changed our observed results.

Conclusion

Our findings clearly indicated that the HCV prevalence in ND incarcerated populations is higher compared with the general population. Also, specific incarcerated populations have higher HCV infection, especially those who have a history of taking intravenous drugs and sharing needles or syringes. HCV screening and treatment and providing education programs to reduce high risk behaviours should be the priority and would be helpful tin reducing the HCV burden in incarcerated populations. Increased needle exchange programs throughout the state can help known IVDU post incarceration. These strategies can help reduce the HCV burden in incarcerated populations and have an indirect impact on reducing HCV prevalence in general populations. The results of this study clearly indicate that policy makers should consider more precautionary measures for preventing HCV in high-risk groups of populations during incarceration. Although it is not always possible to provide antiviral treatment to a large proportion of individuals during their incarceration periods because of their short stays, they still would benefit from HCV education and counselling programs if provided on a regular basis. In addition, the majority of HCV patients will suffered with liver problems, so it would be helpful to provide better treatment facilities for liver problems, which in turn would lead to delayed HCV mortality.

Supporting information

S1 Fig. Reported 1256 HCV cases by risk behavior.

(TIFF)

Click here for additional data file.^{(58.6KB, tiff)}

S1 Table. Sex and race/ethnicity groups by intervenes drug use in study population.

(PDF)

Click here for additional data file.^{(36.2KB, pdf)}

Acknowledgments

The authors thank the North Dakota Department of Corrections and Rehabilitation (NDDOCR) and North Dakota Department of Health (NDDoH) for data management.

Data Availability

Data cannot be shared publicly because of the sensitive nature of justice involved individual data as determined by the North Dakota Department of Corrections Research Ethics Committee. However, data can be obtained for researchers who meet the criteria for access to this confidential data (contact via Kayli Richards karichards@nd.gov).

Funding Statement

Funding for this project provided by the Department of Health and Human Services (https://www.hhs.gov/, G17.1102, TM) with subaward issued to RJJ. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0266047.r001

Decision Letter 0

Andrea Knittel

24 Nov 2021

PONE-D-21-32680Epidemiology of Hepatitis C virus infection among incarcerated populations in North Dakota.PLOS ONE

Dear Dr. Jansen,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. You may note that there is some conflicting advice from the two reviewers - one recommends updated international citations while the other suggests narrowing the focus to the US. I am inclined to recommend the latter, given the scope of the work described in the manuscript. While you should respond to all of the reviewer comments, it is reasonable to describe this alternate approach in justifying the removal of the international content.

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: Partly

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

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Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Overall, this manuscript provides some useful data from a state correctional facility. The authors do a nice job of presenting 10 years of data which add to the current literature around HCV prevalence among incarcerated populations. However, there are numerous inconsistencies, grammatical errors and organizational challenges which need to be addressed.

Introduction:

Line 54: please insert comma after short illness; also this sentence needs to be referenced.

Lines 66-71: these sentences can be omitted since the following paragraph discussed HCV studies among correctional populations (and the authors could transition to this section by indicating that correctional populations have a disproportionate risk to HCV exposure and infection).

Line 75: suggest making this more specific to US populations (there have been several recent studies in other countries on HCV prevalence among correctional populations).

Line 79: please change to: derived from HCV surveillance data from eight states…

Line 81: 1.3 million of the 3.3 million populations? This doesn’t make sense, please clarify.

Lines 83-84: while the data presented certainly imply that correctional populations have much higher prevalence of HCV related risk factors (and studies have clearly documented this), the authors present very little data specific to risk factors. Please include studies that reference specific HCV risk factors in order to justify this.

Methods:

Line 91: what do the authors mean by “screening”? Does this mean testing? If so, what type of testing was performed?

Lines 92-93 (and elsewhere in the manuscript): please use more person-first language and avoid using pejorative terms such as “offenders”. Suggest using persons/individuals who are incarcerated.

Line 96: please change to: informed consent was not collected

Line 98: please change to: data used for this study were the…

Line 102: Again, please describe what screening means and what serological testing was performed.

Line 102: Was the behavioral data collected only through the study or is this information that the prison regularly collects from everyone?

Line 104: Do the authors mean length of total lifetime incarcerated?

Line 105: Please change to: age at first incarceration.

Line 107: How many correctional facilities were included? It would be helpful to provide a brief statement about the organizational structure of the NDDDOCR.

Line 115: Baby boomers are at higher risk, but not all are at high risk, please clarify.

Line 116: Hispanic is not a race so presumably the authors decided to combine race and ethnicity?

Line 117: Prevalence is not a rate, please change.

Line 119: Again, need to specify the testing performed.

Line 126: what do the authors mean by “biologically meaningful interactions”?

Line 126: Which two explanatory variables were thought to be potential confounders and why? Or do the authors mean that they assessed effects of confounders 2 explanatory variables at a time using the methods described? Please clarify.

Results:

Line 135: How were individuals diagnosed? Were the authors able to assess acute versus chronic infection? Was confirmatory testing prior to diagnosis done?

Line 136: Please do not begin a sentence with a number.

Line 137: Please change behaviors to behavioral. What behavioral information was missing (or were the data just incomplete)? Please be more explicit as to what data were missing and why these individuals were excluded.

Line 138: remove “in where” and insert a semi-colon between analysis and 1,1256.

Line 140: please use older age category rather than older people category. Same with younger people.

Line 141: Please change to the prevalence was (not is) much higher

Lines 142-143: this is very confusing as worded. Should be prevalence was higher in people with hx of IDU relative to those without such a hx. And being a new sentence for data related to sharing needles.

Table 1: did the authors collect specific information about frequency and duration of both alcohol and drug use? Especially for alcohol use, a dichotomous yes/no variable is not particular informative.

Line 148: please change to incarcerated individuals rather than peoples.

Lines 148-149: please insert commas for 1,256 and 6,027.

Table 2 with univariate analyses is not needed. The authors can just state what variables were selected, based on univariate analyses, for the multivariate model.

Line 156: change were to are.

Line 157: remove the parentheses around age. Same in the following sentence.

Line 159: add ‘s’ to male.

Line 160: change have to had.

Line 162: what does shared drug injection mean? How does this differ from needle sharing? Does the refer to sharing of drug injection equipment? How were these data collected?

Line 163: the finding related to alcohol may be due to the very imprecise manner in which this variable was measures (e.g. simple yes/no).

Line 166: add an ‘a’ in front of majority.

Discussion:

Line 180: since the authors collected data over 10 years, why didn’t they report annual HCV prevalence and conduct trend analyses to see how the prevalence changed over time?

Line 185: Should be HCV prevalence estimates.

Line 187: please change to: have been reported from other studies in countries such as…

Line 189: Being a new sentence: Overall, available data suggests…

Line 189: please change prisoners to individuals incarcerated in prison settings.

Line 192: this is the first reference to IDU. Previously, the authors have used the term intravenous drug use. Suggest using the acronym IDU consistently throughout.

Line 194: include citation for IDU statement.

Line 195: please be consistent with use of acronyms. Here the authors use IVDU for the first time.

Lines 195-197: please be careful with the use of the term rate. The authors are using prevalence estimates and prevalence is not a rate.

Line 204: please change peoples to individuals

Line 205: why is Birth capitalized?

Lines 205-208: this section should be integrated into the above section where the authors discuss their findings by age.

Lines 209-217: did the authors examine IDU history by gender? This may also partially explain the findings from this study. The authors should also note that this finding is somewhat contradictory to other studies that have documented higher HCV prevalence among men relative to women. Why didn’t the authors collect information on sexual history since they collected data on substance use history? This is a limitation.

Lines 218-223: As previously mentioned, the imprecise measurement of alcohol assumption likely contributed to this finding. The authors need to note this and explain why they reported such a crude measure for alcohol consumption. This is a limitation.

Lines 224-228: this is a weak discussion of the finding that HCV infection was higher among incarcerated Native Americans. As with gender, the authors could have examined history of IDU by race to see if more Native Americans reported IDU behavior.

Line 231: please change inmates to incarcerated individuals.

Line 233: change to non-injecting drugs

Lines 237-242: suggest integrating history of IDU and history of syringe sharing as these overlap. The authors also allude to shared drug injection and as previously noted, this is not clear.

Line 243: there needs to be some sort of transition sentence here. Also, the first part of this section is confusing. Do the authors mean to suggest providing sterile syringes while incarcerated? Their data do not suggest individuals are being infected with HCV prior to incarceration. Was IDU behavior during incarceration assessed? It would seem the authors mean to suggest that syringe access programs in the community, prior to individuals being incarcerated is (and indeed has been shown to be) an important prevention strategy. Most DOCs in the US would be extremely adverse to providing syringes to incarcerated individuals.

Also, this paragraph is unfocused and hard to follow. The authors present several potential interventions but there are significant variations re where and how these interventions are typically implemented. Syringe access is one. Treatment with DAAs is another, but entirely different since this is focused on treatment rather than prevention. And while the authors note that correctional facilities are “underutilized”, they make no mention of how the prohibitive costs of DAAs can be addressed. In fact, there is litigation around compelling correction systems to offer DAAs to their populations. However, most facilities resist offering treatment citing costs as the primary barrier. The authors need to engage in a more thoughtful discussion around all of this.

Line 253: here the authors mention incidence for the first time. Reducing incidence in correctional settings is very different than reduce prevalence (the latter of course depends on community responses while the former depends on preventing infection while incarcerated). Again, this paragraph is not well-organized. Test and treat is an important model worth its own section. Syringe access is separate from this and warrants another section. These are lumped together and neither are described sufficiently. Finally, the authors mention addiction treatment toward the end of this para and this is the first mention of treatment. Medication to treat opioid use disorder (MOUD) is an evidence based treatment approach which can reduce HCV incidence. But the authors make almost no mention of this. And, any discussion of MOUD should include a discussion of the fact that many correctional facilities do not offer MOUD for individuals with opioid use disorder.

Conclusion:

Line 274: Again, please do not refer to prevalence as a rate.

Line 276: the authors’ data documented higher HCV prevalence among females but this is not generalizable so the authors should not state that HCV is higher among incarcerated females vs males.

Line 277—see prior comments about being very clear about intervention strategies and which strategies should be implemented where and with which specific populations.

Line 287: the authors bring up liver problems but do not address this elsewhere in the paper. This seems like an afterthought rather than an important consideration for optimal care for incarcerated persons.

Reviewer #2: Jansen et al aimed to determine the prevalence of HCV infections among incarcerated people in a state prison system. Prison population is one of the most important targets to elaborate HCV micro-elimination pathways and these kinds of papers are fundamental for the scientific community.

However, there are some points to address on the work.

Methods

Regarding behavioral information (alcohol consumption, drug use, and needle sharing) did the authors establish a timeline (e.g. last 6 months etc) or just life history? (This could be a bias, given formers are different by active/recent users). Please, specify.

Results

L134. Please, put ‘table 1’ without brackets.

When discussing your results, please use ‘HCV antibody (Ab) positive’ or ‘HCV active infection’ instead of HCV positive or HCV infection. This would be less confusing for the reader.

Table 1 refers to plausible determinants of HCV in the Incarcerated population. At this point, it seems there is no reason do just report a description. I suggest authors to directly perform a comparative analysis.

Table 2 is reported as "univariate analysis of plausible determinants of HCV in Incarcerated population". It is not understandable if the authors are referring to antibody positivity or active infection. Please, specify. Furthermore, please report the p-values for your chi-squared test.

Discussion

Authors stated in Italy HCV prevalence is higher. However, the reference is old. Please, substitute the reference with Fiore et al. (doi: 10.1016/j.drugpo.2020.103055). Basing on this recent prospective study, HCV-Ab prevalence is 10.4%.

When coming to female population, the authors state ‘[…] higher prevalence of HCV infected women who

215 reported that their sexual partners were injection drug users’. I suggest adding some concepts: the female populations’ offenses maybe more frequently related to drugs and prostitution. Furthermore, these 2 offenses maybe related to each other (e.g. being sex worker to obtain drugs).

Moreover, I suggest authors to better comment NSP/OST usefulness (DOI: 10.1016/j.drugpo.2021.103407; DOI: 10.1002/14651858.CD012021), how educational programs may increase the cascade of care in prison population (https://doi.org/10.1016/j.drugpo.2018.04.003), the needing of a better linkage to care when coming to PWIDs (DOI: 10.1007/s10900-007-9083-3; DOI: 10.1016/j.idc.2018.02.001), and how DAAs changed the perspectives of HCV treatment among incarcerated patients (DOI: 10.1111/liv.14745; DOI: 10.1016/j.drugpo.2018.06.017)

Minor comments

There are a lot of typos inside the text (e.g. double brackets when referring to table 2, ‘peoples’, ‘p-value’ should be in lowercase italics, etc.). Please, carefully revise the text before resubmitting.

For advocacy reasons, do not use ‘inmates’ or ‘prisoners’. Please, substitute this term with ‘incarcerated people’, ‘incarcerated patients’, or ‘people who are incarcerated’.

In conclusion, the paper is worth to be shared with the scientific community, but still needs some adjustments before being ready to be published.

**********

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2022 Mar 29;17(3):e0266047. doi: 10.1371/journal.pone.0266047.r002

Author response to Decision Letter 0

9 Feb 2022

Review Comments to the Author

Introduction:

Line 54: please insert comma after short illness; also this sentence needs to be referenced.

comma and citation added

omitted sentences and added transition sentence

Line 75: suggest making this more specific to US populations (there have been several recent studies in other countries on HCV prevalence among correctional populations).

added “in the US” so line 77 to make it clear this was our focus.

Line 79: please change to: derived from HCV surveillance data from eight states…

phrase modified as suggested.

Line 81: 1.3 million of the 3.3 million populations? This doesn’t make sense, please clarify.

Modified to: “…was responsible for 1.3 million (39%) of the HCV burden within those states”

Risk factors of HCV that are observed at a higher rate in incarcerated populations compared to the general population includes heavy alcohol drinking, IVDU, and needle sharing. Heavy alcohol drinking has been reported to increase the risk of HCV by 1.58 times [doi: 10.5812/hepatmon.31541], IVDU is reported in a meta-analysis study to increase the risk of HCV infection by 24 times [25] while needle sharing has been associated with an increased risk of 2.58 - 4.06 times [18, 27].

Methods:

Line 91: what do the authors mean by “screening”? Does this mean testing? If so, what type of testing was performed?

Yes, here it was measuring the antibody to HCV (anti-HCV) in a person’s serum. Added the phrase: “…negative when testing for antibodies to HCV (anti-HCV) in serum” to clarify.

Lines 92-93 (and elsewhere in the manuscript): please use more person-first language and avoid using pejorative terms such as “offenders”. Suggest using persons/individuals who are incarcerated.

Thanks, changed offenders to person or incarcerated person per suggestion.

Line 96: please change to: informed consent was not collected

Thanks. Changed.

Line 98: please change to: data used for this study were the…

Changed.

Line 102: Again, please describe what screening means and what serological testing was performed.

a. We perform reflex testing:

i. Universal opt-out testing upon arrival for HCV antibody – less than two refusals per year!

ii. If antibody positive, viral load and genotype identification using the same sample.

Line 102: Was the behavioral data collected only through the study or is this information that the prison regularly collects from everyone?

This information was collected regularly by NDDOCR with the help of NDDoH. Modified second to last sentence to read: “All behavioural, medical and incarceration related information routinely were collected for each individual at the time of their entry into the correctional facilities.”

Line 104: Do the authors mean length of total lifetime incarcerated?

Yes, removed comma between lifetime and incarcerated.

Line 105: Please change to: age at first incarceration.

Changed as per suggestion.

Line 107: How many correctional facilities were included? It would be helpful to provide a brief statement about the organizational structure of the NDDDOCR.

Here only the North Dakota Correctional facilities were included.

Line 115: Baby boomers are at higher risk, but not all are at high risk, please clarify.

Changed sentence to read: “Age was categorized into three groups based on the previous literature detailing that persons born during 1945–1965 (i.e., baby boomers) and are at higher risk of HCV as a group because of potential contaminated blood exposures.”

Line 116: Hispanic is not a race so presumably the authors decided to combine race and ethnicity?

Yes, we changed all mentions of race to race/ethnicity.

Line 117: Prevalence is not a rate, please change.

Thanks for pointing out. Changed

Line 119: Again, need to specify the testing performed.

See line 102 response above.

Line 126: what do the authors mean by “biologically meaningful interactions”?

Changed the sentence to read: “Select interactions were also checked based on previously published observations and our study results.”

The sentence was changed to clarify the method used: “Confounding effect of an explanatory variable was also evaluated by assigning the change of parameter estimates before and after removal of a variable from the model.”

Results:

Line 135: How were individuals diagnosed? Were the authors able to assess acute versus chronic infection? Was confirmatory testing prior to diagnosis done?

a. Diagnosis was based on incoming blood tests.

b. Acute vs chronic was determined by persistence of infection on 6 month recheck. Virtually 100% were chronic, as residents were admitted from county jail populations, where they had been in remand for more than 6 months pending trial/legal actions.

c. The reflex testing of positive antibodies for viral load and genotype served as the confirmatory tests.

Line 136: Please do not begin a sentence with a number.

Thanks for pointing out this.

Those individuals’ data were incomplete. They don’t have their drug use history and needle sharing information. Included the reasons for excluding

Line 138: remove “in where” and insert a semi-colon between analysis and 1,1256.

Thanks. Included.

Line 140: please use older age category rather than older people category. Same with younger people.

Thanks. Changed.

Line 141: Please change to the prevalence was (not is) much higher.

Thanks. Replaced.

Thanks. Edited the sentence. It now reads: “Also, the prevalence was much higher in people who had a history of taking intravenous drugs (36.11%) compared with those without history of intravenous drugs (6.98%). Similarly, the prevalence was much higher for people with sharing needles (46.82%) compared with those that did not have any history of needle sharing (10.41%) ((Table 2).”

This study used the secondary data that’s why we have a limitation that we don’t have chance to collect those frequency and duration information.

Line 148: please change to incarcerated individuals rather than peoples.

Thanks. Changed

Lines 148-149: please insert commas for 1,256 and 6,027.

Inserted.

Table 2 with univariate analyses is not needed. The authors can just state what variables were selected, based on univariate analyses, for the multivariate model.

We have combined table 1 and 2 to eliminate overlap of information.

Line 156: change were to are.

changed

Line 157: remove the parentheses around age. Same in the following sentence.

removed

Line 159: add ‘s’ to male.

added

Line 160: change have to had.

changed

Line 162: what does shared drug injection mean? How does this differ from needle sharing? Does the refer to sharing of drug injection equipment? How were these data collected?

a. This data was collected from resident during intake medical interview. The question is “Now or in the past, have you shared injection drugs or needles with anyone else? This includes needles, syringes, spoons, filters or rinse water?” The intention is to identify opportunities to transmit HCV during I the injection process.

Line 163: the finding related to alcohol may be due to the very imprecise manner in which this variable was measures (e.g. simple yes/no).

Thanks for pointing out. Possibly could the reason and we have mentioned this in the limitations in the discussion: “Additionally, the crude categorization of alcohol consumption (yes/no) likely resulted in our observed results and an incomplete confounding adjustment”

Line 166: add an ‘a’ in front of majority.

included

Discussion:

Line 180: since the authors collected data over 10 years, why didn’t they report annual HCV prevalence and conduct trend analyses to see how the prevalence changed over time?

We have now included annual HCV prevalence for 2009 – 2018 and included a figure with a trend line and logistic regression p-value (0.0542).

Line 185: Should be HCV prevalence estimates.

Thanks. Changed.

Line 187: please change to: have been reported from other studies in countries such as…

Changed.

Line 189: Being a new sentence: Overall, available data suggests…

Thanks. Included a new sentence.

Line 189: please change prisoners to individuals incarcerated in prison settings.

Included.

Line 192: this is the first reference to IDU. Previously, the authors have used the term intravenous drug use. Suggest using the acronym IDU consistently throughout.

Thanks. Added.

Line 194: include citation for IDU statement.

Included.

Line 195: please be consistent with use of acronyms. Here the authors use IVDU for the first time.

Thanks edited.

Lines 195-197: please be careful with the use of the term rate. The authors are using prevalence estimates and prevalence is not a rate.

Thanks. Omitted rate.

Line 204: please change peoples to individuals

Replaced

Line 205: why is Birth capitalized?

Thanks. Changed.

Lines 205-208: this section should be integrated into the above section where the authors discuss their findings by age.

Thanks. Integrated with previous section.

We have added an additional table looking at IDU by gender and race/ethnicity as supporting information. This study is based on secondary data, so there was no way to collect sexual history. That’s true it’s a limitation for this study and has been listed as such at the end of the discussion.

We have now mentioned this in the limitations in the discussion: “Additionally, the crude categorization of alcohol consumption (yes/no) likely resulted in our observed results and an incomplete confounding adjustment”

We have added an additional supporting information table looking at IDU by gender and race/ethnicity.

Line 231: please change inmates to incarcerated individuals.

Changed.

Line 233: change to non-injecting drugs

Changed

Lines 237-242: suggest integrating history of IDU and history of syringe sharing as these overlap. The authors also allude to shared drug injection and as previously noted, this is not clear.

a. IDU and sharing of syringes were data collected with different questions and the multivariable regression results indicated that both are independent risk factors for testing positive.

This paragraph was edited.

This section has been edited. Interventions were placed into separate paragraphs, recent references were used and cost barriers addressed for DAAs.

This section was rephrased and paragraphs were separated.

Conclusion:

Line 274: Again, please do not refer to prevalence as a rate.

Thanks. Removed

Line 276: the authors’ data documented higher HCV prevalence among females but this is not generalizable so the authors should not state that HCV is higher among incarcerated females vs males.

Thanks. Removed that part.

Line 277—see prior comments about being very clear about intervention strategies and which strategies should be implemented where and with which specific populations.

We have edited these paragraphs and added additional citations as supporting evidence.

We have mentioned HCV as a major cause of liver disease in the introduction and mention it in the conclusion as a way to identify significant impacts HCV prevention or treatment may have on outcomes in this population.

However, there are some points to address on the work.

Methods

This information routinely was collected at incarceration by North Dakota Department of Corrections and Rehabilitation (NDDOCR) and was a history of exposure with no timeline specified. That’s true that could be a bias due to active or recent users but there is no way get those information by specific time period using our data. We have mentioned it in our limitation. Thanks for pointing out this.

Results

L134. Please, put ‘table 1’ without brackets. Brackets omitted

When discussing your results, please use ‘HCV antibody (Ab) positive’ or ‘HCV active infection’ instead of HCV positive or HCV infection. This would be less confusing for the reader. Thanks for the correction.

We have combined table 1 and 2 to eliminate overlap of information.

Table 2 is reported as "univariate analysis of plausible determinants of HCV in Incarcerated population". It is not understandable if the authors are referring to antibody positivity or active infection. Please, specify. Thanks for mentioning that. Changed to HCV antibody (Ab).

Furthermore, please report the p-values for your chi-squared test.

Thanks. P-value included in the table.

Discussion

When coming to female population, the authors state ‘[…] higher prevalence of HCV infected women who

Minor comments

For advocacy reasons, do not use ‘inmates’ or ‘prisoners’. Please, substitute this term with ‘incarcerated people’, ‘incarcerated patients’, or ‘people who are incarcerated’.

In conclusion, the paper is worth to be shared with the scientific community, but still needs some adjustments before being ready to be published.

Thank you for your thoughtful comments and references. These comments have been addressed and additional references have been utilized. Substitutions have been made in regard to ‘inmates’ and ‘prisoners’ and typos adjusted.

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PLoS One. doi: 10.1371/journal.pone.0266047.r003

Decision Letter 1

Jee-Fu Huang

7 Mar 2022

PONE-D-21-32680R1Epidemiology of Hepatitis C virus infection among incarcerated populations in North Dakota.PLOS ONE

Dear Dr. Jansen,

Please submit your revised manuscript by Apr 21 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

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Academic Editor

PLOS ONE

Additional Editor Comments:

The study aimed to clarify HCV infections and risk factors in incarcerated people in the US by using the large-scale database. However, previous studies have been vigorously investigating the issue. The cross-sectional features of the study and the lack of HCVRNA, both quantitative and genotype approaches, much limited the results and interpretations of the study. The results and the conclusions did not appear to address more novelty in the current knowledge. Therefore,

1. The Authors are encouraged to provide HCVRNA data for the epidemiological features and also put the RNA data into risk analysis.

2. The other well-established risk factors such as receiving surgery, blood transfusion, family members of HCV infection, etc. could be addressed.

3. The proposed strategies for risk reduction in the special population could be discussed in the discussion section.

[Note: HTML markup is below. Please do not edit.]

PLoS One. 2022 Mar 29;17(3):e0266047. doi: 10.1371/journal.pone.0266047.r004

Author response to Decision Letter 1

8 Mar 2022

1. The Authors are encouraged to provide HCVRNA data for the epidemiological features and also put the RNA data into risk analysis.

1. This is a retrospective study and so RNA presence data is only available for patients in the care of NDDOCR on or after 09/2015, but not prior to that. In addition, the original IRB did not specify obtaining this variable and so an additional IRB protocol would need to be submitted and approved to have access to this data. This would extend our resubmission beyond the allotted journal timeframe.

2. The other well-established risk factors such as receiving surgery, blood transfusion, family members of HCV infection, etc. could be addressed.

2. Surgery, blood transfusion, family member info was not collected and so is not available for this population.

3. The proposed strategies for risk reduction in the special population could be discussed in the discussion section.

3. We have discuss strategies that have been implemented in justice involved populations in the discussion pages 14-15. We have also added the following paragraph after line 283 in the discussion section as well:

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PLoS One. doi: 10.1371/journal.pone.0266047.r005

Decision Letter 2

Jee-Fu Huang

10 Mar 2022

PONE-D-21-32680R2Epidemiology of Hepatitis C virus infection among incarcerated populations in North Dakota.PLOS ONE

Dear Dr. Jansen,

Thank you for submitting your manuscript to PLOS ONE. We invite you to submit a revised version of the manuscript that addresses the points raised during the review process after your responses to the previous comments.

Please submit your revised manuscript by Apr 24 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
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An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Jee-Fu Huang, M.D., Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments:

The Authors should put the lack of HCVRNA data and the commonly-observed risk factors into the study limitations.

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Reviewers' comments:

PLoS One. 2022 Mar 29;17(3):e0266047. doi: 10.1371/journal.pone.0266047.r006

Author response to Decision Letter 2

10 Mar 2022

1. The Authors should put the lack of HCVRNA data and the commonly-observed risk factors into the study limitations.

Answer: We have added the following to the limitations paragraph to the end of the discussion:

In this retrospective study, we had additional limitations related to the collection of some data. HCVRNA data is only available for a small fraction of our study population and was not incorporated into this study. Well-established risk factors such as receiving surgery, blood transfusion, family members with HCV infection were also not assessed in this population.

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PLoS One. doi: 10.1371/journal.pone.0266047.r007

Decision Letter 3

Jee-Fu Huang

14 Mar 2022

Epidemiology of Hepatitis C virus infection among incarcerated populations in North Dakota.

PONE-D-21-32680R3

Dear Dr. Jansen,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0266047.r008

Acceptance letter

Jee-Fu Huang

21 Mar 2022

PONE-D-21-32680R3

Epidemiology of Hepatitis C virus infection among incarcerated populations in North Dakota.

Dear Dr. Jansen:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Thank you for submitting your work to PLOS ONE and supporting open access.

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on behalf of

Dr. Jee-Fu Huang

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. Reported 1256 HCV cases by risk behavior.

(TIFF)

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S1 Table. Sex and race/ethnicity groups by intervenes drug use in study population.

(PDF)

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Data Availability Statement

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PERMALINK

Epidemiology of Hepatitis C virus infection among incarcerated populations in North Dakota

Liton Chandra Deb

Hannah Hove

Tracy K Miller

Kodi Pinks

Grace Njau

John J Hagan

Rick J Jansen

Roles

Abstract

Introduction

Methodology

Study population

Data collection

Statistical analysis

Results

Table 1. Univariable analysis (chi-square test) of plausible determinants of HCV antibody (Ab) in Incarcerated population.

Fig 1. Linear trend in annual prevalence across the study period 2009–2018.

Table 2. Final model of multivariable logistic regression analysis of plausible determinants of HCV antibody (Ab) in incarcerated populations.

Discussion

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Andrea Knittel

Roles

Author response to Decision Letter 0

Decision Letter 1

Jee-Fu Huang

Roles

Author response to Decision Letter 1

Decision Letter 2

Jee-Fu Huang

Roles

Author response to Decision Letter 2

Decision Letter 3

Jee-Fu Huang

Roles

Acceptance letter

Jee-Fu Huang

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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