Detection and Molecular Characterization of Rotavirus Infections in Children and Adults with Gastroenteritis from Vojvodina, Serbia.

Rotaviruses (RV) are the leading cause of gastroenteritis in infants, young children, and adults, responsible for serious disease burden. In the period 2012-2018, a cross-sectional study was conducted using stool samples collected from patients with acute gastroenteritis from Vojvodina, Serbia. We described age and gender distribution, as well as seasonal patterns of RV prevalence. Out of 1853 included stool samples, RV was detected in 29%. Hospitalized children between 1-2 years old were especially affected by RV infection (45%). The highest prevalence of infection was observed during the colder, winter/spring months. We compared sequenced representative G and P genotypes circulating in Serbia with vaccine strains and determined their genetic similarity. Genotype combination G2P[4] was the most prevalent (34.6%), followed by G2P[8] (24.1%) and G1P[8] (21.1%). Given that several epitopes were conserved, neutralization motifs among circulating strains can be characterized as sufficiently matching vaccine strains Rotarix™ and RotaTeq™, but existing antigenic disparities should not be overlooked. The present results contribute to a better insight into the prevalence of rotavirus infection in our region and point out the need for epidemiological surveillance of rotaviruses before the introduction of vaccines. These data can help formulate future vaccine strategies in Serbia.

Predicting 30-Day Readmission Risk for Patients With Chronic Obstructive Pulmonary Disease Through a Federated Machine Learning Architecture on Findable, Accessible, Interoperable, and Reusable (FAIR) Data: Development and Validation Study.

BACKGROUND: Owing to the nature of health data, their sharing and reuse for research are limited by legal, technical, and ethical implications. In this sense, to address that challenge and facilitate and promote the discovery of scientific knowledge, the Findable, Accessible, Interoperable, and Reusable (FAIR) principles help organizations to share research data in a secure, appropriate, and useful way for other researchers. OBJECTIVE: The objective of this study was the FAIRification of existing health research data sets and applying a federated machine learning architecture on top of the FAIRified data sets of different health research performing organizations. The entire FAIR4Health solution was validated through the assessment of a federated model for real-time prediction of 30-day readmission risk in patients with chronic obstructive pulmonary disease (COPD). METHODS: The application of the FAIR principles on health research data sets in 3 different health care settings enabled a retrospective multicenter study for the development of specific federated machine learning models for the early prediction of 30-day readmission risk in patients with COPD. This predictive model was generated upon the FAIR4Health platform. Finally, an observational prospective study with 30 days follow-up was conducted in 2 health care centers from different countries. The same inclusion and exclusion criteria were used in both retrospective and prospective studies. RESULTS: Clinical validation was demonstrated through the implementation of federated machine learning models on top of the FAIRified data sets from different health research performing organizations. The federated model for predicting the 30-day hospital readmission risk was trained using retrospective data from 4.944 patients with COPD. The assessment of the predictive model was performed using the data of 100 recruited (22 from Spain and 78 from Serbia) out of 2070 observed (records viewed) patients during the observational prospective study, which was executed from April 2021 to September 2021. Significant accuracy (0.98) and precision (0.25) of the predictive model generated upon the FAIR4Health platform were observed. Therefore, the generated prediction of 30-day readmission risk was confirmed in 87% (87/100) of cases. CONCLUSIONS: Implementing a FAIR data policy in health research performing organizations to facilitate data sharing and reuse is relevant and needed, following the discovery, access, integration, and analysis of health research data. The FAIR4Health project proposes a technological solution in the health domain to facilitate alignment with the FAIR principles.

FAIR4Health: Findable, Accessible, Interoperable and Reusable data to foster Health Research.

Due to the nature of health data, its sharing and reuse for research are limited by ethical, legal and technical barriers. The FAIR4Health project facilitated and promoted the application of FAIR principles in health research data, derived from the publicly funded health research initiatives to make them Findable, Accessible, Interoperable, and Reusable (FAIR). To confirm the feasibility of the FAIR4Health solution, we performed two pathfinder case studies to carry out federated machine learning algorithms on FAIRified datasets from five health research organizations. The case studies demonstrated the potential impact of the developed FAIR4Health solution on health outcomes and social care research. Finally, we promoted the FAIRified data to share and reuse in the European Union Health Research community, defining an effective EU-wide strategy for the use of FAIR principles in health research and preparing the ground for a roadmap for health research institutions. This scientific report presents a general overview of the FAIR4Health solution: from the FAIRification workflow design to translate raw data/metadata to FAIR data/metadata in the health research domain to the FAIR4Health demonstrators' performance.

Sero-epidemiological study in prediction of the risk groups for measles outbreaks in Vojvodina, Serbia.

BACKGROUND: Age-stratified serologic surveys provide insight into the gaps of measles-specific immunity as well as estimates of the age-specific seroprevalence. The aim of this study was to describe the measles sero-epidemiology in Vojvodina before the occurrence of outbreak in 2017/18 and to discuss preventive measures for potential future epidemics. METHODS: A seroprevalence study was conducted from April 2015 to June 2017 on serum bank of 3199 residual samples. Study was performed prior to the last measles outbreak in Vojvodina that occurred between 12th November 2017 and 30th June 2018. Measles-specific IgG antibodies were determined using an indirect chemiluminescent immunoassay (CLIA). RESULTS: Median age of enrolled participants was 20 years (IQR 11-37). Overall, 86.9% serum samples were seropositive. The highest proportion of measles seronegativity was observed in children aged 12-23 months of age and in adults aged 20-39 years (56.1% and 18.5%, respectively). Prevalence of measles seronegativity above WHO target levels susceptibility was observed in the following age groups: 2, 7, 13, 15, and among all adults aged between 20 and 49 years. Out of total measles outbreak cases (177), there were 91 (51.4%) participants aged 20-39 years. A significant positive correlation was observed between measles seronegativity and the number of reported measles cases aged ≥ 12 months (r = 0.4675, p = 0.0213). CONCLUSIONS: In order to prevent new outbreaks and achieve the elimination of measles in Vojvodina, the vaccination coverage of both measles-mumps-rubella (MMR1 and MMR2) vaccines needs to be improved and sustained. Educational campaigns for the improvement of acceptance and timely vaccination with vaccine against measles among doctors and the general population are crucial. Our results indicate possible gap in measles protection in adults born during implementation of one dose of measles vaccine and prioritize supplementary immunization activities targeting adults in Vojvodina, Serbia.

Streptococcus pneumoniae serotype distribution in Vojvodina before the introduction of pneumococcal conjugate vaccines into the National Immunization Program.

Introduction: Streptococcus pneumoniae is the most common causative agent of bacterial pneumonia and meningitis. Mandatory childhood immunization against pneumococcal diseases is introduced in the new Law on Protection of Population against Communicable Diseases in Serbia. Objective: The objective of this study was to determine the prevalence of pneumococcal serotype distribution in Vojvodina region before routine use of pneumococcal conjugate vaccine in Serbia. Methods: A total of 105 isolates of Streptococcus pneumoniae were collected in the period from January 2009 to April 2016. Based on the results of serotyping in the National Reference Laboratory, we analyzed distribution of circulating serotypes and coverage of conjugate and 23-valent polysaccharide pneumococcal vaccines in different age groups. Results: Among 105 isolates, a total of 21 different serotypes of Streptococcus pneumoniae were determined. The most frequent serotypes were 3 (21.9%), 19F (20.0%), and 14 (10.5%). The serotype coverage of pneumococcal conjugate vaccines (PCV7, PCV10, and PCV13) was 48.6%, 54.3%, and 84.8%, respectively, while pneumococcal polysaccharide vaccine (PPV23) covered 89.5% of the total number of isolates in all age groups. Serotypes included in PCV7, PCV10, and PCV13 represented 72.0%, 76.0%, and 88.0% of the total number of isolates in children ≤5 years, respectively. Vaccine serotype coverage of PCV13 and PPV23 ranged from 87.1% to 90.3% in adults 50­64 years of age, and 77.8% to 85.2% in adults ≥65 years old. Conclusion: Serotype distribution of Streptococcus pneumoniae in the population fairly overlaps with the serotypes contained in pneumococcal vaccines, so that implementation of childhood immunization is justified. The study was done in the Province of Vojvodina but the findings may be applied to Serbia as a whole.