Search Results (428)

Crimean–Congo hemorrhagic fever (CCHF) remains a major tick-borne zoonotic infection and a persistent public health challenge in Central Asia. Kazakhstan is among the endemic countries, where natural foci of CCHF are concentrated predominantly in the southern regions. This study evaluated the long-term epidemiological trends, regional distribution, seasonality, and risk factors associated with CCHF in Kazakhstan. A retrospective analysis of national surveillance data from 1980 to 2023 was conducted, complemented by detailed epidemiological and entomological investigations in the Turkestan region and the city of Shymkent during 2011–2023. Laboratory-confirmed cases, tick bite-related healthcare visits, entomological surveillance data, demographic characteristics, and epidemiological risk factors were analyzed. The results demonstrated cyclic fluctuations in CCHF incidence, with epidemic peaks occurring every 4–6 years and pronounced spring–summer seasonality, with the highest incidence observed in June and July. Long-term average annual incidence in endemic southern regions exceeded the national average by 2.67-fold. A total of 50,671 tick bite-related healthcare visits were registered during 2011–2023, while their incidence declined over time. Analysis of 94 laboratory-confirmed cases identified adults aged 18–40 years as the most affected group. Tick bites and livestock-related activities were the principal risk factors. These findings support the strengthening of integrated surveillance, vector control, laboratory diagnostics, and One Health-based prevention strategies in endemic regions. Full article

Objective: Myopia has reached epidemic proportions globally, with approximately 50% of the world population projected to be affected by 2050. Low-concentration atropine eye drops (0.01%, 0.025%, 0.05%) have emerged as a primary intervention for myopia control. Several meta-analyses on this topic have been published; however, none have included the most recent trials nor separately analyzed premyopia prevention outcomes. This systematic review and meta-analysis evaluates the efficacy and safety of these concentrations for myopia progression control and premyopia prevention. Methods: We searched PubMed, Web of Science, Embase, and Cochrane CENTRAL from database inception through April 2026. Randomized controlled trials (RCTs) comparing 0.01%, 0.025%, or 0.05% atropine with placebo or no treatment in children were included. Studies were screened using PICOS criteria (Population, Intervention, Comparison, Outcomes, Study design). Meta-analysis was performed using DerSimonian–Laird random-effects models. Subgroup analyses were conducted by concentration, follow-up duration, and population (myopia progression vs. premyopia prevention). Results: Of 18 full-text articles assessed, 8 RCTs (n = 1756) met all PICOS criteria and were included in the quantitative synthesis. For myopia progression, 0.01% atropine demonstrated significant efficacy at 1 year (pooled MD = +0.291 D, 95% CI: 0.199 to 0.384; p < 0.0001; I² = 29.1%) and at 2 years (pooled MD = +0.174 D, 95% CI: 0.056 to 0.291; p = 0.0038; I² = 0%). The 0.05% concentration showed the largest effect (pooled MD = +0.520 D, 95% CI: 0.409 to 0.630; p < 0.0001; I² = 0%). Clinically, a 0.25 D difference over 1–2 years may translate to approximately 0.50 D cumulative benefit over a typical 5-year treatment course, potentially reducing the risk of high myopia. For premyopia prevention, a narrative synthesis was performed due to extreme heterogeneity between studies (I² = 99.2%). All concentrations showed an excellent safety profile with no serious adverse events. Conclusions: Low-concentration atropine is effective for myopia progression control at all three concentrations, with a concentration-dependent gradient (0.05% > 0.025% > 0.01%). The 0.01% concentration offers a reasonable balance of efficacy and tolerability. Further independent validation of the 0.05% concentration is warranted. The premyopia prevention indication requires additional well-designed RCTs. Full article

Background/Objectives: Following the COVID-19 pandemic, pertussis resurged sharply across Europe, with 209,674 cases reported in the EU/EEA in 2024. This study characterises the epidemiology of the 2024 pertussis resurgence across five counties of southeastern Romania, with emphasis on vaccination status, clinical severity, and regional surveillance performance. Methods: A retrospective, population-based analysis was conducted on 452 cases notified between February 2024 and January 2025, extracted from the national surveillance database. A pre-specified reclassification of PCR-positive cases yielded 326 confirmed cases. Categorical, non-parametric, correlation, and multivariate logistic regression analyses were performed. Results: The epidemic peaked in September 2024, with 56.0% of cases occurring between August and October. Children under five years accounted for 63.2% of confirmed cases, and 72.1% were not vaccinated according to age-appropriate schedule, predominantly due to parental refusal (43.0%) and non-attendance (36.6%). Pneumonia affected 36.8% of confirmed cases, ranging from 81.0% in infants under two months to 0% in adolescents. Age-appropriate vaccination was independently protective against pneumonia (adjusted OR = 0.53, 95% CI 0.29 to 0.96, p = 0.035; population attributable risk 37.3%). Significant inter-county heterogeneity was identified in PCR implementation (72 to 100%) and reporting delays. Conclusions: Vaccination gaps were the principal modifiable driver of the resurgence, supporting targeted coverage improvement and the introduction of a national maternal Tdap programme. Full article

Climate change is significantly altering the distribution, seasonality, and transmission dynamics of vector-borne diseases, posing an increasing public health concern, particularly in regions previously considered at low risk. Key climatic variables, including temperature, precipitation, and humidity, strongly influence vector survival, reproduction, and pathogen transmission capacity. This review provides an overview of current evidence on the relationship between climate change, vector ecology, and vector-borne disease epidemiology in Europe, based on evidence extracted from peer-reviewed literature published between 2010 and 2024 and retrieved from PubMed, Scopus, and Web of Science. Particular attention is given to vector-borne diseases with current or potential relevance to Europe. This includes infections that are already endemic, such as leishmaniasis and tick-borne encephalitis, as well as diseases currently imported, such as malaria, dengue, chikungunya, Zika, yellow fever, and Chagas disease, that may pose a future risk of local transmission due to climate-driven changes in vector distribution and abundance. The analysis highlights potential health and economic impacts, and discusses implications for public health preparedness, environmental sanitation, surveillance, and vector control strategies. Strengthening adaptive and mitigation policies, alongside targeted research efforts, is essential to enhance resilience of health systems against climate-driven epidemic risks. Full article

Peripheral Artery Disease (PAD) is increasingly recognized as a complex environmental pathology driven by “contaminant metals,” rather than solely lifestyle factors. This scoping review (2016–2025) analyses the correlation between anthropogenic soil/water-derived Cadmium (Cd) and Lead (Pb) and progressive vascular hardening. The analysis confirms a robust, non-linear dose–response relationship. Chronic Cd exposure functions as a potent independent toxicant (Risk Ratio = 2.58 at 1 µg/L), significantly lowering Ankle–Brachial Index scores by inducing oxidative stress, inhibiting nitric oxide bioavailability, and displacing calcium in endothelial walls. Synergistically, Pb exposure, even at levels <5 µg/dL, compounds toxicity, amplifying arterial stiffness and hypertension. Consequently, “Heavy Metal Hardening” constitutes a critical link between water quality management and public health. Current regulatory thresholds appear insufficient to prevent chronic vascular remodeling, mandating urgent remediation of metal-laden aquifers and agricultural soils to mitigate this silent cardiovascular epidemic. Full article

Dairy cows are economically significant ruminants in China, and the dairy industry is closely linked to food safety and the agricultural economy. However, various factors such as pathogenic microorganisms often lead to frequent diseases in dairy cows. Furthermore, as potential hosts for diverse viruses, dairy cows can harbor zoonotic pathogens, which pose a threat to public health. The Shaanxi–Gansu–Ningxia region boasts abundant natural resources and extensive pastures. It is a major animal husbandry base in Northwest China, and dairy farming plays a significant role in the local economy. However, research on dairy cow virus diversity in this region remains limited; epidemic prevention and control capabilities are constrained, and the risk of disease outbreaks is elevated. In this study, 790 dairy cow samples were collected from 13 large-scale farms and free-range households in the Shaanxi–Gansu–Ningxia region from 2021 to 2023. Sample types consisted of nasal and anal swabs. Six viral metagenomic libraries were constructed and analyzed using high-throughput sequencing and bioinformatics methods, leading to the identification of 51 viral families. These comprised 16 positive-sense single-stranded RNA virus families, one Retroviridae family, four double-stranded RNA virus families, 21 double-stranded DNA virus families, and nine single-stranded DNA virus families. Among these, RNA viruses were represented by families such as Astroviridae, Coronaviridae, Caliciviridae, Picornaviridae, and Picobirnaviridae; DNA viruses were primarily detected in Circoviridae, Papillomaviridae, Genomoviridae, and Smacoviridae. Alpha diversity analysis revealed no significant differences in viral diversity and abundance among the three regions (p > 0.05); however, significant differences were observed in the read counts and proportions of RNA and DNA viruses across the provinces. Phylogenetic analysis further indicated that viruses carried by dairy cows exhibit considerable genetic diversity and pose potential cross-species transmission risks. This study established a reference database for the dairy cow virome in the Shaanxi–Gansu–Ningxia region, elucidated the phylogenetic relationships of key viruses, and provided a scientific basis for future monitoring and prevention of dairy cow viruses. Full article

An administrator-assisted CLP-SEIRS-T⁺ framework is developed to model malware propagation and urban cyber-resilience in clustered temporal communication networks. The model extends CLP-SEIRS-T by integrating community structure, predicted links, asynchronous node activation, and an endogenous defense layer in which administrator nodes remain infectable, recover faster than ordinary nodes, and trigger local patch diffusion when community-level prevalence exceeds a risk threshold. Unlike formulations that treat defense as an external or perfectly reliable safeguard, the proposed framework embeds administrator intervention directly within the epidemic state space and couples propagation dynamics with resilience-oriented performance measures, including safe functionality, absorptive capacity, spillover attenuation, recovery time, and service continuity. To keep experimental evidence scale-explicit, the validation is organized as a tiered protocol: a 48-node isolated virtual-machine cyber-range verifies safe mechanism realization; emulation-calibrated logical traces and pilot repeated comparisons examine trajectory behavior, pathway composition, and defense-component effects; and expanded numerical sweeps assess scalability, threshold sensitivity, alternative link-prediction scores, and adaptive-stress assumptions. The results show that direct links dominate local amplification, whereas predicted links contribute disproportionately to cross-community spillover. In the pilot comparison, the full CLP-SEIRS-T⁺ configuration achieves the best observed balance, reducing mean peak burden by 56.9%, shortening mean recovery time by 86.7%, increasing absorptive capacity by 37.1%, and improving service continuity by 12.0% relative to the no-intervention baseline. Larger-network sweeps over $N=48,100,150,200,$ and 500 logical hosts preserve the same qualitative mechanism ordering while keeping functionality error below 0.02. Threshold analysis indicates that intermediate trigger values provide a better burden–cost balance than either overly aggressive or delayed patching. Link-score comparisons show that local-neighborhood predictors yield consistent spillover interpretations, whereas degree-driven prediction can increase bridge exposure. Parameterized adaptive-stress tests further indicate that the mechanism remains beneficial under moderate stress but degrades under severe patch suppression, false telemetry, or intensified bridge seeking. These findings suggest that urban cyber-resilience depends jointly on network modularity, temporal availability, structurally likely bridge formation, state-dependent local defense, and the integrity of administrative response. Full article

Lumpy skin disease (LSD), a vector-borne viral disease of cattle, re-emerged in Italy in June 2025 after six years of absence in Europe, affecting the island of Sardinia, which had previously been disease-free. The insular setting, the predominance of extensive cattle farming systems, and the rapid implementation of control measures provided a unique opportunity to investigate epidemic dynamics and evaluate vaccination effectiveness under field conditions. This study aimed to describe the epidemiological pattern of the first epidemic season (June–October 2025), estimate key transmission parameters, and assess vaccination effectiveness at the farm level. Confirmed outbreaks consistent with local transmission and notified between 20 June and 26 October 2025 were analyzed to characterize epidemic transmission dynamics, while vaccination effectiveness was assessed over an extended follow-up period through 31 December 2025. The between-farm basic reproduction number (R₀) was estimated from the early exponential growth phase using log-linear regression and doubling time calculations. Spatio-temporal clustering was assessed using Kulldorff’s scan statistic under a Poisson model, accounting for the population at risk. Vaccination effectiveness was evaluated using a time-dependent Cox proportional hazards model with a 21-day post-vaccination lag. A total of 79 outbreaks were confirmed, of which 68 were consistent with local transmission. Affected farms included a total of 3443 cattle, with morbidity, mortality, and case fatality rates of 14.4%, 7.0%, and 31.1%, respectively. The exponential growth phase lasted four weeks, with an estimated growth rate of 0.366 per week and a doubling time of 1.89 weeks. The estimated R₀ ranged from 1.55 to 1.92, depending on the assumed generation time, indicating moderate but sustained transmission. The median apparent spatial spread velocity was 4.8 km/day. Spatio-temporal analysis identified a single highly significant cluster in the central-eastern area, accounting for approximately 27% of outbreaks (RR = 58.06; p < 0.001). Vaccination was associated with a substantial reduction in outbreak risk (HR = 0.18; 95% CI: 0.06–0.51; p = 0.001), corresponding to an estimated effectiveness of approximately 82% at the farm level. The 2025 Sardinian epidemic was characterized by moderate transmissibility and strong spatial clustering during the early phase. Rapid implementation of vaccination was associated with a significant reduction in outbreak risk, even under conditions of high infection pressure. The integration of spatio-temporal analyses and time-dependent modeling proved essential to support evidence-based control strategies in newly affected regions. Full article

Brucellosis remains a significant public health and economic burden in many regions, primarily transmitted from livestock to humans through direct contact and environmental contamination. In this paper, we develop a novel cross-species epidemic model that couples the transmission dynamics of brucellosis among sheep, humans, and the environmental reservoir of Brucella. The sheep population is divided into susceptible, exposed, infectious, and vaccinated compartments, while the human population is stratified into susceptible and infected classes. Environmental brucella load is explicitly modeled, and distributed time delays are incorporated to account for incubation periods and delayed exposure risks in humans. We prove that all solutions are non-negative and ultimately bounded, ensuring biological consistency. The basic reproduction number ${\mathcal{R}}_0$ is derived using the next-generation matrix method. Using Lyapunov functionals and LaSalle’s invariance principle, we establish that the disease-free equilibrium is globally asymptotically stable when ${\mathcal{R}}_0\le 1$, whereas a unique endemic equilibrium exists and is globally asymptotically stable when ${\mathcal{R}}_0>1$. Sensitivity analysis identifies the environmental transmission rate, shedding rate, and disinfection as the most influential parameters. Treatment efficacy is shown to exhibit a critical threshold $p^{\mathrm{cr}}=1-1/{\mathcal{R}}_0$, above which eradication becomes feasible. Numerical simulations validate the theoretical findings and demonstrate that time delays affect outbreak timing but not asymptotic stability. These results provide quantitative guidance for brucellosis control strategies, emphasizing environmental sanitation, culling, and vaccination as key interventions. Full article

Background and Objectives: New Caledonia, an archipelago in the South Pacific, experienced an unprecedented conjunction of prolonged border closure during the COVID-19 pandemic (2020 to 2022) and marked influence of the El Niño/Southern Oscillation (ENSO). This context provided a unique opportunity to explore how environmental drivers, island isolation, and socio-demographic factors interact to shape infectious disease dynamics. This study aimed to assess the respective and combined effects of climatic variability, travel restrictions, and socio-demographic factors on the dynamics of four priority infectious diseases. Materials and Methods: We retrospectively analysed data from 2017 to 2023 on four infectious diseases: leptospirosis, dengue, influenza, and hepatitis A (HAV). Satellite precipitation data and the Multivariate El Niño/Southern Oscillation Index (MEI) were used. Socio-demographic and economic variables were gathered. Statistical analyses employed descriptive analysis and Generalized Additive Mixed Models to evaluate the associations between climatic events, travel restrictions, and disease circulation using the communal level as a random effect and time (daily) as a spline effect. Results: We analysed 878 cases of leptospirosis, 165 of HAV, 6607 of influenza, and 7377 dengue cases. Influenza was associated with rainfall before lockdown (Odds Ratio (OR) 0.7, Confidence interval 95%, (CI95%), (0.6–0.8)) and disappeared during lockdown but resurged post-reopening losing its meteorological association. Dengue epidemics declined, coinciding with the Wolbachia program and border closure, and were associated with lower MEI (OR 0.78, CI95% (0.6–1) during the 2017 to 2020 period. HAV cases were correlated with the MEI (OR: 1.8, CI95% (1–3.3)). Leptospirosis cases were associated with cumulative rainfall (OR 1.12 (1.1–1.2)) and lower education (OR 1.04, CI95% (1–1.1)) and decreased with water supply (OR 0.7, CI95% (0.5–0.8)). Conclusions: Our findings highlight how climatic conditions, mobility restrictions, and socio-environmental inequities differentially shape infectious disease risks in island ecosystems. These results reinforce the need for integrated One Health surveillance that jointly addresses environmental change, social vulnerability, and infectious disease prevention. Full article

Background: Mycoplasma pneumoniae (MP) is an important pathogen responsible for community-acquired respiratory infections in children. Global surveillance during the COVID-19 pandemic revealed a marked decline in MP activity. However, beginning in early summer 2023, multiple regions across China reported an unexpected resurgence of MP infections, highlighting the need for detailed epidemiological analysis. Objective: This study aimed to characterize the epidemiological features of MP seropositivity among children in Chengdu, southwest China, and to compare its patterns between the COVID-19 pandemic and post pandemic periods. Methods: A retrospective analysis was conducted on MP testing data from 39,552 children with acute respiratory infections who were treated at West China Second University Hospital, Sichuan University, between January 2022 and December 2023. Results: Both the number of MP tests conducted and the seropositivity rate were significantly lower during the pandemic period than during the post pandemic phase. Compared with male children, female children were more susceptible to MP seropositivity. In terms of age distribution, seropositivity rates were highest among toddlers (1–3 years) and school-aged children (6–14 years). During the pandemic period (2022), MP antibody-positive cases were observed mainly between January and July, whereas in the post pandemic phase (2023), the epidemic peak shifted from June to December. Conclusions: In this single-centre study in Chengdu, nonpharmaceutical interventions (NPIs) implemented during the COVID-19 pandemic was associated with a marked reduction in MP transmission. After these restrictions were lifted, a rebound in MP antibody positivity was observed among children in Chengdu, compared to the NPI period (2022), the post-NPI period (2023) showed a later seasonal peak, which may represent a delayed return to pre-pandemic patterns. Continuous strengthening of MP surveillance is necessary to provide early warning of potential resurgences and outbreak risks. Full article

SARS-CoV-2, the causative agent of COVID-19, emerged in late 2019 and rapidly developed into a global health crisis. In this study, we analysed 173,194 SARS-CoV-2 genomes from the GISAID database to explore the intra-continental dynamics and distribution of variants across Africa between 2020 and 2024. We have identified 1377 distinct lineages, which were classified by clade to assess associations with infection and mortality rate. So, we conducted a Shannon entropy analysis to confirm the diversity and we applied a Correspondence Analysis (CA). Our findings revealed that one of the deadliest in Africa during the Delta wave, lineage AY.45 predominated in the South Africa cluster, whereas AY.34.1 drove transmission in the Atlantic West Africa cluster, underscoring regional heterogeneity. Furthermore, early in the pandemic, men exhibited a 39% higher risk of infection compared to women (aOR: 1.39, 95% CI [1.34–1.45]), particularly in association with clade G. By contrast, later stages were dominated by clade GRA, which disproportionately affected the elderly (≥70 years; aOR: 1.39, 95% CI [1.33–1.45]) and children (0–9 years; aOR: 1.26, 95% CI [1.20–1.33]). Our analysis highlighted that the pandemic on the African continent unfolded as a mosaic of epidemics shaped by diverse variants and regional epidemiological contexts. These findings emphasize the importance of genomic surveillance to capture local epidemic signatures and inform region-specific public health strategies. Full article

Healthcare artificial intelligence (AI) is moving from the laboratory into the infrastructure of care. As these systems become embedded in imaging, electronic health records, triage, and clinical decision support, their failures can affect not only individual encounters but also institutions and patient populations. Yet governance still centers on model development, local validation, and one-time compliance, with limited attention to cross-site failure after deployment. This article examines how public health preparedness can help close that gap. It presents a conceptual analysis grounded in two cases: a pneumonia-screening convolutional neural network that learned institutional confounders rather than portable clinical signals, and a widely deployed sepsis prediction model whose external performance and alert burden fell short of developer claims. Together, these cases reveal five governance features of systemic healthcare AI risk: population-level exposure, cascade effects across shared infrastructures, unequal vulnerability, delayed recognition, and coordination needs beyond any single institution. In response, we propose a tripartite framework combining stronger pre-deployment assurance, post-deployment surveillance with escalation thresholds, and tertiary response through investigation, rollback, remediation, and cross-site learning. The argument is not that AI failures are epidemics, but that high-impact clinical AI systems now function as critical digital health infrastructure requiring preparedness alongside lifecycle oversight. Full article

Network dismantling—the targeted removal of nodes to degrade large-scale connectivity—plays a central role in resilience analysis, epidemic containment, and systemic-risk mitigation. Recent work shows that dismantling performance depends strongly on mesoscale modular structure, suggesting that community-aware strategies may offer advantages over classical centrality-based heuristics. In this work, we perform a large-scale, systematic evaluation of dismantling strategies and introduce gateways as a new mesoscale dismantling concept. While similar experiments exist using degree- and betweenness-based dismantling strategies, we check a new strategy based on gateways, which capture asymmetric entry points into communities and generalize the notion of inter-community connectors. Furthermore, we process a massive dataset of 568,584 LFR benchmark graphs, covering a wide range of degree distributions, community sizes, and mixing parameters. For evaluation, we use both extrinsic (ARI, NMI, FMI, VI) and intrinsic (Modularity, Coverage, Performance, Average Conductance, Average Internal Density) metrics. We find that across parameter regimes and evaluation metrics, classical strategies (degree, betweenness, community connections) and gateway-based dismantling exhibit broadly similar performance. Our results also corroborate recent findings that dismantling effectiveness is robust to the specific partitioning algorithm and that inter-community connectivity plays a dominant role in global fragmentation. The evaluation provides large-scale evidence that gateway-aware dismantling captures an operationally relevant mesoscale mechanism as good as previous approaches and motivates further empirical studies on real networks and cost-aware settings. Full article

Getah virus (GETV), a mosquito-borne virus capable of infecting multiple economically important animal species, poses a potential epidemic risk. In May 2024, one pig farm from Heyuan, Guangdong Province, China, suffered reproductive disorders in sows and diarrhea in newborn piglets. Out of the six blood samples that were collected, three tested strongly positive for GETV, yielding a positivity rate of 50%. Moreover, a GETV strain (designated GDHYLC2024) was successfully isolated and identified. The viral titer of GDHYLC2024 was 10^7.687 TCID₅₀/mL in Vero cells. Its genome was composed of 11,688 bases in length. Interestingly, compared with GDHYLC23, it had no unique 32-nucleotide repeat insertion in 3′ non-coding region. However, phylogenetic analysis showed that GDHYLC2024 and GDHYLC23 clustered in genotype III. Animal infection experiments demonstrated that the GDHYLC2024 strain was highly pathogenic to 4-day-old piglets, which caused obvious clinical symptoms including fever, depression, anorexia, periorbital edema, ataxia, and three deaths out of a total of five individuals in the infection group. This study reported re-emergence of GETV in the same region of Guangdong Province, China. The above findings suggest that GETV continuously poses a threat to farm pig’s health and has genetic diversity. Full article