Since a 2016 analysis on the epidemiology and disease burden of HCV in Croatia, the HCV treatment paradigm has shifted substantially. Fibrosis restrictions were removed, and the number of patients treated tripled. With these encouraging changes to policy and practice, an updated analysis was completed to guide resource allocation and a national strategic plan for HCV elimination in Croatia.
A comprehensive literature review and discussions with in-country experts were used to identify epidemiological factors defining HCV disease burden in Croatia. An HCV disease burden model, seeded with this data, was used to assess the impact of increasing screening rates and delineate the steps needed to reach the World Health Organization’s (WHO) Global Health and Sector Strategy hepatitis C elimination targets.
Achieving WHO elimination targets would reduce the number of viremic cases of HCV from 21,000 in 2015 to 4,000 by 2030 while averting 500 liver-related deaths, and 680 cases of hepatocellular carcinoma and decompensated cirrhosis from 2015 to 2030, relative to the projections under the current standard of care. Screening practices will need to ramp up to testing about 250,000 Croatians annually so that about 1,500 patients can be diagnosed and treated each year.
Elimination requires a coordinated effort between country and industry leaders including government authorities, policymakers and healthcare and insurance providers. Improved screening mechanisms will be needed for the scale-up required to achieve goals.
Nakon posljednje analize epidemioloških i kliničkih podataka o HCV infekciji iz 2016. godine došlo je do velikih promjena u paradigmi liječenja. Uklonjene su restrikcije vezane uz uznapredovali stadij fibroze jetre, a broj liječenih se utrostručio. S obzirom na ohrabrujuće činjenice u mogućnostima liječenja napravljena je nova analiza, koja će peciznije usmjeriti prioritete i alokaciju resursa za provedbu nacionalnog akcijskog plana za eliminaciju hepatitisa C.
Opsežan pregled literature i razgovori s hrvatskim stručnjacima korišteni su za identificiranje epidemioloških čimbenika koji definiraju opterećenje bolešću uzrokovanom virusom hepatitisa C u Hrvatskoj. Dobiveni podatci korišteni su u postojećem matematičkom modelu za procjenu opterećenja bolešću uzrokovanom HCV-om (engl.
Postizanje ciljeva SZO-a značilo bi redukciju HCV viremičnih slučajeva na 4.000 u 2030. uz sprječavanje 500 smrtnih ishoda uzrokovanih bolestima jetre i 680 slučajeva hepatocelularnog karcinoma i dekompenzirane ciroze u razdoblju od 2015. do 2030., za koje se procjenjuje da bi nastali uz sadašnju razinu probira i kliničku praksu. Prema upotrijebljenom matematičkom modelu to bi zahtijevalo povećanje broja testiranja na 250.000 osoba godišnje, kako bi se godišnje dijagnosticiralo i liječilo 1.500 pacijenata.
Eliminacija virusnih hepatitisa kompleksan je proces koji zahtijeva koordinirane aktivnosti i suradnju između medicinskih stručnjaka, državne politike, donositelja odluka i pružatelja zdravstvenog osiguranja. Povećanje opsega probirnog testiranja bit će ključno za postizanje ciljeva SZO-a u Hrvatskoj.
Viral hepatitis is a leading cause of death and affects one in 50 people worldwide. (
In 2016, we presented both the historical epidemiology of HCV in Croatia (
This analysis models the interventions needed to achieve WHO targets in addition to various screening strategies. Since HCV is more prevalent in older aged Croatians and in people who inject drugs, we modeled screening efforts for various population cohorts. Data inputs from previous analyses were also re-evaluated and updated with input from Croatian experts in the field of hepatitis. This analysis serves to guide decision-making and resource allocation to eliminate HCV in Croatia.
In January 2019, epidemiologists with the Centers for Disease Analysis Foundation (CDAF) completed a comprehensive literature search for epidemiologic factors associated with HCV infection in Croatia. Over the following three months, CDAF employed a Delphi process to facilitate discussions with in-country experts and reach consensus on epidemiologic inputs by reviewing available estimates and sharing unpublished research and insights. The data collected from this exercise were then input into a disease burden model that has been described in detail previously. (
The Microsoft® Excel-based Markov model uses annual disease progression rates to simulate the natural history of HCV through disease stages from acute hepatitis (considering spontaneous clearance) to chronic fibrosis and end-stage outcomes (including hepatocellular carcinoma, decompensated cirrhosis, liver transplantation and liver-related death). (
Parameter |
Value (Range) |
Estimate Year (EoY) |
Source / Izvor |
---|---|---|---|
HCV-RNA positive infections |
21,800 (20,500–34,200) | 2010 | Vilibić-Čavlek 2014, ( |
HCV genotype / HCV genotip | 56.6% G1 [18.8% G1a and 23.2% G1b], 37.3% G3, 4.2% G4, 1.6% G2 | 2018 | Vince 2018 ( |
Total diagnosed / Ukupno dijagnosticirani (HCV-RNA) | 4,000 | 2014 | EC |
Annual newly diagnosed |
170 | 2018 | EC |
Annual treated / Godišnje liječeni | 470 | 2018 | EC |
Percent of the infected population infected through transfusion |
23% | 2018 | EC |
Percent of the infected population that are people who inject drugs actively |
14% | 2010 | PC, ( |
EC – expert consensus / stručni konsenzus; EoY – end of year / kraj godine; HCV – hepatitis C / virus hepatitisa C; PC – personal communication / osobna komunikacija.
A full list of epidemiological inputs is included in
After seeding the model with Croatia-specific epidemiological factors, the Base scenario and four intervention scenarios were modeled for 2015–2030 (
Scenario / Scenario | Model parameter / Parametar | |||||||
---|---|---|---|---|---|---|---|---|
Base |
Screened / Broj testiranih | 33,400 | 40,800 | 40,600 | 38,600 | 35,700 | 33,500 | 32,000 |
Newly diagnosed |
170 | 210 | 210 | 210 | 210 | 210 | 210 | |
Treated / Liječeni | 470 | 470 | 470 | 400 | 320 | 250 | 250 | |
New infections / Nove infekcije | 140 | 140 | 130 | 120 | 120 | 110 | 110 | |
Screen |
Screened / Broj testiranih | 33,400 | 40,800 | 75,000 per year | ||||
Newly diagnosed |
170 | 210 | 740 | 710 | 680 | 610 | 610 | |
Treated / Liječeni | 470 | 470 | 670 | 640 | 610 | 550 | 550 | |
New infections / Nove infekcije | 140 | 140 | 130 | 120 | 110 | 100 | 100 | |
Screen |
Screened / Broj testiranih | 33,400 | 40,800 | 100,000 per year | ||||
Newly diagnosed |
170 | 210 | 980 | 930 | 870 | 720 | 720 | |
Treated / Liječeni | 470 | 470 | 880 | 830 | 780 | 650 | 650 | |
New infections / Nove infekcije | 140 | 140 | 120 | 120 | 100 | 90 | ||
Graduated Screening + Link to Care |
Screened / Broj testiranih | 33,400 | 40,800 | 75,000 | 100,000 per year | |||
Newly diagnosed |
170 | 210 | 740 | 940 | 880 | 750 | 750 | |
Treated / Liječeni | 470 | 470 | 670+270 | 850+200 | 820+90 | 690+30 | 680+50 | |
New infections / Nove infekcije | 140 | 140 | 130 | 120 | 100 | 90 | 90 | |
WHO Elimination Targets |
Screened / Broj testiranih | 33,400 | 40,800 | 75,600 | 151,000 | 224,000 | *avg 273,000 per year | |
Newly diagnosed |
170 | 210 | 740 | 1,400 | 1,800 | 1,000 | 1,000 | |
Treated / Liječeni | 470 | 470 | 670 +300 | 1,300+300 | 1,600+300 | 900 | 900 | |
New infections / Nove infekcije | 140 | 140 | 130 | 120 | 100 | 40 | 40 |
* Average number of patients screened annually from 2026–2028 in the WHO Elimination Targets scenario (278,000 to 324,000 range). / Prosječni broj testiranih godišnje od 2026. do 2030. prema eliminacijskim ciljevima SZO-a (raspon 278,000–324,000)
Screening trends were assessed for 2018–2030, under the following assumptions.
Base –
Screen 75K –
Screen 100K –
Graduated Screening + Link to Care –
WHO Elimination Targets –
Crystal Ball, an Excel add-in by Oracle, was used to run Monte Carlo simulations to generate 95% uncertainty intervals and sensitivity analysis. Beta-PERT distributions were used for all uncertain inputs.
At the beginning of 2018, there were an estimated 20,000 (95% uncertainty interval (UI): 14,500 – 24,000) viremic infections in Croatia. By the end of 2018, 19% (n=3,700) of infections were diagnosed. Of the total infected population, only 2% (n=470) were initiated on treatment. At an SVR rate of 97%, 460 of these patients were estimated to be cured (
The HCV cascade of care, including the total number of viremic infections, the number of diagnosed patients, and the number of patients treated and cured, Croatia, 2018
Under the Base, the number of viremic cases peaked in 2007 and will continue to decline by 30% between 2015 and 2030, resulting in 14,100 cases by the end of 2030. This decline is largely due to mortality. If no change is made to the HCV treatment paradigm in Croatia, liver-related deaths (LRD), incident hepatocellular carcinoma (HCC), and incident decompensated cirrhosis (DC) will increase by 70%, 80% and 90%, respectively. LRD will increase from 60 in 2015 to 110 in 2030, and incident HCC will increase from 50 in 2015 to 90 in 2030. Annually, new cases of DC will also increase from 40 in 2015 to 70 in 2030 (
Annual Outcomes* |
Cumulative Outcomes |
|||
---|---|---|---|---|
2015 | 2030 | Change from 2015 to 2030 |
Incident cases averted from 2015 to 2030 | |
Total viremic infections / Ukupni broj viremičnih slučajeva | ||||
Base / Polazište |
21,000 | 14,100 |
↓ 30% |
– |
Annual liver-related deaths (LRD) |
||||
Base / Polazište |
60 | 110 |
↑ 70% |
– |
Incident hepatocellular carcinoma (HCC) |
||||
Base / Polazište |
50 | 90 |
↑ 80% |
– |
Incident decompensated cirrhosis (DC) |
||||
Base / Polazište |
40 | 70 |
↑ 90% |
– |
*End of year/Kraj godine
Total infected cases, prevalent decompensated cirrhosis, prevalent HCC, and liver-related deaths, Croatia, 2015–2030
Cumulative number of patients screened and diagnosed, by scenario, Croatia, 2018–2030
By screening 75,000 Croatians annually and linking 90% of newly diagnosed patients to treatment, total infections would decline by 45%, but LRDs, incident HCC and incident DC would increase 45–55% from 2015–2030. Alternatively, if 100,000 Croatians are screened each year (with 90% of diagnosed patients linked to treatment), total infections would decline by 50%, compared with a 20–30% increase in LRD, incident HCC and incident DC. With graduated screening and linkage to care for previously diagnosed patients, total infections would decrease 55%, with a 5% reduction in LRD and 13–20% increase in HCC and DC from 2015–2030 (
Compared with the base scenario, eliminating HCV would avert 500 LRDs, 380 incident cases of HCC and 300 incident cases of DC by 2030 (
Now that a cure for HCV is available, case-finding has become the major obstacle to achieve elimination. Based on current disease burden assumptions, the model estimates that only 20% of infected Croatians are aware of their disease status, and only 2% of the infected population began treatment in 2018. In recent years, Croatia has enhanced effort to address HCV by removing fibrosis-level treatment restrictions and increasing the number of patients initiated on treatment, however a comprehensive strategy is needed to continue the momentum of action and to guide next steps. Four intervention scenarios were modeled to inform one data-driven, national screening strategy. Results demonstrate that as screening efforts are amplified (and assuming timely linkage to treatment for most patients) morbidity and mortality will decline in tandem (
The next crucial decision for Croatian health authorities developing a national plan is to determine which populations to target in the screening campaign. Focused testing among high-risk groups or birth cohorts are the most common method of screening expansion, both shown to be cost-effective. (
Age and sex distribution of hepatitis C cases, Croatia, 2018
Slight but significant changes were made to this analysis compared to previous reports. Guided by expert review and approval, this report updates data in the 2016 analysis (
Limitations inherent to modelling affected this analysis, including the estimation of disease burden based on multiple data sources. Application of the Delphi process, however, ensured that the data were reviewed and vetted by experts and determined to be the best available. Shortcomings in data quality, however, make it difficult to model screening scenarios because current diagnosis and screening data are likely under-reported. Once a formal screening campaign included in a national action plan begins, the data should be used to re-evaluate progress toward elimination and strategic plans. It is also important to acknowledge that projections are dependent on the data inputs and assumptions. The model assumes that DAAs are consistently available to the diagnosed population and that treatment uptake, initiation and retention will remain high, even in difficult-to-treat populations. However, real-world fluctuations in these variables over time could impact projections (
If WHO elimination targets are achieved, 500 liver-related deaths and 680 cases of hepatocellular carcinoma and decompensated cirrhosis could be prevented, and viremic cases of HCV could be reduced from 21,000 to 4,000 between 2015 and 2030. Elimination requires a coordinated effort between various country and industry leaders including government authorities, policymakers and healthcare and insurance providers. Improved screening mechanisms and patient registries (for tracking screening and diagnosis) will be needed for the scale-up required to achieve goals.
This project was supported by Gilead Sciences. Gilead Sciences had no input on the content, study design, data selection, decision to publish, or preparation of the manuscript.
The authors gratefully thank the following organizations for their involvement in consultations in forming this analysis: the Croatian Institute of Public Health, University Hospital of Infectious Disease Zagreb, Split University Hospital, Merkur Hospital Zagreb, Croatian Health Insurance Fund and Hepatos.
Reports of the number of patients diagnosed with chronic HCV were provided by in-country experts for 2014–2018. Case counts were adjusted assuming 80% were viremic (expert input). Experts agree underreporting exists in Croatia, as some patients seek anonymous testing in blood donor clinics and these cases are not consistently reported. The rate of underreporting is unknown; however, experts estimate about 20% of the total infected population is diagnosed. The data shown in
The screening module was developed to calculate the number of screening tests necessary to diagnose a given number of HCV-infections. The module used aforementioned epidemiological inputs (the infected population stratified by age and the number of annual diagnoses) to calculate the population eligible for screening, i.e., the undiagnosed, HCV-infected population that was either asymptomatic or not linked-to-care.
In the model, the more advanced stages of liver disease were assumed to be diagnosed first. It was also assumed that cases of spontaneous clearance were diagnosed at the same rate as asymptomatic, chronically infected cases.
To calculate the size of the population eligible for screening, the module tracked the populations with a history of screening, diagnosis, or SVR. It was assumed that each individual would receive at most one HCV antibody screen, and populations with a history of diagnosis or SVR would be excluded from future screening. Populations outside of the age range eligible for screening were excluded.
The number of patients needed to screen (NNS) to find one HCV antibody positive case was calculated, as shown in Equations 1–2. We then calculated the annual number of HCV antibody screens performed (Equation 3), of which all HCV antibody-positive tests were assumed to receive confirmatory HCV RNA testing. The case-finding algorithm assumed that persons with advanced liver disease were symptomatic and would seek care with or without active screening campaigns. Thus, each newly diagnosed case of advanced liver disease was assumed to require two screens; one HCV antibody and one confirmatory HCV RNA test.
Equation 1. Number needed to screen to diagnose one HCV antibody-positive case, unadjusted, in year
, where
Population eligible for screening
Equation 2. Number needed to screen to diagnose one HCV antibody-positive case, adjusted, in year
, where
is the number needed to screen to diagnose one HCV antibody-positive case, unadjusted, in year
Equation 3. Number of HCV antibody screens performed, in year
Newly diagnosed symptomatic HCV antibody-positive cases
Newly diagnosed asymptomatic or not yet linked-to-care cases
NNS
Appendix
Screening an average of 40,000 people/year results in an average of 200–650 new viremic diagnoses annually.
Screening an average of 75,000 people/year results in an average of 350–900 new viremic diagnoses a year.
Screening an average of 100,000 people/year results in an average of 450–1,1500 new viremic diagnoses a year.
Experts estimate that at least 40,000 Croatians were screened in 2018. The majority were tested in blood banks, with no tests conducted in primary care setting (expert input; Dr. Vince). Experts envisioned a goal of 75,000 Croatians screened annually, starting in 2020 (Appendix
Average Annual Diagnosed (ages 15+) / Prosječni broj dijagnosticiranih godišnje (dob 15+), 2020–2030 | |||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
150 | 200 | 250 | 300 | 350 | 400 | 450 | 500 | 550 | 600 | 650 | 700 | 750 | 800 | 850 | 900 | 950 | 1,000 | 1,050 | 1,100 | 1,150 | 1,200 | ||
Average prevalence in the population screened / Prosječna prevalencija u skriniranoj populaciji | 0.46% | ||||||||||||||||||||||
0.57% | |||||||||||||||||||||||
0.69% | |||||||||||||||||||||||
0.80% | |||||||||||||||||||||||
0.91% | |||||||||||||||||||||||
1.03% | |||||||||||||||||||||||
1.14% | |||||||||||||||||||||||
1.26% | |||||||||||||||||||||||
1.37% | |||||||||||||||||||||||
1.48% |
Screening an average of 40,000 people per year / Prosječni probir od 40,000 osoba godišnje
Screening an average of 75,000 people per year / Prosječni probir od 75,000 osoba godišnje
Screening an average of 100,000 people per year / Prosječni probir od 100,000 osoba godišnje
Population |
Risk of infec-tion in the population* |
Number screened in 2018 |
Number to screen starting in 2020 / Broj testiranih od 2020. |
---|---|---|---|
Blood banks |
Low |
30,000 | 30,000 |
Voluntary centers |
High |
5,000 | 5,000 |
Primary care/Laboratories |
Mixed |
4,500 | 39,500 |
Screening vans |
High |
500 | 500 |
Total / Ukupno | 40,000 | 75,000 |
* Risk of infection in the population is defined as follows: Low – same prevalence (1x) as the general Croatian population; High – 3x general population prevalence (on average); Mixed – 2x general population prevalence (on average) / Rizik infekcije u populaciji je definiran na slijedeći način: nizak – ista prevalencija kao u općoj populaciji; visok – 3x veća prevalencija nego u općoj populaciji; mješovit – 2x veća prevalencija nego u općoj populaciji
Primary care facilities do not screen in-house, but outsource to laboratories (i.e. the 4,500 screened in 2018) / Testiranje se ne obavlja u ambulantama obiteljske medicine, nego se pacijenti upućuju u različite laboratorije koji pružaju tu uslugu