Search Results (1,298)

COVID-19 vaccine hesitancy (VH), like attitudes towards other vaccines, is a critical global public health concern. Despite numerous studies covering psychological, sociodemographic, and other determinants of vaccine acceptance, resistance, and hesitance, few studies have reported these factors among students, particularly in politically unstable settings like Ukraine. This cross-sectional, descriptive, and quantitative study assesses hesitancy towards COVID-19 vaccines, utilizing the 5Cs Model. Among 936 respondents surveyed in 2023, 64% received at least one shot of the COVID-19 vaccine (acceptant), 11% were still considering getting vaccinated (hesitant), and 25% refused vaccination (resistant). Vaccination behavior is significantly associated with the 5Cs. Higher collective responsibility significantly increased acceptance and reduced resistance, while higher constraints lowered the chances of being either acceptant or resistant. Confidence protected against resistance. Complacency, counterintuitively, reduced odds of resistance, pointing to differences between passive hesitancy and active refusal. Male gender and sources of information and misinformation influenced confidence. Collective responsibility was positively associated with official sources and negatively with conspiracy beliefs. Complacency increased with official sources, while constraints and calculation were least explained by predictors. Practical barriers should be tackled through improved accessibility and fostering collective responsibility via targeted communication strategies. These findings provide actionable insights for policymakers, healthcare providers, and academic institutions to enhance vaccine uptake among university students, particularly in crisis settings. Full article

Background/Objectives: This retrospective multicenter study, conducted within the ORCHESTRA Project, investigated SARS-CoV-2 reinfections among 5777 healthcare workers (HCWs) from four University Hospitals (Modena, Verona, Padova and Trieste) in northern Italy, aiming to assess the risk of reinfection and its determinants, comparing the clinical characteristics of reinfections with those of first infections, and examining the impact of preventive measures and vaccination strategies. Methods: HCWs completed an online questionnaire between June and August 2022. The survey collected demographic, occupational, and clinical data, including information on first infections and reinfections. Statistical analyses were performed using SPSS 28.0, through bivariate and multivariate approaches. Results: Response rates were 41.8% for Modena, 39.5% for Verona, 17.9% for Padova, and 17.4% for Trieste. Among the respondents, 4.8% (n = 276) experienced 2 infections and 0.5% (n = 27) reported 3 infections, out of a total of 330 reinfection cases. Additionally, 43.0% (n = 2787) reported only one infection, while 51.5% were never infected. Reinfection rates increased across five study phases (based on the epidemiological context), likely due to the emergence of new SARS-CoV-2 variants. A booster vaccine dose significantly reduced reinfection risk. Higher reinfection risk was found among HCWs aged ≤30 years, those with chronic respiratory diseases, and those working in COVID-19 wards, particularly nurses and allied health professionals. Reinfections were associated with a lower frequency of symptoms both during the period of swab positivity and after a negative swab, as well as with a shorter duration of swab positivity. No significant differences in symptom duration were found between first infections and reinfections. Conclusions: Despite its limitations, the online questionnaire proved a useful tool. Natural infection and vaccination reduced both reinfection risk and symptom severity. Prior infections should be considered in planning vaccination schedules and prioritizing HCWs. Full article

Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus, whose 2020 outbreak was characterized as a pandemic by the World Health Organization. Restriction measures changed healthcare delivery, with telehealth providing a viable alternative throughout the pandemic. This study analyzed a telemedicine platform database with the goal of developing a diagnostic prediction model for COVID-19 patients. This is a longitudinal study of patients seen on the Conexa Saúde telemedicine platform in 2022. A multiple binary logistic regression model of controls (negative confirmation for COVID-19 or confirmation of other influenza-like illness) versus COVID-19 was developed to obtain an odds ratio (OR) and a 95% confidence interval (CI). In the final binary logistic regression model, six factors were considered significant: presence of rhinorrhea, ocular symptoms, abdominal pain, rhinosinusopathy, and wheezing/asthma and bronchospasm were more frequent in controls, thus indicating a greater chance of flu-like illnesses than COVID-19. The presence of tiredness and fatigue was three times more prevalent in COVID-19 cases (OR = 3.631; CI = 1.138–11.581; p-value = 0.029). Our findings suggest potential predictors associated with influenza-like illness and COVID-19 that may distinguish between these infections. Full article

Background: Telehealth is an essential component of modern healthcare, and it was especially relevant during the COVID-19 pandemic, but disparities in digital and technological literacy among health professionals may limit its equitable adoption and impact. Objective: This study seeks to validate an eight-item telehealth literacy survey among health professionals in Central–South Chile and to examine demographic and behavioral determinants of literacy levels, developing predictive models to identify key factors. Methods: In this cross-sectional study, 2182 health professionals from urban and rural centers in Central–South Chile completed the adapted survey along with questions on age, gender, nationality, and frequency of telehealth use. We assessed internal consistency (Cronbach’s α), explored factor structure via exploratory factor analysis (EFA), and tested associations using Pearson correlations, t-tests, one-way ANOVA, and both linear and multinomial logistic regressions. Results: The instrument demonstrated high reliability (Cronbach’s α = 0.92) and a two-factor structure explaining 65% of variance. Age negatively correlated with literacy (r = −0.26; p < 0.001), while the frequency of telehealth use showed a positive correlation (r = 0.26; p < 0.001). Female professionals and those in urban settings scored significantly higher on telehealth literacy (p = 0.005 and p < 0.001, respectively). The reduced multinomial model achieved moderate classification accuracy (51.65%) in distinguishing low, medium, and high literacy groups. Conclusions: The validated survey is a reliable tool for assessing telehealth literacy among health professionals in Chile. The findings highlight age, gender, and geographic disparities, and support targeted digital literacy interventions to promote equitable telehealth practice. Full article

Background: This study examined risk factors for syndrome novel coronavirus 2 virus (SARS-CoV-2) infection and self-reported adherence to infection prevention and control (IPC) measures among healthcare workers (HCWs) at a hospital in Thailand near the Myanmar border. Methods: From March to July 2022, HCWs aged ≥ 18 with COVID-19 exposure at Mae Sot General Hospital completed a questionnaire on IPC adherence, training, and COVID-19 knowledge. Nasopharyngeal samples were collected bi-weekly for SARS-CoV-2 testing. A mobile application was used for real-time monitoring of daily symptoms and exposure risks. Chi-square, Fisher’s exact tests, and log-binomial regression were performed to investigate association. Results: Out of 289 (96.3%) participants, 27 (9.9%) tested positive for SARS-CoV-2, with cough reported by 85.2% of cases. Nurse assistants (NAs) had a higher risk of infection (adjusted relative risk [aRR] 3.87; 95% CI: 0.96–15.6). Working in inpatient departments (aRR 2.37; 95% CI: 1.09–5.15) and COVID-19 wards (aRR 5.97; 95% CI: 1.32–26.9) was also associated with increased risk. While 81.7% reported consistent hand hygiene, 37% indicated inadequate IPC knowledge. Conclusions: HCWs, especially NAs and those in high-risk departments, should receive enhanced IPC training. Real-time digital monitoring tools can enhance data collection and HCW safety and are likely to be useful tools for supporting surveillance and data collection efforts. Full article

Background: The longitudinal RisCoin study investigated risk factors for COVID-19 vaccination failure among healthcare workers (HCWs) and patients with inflammatory bowel disease (IBD) at a University Hospital in Germany. Since the hospital served as the study sponsor and employer of the HCW, we implemented a custom mobile application. We aimed to evaluate the implementation, adherence, benefits, and limitations of this study’s app. Methods: The app allowed secure data collection through questionnaires, disseminated serological results, and managed bidirectional communication. Access was double-pseudonymized and irreversibly anonymized six months after enrollment. Download frequency, login events, and questionnaire submissions between October 2021 and December 2022 were analyzed. Multivariable logistic regression identified factors associated with app adherence. Results: Of the 3979 participants with app access, 3622 (91%) used the app; out of these, 1016 (28%) were “adherent users” (≥12 submitted questionnaires). App adherence significantly increased with age. Among HCW, adherent users were more likely to be non-smokers (p < 0.001), working as administrators or nursing staff vs. physicians (p < 0.001), vaccinated against influenza (p < 0.001), and had not travelled abroad in the past year (p < 0.001). IBD patients exposed to SARS-CoV-2 (p = 0.0133) and those with adverse events following the second COVID-19 vaccination (p = 0.0171) were more likely adherent app users. Despite technical issues causing dropout or non-adherence, the app served as a secure solution for cohort management and longitudinal data collection. Discussion: App-based cohort management enabled continuous data acquisition and individualized care while providing flexibility and anonymity for the study team and participants. App usability, technical issues, and cohort characteristics need to be thoroughly considered prior to implementation to optimize usage and adherence in clinical research. Full article

COVID-19 vaccine hesitancy in Pakistan is a barrier to optimal vaccine uptake and has been situated within a context of hesitancy towards other vaccines. A mixed-methods study was conducted during the initial COVID-19 vaccine roll-out in 2021 in four union councils in Peshawar, consisting of a cross-sectional survey, eight focus group discussions (FGDs) with community members and eight in-depth interviews with healthcare workers (HCWs) to assess perceptions toward vaccines. Multivariable logistic regression was used to assess factors associated with COVID-19 vaccine hesitancy. Of 400 survey participants, 57.3% were vaccine acceptant and 42.8% vaccine hesitant. Just over half (56.8%) perceived COVID-19 vaccines to be safe. Most (88%) reported trust in HCWs to provide accurate vaccine information. FGDs revealed that women received less information about the vaccine compared to men and cultural restrictions were barriers even for those willing to be vaccinated. Correlates of vaccine acceptance included male sex (aOR 2.25; 95% CI 1.29–3.91), age 50 years or greater (aOR 1.74; 95% CI 1.19–6.31), social network support (e.g., vaccine acceptance among an individual’s social network) in receiving COVID-19 vaccines (aOR 2.38; 95% CI 1.45–3.89), community concern about COVID-19 spread (aOR 2.84; 95% CI 1.73–4.66), and trust in HCWs to provide vaccine information (aOR 3.47; 95% CI 1.62–7.42). Future vaccine promotion should prioritize engaging community leaders, sharing transparent information, combatting misinformation and rumors, and implementing household-based interventions especially targeting the importance of vaccination among women and young people to increase uptake. Full article

Background and Objectives: COVID-19 may have long-term adverse effects on bone health, particularly in individuals aged ≥50 years with obesity or diabetes, who are predisposed to impaired bone quality. Materials and Methods: This retrospective cohort study used TriNetX data from 141 healthcare organizations across North America and Western Europe. Patients aged ≥50 years with overweight (body mass index 25–30 kg/m²), obesity (body mass index ≥ 30 kg/m²), or type 2 diabetes (T2DM) and COVID-19 (2019–2024) were propensity score-matched to non-COVID-19 controls. Exclusion criteria included prior overweight, obesity, diabetes, osteoporosis, T-score ≤ −2.5, Z score ≤ −2.0, fractures, pneumonia, tuberculosis, and cancer. Outcomes included new-onset osteoporosis, fragility fractures, and low T-scores (≤−2.5). Cox regression estimated hazard ratios (HRs); sensitivity analyses assessed lag effects (1–4 years). Results: Among 327,933 matched pairs, COVID-19 was linked to increased osteoporosis risk at 3 years (HR, 1.039; 95% CI, 1.003–1.077) and 6 years (HR, 1.095; 95% CI, 1.059–1.133). Sensitivity analysis showed rising risk with longer lag times: HRs were 1.212, 1.379, 1.563, and 1.884 at 1 to 4 years, respectively. Subgroup analyses confirmed consistent trends. Conclusions: COVID-19 is independently associated with elevated long-term osteoporosis risk in older adults with new-onset overweight, obesity, or T2DM, peaking at 4 years post-infection and persisting through 6 years. Full article

Introduction: Efficient communication and collaboration among local health departments (LHDs), healthcare organizations, governmental entities, and other community stakeholders are critical for public health preparedness and response. This study evaluates (1) the impact of informatics on LHDs’ frequency and collaboration in creating consistent COVID-19 messaging; (2) the influence of informatics on targeted messaging for vulnerable populations; and (3) LHD characteristics linked to their consistent and/or targeted messaging engagement. Methods: This study analyzed the 2020 National Association of County and City Health Officials (NACCHO) Forces of Change (FOC) survey, the COVID-19 Edition. Of the 2390 LHDs invited to complete the core questionnaire, 905 were asked to fill out the module questionnaire as well. The response rate for the core was 24% with 587 responses, while the module received 237 responses, achieving a 26% response rate. Descriptive analyses and six logistic regression models were utilized. Results: Over 80% (183) of LHDs collaborated regularly with public health partners, and 95% (222) used information management applications for COVID-19. Most interacted with local and state agencies, but only half with federal ones. LHDs that exchanged data with local non-health agencies, engaged with local non-health agencies, and communicated weekly to daily with the public about long-term/assisted care had higher odds of creating consistent messages for the public, and about the use and reuse of masks had lower odds of collaborating with public health partners to develop consistent messages for the public. Conclusion: Our findings underscore the centrality of informatics infrastructure and collaboration in ensuring equitable public health messaging. Strengthening public health agencies and investing in targeted training are crucial for effective communication across the communities served by these agencies. Full article

The colonization of Legionella spp. in engineered water systems constitutes a major public health threat. In this study, a six-year environmental surveillance (2020–2025) of Legionella colonization in five different types of facilities in Crete, Greece is presented, including hotels, passenger ships, primary healthcare facilities, public hospitals, and private clinics. A total of 1081 water samples were collected and analyzed, and the overall positivity was calculated using culture-based methods. Only 16.46% of the samples exceeded the regulatory limit (>10³ CFU/L) in the total sample, with 44.59% overall Legionella positivity. Colonization by facility category showed the highest rates in primary healthcare facilities with 85.96%, followed by public hospitals (46.36%), passenger ships with 36.93%, hotels with 38.08%, and finally private clinics (21.42%). The association of environmental risk factors with Legionella positivity revealed a strong effect at hot water temperatures < 50 °C (RR = 2.05) and free chlorine residuals < 0.2 mg/L (RR = 2.22) (p < 0.0001). Serotyping analysis revealed the overall dominance of Serogroups 2–15 of L. pneumophila; nevertheless, Serogroup 1 was particularly prevalent in hospitals, passenger ships, and hotels. Based on these findings, the requirement for continuous environmental monitoring and risk management plans with preventive thermochemical controls tailored to each facility is highlighted. Finally, operational disruptions, such as those experienced during the COVID-19 pandemic, especially in primary care facilities and marine systems, require special attention. Full article

Background/Objectives: Postoperative acute respiratory distress syndrome (ARDS) is a recognized complication with reported prevalence rates of up to 20% and highly variable mortality. However, there is limited published evidence comparing the outcomes of postoperative ARDS with those of medical ARDS. We aimed to evaluate the prevalence, hospital mortality, and healthcare costs of postoperative ARDS in Spain between 2000 and 2022 and to compare them with those of medical ARDS. Methods: We performed a nationwide, registry-based study of all hospitalizations for postoperative ARDS in Spain between 1 January 2000 and 31 December 2022 using the Minimum Basic Data Set (MBDS) Registry. Results: We identified a total of 93,192 ARDS patients, of which 40,601 had postoperative ARDS. The postoperative ARDS prevalence varied between 0.05 and 0.22%, accounting for 45–50% of total ARDS cases recorded during the study period. Hospital mortality was lower in postoperative ARDS compared with medical ARDS during the first phase (2000–2015) (47.0% vs. 49.9%, p < 0.001) and converged during the second phase (2017–2022) (42.7% vs. 43.2%, p = 0.413). Postoperative ARDS was associated with a longer hospital stay and 1.5 times higher healthcare costs compared with medical ARDS. During the COVID-19 pandemic, mortality rates declined but costs peaked in both groups. The incidence of digestive tract infection was higher in postoperative ARDS. Conclusions: The prevalence of postoperative ARDS remained stable, except during the COVID-19 pandemic, and its hospital mortality declined and equalized with that of medical ARDS. However, the costs associated with postoperative ARDS remained significantly higher. Full article

Background/Objective: Frontline healthcare staff who contend diseases and mitigate their transmission were repeatedly exposed to high-risk conditions during the COVID-19 pandemic. They were at risk of mental health issues, in particular, psychological stress, depression, anxiety, financial stress, and/or burnout. This study aimed to investigate and evaluate the occupational stress of medical doctors, nurses, pharmacists, physiotherapists, and other hospital support crew during the COVID-19 pandemic in Saudi Arabia. Methods: We collected both qualitative and quantitative data from a survey given to public and private hospitals using methods like correspondence analysis, cluster analysis, and structural equation models to investigate the work-related stress (WRS) and anxiety of the staff. Since health-related factors are unclear and uncertain, a fuzzy association rule mining (FARM) method was created to address these problems and find out the levels of work-related stress (WRS) and anxiety. The statistical results and K-means clustering method were used to find the best number of fuzzy rules and the level of fuzziness in clusters to create the FARM approach and to predict the work-related stress and anxiety of healthcare staff. This innovative approach allows for a more nuanced appraisal of the factors contributing to work-related stress and anxiety, ultimately enabling healthcare organizations to implement targeted interventions. By leveraging these insights, management can foster a healthier work environment that supports staff well-being and enhances overall productivity. This study also aimed to identify the relevant health factors that are the root causes of work-related stress and anxiety to facilitate better preparation and motivation of the staff for reorganizing resources and equipment. Results: The results and findings show that when the financial burden (FIN) of healthcare staff increased, WRS and anxiety increased. Similarly, a rise in psychological stress caused an increase in WRS and anxiety. The psychological impact (PCG) ratio and financial impact (FIN) were the most influential factors for the staff’s anxiety. The FARM results and findings revealed that improving the financial situation of healthcare staff alone was not sufficient during the COVID-19 pandemic. Conclusions: This study found that while the impact of PCG was significant, its combined effect with FIN was more influential on staff’s work-related stress and anxiety. This difference was due to the mutual effects of PCG and FIN on the staff’s motivation. The findings will help healthcare managers make decisions to reduce or eliminate the WRS and anxiety experienced by healthcare staff in the future. Full article

Background: Myocarditis and pericarditis are recognised risks following COVID-19 vaccination, including the mRNA-1273 vaccine. Most cases occur shortly following the second dose of this vaccine, and incidence is highest among young males. However, little is known about risk factors beyond age and sex and about the longer-term clinical course. This study aims to identify possible risk factors for myocarditis and pericarditis following mRNA-1273 vaccination, to characterise the clinical course of myocarditis and pericarditis, both associated with mRNA-1273 vaccination and not associated with vaccination, and to identify risk factors for severe outcomes (i.e., cardiac or thromboembolic complications, severe hospital outcomes, all-cause hospital readmission, and death). Methods: This study is being conducted within the Vaccine Monitoring Collaboration for Europe (VAC4EU) association using routinely collected healthcare data from five data sources from four European countries (Denmark, Norway, Spain, and the United Kingdom). The study is being performed using a common data model, and all analyses are performed separately in each data source in a federated manner following a common protocol. A case–cohort analysis set is identified within each data source for identifying potential risk factors for myocarditis and pericarditis following mRNA-1273 vaccination using logistic regression analysis. The clinical course of myocarditis and pericarditis is being assessed using a cohort study design and describes all cases (i.e., cases associated with mRNA-1273 and unexposed cases). Cox regression analysis is applied to assess the associations between risk factors and several follow-up outcomes. Conclusions: This protocol describes the study methodology of an international collaborative initiative with the aim of assessing the risk factors and clinical course of myocarditis and pericarditis following mRNA-1273 vaccination using a federated network of five European data sources. Full article

In recent years, the open data initiative has led to the willingness of many governments, researchers, and organizations to share their data and make it publicly available. Healthcare, disease, and epidemiological data, such as privacy statistics on patients who have suffered from epidemic diseases such as the Coronavirus disease 2019 (COVID-19), are examples of open big data. Therefore, huge volumes of valuable data have been generated and collected at high speed from a wide variety of rich data sources. Analyzing these open big data can be of social benefit. For example, people gain a better understanding of disease by analyzing and mining disease statistics, which can inspire them to participate in disease prevention, detection, control, and combat. Visual representation further improves data understanding and corresponding results for analysis and mining, as a picture is worth a thousand words. In this paper, we present a visual data science solution for the visualization and visual analysis of large sequence data. These ideas are illustrated by the visualization and visual analysis of sequences of real epidemiological data of COVID-19. Through our solution, we enable users to visualize the epidemiological data of COVID-19 over time. It also allows people to visually analyze data and discover relationships between popular features associated with COVID-19 cases. The effectiveness of our visual data science solution in improving the user experience of visualization and visual analysis of large sequence data is demonstrated by the real-life evaluation of these sequenced epidemiological data of COVID-19. Full article

Background: Bacterial infections are frequent complications in critically ill COVID-19 patients, and are associated with increased morbidity, antibiotic use, and healthcare burden. Early and accurate identification of infection remains challenging. Pancreatic Stone Protein (PSP) has emerged as a promising biomarker of infection. In this study, PSP was evaluated alongside C-reactive protein (CRP). Methods: We conducted a prospective study including 105 critically ill COVID-19 patients admitted to the intensive care unit (ICU). Blood samples were collected at admission to measure PSP and CRP. A LASSO Least Absolute Shrinkage and Selection Operator (LASSO) regression model was used to identify independent predictors of proven or suspected bacterial infection. Mixed-effects models were applied to account for repeated measures and clinical confounders. Results: Among 105 patients, 57 (54%) developed bacterial infections. PSP levels were significantly higher in infected patients (median 100 ng/mL) than in non-infected patients (median 37 ng/mL, p < 0.001). CRP was also elevated in infected patients (median 125 vs. 70 mg/L, p = 0.015). The LASSO model retained PSP as the most informative predictor. In mixed-effects logistic regression, PSP remained significantly associated with infection (OR 1.017, 95% CI 1.006–1.027, p = 0.001). The AUC for PSP was 0.87. Conclusion: PSP appears to be a useful biomarker for early detection of bacterial infection in critically ill COVID-19 patients. Its integration into infection surveillance protocols could support antibiotic stewardship efforts and improve clinical decision-making. Full article