Effectiveness of SARS-CoV-2 primary vaccines and boosters in patients with type 2 diabetes mellitus in Hungary (HUN-VE 4 Study).

INTRODUCTION: Type 2 diabetes mellitus is a risk factor for severe COVID-19 infection and is associated with increased risk of complications. The present study aimed to investigate effectiveness and persistence of different COVID vaccines in persons with or without diabetes during the Delta wave in Hungary. RESEARCH DESIGN AND METHODS: Data sources were the national COVID-19 registry data from the National Public Health Center and the National Health Insurance Fund on the total Hungarian population. The adjusted incidence rate ratios and corresponding 95% CIs were derived from a mixed-effect negative binomial regression model. RESULTS: A population of 672 240 cases with type 2 diabetes and a control group of 2 974 102 non-diabetic persons free from chronic diseases participated. Unvaccinated elderly persons with diabetes had 2.68 (95% CI 2.47 to 2.91) times higher COVID-19-related mortality rate as the 'healthy' controls. Primary immunization effectively equalized the risk of COVID-19 mortality between the two groups. Vaccine effectiveness declined over time, but the booster restored the effectiveness against mortality to over 90%. The adjusted vaccine effectiveness of the primary Pfizer-BioNTech against infection in the 14-120 days of postvaccination period was 71.6 (95% CI 66.3 to 76.1)% in patients aged 65-100 years with type 2 diabetes and 64.52 (95% CI 59.2 to 69.2)% in the controls. Overall, the effectiveness tended to be higher in individuals with diabetes than in controls. The booster vaccines could restore vaccine effectiveness to over 80% concerning risk of infection (eg, patients with diabetes aged 65-100 years: 89.1 (88.1-89.9)% with Pfizer-on-Pfizer, controls 65-100 years old: 86.9 (85.8-88.0)% with Pfizer-on-Pfizer, or patients with diabetes aged 65-100 years: 88.3 (87.2-89.2)% with Pfizer-on-Sinopharm, controls 65-100 years old: 87.8 (86.8-88.7)% with Pfizer-on-Sinopharm). CONCLUSIONS: Our data suggest that people with type 2 diabetes may have even higher health gain when getting vaccinated as compared with non-diabetic persons, eliminating the marked, COVID-19-related excess risk of this population. Boosters could restore protection.

Waning of SARS-CoV-2 Vaccine Effectiveness in COPD Patients: Lessons from the Delta Variant.

Although the COVID-19 pandemic is profoundly changing, data on the effect of vaccination and duration of protection against infection and severe disease can still be advantageous, especially for patients with COPD, who are more vulnerable to respiratory infections. The Hungarian COVID-19 registry was retrospectively investigated for risk of infection and hospitalization by time since the last vaccination, and vaccine effectiveness (VE) was calculated in adults with COPD diagnosis and an exact-matched control group during the Delta variant of concern (VOC) wave in Hungary (September-December 2021). For the matching, sex, age, major co-morbidities, vaccination status, and prior infection data were obtained on 23 August 2021. The study population included 373,962 cases divided into COPD patients (age: 66.67 ± 12.66) and a 1:1 matched group (age: 66.73 ± 12.67). In both groups, the female/male ratio was 52.2:47.7, respectively. Among the unvaccinated, there was no difference between groups in risk for infection or hospitalization. Regarding vaccinated cases, in the COPD group, a slightly faster decline in effectiveness was noted for hospitalization prevention, although in both groups, the vaccine lost its significant effect between 215 and 240 days after the last dose of vaccination. Based on a time-stratified multivariate Cox analysis of the vaccinated cases, the hazard was constantly higher in the COPD group, with an HR of 1.09 (95%: 1.05-1.14) for infection and 1.87 (95% CI: 1.59-2.19) for hospitalization. In our study, COPD patients displayed lower vaccine effectiveness against SARS-CoV-2 infection and hospitalization but a similar waning trajectory, as vaccines lost their preventive effect after 215 days. These data emphasize revaccination measures in the COPD patient population.

Opposite trends in incidence of breast cancer in young and old female cohorts in Hungary and the impact of the Covid-19 pandemic: a nationwide study between 2011-2020.

Background: This nationwide study examined breast cancer (BC) incidence and mortality rates in Hungary between 2011-2019, and the impact of the Covid-19 pandemic on the incidence and mortality rates in 2020 using the databases of the National Health Insurance Fund (NHIF) and Central Statistical Office (CSO) of Hungary. Methods: Our nationwide, retrospective study included patients who were newly diagnosed with breast cancer (International Codes of Diseases ICD)-10 C50) between Jan 1, 2011 and Dec 31, 2020. Age-standardized incidence and mortality rates (ASRs) were calculated using European Standard Populations (ESP). Results: 7,729 to 8,233 new breast cancer cases were recorded in the NHIF database annually, and 3,550 to 4,909 all-cause deaths occurred within BC population per year during 2011-2019 period, while 2,096 to 2,223 breast cancer cause-specific death was recorded (CSO). Age-standardized incidence rates varied between 116.73 and 106.16/100,000 PYs, showing a mean annual change of -0.7% (95% CI: -1.21%-0.16%) and a total change of -5.41% (95% CI: -9.24 to -1.32). Age-standardized mortality rates varied between 26.65-24.97/100,000 PYs (mean annual change: -0.58%; 95% CI: -1.31-0.27%; p=0.101; total change: -5.98%; 95% CI: -13.36-2.66). Age-specific incidence rates significantly decreased between 2011 and 2019 in women aged 50-59, 60-69, 80-89, and ≥90 years (-8.22%, -14.28%, -9.14%, and -36.22%, respectively), while it increased in young females by 30.02% (95%CI 17,01%- 51,97%) during the same period. From 2019 to 2020 (in first COVID-19 pandemic year), breast cancer incidence nominally decreased by 12% (incidence rate ratio [RR]: 0.88; 95% CI: 0.69-1.13; 2020 vs. 2019), all-cause mortality nominally increased by 6% (RR: 1.06; 95% CI: 0.79-1.43) among breast cancer patients, and cause-specific mortality did not change (RR: 1.00; 95%CI: 0.86-1.15). Conclusion: The incidence of breast cancer significantly decreased in older age groups (≥50 years), oppositely increased among young females between 2011 and 2019, while cause-specific mortality in breast cancer patients showed a non-significant decrease. In 2020, the Covid-19 pandemic resulted in a nominal, but not statistically significant, 12% decrease in breast cancer incidence, with no significant increase in cause-specific breast cancer mortality observed during 2020.

Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants.

(MOTIVATION): Wastewater-based epidemiology (WBE) has emerged as a promising approach for monitoring the COVID-19 pandemic, since the measurement process is cost-effective and is exposed to fewer potential errors compared to other indicators like hospitalization data or the number of detected cases. Consequently, WBE was gradually becoming a key tool for epidemic surveillance and often the most reliable data source, as the intensity of clinical testing for COVID-19 drastically decreased by the third year of the pandemic. Recent results suggests that the model-based fusion of wastewater measurements with clinical data and other indicators is essential in future epidemic surveillance. (METHOD): In this work, we developed a wastewater-based compartmental epidemic model with a two-phase vaccination dynamics and immune evasion. We proposed a multi-step optimization-based data assimilation method for epidemic state reconstruction, parameter estimation, and prediction. The computations make use of the measured viral load in wastewater, the available clinical data (hospital occupancy, delivered vaccine doses, and deaths), the stringency index of the official social distancing rules, and other measures. The current state assessment and the estimation of the current transmission rate and immunity loss allow a plausible prediction of the future progression of the pandemic. (RESULTS): Qualitative and quantitative evaluations revealed that the contribution of wastewater data in our computational epidemiological framework makes predictions more reliable. Predictions suggest that at least half of the Hungarian population has lost immunity during the epidemic outbreak caused by the BA.1 and BA.2 subvariants of Omicron in the first half of 2022. We obtained a similar result for the outbreaks caused by the subvariant BA.5 in the second half of 2022. (APPLICABILITY): The proposed approach has been used to support COVID management in Hungary and could be customized for other countries as well.

Underlying reasons for post-mortem diagnosed lung cancer cases - A robust retrospective comparative study from Hungary (HULC study).

Objective: The Hungarian Undiagnosed Lung Cancer (HULC) study aimed to explore the potential reasons for missed LC (lung cancer) diagnosis by comparing healthcare and socio-economic data among patients with post-mortem diagnosed LC with those who were diagnosed with LC during their lives. Methods: This nationwide, retrospective study used the databases of the Hungarian Central Statistical Office (HCSO) and National Health Insurance Fund (NHIF) to identify patients who died between January 1, 2019 and December 31, 2019 and were diagnosed with lung cancer post-mortem (population A) or during their lifetime (population B). Patient characteristics, socio-economic factors, and healthcare resource utilization (HCRU) data were compared between the diagnosed and undiagnosed patient population. Results: During the study period, 8,435 patients were identified from the HCSO database with LC as the cause of death, of whom 1,203 (14.24%) had no LC-related ICD (International Classification of Diseases) code records in the NHIF database during their lives (post-mortem diagnosed LC population). Post-mortem diagnosed LC patients were significantly older than patients diagnosed while still alive (mean age 71.20 vs. 68.69 years, p<0.001), with a more pronounced age difference among female patients (difference: 4.57 years, p<0.001), and had significantly fewer GP (General Practitioner) and specialist visits, X-ray and CT scans within 7 to 24 months and 6 months before death, although the differences in GP and specialist visits within 7-24 months did not seem clinically relevant. Patients diagnosed with LC while still alive were more likely to be married (47.62% vs. 33.49%), had higher educational attainment, and had more children, than patients diagnosed with LC post-mortem. Conclusions: Post-mortem diagnosed lung cancer accounts for 14.24% of total lung cancer mortality in Hungary. This study provides valuable insights into patient characteristics, socio-economic factors, and HCRU data potentially associated with a high risk of lung cancer misdiagnosis.

Effectiveness and Waning of Protection With Different SARS-CoV-2 Primary and Booster Vaccines During the Delta Pandemic Wave in 2021 in Hungary (HUN-VE 3 Study).

Background: In late 2021, the pandemic wave was dominated by the Delta SARS-CoV-2 variant in Hungary. Booster vaccines were offered for the vulnerable population starting from August 2021. Methods: The nationwide HUN-VE 3 study examined the effectiveness and durability of primary immunization and single booster vaccinations in the prevention of SARS-CoV-2 infection, Covid-19 related hospitalization and mortality during the Delta wave, compared to an unvaccinated control population without prior SARS-CoV-2 infection. Results: The study population included 8,087,988 individuals who were 18-100 years old at the beginning of the pandemic. During the Delta wave, after adjusting for age, sex, calendar day, and chronic diseases, vaccine effectiveness (VE) of primary vaccination against registered SARS-CoV-2 infection was between 11% to 77% and 18% to 79% 14-120 days after primary immunization in the 16-64 and 65-100 years age cohort respectively, while it decreased to close to zero in the younger age group and around 40% or somewhat less in the elderly after 6 months for almost all vaccine types. In the population aged 65-100 years, we found high, 88.1%-92.5% adjusted effectiveness against Covid-19 infection after the Pfizer-BioNTech, and 92.2%-95.6% after the Moderna booster dose, while Sinopharm and Janssen booster doses provided 26.5%-75.3% and 72.9%-100.0% adjusted VE, respectively. Adjusted VE against Covid-19 related hospitalization was high within 14-120 days for Pfizer-BioNTech: 76.6%, Moderna: 83.8%, Sputnik-V: 78.3%, AstraZeneca: 73.8%, while modest for Sinopharm: 45.7% and Janssen: 26.4%. The waning of protection against Covid-19 related hospitalization was modest and booster vaccination with mRNA vaccines or the Janssen vaccine increased adjusted VE up to almost 100%, while the Sinopharm booster dose proved to be less effective. VE against Covid-19 related death after primary immunization was high or moderate: for Pfizer-BioNTech: 81.5%, Moderna: 93.2%, Sputnik-V: 100.0%, AstraZeneca: 84.8%, Sinopharm: 58.6%, Janssen: 53.3%). VE against this outcome also showed a moderate decline over time, while booster vaccine types restored effectiveness up to almost 100%, except for the Sinopharm booster. Conclusions: The HUN-VE 3 study demonstrated waning VE with all vaccine types for all examined outcomes during the Delta wave and confirmed the outstanding benefit of booster vaccination with the mRNA or Janssen vaccines, and this is the first study to provide clear and comparable effectiveness results for six different vaccine types after primary immunization against severe during the Delta pandemic wave.

Booster Vaccination Decreases 28-Day All-Cause Mortality of the Elderly Hospitalized Due to SARS-CoV-2 Delta Variant.

(1) Background: SARS-CoV-2 infections are associated with an increased risk of hospital admissions especially in the elderly (age ≥ 65 years) and people with multiple comorbid conditions. (2) Methods: We investigated the effect of additional booster vaccinations following the primary vaccination series of mRNA, inactivated whole virus, or vector vaccines on infections with the SARS-CoV-2 delta variant in the total Hungarian elderly population. The infection, hospital admission, and 28-day all-cause mortality of elderly population was assessed. (3) Results: A total of 1,984,176 people fulfilled the criteria of elderly including 299,216 unvaccinated individuals, while 1,037,069 had completed primary vaccination and 587,150 had obtained an additional booster. The primary vaccination series reduced the risk of infection by 48.88%, the risk of hospital admission by 71.55%, and mortality by 79.87%. The booster vaccination had an additional benefit, as the risk of infection, hospital admission, and all-cause mortality were even lower (82.95%; 92.71%; and 94.24%, respectively). Vaccinated patients needing hospitalization suffered significantly more comorbid conditions, indicating a more vulnerable population. (4) Conclusions: Our data confirmed that the primary vaccination series and especially the booster vaccination significantly reduced the risk of the SARS-CoV-2 delta-variant-associated hospital admission and 28-day all-cause mortality in the elderly despite significantly more severe comorbid conditions.

Nationwide Effectiveness of First and Second SARS-CoV2 Booster Vaccines During the Delta and Omicron Pandemic Waves in Hungary (HUN-VE 2 Study).

Background: In Hungary, the pandemic waves in late 2021 and early 2022 were dominated by the Delta and Omicron SARS-CoV-2 variants, respectively. Booster vaccines were offered with one or two doses for the vulnerable population during these periods. Methods and Findings: The nationwide HUN-VE 2 study examined the effectiveness of primary immunization, single booster, and double booster vaccination in the prevention of Covid-19 related mortality during the Delta and Omicron waves, compared to an unvaccinated control population without prior SARS-CoV-2 infection during the same study periods. The risk of Covid-19 related death was 55% lower during the Omicron vs. Delta wave in the whole study population (n=9,569,648 and n=9,581,927, respectively; rate ratio [RR]: 0.45, 95% confidence interval [CI]: 0.44-0.48). During the Delta wave, the risk of Covid-19 related death was 74% lower in the primary immunized population (RR: 0.26; 95% CI: 0.25-0.28) and 96% lower in the booster immunized population (RR: 0.04; 95% CI: 0.04-0.05), vs. the unvaccinated control group. During the Omicron wave, the risk of Covid-19 related death was 40% lower in the primary immunized population (RR: 0.60; 95% CI: 0.55-0.65) and 82% lower in the booster immunized population (RR: 0.18; 95% CI: 0.16-0.2) vs. the unvaccinated control group. The double booster immunized population had a 93% lower risk of Covid-19 related death compared to those with only one booster dose (RR: 0.07; 95% CI. 0.01-0.46). The benefit of the second booster was slightly more pronounced in older age groups. Conclusions: The HUN-VE 2 study demonstrated the significantly lower risk of Covid-19 related mortality associated with the Omicron vs. Delta variant and confirmed the benefit of single and double booster vaccination against Covid-19 related death. Furthermore, the results showed the additional benefit of a second booster dose in terms of SARS-CoV-2 infection and Covid-19 related mortality.

Nationwide effectiveness of five SARS-CoV-2 vaccines in Hungary-the HUN-VE study.

OBJECTIVES: The Hungarian vaccination campaign was conducted with five different vaccines during the third wave of the coronavirus disease 2019 (COVID-19) pandemic in 2021. This observational study (HUN-VE: Hungarian Vaccine Effectiveness) estimated vaccine effectiveness against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and COVID-19-related mortality in 3.7 million vaccinated individuals. METHODS: Incidence rates of SARS-CoV-2 infection and COVID-19-related mortality were calculated using data from the National Public Health Centre surveillance database. Estimated vaccine effectiveness was calculated as 1 - incidence rate ratio ≥7 days after the second dose for each available vaccine versus an unvaccinated control group using mixed-effect negative binomial regression controlling for age, sex and calendar day. RESULTS: Between 22 January 2021 and 10 June 2021, 3 740 066 Hungarian individuals received two doses of the BNT162b2 (Pfizer-BioNTech), HB02 (Sinopharm), Gam-COVID-Vac (Sputnik-V), AZD1222 (AstraZeneca), or mRNA-1273 (Moderna) vaccines. Incidence rates of SARS-CoV-2 infection and COVID-19-related death were 1.73-9.3/100 000 person-days and 0.04-0.65/100 000 person-days in the fully vaccinated population, respectively. Estimated adjusted effectiveness varied between 68.7% (95% CI 67.2%-70.1%) and 88.7% (95% CI 86.6%-90.4%) against SARS-CoV-2 infection, and between 87.8% (95% CI 86.1%-89.4%) and 97.5% (95% CI 95.6%-98.6%) against COVID-19-related death, with 100% effectiveness in individuals aged 16-44 years for all vaccines. CONCLUSIONS: Our observational study demonstrated the high or very high effectiveness of five different vaccines in the prevention SARS-CoV-2 infection and COVID-19-related death.

A nationwide study of the epidemiology of relapsing polychondritis.

OBJECTIVE: Relapsing polychondritis (RP) is a rare autoimmune inflammatory disease that attacks mainly cartilaginous structures or causes serious damage in proteoglycan-rich structures (the eyes, heart, blood vessels, inner ear). This study shows results regarding the epidemiology, progression, and associations of this highly variable disease by collecting all cases from a 124-million-person-year Central European nationwide cohort. METHODS: We used the Hungarian Health Care Database to identify all persons with possible RP infection. We followed patients who had International Classification of Diseases 10th edition code M94.1 at least once in their inpatient or outpatient records between January 1, 2002 and December 31, 2013 in Hungary. We classified these patients into disease severity groups by their drug consumption patterns between January 1, 2010 and December 31, 2013. We analyzed the regional distribution of RP incidences as well. Overall maps of comorbidity are presented with network layouts. RESULTS: We identified 256 patients with RP among cumulatively 11.5 million registered inhabitants. We classified these patients into four severity classes as "extremely mild" (n=144), "mild" (n=22), "moderate" (n=41), and "severe" (n=4). Two additional groups were defined for patients without available drug data as "suspected only" (n=23) and "confirmed but unknown treatment" (n=22). The age and sex distributions of patients were similar to worldwide statistics. Indeed, the overall survival was good (95% confidence interval for 5 years was 83.6%-92.9% and for 10 years was 75.0%-88.3% which corresponds to the overall survival of the general population in Hungary), and the associations with other autoimmune disorders were high (56%) in Hungary. Almost any disease can occur with RP; however, the symptoms of chromosomal abnormalities are only incidental. Spondylosis can be a sign of the activation of RP, while Sjögren syndrome is the most frequent autoimmune association. Regional distribution of incidences suggests arsenic drinking water and sunlight exposure as possible triggering factors. CONCLUSION: The good survival rate of RP in Hungary is probably associated with the early diagnosis of the disease.

Is there a common background to support better healthcare in Central and South East Europe?

The workshop is proposed by the EFMI WG Health Informatics for Interregional Cooperation with the support of the Electronic Healthcare Records WG as a platform for finding common interests regarding improvement of healthcare services for the Central and East European geographical area. The goal is to assess conformance to international standards in healthcare and to find domains in which each country can provide best practices results of using ICT in support of healthcare.

Ontological analysis of SNOMED CT.

BACKGROUND: SNOMED CT is the most comprehensive medical terminology. However, its use for intelligent services based on formal reasoning is questionable. METHODS: The analysis of the structure of SNOMED CT is based on the formal top-level ontology DOLCE. RESULTS: The analysis revealed several ontological and knowledge-engineering errors, the most important are errors in the hierarchy (mostly from an ontological point of view, but also regarding medical aspects) and the mixing of subsumption relations with other types (mostly 'part of'). CONCLUSION: The found errors impede formal reasoning. The paper presents a possible way to correct these problems.

A deployment and Research Roadmap for Semantic Interoperability: the EU semantic health project.

The purpose of this EU funded project is to describe a short and medium term Research and Deployment Roadmap for Semantic Interoperability in e-health. It started by defining 4 levels and 3 dimensions for Semantic Interoperability. The vision is to reconcile the needs for the direct patient care safety, biomedical and clinical research and for public health by the reuse of direct care data: from gene to individuals and populations. The methodology is presented and preliminary results and milestones for the short and the long term are set. We conclude by statements on the main characteristics and needs of the roadmap to sustain better health for individual and populations in the changing EU health care systems.

Design principles of DOLCE-based formal representation of ICD10.

The authors present the framework of formal representation of ICD10 based on DOLCE. The goal of the work is to represent the meaning of the categories of the classification systems based on a formal top-level ontology. The ICD categories are described in the space of atomic disease concepts, while the diseases themselves are defined on a pathological basis. The anatomical entities are taken from FMA, functions, morphological abnormalities and procedures from SNOMED International, while organisms are taken form the biological taxonomy. The ontology is represented in OWL 1.0 in a modularised way. The transformation of the previous GALEN-based representation to the same conceptual system is also under way.

Dichotomy - a forgotten ancient principle.

UNLABELLED: Dichotomy is an ancient principle of categorisation, where a class is divided into two jointly exhaustive and mutually disjoint categories. The principle as a general requirement was abandoned during the middle. The recent inquiry shows that studying this principle is still worthwhile and in some cases it can be used as a quality assessment tool. The paper presents algorithms that can transform any kind of categorial structures into dichotomy. The resulting representation sometimes can make apparent the problematic parts of the source. Problems often result from stating Is_a relations without differentiating criteria. A simple experiment of dichotomous transformation of the high level categories of the first chapter of ICD was carried out. The problem of "other" and "not elsewhere classified" categories is discussed. CONCLUSION: we should not strive to build dichotomous structures but sometimes a dichotomous transformation of an existing structure can be helpful to detect critical parts of a system of categories.

GALEN based formal representation of ICD10.

OBJECTIVES: The main objective is to create a knowledge-intensive coding support tool for the International Classification of Diseases (ICD10), which is based on formal representation of ICD10 categories. Beyond this task the resulting ontology could be reused in various ways. Decidability is an important issue for computer-assisted coding; consequently the ontology should be represented in description logic. METHODS: The meaning of the ICD10 categories is represented using the GALEN Core Reference Model. Due to the deficiencies of its representation language (GRAIL) the ontology is transformed to the quasi-standard OWL. A test system which extracts disease concepts and classifies them to ICD10 categories has been implemented in Prolog to verify the feasibility of the approach. RESULTS: The formal representation of the first two chapters of ICD10 (infectious diseases and neoplasms) has been almost completed. The constructed ontology has been converted to OWL DL. The test system successfully identified diseases in medical records from gastrointestinal oncology (84% recall, however precision is only 45%). The classifier module is still under development. Due to the experiences gained during the modelling, in the future work FMA is going to be used as anatomical reference ontology.

Non Aristotelian categories in medicine.

This paper discusses the representation of medical categories that can not be defined in Aristotelian sense. Two kinds of these categories are mentioned: the prototype and the family resemblance categories. Such categories obviously do exist in medical domain. Search on the Net was performed for free text definition for some commonly used medical categories, like 'autism', 'Burkitt lymphoma' and 'disease'. Most of the found often contradicting definitions do not follow the Aristotelian rules of definition. Many definitions describe statistical properties of the category that are often useless in individual cases. A simple way is suggested that makes possible to represent such categories in biomedical ontologies and treat them separate from better formed categories. This makes possible to revise these categories at any later stage of ontology development.

Restructuring the foundational model of anatomy.

The authors present a method to convert the FMA to a description logic-based representation in OWL. The concepts denoting anatomical structures are aligned to the DOLCE formal top-level ontology, and converted to a compact core ontology in the spirit of GALEN. The paper presents the identified problems in the FMA and the main aspects of the re-modelling.

A pilot ontological model of public health indicators.

UNLABELLED: There are various public health databases in the world aiming to provide data to compare health conditions in different countries. Their data sets are more or less overlapping but data from different databases and different countries are hard to compare due to different definitions and interpretations. Our aim was to create a core ontological model that is able to represent public health indicators. We assumed, that by such representation comparability and quality of data could be improved. METHOD: Three sets of indicators were taken, and a core ontology was built from information objects describing their top level entities. The Protégé ontology editor with RDF backend was used for building the ontology. The used indicator sets were the indicators of the Health for All Database of the World Health Organisation (HFA), the OECD Health Data, and the set of indicators proposed by the European Community Health Indicators (ECHI) European project. Then 19 indicators selected from HFA was represented using the core ontology. Strength and weaknesses of the descriptive capability of the model was studied. RESULT: The drafted core model seems to be useful in representing many of the public health indicators. In some cases it really helps improve comparability. However, some of the semantic details cannot be sufficiently expressed by the used ontology representation language. There is a need of merging other domain ontologies to represent indicators related to other domains, such as economy, social and environmental sciences.