Number HBV diagnosed, Number HCV diagnosed

This indicator measures progress of diagnosis coverage among people living with chronic HBV and viraemic HCV infections, towards the 2030 hepatitis elimination goals.

• Number of chronic HBV infected persons diagnosed with a positive HBsAg test
• Number of chronic HCV infected persons currently viraemic, diagnosed with a positive HCV RNA (PCR) or HCV core antigen, any year prior to or in the reporting year as long as they are still alive and viraemic
• Number of chronic HCV infected persons ever diagnosed with a positive HCV RNA (PCR) or HCV core antigen, including those cured

By country and WHO region

Country-reported data: The indicator is compiled from routine national programme, surveillance, laboratory, clinical or health information system records. Data should cover the reporting year and the geographical and population scope reported by the country. Countries should describe whether the data are national or subnational, which sectors and facilities are included, and whether individual-level deduplication or record linkage is used.

Modelled estimates: Where complete country-reported data are unavailable, WHO may produce a country-calibrated estimate using available programme data, epidemiological evidence, demographic data and other relevant inputs. The modelled estimate is intended to provide a coherent value for the specified reference year and may not equal a value reported directly by the country.

HBV model structure (PRoGReSs model): the HBV model uses a dynamic mathematical framework that estimates annual HBV prevalence and incidence by stage of liver disease, age and sex using disease progression and mortality (all-cause and liver-related) rates. The model integrates demographic profiles, vaccination coverage (including timely birth dose and three-dose infant series), prevention measures such as hepatitis B immune globulin (HBIG) and maternal antiviral prophylaxis, HBV diagnosis and treatment schedules, and established HBV epidemiological parameters. Perinatal, early childhood and horizontal transmission are modelled using age-specific hepatitis B surface antigen (HBsAg) prevalence together with available prevention-coverage data. This allows the model to reflect both historical and current programme performance.

HCV model structure: the HCV model employs a Markov/semi-dynamic natural history framework that follows people with viraemic infection across stages of liver disease, by age and sex, over time using disease progression and mortality (all-cause and liver-related) rates. It incorporates inputs from demographic profiles, HCV diagnosis and treatment initiation schedules, and subsequent cure (sustained virological response, SVR).

Regional estimates are the sum of the country data in each WHO region.

Cases

Every two years

Continuous at country level reported every two years to WHO

Comparability and Interpretation: Country-reported diagnosed populations reflect testing and reporting practices and should not be interpreted as the total number of people living with infection. Comparison between countries should account for differences in testing strategies, health system coverage and reporting completeness.

This dataset contains a combination of country-reported data and WHO-supported modelled estimates. Values may differ because they are derived from different data sources, population coverage, reference years and methodologies. Country-reported data are intended primarily for national programme monitoring, whereas modelled estimates are intended to support standardized comparisons across countries and over time. Direct comparisons between country-reported and modelled values, or between countries represented by different observation types, should therefore be made with caution. Differences between WHO estimates and official national figures should not necessarily be interpreted as errors but may reflect methodological and data-source differences.

hepatitisreporting@who.int

Diana Faini

3525

Reported numbers of diagnosed persons may be affected by incomplete testing coverage, fragmented reporting systems, limited capture of private-sector services, duplicate records and lack of unique patient identifiers. Cumulative diagnosed counts may include individuals who have subsequently died, migrated or been cured. Variations in diagnostic algorithms and reporting practices may affect comparability.