Foodborne diseases in food facilities are a major public health problem, due mostly to the limited surveillance and educational level of food-handling workers. This study was conducted in 220 food service locations in Montenegro. Participants’ behaviour was assessed by a survey using the specifically designed structured questionnaire, administered before and after the training. To determine the effect of the training on the performance of food handlers, a microbiological analysis of food contact surfaces and food handlers’ hands was also performed. The behaviour of food handlers, viewed as a whole, is unacceptable. There was a statistically significant difference (<0.05) among participants who completed catering school compared with those who did not, regarding hand washing. The type of facility in which participants worked (restaurant, bakery, or pastry shop) revealed statistically significant differences (<0.05) in relation to hand washing, that is, restaurant employees had better habits than those from bakeries and pastry shops. Before the training, participants showed acceptable behaviour regarding hand hygiene, but it was much better after the training. Results of microbiological analyses of food contact surfaces and food handlers’ hands indicated better results after the education, especially with regard to hand swabs. The results of this study indicate the importance of education to improve food handling practices among food handlers, which might also decrease the possibilities for contamination of food.

ObjectivesOur study described how the WHO intra-action review (IAR) methodology was operationalised and customised in three Western Balkan countries and territories and the Republic of Moldova and analysed the common key findings to inform analyses of the lessons learnt from the pandemic response.DesignWe extracted data from the respective IAR reports and performed a qualitative thematic content analysis to identify common (between countries and territories) and cross-cutting (across the response pillars) themes on best practices, challenges and priority actions. The analysis involved three stages, namely: extraction of data, initial identification of emerging themes and review and definition of the themes.SettingIARs were conducted in the Republic of Moldova, Montenegro, Kosovo and the Republic of North Macedonia between December 2020 and November 2021. The IARs were conducted at different time points relative to the respective pandemic trajectories (14-day incidence rate ranging from 23 to 495 per 100 000).ResultsCase management was reviewed in all the IARs, while the infection prevention and control, surveillance and country-level coordination pillars were reviewed in three countries. The thematic content analysis identified four common and cross-cutting best practices, seven challenges and six priority recommendations. Recommendations included investing in sustainable human resources and technical capacities developed during the pandemic, providing continuous capacity-building and training (with regular simulation exercises), updating legislation, improving communication between healthcare providers at all levels of healthcare and enhancing digitalisation of health information systems.ConclusionsThe IARs provided an opportunity for continuous collective reflection and learning with multisectoral engagement. They also offered an opportunity to review public health emergency preparedness and response functions in general, thereby contributing to generic health systems strengthening and resilience beyond COVID-19. However, success in strengthening the response and preparedness requires leadership and resource allocation, prioritisation and commitment by the countries and territories themselves.

Background: Comorbidities are major predictors of in-hospital mortality in stroke patients. The Charlson comorbidity index (CCI) and the Elikhauser comorbidity index (ECI) are scoring systems for classifying comorbidities. We aimed to compare the performance of the CCI and ECI to predict in-hospital mortality in stroke patients. Methods: We included patients hospitalized for stroke in the Clinical Center of Kragujevac, Serbia for the last 7 years. Hospitalizations caused by stroke, were identified by the International Classification of Diseases-10 (ICD-10) codes I60.0 - I69.9. All patients were divided into two cohorts: Alive cohort (n=3297) and Mortality cohort (n=978). Results: There were significant associations between higher CCIS and increased risk of in-hospital mortality (HR = 1.07, 95% CI = 1.01–1.12) and between higher ECIS and increased risk of in-hospital mortality (HR = 1.04, 95% CI = 0.99–1.09). Almost 2/3 patients (66.9%) had comorbidities included in the CCI score and 1/3 patients (30.2%) had comorbidities included in the ECI score. The statistically significant higher CCI score (t = -3.88, df = 1017.96, P <0.01) and ECI score (t = -6.7, df = 1447.32, P <0.01) was in the mortality cohort. Area Under the Curve for ECI score was 0.606 and for CCI score was 0.549. Conclusion: Both, the CCI and the ECI can be used as scoring systems for classifying comorbidities in the administrative databases, but the model’s ECI Score had a better discriminative performance of in-hospital mortality in the stroke patients than the CCI Score model.

Introduction/Objective. At the end of 2021, Omicron wave (B.1.1.529) SARS-CoV-2 variant superseded the Delta variant (B.1.617). The main goal of the research is to provide a detailed and comprehensive presentation of data related to people infected with the coronavirus in Montenegro. The specific goal of the research is to determine whether virus mutations influenced the course of the epidemic during its two-year duration. Methods. This is a retrospective study. We used data from the Institute of Public Health of Montenegro. Our sample consisted of 127 134 people who tested positive for Delta or Omicron infection aged 0-100 years, who had a positive PCR test for Covid-19 between August 17 2021 and April 17 2022. Results. The respondents aged 40 to 49 years were taken as a reference group for age. The results showed that the age group from 20 to 29 years old was affected 1.03 times more than the reference group - persons belonging to the age group of 30 to 39 years were affected 1.07 times more than the reference group. The Central region was taken as the reference group for the region. The results showed that people who live in southern region got sick 1.14 times more often and people who live in northern region got sick 1.20 times less than people from the central region. Conclusion. The biggest predictor that a person would get sick is the age group. Also, the predictor is the region, and in our research, it was southern region.

No abstract