COVID, Volume 5, Issue 7 (July 2025) – 16 articles

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

Background: The COVID-19 pandemic progressed unevenly across the 417 municipalities of Bahia, Brazil. Pinpointing where and when risk peaked is vital for preparing for future emergencies. Methods: We performed an ecological, spatiotemporal study using COVID-19-confirmed cases in Bahia, Brazil, from January 2020 to December 2022. A discrete Poisson space–time scan in SaTScan-identified clusters. For each cluster, we calculated relative risk (RR) and Log Likelihood Ratio, considering p < 0.05 as significant. Results: A total of 33 clusters were detected; 25 statistically significant. The largest cluster (164 municipalities; May 2020–June 2021) comprised 702,720 observed versus 338,822 expected cases (RR = 2.8). Two overlapping large clusters (185 and 136 municipalities) during January–February 2022—coinciding with Omicron circulation—showed RR > 2.0. Localized clusters reached RR > 3.0. Spatially, risk concentrated in the south, southwest, and east of the state, with isolated countryside outbreaks. Conclusions: The heterogeneous spatiotemporal dynamics of COVID-19 in Bahia underscore the value of cluster detection for targeted surveillance and resource allocation. We recommend employing statistical techniques for early detection and control, as well as conducting further studies on socioeconomic and behavioral factors. Full article

(1) Background: The ongoing global health threat posed by SARS-CoV-2 requires reliable and accessible diagnostic tools, especially in resource-limited settings where RT-qPCR may be impractical. This study describes the development and validation of two enzyme-linked immunosorbent assays (ELISA) designed to detect anti-SARS-CoV-2 IgG antibodies employing recombinant S1 and S2 spike protein subunits. (2) Methods: The assays were optimized and validated using serum samples from 354 RT-qPCR-confirmed hospitalized patients and 337 pre-pandemic blood donors. (3) Results: The S1-based ELISA achieved a 52.8% sensitivity and a specificity of 93.5%, with an area under the ROC curve (AUC) of 71.6%. In contrast, the S2-based ELISA demonstrated superior diagnostic performance, with a sensitivity of 63.7%, a specificity of 99.7%, and an AUC of 83.1%. Cross-reactivity analysis using sera from individuals with unrelated infectious diseases confirmed the high specificity of the S2-ELISA. Time-stratified analysis revealed that sensitivity increased with time, peaking between 15 and 21 days post-symptom onset. Compared to commercial serological assays, the S2-ELISA demonstrated comparable or improved performance, particularly in specificity and diagnostic odds ratio. (4) Conclusions: The S2-ELISA offers a robust, highly specific, and operationally simple tool for serological detection of SARS-CoV-2 infection. Its strong diagnostic performance and accessibility make it well-suited for implementation in diverse epidemiological settings, particularly where molecular testing is limited. The development of affordable, validated serological assays such as this is critical for strengthening surveillance, understanding transmission dynamics, and informing public health responses. Full article

Objective: This study aims to investigate the feasibility of an online music therapy protocol for individuals previously diagnosed with COVID-19, focusing on their perceptions of their respiratory symptoms and the intervention’s impact on psychosocial measures. Methods: A within-subject experimental design was applied to examine an eight-week weekly online music therapy protocol, including singing, wind instrument playing, and music visualizations. All self-report data were collected bi-weekly throughout the 16-weeks study period, including baseline and post-tests. The measures for respiratory symptoms included the Medical Research Council’s Dyspnea Scale (MRC Dyspnea), Chronic Respiratory Questionnaire-Mastery Scores (CRQ Mastery), and Visual Analogue Scale for breathlessness. The measures for the secondary psychosocial outcomes were the Beck Depression Inventory-Short Form, the Generalized Anxiety Disorder 7-item, the Hospital Anxiety and Depression Scale, the Fatigue Severity Scale, the Epworth Sleepiness Scale, the EuroQol 5-Dimension 5-Level, and the Connor-Davidson Resilience Scale. Results: Twenty-four participants were enrolled. The participants perceived a reduction in respiratory symptoms, and shortness of breath (MRC Dyspnea). Planned comparisons showed significant decreases in MRC from baseline to post-treatment (p = 0.008). The mixed-effects model, including pre-baseline and post-treatment, was significant (p < 0.001). Significant changes in Breathing VAS were consistent with improvements in MRC Dyspnea, showing a significant baseline-to-post difference (p = 0.01). The CRQ Mastery showed significant improvements from baseline to Week 12 (p < 0.001). No significant changes were observed in other secondary measures. Conclusions: Our preliminary findings suggest that this protocol is feasible, and as a result, may help individuals previously diagnosed with COVID-19 to cope with lasting respiratory symptoms and improve their perception of shortness of breath. Live music-making, including playing accessible wind instruments and singing, may contribute to an increase sense of control over breathing. As this was a feasibility study, we conducted multiple uncorrected statistical comparisons to explore potential effects. While this approach may increase the risk of Type I error, the findings are intended to inform hypotheses for future confirmatory studies rather than to draw definitive conclusions. Full article

Background: Breakthrough infections (BTIs) continue to occur among healthcare workers (HCWs) despite full COVID-19 vaccination, raising concerns about ongoing vulnerability in this high-risk group. In addition to initial BTIs, breakthrough reinfections (BTRs) have emerged as a challenge, with some HCWs experiencing multiple episodes of infection after vaccination. This study investigated the factors influencing breakthrough infection and reinfection rates among HCWs between January 2021 and December 2022 in Davao City, Philippines. Methods: This retrospective cohort study was conducted using secondary data from the Davao City Epidemiological Surveillance Unit, approved by the Department of Health. This study included 1011 fully vaccinated HCWs from various congressional districts. Results: BTI was observed in all HCWs included in the study. However, BTRs varied across occupational groups: medical technologists showed the highest reinfection rate (22.37%), followed by physicians (13.48%), and nurses/nurse aides (10.14%). Booster vaccination significantly reduced BTRs (5.83% vs. 11.18%, p = 0.0267). Occupation and institutional type were significant factors, with higher rates reported by physicians and in public hospitals (p = 0.0002 and p = 0.0041, respectively). The vaccine manufacturer, sex, age, and booster type showed no significant differences. Conclusion: These findings highlight the importance of targeted interventions for high-risk HCWs and emphasize the effectiveness of the booster vaccination. Full article

Severe COVID-19 disproportionately impacts patients with comorbidities such as type 1 diabetes (T1D), type 2 diabetes (T2D), obesity (OBCD), cardiovascular disease (CVD), hypertension (HTN), and cerebrovascular disease (CeVD), affecting 10–30% of cases. This study elucidates shared molecular mechanisms by identifying common hub genes and genetic variants across these conditions using an integrative bioinformatics approach. We curated 5463 COVID-19-related genes from DisGeNET, GeneCards, T-HOD, and other databases, comparing them with gene sets for T1D (324 genes), T2D (497), OBCD (835), CVD (1756), HTN (837), and CeVD (1421). Functional similarity analysis via ToppGene, hub gene prediction with cytoHubba, and Cytoscape-based protein–protein interaction networks identified four hub genes—CCL2, IL6, IL10, and TLR4—consistently shared across all conditions (p < 1.0 × 10⁻⁵). Enrichr-based gene ontology and KEGG analyses revealed cytokine signaling and inflammation as key drivers of COVID-19 cytokine storms. Polymorphisms like IL6 rs1800795 and TLR4 rs4986790 contribute to immune dysregulation, consistent with previous genomic studies. These genes suggest therapeutic targets, such as tocilizumab for IL6-driven inflammation. While computational, requiring biochemical validation, this study illuminates shared pathways, advancing prospects for precision medicine and multi-omics research in high-risk COVID-19 populations. Full article

COVID-19 continues to spread six years after its discovery. Cancer patients are at an increased risk of severe outcomes, likely due to immunosuppression and tumor-related dysregulation. Programmed cell death protein 1 (PD-1), encoded by the PDCD1 gene, is a critical immune checkpoint involved in T-cell regulation. Since genetic polymorphisms can influence immune responses and individual susceptibility to SARS-CoV-2 infection, this case–control study aimed to investigate the association between the PDCD1 rs41386349 polymorphism and COVID-19 severity in individuals with and without cancer. This study included 279 COVID-19-positive and 160 negative individuals, genotyped by qPCR. COVID-19- positive cancer patients were significantly more likely to develop moderate (OR = 13.6) and severe (OR > 200) disease compared to cancer-negative individuals. No association was observed between the PDCD1 polymorphism and SARS-CoV-2 infection or disease severity, even after adjusting for cancer status, age and sex. However, age and sex were independently associated with severe outcomes: each additional year of age increased the odds of severe disease by 5.3%, and male patients had a three times higher risk of severe COVID-19. These findings confirm that cancer, male sex and older age are major predictors of worse prognosis in COVID-19, while the rs41386349 polymorphism alone does not appear to influence susceptibility or disease progression. Full article

Introduction: COVID-19 and influenza are viruses that have been major causes of morbidity and mortality worldwide. While a combination vaccine for these two viruses is currently in development, little is known about public perceptions and attitudes towards such a vaccine. Therefore, we have aimed to conduct a scoping review to evaluate the attitudes and reasons for the acceptance/rejection of a combination COVID-19 and influenza vaccination. Material and Methods: Our review has followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR) guidelines. Search terms included those on COVID-19, influenza, and combination vaccines. Searches were conducted in a total of 10 different databases, as follows: Embase, Global Health, Google Scholar, CINAHL, Medline, Scopus, ScienceDirect, PubMed, PsycINFO, and Web of Science. Results: Searches across all databases produced a total of 1763 results, of which five studies were deemed to be eligible for this review. Data from included studies encompassed a total of 20,581 participants across 14 countries. Generally, participants had favorable views towards a combination vaccine. However, attitudes varied by region, demographics, and prior vaccine exposure. Reasons provided for accepting a combination vaccine include low cost, reasonable effectiveness, fewer injections, and higher safety. However, reasons for rejection of a potential combination vaccine include a potential lack of evidence and studies regarding its effectiveness and a fear of possible side effects. Conclusions: There are generally positive attitudes and perceptions towards a combination vaccination for COVID-19 and influenza, and there are also specific segments of populations that may show hesitancy towards such a vaccine. Vaccination delivery programs should clearly demonstrate that these vaccines are safe and must concurrently address false rumors and misinformation. Ensuring that as many people as possible can receive the vaccination without barriers via equity in access should be a public health priority. It is also important to recognize the limitations of this work, especially that the review was limited to five studies, the majority of which were cross-sectional and relied on self-reporting. Full article

The COVID-19 pandemic caused immense physical disruptions, affecting young adults in the U.S. The Health Belief Model is a social psychological framework that predicts the likelihood of adopting health behavior. The purpose of this research is to investigate COVID-19-related health beliefs and dietary behaviors among undergraduate students during the pandemic. Using convenience sampling, a cross-sectional survey was completed by 304 individuals at a New Jersey state university. Survey data included the frequency of COVID-19 prevention behaviors (e.g., wearing an indoor mask, handwashing), and consumption of fruit and vegetables. The Health Belief Model constructs measured perceived susceptibility to COVID-19, severity, benefits, barriers, and self-efficacy. Frequency distributions, t-tests, and Kruskal–Wallis tests were investigated for racial subgroups (Whites, Blacks, Latinos, and Asians). The mean age of the sample was 21.7, with 27% males, and 46% self-identified as White. Whites adopted fewer COVID-19 prevention behaviors (p < 0.001) than non-Whites. Black students perceived less COVID-19 severity (p < 0.01) and stronger perceived benefits (p < 0.05) than the other subgroups. Latino students perceived greater susceptibility (p < 0.01) and greater barriers than non-Latinos. Asians practiced higher mask wearing frequency (p < 0.05) but less daily fruit intake than their counterparts (p < 0.01). This research highlights the importance of handwashing, wearing indoor masks, and consuming produce among university students. Addressing barriers to health action while promoting the benefits of enacting behaviors to mitigate the risk of COVID-19 is warranted. Full article

The COVID-19 pandemic sparked changes globally, as leaders scrambled to protect wellbeing and safety. With many U.S. students sent away from their campuses, undergraduate students still grappled with the time-old question: “what will I do after college,” except during an unprecedented time in history rife with heightened career uncertainty. This qualitative study presents the results of a survey administered as part of a mind–body health project conducted in the wake of the pandemic, speaking directly to undergraduate college students’ health-related career aspirations. Two open-ended survey questions—(1) what is your intended career, and (2) how (if at all) has the COVID-19 pandemic changed your perspective about your future career—were administered with thematic analysis conducted. Qualitative analysis using hybrid data and theory-driven approaches revealed several themes around an increased desire to work within health-related fields, decreased desire to work in healthcare, non-medical to medical career shift, and additional undecidedness. Connecting theory to practice, Super’s Life-Space, Life-Span Career Theory and Krumboltz’s Social Learning Theory of Career Decision-Making guide practical implications and grander discussion around career development during periods of crisis. Full article

The purpose of this study is to compare the accuracy and readability of Coronavirus Disease 2019 (COVID-19)-prevention and control knowledge texts generated by four current generative artificial intelligence (AI) models—two international models (ChatGPT and Gemini) and two domestic models (Kimi and Ernie Bot)—and to evaluate the other performance characteristics of texts generated by domestic and international models. This paper uses the questions and answers in the COVID-19 prevention guidelines issued by the U.S. Centers for Disease Control and Prevention (CDC) as the evaluation criteria. The accuracy, readability, and comprehensibility of the texts generated by each model are scored against the CDC standards. Then the neural network model in the intelligent algorithms is used to identify the factors that affect readability. Then the medical topics of the generated text are analyzed using text analysis technology. Finally, a questionnaire-based manual scoring approach was used to evaluate the AI-generated texts, which was then compared to automated machine scoring. Accuracy: domestic models have higher textual accuracy, while international models have higher reliability. Readability: domestic models produced more fluent and publicly accessible language; international models generated more standardized and formally structured texts with greater consistency. Comprehensibility: domestic models offered superior readability, while international models were more stable in output. Readability factors: the average words per sentence (AWPS) emerged as the most significant factor influencing readability across all models. Topic analysis: ChatGPT emphasized epidemiological knowledge; Gemini focused on general medical and health topics; Kimi provided more multidisciplinary content; and Ernie Bot concentrated on clinical medicine. From the empirical results, it can be found that the manual and machine scoring are highly consistent in the indicators SimHash and FKGL, which proves the effectiveness of the evaluation method proposed in this paper. Conclusion: Texts generated by domestic models are more accessible and better suited for public education, clinical communication, and health consultations. In contrast, the international model has a higher accuracy in generating expertise, especially in epidemiological studies and assessing knowledge literature on disease severity. The inclusion of manual evaluations confirms the reliability of the proposed assessment framework. It is therefore recommended that future AI-generated knowledge systems for infectious disease control balance professional rigor with public comprehensibility, in order to provide reliable and accessible reference materials during major infectious disease outbreaks. Full article

COVID-19 causes instant and often prolonged effects with multisystemic and heterogeneous symptoms, significantly affecting the bio-psychosocial life of patients. In view of this, the present prospective cohort study aims to document the evolution of symptoms in hospitalized COVID-19 patients, monitoring variations in their mental and physical health for eighteen months after clinical recovery. A sample of 117 patients was examined at four distinct time points: at 2, 6, 12 and 18 months after discharge from the Pulmonology Clinic of the General University Hospital of Larissa (single-center approach). The data collection focused on psycho-physical symptoms, sleep disturbances and quality of life indicators. The study results revealed that over the 18-month period the participants gradually recovered both physically and psychologically, as well as regained pre-disease sleep patterns. However, substantial recovery was noted by month 6, followed by stabilization of their health status. However, a complete return to the pre-disease state of all assessed variables was not achieved, confirming and reinforcing the need for long-term follow-up and overall patient care. Full article

We present a case with unusual findings on nuclear imaging after mild SARS-CoV-2 infection. During evaluation for an incidentaloma, 18F-Fluorodeoxyglucose Positron Emission Tomography–Computed Tomography imaging showed activity in the thyroid gland, in the lower thoracic spinal column, in portal lymph nodes, and in the terminal ileum and surrounding lymph nodes, all suspicious for metastatic cancer. The patient underwent extensive invasive and non-invasive diagnostic procedures, including biopsies of all the suspicious foci, only showing a small low-grade thyroid cancer that would often be followed and not immediately operated on. Three months later, the findings had either disappeared or were considered reactive. The patient later recalled having had mild COVID-19 seven days prior to the PET/CT. Full article

Background: The COVID-19 pandemic has affected countries globally, causing significant respiratory tract symptoms, including shortness of breath, coughing, chest tightness, and wheezing. Vitamin D has been proposed to play a key role, especially in upper respiratory tract infections. Recently, numerous studies and reports associating low serum 25-hydroxyvitamin D levels (s-25-(OH)D) and adverse outcomes in COVID-19 have emerged. We aimed to assess the association between vitamin D status and SARS-CoV-2 positivity among adults in Lebanon. Method: A cross-sectional study was conducted, recruiting 384 participants aged 18–75 years from a university hospital in South Lebanon. Background variables were collected through structured questionnaires. Serum 25(OH)D levels were measured using electrochemiluminescence immunoassay, and SARS-CoV-2 positivity was assessed through PCR testing. Results: The mean s-25(OH)D level was 46.8 nmol/L (SD 28.1), and 30% of the participants had vitamin D deficiency (s-25-(OH)D level <30 nmol/L). SARS-CoV-2 positivity was reported in 28% of participants. However, no significant association was found between s-25(OH)D levels and SARS-CoV-2 positivity. This study had several limitations, including potential selection bias due to recruiting participants from a hospital for PCR testing, the collection of data across different seasons, and the refusal of several eligible individuals to participate. Additionally, the lack of data on participants’ immunization status and assay variability may impact the generalizability and interpretation of the findings. Conclusion: There was a high prevalence of vitamin D insufficiency among adults participating in COVID-19 tests in Lebanon, but it was not associated with SARS-CoV-2 positivity. Full article

Background: Severe and critical forms of COVID-19 have been associated with high mortality, particularly in vulnerable or underrepresented populations. The neutrophil-to-lymphocyte ratio (NLR) is an emerging inflammatory biomarker that may aid in early risk stratification. Objective: To evaluate the prognostic value of the NLR in hospitalized patients with severe or critical COVID-19 and assess its association with in-hospital mortality in the Yucatecan Maya population of southeastern Mexico. Methods: This retrospective cohort study included 172 adult patients admitted with severe or critical COVID-19 to a tertiary care center in Yucatán, Mexico. Clinical, demographic, and laboratory variables were analyzed. Univariate and multivariate logistic regression were used to identify predictors of in-hospital mortality. ROC analysis determined the optimal NLR threshold. Results: Among the 172 patients, 79 (45.9%) died during hospitalization. Non-survivors exhibited significantly higher NLR values compared to survivors (median 18.4 vs. 6.3; p < 0.001). In multivariate analysis, the NLR remained an independent predictor of mortality (OR 1.66; 95% CI: 1.26–2.17; p < 0.001). The ROC curve showed an AUC of 0. 0.83 for Intensive Care Unit and 903 for in hospital death. Conclusions: In this regional cohort of the Yucatecan Maya population, the NLR was a strong independent predictor of mortality in patients with severe or critical COVID-19. The identified cutoff of the NLR ≥ 9.76 may serve as a valuable, low-cost tool for early risk assessment in similar settings with limited resources. Full article

The increased menstrual disturbances post-vaccination remain unclear. We examined factors, types, frequencies, and emotional challenges. We used a self-administered online questionnaire with the IBM-based SPSSv-24-Windows software for analysis. Of 1372 females, 61.1% (n = 838) were aged 19–29 years, 94.2% (n = 1292) were Saudis, 66.4% (n = 911) were graduates, 70% (n = 965) were single, and 15% (n = 205) had chronic diseases. Moreover, 96.5% (n = 1285/1332) had two vaccine doses, mostly Pfizer’s first- and second doses (82% and 78, respectively), while 3.5% (n = 47) only had one. Vaccine groups significantly differed (Pfizer, Moderna, Oxford, and do not know) after the first (0.047) and second (0.049) doses, while Pfizer vaccines were predictive [OR = 2.09 (0.96–4.10), p = 0.029] at two-doses [OR = 3.21 (1.23–5.21), p = 0.030]. No acute COVID appeared. The majority (77%; n = 1057) had no issues, except, in a subgroup of 23% (n = 315) of participants, 43% (n = 135) experienced worsening issues. However, 47.2% (n = 629) complained only post vaccination. Most issues were (75%; n = 471) cycle-timing disruptions; the rest were minor (decreased blood or bleeding, missed-periods, or pain). Other potential reasons were fear, stress, and mental health problems, which occurred in 51% (n = 674) of the group, while 53% (n = 701) were worried. Intriguingly, the menstrual issues in the remaining 47% (n=631) who were not worried could be due to a direct molecular vaccine interaction, irrespective of any mental issue ([OR = 1.78 (0.76–3.21), p = 0.033]. Age proportionalities were significant (p = 0.05) in the 30–39 year-old group (51%). Postgraduate education [OR = 2.11 (0.98–4.72), p = 0.015) and employment [OR = 2.18 (0.95–4.86), p = 0.049] were also predictors. These findings have significant implications in women’s health and vaccine improvement. Future studies on diverse factors are warranted. Full article