Outbreak Of Illness Research Articles

Antibacterial and Antibiofilm Efficacy of Thyme (Thymus vulgaris L.) Essential Oil against Foodborne Illness Pathogens, Salmonella enterica subsp. enterica Serovar Typhimurium and Bacillus cereus.

Nowadays, the wide spread of foodborne illness and the growing concerns about the use of synthetic food additives have shifted the focus of researchers towards essential oils (EOs) as possible antimicrobials and preservatives of natural origin. Thanks to their antimicrobial properties against pathogenic and food spoilage microorganisms, EOs have shown good potential for use as alternative food additives, also to counteract biofilm-forming bacterial strains, the spread of which is considered to be among the main causes of the increase in foodborne illness outbreaks. In this context, the aim of this study has been to define the antibacterial and antibiofilm profile of thyme (Thymus vulgaris L.) essential oil (TEO) against widespread foodborne pathogens, Salmonella enterica subsp. enterica serovar Typhimurium and Bacillus cereus. TEO chemical composition was analyzed through gas chromatography-mass spectrometry (GC-MS). Preliminary in vitro antibacterial tests allowed to qualitatively verify TEO efficacy against the tested foodborne pathogens. The subsequent determination of minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) values allowed to quantitatively define the bacteriostatic and bactericidal effects of TEO. To evaluate the ability of essential oils to inhibit biofilm formation, a microplate assay was performed for the bacterial biofilm biomass measurement. Results suggest that TEO, rich in bioactive compounds, is able to inhibit the growth of tested foodborne bacteria. In addition, the highlighted in vitro anti-biofilm properties of TEO suggest the use of this natural agent as a promising food preservative to counteract biofilm-related infections in the food industry.

The effects of antibiotics and illness on gut microbial composition in the fawn-footed mosaic-tailed rat (Melomys cervinipes).

The gut microbiota are critical for maintaining the health and physiological function of individuals. However, illness and treatment with antibiotics can disrupt bacterial community composition, the consequences of which are largely unknown in wild animals. In this study, we described and quantified the changes in bacterial community composition in response to illness and treatment with antibiotics in a native Australian rodent, the fawn-footed mosaic-tailed rat (Melomys cervinipes). We collected faecal samples during an undiagnosed illness outbreak in a captive colony of animals, and again at least one year later, and quantified the microbiome at each time point using 16s ribosomal rRNA gene sequencing. Gut bacterial composition was quantified at different taxonomic levels, up to family. Gut bacterial composition changed between time periods, indicating that illness, treatment with antibiotics, or a combination affects bacterial communities. While some bacterial groups increased in abundance, others decreased, suggesting differential effects and possible co-adapted and synergistic interactions. Our findings provide a greater understanding of the dynamic nature of the gut microbiome of a native Australian rodent species and provides insights into the management and ethical well-being of animals kept under captive conditions.

Influence of Biological and Environmental Factors in the Extraction and Concentration of Foodborne Pathogens using Glycan-Coated Magnetic Nanoparticles

Rapid detection of foodborne pathogens is essential to preventing foodborne illness outbreaks. Before detection can occur, however, it is often necessary to extract and concentrate bacteria. Conventional methods such as centrifugation, filtration, and immunomagnetic separation can often be time-consuming, ineffective, or costly when working with complex food matrices. This work used cost-effective glycan-coated magnetic nanoparticles (MNPs) for rapid concentration of Escherichia coli O157, Listeria monocytogenes, and Staphylococcus aureus. Glycan-coated MNPs were used to concentrate bacteria from both buffer solution and food matrices while examining the effect of factors including solution pH, bacterial concentration, and target bacterial species. In both pH 7 and reduced pH experiments, successful extraction of bacterial cells occurred in all food matrices and bacteria tested. In neutral pH buffer solution, bacteria were concentrated to 4.55 ± 1.17, 31.68 ± 6.10 and 64.27 ± 16.78 times their initial concentration (mean ± standard deviation) for E. coli, L. monocytogenes and S. aureus, respectively. Successful bacterial concentration occurred in several food matrices, including S. aureus in milk (pH 6), L. monocytogenes in sausage (pH 7), and E. coli O157 in flour (pH 7). The insights gained may facilitate future applications of glycan-coated MNPs to extract foodborne pathogens.

Pterostilbene, an active constituent of blueberries, enhances innate immune activation and restricts enterovirus D68 infection.

Enterovirus D68 (EV-D68) is a globally re-emerging respiratory pathogen implicated in outbreaks of severe respiratory illnesses and associated with acute flaccid myelitis. However, effective vaccines or treatments for EV-D68 infections remain scarce. We demonstrated that the active constituent of blueberries, pterostilbene (Pte), and its major metabolite, pinostilbene (Pin), facilitated innate immune responses in EV-D68-infected human respiratory cells. Pte and Pin treatment clearly relieved EV-D68-triggered cytopathic effects. Importantly, both Pte and Pin disrupted viral RNA replication (EC50 rank from 1.336 to 4.997 µM) and infectious virion production in a dose-dependent manner, without cytotoxicity at virucidal concentrations. Pte- or Pin-treated respiratory cells did not show any influences on EV-D68 entry but showed substantially decreased viral RNA replication and protein synthesis. Finally, we showed that Pte and Pin broadly suppressed the replication capacity of circulating EV-D68 strains isolated from recent pandemics. In summary, our results suggest that Pte and its derivative, Pin, enhance host immune recognition of EV-D68 and suppress EV-D68 replication, which represents a promising strategy for antiviral drug development.

Long Short-term Memory-Based Prediction of the Spread of Influenza-Like Illness Leveraging Surveillance, Weather, and Twitter Data: Model Development and Validation.

The potential to harness the plurality of available data in real time along with advanced data analytics for the accurate prediction of influenza-like illness (ILI) outbreaks has gained significant scientific interest. Different methodologies based on the use of machine learning techniques and traditional and alternative data sources, such as ILI surveillance reports, weather reports, search engine queries, and social media, have been explored with the ultimate goal of being used in the development of electronic surveillance systems that could complement existing monitoring resources. The scope of this study was to investigate for the first time the combined use of ILI surveillance data, weather data, and Twitter data along with deep learning techniques toward the development of prediction models able to nowcast and forecast weekly ILI cases. By assessing the predictive power of both traditional and alternative data sources on the use case of ILI, this study aimed to provide a novel approach for corroborating evidence and enhancing accuracy and reliability in the surveillance of infectious diseases. The model's input space consisted of information related to weekly ILI surveillance, web-based social (eg, Twitter) behavior, and weather conditions. For the design and development of the model, relevant data corresponding to the period of 2010 to 2019 and focusing on the Greek population and weather were collected. Long short-term memory (LSTM) neural networks were leveraged to efficiently handle the sequential and nonlinear nature of the multitude of collected data. The 3 data categories were first used separately for training 3 LSTM-based primary models. Subsequently, different transfer learning (TL) approaches were explored with the aim of creating various feature spaces combining the features extracted from the corresponding primary models' LSTM layers for the latter to feed a dense layer. The primary model that learned from weather data yielded better forecast accuracy (root mean square error [RMSE]=0.144; Pearson correlation coefficient [PCC]=0.801) than the model trained with ILI historical data (RMSE=0.159; PCC=0.794). The best performance was achieved by the TL-based model leveraging the combination of the 3 data categories (RMSE=0.128; PCC=0.822). The superiority of the TL-based model, which considers Twitter data, weather data, and ILI surveillance data, reflects the potential of alternative public sources to enhance accurate and reliable prediction of ILI spread. Despite its focus on the use case of Greece, the proposed approach can be generalized to other locations, populations, and social media platforms to support the surveillance of infectious diseases with the ultimate goal of reinforcing preparedness for future epidemics.

Springing in Your “Cleanup” Journey

Now, more than ever, nurses need to focus on self-care. This is especially true of school nurses returning to all regular responsibilities while managing multiple outbreaks of respiratory illnesses this past winter. In this brief article, the author discusses the various meanings of the word "clean-up" and how they can be applied to improved self-care.

Herbal Medicines Used for the Management of COVID-19

Abstract: A worldwide outbreak of respiratory illnesses has been caused by coronavirus disease (COVID-19). Traditional healers have used herbs and dietary plants for centuries to treat various conditions. This review discusses the prevention of COVID-19, multiple herbs used in the treatment of COVID-19, and their future perspectives. Various databases, such as PubMed, Web of Science, Scopus, Medline, and Google Scholar, were searched for articles related to herbal products' antiviral effects using different keywords: herbal, SARS-CoV-2, plant-derived drugs, COVID-19, coronavirus, etc. Herbal treatment has been used as a contemporary alternative medicine for COVID-19. By inhibiting the replication and entry of SARS-CoV-2 into host cells, herbs can inhibit the pathogenesis of COVID-19. This article discusses COVID-19 infection, its salient features, spread, the life cycle of coronavirus, active response to coronavirus, proposed treatment, and herbal drugs used in the prevention and treatment of COVID-19.

Genomically Informed Custom Selective Enrichment of Shiga Toxigenic Escherichia coli (STEC) Outbreak Strains in Foods Using Antibiotics

Shiga toxigenic Escherichia coli (STEC) have been implicated in major foodborne outbreaks worldwide. The STEC family of pathogens is biochemically diverse, and current microbiological methods for detecting STEC are limited by the lack of a universal selective enrichment approach and prone to interference by high levels of background microbiota associated with certain types of foods. A novel approach has been developed for the recovery of foodborne illness outbreak strains during outbreak investigations based on the analysis of whole genome sequence data of implicated clinical isolates to determine antimicrobial resistance (AMR) genes. The presence of certain AMR genes in STEC has been correlated with the ability to grow in the presence of a specific antibiotic, which can be used to supplement enrichment broths to improve the recovery of a target strain. The enhanced recovery of STEC strains with different AMR profiles from various food types (beef, sprouts, leafy greens, and raw milk cheese) containing high levels of background microbiota was demonstrated using AMR predictions for nine different antibiotics. This genomically informed custom selective enrichment approach increases the availability of analytical options and improves the reliability of food microbiological analyses in confirming food vehicles implicated in outbreak events and defining the scope of product contamination to support risk assessment and risk management actions.

Achieving UN SDGs in Food Supply Chain Using Blockchain Technology

Food supply chains are highly distributed, collaborative, heterogeneous, diverse, and varied by product, process, and destination. The global food supply chain (FSC) objective is to maintain a good balance between supply and demand and move products from producer to market. However, sustainability of the FSC has become a major concern as limited resources and increasing population pressure threaten its existence. Supply chain management is an important issue for FSC due to information flow throughout the supply chain. Industry-specific characteristics and extensive integration among multiple actors in an entire supply chain exacerbate this situation. The agri-food sector has one of the lowest rates of information technology penetration for innovation. Over the past thirty years, information and communication technology (ICT) has been introduced into the agricultural and food sectors, helping to improve food production and transportation. However, there are various challenges, such as transparency, accountability, food scandal, trust, and inefficient information flow, that the food supply chain is still facing in reaching sustainable goals. The complexity of food supply systems and the opportunities and challenges faced regarding desired sustainability performance need to be examined to achieve the United Nations Sustainable Development Goals (SDGs). Blockchain is an emerging and disruptive digital technology that can transform governance and sustainability in integrated food supply chains. It provides a transparent, immutable, and traceable ledger that minimizes anomalies and information fraud, making it a potential solution for designing a transparent, traceable food system. Blockchain can potentially improve the sustainability of the food supply chain by providing a transparent traceability system. Food traceability is important for managing the food supply chain and protecting public health. It allows quick and accurate traceability of contaminated food that causes foodborne illness outbreaks, leading to the withdrawal of contaminated food from markets. Blockchain can achieve traceability, provenance tracking, transparency, and reduce environmental impact in the food supply chain. It also helps in achieving sustainable development goals set by the UN. However, there is no scientific research on blockchain’s contribution to achieving these goals in the food supply chain. Therefore, this article presents a systematic literature review and thematic analysis to study the relationship between FSC sustainability, blockchain, and sustainable development goals.

Development of an Empirically Derived Measure of Food Safety Culture in Restaurants

A poor food safety culture has been described as an emerging risk factor for foodborne illness outbreaks, yet there has been little research on this topic in the retail food industry. The purpose of this study was to identify and validate conceptual domains around food safety culture and develop an assessment tool that can be used to assess food workers’ perceptions of their restaurant’s food safety culture. The study, conducted from March 2018 through March 2019, surveyed restaurant food workers for their level of agreement with 28 statements. We received 579 responses from 331 restaurants spread across eight different health department jurisdictions. Factor analysis and structural equation modeling supported a model composed of four primary constructs. The highest rated construct was Resource Availability (x¯=4.69, sd=0.57), which assessed the availability of resources to maintain good hand hygiene. The second highest rated construct was Employee Commitment (x¯=4.49, sd=0.62), which assessed workers’ perceptions of their coworkers’ commitment to food safety. The last two constructs were related to management. Leadership (x¯=4.28, sd=0.69) assessed the existence of food safety policies, training, and information sharing. Management Commitment (x¯=3.94, sd=1.05) assessed whether food safety was a priority in practice. Finally, the model revealed one higher-order construct, Worker Beliefs about Food Safety Culture (x¯=4.35, sd=0.53). The findings from this study can support efforts by the restaurant industry, food safety researchers, and health departments to examine the influence and effects of food safety culture within restaurants.

Combine thermal processing with polyvalent phage LPEK22 to prevent the Escherichia coli and Salmonella enterica contamination in food

Thermal processing is the most frequently used method to destruct bacteria in food processing. However, insufficient thermal processing may lead to the outbreak of foodborne illness. This study combined thermal processing with thermostable phage to prevent food contamination. The thermostable phages were screened which can retain activity at 70 °C for 1 h. Among them, the polyvalent phage LPEK22 was obtained to lyse Escherichia coli and Salmonella enterica, especially several multi-drug resistant bacteria. In milk (liquid food matrix), LPEK22 significantly reduced the E. coli by 5.00 ± 0.18 log10 CFU/mL and S. enterica by 4.20 ± 0.23 log10 CFU/mL after thermal processing at 63 °C for 30 min. For beef sausage (solid food matrix), LPEK22 significantly reduced the E. coli by 2.34 ± 0.17 log10 CFU/cm2 and S. enterica by 1.54 ± 0.13 log10 CFU/cm2 after thermal processing at 66 °C for 90 s. Genome analysis revealed that LPEK22 was a novel phage with a unique tail spike protein belonging to the family of Ackermannviridae. LPEK22 did not contain lysogenic, drug-resistant, and virulent genes that may compromise the safety of food application. These results determined that LPEK22, a novel polyvalent Ackermannviridae phage, could combine with thermal processing to prevent drug-resistant E. coli and S. enterica both in vitro and in foods.

Clinical and Etiological Study of Influenza Like Illness Outbreak in Children: An Office-Based Study

Background Many viral infections can show clinical presentations mimicking influenza. A broad term influenza like illness ILI was given to these. Objective To ascertain relative proportion of influenza and non-influenza viruses in severe ILI. To study clinical or epidemiological patterns differentiating both influenza and non-influenza etiologies of ILI.Methods All the patients who presented with severe ILI were included. Their clinical and epidemiological data was entered in a proforma and respiratory secretions were analyzed for presence of Influenza andor Respiratory syncitial virus RSV.Results A total of 112 patients reported to the practice during the outbreak and at least one virus was detected in 89.28 n100 of the nasopharyngeal secretions. Majority of the isolates 58.03 n65 were of non-influenza virus with RSV being the dominant virus identified 55.35 n62. There were some clinical indicators for the etiological agent with isolated URTI being less common while LRTI and wheeze being common in RSV.Conclusion Clinician should be aware of wide range of viral etiologies for the ILI and should take the assistance of viral diagnostic tests whenever possible.nbsp

Detection, Biochemical and Molecular Characterization of <i>Clostridium sporogens</i> in <i>Nono</i>: A Nigerian Traditionally Fermented Yoghurt Drink

Nono is a traditionally fermented milk drink commonly consumed in the Northern parts of Nigeria. It is produced through the spontaneous fermentation of raw cow milk by Lactic Acid Bacteria (LAB), a process that could result to the contamination of the product with such pathogenic organisms as Clostridia spp. The aim of this research was therefore to determine the incidence of Clostridia species in thirty-two (32) ready-to-drink nono samples collected directly from a number of Fulani vendors in randomly selected locations within the Federal Capital Territory (FCT), Abuja, Nigeria. Isolated organisms were further subjected to some morphological and biochemical characterizations using standard microbiological procedures. The results obtained indicate that fourteen (14) isolates were putatively identified to be Clostridium sp., out of which five (5) isolates were confirmed to be Clostridium sporogens by a BLAST analysis of their respective 16SrRNA nucleotide sequence. It was concluded that, the detection of these pathogenic strains in frequently consumed product like nono could pose a public health risk and proactive measures to prevent an outbreak of food borne illness from nono consumption, were recommended.

Multiplex Immunoassay Approaches Using Luminex® xMAP® Technology for the Study of COVID-19 Disease.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has been one of the most severe outbreaks of respiratory illness in history. The clinical symptoms of COVID-19 may be similar to flu, although they can be life-threatening, particularly in the elderly and immunocompromised population. Together with nucleic acid detection, serological testing has been essential for the diagnosis of SARS-CoV-2 infection but has been critically important for studying the epidemiology, serosurveillance, and for vaccine research and development. Multiplexed immunoassay technologies have a particular advantage as they can simultaneously measure multiple analytes from a single sample. xMAP technology is a multiplex analysis platform that can measure up to 500 analytes at the same time from the same sample. It has been shown to be an important tool for studying immune response to the various SARS-CoV-2 antigens, as well as for measuring host protein biomarker levels as prognostic indicators of COVID-19. In this chapter, we describe several key studies where xMAP technology was used for multiplexed analysis of SARS-COV-2 antibody responses and host protein expression in COVID-19 patients.

Significant Causative Agents That Cause Toxicity in Mushrooms

Worldwide outbreaks of food-related illnesses brought on by wild mushroom poisoning have raised questions about food safety. On an annual basis, we hear a lot of stories from all over the globe concerning people eating toxic mushrooms. Scientists are interested in it, notably in the areas of hazardous substance composition, process, and its use in poisonous mushrooms. The toxins which are present in poisonous mushrooms are quickly taken in by blood vessels and travel straight towards their aimed target despite withstanding the extremes of the temperature of cooking and the digestive acids. However, patients must be aware that in 95% of instances, the nature of fungus and toxins is unknown, thus evaluation and therapy rely on the symptoms they are experiencing at the time of hospitalization. Clinical syndromes associated with mushroom poisoning include fulminate hepatic failure, immediate failure of the renal system, rhabdomyolysis, erythromelalgia, haemorrhage, gastroenteritis, mental disturbance, and irritation of the skin. The aim of this review is to explain poisonous mushrooms, the medical symptoms of toxic mushrooms, different noxious, and how they are used medically.

Conhecimento e boas práticas de manipulação de produtos de origem animal no ambiente domiciliar

Abstract Good food handling practices should be adopted in the home setting, as inadequate practices could lead to the outbreak of foodborne illnesses. The aim of the present study was to investigate knowledge and good food handling practices for products of animal origin by consumers in the home setting and test associations with the socioeconomic characteristics of the respondents. A questionnaire was answered by a non-probabilistic sample. The questionnaire was available online on free access digital platforms for seven days and was used to collect information on the gender, age, income, and schooling of the respondents as well as safe food handling practices in the home setting. Data analysis involved descriptive statistics and the chi-square test to compare the frequencies of the answers per category. A total of 666 responses were obtained. Most respondents were women, had a university/college education, were between 30 and 59 years of age, and had an income of more than four times the monthly minimum wage. The majority of respondents reported positive practices and attitudes regarding food handling in the home setting; 99.5% washed their hands prior to handling food, 89% performed the cooking of animal products and 85.6% washed the cutting surface after cutting each food. Associations were found between some attitudes reported by consumers and the categories of gender, age, schooling, and income (p ≤ 0.05). Women had more good food handling practices compared to men. The results suggest that most respondents practiced good food handling practices. Safe practices were related to the level of schooling, monthly income and age of the participants.

Developing Intelligent Packaging Solutions to Prevent Foodborne Illnesses

Many of us avoid foods that contain ingredients we haven’t heard of. However, many of these chemicals are beneficial because they prevent the growth of bacteria that cause foodborne illnesses. Although food quality standards have improved dramatically, outbreaks of foodborne illnesses are still common. Luckily, we have one line of defence to exploit: antibacterial food packaging. Dr Kay Cooksey of Clemson University is leading ground-breaking research to overcome the hurdles associated with antibacterial food packaging, bringing it one step closer to market.

Brewing epidemic of communicable diseases after massive flooding in Pakistan.

Brewing epidemic of communicable diseases after massive flooding in Pakistan.

Campylobacter fetus foodborne illness outbreak in the elderly.

In June 2021, a cluster of seven cases of Campylobacter fetus infections occurred in a rehabilitation center and caused significant morbidity in elderly patients including five with bacteremia and two with osteoarticular medical device infections. The genetic identity identified by whole genome sequencing of the different Campylobacter fetus strains confirms a common source. This foodborne illness outbreak may have resulted from the consumption of unpasteurized dairy products, such as a cow's raw milk cheese resulting from a farm-to-fork strategy.

Importance of Livestocks and Blackleg Disease Spread in Livestock After Flood

Animals are utilized for a variety of things, including food production, companionship, and scientific research. Different products such as wool, hides, skin, and hoofs used to make different products for the benefit of human. One of the many different types of health effects caused by natural disasters that happen all over the world are floods. Floods can worsen the spread of various contagious diseases in animals in addition to the immediate risks like drowning. No reports of infectious diseases spread by floods around the world have been made as of yet. This review describes a potential illness outbreak that could happen during or after flooding.