The Global Health Observatory
Explore a world of health data
The Global Health Observatory
Explore a world of health data
Numerator : Number of deaths attributed to hepatitis B plus Number of deaths attributed to hepatitis C (multiplied by 100,000)
Denominator: Total population of the specified reporting year
Routine hepatitis mortality surveillance reported by countries .
WHO recommends the use of hepatitis sequalae surveillance from sentinel site. This involves estimating proportion people with HCC and decompensated cirrhosis who have chronic hepatitis B or C in the sentinel sites.
Where these data are unavailable, WHO leads a consultative process to produce country-calibrated modelled estimates of number of deaths from chronic HBV and viraemic HCV.
Number of deaths chronic HBV infection are estimated using the PRoGReSs model. 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.
The disease stages considered in the PRoGReSs model are chronic hepatitis B, compensated cirrhosis, decompensated cirrhosis, hepatocellular carcinoma, and liver transplant .HBV-infected population in each disease stage is further divided into high-viral load (HBsAg-positive with HBV DNA of 20,000 IU/mL or more), low-viral load (HBsAg-positive with HBV DNA of less than 20,000 IU/mL), and treatment responder subpopulations. The population susceptible to HBV is also tracked by age and sex, consisting of uninfected individuals who had never been exposed to HBV and had not been successfully immunized. Those developing a chronic hepatitis B infection are split into low- and high-viral load cases using reported data on respective proportions of high-viral load cases among HBeAg-negative and HBeAg-positive populations. Since the risk for chronic hepatitis B infection largely depends on the age of acquisition of infection, the model begins in 1900 to allow for full flexibility.
Number of deaths viraemic HCV infections are estimated using the Markov/semi-dynamic (disease progression) model . The model employs a 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).The model starts with the annual number of acute infections that progressed to chronic HCV (viraemic) infection after accounting for spontaneous clearance of the virus. The progression of these new cases is followed along with all chronic infections from prior years. Unless specified, the scope of the model is limited to viraemic, HCV ribonucleic acid (RNA) positive cases. Non-viraemic cases (those exposed to the virus but spontaneously cleared the virus or were treated and cured) are not considered. The number of new cases at each stage of disease (incidence) is calculated annually by multiplying the annual progression rates times the prevalent population (by age and gender) in the previous stage. After one year, new cases are considered prevalent cases (after accounting for mortality and cured).
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