Skip to main content
PLOS One logoLink to PLOS One
. 2020 Sep 3;15(9):e0238203. doi: 10.1371/journal.pone.0238203

Hepatitis C prevalence in Denmark in 2016—An updated estimate using multiple national registers

Stine Nielsen 1, Janne Fuglsang Hansen 1, Gordon Hay 2, Susan Cowan 3, Peter Jepsen 4,5, Lars Haukali Omland 6, Henrik Bygum Krarup 7,8, Jacob Søholm 1, Jeffrey V Lazarus 9, Nina Weis 10,11, Anne Øvrehus 1,12, Peer Brehm Christensen 1,12,*
Editor: Yury E Khudyakov13
PMCID: PMC7470322  PMID: 32881877

Abstract

Background

Chronic hepatitis C (CHC) can be eliminated as a public health threat by meeting the WHO targets: 90% of patients diagnosed and 80% treated by 2030. To achieve and monitor progress towards elimination, an updated estimate of the size of the CHC population is needed, but Denmark has no complete national CHC register. By combining existing registers in 2007, we estimated the population living with CHC to be 16,888 (0.38% of the adult population).

Aim

To estimate the population living with diagnosed and undiagnosed CHC in Denmark on 31 December 2016. Among additional aims were to estimate the proportion of patients attending specialised clinical care.

Methods

People with diagnosed CHC were identified from four national registers. The total diagnosed population was estimated by capture-recapture analysis. The undiagnosed population was estimated by comparing the register data with data from two cross-sectional surveys.

Results

The population living with diagnosed CHC in Denmark was 7,581 persons (95%CI: 7,416–12,661) of which 6,116 (81%) were identified in the four registers. The estimated undiagnosed fraction was 24%, so the total CHC infected population was 9,975 corresponding to 0.21% of the adult population (95%CI: 9,758–16,659; 0.21%-0.36%). Only 48% of diagnosed patients had received specialised clinical care.

Conclusion

CHC prevalence in Denmark is declining and 76% of patients have been diagnosed. Linking diagnosed patients to care and increasing efforts to test people with former or current drug use will be necessary to achieve CHC elimination.

Introduction

Chronic hepatitis C (CHC) is a major health problem worldwide, but new treatments have made elimination possible [1, 2]. The World Health Organization (WHO) has set the ambitious targets of 90% diagnosed and 80% treated by 2030, which was endorsed by all Member States, including Denmark, in 2016 [3]. In the same year, Denmark also endorsed the action plan for the health sector response to viral hepatitis in the WHO European Region [4].

Achieving the elimination goal requires knowing the size of the population living with CHC. This is also a cornerstone in any national elimination plan. However, unlike many countries in the world, Denmark has not formulated a national viral hepatitis strategy or action plan.

Denmark is well known for its high coverage national health registers and in 2012, we published the first Danish CHC estimate based on four national registers using a capture-recapture model [5]. This method gives an estimate of a ‘hypothetical’ population which would have been diagnosed if one or more of the registers included 100% of all diagnosed individuals [6]. We calculated a diagnosed population of 9,166 and estimated the total population (diagnosed and undiagnosed) living with CHC to be 16,888 (0.38% of the adult population) at the end of 2007. However, due to incomplete reporting to the registers, the total CHC population could have been as high as 21,468 (0.49%). An update is now urgently needed to plan the CHC elimination efforts in Denmark. The primary aim of this study was to estimate the population with diagnosed and undiagnosed CHC in Denmark at the end of 2016. Secondary aims were to estimate the proportion of patients attending specialised clinical care and the coverage of the national CHC registers.

Methods

Data sources

We used the same four national source registers as in our previous estimate from 2007 [5].

  1. Communicable diseases register: Since May 2000, Denmark has implemented mandatory reporting of CHC from the diagnosing physician. The CHC case definition is based on the presence of hepatitis C virus RNA (HCV-RNA). This register is known to have low (<50%) coverage [7].

  2. Hospital register: In 1977, Denmark established the Danish National Patient Registry, which included all inpatient discharge diagnoses, according to ICD-8 and ICD-10. Since 1995, it also included all hospital outpatient and emergency department visits [8]. We extracted data on all individuals registered with CHC (ICD-10 diagnosis B18.2). The case definition for CHC is not specified. The validity of the register was approximately 67% for gastroenterology disease diagnoses in 2002 [9]. A 2004 study found that 48% of CHC/HIV co-infected patients were recorded with a CHC diagnosis in the hospital register [10].

  3. Clinical hepatitis database (DANHEP): In 2002, Denmark established the Danish Database for Hepatitis B and C. It contains detailed information on demographics, test results, treatment status, risk factors, co-morbidities and other relevant information on all chronic hepatitis B and CHC patients seen for care in specialised clinics in Denmark. Patients positive for HCV-RNA in their most recent test were classified as having CHC.

  4. Laboratory database (Danvir): Denmark has 18 laboratories performing tests for hepatitis C [5]. We requested information on all people ever tested for either hepatitis C (antiHCV or HCV-RNA test) or hepatitis B. The case definition for CHC was positive HCV-RNA at last test. People with negative HCV-RNA at last test or those only antiHCV positive were excluded. In contrast to the other three source registers, the laboratory register was not updated automatically; it is only updated on request from the research team, and not all laboratories provided fully updated data.

For patients present in the source registers, we extracted data from two additional registers: The Danish civil register: established in 1968 and stores information on vital status, current place of residence as well as immigration/emigration on all Danish residents [11].

The drug treatment register: established in 1996 and contains information on all persons treated for drug use in Denmark [12]. This register was used to explore how many people with diagnosed CHC had been in contact with drug treatment services.

All persons with permanent residence in Denmark are assigned a unique 10-digit personal identification number (PIN). This number was used to link the information on individuals from the different registries. The total population in Denmark at the end of 2016 was 5.7 million, of which the adult population (≥18 years) was 4.6 million (80%) [13].

We identified the individuals who fulfilled the CHC case definition in each register and excluded those who had died, left Denmark or had an invalid PIN as of 31 December 2016.

We excluded those who had cleared their hepatitis C virus (HCV) infection (i.e. their last HCV-RNA test was negative and/or they were classified as cured in the clinical database). Information about cleared infections was only available from the laboratory register and the clinical database. Therefore, we also excluded patients from the hospital and communicable disease register if their last registration in these registers were before the date of CHC clearance in the other registers. We removed patients who were only registered with CHC in the hospital register but were “non-CHC cases” according to other registers (e.g. they were HCV-RNA negative or not tested for HCV-RNA and either antiHCV negative or hepatitis B virus positive in any of the other registers).

The following variables were extracted for all cases as of 31 December 2016: First year of diagnosis (i.e. first year the person appeared in any of the four registers), age, sex, region of current residence and treatment for drug use.

Capture-recapture estimation

Assuming independence between the source registers and a common CHC case definition, we analysed the overlap patterns between the four registers stratified by age (3 groups), sex (2 groups), geographic region (5 groups) and first year of diagnosis (3 groups). As some cells had too few observations to produce valid estimates, these were analysed without year of diagnosis to obtain stable estimates. We carried out log-linear modelling using the statistical program GLIM4 [14] and used the same analytical approach as in 2007 [5, 15]. The final analysis contained 113 different models including all possible two-way and three-way interactions fitted to the overlap data. Confidence intervals for the total estimate were derived from bootstrap analysis of 1000 samples [16].

Estimating the undiagnosed fraction

We used data from two cross-sectional studies to estimate the proportion of undiagnosed CHC in Denmark:

  1. A regional study of older adults (The “3B-study”): Retrospective testing of 4,945 stored blood samples originally collected between 1998–2000 to investigate Helicobacter pylori infection [17, 18]. The population tested in this study was 58–83 years old in 2016. The stored samples were tested for HCV-RNA in 2014.

  2. A seroprevalence study of HCV infection among 1,041 people in prison conducted between 2016–2017 where 801 (77%) were tested for HCV-RNA. The study was performed in eight prisons in the South Region. Participants came from all over Denmark and were representative of the national prison population. The median age of participants was 30 years, 97% were male, and 8.5% reported injecting drug use [19].

We investigated if individuals identified with CHC in these two studies were diagnosed with CHC in any of the source registers and calculated a 95% confidence interval on the estimated undiagnosed fraction.

Sensitivity analyses

To investigate the impact that under-reporting and misclassification of hepatitis cases might have on our estimate, we performed several sensitivity analyses. We performed three source capture-recapture analyses to evaluate the effect of excluding one of the four source registers [20].

In addition, we used a multiple indicator method (MIM) analysis to validate an unrealistically high estimate for the South Region in the capture-recapture analysis [21]. In this multiple regression model, the CHC prevalence (per capita) was the dependent variable and the ‘independent’ variables were the four source registers. The model with only the hospital register had the best fit across regions, and this was not improved by including other source registers.

We followed the WHO guidelines for accurate and transparent health estimates reporting [22]. The study was approved by the Danish Data Protection Agency in 2016 (Journal no: 16/43190 and 18/52996). Data were fully anonymized prior to analysis. As a register-based study without contact to patients, informed consent from participants was not required, according to Danish law. However patients registered in the clinical database (DANHEP) did provide written consent to have their data used in research prior to registration in the database.

Results

The initial extraction included 1,046,013 individuals, of whom 20,174 were identified as ever registered as infected with hepatitis C. Of these, 6,380 (32%) had died and 1,188 (6%) did not have a valid PIN, resulting in 12,606 individuals (62%) being included for further analysis. Among these, 9,973 (79%) people had ever had a positive HCV-RNA test, including 2,565 (26%) who had cleared their infection (of which 1,604 (63%) had recorded successful CHC treatment). Excluding patients with past infection left 7408 (74%) patients for further analysis.

Among the 7408 patients the overlap between the four registers varied: most cases were in all four registers and the second-largest group was those, only present in the hospital register. Of 1,681 patients, only in the hospital register, we identified 1,292 who had either negative antiHCV or HCV-RNA results and/or had chronic hepatitis B (ICD10 code 18.1) with no signs of HCV co-infection according to the other source registers. We could not check the clinical records of these patients, but in the “3B-study” with complete laboratory data, 7 patients only diagnosed in the hospital register were all found to be non-CHC cases. We excluded the 1,292 (17%) non-CHC patients reducing the “Hospital only” group to 388 and our total captured population to 6,116 (Fig 1).

Fig 1. Overlap pattern between chronic hepatitis C cases in each of the four Danish registers (N = 6,116) after validation.

Fig 1

Among the 6,116 living with CHC, most were identified through the hospital register (N = 5,080, 83%) and the laboratory database (N = 4,644, 76%) and 60% had attended specialised clinical care (Table 1).

Table 1. People living with diagnosed chronic hepatitis C in Denmark according to four national registers end 2016 (N = 6,116).

Database Laboratory Comm. Dis Hospital Clinical TOTAL
Chronic hepatitis C 4644 76% 3109 51% 5080 83% 3676 60% 6116 100%
only in one register 538 9% 236 4% 388 6% 116 2% 1278 21%
Sex
Male 3069 66% 2009 65% 3278 65% 2341 64% 3986 65%
Age
<40 700 15% 516 17% 871 17% 682 19% 1052 17%
40–49 1412 30% 990 32% 1451 29% 1067 29% 1795 29%
50+ 2532 55% 1603 52% 2758 54% 1927 52% 3269 53%
Administrative region
North 390 8% 168 5% 397 8% 317 9% 490 8%
Central 782 17% 392 13% 833 16% 680 18% 962 16%
South 1243 27% 910 29% 1183 23% 1002 27% 1595 26%
Zealand 524 11% 480 15% 688 14% 369 10% 825 13%
Capital region 1705 37% 1159 37% 1979 39% 1308 36% 2244 37%
Year of diagnosis
≤2000 1462 31% 1000 32% 1487 29% 999 27% 1787 29%
2001–2007 1743 38% 1104 36% 1617 32% 1248 34% 1990 33%
2008–2016 1439 31% 1005 32% 1976 39% 1429 39% 2339 38%
Registered in the drug treatment register 2804 60% 2014 65% 2917 58% 2119 58% 3556 58%

The median age was 50 years (with 80% being between 36–64 years) and 65% were male. Most living with diagnosed CHC were aged between 50–59 years in 2016 (N = 1,938, 32%). The age at diagnosis had increased with time: the median age of those with first entry in any register before 2001 was 33 years and increased to 44 years for those diagnosed after 2008. The majority of cases were among people living in the Capital region (37%) and overall, most people (38%) were diagnosed after 2008. More than half (58%) of those with diagnosed CHC had ever been in treatment for drug use, ranging between 54% in the Capital and 65% in the South Region.

Capture-recapture results

The capture-recapture analysis suggests that if the registers were not subject to under-reporting there would be, in total, 7,581 people (95%CI 7,416–12,661) living with diagnosed CHC in Denmark. This represents a 17% decrease over 9 years (N = 9,166 diagnosed cases in 2007 [5]). The total “hidden” diagnosed population was 1,465 (19%) but varied between 6% in the North and 31% in the South Region (Table 2).

Table 2. Estimated number of people living with chronic hepatitis C (diagnosed and undiagnosed) in Denmark at the end of 2016 (N = 9,975).

North Central South Zealand Capital Denmark 95% CI
n (%) n (%) n (%) n (%) n (%) n (%)
Age
<40 100 (19) 193 (17) 531 (23) 146 (15) 365 (14) 1,335 (18) 1,199–2,996
40–49 136 (26) 329 (29) 811 (35) 267 (27) 707 (27) 2,250 (30) 2,088–3,663
50+ 283 (55) 628 (55) 959 (42) 561 (58) 1,565 (59) 3,996 (53) 3,815–7,199
Sex
Male 342 (66) 756 (66) 1,613 (70) 592 (61) 1,579 (60) 4,882 (64) 4,742–8,127
Year of diagnosis
≤ 2000 195 (38) 356 (31) 728 (32) 249 (26) 569 (22) 2,097 (28) 1,954–2,290
2001–2007 141 (27) 392 (34) 714 (31) 295 (30) 989 (38) 2,531(33) 2,344–6,316
2008–2016 183 (35) 402 (35) 859 (37) 430 (44) 1,079 (41) 2,953 (39) 2,789–4,994
Total estimated diagnoses 519 (7) 1,150 (15) 2,301 (30) 974 (13) 2,637 (35) 7,581 (100) 7,416–12,661
95% CI 507–619 1,052–2,397 2,044–5,141 929–1,212 2,465–5,232
“Hidden” CHC diagnosesa 29 (6) 188 (16) 706 (31) 149 (15) 393 (15) 1,465 (19) 1,300–6,545
Total CHC populationb 683 1,513 3,028 1,282 3,470 9,975 9,758–16,659
Population prevalencec 0.14% 0.15% 0.31% 0.19% 0.24% 0.22% 0.21%-0.36%

a The “hidden” CHC diagnoses is the main outcome of the capture-recapture analyses and refers to the estimated number of CHC diagnoses not identified due to incompleteness of the registers (i.e. it is the total estimated diagnoses minus the observed (“captured”) diagnoses).

b Total CHC population: adjustment for 24% undiagnosed.

c Population prevalence: estimated CHC prevalence (diagnosed and undiagnosed) in the adult population.

Estimating the fraction with undiagnosed CHC

We used two cross-sectional studies where, in total, N = 12 (the “3B-study”) and N = 34 (prison study) participants respectively tested HCV-RNA positive. Of these, 4 (33%) and 7 (21%) were not found in any of the four source registers and we therefore classified in total 24% (11/46) (95% CI 13%-39%) to have undiagnosed CHC.

Applying this to our estimated 7,581 diagnosed chronic infections resulted in a total estimated population living with CHC (diagnosed plus undiagnosed) of 9,975 (95% CI 9,758–16,659). This corresponded to a national adult CHC prevalence of 0.22% (95% CI 0.21%-0.36%), significantly lower than the 0.38% reported in 2007 (p<0.05) [5].

Sensitivity analyses

We addressed several issues in our data:

Firstly, if we had not excluded the 1,292 misclassified CHC cases, the estimated diagnosed population would be 11,158 (95%CI 10,489–15,630).

Secondly, the major decline in reporting from laboratories after 2010, not mirrored in the other registers reflects that the laboratory database was not automatically updated (Fig 2).

Fig 2. Number of new chronic hepatitis C cases reported per year in the four source registers (N = 6,116).

Fig 2

If reports from the laboratory had continued to follow the hospital register after 2010, then approximately 700 additional cases would have been reported. A simple three-source capture-recapture estimate [20] excluding the laboratory register and with no correction for interactions increased the estimated diagnosed population by 24% (N = 1,850), whereas excluding the hospital register meant an increase of 9% (N = 669).

Thirdly, the South Region had the highest proportion of diagnosed patients not present in the registers (the hidden population). This was unexpected as this region has been a pioneer in outreach hepatitis C testing for decades. Completeness of registers in the South Region is believed to be high, and “laboratory only” was 14% here compared to 9% in the national estimate (Fig 1). The capture-recapture analyses in the South Region tended to favour more complex models (with more interaction between source registers than the other areas). These factors could lead to over-estimation. To address this, we adjusted CHC prevalence in the South using a multiple indicator method (MIM) regression model. This reduced the estimated diagnosed CHC population in the South from 2,301 to 1,599 (95% CI 1,308–1,890) compared to 1,595 observed cases, suggesting only 0.2% hidden in the region, an unlikely high reporting rate. If we accept the MIM adjustment for the South, the national estimate would decrease by 9% to 6,879 (95% CI 6,674–10,215).

Fourthly, antiHCV positive patients without a positive HCV-RNA result were excluded. This reflected that previously, HCV-RNA was only ordered by hospital specialists once the patient was referred, thus patients tested in drug treatment facilities and primary care, but not entering specialised care, did not get HCV-RNA tested. In the 2007 study, 62% of antiHCV positive patients tested with PCR were HCV-RNA positive [5]. Thus by excluding the antiHCV only patients we underestimated the chronically infected population.

In summary, the sensitivity analysis indicated both under- and over-estimations, and the point estimate of 9,975 is likely to be a conservative estimate given the limitations of our source registers.

Combining our results in a national cascade of care showed that 37% of all people living with CHC in Denmark had attended specialised clinical care (Fig 3).

Fig 3. The estimated continuum of care for chronic hepatitis C in Denmark (end 2016).

Fig 3

Discussion

This study estimated the population living with CHC in Denmark to be 9,975 (95% CI 9,758–16,659) including an undiagnosed fraction of 24%. From 2007 to 2016, the estimated CHC prevalence fell from 0.38 to 0.21%, and the diagnosed fraction increased from 54% to 76%. However, comparison is difficult as we did not exclude patients misclassified in the hospital register in the 2007 estimate. Still we think that using the same registers and capture recapture methodology makes the observed decline in prevalence over time credible.

One reason for the declining prevalence was a high mortality in the cohort; 32% of all in the registers exposed to hepatitis C had died. In addition, 10% had been cured of CHC. Another force driving the reduction in CHC prevalence in Denmark was a low CHC prevalence in young people who use drugs [23]. Moreover, several studies suggest that fewer young people inject drugs in later years [12, 19, 23]. The very low CHC prevalence among those younger than 40 years also suggests a low incidence of new infections. In contrast, the prevalence among 50+ years has doubled the last 10 years, reflecting an ageing cohort effect.

Our findings are in line with a recent study from England, which estimated the CHC prevalence in 2015 to be 0.27% in the adult population and a 10-year decrease of 23% from 2005, compared to our decrease of 42% from 2007 (0.38%) to 2016 (0.21%) [24]. However, estimates in England suggest that only 31% of people living with CHC have been diagnosed. Our estimate of the diagnosed proportion (76%) was based on two very small samples ranging between 67–79%, of which only one (the prison study) had national coverage. This is similar to the findings from a recent modelling study which estimated that in 2015 63% of CHC cases in Denmark were diagnosed [25]. The general population sample was older than our register cohort and the prison study participants were younger. Applying the same proportion of undiagnosed CHC in all regions assumes that the testing coverage and reporting was similar between regions, but this is unlikely. It is expected that higher test coverage would be found in persons born 1950–1980 as these birth-cohorts have been the focus for testing in Denmark inspired by the “baby boomer” testing initiative in the US. On the other hand, the 3B-study was performed in Funen, a region where the focus on HCV testing has been high, and it is possible that this is lower in other regions. Our diagnosed proportion was similar to Sweden, where a recent hepatitis C survey found that 73% of people who tested antiHCV positive had been previously diagnosed [26]. A recent systematic review found that 13 EU/EEA countries had conducted HCV prevalence surveys with an estimated antiHCV prevalence in the EU/EEA of 1.1% (95% CI 0.9–1.4%) of which an estimated 70% have CHC [27]. In the Netherlands, a CHC prevalence of 0.16% was found using the workbook method, whereas Ireland and Belgium reported 0.98% and 0.13% CHC prevalence using residual sera testing [2830]. However, none of these methods were directly comparable to our study.

We were surprised to see the variation in prevalence between the different regions, and, especially the higher prevalence (and larger diagnosed population not in the registers) in the Southern Region than in the Capital Region. CHC is strongly associated with injecting drug use and half of the people using drugs in Denmark are believed to live in Copenhagen, so we would expect a much higher prevalence here than observed. As the South Region had more focus on testing people who use drugs for HCV, the difference could be explained by more people tested in the South, where registers were updated until end 2016. However, this would imply a lower hidden population in the South, in contrast to what our model predicted. This was also suggested by the MIM analysis, although this resulted in an unrealistically high diagnosed proportion in the South Region (99.8%). So all things considered, we believe that the hidden population in the Southern Region is likely over-estimated.

The coverage of the national communicable disease register had risen from 32% in 2007 to 41% in 2016. This still relatively low coverage reflects that the register relies on clinicians reporting as Denmark is one of few European countries without mandatory laboratory reporting for hepatitis C [31].

The proportion of diagnosed patients attending clinical care had risen from 34% (3,065/9,166) in 2007 to now 48% (3,676/7,581), but still more than half of those living with diagnosed CHC are not attending specialised care. This suggests that calling in patients not attending care and offering them treatment could be more cost-effective than increasing screening for the remaining undiagnosed CHC patients in a low prevalence population like Denmark.

There are a number of weaknesses in our study. Firstly, the basic assumption of independence of registers in the capture-recapture analysis was not fulfilled. We used log-linear modelling including interaction terms between registers to compensate for this, but with only limited success. Secondly, the case definition was not the same in all registers. Particularly, in the hospital register, the case definition was probably not always based on HCV-RNA positivity: patients are usually coded by the discharging doctor or by administrative staff and HCV-RNA results may not be available at the time of discharge.

Differences in case definitions will decrease the overlap between registers and inflate the estimate. We tried to adjust for this by applying another statistical method (MIM), but this resulted in too low an estimate for the South Region.

Our estimate of the proportion with undiagnosed infection was based on small numbers. This was because the CHC prevalence was low and general population serological surveys, which enable assessment of the undiagnosed fraction, are rarely conducted in Denmark. Also, recent sentinel studies in key populations, like people who inject drugs or migrants from high prevalence areas, were not available.

A major weakness was that the laboratory register we used was a research database with incomplete reporting from the participating laboratories. Efforts are currently underway to implement mandatory laboratory-based reporting of CHC in Denmark, which would simplify future assessments of the national hepatitis C burden. Finally, we did not consider reinfection among the cured. However, with only 1,604 successfully treated, this would probably only add few extra cases.

Conclusion

Our study suggests that the population living with CHC in Denmark in 2016 was 9,975 (9,758–16,659) people and declining. Only 41% had been reported to the national communicable diseases register and less than half had attended specialised care. The relatively large range on our estimate, highlights the methodological challenges and uncertainties. However, no better evidence-based estimate exists and we believe this result can assist the health authorities to formulate a national elimination plan that can assure that Denmark will fulfil the WHO hepatitis C elimination goal by 2030. According to our study, the most urgent initiative will be to ensure that infected people are linked to care and that treatment is offered to all diagnosed patients, and this strategy has recently been accepted by the national health authorities (PBC personal communication). People with current or former drug use constitute the main CHC population in Denmark and thus addressing the needs of this population will be key to reach national elimination.

Acknowledgments

Anderson Rael dos Santos (Liverpool John Moores University) carried out the capture-recapture analyses.

Data Availability

The dataset for the manuscript has been published at Zenodo.org: DOI 10.5281/zenodo.3959476.

Funding Statement

The study was supported by an unrestricted grant from MSD Denmark URL: https://www.msd.dk/home. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Smith S, Harmanci H, Hutin Y, Hess S, Bulterys M, Peck R, et al. Global progress on the elimination of viral hepatitis as a major public health threat: An analysis of WHO Member State responses 2017. JHEP Reports. 2019;1(2):81–9. 10.1016/j.jhepr.2019.04.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Cooke GS, Andrieux-Meyer I, Applegate TL, Atun R, Burry JR, Cheinquer H, et al. Accelerating the elimination of viral hepatitis: a Lancet Gastroenterology & Hepatology Commission. (2468–1253 (Electronic)).
  • 3.WHO. Global health sector strategy on viral hepatitis 2016–2021—Towards ending viral hepatitis. 2016.
  • 4.WHO/Europe. Action plan for the health sector response to viral hepatitis in the WHO European Region. WHO/Europe, 2017.
  • 5.Christensen PB, Hay G, Jepsen P, Omland LH, Just SA, Krarup HB, et al. Hepatitis C prevalence in Denmark -an estimate based on multiple national registers. BMC Infectious Diseases. 2012;12(1):178 10.1186/1471-2334-12-178 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.International Working Group for Disease Monitoring and Forecasting. Capture-recapture and multiple-record systems estimation II: Applications in human diseases. American Journal Of Epidemiology. 1995;142:1059–68. [PubMed] [Google Scholar]
  • 7.Hansen N, Cowan S, Christensen PB, Weis N. [Reporting chronic hepatitis B and C in Denmark]. Ugeskrift for laeger. 2008;170(18):1567–70. Epub 2008/05/06. . [PubMed] [Google Scholar]
  • 8.Schmidt M, Schmidt SA, Sandegaard JL, Ehrenstein V, Pedersen L, Sorensen HT. The Danish National Patient Registry: a review of content, data quality, and research potential. Clinical epidemiology. 2015;7:449–90. Epub 2015/11/26. 10.2147/CLEP.S91125 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Nickelsen TN. [Data validity and coverage in the Danish National Health Registry. A literature review]. Danish Medical Journal. 2002;164(01):7–33. [PubMed] [Google Scholar]
  • 10.Obel N, Reinholdt H, Omland LH, Engsig F, Sørensen HT, Hansen A-BE. Retrivability in The Danish National Hospital Registry of HIV and hepatitis B and C coinfection diagnoses of patients managed in HIV centers 1995–2004. BMC Medical Research Methodology. 2008;8(1):25 10.1186/1471-2288-8-25 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Schmidt M, Pedersen L, Sorensen HT. The Danish Civil Registration System as a tool in epidemiology. European journal of epidemiology. 2014;29(8):541–9. Epub 2014/06/27. 10.1007/s10654-014-9930-3 . [DOI] [PubMed] [Google Scholar]
  • 12.Danish Health Authority. Drug use treatment—demand and availability (In Danish: “Stofmisbrugsbehandling–efterspørgsel og tilgængelighed. Narkotikasituationen i Danmark—delrapport 3”. Copenhagen: Danish Health Authority, 2019 6 June 2019.
  • 13.StatBank Denmark (www.statistikbanken.dk/folk1a) [Internet]. Statistics Denmark. 2019 [cited 23 September 2019].
  • 14.Francis B, Green M, Payne C. The GLIM System: Release 4 Manual. Oxford: Clarendon Press; 1993. [Google Scholar]
  • 15.Schwarz G. Estimating the Dimension of a Model. The Annals of Statistics. 1978;6(2):461–4. [Google Scholar]
  • 16.Gemmell I, Millar T Fau—Hay G, Hay G. Capture-recapture estimates of problem drug use and the use of simulation based confidence intervals in a stratified analysis. J Epidemiol Community Health. 2004;58(9):758–65. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Wildner-Christensen M, Hansen JM, De Muckadell OB. Risk factors for dyspepsia in a general population: non-steroidal anti-inflammatory drugs, cigarette smoking and unemployment are more important than Helicobacter pylori infection. Scandinavian journal of gastroenterology. 2006;41(2):149–54. Epub 2006/02/18. 10.1080/00365520510024070 . [DOI] [PubMed] [Google Scholar]
  • 18.Øvrehus A. Towards Elimination of Hepatitis C. Odense, Denmark: University of Southern Denmark; 2019.
  • 19.Soholm J, Holm DK, Mossner B, Madsen LW, Hansen JF, Weis N, et al. Incidence, prevalence and risk factors for hepatitis C in Danish prisons. PloS one. 2019;14(7):e0220297 Epub 2019/07/28. 10.1371/journal.pone.0220297 has been clinical investigator, lecturer and advisory board member for BMS, MSD and AbbVie; lecturer and/or advisory board member for Gilead and GSK. Honorarium paid to her institution. APS has received payment for serving as an advisory board member for AbbVie. The authors confirm that no other known conflicts of interest associated with this publication apart from those disclosed. This does not alter our adherence to PLOS ONE’s policies on sharing data and materials. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Hook EB, Regal RR. Capture-Recapture Methods in Epidemiology: Methods and Limitations. Epidemiologic Reviews. 1995;17(2):243–64. 10.1093/oxfordjournals.epirev.a036192 J Epidemiologic Reviews. [DOI] [PubMed] [Google Scholar]
  • 21.Kraus L, Augustin R, Frischer M, Kummler P, Uhl A, Wiessing L. Estimating prevalence of problem drug use at national level in countries of the European Union and Norway. Addiction (Abingdon, England). 2003;98(4):471–85. Epub 2003/03/26. 10.1046/j.1360-0443.2003.00326.x . [DOI] [PubMed] [Google Scholar]
  • 22.Stevens GA, Alkema L, Black RE, Boerma JT, Collins GS, Ezzati M, et al. Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement. The Lancet. 2016;388(10062):e19–e23. 10.1016/S0140-6736(16)30388-9 [DOI] [PubMed] [Google Scholar]
  • 23.Øvrehus A, Nielsen S, Hansen JF, Holm DK, Christensen P. Test uptake and hepatitis C prevalence in 5483 Danish people in drug use treatment from 1996 to 2015: a registry-based cohort study. 2019;114(3):494–503. 10.1111/add.14479 [DOI] [PubMed] [Google Scholar]
  • 24.Harris RJ, Harris HE, Mandal S, Ramsay M, Vickerman P, Hickman M, et al. Monitoring the hepatitis C epidemic in England and evaluating intervention scale-up using routinely collected data. 2019;26(5):541–51. 10.1111/jvh.13063 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Razavi H, Robbins S, Zeuzem S, Negro F, Butti M, Duberg AS, et al. Hepatitis C virus prevalence and level of intervention required to achieve the WHO targets for elimination in the European Union by 2030: a modelling study. Lancet Gastroenterol Hepatol. 2017;2(5):325–36. Epub 2017/04/12. 10.1016/S2468-1253(17)30045-6 . [DOI] [PubMed] [Google Scholar]
  • 26.Millbourn C, Lybeck C, Fadl H, Fredlund H, Lindahl K, Duberg AS. Screening for HCV in pregnant women and their partners. Journal of Hepatology. 2017;66(1):S404–S5. 10.1016/S0168-8278(17)31167-4 [DOI] [Google Scholar]
  • 27.Hofstraat SHI, Falla AM, Duffell EF, Hahne SJM, Amato-Gauci AJ, Veldhuijzen IK, et al. Current prevalence of chronic hepatitis B and C virus infection in the general population, blood donors and pregnant women in the EU/EEA: a systematic review. Epidemiol Infect. 2017;145(14):2873–85. Epub 2017/09/12. 10.1017/S0950268817001947 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Koopsen J, van Steenbergen JE, Richardus JH, Prins M, Op de Coul ELM, Croes EA, et al. Chronic hepatitis B and C infections in the Netherlands: estimated prevalence in risk groups and the general population. Epidemiol Infect. 2019;147:e147–e. 10.1017/S0950268819000359 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Litzroth A, Suin V, Wyndham-Thomas C, Quoilin S, Muyldermans G, Vanwolleghem T, et al. Low hepatitis C prevalence in Belgium: implications for treatment reimbursement and scale up. BMC Public Health. 2019;19(1):39-. 10.1186/s12889-018-6347-z . [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Garvey P, O’Grady B, Franzoni G, Bolger M, Irwin Crosby K, Connell J, et al. Hepatitis C virus seroprevalence and prevalence of chronic infection in the adult population in Ireland: a study of residual sera, April 2014 to February 2016. Euro Surveill. 2017;22(30):30579 10.2807/1560-7917.ES.2017.22.30.30579 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Annual epidemiological report for 2018. Surveillance systems overview for 2018 [Internet]. European Centre for Disease Prevention and Control. 2019 [cited 15 November 2019]. https://www.ecdc.europa.eu/en/publications-data/surveillance-systems-overview-2018.

Decision Letter 0

Yury E Khudyakov

14 Jul 2020

PONE-D-20-12246

Hepatitis C prevalence in Denmark in 2016

- an updated estimate using multiple national registers

PLOS ONE

Dear Dr. Christensen,

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.

Your manuscript was reviewed by 2 experts in the field. Both identified many important problems in your submission. Please carefully review the attached comments and provide clear point-by-point responses.

Please submit your revised manuscript by Aug 28 2020 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'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Yury E Khudyakov, PhD

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. In the ethics statement in the manuscript and in the online submission form, please provide additional information about the participant information used in your retrospective study.

Specifically, please ensure that you have discussed whether all data were fully anonymized before you accessed them and/or whether the IRB or ethics committee waived the requirement for informed consent.

If patients provided informed written consent to have data from these registries/databases used in research, please include this information.

3. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

4.Thank you for stating the following in the Financial Disclosure section:

'The study was supported by an unrestricted grant from MSD Denmark

URL: https://www.msd.dk/home

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.'

We note that you received funding from a commercial source: MSD Denmark

a. Please provide an amended Competing Interests Statement that explicitly states this commercial funder, along with any other relevant declarations relating to employment, consultancy, patents, products in development, marketed products, etc.

Within this Competing Interests Statement, please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests).  If there are restrictions on sharing of data and/or materials, please state these.

Please note that we cannot proceed with consideration of your article until this information has been declared.

b. Please include your amended Competing Interests Statement within your cover letter. We will change the online submission form on your behalf.

Please know it is PLOS ONE policy for corresponding authors to declare, on behalf of all authors, all potential competing interests for the purposes of transparency. PLOS defines a competing interest as anything that interferes with, or could reasonably be perceived as interfering with, the full and objective presentation, peer review, editorial decision-making, or publication of research or non-research articles submitted to one of the journals. Competing interests can be financial or non-financial, professional, or personal. Competing interests can arise in relationship to an organization or another person. Please follow this link to our website for more details on competing interests: http://journals.plos.org/plosone/s/competing-interests

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

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: No

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

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: The paper is of very poor value from the scientific point of view. The estimate of the proportion of subjects with undiagnosed CHC is affected by important biases: prisoners aren't representative of the general population, indeed findings lack of external validity; data from sera collected more than 20 years ago (1998-2000) are extremely out-dated.

Furthermore, the epidemiological data presented are obsolete because, starting from 2014, the epidemiological context has completely changed following the new direct-acting oral antiviral therapies (DAA) which, with a high sustained viral response (> 95%) and the consequent increase in treatments, have led to a faster decline of chronic hepatitis C prevalence globally.

HCV infection is mostly asymptomatic end random population-based surveys may provide accurate figures. Several national surveys have been performed in France, Spain, Italy, and U.S.A. over the last few years. None of them has been commented in the Discussion and reported in the References.

Reviewer #2: PONE-D-20-12246

The authors used a capture recapture method to estimate the population living with HCV in Denmark in the year 2016. The concept of this study is of value and the results will contribute to the literature. However, I have some comments regarding the analysis, and the content of the study.

I have below a few comments and suggestions that may improve the readability and understandability of the article.

Major comments:

1- In the method section, the first paragraph placement is confusing (line 82-line 86). I would suggest placing this paragraph after the data sources listing since this is highlighting the indicator used for the recapture stage.

2- In the Results section, the 2nd paragraph was confusing and hard to follow. The excluded 1,292 patients from the hospital register should be mentioned in the first paragraph where the authors are listing how they ended up with the number of patients included in the analysis (Line 190-198).

3- Also, I don’t understand how these patients were still counted since they didn’t meet the case definition mentioned in the methods section above: "1,292 who had either negative antiHCV or HCV-RNA results and/or had chronic hepatitis B (ICD10 code 18.1) with no signs of HCV coinfection according to the other source registers."

Minor comments:

1- Method section line 96, the word "included" is missing: " Since 1995, it also included all 97 hospital outpatient and emergency department visits

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Filomena Morisco

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 Sep 3;15(9):e0238203. doi: 10.1371/journal.pone.0238203.r002

Author response to Decision Letter 0


25 Jul 2020

Author response to queries in bold italic (please se uploaded file Response to Reviewers)

2. In the ethics statement in the manuscript and in the online submission form, please provide additional information about the participant information used in your retrospective study.

Specifically, please ensure that you have discussed whether all data were fully anonymized before you accessed them and/or whether the IRB or ethics committee waived the requirement for informed consent.

ANSWER: Data were fully anonymized prior to analysis. As a register-based study without contact to patients, informed consent from participants was not required, according to Danish law. This has been added to the methods section

If patients provided informed written consent to have data from these registries/databases used in research, please include this information.

ANSWER: Patients registered in the clinical database (DANHEP) provided written consent to have data used in research. This has been specified in the methods section.

3. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

ANSWER: We have obtained accept from our data safety authority to publish the anonymized dataset. This is available as an Excel-file. (DOI: 10.5281/zenodo.3959476)

4.Thank you for stating the following in the Financial Disclosure section:

'The study was supported by an unrestricted grant from MSD Denmark

URL: https://www.msd.dk/home

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.'

We note that you received funding from a commercial source: MSD Denmark

a. Please provide an amended Competing Interests Statement that explicitly states this commercial funder, along with any other relevant declarations relating to employment, consultancy, patents, products in development, marketed products, etc.

ANSWER: we have provided a specific statement of the funding role.

Within this Competing Interests Statement, please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests). If there are restrictions on sharing of data and/or materials, please state these.

Please note that we cannot proceed with consideration of your article until this information has been declared.

b. Please include your amended Competing Interests Statement within your cover letter. We will change the online submission form on your behalf.

ANSWER: we have included the statement in the cover letter.

Please know it is PLOS ONE policy for corresponding authors to declare, on behalf of all authors, all potential competing interests for the purposes of transparency. PLOS defines a competing interest as anything that interferes with, or could reasonably be perceived as interfering with, the full and objective presentation, peer review, editorial decision-making, or publication of research or non-research articles submitted to one of the journals. Competing interests can be financial or non-financial, professional, or personal. Competing interests can arise in relationship to an organization or another person. Please follow this link to our website for more details on competing interests: http://journals.plos.org/plosone/s/competing-interests

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

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: No

________________________________________

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

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: The paper is of very poor value from the scientific point of view. The estimate of the proportion of subjects with undiagnosed CHC is affected by important biases: prisoners aren't representative of the general population,

ANSWER As for the external validity, we agree that our samples are small and biased, but they are the only ones available in the country at the moment as no systematic HCV screening at population level is available. In addition, general population surveys also have drawbacks: most patients with chronic HCV are people with current or previous drug use and this population is usually not well captured in general population surveys (See e.g. the ECDC technical protocol for hepatitis C prevalence surveys in the general population published in March 2020. https://www.ecdc.europa.eu/en/publications-data/toolkit-support-generation-robust-estimates-hepatitis-c-prevalence). We agree that prison populations are not representative of the general population, but drug users may be tested here and we did not use the study to estimate the HCV prevalence but the undiagnosed fraction of chronic hepatitis C.

indeed findings lack of external validity;

ANSWER We agree that it would have been of high scientific value to perform a systematic population based survey of HCV prevalence in Denmark. However, we have not had the resources to do this. As an example testing a randomly selected population of 5000 individuals would cost 80.000€ in test kits –not including the costs of contacting and collecting the samples- and with an estimated population prevalence of 0.2% such a study would likely only identify about 10 patients with chronic HCV. In contrast the total cost of our study was less than 25.000 €. With the reservations mentioned in the discussion we find it is a cheap and feasible method to produce a national HCV prevalence estimate for Denmark.

data from sera collected more than 20 years ago (1998-2000) are extremely out-dated:

ANSWER: We find that the 3B samples are not outdated: There is no ongoing infection in this cohort and the few participants with HCV were infected in their youth in 60ies-80ies through drug use or nosocomial transmission prior to HCV screening introduced in the 90ies. They had not been identified in the registers since 2000 and therefor still represent the undiagnosed hepatitis C in the “pre-baby-boomer generation” that is still alive.

Furthermore, the epidemiological data presented are obsolete because, starting from 2014, the epidemiological context has completely changed following the new direct-acting oral antiviral therapies (DAA) which, with a high sustained viral response (> 95%) and the consequent increase in treatments, have led to a faster decline of chronic hepatitis C prevalence globally.

ANSWER: Unfortunately our data is not obsolete; In Denmark restrictions for DAA use were not removed until Nov. 2018 and few patients were treated between 2016 and 2018. Our study shows that in Denmark there will be a greater impact on HCV prevalence by contacting and treating diagnosed patients than by screening for undiagnosed HCV patients. Also importantly, our data will provide the denominator to measure the current Danish efforts to reach the WHO targets of 90% diagnosed and 80% treated.

HCV infection is mostly asymptomatic end random population-based surveys may provide accurate figures. Several national surveys have been performed in France, Spain, Italy, and U.S.A. over the last few years. None of them has been commented in the Discussion and reported in the references.

ANSWER: We are aware of the national population-based HCV prevalence surveys conducted in many countries -reviewed by e.g. Hofstraat et. al. 2017- and have added a reference to this in the discussion section. We have also added a short paragraph and reference to a recent HCV modelling study which found a similar proportion of diagnosed among people living with chronic HCV in Denmark to further support the data from the two external sources used in our study.

Reviewer #2: PONE-D-20-12246

The authors used a capture recapture method to estimate the population living with HCV in Denmark in the year 2016. The concept of this study is of value and the results will contribute to the literature. However, I have some comments regarding the analysis, and the content of the study.

I have below a few comments and suggestions that may improve the readability and understandability of the article.

Major comments:

1- In the method section, the first paragraph placement is confusing (line 82-line 86). I would suggest placing this paragraph after the data sources listing since this is highlighting the indicator used for the recapture stage.

ANSWER: We have mowed the paragraph as suggested.

2- In the Results section, the 2nd paragraph was confusing and hard to follow. The excluded 1,292 patients from the hospital register should be mentioned in the first paragraph where the authors are listing how they ended up with the number of patients included in the analysis (Line 190-198).

ANSWER: We have joint the two paragraphs and clarified why we don’t think the 1292 patients had hepatitis C. The bottom line is that the hospital register is not as reliable as the other registers we use, and we have removed patients who in the other registers had clear indication not to have chronic hepatitis C.

3- Also, I don’t understand how these patients were still counted since they didn’t meet the case definition mentioned in the methods section above: "1,292 who had either negative antiHCV or HCV-RNA results and/or had chronic hepatitis B (ICD10 code 18.1) with no signs of HCV coinfection according to the other source registers."

ANSWER: The 1.292 had the hepatitis C code in the hospital register (ICD code 18.2). However they had a later negative test for HCV in the laboratory register, or had no HCV test results and were instead positive for HBsAg or HBVDNA indicating chronic hepatitis B and suggesting a typing error in the hospital register where hepatitis B is coded as 18.0 or 18.1 We have clarified this in the text.

Minor comments:

1- Method section line 96, the word "included" is missing: " Since 1995, it also included all 97 hospital outpatient and emergency department visits

ANSWER: line 96 includes corrected to included”, and “it also all” changed to “it also included a

Attachment

Submitted filename: Response to reviewers.docx

Decision Letter 1

Yury E Khudyakov

12 Aug 2020

Hepatitis C prevalence in Denmark in 2016

- an updated estimate using multiple national registers

PONE-D-20-12246R1

Dear Dr. Christensen,

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.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. 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.

Kind regards,

Yury E Khudyakov, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

**********

6. 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 #2: (No Response)

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

Acceptance letter

Yury E Khudyakov

26 Aug 2020

PONE-D-20-12246R1

Hepatitis C prevalence in Denmark in 2016 - an updated estimate using multiple national registers

Dear Dr. Christensen:

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.

If we can help with anything else, please email us at plosone@plos.org.

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

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Yury E Khudyakov

Academic Editor

PLOS ONE

Associated Data

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

    Supplementary Materials

    Attachment

    Submitted filename: Response to reviewers.docx

    Data Availability Statement

    The dataset for the manuscript has been published at Zenodo.org: DOI 10.5281/zenodo.3959476.


    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES