Modern commercial air travel connects disparate human populations with the global airline industry transporting up to 4.5 billion passengers annually in the years leading up to the COVID-19 pandemic. While such connections are convenient for commerce and tourism, air travel networks can also be efficient distributors of infectious diseases such as influenza, SARS-CoV-1, hemorrhagic fevers, and more recently SARS-CoV-2 and monkeypox. During the COVID-19 pandemic, public health agencies used multi-layered control strategies including pre-departure testing and vaccination requirements, masking, post-arrival testing, and quarantine to manage the risk of COVID-19 transmission associated with air travel. Simultaneously, the surveillance of aircraft wastewater emerged as a promising new data source to screen for SARS-CoV-2 infections, including newly emergent lineages, among international air travelers. Herein, we review the potential of aircraft wastewater for public health surveillance. The known contributing population and flight itinerary combined with the highly concentrated waste stream and convenient sampling during routine lavatory servicing make aircraft wastewater a strategic opportunity for unintrusive surveillance of the global fluxes of human pathogens. We estimate for the cases of fecal- or urine-shed pathogens, sampling from 3,500 and 1,250 flights per week, respectively, would be required to survey 10% of all global long-haul flight passengers. In the case of the United States, achieving 10% coverage of all international arrivals would require sampling from 925 and 322 flights per week, respectively. Aircraft wastewater surveillance could also be integrated with network and infectious disease models to better inform traditional public health control measures during emerging epidemics. Given the tremendous potential for public good and the massive economic costs of epidemics, governments should consider international collaboration to create a global aircraft wastewater surveillance system.

Sewage surveillance can be used as an effective complementary tool for detecting pathogens in local communities, providing insights into emerging threats and aiding in the monitoring of outbreaks. In this study using qPCR and whole genomic sewage surveillance, we detected Mpox virus along with other viruses, in municipal and hospital wastewaters in Belo Horizonte, Brazil over a 9 months period (from July 2022 till March 2023). MPXV DNA detection rates varied in our study, with 19.6% (11 out of 56 samples) detected through the hybrid capture method of whole genome sequencing and 20% (12 out of 60 samples) through qPCR. In hospital wastewaters, the detection rate was higher at 40% (12 out of 30 samples), compared to 13.3%(4 out of 30 samples) in municipal wastewaters. This variation could be attributed to the relatively low number of MPXV cases reported in the city, which ranged from 106 to 341 cases during the study period, and to dilution effects, given that each of the two wastewater treatment plants (WWTP) investigated serves approximately 1.1 million inhabitants. Additionally, nine other virus families were identified in both hospitals and municipal wastewaters including Adenoviridade, Astroviridae, Caliciviridae, Picornaviridade, Polyomaviridae, Coronaviridae (which includes SARS-CoV-2), Herspesviridae, Papillomaviridae and Flaviviridae (notably including Dengue). These findings underscore the potential of genomic sewage surveillance as a robust public health tool for monitoring a wide range of viruses circulating in both community and hospitals environments including MPXV.

Clinical microbiology studies and systematic reviews have largely concluded that SARS-CoV-2 RNA is rarely present in the urine of COVID-19 patients. Thus, wastewater surveillance has largely focused on human stool and defecation as the relevant matrix and behavior. But, the over-performance of wastewater testing during near-source surveillance, especially in settings where on-site defecation is presumed to be de minimis such as aircraft and non-residential schools, suggests the possibility of SARS-CoV-2 RNA input from a non-fecal source. To revisit the possibility of urine as an explanation, data was compiled from 45 studies reporting on SARS-CoV-2 RNA in the urine of 1,924 COVID-19 patients. In general, the reporting quality was low with most studies (86.7%) failing to report even basic details such as the volume of urine collected. Only 11 reported quantitative data and of these only a single study reported its experiments to the standards established for publication of quantitative PCR data. Taking the data at its face value, the pooled prevalence of urinary SARS-CoV-2 RNA shedding was 11.3% (95%CI: 8.4 - 14.3), which roughly agrees with previous analyses. However, the percentage of variability in the estimate attributable to heterogeneity between studies (I² = 93.66%) warrants careful consideration. Notably, for the 8 studies reporting sufficient workflow information, the observed urinary RNA shedding prevalence was normally distributed (r² = 1.00) as a function of the volume of urine being assayed in a single PCR reaction (i.e., the equivalent sample volume, ESV). The study achieving the highest ESV (83.3 µL of urine) detected SARS-CoV-2 RNA in urine sediments of 95.5% of COVID-19 patients. Conversely, during two studies achieving ESVs of only 2 µL and 11.7 µL of urine, SARS-CoV-2 RNA was not detected in the urine of 72 and 132 patients, respectively. For wastewater surveillance of COVID-19, these observations suggest the rarity of SARS-CoV-2 RNA in urine may be a methodological artifact. Further, the data on which rarity is presumed are of low quality. Beyond COVID-19, the findings demonstrate that clinical studies, by virtue of their design to answer clinically relevant questions, could produce datasets subject to large biases that make them less useful when assessing the feasibility of wastewater surveillance of infectious agents. Wastewater surveillance practitioners must carefully consider the appropriateness and limitations of clinical data considering the important differences between the methods and aims of the two disciplines. Given the great potential of wastewater testing, clinical and environmental microbiologist should collaborate to produce robust quantitative datasets for reliable feasibility assessments for both community and near-source public health surveillance.

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.

We systematically reviewed studies using wastewater for AMR surveillance in human populations, to determine: (i) the strength of the evidence for a wastewater-human AMR association, and (ii) methodological approaches which optimised identifying such an association, and which could be recommended as standard. We used Lin’s concordance correlation coefficient (CCC) to quantify agreement between AMR prevalence in wastewater and human compartments, and logistic regression to identify study features (e.g. sampling methods) associated with high-agreement (defined as wastewater-human AMR prevalences within ±10%). Of 8,867 records and 232 full-text methods reviewed, 29 studies were included. AMR prevalence data was extractable from 20 studies conducting phenotypic-only (n=11), genotypic-only (n=1) or combined (n=8) AMR detection. Overall wastewater-human AMR concordance was reasonably high for both phenotypic (CCC=0.81 [95% CI 0.74-0.87]) and genotypic comparisons (CCC=0.88 (95% CI 0.85-0.91)) despite diverse species-phenotypes/genotypes and study design. Logistic regression was limited by inconsistent reporting of study features, and limited sample size; no significant relationships between study features and high wastewater-human AMR agreement were identified. Based on descriptive synthesis, composite/flow-proportional sampling of wastewater influent, longitudinal sampling >12 months, and time/location-matched comparisons generally had higher-agreement. Further research and clear and consistent reporting of study methods is required to confirm optimal practice.

Wastewater surveillance for SARS-CoV-2 has garnered extensive public attention during the COVID-19 pandemic as a proposed complement to existing disease surveillance systems. Over the past year, methods for detection and quantification of SARS-CoV-2 viral RNA in untreated sewage have advanced, and concentrations in wastewater have been shown to correlate with trends in reported cases. Despite the promise of wastewater surveillance, for these measurements to translate into useful public health tools, it is necessary to bridge the communication and knowledge gaps between researchers and public health responders. Here we describe the key uses, barriers, and applicability of SARS-CoV-2 wastewater surveillance for supporting public health decisions and actions, including establishing ethical consideration for monitoring. Overall, while wastewater surveillance to assess community infections is not a new idea, by addressing these barriers, the COVID-19 pandemic may be the initiating event that turns this emerging public health tool into a sustainable nationwide surveillance system.

Background: Emerging and re-emerging infectious diseases that infect wildlife, such as African swine fever, avian influenza, and SARS-CoV-2, have highlighted the necessity for wildlife health surveillance (WHS) due to their direct and indirect impacts on wildlife species, ecosystems, domestic animals, and human health. While global policies and guidelines exist, a critical gap remains in local-to-national implementation of WHS systems. A group of local, national, and global actors in WHS have formed a working group to address this gap. Methods and Findings: The working group reports on a theory of change (ToC) developed to implement WHS from local to global scales. Through brainstorming, plenary exercise, and building on peer-reviewed science and existing surveillance systems, we identified six transformative pathways to be implemented via collaborations across scales and contexts: mindset change, policy and investment, user-driven science, user-driven technologies, capacity enhancement, and mobilization of a global community of practice. Interpretation: This ToC serves as a roadmap to develop effective WHS systems that support adaptive management and implementation. WHS is fundamental to understanding the impacts of health threats to biodiversity and human and domestic animal health. This ToC presents an approach to operationalize integration of wildlife health into collaborative One Health surveillance. Funding: The Science for Nature and People Partnership.

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.

Bats are of significant interest as reservoirs for various zoonotic viruses with high diversity. During the past two decades, many herpesviruses have been identified in various bats worldwide by genetic approaches, whereas there have been few reports on the isolation of infectious herpesviruses. Herein, we report the prevalence of herpesvirus infection of bats captured in Zambia and genetic characterization of novel gammaherpesviruses isolated from Macronycteris vittatus bats. By our PCR screening, herpesvirus genomes were detected in 29.2% (7/24) of Rousettus aegyptiacus, 78.1% (82/105) of Macronycteris vittatus, and 100% (1/1) of Hipposideros caffer bats in Zambia. Phylogenetic analyses of the detected herpesvirus genomes revealed that the Zambian bat herpesviruses were divided into seven betaherpesvirus groups and five gammaherpesvirus groups. Two infectious strains of a novel gammaherpesvirus, tentatively named Macronycteris gammaherpesvirus 1 (MaGHV1), were successfully isolated from Macronycteris vittatus bats, and their complete genomes were sequenced. The genome of MaGHV1 encoded 79 open reading frames, and phylogenic analyses of the DNA polymerase and glycoprotein B demonstrated that MaGHV1 formed an independent lineage sharing a common origin with other bat-derived gammaherpesviruses. Our findings provide new information regarding the genetic diversity of herpesviruses maintained in African bats.

Legionnaires’ disease is normally acquired by inhalation of legionellae from a contaminated environmental source. Water systems of large buildings, such as hospitals, are often contaminated with legionellae and therefore represent a potential risk for the hospital population. In this study, we demonstrated the constant presence of Legionella in water samples from the water system of a large university hospital in Messina (Sicily, Italy) consisting of 11 separate pavilions during a period of 15 years (2004-2018). In total, 1346 hot water samples were collected between January 2004 and December 2018. During this period, to recover Legionella spp. from water samples the standard procedures reported by the Italian Guidelines emanated in 2000 were adopted; from May 2015 to 2018 Italian Guidelines revised in 2015 (ISS, 2015), were used. The most water samples (72%) were positive to L. pneumophila serogroups 2-14 whereas L. pneumophila serogroup 1 accounted for the 18% and Legionella spp. for the 15%. Most of the positive samples were found in the buildings where are situated critical wards as ICU, Neurosurgery, Surgeries, Pneumology and Neonatal Intensive Unit Care. We highlighted the importance of a continuous monitoring of hospital water samples to prevent the potential risk of nosocomial legionellosis.

In mountain communities like Sebei, Uganda, that are highly vulnerable to emerging and reemerging infectious diseases, community-based surveillance plays an important role in the monitoring of public health hazards. In this survey, we explored capacities of Village Health Teams (VHTs) in Sebei communities of Mount Elgon in undertaking surveillance tasks for emerging and reemerging infectious diseases in the context of a changing climate. We used participatory epidemiology techniques to elucidate VHTs’ perceptions on climate change and public health and assess their capacities in conducting surveillance for emerging and reemerging infectious diseases. Overall, VHTs perceived climate change to be occurring with wider impacts on public health. However, they have inadequate capacities in collecting sur-veillance data. The VHTs lack transport to navigate through their communities and have in-sufficient capacities in using mobile phones for sending alerts. They do not engage in reporting other hazards related with the environment, wildlife and domestic livestock that would ac-celerate infectious disease outbreaks. Records are not maintained for disease surveillance ac-tivities and the abilities of VHTs to analyze data are also limited. However, VHTs have access to platforms that can enable them to disseminate public health information. The VHTs thus need to be retooled to conduct their work effectively and efficiently through equipping them with adequate logistics and knowledge on collecting, storing, analyzing, and relaying data, which will improve infectious disease response and mitigation efforts.

We evaluated performance of two American surveillance systems for monitoring the spread of antimicrobial-resistant (AMR) gonorrhea: the Gonococcal Isolate Surveillance Project (GISP) and the enhanced Gonococcal Isolate Surveillance Project (eGISP) which includes the non-urethral isolates in addition to the urethral ones utilized in the original surveillance system. A continuous-time agent-based model of gonorrhea transmission among the US men who have sex with men (MSM) population was developed and used for this purpose. The model accounts for susceptible and resistant strains of N. gonorrhoeae, symptomatic and asymptomatic infection and different transmission routes. Overall, eGISP system outperforms the original GISP system and allows to obtain a higher accuracy using a significantly lower number of isolates. Most of time, the original surveillance system determines the moment of switch to a new antibiotic later than necessary which leads to additional gonorrhea cases and spread of the resistance. Informing the gonorrhea treatment guidelines by eGISP estimates instead of the currently used GISP estimates would result in reduction of 622 (95% uncertainty interval: -4,009, 9,099) gonorrhea cases in the simulated cohort of 10,000 US MSM over a 25-year period without reduction in the lifespan of the current first-line antibiotic.

Antimicrobial resistance (AMR) is a public health problem exacerbated by the overuse and misuse of antibiotics and an inadequate capacity of laboratories to conduct AMR surveillance. This study assessed the capacity of laboratories in seven faith-based hospitals to conduct bacteriology, AMR testing and surveillance in Zambia. This multi-facility, cross-sectional exploratory study was conducted from February 2024 to April 2024. We collected and analysed data using the self-scoring Laboratory Assessment of Antibiotic Resistance Testing Capacity (LAARC) tool. This study found an overall score of 39%, indicating a low capacity of laboratories to conduct AMR surveillance. The highest capacity score was 47%, while the lowest was 25%. Only one hospital had full capacity (100%) to utilise a Laboratory Information System (LIS). Three hospitals had good capacity to perform data management with scores of 83%, 85%, and 95%. Only one hospital had full capacity (100%) to process specimens, and only one hospital had good safety requirements for a microbiology laboratory, with a score of 89%. This study demonstrates that all the assessed hospitals have a low capacity to conduct AMR surveillance. Therefore, there is an urgent need to strengthen the microbiology capacity of laboratories to enhance surveillance in faith-based hospitals in Zambia.

Metabolic Associated Steatohepatitis Liver Disease (MASLD) currently impacts a quarter of the global population and its prevalence is expected to increase in the future. As a result, the incidence of hepatocellular carcinoma associated with MASLD is also on the rise. Notably, hepatocellular carcinoma in this group does not always develop alongside liver cirrhosis, often leading to a more advanced stage at diagnosis. The challenge lies in accurately identifying patients who are at a higher risk of hepatocellular carcinoma to tailor screening processes effectively. Additionally, several therapeutic approaches are being explored to prevent hepatocellular carcinoma, although there are yet no universally accepted guidelines

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.

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.

(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.

Human exposure to antimicrobial resistance (AMR) through food is now very imperfectly understood, creating a significant gap in the design of interventions. The interchange of AMR genes and the transfer of AMR bacteria from animals to humans through the food chain necessitate comprehensive methods to risk reduction. With a focus on AMR in bacterial species isolated from food products, foods (of both animal and non-animal origin), and ambient samples, the current meta-analysis gathered up-to-date information on the epidemiology of AMR in animal-source food chain. As a result, the combined prevalence of AMR across the various food sources was calculated. From the 18,784 food samples obtained as a result of selected publications, 7,676 (40.9%) samples were contaminated, including 4343 (56.6%) and 3363 (43.4%) samples from Taiwan and India, respectively. Meat (chicken, pork, and beef), fish and milk all have moderate to medium potential for AMR exposure to both Gram-positive and Gram-negative foodborne pathogens such S. aureus, Clostridium, E. coli, Salmonella, etc. Antibiotic resistance to β-lactam, fluoroquinolone, carbapenem etc, is present in the majority of food samples. The results of this study emphasize the persistent danger of antimicrobial residue in animal-derived foods in Taiwan, India, and other nations with comparable customs.

Lymphatic filariasis (LF) is a vector-borne disease caused by parasitic helminths and constitutes a serious public health issue in tropical regions. According to the World Health Organization (WHO), infected cases in Southeast Asia constitute 50% of the estimated 120 million infections globally. In Indonesia, LF is caused by all filarial species, and in 2018, 236 districts from a total of 514 districts in the entire country were declared as endemic areas. The global program to eliminate filariasis has been running for the last 19 years and has been conducted as a full national initiative for the last 8 years in Indonesia. The study describes the surveillance of LF cases and prevalence in Indonesia for the past 17 years (2001-2017) – during the global and national LF elimination programs-, using national registry-based data. The data demonstrates that the national program has been largely effective in the areas it has been active the longest, while there are provinces lagging behind in the successful suppression of LF. The high geographical fragmentation of the country with the associated ecological parameters relating to LF incidence, likely play an important role in maintaining the highly varied incidence rate across Indonesia.

Secondary and tertiary prevention strategies targeting people with disabilities to improve their health and wellbeing is important. In Sweden, >95% of all children with cerebral palsy (CP) participate in a follow-up program, where one of the goals is the prevention of hip dislocations. We reviewed the incidence of hip dislocations from 2010 to 2019 and the number of children who underwent different types of hip surgeries. The number of hip dislocations was reduced from 8.8% before introduction of the program to 0.3-0.4% up to 2015, followed by a gradual increase to 0.8% in 2019. The proportion of children who underwent adductor-psoas lengthening as their primary preventive surgery decreased from 50% in 2017 to 37% in 2019 with a corresponding increase of children undergoing femoral osteotomy, indicating more children underwent surgery at a later stage. Reasons for the increased number of children with hip dislocation may be that more children have moved to Sweden in recent years without corresponding compensation in health care resources and increased waiting times for surgery due to, among other things, a shortage of nurses. The results highlight the importance of constantly monitoring follow-up programs.

Medical surveillance and risk mitigation protocols to reduce viral transmission have underpinned the return of elite football during the COVID-19 pandemic. This article describes the evidence-informed approach and surveillance findings from the English Football League across a 9-week period at the end of the 2019-20 season. Protocols were devised by the lead EFL Medical Advisor with specialist occupational medicine input. Isolation requirements for cases and contacts were in-line with UK Government regulations, with external contact tracing conducted by local public health authorities. Quantitative PCR testing was conducted twice weekly and within 72 hours of fixtures. 43 individuals, including 18 players returned positive tests. No positive results were returned after week 5 (round 10). Our findings support those from other leagues that with appropriate compliance, elite football can continue safely during this pandemic. We recommend that protocols and compliance should be revised as necessary according to community prevalence and changes in viral transmission dynamics.

Background: Foodborne disease is a major public health concern in both developed and developing countries. China has established a nationwide Foodborne Disease Outbreak Surveillance System (FDOSS) for collection and periodic reporting of data on the occurrence and causes of foodborne disease outbreaks in China. Each provincial Centers for Disease Control and Prevention (CDC) conducts the system working. Methods We reviewed foodborne disease outbreaks that occurred during 2011-2016 in Shandong Province from the FDOSS. The Wilcoxon test was used to compare the median number of ill persons in outbreaks. All data analysis was performed using Epi Info 7. Results: During 2011-2016, Shandong CDC received reports of 1043 foodborne disease outbreaks, resulting in 8078 illnesses, 2442 hospitalizations, and 17 deaths. Hotels were the most common setting. Among the 744 (71.3%) outbreaks with an implicated food or contaminated ingredient reported, 704 (94.6%) could be assigned to one of 17 predefined commodity categories. Of the 280 outbreaks with a known aetiology, 117(41.8%) were caused by poisonous plants and animals and their toxins, 39(13.9) were caused by nitrite, and 27(9.6%) were caused by vibrio parahaemolyticus. Conclusion: Timely investigation, disposal and reporting of foodborne disease outbreaks provides information that might help FDOSS to make full use of efficiency and FDOSS should be continued and strengthened even more in Shandong Province, such as an increase in diagnostic laboratory capacities.

This study investigated commensal and pathogenic E. coli from pigs at farms and slaughterhouses in Sardinia, focusing on genetic relatedness and antimicrobial resistance (AMR). Samples were collected from six fattening pig farms (A-F) and five slaughterhouses (S1-S5). In the farms, environmental fecal sampling from the fattening pigs’ pens was carried out and information regarding farm management and biosecurity measures were collected. Pigs that had been in the sampled pens were selected for sampling at the slaughterhouse. Mesenteric lymph nodes, colon content and carcass surface samples were collected at the five slaughterhouse (S1-S5), in a total of 38 samples form 152 animals. At the slaughterhouses, also environmental samples were collected from food-contact surfaces and non-food-contact surfaces (36 samples overall). E. coli was detected in all farms, 97% of pigs, and 100% of slaughterhouses. Whole genome sequencing and antimicrobial susceptibility testing were per-formed on 96 isolates, revealing 13.5% pathogenic isolates, including ExPEC, ETEC, STEC-ETEC hy-brids, and UPEC. A total of 40 sequence types (STs) were identified, with ST10 being the most com-mon. High-risk clones (ST88, ST101, ST410, and ST648) were also detected. Over half of the isolates (52.1%) carried at least one AMR gene, with 42.7% harboring multiple AMR genes, particularly tet (37.5%) and blaTEM (32.3%). High phenotypic resistance was observed for tetracycline, ampicillin, and sulfamethoxazole-trimethoprim. The study highlights the widespread presence of pathogenic E. coli in pigs, even in isolated environments, and emphasizes the need for continuous surveillance due to the significant AMR found in both pathogenic and non-pathogenic isolates.

Background: Leprosy control remains challenging in Brazil and has been aggravated by the Covid-19 pandemic. Objective: To analyze the impact of the Covid-19 pandemic on the epide-miological scenario of leprosy through the detection rate of new cases, risk of illness and hidden prevalence according to high-risk micro-region in Minas Gerais, Brazil. Methods: Ecological study conducted in the health micro-regions, using data on new leprosy cases diagnosed between 2015 and 2023. The annual detection rate of new cases, the Risk of Illness Index and the Hidden Preva-lence were evaluated. The time trend was evaluated by calculating the Annual Percentage Change (APC) of the detection rate, based on segmented linear regression. Results: A reduction in the detection of new cases was identified in most of the micro-regions evaluated. Minas Gerais and some micro-regions showed a positive increase in the variation of the overall detection rate in 2021. The reduction in hidden prevalence in certain micro-regions is linked to the reduction in diagnoses, especially those cases with installed physical disability. Despite the reduction in the risk of becoming ill with leprosy in some micro-regions, Minas Gerais showed an increase in risk. Conclusions: The pandemic has had a considerable and heterogeneous impact on the detection of new cases, as well as on the risk of becoming ill and the hidden prevalence, with repercussions for the control of the endemic in populations. There is a need to implement public health policies that prioritize the early identification of cases and ensure that vulnerable populations are monitored.

Objective: To report time-loss match injuries in Portugal’s “Divisão de Honra” (Portuguese First Tier) 2022/23 season focusing on injury incidence, injury burden, anatomical region and type of injury. Methods: A cohort prospective observational study was conducted. Data was collected through an online form sent for every team medical department categorizing player position, injury type, location and severity. Injury incidence and burden were calculated per 1000-player-match-hours. Results: The overall injury incidence was 54.4 injuries per 1000 player-match-hours (CI95% 30.3-96.2). Forwards had a higher incidence comparing to backs. Lower limbs were the most affected location (52% of the injuries). Sprain/ligaments injuries were the most common type of injury followed by muscle injuries. Discussion: The injury incidence was higher than what is reported in amateur competitions and lower than professional ones. Injury severity was similar to other studies. Our study suggests a lower injury burden compared to other semi-professional and elite leagues. Further research with broader participation and training injury data is needed.

Following the detection of highly pathogenic avian influenza (HPAI) virus in countries bordering Kenya to the west, we conducted surveillance among domestic and wild birds along the shores of Lake Victoria. In addition, between 2018 and 2020, we conducted surveillance among poultry and poultry workers in live bird markets and among wild migratory birds in various lakes that are resting sites during migration to assess introduction and circulation of avian influenza viruses in these populations. We tested 7,464 specimens (oropharyngeal and cloacal swabs) from poultry and 6,531 fresh fecal specimens from wild birds for influenza A viruses by real-time RT-PCR. Influenza was detected in 3.9% (n=292) of specimens collected from poultry and 0.2% (n=10) of fecal specimens from wild birds. On hemagglutinin subtyping, most of the influenza A positives from poultry (274/292, 93.8%) were H9. Of 34 H9 specimens randomly selected for further subtyping, all were H9N2. On phylogenetic analysis, these viruses were genetically similar to other H9 viruses detected in East Africa. Only two of the ten influenza A positive specimens from the wild bird fecal specimens were successfully subtyped; sequencing analysis of one specimen collected in 2018 was identified as low pathogenicity avian influenza H5N2 virus of the Eurasian lineage and the second specimen, collected in 2020, was subtyped as H11. A total of 18 OP/NS swabs from poultry workers with ARI (12%) were collected; none were positive for influenza A virus. We observed significant circulation of H9N2 influenza viruses in poultry in live bird markets in Kenya. During the same period, low pathogenic H5N2 virus was detected in a fecal specimen collected in a site hosting a variety of migratory and resident birds. Although HPAI H5N8 was not detected in this survey, these results highlight the potential for introduction and establishment of highly pathogenic avian influenza viruses in poultry populations and the associated risk of spillover to human populations.

Hearing loss (HL) is a major clinical, population and public health leading to serious disorders and often early mortality. However, there is a significant paucity in high quality data. Saudi Arabia has a genetically uniform and young population; however factors and estimates on prevalence of HL remains unknown. Background/Objectives: we aimed to determine the frequency, factors, and patterns of HL in different regions. Methods: this study was a descriptive cross-sectional design using a web-based online public questionnaire sent out simultaneously to different regions of Saudi Arabia; namely Eastern, Western, Northen, and Southern as self-administered non-probability sample of social media users mainly WhatsApp, Twitter, and others. Results: Among 789 responses, 6.6 % reported HL, 62.4% were from the Eastern province of which 41.2% were employed and 31.7% were students. Many (36.5%) reported HL > 5-years while 21.2% had programmed and fitted with hearing aids or cochlear implants implying negligence. 19.2% reported diabetes and 51.9% had family history. Ages (11– 50 years) were examined with a slight female predominance (females 59.1%, males 41%). Age was significantly associated with HL (P <0.001) irrespective of gender (males 6.8%, females 6.4%, P value =0.838) reaching peaks at 17.2% in age groups 51-60 years and 25% in 71-80 indicating a risk for HL (OR = 1.43, 95% CI: 0.78-2.81, p = 0.032). Genetic diseases reported as leading cause in 34.6% (OR = 2.23, 95% CI: 1.34-3.58, p = 0.432) followed by noise (26.9%), while other factors including infections, stroke, and fevers made 19.2%. Work involving air or sea travels reported (7.7%) with no significant association (P = 0.628) while history of head injury or trauma (11.5%), or relocation between low- and high-altitudes showed 21.2%. However, frequent noise pollution (OR = 1.54, 95% CI: 0.83-3.01, p = 0.048), regular use of medications (OR = 2.15, 95% CI: 1.03-3.32, p = 0.017), and history of inflammatory disorders (OR = 0.72, 95% CI: 0.32-1.87, p = 0.229) were also associated with higher odds of HL. Conclusion: thus, these findings have significant clinical implications in early diagnosis and management of HL in genetic disorders, diabetes, geriatrics, as well as awareness on family history and occupational health and safety. The study was limited in size and use of online questionnaires. Future large cohort multicenter study would gain more insights.

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.

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.

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.

The dengue virus (DENV) is an arbovirus belonging to the Flaviviridae family; the species comprises four antigenically distinct serotypes (DENV–1, DENV–2, DENV–3, and DENV–4), which are further subdivided into genotypes. The virus is transmitted to humans through mosquito bites, primarily from the Aedes spp. genus. Dengue is endemic in various parts of the world, including tropical and subtropical regions of Asia, Latin America, Africa, and Oceania. In Brazil, the state of Tocantins, located in north-central Brazil, has experienced a significant number of arboviral disease cases, particularly dengue. This study aimed to monitor DENV circulation within the state by conducting full genome sequencing of viral genomes recovered from 61 patients between June 2021 and July 2022. During this period, both DENV-1 and DENV-2 serotypes were identified. Our findings confirm the circulation of DENV serotypes 1 and 2 in Tocantins, affecting males and females equally, with younger age groups (4 to 43 years old) being the most susceptible. Phylogenetic analysis revealed that the circulating viruses belong to DENV–1 genotype V American and DENV–2 genotype III Southeast Asian/American. The Bayesian analysis of DENV-1 Genotype V sequenced here is closely related to genomes previously sequenced in the state of São Paulo. Regarding DENV-2 genotype III genomes, these are clustered in a distinct, well-supported subclade, along with previously reported isolates from the states of Goiás and São Paulo. In both cases, our results suggest that multiple introductions of these genotypes occurred in the Tocantins state. This observation highlights the significant impact of major population centers in Brazil on virus dispersion, including other Latin-American countries and the USA. In the SNP analysis, DENV-1 displayed 122 distinct missense mutations, while DENV-2 had 44, with significant mutations predominantly occurring in the envelope and NS5 proteins. The analyses performed here reveal the concomitant circulation of distinct DENV-1 and -2 genotypes in some Brazilian states, underscoring the dynamic evolution of the DENV and the ongoing significance of surveillance efforts in supporting public health policies.

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.

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.

The unprecedented COVID-19 pandemic posed major challenges to local, regional, and global economies and health systems, and fast clinical diagnostic workflows were urgently needed to contain the spread of SARS-CoV-2. Here, we describe the platform and workflow established at the Cornell COVID-19 Testing Laboratory (CCTL) for high-throughput testing of clinical samples from the university and the surrounding community. This workflow enabled efficient and rapid detection, and successful control of SARS-CoV-2 infection on campus and its surrounding communities. Our cost-effective and fully automated workflow enabled testing of over 8,000 pooled samples per day and provided results for over 2 million samples. Automation of time- and effort-intensive sample processing steps such as accessioning and pooling increased laboratory efficiency. Customized software applications were developed to track and store samples, deconvolute positive pools, track and report results and for workflow integration from sample receipt to result reporting. Additionally, quality control dashboards and turn-around time tracking applications were built to monitor assay and laboratory performance. As infectious disease outbreaks pose a constant threat to both human and animal health, the highly effective workflow implemented at CCTL could be modeled to establish regional high-capacity testing hubs for infectious disease preparedness and emergency response.

The Americas, particularly Brazil, were greatly impacted by the widespread outbreak of Zika virus (ZIKV) in 2015 and 2016. Efforts were made to implement genomic surveillance of ZIKV as part of the public health responses. The accuracy of spatiotemporal reconstructions of the epidemic spread relies on the unbiased sampling of the transmission process. In the early stages of the outbreak, we recruited patients exhibiting clinical symptoms of arbovirus-like infection from Salvador and Campo Formoso, Bahia, in Northeast Brazil. Between May 2015 and June 2016, we identified 21 cases of acute ZIKV infection and subsequently recovered 14 near full-length sequences using the amplicon tiling multiplex approach with nanopore sequencing. We perform a time-calibrated discrete phylogeographic analysis to trace the spread and migration history of the ZIKV. Our phylogenetic analysis supports a consistent relationship between ZIKV migration from Northeast to Southeast Brazil and its subsequent dissemination beyond Brazil. Additionally, our analysis provides insights into the migration of ZIKV from Brazil to Haiti and the role Brazil played in the spread of ZIKV to other countries, such as Singapore, the USA and Dominican Republic. The data generated by this study enhances our understanding of ZIKV dynamics and supports the existing knowledge, which can aid in future surveillance efforts against the virus.

Organisms release their nucleic acid in the environment including the DNA and RNA which can be used to detect their presence. eDNA/eRNA techniques are being used in different sectors to identify organisms from soil, water, air, and ice since long. The advancement in technology led to easier detection of different organisms without impacting the environment and the organism itself. These methods are being employed in different areas including surveillance, history, and conservation. eDNA and eRNA methods are being extensively used in aquaculture and fisheries setting to understand the presence of different fish species and pathogens in water. However, there are some challenges associated with the reliability of the results because of the degradation of nucleic acid by several factors. In aquaculture there are several diseases and parasites detected with these methods. In this review we discuss different aquaculture diseases and parasites detected with eDNA/eRNA approach and the fate of these nucleic acids when subjected to different water quality and environmental parameters. This review intends to help the researcher about the potential of eDNA/eRNA based detection of pathogens in aquaculture; this will be useful to predict the potential outbreak before it occurs. Along with that this paper intends to make people understand several factors that degrade and can hamper the detection of these nucleic acids.

The major goal of this paper is to use image enhancement techniques for enhancing and extracting data in FANET applications to improve the efficiency of surveillance. The proposed conceptual system design can improve the likelihood of FANET operations in oil pipeline surveillance, and sports and media coverage with the ultimate goal of providing efficient services to those who are interested. The system architecture model is based on current scientific principles and developing technologies. A FANET, which is capable of gathering image data from video-enabled drones, and an image processing system that permits data collection and analysis are the two primary components of the system. Based on the image processing technique, a proof of concept for efficient data extraction and enhancement in FANET situations and possible services is illustrated

Pathogen genomics is a critical tool for public health surveillance, infection control, outbreak investigations, as well as research. In order to make use of pathogen genomics data, it must be interpreted using contextual data (metadata). Contextual data includes sample metadata, laboratory methods, patient demographics, clinical outcomes, and epidemiological information. However, the variability in how contextual information is captured by different authorities and how it is encoded in different databases poses challenges for data interpretation, integration, and its use/re-use. The DataHarmonizer is a template-driven spreadsheet application for harmonizing, validating, and transforming genomics contextual data into submission-ready formats for public or private repositories. The tool’s web browser-based JavaScript environment enables validation and its offline functionality and local installation increases data security. The DataHarmonizer was developed to address the data sharing needs that arose during the COVID-19 pandemic, and was used by members of the Canadian COVID Genomics Network (CanCOGeN) to harmonize SARS-CoV-2 contextual data for national surveillance and for public repository submission.In order to support coordination of international surveillance efforts, we have partnered with the Public Health Alliance for Genomic Epidemiology to also provide a template conforming to its SARS-CoV-2 contextual data specification for use worldwide. Templates are also being developed for One Health and foodborne pathogens. Overall, the DataHarmonizer tool improves the effectiveness and fidelity of contextual data capture as well as its subsequent usability. Harmonization of contextual information across authorities, platforms and systems globally improves interoperability and reusability of data for concerted public health and research initiatives to fight the current pandemic and future public health emergencies. While initially developed for the COVID-19 pandemic, its expansion to other data management applications and pathogens is already underway.

Background: In the span of just two years, tracking the COVID-19 pandemic through wastewater surveillance has advanced from early reports of successful SARS-CoV-2 RNA detection in untreated wastewater to implementation of programs in at least 60 countries. Early wastewater monitoring efforts primarily originated in research laboratories and are now transitioning into more formal surveillance programs run in commercial and public health laboratories. A major challenge in this progression has been to simultaneously optimize methods and build scientific consensus while implementing surveillance programs, particularly during the rapidly changing landscape of the pandemic. Translating wastewater surveillance results for effective use by public health agencies also remains a key objective for the field. Objectives: We examine the evolution of wastewater surveillance to identify model collaborations and effective partnerships that have created rapid and sustained success. We propose needed areas of research and key roles academic researchers can play in the framework of wastewater surveillance to aid in the transition of early monitoring efforts to more formalized programs within the public health system. Discussion: Wastewater surveillance has rapidly developed as a public health tool Clinical testing programs are ramping down and home testing is on the rise, making wastewater monitoring important for future surveillance of COVID-19. Our experience in initiating and implementing wastewater surveillance programs in the United States has allowed us to reflect on key barriers and organizational challenges and draw useful lessons. As wastewater surveillance programs are formalized, the working relationships developed between academic researchers, commercial and public health laboratories, and data users should continue and should promote knowledge co-development. While wastewater surveillance has demonstrated utility for tracking COVID-19, there remain technical challenges and open scientific questions that researchers are equipped to address, which will contribute to building robust surveillance programs that provide public health practitioners with new insights into population health.

Infectious diseases, as COVID-19 is proving, pose a global health threat in an interconnected world. In the last 20 years, resistant infectious diseases such as SARS, MERS, H1N1, Ebola, Zika and now COVID-19 have been impacting global health defences, and aggressively flourishing within the rise of global travel, urbanization, climate change and ecological degradation. In parallel, this extraordinary episode in global human health highlights the potential for artificial intelligence (AI)-enabled disease surveillance to collect and analyse vast amounts of unstructured and real-time data to inform epidemiological and public health emergency responses. The uses of AI in these dynamic environments are increasingly complex, challenging the potential for human autonomous decisions. In this context, our study of qualitative perspectives will consider a responsible AI framework to explore its potential application to disease surveillance in a global health context. Thus far, there is a gap in the literature in considering these multiple and interconnected levels of disease surveillance and emergency health management through the lens of a responsible AI framework.

Abstract Introduction: The mHealth active participant centred (MAPC) adverse events following immunisation (AEFI) surveillance is a promising area for early AEFI detection resulting in risk minimisation. Passive (spontaneous) AEFI surveillance is the backbone for vaccine pharmacovigilance, but has inherent drawbacks of under reporting, and requires strengthening with active surveillance methods. The Zimbabwe stimulated telephone assisted rapid safety surveillance (Zm-STARSS) randomized controlled trial (RCT) sought to evaluate the efficacy and feasibility of AEFI detection using a short message service (SMS) and computer assisted telephone interview (CATI) approach. Method: A multicentre Zm-STARSS RCT enrolled consented adult vaccinees or parents or guardians of children receiving vaccines, including COVID-19 vaccines, at study vaccination clinics. At enrolment study participants were randomised to either SMS-CATI group or control group. SMS prompts were sent on days 0-2 and 14 post-vaccination to SMS-CATI group to ascertain if a medical event following immunisation (MEFI) had occurred. However, no SMSs were sent to the control group. SMS-CATI group who responded “Yes” to SMS prompts were interviewed by research healthcare workers (RHCWs) who completed a CATI to determine if an MEFI/AEFI had occurred whilst an AEFI in control group was determined from passive AEFI reporting channels. The primary study outcome was the AEFI detection rate in the SMS-CATI group compared to the control group. Results: A total of 704 (31%) participants responded to the SMS prompts, with 75% (528/704) indicating “No” and 25% (176/704) "Yes” to experiencing a MEFI. However, 31% (55/176) who responded “Yes” did not complete a CATI survey, but 69% (121/176) did; and 64% (77/121) of these indicated negative to AEFI experience whilst 36% (44/121) were affirmative. There were no AEFI reported in control group participants. Zm-STARSS showed promising results in that the AEFI detection rate using SMS-CATI was 2% (44/2280) on an intention to treat cohort. Conclusion: Despite the low SMS response and CATI completion rate, we demonstrated that Zm-STARSS SMS system improves AEFI detection compared to passive AEFI surveillance. We recommend cost-effective multi-channel digital approaches for holistic pharmacovigilance to improve AEFI detection in LMICs for all vaccines.

This study examines a case involving a 7-year-old child who developed dengue symptoms following Qdenga vaccination. Despite initial negative diagnostic results, molecular analysis confirmed an infection with DENV4. Next-generation sequencing detected viral RNA from both DENV2 and DENV4 serotypes, which were identified as vaccine-derived strains using specific primers. Phylogenetic analysis further confirmed that these sequences belonged to the Qdenga vaccine rather than circulating wild-type viruses. This case underscores the critical need for precise diagnostic interpretation in vaccinated individuals to avoid misdiagnosis and to strengthen public health surveillance. A comprehensive understanding of vaccine-induced viremia is essential for refining dengue surveillance, improving diagnostic accuracy, and informing public health strategies in endemic regions.

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.

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.

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.

To describe the main health surveillance strategies for the control of COVID-19 in Brazil, with emphasis on decisions and actions taken at the federal level to prevent the infection caused by the new SARS-CoV-2. This is a scoping review study carried out from November 2019 to January 2021 using the DECS and MeSH health descriptors in Portuguese and English in four databases, in addition to the legislation found on the Brazilian Government's legislation portal. Based on the analysis of the documents, the actions describe non-pharmacological and pharmacological measures, measures related to decisions on closing and opening international borders, the acquisition of supplies and essential services. Although some strategies for containing the pandemic were identified, discrete and unnoticed surveillance measures are observed in view of the number of cases and number of deaths during the period of research analysis. The results show the absence of the federal level as support for the states and municipalities and imply decision-making and planning of actions by the Unified Health System to control the pandemic.

Wastewater surveillance, initially conceived in the early 20th century during typhoid fever outbreaks, has evolved into a powerful tool for monitoring public health-relevant analytes. Recent applications in tracking SARS-CoV-2 infection highlight its potential. Beyond humans, it can be extended to livestock populations due to the increasing demand for livestock products. Livestock intensification poses risks of zoonotic disease emergence. Wastewater surveillance offers non-invasive, cost-effective means to detect potential outbreaks. This approach aligns with the "One Health" paradigm, emphasizing the interconnectedness of human, animal, and ecosystem health. By monitoring viruses in livestock wastewater, early detection, prevention, and control strategies can be employed, safeguarding both animal and human health, economic stability, and international trade. This integrated One Health approach enhances collaboration and a comprehensive understanding of disease dynamics, supporting proactive measures in the Anthropocene era where animal and human diseases are on the rise.

Next generation sequencing (NGS) from SARS-CoV-2-positive swabs collected during the last months of 2022 revealed a large deletion between ORF7b and ORF8 (426 nt) in six patients infected with the BA.5.1 Omicron variant. This extensive genome loss removed a large part of these two genes, maintaining in frame the first 22 aminoacids of ORF7b and the last 3 aminoacids of ORF8. Interestingly, the deleted region was flanked by 2 small repeats, likely involved in the formation of a hairpin structure. Similar rearrangements, comparable in size and location to the deletion, were also identified in 15 sequences in the NCBI database. In this group, 7 out of 15 cases from the USA and Switzerland presented both the BA.5.1 variant and the same 426 nuclotides deletion. It is noteworthy that 3 out of 6 cases were detected in patients with immunodeficiency and is conceivable that this clinical condition could promote the replication and selection of these mutations.

Huge-scale video surveillance systems have become essential in crime prevention and situation recording. Traditional surveillance systems relied on human monitoring of video streams, which often led to errors and difficulties in understanding events. Furthermore, locating specific scenes within recorded videos required extensive human investigation. To overcome these challenges of inefficiency, inconvenience, and potential risks, we propose an intelligent analysis scheme that utilizes abnormal behavior recognition and metadata retrieval algorithms to replace human monitoring. The proposed method consists of three stages: i) metadata generation through object detection and tracking, ii) abnormal behavior recognition, and iii) SQL-based metadata retrieval. By incorporating specific information such as object color and aspect ratio, our technique enhances the usability of retrieval. Moreover, our abnormal behavior recognition module demonstrates robust classification capabilities for activities such as pushing, violence, falling, and crossing barriers. The proposed method can be seamlessly deployed on both edge cameras and analysis servers, making it adaptable to various surveillance setups. This approach revolutionizes the traditional surveillance paradigm, enabling more efficient, reliable, and secure video monitoring and analysis.

The effective detection of viruses in aircraft wastewater is crucial to establish surveillance programs for monitoring virus spread via aircraft passengers. This study aimed to compare the performance of two virus concentration workflows, adsorption-extraction (AE) and Nanotrap® Microbiome A Particles (NMAP), in detecting the prevalence and concentrations of 15 endogenous viruses in aircraft lavatory wastewater samples. The viruses tested include two indicator viruses, four enteric viruses, and nine respiratory viruses. The results showed that cross-assembly phage (crAssphage), human polyomavirus (HPyV), rhinovirus A (RhV A), and rhinovirus B (RhV B) were detected in all wastewater samples using both workflows. However, enterovirus (EV), human norovirus (HNoV GII), human adenovirus (HAdV), bocavirus (BoV), parechovirus (PeV), epstein-barr virus (EBV), influenza A virus (IAV), and respiratory syncytial virus B (RsV B) were infrequently detected by both workflows, and hepatitis A virus (HAV), influenza B virus (IBV), and respiratory syncytial virus B (RsV A) were not detected in any samples. The NMAP workflow had greater detection rates of EV, PeV, and RsV B than the AE workflow, while the AE workflow had greater detection rates of HAdV, BoV, and EBV than the NMAP workflow. The concentration of each virus was also analyzed, and the results showed that CrAssphage had the highest mean concentration (6.76 log₁₀ GC/12.5 mL) followed by HPyV (5.46 log₁₀ GC/12.5 mL using the AE workflow, while the mean concentrations of enteric and respiratory viruses ranged from 2.48 to 3.63 log₁₀ GC/12.5 mL. Using the NMAP workflow, the mean concentration of crAssphage was 5.18 log₁₀ GC/12.5 mL and the mean concentration of HPyV was 4.20 log₁₀ GC/12.5 mL, while mean concentrations of enteric and respiratory viruses ranged from 2.55 to 3.74 log₁₀ GC/12.5 mL. The mean concentrations of CrAssphage, HPyV, RhV A, and RhV B between the two workflows were statistically significant (p < 0.05). In summary, the present study provides valuable insights into the performance of virus concentration workflows in detecting and quantifying different viruses in aircraft lavatory wastewater samples. The findings can aid in the selection of an appropriate concentration workflow for virus surveillance studies and contribute to the development of efficient and reliable virus detection methods.

Research indicates that farmers’ demographic characteristics and production practices have safety and health implications. However, current systems do not identify organic farmers independently from conventional farmers, and literature on how organic and conventional farmers compare is very limited. We conducted a secondary analysis of 2012 Census of Agriculture data to compare organic and non-organic farms and principal operators (POs) in New Mexico (NM). Organic farms were smaller in size, and POs of farms with organic sales were significantly younger (55.8±9.5 vs. 60.5±5.5 years) and less experienced (19.5±6.8 vs. 25.2±6.8 years). Significant differences were also found in POs ethnicity, race, and primary occupation. More farms with organic sales had a female PO compared to farms with non-organic sales (27% vs. 19%). Other significant differences related to work arrangements, household income, living conditions, and access to Internet. National surveys and regional studies may not accurately typify and describe the local organic producer, which is essential in order to advance policy, develop health interventions, and properly address occupational safety and risk among organic farmers. This study makes a unique contribution to understanding the importance of surveillance and collecting place-based data that are specific to the organic producer.

The genetic diversity of foot-and-mouth disease virus (FMDV) poses a challenge to the successful control of the disease, and it is important to identify the emergence of different strains in endemic settings. The objective of this study was to evaluate sampling of clinically healthy livestock at slaughterhouses as a strategy for genomic FMDV surveillance. Serum samples (n = 11875) and oropharyngeal fluid (OPF) samples (n = 5045) were collected from asymptomatic cattle and buffalo on farms in eight provinces in southern and northern Vietnam (2015 to 2019) to characterize viral diversity. Outbreak sequences were collected between 2009 and 2019. In two slaughterhouses in southern Vietnam, 1200 serum and OPF samples were collected from asymptomatic cattle and buffalo (2017 to 2019) as a pilot study on the use of slaughterhouses as sentinel points of surveil-lance. VP1 sequences were analyzed using discriminant principal component analysis and time-scaled phylodynamic trees. Six of seven serotype O and A clusters circulating in southern Vietnam from 2017-19 were detected at least once in slaughterhouses, sometimes pre-dating outbreak sequences associated with the same cluster by 4-6 months. Routine sampling at slaughterhouses may provide timely and cost-effective strategy for genomic surveillance to identify circulating and emerging FMDV strains.

Background: About 10% of Wilms Tumor (WT) patients have a malformation or cancer predisposition syndrome (CPS) with causative germline genetic or epigenetic variants. Knowledge on CPS is essential for genetic counselling. Methods: This retrospective analysis focused on 2927 consecutive patients with WTs registered between 1989 and 2017 in the SIOP/GPOH studies. Results: (GU, N=66, 2,3%), Beckwith-Wiedemann spectrum (BWS, N=32, 1,1%), isolated hemihypertrophy (IHH, N=29, 1,0%), Denys-Drash syndrome (DDS, N=24, 0,8%) and WAGR syndrome (N=20, 0,7%) were reported most frequently. Compared to others, these patients were younger at WT diagnosis (median age 24,5 months vs. 39,0 months), had smaller tumors (334,8mL vs. 496,9mL), less often metastasis (8,2% vs. 18%), but more often nephroblastomatosis (12,9% vs. 1,9%). WT with IHH was associated with blastemal WT and DDS with stromal subtype. Bilateral WTs were common in WAGR (30%), DDS (29%) and BWS (31%). Chemotherapy induced reduction in tumor volume was poor in DDS (7,7% increase) and favorable in BWS (84,6% reduction). The event-free survival (EFS) of patients with BWS was significantly (p=0,002) worse than in others. Conclusions: CPS should be considered in WTs with specific clinical features resulting in referral to a geneticist. Their outcome was not always favorable.

Background: drugs provide a significant benefit; however, their use implies an intrinsic potential danger, with the possibility to cause unwanted effects. These effects are known as adverse drug reactions (ADRs). Post-marketing drug safety surveillance detects unknown risks that have not been identified in clinical trials and it is necessary to monitor marketed medications under real-life practice. Due to the scarce information about fixed combination of ciprofloxacin 0.3% / dexamethasone 0.1% (SDO), we performed a drug safety surveillance study. (2) Methods: A prospective non-controlled drug safety surveillance study was conducted in Peruvian population. A total of 236 patients prescribed SDO were included derivates from 12 sites. Patients' standardized information was collected through two phone calls, including demographics, medical history, prescribing patterns of SDO, concomitant medication, and ADRs in detail. The ADRs were classified by causality and severity, followed by outcome measures to identify new risk. (3) Results: 236 patients prescribed with SDO participated in the study and 220 were included. A total of 82 ADRs/220 patients were reported after the use of SDO, presenting a ratio 0.37 ADR/patient. The most frequent ADR with SDO administration was eye irritation (30%). The totality of the ADR was classified as non-serious, and the 97.5% (n=80) was classified as mild and 2.5% as moderate (n=2). No cases under the severe category were identified. (4) Conclusion: No new risks were found in the population where this study was conducted.

Background: Epidemiological surveillance of nursing diagnosis is an approach anchored on a post-modern epidemiology focused on persons health-disease responses. Regarding to public health priorities, the population where our study occurred had as priority problem the arterial hypertension. Related to this chronical disease, nursing diagnoses about health-disease responses in primary healthcare has as major focus Therapeutic Regime Management. Our aim was to study the nursing diagnosis in this issue, from an epidemiological approach. Methods: A descriptive study from an epidemiological approach was developed, analyzing nursing diagnoses in hypertensive patients. Results: We found 17,7% of undiagnosed patients and better diagnoses in patients with complications than in those without complications. Conclusions: nursing records need to be improved in order to promote more robust studies in the post-modern epidemiology defended for the future.

In tracking-by-detection paradigm for multi-target tracking, target association is modeled as an optimization problem that is usually solved through network flow formulation. In this paper, we proposed combinatorial optimization formulation and used a bipartite graph matching for associating the targets in the consecutive frames. Usually, the target of interest is represented in a bounding box and track the whole box as a single entity. However, in the case of humans, the body goes through complex articulation and occlusion that severely deteriorate the tracking performance. To partially tackle the problem of occlusion, we argue that tracking the rigid body organ could lead to better tracking performance compared to the whole body tracking. Based on this assumption, we generated the target hypothesis of only the spatial locations of person’s heads in every frame. After the localization of head location, a constant velocity motion model is used for the temporal evolution of the targets in the visual scene. Qualitative results are evaluated on four challenging video surveillance dataset and promising results has been achieved.

The outbreak of coronavirus 2 (SARS-CoV-2) has already taken on pandemic proportions and has affected more than 100 countries in recent weeks. It is imperative that global healthcare systems are prepared. Containment initiatives in Jordan, on the other hand, have decreased new cases by over 63%. The Jordanian national health system has been very pleased with its ability to adequately meet the needs of the patients diagnosed with SARS-CoV-2 pneumonia, and includes intensive care. From 2 March to 14 April 2020, between 4% and 8% of active infected patients in Jordan registered daily in intensive care. The percentage is very low.

We aimed to evaluate the safety of maternal Tdap we assessed health events by examining the difference in birth and hospital-related outcomes of infants with and without fetal exposure to Tdap. This was a retrospective cohort study using linked administrative datasets. The study population were all live-born infants in New Zealand (NZ) weighing at least 400 grams at delivery and born to women who were eligible for the government funded, national-level vaccination program in 2013. Infants were followed from birth up to one year of age. There were a total of 69,389 eligible infants in the cohort. Of these, 8,299 infants were born to 8,178 mothers exposed to Tdap (12%), primarily between 28-38 weeks gestation as per the national schedule. Among the outcomes, we found a reduced risk for moderate to late preterm birth, low birth weight, small for gestational age, large for gestational age, respiratory distress syndrome, transient tachypnea of newborn, tachycardia or bradycardia, haemolytic diseases, other neonatal jaundice, anaemia, syndrome of infant of mother with gestational diabetes, and hypoglycemia in infants born to vaccinated mothers. There was no association between maternal Tdap and stillbirth, infant Apgar score at 5 minutes after birth, microcephaly, asphyxia, sepsis or infection, or hypoxic ischemic encephalopathy. Infant exposure to Tdap during pregnancy was associated with a higher mean birthweight (not clinically significant) and higher odds for ankyloglossia and neonatal erythema toxicum diagnoses. There were insufficient observations to allow examination of the effect of Tdap on extreme preterm and very preterm birth, and infant death. Overall, we found no outcomes of concern associated with the administration of Tdap during pregnancy.

Pancreatic ductal adenocarcinoma (PDA), the most frequent type of pancreatic cancer, is one of the main unfinished businesses in the biomedical and clinical fields, with still discouraging 5 year survival rates and poor therapy efficiency. PDA abundant desmoplasia has for long played the lead in the mechanisms involved in poor drug performance, being the main source of cytokines and chemokines orchestrating rapid and silent tumor progression and guilty of isolating tumor cells into a extense fibrotic reaction resulting in inefficient drug delivery. However, since immunotherapy was proclaimed the breakthrough of the year back to 2013, the focus in the stroma of pancreatic cancer has interestingly moved from activated fibroblasts to the immune compartment, trying to understand the immunosuppressive factors that play part in the strong immune evasion that characterizes PDA. PDA microenvironment is highly immune-suppressive, being basically composed of T regulatory cells (Tregs), tumor-associated macrophages (TAMs) and myeloid-derived suppressive cells (MDSCs), which boycott CD8⁺ T-cell duties in tumor recognition and clearance. Interestingly, preclinical data have highlighted the importance of this immune evasion as the source of resistance to single checkpoint immunotherapies and cancer vaccines and point at pathways inhibiting the immune attack as the key to solve the therapy puzzle. Here, we will discuss the molecular mechanisms involved in PDA immune escape as well as the state of the art of the PDA immunotherapy.

Depth-sensing technology has led to broad applications of inexpensive depth cameras that can capture human motion and scenes in 3D space. Background subtraction algorithms can be improved by fusing color and depth cues, thereby allowing many issues encountered in classical color segmentation to be solved. In this paper, we propose a new fusion method that combines depth and color information for foreground segmentation based on an advanced color-based algorithm. First, a background model and a depth model are developed. Then, based on these models, we propose a new updating strategy that can eliminate ghosting and black shadows almost completely. Extensive experiments have been performed to compare the proposed algorithm with other, conventional RGB-D algorithms. The experimental results suggest that our method extracts foregrounds with higher effectiveness and efficiency.

A new maritime order is emerging – the blue economy – characterised by a plethora of non-traditional security threats. Using the case of the Western Indian Ocean I demonstrate how the creation of spaces of risk in response to traditional security threats by world powers has led to a new, regionally-led governance regime in response to the new maritime order. International efforts to protect shipping lanes from the threat of piracy off the coast of Somalia have evolved into wider environmental and human security measures. I analyse these changes through the lens of governmentality and argue that this case represents an example of a global governmentality in which states are responsibilised to act collaboratively by the international community through discourses of risk. Regional States have turned this to their advantage, acting together to construct and secure a new development frontier - a shared blue economy space in an extensive and difficult-to-govern territory.

Wastewater-based surveillance has emerged as an important method for monitoring SARS-CoV-2. This study investigated the presence of SARS-CoV-2 in wastewater in Zambia. We conducted a longitudinal study in the Copperbelt and Eastern provinces of Zambia from October 2023 to December 2023 during which 155 wastewater samples were collected. The samples were subjected to three different concentration methods, namely bag-mediated filtration, skimmed milk flocculation, and polythene glycol-based concentration assays. Molecular detection of SARS-CoV-2 nucleic acid was conducted using real-time PCR. Whole genome sequencing was conducted using Illumina COVIDSEQ assay. Of the 155 wastewater samples, 62 (40%) tested positive for SARS-CoV-2. Of these, 13 sequences of sufficient length to determine SARS-CoV-2 lineages were obtained and two sequences were phylogenetically analyzed. Various Omicron subvariants were detected in wastewater including BA.5, XBB.1.45, BA.2.86, and JN.1. Some of these subvariants have been detected in clinical cases in Zambia. Interestingly, phylogenetic analysis positioned a sequence from the Copperbelt Province in the B.1.1.529 clade, suggesting that earlier Omicron variants detected in late 2021 could still be circulating and may not have been wholly replaced by newer subvariants. This study stresses the need for integrating wastewater surveillance of SARS-CoV-2 into mainstream strategies for monitoring SARS-CoV-2 circulation in Zambia.

The Chikungunya virus (CHIKV) poses a significant global public health concern, especially in Africa. Since its first isolation in Tanzania in 1953, CHIKV has caused recurrent outbreaks, challenging healthcare systems in low-resource settings. Recent outbreaks in Africa highlight the dynamic nature of CHIKV transmission and the challenges of underreporting and underdiagnosis. Here, we review literature and analyze publicly available cases, outbreaks, and genomic data providing insights into the epidemiology, genetic diversity, and transmission dynamics of CHIKV in Africa. Our analyses reveal the circulation of geographically distinct CHIKV genotypes, with certain regions experiencing a disproportionate burden of disease. Phylogenetic analysis of sporadic outbreaks in West Africa suggests repeated emergence of the virus through enzootic spillover, which is markedly different from inferred transmission dynamics in East Africa, where the virus is often introduced from Asian outbreaks, including the recent reintroduction of the Indian Ocean lineage from the Indian subcontinent to east Africa. Furthermore, there is limited evidence of viral movement between these two regions. Understanding the history and transmission dynamics of outbreaks is crucial for public health planning. Despite advances in surveillance and research, diagnostic and surveillance challenges persist. This review and secondary analysis highlight the importance of ongoing surveillance, research, and collaboration to mitigate the burden of CHIKV in Africa and improve public health outcomes.

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.

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.

After eight decades, the largest outbreak of sylvatic yellow fever virus (YFV) was recorded in Brazil between 2016-2018. Besides human and NHP surveillance, the entomo-virological approach is considered as a complementary tool. For this study, a total of 2904 mosquitoes of Aedes, Haemagogus and Sabethes genera from six Brazilian states (Bahia, Goiás, Mato Grosso, Minas Gerais, Pará, and Tocantins), were collected and grouped in 246 pools, which were tested for YFV using RT-qPCR. We detected 20 positive pools from Minas Gerais, 5 from Goiás, and 1 from Bahia, including 12 of Hg. janthinomys and 5 of Ae. albopictus. This is the first description of natural YFV infection in this species and warns of the likelihood of urban YFV re-emergence with the Ae. albopictus as a potential bridge vector. Three YFV sequences from Hg. janthinomys from Goiás and one from Minas Gerais, as well as one from Ae. albopictus from Minas Gerais clustered within the 2016-2018 outbreak clade, indicating YFV spread from Midwest and its infection in a main and in a likely-novel bridging vector species. Entomo-virological surveillance is critical in the YFV monitoring in Brazil, which could highlight the need to strengthen YFV surveillance, vaccination coverage, and vector control measures.

This study identified and mapped worldwide surveillance actions and initiatives of drinking water quality implemented by government agencies or public health services. The scoping review was conducted between July 2021 and August 2022 based on the Joanna Briggs Institute. The search was performed in relevant databases and grey literature; 49 studies were obtained. Quantitative variables were presented as absolute and relative frequencies, while qualitative variables were analyzed using the IRaMuTeQ software. The actions developed worldwide and their impacts and results provided four thematic classes: (1) assessment of coverage, accessibility, quantity, and drinking water quality in routine and emergency situations; (2) analysis of physical-chemical and microbiological parameters in public supply networks or alternative water supply solutions; (3) identification of household water contamination, communication, and education with the community; (4) and investigation of water-borne disease outbreaks. Preliminary results were shared with stakeholders to favor early knowledge dissemination.

In this study, we analyzed sequences of SARS-CoV-2 isolates of the Delta variant in Mexico, which completely replaced other previously circulating variants in the country due to its transmission advantage. Among Delta sublineages detected, 81.5 % were classified as AY.20, AY.26, and AY.100. According to publicly available data, these sublineages only reached a world prevalence of less than 1%, suggesting a possible Mexican origin. The signature mutations of these sublineages are described, and phylogenetic analyses and haplotype networks were used to track their spread across the country. Other frequently detected sublineages include AY.3, AY.62, AY.103, and AY.113. Over time, the principal sublineages showed different geographical distributions, with AY.20 predominant in Central Mexico, AY.26 in the North, and AY.100 in the Northwest and South/Southeast. This work describes the circulation, from May to November 2021, of the primary sublineages of the Delta variants associated to the third wave of the COVID-19 pandemic in Mexico and reinforces the importance of SARS-CoV-2 genomic surveillance for timely identification of emerging variants that may impact public health.

Genomic surveillance represents an important strategy for understanding evolutionary mechanisms, transmission profile, and infectivity of different SARS-CoV-2 variants. We assessed the epidemiological profile of 366 individuals who tested positive for SARS-CoV-2 from 29 municipalities in Rondônia between December 2021 to March 2022. Samples were collected, RNA was ex-tracted and screened using RT-qPCR for Alpha, Beta, Gamma, Delta and Omicron VOCs and viral quantification was performed. Sequences were analyzed for phylogeny, mutations and lineages. Of the samples analyzed, 93.71% were positive for the Omicron variant and 6.28% were positive for the Delta variant. The symptoms observed were cough, sore throat, and fever, with a mean duration of 5 days; no hospitalizations or deaths were reported. We noted that among the positive individuals, 51% had been immunized with two doses, 22% received three doses, 13% received one dose, and 13% were not immunized. Just 242 samples were amenable to analysis for alignment and phylogenetic characterization; corresponding to variants BA.1 and BA.1.1; a total of 120 mutations were identified, 36% of which were found in the S gene. In conclusion, there was a high frequency of mutations in the SARS-CoV-2 genome, but no record of clinical severity, demonstrating the positive effect of vaccination.

Background Reliable and field-applicable diagnosis of schistosome infections in non-human animals is important for surveillance, control, and verification of interruption of human schistosomiasis transmission. This study aimed to summarize uses of available diagnostic techniques through a systematic review and meta-analysis. Methods and principal findings We systematically searched the literature and reports comparing two or more diagnostic tests in non-human animals for schistosome infection. Out of 4,909 articles and reports screened, 18 met our inclusion criteria, four of which were considered in the meta-analysis. A total of 14 techniques (parasitologic, immunologic, and molecular) and nine types of non-human animals were involved in the studies. Notably, four studies compared parasitologic tests (miracidium hatching test (MHT), Kato-Katz (KK), the Danish Bilharziasis Laboratory technique (DBL), and formalin-ethyl acetate sedimentation-digestion (FED-SD)) with quantitative polymerase chain reaction (qPCR), and sensitivity estimates (using qPCR as the reference) were extracted and included in the meta-analyses, showing significant heterogeneity across studies and animals hosts. The pooled estimate of sensitivity was 0.21 (95% confidence interval (CI): 0.03 – 0.48) with FED-SD showing highest sensitivity (0.89, 95% CI: 0.65 – 1.00). Conclusions and significance Our findings suggest that the parasitologic technique FEA-SD and the molecular technique, qPCR, are the most promising field-applicable techniques for schistosome diagnosis in non-human animal hosts. Future studies are needed for validation and standardization of the techniques for real-world field applications.

The worldwide spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has ubiquitously impacted many aspects of life. As vaccines continue to be manufactured and administered, limiting the spread of SARS-CoV-2 will rely more heavily on the early identification of contagious individuals occupying reopened and increasingly populated indoor environments. In this study, we investigated the utility of an impaction-based aerosol sampling system with multiple nucleic acid collection media. Heat-inactivated SARS-CoV-2 was utilized to perform bench-scale, short-range aerosol, and room-scale aerosol experiments. Through bench-scale experiments, AerosolSense Capture Media (ACM) and nylon flocked swabs were identified as the highest utility media. In room-scale aerosol experiments, consistent detection of aerosol SARS-CoV-2 was achieved at a concentration equal to or greater than 0.089 genome copies per liter of room air (gc/L) when air was sampled for eight hours or more at less than one air change per hour (ACH). Shorter sampling periods (~75 minutes) yielded consistent detection at ~31.8 gc/L of room air and intermittent detection down to ~0.318 gc/L at (1 and 6+ ACH respectively). These results support further exploration in real-world testing scenarios and suggest the utility of indoor aerosol surveillance as an effective risk mitigation strategy in occupied buildings.

Aedes scapularis is a neotropical mosquito known to transmit pathogens of medical and veterinary importance. Its recent establishment in southeastern Florida has potential public health implications. We used an ecological niche modeling approach to predict the abiotic environmental suitability for Ae. scapularis across much of the Americas and Caribbean Islands. Georeferenced occurrence data obtained from the Global Biodiversity Inventory Facility and recent collection records of Ae. scapularis from southern Florida served as input for model calibration. Environmental layers included bioclimatic variables provided in 2000 to 2010 average Modern Era Retrospective-analysis for Research and Applications climatic (MERRAclim) data. Models were run in the software program Maxent. Isothermality values found often in costal environments contributed strongest to model performance. Model projections suggested areas predicted suitable for Ae. scapularis across portions of the Amazon Basin, the Yucatán Peninsula, the Florida Peninsula, and multiple Caribbean Islands. Additionally, model predictions suggested connectivity of highly suitable or relatively suitable environments spanning the United States Gulf Coast, which may facilitate geographic expansion of this species. At least sixteen Florida counties were predicted highly suitable for Ae. scapularis, suggesting vigilance is needed by vector control and public health agencies to recognize further spread of this vector.

Objectives: The aim of this study was to assess the knowledge, attitude and practice of healthcare professionals regarding adverse drug reaction [ADR] monitoring and pharmacovigilance [PV] in India. Materials and Methods: It was a questionnaire based cross sectional observational study. Data was collected with the help of data collection Google form that included the demographics and twenty two survey based questions. Data were analysed by using Microsoft Excel sheet, further analysed for results, including frequency, percentage, mean and standard deviation. Result: The questionnaire was filled by two hundred ten healthcare professionals in which 52.9 % were male and 47.10% of female. Most of the respondents were pharm d students (50.47%). Out of the total 91.4% responded to the definition of pharmacovigilance correctly. 87.6% participants said all ADR should be reported. 86.20% participants think Pharmacovigilance should be taught in detail to healthcare professionals. Most of the respondents (43.8%) always informed the patients about ADR while prescribing the medicines. Conclusion: Study revealed most of the participants have good knowledge about ADR and pharmacovigilance. Difficult to decide whether ADR occur or not and extra work load being major factors responsible for under reporting.

The vast array of omics data in microbiology presents significant opportunities for studying bacterial pathogenesis and creating computational tools for predicting pathogenic potential. However, the field lacks a comprehensive, curated resource that catalogs bacterial strains and their ability to cause human infections. Current methods for identifying pathogenicity determinants often introduce biases and miss critical aspects of bacterial pathogenesis.In response to this gap, we introduce BacSPaD (Bacterial Strains’ Pathogenicity Database), a thoroughly curated database focusing on pathogenicity annotations for a wide range of high-quality, complete bacterial genomes. Our rule-based annotation workflow combines metadata from trusted sources with automated keyword matching, extensive manual curation, and detailed literature review. Our analysis classified 5,502 genomes as pathogenic to humans (HP) and 490 as non-pathogenic to humans (NHP), encompassing 532 species, 193 genera, and 96 families. Statistical analysis demonstrated a significant but moderate correlation between virulence factors and HP classification, highlighting the complexity of bacterial pathogenicity and the need for ongoing research. This resource is poised to enhance our understanding of bacterial pathogenicity mechanisms and aid in the development of predictive models. To improve accessibility and provide key visualization statistics, we developed a user-friendly web interface, accessible at https://bacspad.altrabio.com.

Knowing the number of cases of an epidemic is the first function of epidemiological surveillance. An important underreporting of cases was observed in many places during the first wave of COVID-19 pandemic. To estimate this underreporting in the COVID-19 outbreak of Borriana (Valencia Community, Spain), during “Falles” mass gathering events in March 2020, a cross-sectional study was performed in June 2020 querying public health register. Logistic regression models were used. From a total of 468 symptomatic COVID-19 cases diagnosed in the outbreak by anti-SARS-CoV-2 serology, 36 cases were reported (7.7%), thus an underreporting of 92.3% (95% Confidence Interval [CI] 89.5%-94.6%), 13 unreported cases for every reported case. Only positive SARS-CoV-2 polymerase chain reaction cases were predominantly reported due to a limited testing capacity and following a national protocol. Significant factors associated with underreporting were no medical assistance for COVID-19 disease, adjusted odds ratio [aOR] 10.83 (95% CI 2.49-47.11), no chronic illness, aOR=2.81 (95% CI 1.28-6.17), middle and lower social classes, aOR=3.12 (95% CI 1.42-6.85), younger age, aOR=0.97 (95% CI 0.94-0.99), shorter duration of illness, aOR=0.98 (95% CI 0.97-0.99). To improve surveillance, studies of representative population samples are necessary to estimate the magnitude of future epidemics, and novel approaches are recommended.

The exponential growth of maritime traffic has brought with it a multitude of business opportunities, while at the same time posing unprecedented challenges in terms of control and surveillance. Traditional methods struggle to cope with the sheer volume and complexity of maritime activities, which calls for innovative solutions. This study presents a comparative analysis of three prominent computing object detection models applied to maritime surveillance. By evaluating their performance metrics in dynamic maritime environments, this study provides information on the most suitable model for effective maritime monitoring applications, attaining an impressive 91\% mean Average Precision (mAP) using the YOLOv5n model.

Poultry eggs are a critical source of protein, vitamins, and minerals for people worldwide; facing the current global egg shortage is a significant concern. The shortage results from various factors, including avian flu outbreaks, changes in consumer demand, and supply chain disruptions caused by the COVID-19 pandemic. The economic crisis caused by the pandemic has also impacted the availability and affordability of eggs, particularly in low-income countries. The global egg shortage has implications for public health, particularly for vulnerable populations who rely on eggs for essential nutrients. One Health, an approach that recognizes the interconnectedness of human, animal, and environmental health, provides a useful framework for understanding and addressing the egg shortage. One Health approaches to the egg shortage involve collaboration between agriculture and environmental sectors to address the root causes of the lack and ensure the sustainable production and distribution of eggs. Addressing the global egg shortage requires a multifaceted approach considering the complex social, economic, and environmental factors. One Health perspectives offer a way to understand and address the interconnected factors contributing to the shortage to ensure access to affordable, nutritious eggs for all in a healthy way

The unprecedented growth of publicly available SARS-CoV-2 genome sequence data has increased demand for effective and accessible SARS-CoV-2 data analysis and visualization tools. A majority of the currently available tools either require computational expertise to deploy or limit user input to pre-selected subsets of SARS-CoV-2 genomes. To address these limitations, we developed ViralVar, a publicly available, point-and-click webtool that gives users the freedom to investigate and visualize user-selected subsets of SARS-CoV-2 genomes obtained from the GISAID public database. ViralVar has two primary features that enable: 1) visualization of spatiotemporal dynamics of SARS-CoV-2 lineages, and 2) structural/functional analysis of genomic mutations. As proof-of-principle, ViralVar was used to explore the evolution of the SARS-CoV-2 pandemic in the USA in the pediatric, adult, and elderly population (n > 1.7 million genomes). While the spatiotemporal dynamics of variants did not differ between these age groups, several USA-specific sublineages arose relative to the rest of the world. Our development and utilization of ViralVar to provide insights on the evolution of SARS-CoV-2 in the USA demonstrates the importance of developing accessible tools to facilitate and accelerate large-scale surveillance of circulating pathogens. The ViralVar webserver is freely available at http://viralvar.org/.

Antibiotics are in excessive use that has extensively increased antimicrobial resistance worldwide which has become the major public concern among the countries. To control this threat proper monitoring of the antimicrobial usage along with the increasing rate of antimicrobial resistance (AMR) is required. Further, surveillance of both the parameters is highly recommended for comparing the differences in distinct countries. Moreover, alternatives for antibiotics are also surveyed and are being researched for quick use in the near future. AMR is an issue that needs immense attention from various sectors. Thus, intervention of multisector is highly encouraged for better outcomes. One Health is one of the approaches that play a vital role in resolving this issue. In this research paper, six different European countries are discussed in terms of antimicrobial usage and AMR in the human and livestock sectors with the help of literature study and various reports published by different organizations. Data study has been conducted to collect the data for comparison study. Data sources of AMR and antimicrobial usage are analyzed and a thorough comparison of both antimicrobial use and AMR are conducted. Also, the application of One Health is studied for a balanced system. This article provides about various surveillance systems that are formed only to keep a track on the upcoming situation of AMR and the consumption of antimicrobials by the humans as well as animals. The article does not provide about all the details required to monitor the AMR issue but firmly allow the readers to get acknowledged with the broad information about the antimicrobial resistance across the six countries of Europe. The regular data collected by the different organizations play a vital role in monitoring the status of AMR and antimicrobial usage by humans and in live stocks. These annual reports have highly helped the government to decide for alternatives and have focused in many training activities to combat the AMR situation globally. AMR prevention is linked to the One Health concept. As antibiotic resistance genes persist on an interface between environment and animal and animal health, an approach is required in all three areas that stress the concept of 'One Approach to Health.'

The ever-burgeoning growth of autonomous unmanned aerial vehicles (UAVs) has demonstrated a promising platform for utilization in real-world applications. In particular, UAV equipped with a vision system could be leveraged for surveillance applications. This paper proposes a learning-based UAV system for achieving autonomous surveillance, in which the UAV can be of assistance in autonomously detecting, tracking, and following a target object without human intervention. Specifically, we adopted the YOLOv4-Tiny algorithm for semantic object detection and then consolidated it with a 3D object pose estimation method and Kalman Filter to enhance the perception performance. In addition, a back-end UAV path planning for surveillance maneuver is integrated to complete the fully autonomous system. The perception module is assessed on a quadrotor UAV, while the whole system is validated through flight experiments. The experiment results verified the robustness, effectiveness, and reliability of the autonomous object tracking UAV system in performing surveillance tasks. The source code is released to the research community for future reference.

Current oncological developments are based on improved understanding of genetics, and especially the discovery of genes whose alterations affect cell functions with consequences for the whole body. Our work is focused on the one of these genes, the BARD1 and its oncogenic role in breast cancer. Most importantly, the study points to new avenues in the treatment and prevention of the most frequent female cancer based on BARD1 research. The BARD1 and BRCA1 proteins have similar structures and functions, and they combine to form the new molecule BARD1-BRCA1 heterodimer. The BARD1-BRCA1 complex is involved in genetic stabilization at the cellular level. It allows to mark abnormal DNA fragments by attaching ubiquitin to them. In addition, it blocks (by ubiquitination of RNA polymerase II) the transcription of damaged DNA. Ubiquitination, as well as stabilizing chromatin, or regulating the number of centrosomes, confirms the protective cooperation of BARD1 and BRCA1 in the stabilization of the genome. The overexpression of the oncogenic isoforms BARD1β and BARD1δ permit cancer development. The introduction of routine tests, for instance, to identify the presence of the BARD1β isoform, would make it possible to detect patients at high risk of developing cancer. On the other hand, introducing BARD1δ isoform blocking therapy, which would reduce estrogen sensitivity, may be a new line of cancer therapy with potential to modulate responses to existing treatments. It is possible that the BARD 1 gene offers new hope for improving breast cancer therapy.

Current oncological developments are based on improved understanding of genetics, and especially the discovery of genes whose alterations affect cell functions with consequences for the whole body. Our work is focused on the most important of these genes, the BARD1 and its oncogenic role in breast cancer. Most importantly, the study points to new avenues in the treatment and prevention of the most frequent female cancer based on BARD1 research. The BARD1 and BRCA1 proteins have similar structures and functions, and they combine to form the new molecule BARD1-BRCA1 heterodimer. Through ubiquitination, this heterodimer has significant effects on individual proteins, enabling, among others, the destruction of damaged DNA fragments. Ubiquitination, as well as stabilizing chromatin, or regulating the number of centrosomes, confirms the protective cooperation of BARD1 and BRCA1 in the stabilization of the genome. The overexpression of the oncogenic isoforms BARD1β and BARD1δ permit cancer development. The introduction of routine tests, for instance, to identify the presence of the BARD1β isoform, would make it possible to detect patients at high risk of developing cancer. On the other hand, introducing BARD1δ isoform blocking therapy, which would reduce estrogen sensitivity, may be a new line of cancer therapy with potential to modulate responses to existing treatments. It is possible that the BARD 1 gene offers new hope for improving breast cancer therapy.

The disease COVID-19 is highly infectious, and infectious in asymptomatic incubation period. The national epidemic development has been effectively controlled and continues improving, especially in areas outside Hubei province. Such periodical results were achieved by the joint efforts of the whole society, including not only the hard work and dedication of the front-line medical workers but also the active cooperation of the general public. The strict epidemic prevention and control measurements have brought remarkable control results. In the present study, the basic infection number of the coronavirus R0 (basic replication number of the infection) before and after prevention and control measurements was simulated to elaborate the measurements of the Chinese government on epidemic prevention and control, providing reference for the people around the world.

Artificial intelligence (A.I.) is the key to process big amounts of data to useful information for operators. In the present study the suitability of a 24/7 A.I. sound based coughing monitoring system for early detection of respiratory distress caused by porcine respiratory disease complex (PRDC) associated pathogens was assessed in the nursery of a conventional pig farm. Screening for PRDC associated pathogens was conducted by PCR examination of oral fluids (OFs) and bioaerosol samples (AS). A significant correlation between A.I. and human gained health data was observed in both batches. An increase in coughing episodes, either measured by A.I. or human, was significantly correlated with decreasing Ct-values of swIAV. The Odds to detect nucleic acids of PRRSV or Actinobacillus (A.) pleuropneumonia was significantly higher for OFs compared to AS. Moreover, PCR examinations of OFs revealed significantly lower Ct-values for swIAV and A. pleuropneumonia compared to AS. The quantity of swIAV RNA in OFs and AS was significantly associated with the A.I. calculated respiratory health score and thus, with clinical disease. Due to its reliable data A.I. based health monitoring is beneficial for early recognition of respiratory distress and thus can assist farmer’s daily work.

Patients with inflammatory bowel diseases (IBD), including both ulcerative colitis (UC) and Crohn's disease (CD), are at a higher risk of developing colorectal cancer (CRC). However, advancements in endoscopic imaging techniques, integrated surveillance programs, and improved medical therapies have led to a decrease in the incidence of CRC among IBD patients. Currently, the management of patients with IBD who have a history of or ongoing active malignancy is an unmet need. This involves balancing the risk of cancer recurrence/progression with the potential exacerbation of IBD if the medications are discontinued. The objective of this review is to provide an updated summary of the epidemiology, causes, risk factors, and surveillance approaches for CRC in individuals with IBD, and to offer practical guidance on managing IBD patients with history of previous or active cancer.

Public safety and intelligent surveillance systems critically depend on anomaly behavior detection for effective monitoring. In real-world pedestrian detection scenarios, prevalent challenges such as missed detections, complex background interference, and small target sizes hinder accurate anomaly identification. To address these issues, this study introduces YOLO-ABD, a lightweight method for anomaly behavior detection that integrates small target detection and channel shuffling. This method employs YOLOv8n as the baseline model, incorporating a small target detection mechanism in the Head part and utilizing GSConv convolution in the Backbone to enhance perceptual capability. Additionally, the SimAM attention mechanism is integrated to mitigate complex background interference, thereby improving target detection performance. Evaluation on the IITB-Corridor dataset demonstrated mAP50 and mAP50-95 scores of 89.3% and 60.6%, respectively. Generalization testing on the street-view-gdogo dataset further highlighted the superiority of YOLO-ABD over advanced detection algorithms, underscoring its effectiveness and generalizability. With a relatively small parameter count, YOLO-ABD presents an excellent lightweight solution for pedestrian anomaly behavior detection.

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.

Artificial intelligence (AI) has emerged as a powerful tool for addressing the challenges posed by climate change and their impact on public health. By leveraging its capacity to analyze and predict climatic patterns, AI offers opportunities to enhance resource management and develop effective strategies for climate change mitigation. Moreover, AI can contribute to generating sustainable solutions that address the complex and interconnected nature of climate change. For example, AI can enable the optimization of energy consumption and facilitate the integration of renewable energy sources into existing systems. It can also support the development of climate models that provide timely and accurate predictions, enabling policymakers to implement proactive measures for disaster preparedness and response. Furthermore, AI-powered disease surveillance and mitigation techniques can improve public health outcomes by identifying patterns and trends in the spread of diseases in relation to climatic factors.However, the widespread adoption of AI-based solutions is not without challenges. Ethical concerns surrounding privacy and data ownership must be addressed, as the use of AI requires access to large datasets, raising potential privacy risks. Technical constraints, such as limited computational power and the need for sophisticated algorithms, also pose obstacles to the implementation of AI in climate change mitigation strategies. Furthermore, issues related to the accessibility and affordability of AI technologies must be resolved to ensure equitable distribution and maximize its potential impact on public health.To fully harness the power of AI in addressing climate change and improving public health outcomes, it is crucial to promote innovation, multidisciplinary collaboration, and open data science. Innovation can drive the development of new AI algorithms and technologies specifically tailored to address climate change challenges. Multidisciplinary approaches that bring together experts from diverse fields, including climate science, public health, and computer science, can foster a holistic understanding of complex systems and enable the design of comprehensive solutions. Finally, open data science practices, such as sharing data and algorithms, can facilitate collaboration and accelerate progress in mitigating climate change and its public health impacts.In conclusion, AI offers promising opportunities for effectively addressing climate change and its impact on public health. However, to fully realize its potential, it is essential to tackle ethical and privacy concerns, overcome technical constraints, and ensure accessibility and affordability. By promoting innovation, multidisciplinary collaboration, and open data science, we can unlock the transformative power of AI in mitigating climate change and improving public health outcomes.

Background: Waterborne diseases pose a significant global public health threat, compelling enhanced comprehensive surveillance. This study investigates the current infectious disease and antimicrobial resistance (AMR) surveillance systems, including wastewater and environmental surveillance (WES), in three sub-Saharan African countries: Tanzania, Burkina Faso, and the Democratic Republic of the Congo (DRC). The three countries have their specificities regarding wastewater networks and logistic systems. So, emphasizing the need to strengthen existing disease surveillance, the paper advocates for incorporating WES systems specifically designed for countries' context to monitor waterborne and re-emerging pathogens, as well as AMR.Methods: National workshops were conducted to assess the current clinical and environmental surveillance systems and identify priority pathogens for new environmental monitoring. Data were collected through surveys from experts in academia, research, policy, and healthcare. Results: Prioritized pathogens for WES include waterborne (poliovirus, Salmonella Typhi, Vibrio cholerae), respiratory (influenza A&B, SARS-CoV-2), other (Measles and Rubella, Mycobacterium tuberculosis). Recommended AMR pathogens include drug-resistant Mycobacterium tuberculosis, Salmonella spp., methicillin-resistant Staphylococcus aureus, and extended-spectrum beta-lactamase and carbapenemase-producing E. coli. Tanzania, Burkina Faso, and the DRC employ DHSI2-based centralized electronic systems for clinical data collection, complemented by Excel and paper-based registries. The WES approach is commonly employed for monitoring poliovirus and rarely for AMR and other pathogens. Discussion and conclusions: WES is a valuable tool for early detection of locally circulating human-derived pathogens, aiding in outbreak detection, data-driven epidemic response, and prevention. The availability of WES results underscores the importance of effective sanitation for safeguarding human, animal, and environmental health. WES is a pivotal tool for integrated risk management, preventing waterborne outbreaks, protecting drinking water sources, and ultimately gaining various UN Sustainable Development Goals. The study highlights the importance of customized WES systems in line with each country's context, emphasizing localized approaches for effective monitoring of waterborne pathogens and AMR.

GCN1 is recognized as a factor that is essential for the activation of GCN2, which is a sensor of amino acid starvation. This function is evolutionarily conserved from yeast to higher eukaryotes. However, recent studies have revealed non-canonical functions of GCN1 that are independent of GCN2, such as its participation in cell proliferation, apoptosis, and the immune response, beyond the borders of species. Although it is known that GCN1 and GCN2 interact with ribosomes to accomplish amino acid starvation sensing, recent studies have reported that GCN1 binds to disomes (i.e. ribosomes that collide each other), thereby regulating both the co-translational quality control and stress response. We propose that GCN1 regulates ribosome-mediated signaling by dynamically changing its partners among RWD domain-possessing proteins via unknown mechanisms. We recently demonstrated that GCN1 is essential for cell proliferation and whole-body energy regulation in mice. However, the manner in which ribosome-initiated signaling via GCN1 is related to various physiological functions warrants clarification. GCN1-mediated mechanisms and its interaction with other quality control and stress response signals should be important for proteostasis during aging and neurodegenerative diseases, and may be targeted for drug development.

Background: Poisoning is a growing public problem that has shown increased prevalence in many countries worldwide, contributing to increased costs and mortalities. A lack of or insufficient information regarding the circumstances, chemicals, drugs and people at risk due to imperfect reporting system is regarded as a barrier to successful poisoning prevention and intervention efforts. In Saudi Arabia, poisoning cases are monitored at the central level in the Ministry of Health, with meticulous follow-up of cases across country areas through public health departments. The current study's objective was to describe the poisoning notification and reporting system in Makkah.Subjects and methods: All reports of chemical and drug overdose poisoning delivered to the environmental health and occupational safety department in Makkah Almukarramah over two years (2018-2019) were reviewed, together with verification of all systems, rules and guidelines organizing the performance of the department.Results: The total number of cases reported in 2018 was 209 cases, while it reached 42 cases in 2019. The overwhelming majority of the cases were Saudi (91.6%), with a slight predominance of males (57.4%) over females (42.6%). Generally, almost two-thirds of the cases occurred in children below 13 years (61.4%), most of the poisoning cases resulted from drug overdose (63.3%), while 34.7% were chemical poisoning. The most common drug poisoning was attributed to analgesics followed by antiepileptics, antihypertensive drugs, antipsychotics and antimicrobials, while cleaning and detergent agents were the most commonly poisoned chemicals. The majority of these agents were taken by the oral route. Children's chemical poisoning was significantly higher than that in older age groups (p<0.05). All intentional poisoning occurred in adults; the great majority of them (88.9%) used drug overdosing rather than chemical substances.Conclusion and recommendations: The current study results are consistent with most of the previous studies carried out in different regions in Saudi Arabia. Reviewing the performance and adherence of the “Environmental Health and Occupational Safety Department” to the guidelines and instruction regulating monitoring, notification and reporting of poison cases are satisfactory and the poisoning surveillance system is effective. Further in-depth studies are needed to elaborate other socioeconomic and demographic factors associated with chemical and drug overdose poisoning. Public health plans, policies and legislations should be implemented to reduce these factors, including prohibition over-the-counter pharmaceutical sales, selling the possibly harmful substances in kid-proof bottles and additional stringent rules governing chemical sale and storage. Intensive supervision of children is needed. Suicidal poisoning patients should seek psychiatric help to limit the possibility of attempting suicide again in the future. Furthermore, efforts are needed to plan and implement health education programs and campaigns about the factors proven in the current study to be significantly related to chemical and drug overdose poisoning to raise public knowledge about exposure to chemicals and its consequences. Popular communication media, commercial malls, road ads, learning institutions and workplaces can be used to deliver health education campaigns and programs. Advice on how to store chemicals safely and how to keep kids safe should be focused on during such programs.

Background: Irish dance is growing in popularity, evolving to a more athletic and demanding dance style. Aims: To conduct a systematic review, previously registered with PROSPERO, to identify prevalence, incidence, and injury pattern among Irish dancers and analyse associated risk factors. Methods: Six online databases, plus two dance-specific science publications were searched systematically. Studies were included if the pattern of injuries among Irish dancers were evaluated or the factors associated with injury were analysed, published in English or Portuguese, in peer-reviewed scientific journals. Four reviewers assessed the quality and level of evidence using the Downs and Black criteria and a modified Oxford Centre of Evidence-Based Medicine 2009 model, respectively. Results: Eleven articles were included, 8 level 3c (cross-sectional) and 3 level 3b (prospective). Mean DB percentage score was 63% ± 7,2%. Prevalence ranged from 72,2% to 92,6%, affecting mostly the foot/ankle complex. Only 2 articles reported incidence, which ranged from 3,4–10,6 injuries/1000 hours danced depending on injury definition. Psychological factors, elite level, and insufficient/poor sleep were associated with musculoskeletal injury. Conclusions: Injury prevalence and incidence is high in Irish dancers, with the foot and ankle more affected. Due to heterogeneity in injury definitions, methods, and populations, along with the need for improvement in studies quality, recommendations were made for future research.

(1)Aims of the study: calculating the underreporting ratio for two different medications, a fixed combination of 0.5% timolol + 0.2% brimonidine + 2.0% dorzolamide (antiglaucoma) and a fixed combination of sodium hyaluronate 0.1% + chondroitin sulfate 0.18% (artificial tear) and characterizing the features influencing the reporting of adverse drug reactions (ADRs) in spontaneous reporting; (2) Methods: the underreporting ratio was calculated by comparing the adverse drug reactions reported in the spontaneous reporting database for every 10,000 defined daily doses marketed and the adverse drug reactions from an active surveillance study for every 10,000 defined daily doses used for different drugs (antiglaucoma and artificial tear). The factors related to the report in spontaneous reporting through statistical tests were also determined; (3) Results: The underreporting ratio of spontaneous reporting was 0.006029% for antiglaucoma and 0.003552% for artificial tear; additionally, statistically significant differences were found for severity, unexpected adverse drug reactions, and incidence of adverse drug reactions in females; (4) Conclusions: The underreporting ratio of ADRs related to ophthalmic medications indicates worry since the cornerstone of pharmacovigilance focuses on spontaneous reporting. Besides, since underreporting seems to be selective, the role of certain aspects like gender, seriousness, severity, and unexpected ADRs, must be considered in future research.

Coronavirus Disease-19 (COVID-19) is presently wreaking havoc on public health and socio-economic development. Besides the upper and lower respiratory tract involvement, gastrointestinal symptoms are also reported in COVID-19 patients through gut-lung axis. Finding its way through the feces of infected individuals and other sources, the genetic material of SARS-CoV-2 (ssRNA) is reported widely in wastewater and is being used as a fingerprint for its detection. With millions of cases arriving every day, there is a need to level up the testing speed efficiency. Due to the restricted sampling potential of testing laboratories, clinical testing is unable to track all the symptomatic and asymptomatic cases. Wastewater-based epidemiology (WBE) bestows an auxiliary monitoring tool that will contribute in community level screening. Sample collection, concentration, RNA extraction, quantification and data analysis are the main steps involved in implementation of WBE that can be relied upon as an alarm call for an upcoming wave, emergence of a new variant or any future pandemic. WBE can be a cheaper and more practical alternative to high end and sophisticated clinical testing for community transmission detection. Worldwide, there are more than 300 reports entailing the occurrence of SARS-CoV-2 in wastewater exhibiting unique temporal trends with five of them in India. This review aims to address the present knowledge on surveillance of SARS-CoV-2 in wastewater and its implications.

Background: In Switzerland, Aedes albopictus is well established in Ticino, south of the Alps, where surveillance and control are implemented. The mosquito has also been observed in Swiss cities north of the Alps. Decision-making tools are urgently needed by the local authorities in order to optimize surveillance and control. Methods: A regularized logistic regression was used to link the long-term dataset of Ae. albopictus occurrence in Ticino with socio-environmental predictors. The probability of establishment of Ae. albopictus was extrapolated to Switzerland and more finely to the cities of Basel and Zurich. Results: The model performed well, with an AUC of 0.86. Ten so-cio-environmental predictors were selected as informative, including the road-based distance in minutes of travel by car from the nearest cell established in the previous year. The risk maps showed high suitability for Ae. albopictus establishment in the Central Plateau, the area of Basel and the lower Rhone Valley in the Canton of Valais. Conclusions: The areas identified as suitable for Ae. albopictus establishment are consistent with the actual current findings of tiger mosquito. Our approach provides a useful tool to prompt authorities’ intervention in the areas where there is higher risk of introduction and establishment of Ae. albopictus.

Abstract: The aim of the present study was to identify the age and sex-related associations between marital status with PA and TV time. We used data from Vigitel, an annual telephone survey started in 2006 in Brazil. We applied a complex sample logistic regression model to estimate the odds for PA and TV time comparing marital statuses according to age and sex subgroups, independent of obesity, hypertension, diabetes, self-assessed poor health, and smoking. Our sample included 561,837 individuals with a TV time &gt; 3 h/day (prevalence = 25.2%) and PA &gt; 150 min/week (prevalence = 35%). Compared to single individuals, married men and women were less likely to watch TV more than 3 h/day in participants &gt; 30 years old. When compared to single, married participants were less likely to do more than 150 min of PA/week at younger age groups. Married women older than 40 years were more likely to do more than 150 min of PA/week than the single ones, while there were no differences among married men by age group. In conclusion, married individuals are less likely to spend more than 3 hours a day watching TV than single individuals. Single men and women were more likely to do more than 150 min of PA/week at younger age groups and married women older than 40 years were more likely to do 150 min of PA/week than single women.

The coronavirus disease 2019 (COVID-19) pandemic has led to wastewater surveillance becoming an important tool for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within communities. As a result, molecular methods, in particular reverse transcription-quantitative PCR (RT-qPCR), have been employed to generate large data sets aimed at the detection and quantification of SARS-CoV-2 in wastewater. Although RT-qPCR is rapid and sensitive, there is no standard method that fits all use cases, there are no certified quantification standards and experiments are carried out using numerous different assays, reagents, instruments, and data analysis protocols. These variations can lead to the reporting of erroneous quantitative data resulting in potentially misleading interpretations and conclusions. We have reviewed the SARS-CoV-2 wastewater surveillance literature focusing on the variability of RT-qPCR data as revealed by inconsistent standard curves and associated parameters. We find that variation in these parameters and deviations from best practices as described in The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines suggest a lack of reproducibility and reliability in quantitative measurements of SARS-CoV-2 RNA in wastewater.

This study aims to analyze the pedigrees of calves affected by one of three congenital defects: aplasia genitalis, atresia ani et recti and hernia cerebralis. The defects were diagnosed by veterinary surgeons in the Czech surveillance program for bovine genetic disorders. The sires fathering affected calves were born in the Czech Republic or imported from 1986-2001. The cases occurred on farms across the Czech Republic. The pedigree of each case was examined for common maternal and paternal ancestors (inbreeding loops) and for ancestors shared by other cases of the defect. The 13 calves affected by aplasia genitalis had common ancestors in all cases. The results indicate hereditary causation with recessive inheritance. Additionally, in atresia ani et recti, some of the pedigrees of 25 affected calves support hereditary causation, and repeating ancestors were found for 11 calves. In contrast, our analysis of 11 hernia cerebralis cases did not confirm the genetic background. We demonstrated that the pedigree analysis of congenital defects could help in controlling genetic health, although the final goal in terms of inherited defects is the description of causal genes and mutations. Measures to control sires that father affected calves should be appropriate under the current knowledge, which include culling or prudent use of breeding with the monitoring of descendants.

The novel coronavirus SARS-CoV-2 likely emerged from a wildlife source with transmission to humans followed by rapid geographic spread throughout the globe and severe impacts on both human health and the global economy. Since the onset of the pandemic, there have been many instances of human-to-animal transmission involving companion, farmed and zoo animals, and limited evidence for spread into free-living wildlife. The establishment of reservoirs of infection in wild animals would create significant challenges to infection control in humans and could pose a threat to the welfare and conservation status of wildlife. We discuss the potential for exposure, onward transmission and persistence of SARS-CoV-2 in an initial selection of wild mammals (bats, canids, felids, mustelids, great apes, rodents and cervids). Dynamic risk assessment and targeted surveillance are important tools for the early detection of infection in wildlife, and here we describe a framework for collating and synthesising emerging information to inform targeted surveillance for SARS-CoV-2 in wildlife. Surveillance efforts should be integrated with information from public and veterinary health initiatives to provide insights into the potential role of wild mammals in the epidemiology of SARS-CoV-2.

In December 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in the province of Wuhan, China. Since then, it has spread worldwide with new mutations being reported. We performed genomic analysis to identify the changes in genetic diversity of SARS-CoV-2 between December 2019 and November 2020, and through molecular surveillance, we monitored the mutations that could be involved in viral fitness. We analyzed 2,213 complete genomes from 6 geographical regions worldwide, which were downloaded from GenBank and GISAID databases. Although SARS-CoV-2 presented low genetic diversity, there has been an increase over time, with the presence of several hotspot mutations throughout its genome. We identified 7 frequent mutations that resulted in non-synonymous substitutions (dN). Two of them, C14408T>P323L and A23403G>D614G, located in the nsp12 and Spike protein, respectively, emerged early in the pandemic and showed a considerable increase in frequency over time. Two other mutations, A1163T>I120F in nsp2 and G22992A>S477N in the Spike protein emerged recently and have spread in Oceania and Europe. Continuous molecular surveillance of SARS-CoV-2 will be necessary to detect and describe the transmission dynamics of new variants of the virus with clinical relevance. This information is important to improve programs to control the virus.