Search Results (616)

This study presents an extended approach to compartmental modeling of infectious disease spread, focusing on regional heterogeneity within affected areas. Using classical SIS, SIR, and SEIR frameworks, we simulate the dynamics of COVID-19 across two major regions of Ukraine—Dnipropetrovsk and Kharkiv—during the period 2020–2024. The proposed mathematical model incorporates regionally distributed subpopulations and applies a system of differential equations solved using the classical fourth-order Runge–Kutta method. The simulations are validated against real-world epidemiological data from national and international sources. The SEIR model demonstrated superior performance, achieving maximum relative errors of 4.81% and 5.60% in the Kharkiv and Dnipropetrovsk regions, respectively, outperforming the SIS and SIR models. Despite limited mobility and social contact data, the regionally adapted models achieved acceptable accuracy for medium-term forecasting. This validates the practical applicability of extended compartmental models in public health planning, particularly in settings with constrained data availability. The results further support the use of these models for estimating critical epidemiological indicators such as infection peaks and hospital resource demands. The proposed framework offers a scalable and computationally efficient tool for regional epidemic forecasting, with potential applications to future outbreaks in geographically heterogeneous environments. Full article

During the coronavirus 2019 pandemic, sports activities were restricted, raising concerns about their impact on the physical condition of adolescent athletes, which remained largely unquantified. This study was designed with two primary objectives: first, to precisely quantify and elucidate the differences in the physical condition of adolescent athletes before and after activity restrictions due to the pandemic; and second, to innovatively develop and validate a non-contact medical checkup application. Medical checks were conducted on 563 athletes designated for sports enhancement. Participants were junior high school students aged 13 to 15, and the sample consisted of 315 boys and 248 girls. Furthermore, we developed a smartphone application and compared self-checks using the application with in-person checks by orthopedic surgeons to determine the challenges associated with self-checks. Statistical tests were conducted to determine whether there were statistically significant differences in range of motion and flexibility parameters before and after the pandemic. Additionally, items with discrepancies between values self-entered by athletes using the smartphone application and values measured by specialists were detected, and application updates were performed. Student’s t-test was used for continuous variables, whereas the chi-square test was used for other variables. Following the coronavirus 2019 pandemic, athletes were stiffer than during the pre-pandemic period in terms of hip and shoulder joint rotation range of motion and heel–buttock distance. The dominant hip external rotation decreased from 53.8° to 46.8° (p = 0.0062); the non-dominant hip external rotation decreased from 53.5° to 48.0° (p = 0.0252); the dominant shoulder internal rotation decreased from 62.5° to 54.7° (p = 0.0042); external rotation decreased from 97.6° to 93.5° (p = 0.0282), and the heel–buttock distance increased from 4.0 cm to 10.4 cm (p < 0.0001). The heel–buttock distance and straight leg raising angle measurements differed between the self-check and face-to-face check. Although there are items that cannot be accurately evaluated by self-check, physical condition can be improved with less contact by first conducting a face-to-face evaluation under appropriate guidance and then conducting a self-check. These findings successfully address our primary objectives. Specifically, we demonstrated a significant decline in the physical condition of adolescent athletes following pandemic-related activity restrictions, thereby quantifying their impact. Furthermore, our developed non-contact medical checkup application proved to be a viable tool for monitoring physical condition with reduced contact, although careful consideration of measurable parameters is crucial. This study provides critical insights into the long-term effects of activity restrictions on young athletes and offers a practical solution for health monitoring during infectious disease outbreaks, highlighting the potential for hybrid checkup approaches. Full article

Since the first emergence of the Bluetongue virus (BTV) in 2006 in Northern Europe, there has been a reported association between BTV Serotype 8 (BTV-8) and brain malformations in calves. The first BTV-3 outbreak in Germany was registered in October 2023. Since then, numbers have increased steadily. In a suckler cow herd in the Lower Saxony region, two Angus calves with clinical signs of diffuse encephalopathy, including ataxia, abnormal gait, and central blindness, were born in autumn 2024. Both calves were submitted for Magnetic Resonance Imaging (MRI) and pathological examination, revealing hydranencephaly and internal hydrocephalus, respectively. BTV-3 was detected in blood and tissue samples of both calves using BTV-specific real-time PCR. The presented findings demonstrate that there seems to be an association between transplacental BTV-3 infections and congenital malformations in calves, as previously reported for BTV-8 and -10. Full article

Background: Osteogenesis imperfecta (OI) is a rare genetic connective tissue disorder characterized by bone fragility, most often caused by pathogenic variants in type I collagen genes. In this context, we aimed to describe the clinical and epidemiological characteristics of patients with OI who were hospitalized for coronavirus disease (COVID)-19 in Brazil between 2020 and 2024. Methods: We conducted a retrospective descriptive analysis using data from the Brazilian Unified Health System (SUS, which stands for the Portuguese Sistema Único de Saúde) through the Open-Data-SUS platform. Patients with a confirmed diagnosis of OI and hospitalization due to COVID-19 were included. Descriptive statistical analysis was performed to evaluate demographic, clinical, and outcome-related variables. We included all hospitalized COVID-19 cases with a confirmed diagnosis of OI between 2020 and 2024. Results: Thirteen hospitalized patients with OI and COVID-19 were identified. Most were adults (9; 69.2%), male (7; 53.8%), self-identified as White (9; 69.2%), and all were residents of urban areas (13; 100.0%). The most frequent symptoms were fever (10; 76.9%), cough (9; 69.2%), oxygen desaturation (9; 69.2%), dyspnea (8; 61.5%), and respiratory distress (7; 53.8%). Two patients had heart disease, one had chronic lung disease, and one was obese. As for vaccination status, five patients (38.5%) had been vaccinated against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Four patients (30.8%) required admission to an intensive care unit (ICU), and six (46.2%) required noninvasive ventilatory support. Among those admitted to the ICU, only two required invasive mechanical ventilation. The clinical outcome was death in two cases (15.4%). Both patients were male, White, and had not been vaccinated against SARS-CoV-2. One was 47 years old, was not admitted to the ICU, but required noninvasive ventilation. Despite the underlying condition most patients had favorable outcomes, consistent with an international report. Conclusions: This is the first report to describe the clinical and epidemiological profile of patients with OI hospitalized for COVID-19 in Brazil, providing initial insights into how a rare bone disorder intersects with an acute respiratory infection. The generally favorable outcomes observed—despite the underlying skeletal fragility—suggest that individuals with OI are not necessarily at disproportionate risk of severe COVID-19, particularly when appropriately monitored. The occurrence of deaths only among unvaccinated patients underscores the critical role of SARS-CoV-2 vaccination in this population. Although pharmacological treatment data were unavailable, the potential protective effects of bisphosphonates and vitamin D merit further exploration. These findings support the need for early preventive strategies, systematic vaccination efforts, and dedicated clinical protocols for rare disease populations during infectious disease outbreaks. Full article

In Kenya, Rift Valley fever (RVF) outbreaks pose significant challenges, being one of the most severe climate-sensitive zoonoses. While machine learning (ML) techniques have shown superior performance in time series forecasting, their application in predicting disease outbreaks in Africa remains underexplored. Leveraging data from the International Livestock Research Institute (ILRI) in Kenya, this study pioneers the use of ML techniques to forecast RVF outbreaks by analyzing climate data spanning from 1981 to 2010, including ML models. Through a comprehensive analysis of ML model performance and the influence of environmental factors on RVF outbreaks, this study provides valuable insights into the intricate dynamics of disease transmission. The XGB Classifier emerged as the top-performing model, exhibiting remarkable accuracy in identifying RVF outbreak cases, with an accuracy score of 0.997310. Additionally, positive correlations were observed between various environmental variables, including rainfall, humidity, clay patterns, and RVF cases, underscoring the critical role of climatic conditions in disease spread. These findings have significant implications for public health strategies, particularly in RVF-endemic regions, where targeted surveillance and control measures are imperative. However, this study also acknowledges the limitations in model accuracy, especially in scenarios involving concurrent infections with multiple diseases, highlighting the need for ongoing research and development to address these challenges. Overall, this study contributes valuable insights to the field of disease prediction and management, paving the way for innovative solutions and improved public health outcomes in RVF-endemic areas and beyond. Full article

Peste des petits ruminants is a highly contagious transboundary viral disease that poses a serious threat to small ruminant populations worldwide. In 2024, seven outbreaks of PPR were recorded in sheep flocks from Timiș County, marking the second confirmed incursions of peste des petits ruminants virus (PPRV) in Romania. This study aimed to document the clinical presentation, pathological findings, and diagnostic confirmation with these field outbreaks. Comprehensive field investigations were carried out between July and September 2024, including clinical examinations, post mortem analysis, serological screening, and molecular detection using reverse transcription polymerase chain reaction (RT-PCR). A total of 13,203 sheep were evaluated, with an overall mortality rate of 12.77%. Characteristic clinical signs included mucopurulent nasal discharge, oral erosions, respiratory distress, and diarrhea. Gross lesions observed during necropsy included hemorrhagic bronchopneumonia, bile-stained liver, catarrhal enteritis, and mucosal hemorrhages. Serological testing revealed flock-level seroprevalence rates ranging from 46.7% to 80.0%, with higher rates observed in older animals. RT-PCR confirmed PPRV infection in all affected flocks. Our findings provide strong evidence of virulent PPRV circulation in an area where the virus had not been reported before. The results highlight an urgent need to strengthen surveillance systems, enhance diagnostic capacity, and foster cross-border collaboration. These field-based insights can contribute to both national and international efforts aimed at controlling and ultimately eradicating the disease. Full article

Background: An effective vaccine against Nipah virus (NiV) is crucial due to its high fatality rate and recurrent outbreaks in South and Southeast Asia. Vaccine development is challenged by the lack of validated accessible neutralization assays, as virus culture requires BSL-4 facilities, restricting implementation in resource-limited settings. To address this, we standardized and validated a pseudotyped virus neutralization assay (PNA) for assessing NiV-neutralizing antibodies in BSL-2 laboratories. Methods: The NiV-PNA was validated following international regulatory standards, using a replication-defective recombinant Vesicular stomatitis virus (rVSV) backbone dependent pseudotyped virus. Assessments included sensitivity, specificity, dilutional linearity, relative accuracy, precision, and robustness. The assay was calibrated using the WHO International Standard for anti-NiV antibodies and characterized reference sera to ensure reliable performance. Findings: Preliminary evaluation of the developed NiV-PNA showed 100% sensitivity and specificity across 10 serum samples (5 positive, 5 negative), with a positive correlation to a calibrated reference assay (R² = 0.8461). Dilutional linearity (R² = 0.9940) and accuracy (98.18%) were confirmed across the analytical titer range of 11-1728 IU/mL. The assay also exhibited high precision, with intra-assay and intermediate precision geometric coefficients of variation of 6.66% and 15.63%, respectively. Robustness testing demonstrated minimal variation across different pseudotyped virus lots, incubation times, and cell counts. Conclusions: The validated NiV-PNA is a reproducible and scalable assay platform for quantifying NiV neutralizing antibodies, offering a safer alternative to virus culture. Its validation and integration into the CEPI Centralized Laboratory Network will enhance global capacity for vaccine evaluation and outbreak preparedness. Full article

With the advancement of Agriculture 4.0, intelligent systems and data-driven technologies offer new opportunities for pork supply-demand balance regulation, while also confronting challenges such as production cycle fluctuations and epidemic outbreaks. This paper introduces a knowledge-driven smart system for pork supply-demand regulation, which integrates essential components including a knowledge base, a mathematical-model-based expert system, an enhanced optimization framework, and a real-time feedback mechanism. Around the core of the system, a nonlinear constrained optimization model is established, which uses adjustments to newly retained gilts as decision variables and minimizes supply-demand squared errors as its objective function, incorporating multi-dimensional factors such as pig growth dynamics, epidemic impacts, consumption trends, and international trade into its analytical framework. By harnessing dynamic decision-making capabilities of reinforcement learning (RL), we design an optimization architecture centered on the Q-learning mechanism and dual-strategy pools, which is integrated into the honey badger algorithm to form the RL-enhanced honey badger algorithm (RLEHBA). This innovation achieves an efficient balance between exploration and exploitation in model solving and improves system adaptability. Numerical experiments demonstrate RLEHBA’s superior performance over State-of-the-Art algorithms on the CEC 2017 benchmark. A case study of China’s 2026 pork regulation confirms the system’s practical value in stabilizing the supply-demand balance and optimizing resource allocation. Finally, some targeted managerial insights are proposed. This study constructs a replicable framework for intelligent livestock regulation, and it also holds transformative significance for sustainable and adaptive supply chain management in global agri-food systems. Full article

In this article, to address the uncertainty of preference information in interrelated conflicts in the real world, a hierarchical conflict modeling and analysis approach based on hesitant fuzzy linguistic term sets (HFLTSs) is proposed. First, considering the hesitancy and fuzziness of decision makers (DMs) when expressing preferences in hierarchical conflicts, a preference representation approach based on HFLTSs is introduced. Building upon hesitant fuzzy linguistic preference, four distinct types of hesitant fuzzy stability definitions of the two-level hierarchical graph model for conflict resolution (HGMCR) are extended, and a corresponding algorithm is developed to solve the global conflict hesitant fuzzy equilibrium states. Finally, this study is applied to investigate the outbreak and development of a specific international conflict, verifying the feasibility and effectiveness of the proposed approach. The hesitant fuzzy equilibrium states of an international conflict indicate that the attitudes of domestic forces reflect a nation’s performance in the warand that the conflict may endure for an extended duration. The hierarchical conflict modeling and analysis approach based on HFLTSs allows DMs to express the hesitation and fuzziness of preferences under uncertainty, facilitates the comprehension of the intrinsic logic behind interactions among DMs at various levels, and enhances the analysis to achieve more foresighted equilibria. 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

Background/Objectives: A resurgence of measles has been observed in Europe and worldwide since 2023. The aim of this article is to describe characteristics of cases reported to the Italian national measles surveillance system and discuss reasons for the outbreak and its public health relevance. Methods: We analyzed measles cases reported to the Italian national measles surveillance system with a symptom onset from August 2023 to January 2025. Results: Overall, 1164 cases were reported, of which 1065 (91.5%) were laboratory confirmed. The median age was 30 years, but the highest incidence was in children under one year of age. Transmission occurred mainly in families and nosocomial settings. Multiple importations occurred during 2023, which initially led to localized outbreaks with limited spread but was subsequently followed by increasing local transmission in 2024. Conclusions: These findings suggest lingering immunity gaps in children and adults in Italy, highlighting the potential severity of measles and the ease with which measles crosses country borders. Besides improving routine immunization coverage, targeted vaccination opportunities should be provided to susceptible population groups. Communication activities are also needed to increase awareness about disease severity, especially among young adults. In view of the upcoming travel season, travel clinics should encourage persons without evidence of measles immunity to be vaccinated before any international travel. Full article

Henipaviruses are emerging zoonotic viruses that have caused deadly outbreaks in humans and livestock across several regions of the world. The fusion (F) protein of henipaviruses plays a critical role in viral entry into host cells and represents a key determinant of viral pathogenicity. This review provides a comprehensive analysis of current knowledge regarding trafficking, activation, as well as the role in particle assembly, of henipavirus F proteins. We discuss the unique characteristics of henipavirus F proteins compared to other paramyxovirus fusion proteins, with particular emphasis on their distinctive trafficking and activation mechanisms. Attention is also given to novel henipaviruses that have been detected in hosts other than bats, namely rodents and shrews. These viruses are sufficiently different that the International Committee on Taxonomy of Viruses has proposed a new genus for them, the Parahenipaviruses. We discuss how variations in F protein characteristics between Henipaviruses, Parahenipaviruses, and yet-unclassified henipa-like viruses might influence their trafficking and activation. Understanding these molecular mechanisms is crucial for developing effective therapeutic strategies against henipavirus infections and for predicting the emergence of novel henipavirus strains with pandemic potential. Full article

Background/Objectives: In the Republic of Serbia, measles vaccination was first introduced in 1971, while combined vaccination (measles, mumps, rubella) was made mandatory in 1996 as part of the national vaccination program. Reported prevalence values for 2023 were <0.75 cases per 100K population for measles, 0.09 cases per 100K for mumps, and no cases of rubella. Methods: This cross-sectional study was performed in May, 2024 as part of the project “Herd Immunity to Vaccine-Preventable and Other Relevant Infections in the Belgradian Population.” It focused on assessing herd immunity to measles, mumps and rubella (MMR) among residents insofar as these remain a public concern despite the availability of vaccines. A total of 2533 subjects were distributed across nine age groups, covering those aged 1–70⁺ years and various professional groups residing in Belgrade. Participants were stratified by age and activity. Upon obtaining individual information by online questionnaire and receiving a signed statement of informed consent, blood samples were obtained for IgG antibody testing (ELISA) to determine MMR serological status. The results were compared to national and international immunization standards to evaluate herd immunity levels. Results: Our results indicate varying levels of immunity for each virus, with specific demographic groups showing different immunity levels. Total measles seroprevalence during this study was 74.7%, with significant variation across all age groups. While high seropositivity was observed in both children (90.7%) and elder age groups (98.4%), middle-aged individuals in the age group 30–49 years showed significantly lower IgG levels. Between 2021 and 2023, there were no registered cases of rubella detected in Serbia, which indicates a high level of immunity. This was confirmed here with consistently high IgG levels across all age groups, with an average seropositivity of 94.8%. Average mumps seropositivity across all age groups was 85.1%. The lowest value was in the young child (1–5 years) age group (76.1%); the highest was in the elderly group (92.6%). Conclusions: The current findings suggest that the Belgradian population has strong overall immunity to MMR, yet with some concerns regarding measles immunity in middle-aged adults, suggesting a potential need for catch-up vaccinations. While rubella status indicates strong herd immunity and minimal risk of outbreaks, mumps immunity in some groups (children, middle-aged adults) is below the protective threshold. While it is still sufficient to prevent widespread transmission, it should be closely observed. To our knowledge, this study is the first of its kind to provide data about MMR seroprevalence in Belgrade. Findings indicate the need for constant surveillance and revaccination of vulnerable/seronegative groups. Full article

Measles is a highly contagious viral disease and remains a global health challenge despite the availability of effective vaccines. Although many regions have successfully eliminated measles, outbreaks continue to occur owing to vaccine hesitancy, inadequate coverage, and imported cases. Differences in epidemiology, vaccination policies, and immunity assessment influence measles control across countries. This paper compares measles epidemiology, vaccination policies, and immunity assessment approaches in the United States and Japan. Data were obtained from surveillance reports, national immunization programs, and peer-reviewed literature. The introduction of the measles vaccine led to substantial reductions in incidence. The United States eliminated measles in 2000 but continues to experience outbreaks due to vaccine hesitancy and imported cases. Japan implemented a two-dose policy in 2006, reducing case numbers; however, sporadic outbreaks among adults persist. In the United States, immunity is primarily assessed using documented vaccination history, whereas in Japan, enzyme immunoassay is commonly used to evaluate immunity status. Despite progress in measles elimination, achieving high vaccination coverage and addressing vaccine hesitancy remain critical challenges. Variations in immunity assessment methods impact surveillance accuracy and outbreak control. Strengthening international collaboration, standardizing assessment protocols, and enhancing public health education are crucial for sustained measles elimination. Full article

Background: Parvovirus B19 is the major cause of transient aplastic crisis in children with hereditary spherocytosis (HS) inhibiting erythropoiesis and leading to a severe drop in hemoglobin levels, requiring hospitalization and transfusional support. During the COVID-19 pandemic, the circulation of non-COVID respiratory viruses, such as parvovirus B19, initially declined but subsequently increased abruptly following the relaxation of containment strategies. Moreover, it remains unclear whether this has resulted in a rise in parvovirus B19-induced aplastic crises among individuals with HS. Methods: This retrospective, single-center study conducted at the Pediatric University Hospital of Bari (Italy) aims to describe the clinical characteristics and frequency of parvovirus B19-induced aplastic crises in pediatric patients with HS before and after the COVID-19 Public Health Emergency of International Concern (PHEIC, 30 January 2020–5 May 2023). The study was divided into four distinct periods: Period A: from 1 December 2018 to 31 December 2019, representing one year before the declaration of the PHEIC; Period B: from 1 June 2023 to 30 June 2024, representing one year after the cessation of the PHEIC; Period C: before 1 December 2018; Period D: from 1 January 2020 to 31 May 2023, which refers to the pandemic period. Results: A total of 30 patients (55% of the study population, n = 55) experienced a parvovirus B19-induced aplastic crisis. The frequency of these crises in Period B was significantly higher than in Period A (p < 0.0001). Conclusions: This study suggests a substantial increase in parvovirus B19-induced aplastic crises among children with HS following the COVID-19 outbreak indicating a potential impact of public health containment strategies on parvovirus B19 infection rates. Full article