Background: To describe epidemiological characteristics and perform a SARS-CoV-2 genomic surveillance in the southeastern region of São Paulo state. Methods: During the first months of 2022, we compared weekly SARS-CoV-2 infection prevalence considering age, Ct value and variants lineages. Results: An increase in the number of SARS-CoV-2 positive cases until the fourth epidemiological week were observed. From the 4th epidemiological week onwards, the number of tests for SARS-CoV-2 diagnosis began to decrease, but the number of positive samples for SARS-CoV-2 remained high, reaching its most expressive level with a rate of 60% of infected individual cases. In this period, we observed a growing increase in SARS-CoV-2 infection within the age group 0-10 throughout the epidemiological weeks, from 2.8% in the 1st epidemiological week to 9.2% in the 8th epidemiological week. We further observed significantly higher Ct values within younger patients samples compared to other older age groups. According to lineage assignment, SARS-CoV-2 (BA.1) was the most prevalent (74.5%) in the younger group, followed by BA.1.1 (23%), BA.2 (1.7%) and Delta (1%). Phylogenetic analysis showed that BA.2 sequences clustered together, indicating sustained transmission of this Omicron VOC sublineage by that time. Our results suggest the initial dissemination steps of the Omicron’s sublinage BA.2 into the younger group, due specific genomic features of the detected sequences. Conclusion: These data provide interesting results related to the spread, emerging and evolution of the Omicron variant in the Southeast Brazilian population.

Influenza A viruses (IAV) are still a cause of concern for public health and veterinary services worldwide. With (-) RNA-segmented genome architecture, influenza viruses are prone to reassortment and can generate a great variety of strains, some capable of crossing interspecies barriers. The latest 2009 pandemic and numerous reports of zoonotic infections worldwide show that these capabilities cannot be underestimated. Seasonal IAV strains continuously spread from humans to pigs, leading to multiple reassortation events with strains endemic to swine. Due to high adaptability to human, reassortant strain based on “human-like” genes could potentially be a carrier of avian origin segments responsible for high virulence, hence become next pandemic strain with unseen pathogenicity. We must foresee this kind of event, paying close attention to the surveillance of common human-animal interfaces. The rapid evolution of sequencing methods has provided a fast and cost-efficient way to assess the genetic diversity of IAV. In this study, we investigated the genetic diversity of swine influenza viruses (swIAVs) collected from Polish farms. A total of 376 samples were collected from 11 farms. The infection was confirmed in 112 cases. The isolates were subjected to next-generation sequencing (NGS), resulting in 93 full genome sequences. Phylogenetic analysis classified 59 isolates as genotype T (H1avN2g) and 34 isolates as genotype P (H1pdmN1pdm), all of which had an internal gene cassette (IGC) derived from the H1N1pdm09-like strain. These data are consistent with evolutionary trends in European swIAVs. The applied methodology proved to be useful in monitoring the genetic diversity of IAV at the human-animal interface.

Occupational accidents, despite continuous safety updates, are still a scourge in the occupational and forensic spheres, constituting, among other things, the subject of a large share of litigation. Demographic data can help to understand the areas where the application of health surveillance is lacking. This meta-analysis sets out to analyze data from studies on accidents at work, focusing on the correlation between the areas in which accidents occur and whether or not personal safety equipment is used, about the different regulations in force. For the selection of the data, a systematic review was carried out according to the PRISMA guidelines, with the primary objective of identifying the trend of occupational accidents in specific geographical areas, which differ in terms of the attention paid to preventive aspects. The data we highlighted showed, regarding the type of accident, substantial differences between low-income countries and industrialized countries (stratified according to the Human Development Index) and, an overall indifference as to whether or not individual safety devices were used, revealing that, despite the continuous normative evolution in the field of safety at work, even today, the investigative data on the actual application of the regulations, during accidents at work, is underestimated and little researched.

Viral hepatitis remains one of the largest public health concerns worldwide. Especially in Central Africa, information on hepatitis virus infections has been limited, although the prevalence in this region has been reported to be higher than the global average. To reveal the current status of hepatitis B and C viruses (HBV and HCV) infections and the genetic diversity of the viruses, we conducted longitudinal surveillance in Gabon. We detected 22 HBV and 9 HCV infections in 2,047 patients with febrile illness. Genetic analyses of HBV identified subgenotype A1 for the first time in Gabon and an insertion generating a frameshift to create an X-preC/C fusion protein. We also revealed that most of the detected HCVs belonged to the “Gabon-specific” HCV subtype 4e (HCV-4e), and the entire nucleotide sequence of the HCV-4e polyprotein was determined to establish the first reference sequence. HCV-4e strains possessed resistance-associated substitutions similar to those of other HCV-4 strains, indicating that the use of direct-acting antiviral therapy may be complex. These results provide a better understanding of the current situation of hepatitis B and C virus infections in Central Africa, and will help public health organizations develop effective countermeasures to eliminate chronic viral hepatitis in this region.

Abstract: Our research analyzed the characteristics of phase IV clinical trials in oncology using data from the ClinicalTrials.gov registry. The included trials were conducted between January 2013 and December 2022 and were examined for key characteristics, including outcome measures, interventions, sample sizes, and study design, different cancer types, and geographic regions. Our analysis included 368 phase IV oncology studies. We found that 50% of these studies aimed to examine both safety and efficacy, while 43.5% only reported efficacy outcome measures, and 6.5% only described safety outcome measures. Only 16.9% of studies were powered to detect adverse events with a frequency of 1 in 100. Targeted therapies accounted for the majority of included studies (53.5%), with breast (32.91%) and hematological cancers (25.82%) being the most frequently investigated malignancies. Most phase IV oncology studies lacked sufficient power to detect rare adverse events due to their small sample sizes and instead focused on effectiveness. To ensure that there is no gap in drug safety data collection and detection of rare adverse events due to limited phase IV clinical trials, there is a significant need for additional education and participations by both health care providers and patients in spontaneous reporting processes.

The Work Ability Index (WAI) is the most widely used questionnaire for the self-assessment of working ability. Because of its different applications, shorter versions, and widespread use in healthcare activities, it is worthwhile assessing its characteristics. The WAI was distributed online among the workers of a healthcare company; the results were compared with data contained in the workers' personal health records and with absence registers. 340 out of 575 workers (59.1%) participated; 6.5% of them reported poor work ability. Exploratory factor analysis indicated that the one-factor version best described the characteristics of the WAI. The scores of the complete WAI, the shorter form without the list of diseases, and the minimal one-item version (WAS) had equal distribution and were significantly correlated. The WAI score was inversely related to age and significantly lower in women than in men, but it was higher in night workers than in colleagues due to the probable effect of selective factors. The WAI score was also correlated with absenteeism, but no differences were found between males and females in the average number of absences, suggesting that cultural or emotional factors influence the self-rating of the WAI. Workers tended to overreport illnesses in the online survey compared to data collected during occupational health checks. Musculoskeletal disorders were the most frequently reported illnesses (53%). Psychiatric illnesses affected 21% of workers and had the greatest impact on work ability. Multilevel ergonomic and human factor intervention seems to be needed to recover the working capacity of healthcare workers.

Human violence recognition is an area of great interest in the scientific community, given its broad spectrum of applications, especially in video surveillance systems, since detecting violence in real-time could prevent criminal acts and save lives. Despite the number of existing proposals and research, most focus on the precision of results, leaving aside efficiency and its practical implementation. Thus, this work proposes a model that is effective and efficient in recognizing human violence in real-time. The proposed model consists of three modules: a first module called Spatial Motion Extractor (SME), in charge of extracting regions of interest from a frame; a second module called Short Temporal Extractor (STC), whose function is to extract temporal characteristics of rapid movements, finally the Global Temporal Extractor (GET) module, responsible for identifying long-lasting temporal features and fine-tuning the model. The proposal was evaluated regarding efficiency, effectiveness, and ability to operate in real-time. The results obtained on Hockey, Movies, and RWF-2000 datasets demonstrated that this approach is highly efficient compared to other alternatives. A VioPeru dataset was created to validate real-time applicability with violent and non-violent videos captured by real video surveillance cameras in Peru. The effectiveness results in this dataset outperformed the best existing proposal. Therefore, our proposal has contributions in efficiency, effectiveness, and real-time.

(1) Influenza causes a significant health and socio-economic burden every year, and health personnel (HP) are at higher risk of exposure to respiratory pathogens than general population. (2) The study purpose was to describe and compare influenza vaccine uptake and its prognostic factors among Medical Doctors (MDs) and Non-Medical Health Personnel (NMHP) vs Non-HP (NHP). We analysed 2014-2018 data (N=105,608) from the Italian Behavioural Risk Factor Surveillance System PASSI that, since 2008, has been collecting health-related information continuously in sampled adults. (3) MDs and NMHP represented, respectively, 1.1% and 4.6% of the sample. Among HP, 22.8% (CI 19.8% - 26.1%) of MDs and 8.5% (CI 7.5% - 9.5%) of NMHP reported to have been vaccinated vs 6.3% (CI 6.1% - 6.5%) in NHP. This difference is confirmed in the three categories (MDs, NMHP, NHP), even more across age groups: in 18-34yy, respectively, 9.9%, 4.4%, 3.4% vs 28.4%, 13.9%, 10.6% in 50-64yy. PASSI surveillance shows an increasing influenza vaccination uptake over time, especially among MDs (22.2% in 2014 vs 30.5% in 2018). (4) Despite such increase, especially among younger HP, influenza vaccination uptake is low. Even more under pandemic scenarios, these figures represent key information to address effective strategies for disease prevention and health promotion.

This study conducted an extensive analysis of campylobacteriosis surveillance in Portugal from 2009 to 2021, aiming to investigate demographic shifts, seasonal variations, and antimicrobial resistance (AMR) within Campylobacter isolates. Surveillance network and sentinel laboratory-based system data revealed a substantial under-notification of campylobacteriosis cases, suggesting an underestimated disease burden. A paradigm shift was observed in notification rates, with a notable prevalence among the pediatric population, particularly in children aged 1-4 years, diverging from European reports. However, the study also highlighted an emerging trend of Campylobacter infections in younger adults (15-44 years). The study unveiled a unique seasonal distribution of cases, defying typical summer peaks seen elsewhere. AMR analysis revealed extremely to very high-level resistance to ciprofloxacin and tetracycline, both in C. jejuni (93.7% and 79.2%, respectively) and in C. coli (96.5% and 93.2%, respectively), stable throughout the studied period (2013-2021). C. coli also exhibited significantly higher resistance to erythromycin, gentamicin, ampicillin, amoxicillin-clavulanic acid (decreased resistance), and ertapenem compared to C. jejuni (P<0.001). In conclusion, the study highlights the need for enhanced surveillance efforts and emphasizes worrying AMR levels. The implementation of WGS-based surveillance is recommended to attain a more profound comprehension of disease patterns and the evolving landscape of AMR.

The emergence of SARS-CoV-2 subvariant BA.2.86, also known as Pirola, has raised concerns about its transmissibility, virulence, and immune escape. The aim of this letter is to address the current evidence on the origin, spread, and characteristics of Pirola, and discuss its implications for public health and vaccine development. The need for enhanced surveillance, genomic sequencing, and epidemiological studies to monitor the evolution and impact of Pirola and other SARS-CoV-2 variants are highlighted in this letter along with the importance of global cooperation and coordination to prevent and control future outbreaks of this novel coronavirus strain.

Dengue fever remains a persistent threat in Mexico, with cyclical outbreaks driven by the circulation of multiple dengue virus serotypes. The sudden emergence of DENV-3 in 2023 raised questions about its epidemiological significance and potential implications for disease severity. This study aimed to characterize dengue virus serotypes by age and their association with disease severity, considering sex, time, and the origin of clinical samples. A retrospective analysis was conducted on dengue laboratory results obtained from the epidemiological surveillance system in Mexico during 2023. Descriptive statistics summarized the prevalence of dengue virus serotypes, while bivariate analysis utilized an adjusted Chi-squared test to assess associations with demographic variables. Multivariate analysis using unconditional logistic regression evaluated the relationship between dengue virus serotypes and disease severity, adjusting for potential confounders. Additionally, co-infections were identified and analyzed. Results revealed DENV-3 as the most prevalent serotype (63.9%), with co-infection involving two serotypes detected in 0.75% of cases. DENV-2 exhibited a higher median age compared to other serotypes. Pregnant women in their last trimester faced elevated risks of hospitalization and mortality. Multivariate analysis indicated a stronger association between DENV-2 and hospitalization. However, co-infection did not significantly influence disease severity. The unexpected predominance of DENV-3 underscores the dynamic nature of dengue virus circulation in Mexico. Despite its prevalence, DENV-2 demonstrated a stronger association with hospitalization, highlighting the importance of serotype-specific surveillance and management strategies.

We aim to evaluate efficiency of two American surveillance systems for monitoring the spread of antimicrobial-resistant (AMR) gonorrhea among men who have sex with men (MSM) using the novel continuous-time agent-based model of gonorrhea transmission. The model was developed using the simulation modelling tool AnyLogic and accounts for susceptible and resistant strains of N. gonorrhoeae, symptomatic and asymptomatic infection and various routes of transmission between different anatomical sites. The model was calibrated using a Bayesian calibration approach. The surveillance systems are the Gonococcal Isolate Surveillance Project (GISP) and the enhanced Gonococcal Isolate Surveillance Project (eGISP). We calculated accuracy, sensitivity, specificity and estimation error for each surveillance system based on the number of isolates submitted in 2018. We also varied that number to see its effect on the outcomes. Our results show that the accuracy of eGISP was between 66% and 92%, while GISP demonstrates low accuracy between 44% and 48%. We also determined that increasing the number of isolates results in improved performance for eGISP, while GISP is not particularly sensitive to it.

(1) Background: The HIV subtype D is generally associated with a faster decline in CD4+ T cell counts, a higher viral load, and a faster progression to AIDS. However, it is still poorly characterized in Brazil. In this study, we used genomics and epidemiological data to investigate the transmission dynamics of HIV subtype D in the state of Bahia, Northeast Brazil. (2) Methods: to achieve this goal, we obtained four novel HIV-1 subtype D partial pol genome sequences using the Sanger method. To understand the emergence of this novel subtype in the state of Bahia, we used phylodynamic analysis on a dataset comprising 3,704 pol genome sequences downloaded from the Los Alamos database. (3) Results: Our analysis revealed three branching patterns, indicating multiple introductions of the HIV-1 subtype D in Brazil from the late 1980s to the late 2000s and a single introduction event in the state of Bahia. Our data further suggest that these introductions most likely originated from European, Eastern African, Western African and Southern African countries. (4) Conclusion: Understanding the distribution of HIV-1 viral strains and their temporal dynamics is crucial for monitoring the real-time evolution of circulating subtypes and recombinant forms, as well as for designing novel diagnostic and vaccination strategies. We advocate for a shift to active surveillance, to ensure adequate preparedness for future epidemics mediated by emerging viral strains.

In today's world, wherein more than 80% of world trade is carried out by maritime routes, the safety and security of the seas where this trade takes place is of vast importance for nations and the in-ternational community. For this reason, ensuring the sustainable safety and security of the seas has become an integral part of the mission of all maritime-related entities. The utilization of big data extracted from the seas and maritime activities into meaningful information with artificial intelli-gence applications and developing applications that can be used in maritime surveillance will be of great importance for augmenting maritime safety and security. In this article, data sources which can be used by a maritime surveillance system based on big data and artificial intelligence tech-nologies and which can be established around sensitive sea areas and critical coastal facilities, are identified and a model proposal using this maritime big data is put forward.

Skin and soft-tissue infections (SSTI) are common cases of hospital-acquired infections with aetiologic agents exhibiting antimicrobial resistance (AMR). We determined the prevalence, proportion of laboratory-investigated cases, AMR-profiles, and factors associated with SSTI and multi-drug resistance (MDR). This study was based on archived data of patients suspected of SSTI from 2019-2021 at Jinja Regional Referral Hospital. The analysis involved 268 randomly selected patient reports. Prevalence of SSTI was 66.4%. Laboratory-investigated cases were 14.11%. Staphylococcus aureus (n=51) was the most isolated organism. MDR pathogens explained 47% of infections. Methicillin-resistant S. aureus was up to 44%. In addition, 61% of Gram-negatives had the potential to produce extended-spectrum beta-lactamases, while 27% were non-susceptible to carbapenems. Ward of admission was significantly associated with infection (aPR=1.78, 95% CI: 1.003-3.18, p-value=0.04). Age category (19-35) was an independent predictor for MDR infections (aPR=2.30, 95%CI:1.02-5.23, p-value=0.04). The prevalence is relatively high with MDR pathogens responsible for almost half of the infections. Routine use of culture and sensitivity testing should be done for proper infection management. Gentamicin and ciprofloxacin can be considered for empirical management of emergency SSTI suspected of S. aureus. Recognizing SSTI under the Global Antimicrobial resistance Surveillance System would lead to improved preparedness and response to AMR.

Herpes B virus (BV) is a zoonotic virus which can be transmitted from macaques to humans, which is often associated with high mortality rates. Because macaques often exhibit asymptomatic infections, individuals who come into contact with these animals face unexpected risks of BV infections. Serological test is widely performed to investigate BV infections. However, the assay’s sensitivity and specificity appeared to be inadequate, and it does not necessarily indicate ongoing viral shedding. Here, we developed LAMP and qPCR assays aiming to detect BVs with high sensitivity and specificity in various macaque species and validated them using oral swab samples collected from 97 wild cynomolgus macaques living in Thailand. Our LAMP and qPCR assays detected more than 50 and 10 copies of the target sequences per reaction, respectively. The LAMP assay could detect BV within 25 min, indicating its advantages for the rapid detection of BV. Collectively, our findings indicated that both assays developed in this study exhibit advantages and usefulness for BV surveillance and diagnosis of BV infections in macaques. Furthermore, for the first time, we determined the partial genome sequences of BVs detected in cynomolgus macaques in Thailand. Phylogenetic analysis revealed the species-specific evolution of BV within macaques.

Surveillance is the systematic data collection, analysis, and interpretation essential to planning and implementing control activities. The lack of success in control and surveillance elsewhere for the Ae. aegypti mosquito demands developing new accessible and effective strategies. This work aimed to develop and evaluate an adhesive and lure trap for household indoor and outdoor surveillance of Ae. aegypti. Based on a bibliographic review, four compounds with significant attraction percentages for Ae. aegypti were considered. Our more effective blend was determined by preliminary bioassays using the high-throughput screening system (HITSS) and 90 × 90 cm mosquito cages. We designed a low-cost, pyramid-shaped, sticky cardboard trap to incorporate the selected blend. Semi-field 2 x 2 m cages and field tests were conducted to evaluate its effectiveness through mosquito capture percentages. In laboratory tests, blend number 2 presented an attraction percentage of 47.5 ± 4.8%; while in semi-field cages, a 4-inch, 110-v powered fan was used to disperse the attractants, then a similar capture percentage of 43.2 ± 4.0 % was recorded. Field evaluation of the at-house indoor environment and comparing it with the golden standard BG-Sentinel trap recorded interesting results, i.e., an average of our prototype 6.0 ± 1.5 trapped mosquitoes versus 10.0 ± 2.6. In most Latin American countries, there is a lack of formal and accessible strategies for monitoring adult populations of Ae. aegypti, therefore, must develop tools that reinforce entomological surveillance methods.

Owing to the upsurge in the number of endangered species and understanding animal patterns in general as well as population demographics; the monitoring of wildlife species is an essential for the conservation and safety of animals. In order to organize and manage the reserves, the nature bequeaths to us, we need to have hands-on information of their population and food trends, conditions where they survive and other species in the ecosystem. The paper presents a vision-based approach to monitor wildlife using an aerial platform. A quad-rotor based aerial platform is used for the very first time for this purpose. Field imaging is done using a digital cellphone camera mounted on the platform to acquire video of horses in the field. Two techniques, Lucas-Kanade and Horn-Schunck methods are applied on the acquired set of images and the results are compared. Noise due to fluctuations and light conditions are minimized using Gaussian and HSV filters. Experiments show results with an absolute mean difference of 2.84 pixels and 8.50 pixels for changes in X and Y directions respectively for the two approaches.

Dirofilaria immitis and D. repens are the two most widespread and important species of mosquito-borne nematodes, posing a significant threat to veterinary health, particularly affecting canines and felines. While D. immitis causes cardiopulmonary dirofilariasis, D. repens causes subcutaneous infections in dogs and other carnivores. Despite extensive knowledge about the aforementioned parasites, little is known about their natural vectors in Serbia. Thus, the aim of this study was to: i) further map out Dirofilaria sp. hotspots in the Vojvodina Province, ii) detect positive mosquito species which can provide insights in how the nematodes spread and adapt to the environmental conditions, and iii) analyze the blood fed mosquitoes females of species found infected to identify the potential source of parasite infection. A total of 2,902 female mosquitoes were collected across 73 locations during 2021 and 2022. Molecular biology methods, based on conventional PCR, were used to analyze non-blood fed (2,521 specimens) and blood fed (381 specimens) mosquito females, in order to detect filarial nematode presence and identify blood meal sources respectively. When the parasite genome was detected, the amplicon (COI gene, 650 bp fragment) was sent for Sanger sequencing, further confirming the presence of nematodes and species assignation. D. immitis was detected in three Culex pipiens mosquitoes collected in XXXX (location and date), while Setaria tundra was detected in Aedes vexans and Aedes caspius. This work adds two new locations where D. immitis occurs in Vojvodina, and is the first report of S. tundra on the territory of Serbia. Blood meal analysis provided insights into the preferences of mosquitoes that were positive for Dirofilaria sp. and S. tundra.

The social- and self-directed behaviours of two golden lion tamarins (Leontopithecus rosalia) was investigated while having residence in the tropical house of Aalborg Zoo, Denmark. The behaviour of the female had been distinct from the male since 2018. Despite several diagnostic examinations and medicinal treatments, the cause of the aberrant and apparently stereotypical behavioural patterns remained undetermined, which initiated this study. The pair were recorded throughout a predetermined observation period and these recordings were analysed to illuminate the behaviours of the individuals. The results showed that there were differences in the type, frequency, and durations of both social- and self-directed behaviours between the sick female and the healthy male. The female expressed both social- and self-directed behaviours more frequently and for longer durations, while the male were more socially reserved and did not engage in social behaviours as frequently. Furthermore, subsequent necropsy of the female revealed uro-genital disease.

This review article focuses on the role of Artificial Intelligence (AI) in transforming healthcare in Africa, specifically in combatting infectious diseases, neglected tropical diseases (NTDs), and antimicrobial resistance. We provide a comprehensive overview of the significance of AI in the healthcare industry, highlighting its urgency and importance in addressing these specific health challenges in Africa. We begin by discussing the role of AI in infectious disease surveillance and outbreak detection. We explore how AI technology can be employed for real-time tracking and prediction of outbreaks, providing examples of successful AI applications in infectious disease surveillance within the African context.Next, we examine the potential of AI-enabled diagnosis and treatment for faster and more accurate diagnoses of infectious diseases and NTDs. We highlight specific examples of AI applications in diagnosing and treating these diseases in Africa, showcasing the potential of AI to improve clinical outcomes and save lives.Furthermore, we focus on how AI-driven drug discovery and development can expedite the search for new treatments for infectious diseases and combat antimicrobial resistance. We present examples of AI applications in drug discovery within the African context, illustrating the potential for AI to revolutionize the development of effective therapeutics.In addition, we delve into how AI-powered public health interventions can enhance the design and implementation of targeted interventions. We explore how AI can optimize resource allocation and facilitate data-driven decision-making processes, providing examples of AI applications in public health in Africa.Finally, we address the challenges and limitations of implementing AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. We discuss potential barriers and ethical concerns surrounding AI applications in healthcare, aiming to encourage informed and responsible utilization of AI technologies.Overall, this review emphasizes the importance and potential of AI in combatting infectious diseases, NTDs, and antimicrobial resistance in Africa. It positions AI as a catalyst for revolutionizing healthcare in the region, leading to more effective disease surveillance, diagnosis, treatment, drug discovery, and public health interventions.

Unmanned vehicles (UVs) have become increasingly important in various scenarios of civil and military operations. The present work aims at the conceptual design of a modular Amphibious Unmanned Ground Vehicle (A-UGV), that can be easily adapted for different types of land and/or water missions, with low monetary cost (<5k€, without sensors). Basing the design on the needs highlighted in the 2021 review of the Strategic Directive of the Portuguese Navy, the necessary specifications and requirements are established for two mission scenarios. Then a market research analysis focused on vehicles currently available, and their technological advances, is conducted to identify existing UVs solutions and respective characteristics/capabilities of interest to the current work. To study and define the geometry of the hull and the configuration of the A-UGV itself, preliminary computational structural and fluid analyses are carried out to ensure it complies with the specifications initially established. As a result, one obtains a fully electric vehicle, with approximate dimensions of 1050×670×450mm (length-width-height), enabled with 6×6 traction capable of reaching 20km/h in land, possesses amphibious capabilities of independent propulsion in water up to 8kts, and with an estimated autonomy of over 60 minutes.

Several pathotypes of enteric E. coli have been identified. The group represented by Shiga toxin-producing E. coli (STEC) is of particular interest. Raw milk and raw milk products are significant sources of STEC infection in humans; therefore, identifying pathogens at the herd level is crucial for public health. Most national surveillance programs focus solely on raw milk and raw milk cheeses that are ready for retail sale, neglecting the possibility of evaluating the source of contamination directly at the beginning of the dairy chain. In order to assess the viability of new molecular methodologies applied to raw milk filters enabling the identification of the presence of STEC serotypes in milk production and apply the same methods to identify the presence of these pathogens in calf feces we analyzed, through a commercial real-time PCR assay, a total of 290 samples coming from 18 different dairy herds; 88 bulk tank milk (BTM), 104 raw milk filters (RMF) and 98 calves’ feces samples. In total 3.4% of BTM, 41.4% of RMF and 73.4% of calves’ feces tested positive for stx presence, supporting our hypothesis that BTM is not a suitable matrix to assess the STEC presence at herd level, underestimating it. Our conclusion is that the surveillance program needs critical and extensive improvements such as RMF and calves’ feces analysis implementation in order to be more efficient in detecting and preventing STEC infections. The epidemiology of these infections and the characteristics of the pathogen clearly show how a One Health approach will be pivotal to improve our capabilities to control the spread of these infections.

Healthcare personnel must face two problems of growing importance: violence in the workplace and the loss of work ability due to ageing of the workforce. Studying the relationship between these two phenomena can help to prepare effective prevention measures. In a public health company, we asked nurses to self-assess their work ability using the Work Ability Index (WAI) and we analysed the relationship between this indicator and the violence experienced in the previous and following years. 321 out of 344 nurses (99.3%) participated. In a logistic regression model, the WAI score was a significant protective factor for violence experienced in the previous year (OR=0.94 CI95%=0.90; 0.98 p<0.01) and in the following year (OR=0.88 CI95%=0.84; 0.92 p<0.01). In a hierarchical logistic regression model, social support acted as a protective factor (OR = 0.87 CI95% = 0.79; 0.95 for violence experienced in the previous year), while occupational stress was a significant determinant of the risk of aggression (OR=3.65 CI95%=1.90; 7.03 in the previous year, OR=3.54 CI95%=1.801; 6.947 in the following year). The difficulties that nurses encounter in carrying out their growing work demands in an environment that is not promptly adapted to their changing physical and mental conditions can lead to an increased risk of violence. Prevention of workplace violence should include organizational and ergonomic measures that reduce stress and increase staff support and work ability.

The 2020-2025 Dietary Guidelines for Americans recommends limiting intakes of saturated fat and added sugars (SF/AS) to 88% of the representative sample of U.S. adults. The top sources of SF were cheese, pizza, ice cream, and eggs. The leading sources of AS were soft drinks, tea, fruit drinks, and cakes and pies. This analysis reflects a parsimonious approach to reliably identify foods and beverages that contribute to SF/AS intakes in U.S. adults.