ABSTRACT Here, we report the emergence of a new mpox lineage, named B.1.6.1. This lineage is native to Peru and has been reported mainly in young and adult men with immunocompromised systems. It is characterized by 5 mutations: OPG019 (Q81stop), OPG025 (A21T, E34K), OPG121 (S65L), OPG064 (M424I) and OPG210 (S1590F).

ABSTRACT Crimean – Congo hemorrhagic fever (CCHF) is a severe tick-borne infection with high mortality, where macrophage activation and systemic inflammation drive pathogenesis. Prognostic biomarkers are crucial for early risk stratification. In this prospective study (April – July 2025), 60 confirmed CCHF patients (30 severe, 30 mild – moderate) and 50 healthy controls were enrolled. Soluble CD163 (sCD163) and interleukin-6 (IL-6) were measured by ELISA, while platelet-to-lymphocyte ratio (PLR) and systemic immune – inflammation index (SII) were derived from blood counts. Severe cases showed lower platelet counts, PLR, and SII, but higher AST, ALT, LDH, GGT, CK, direct bilirubin, fibrinogen, sCD163, and IL-6 than mild – moderate patients (all p < 0.05). Compared with controls, CCHF patients had elevated sCD163 and IL-6 (p < 0.001). sCD163 correlated negatively with platelet count (r=–0.453, p = 0.001) and positively with AST, ALT, and IL-6 (r = 0.953, p < 0.001), linking macrophage activation to systemic inflammation. ROC analysis showed sCD163 (AUC = 0.853) and IL-6 (AUC = 0.852) as accurate predictors of severe CCHF, with an sCD163 cutoff of 2.7 ng/mL yielding 96% sensitivity and 77% specificity. PLR and SII also distinguished severity but with lower accuracy. These findings highlight sCD163 and IL-6 as strong early prognostic biomarkers that may improve clinical assessment and guide timely therapeutic interventions in CCHF.

ABSTRACT Schistosomiasis is a parasitic disease primarily controlled by Praziquantel-based Mass Drug Administration (MDA) targeting school-aged children. This study aimed to generate a high-resolution schistosomiasis prevalence map in a region with regular MDA in Madagascar, identify at-risk groups, assess population knowledge, and explore risk factors to support alignment with WHO guidelines. Conducted between July and October 2022 in the District of Vatomandry, Madagascar, this cross-sectional study included participants aged five and older. Point-of-Care Circulating Cathodic Antigen testing determined infection prevalence. A choropleth map was generated to show the geographical distribution of schistosome infection across local communities. Individual risk factors were assessed using hierarchical Poisson regression. The study included 1,215 households (5,200 participants) from 42 communities revealing a high overall prevalence of 59%. Adjusted prevalence ratios (PR) indicated higher infection risks for farmers (PR = 1.17, 95% CI: 1.09–1.25) and older age groups (≥38 years: PR = 1.34, 95% CI: 1.16–1.55; against ≤15 years), while participants with higher education or knowledge about schistosome transmission showed a reduced risk (PR = 0.88, 95% CI: 0.78–0.99). The results show high schistosome prevalence in adults, emphasizing the need to adapt strategies in endemic countries to meet the WHO’s 2030 goal of eliminating schistosomiasis as public health problem.

ABSTRACT Dengue fever is a growing global health concern, especially in regions like the United Arab Emirates (UAE), where environmental factors and high levels of international travel increase the risk of outbreaks. Despite this, public awareness and adoption of preventive measures remain understudied. This cross-sectional study aimed to assess the public’s knowledge, attitudes, and practices (KAP) regarding dengue fever and its prevention. A validated online questionnaire was distributed to 1106 individuals using convenience sampling. The results revealed significant knowledge gaps, with only 24.6% correctly identifying dengue as a viral infection and 24.5% recognizing mosquito transmission. Median knowledge scores were higher among participants with elementary education (median = 13, IQR: 13-18), postgraduate degrees (median = 12, IQR: 8-15) than among those with other education levels, and higher among those with health insurance (median = 11, IQR: 10-13) than among those without insurance. Attitudes varied significantly based on education and residency, while regression analysis showed that male gender, older age, and smoking were associated with higher practice scores. These findings emphasize the need for targeted educational campaigns and public health interventions to improve awareness and engagement with dengue prevention, particularly in vulnerable demographic groups.

ABSTRACT We analyzed the geographic risk of Lyme borreliosis taking into account the biogeography of tick vectors and wild carrier hosts, together with environmental and anthropogenic factors. Four pathogeographical scenarios were set in order to represent the contribution of vectors and hosts in the spatial zoonotic risk. For that propose, we built distribution models based on the occurrence of Lyme borreliosis cases in humans and ixodid vectors. Besides Ixodes species, we considered other ixodid ticks with potential to be vectors. These models were combined through fuzzy logic operators, according to the criteria established in each scenario. Finally, the transmission risk model for Lyme borreliosis which best fitted its global distribution was selected. The risk model selected considered ixodid vectors and mammal carriers as explanatory variables together with environment and anthropogenic factors. Ixodes species contributed to explain the geographical risk of Lyme borreliosis to a larger extent than other ixodid ticks. The risk model described regions with Lyme borreliosis transmission risk where its presence is still uncertain, such as northern Africa and inland areas of western U.S.A. Likewise, our model indicated favorable conditions for the presence of human cases in northern latitudes beyond its endemic distribution. Applying this multi-scenario methodology approach have led us to a risk model, in which the diversity of ixodid vectors and carrier hosts might modify the spatial risk without a geographical limitation.

ABSTRACT Crimean-Congo hemorrhagic fever (CCHF) is a potentially fatal zoonotic disease caused by a tick-borne virus from the genus Orthonairovirus. This study investigates the feasibility of using high-density lipoprotein (HDL) and eosinophils as novel parameters in determining the prognosis of the disease. Sixty patients with CCHF admitted to our hospital’s infectious diseases ward between March and September 2022 were included in the study. The patients’CCHF reverse transcriptase (RT)-PCR tests performed on blood samples were positive. Their recorded clinical findings and routine laboratory, biochemistry, complete blood count, and coagulation tests were investigated retrospectively. The patients’demographic, clinical, and laboratory data were recorded, and the disease severity was scored. The patients were then assigned into one of three groups depending on that severity. HDL, low-density lipoprotein (LDL), cholesterol, and triglyceride values were compared between the groups. Negative correlations were observed between HDL, LDL, and cholesterol values and increasing disease severity, while no difference was determined between the groups’ triglyceride values. Eosinophil values were also negatively correlated with disease severity between the three groups. The most marked correlations with disease severity were observed in HDL and eosinophils. New scoring systems for determining the prognosis of CCHF have been investigated in recent years. HDL and eosinophil levels may represent the most important prognostic parameters in these novel scoring systems.

ABSTRACT Cases of travel-associated Legionnaires’ disease (TALD) are frequently reported in Italy. From 1987 to 2021, 61 cases of TALD were linked to 22 hotels in a municipality in northern Italy. Legionella pneumophila serogroup 1 (Lp1) strains isolated from both patients and hotel water systems were identified as sequence type (ST) 901, a genotype rarely associated with travel-related infections in Italy or elsewhere. Whole-genome sequencing was used to analyze 41 isolates, and phylogenetic relationships were inferred by core genome multilocus sequence typing (cgMLST), single nucleotide polymorphisms (SNP) and pangenome analyses. The Lp ST901 isolates were found to form a clade characterized by some accessory genomic islands (AGI) already described in other epidemic strains, such as Alcoy, Corby, Paris and Philadelphia; other islands, containing either transposase/recombinase or transcriptional regulator factors or Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-cas systems, were specific to Lp ST901. Lp ST901 also appears to have undergone possible recombination with other strains, such as Lp ST47 (Lorraine strain). Additionally, CRISPR-Cas systems may have contributed to the protection of Lp ST901 from external dangers, while the colonized hotel water systems may have provided an ideal environmental protective niche. Our findings highlight that Lp ST901 has public health significance and deserves attention in Legionnaires’ disease surveillance and risk assessment.

ABSTRACT Our unpreparedness in responding to the prompt emergence of COVID-19 in its early stage of outbreak, especially the lack of rapid and early diagnostic techniques for mass screening which should have been prioritized, contributed to the virus’ spread alongside other factors. This article provides an overview of the common diagnostic techniques with special focus on the reported and/or authorized point-of-care methods for early COVID-19 diagnosis, including lateral flow assays and localized surface plasmon resonance-based approaches. The inherent limitations of these techniques are critically examined. We then propose a potentially more competent alternative, i.e. direct detection of viral particles with aptamer-conjugated gold nanoparticles in liquid solution in combination with noninvasive breath sampling or saliva sampling, for further improvement in early diagnostic capability for infectious respiratory diseases like COVID-19. In addition, an integration of air sampling with in-situ direct colorimetric detection of viral particles could represent a potential option for airborne virus detection, thus minimizing the transmission of infectious diseases and their impact on the economy and life in the future.

ABSTRACT Neglected tropical vector-borne diseases (NTVBDs) pose a significant global health challenge, disproportionately affecting low- and middle-income countries. This review begins by defining NTVBDs and their classification criteria, providing a comprehensive overview of their geographical distribution, vectors, and causative agents. Climate change, socioeconomic factors, and land-use changes are changing NTVBD transmission dynamics, with temperature increases expanding vector ranges and creating new transmission hotspots in previously unsuitable regions. The review examines both established vector control approaches and emerging technologies, including CRISPR-based gene editing, artificial intelligence, and microbiome manipulation for NTVBD control. Housing improvements have shown particular promise, with studies demonstrating significant reductions in vector presence through structural interventions. Sustainable control programs emphasize community-based and culturally appropriate interventions, with gender-responsive approaches enhancing both intervention coverage and women’s economic empowerment. The review explores the integration of NTVBD control with existing health systems through formal coordination mechanisms and sustainable financing frameworks beyond traditional donor-dependent models. Recent field initiatives addressing the psychological dimensions of NTVBDs highlight the importance of comprehensive approaches that extend beyond physical symptoms. To address the complex challenges of NTVBDs in a rapidly changing world, the review concludes that a multidisciplinary approach integrating technological innovation with social and ecological considerations is essential. Future research should examine the long-term effects of climate change on NTVBD dynamics, develop broadly protective vaccines, optimize integrated control strategies, and investigate innovative funding mechanisms for resource-limited settings.

ABSTRACT Tuberculosis (TB) is a highly infectious disease caused by Mycobacterium tuberculosis. The World Health Organization (WHO) has reported more than 8 million new or relapse TB cases and 1.25 million deaths in 2023. Even though the global End TB strategy implemented by WHO has reduced the TB incidence rate between the years 2015 and 2023 up to 8.3%, TB remains one of the leading infectious causes of death worldwide. Active tuberculosis can affect any part of the body, and the clinical symptoms include fever, weight loss, and night sweats, whereas latent TB does not show any clinical symptoms. One of the significant concerns regarding the control of TB is the reservoir nature of latent tuberculosis. The Bacillus Calmette-Guerin (BCG) vaccine helps control TB and is still used globally to combat it. Currently, two methods are primarily used to identify tuberculosis infection: the Tuberculin Skin Test (TST) and the Interferon-Gamma Release Assay (IGRA). A significant disadvantage of these two methods is the inability to differentiate between latent and active tuberculosis. Accurate and timely diagnosis of TB is essential for effective management, mainly due to the emergence of multidrug-resistant strains. Specific biomarkers are required to evaluate tuberculosis infection, and novel biomarkers are needed to develop new diagnostic methods for tuberculosis. This article presents a brief review of recent developments in TB diagnostics, covering immunological, molecular, and monoclonal antibody-based platforms. The review also discusses the emerging role of artificial intelligence and deep machine learning platforms as complementary diagnostic tools.