Risk Of Disease Outbreaks Research Articles

Zoonotic outbreak risk prediction with long short-term memory models: a case study with schistosomiasis, echinococcosis, and leptospirosis

BackgroundZoonotic infections, characterized with huge pathogen diversity, wide affecting area and great society harm, have become a major global public health problem. Early and accurate prediction of their outbreaks is crucial for disease control. The aim of this study was to develop zoonotic diseases risk predictive models based on time-series incidence data and three zoonotic diseases in mainland China were employed as cases.MethodsThe incidence data for schistosomiasis, echinococcosis, and leptospirosis were downloaded from the Scientific Data Centre of the National Ministry of Health of China, and were processed by interpolation, dynamic curve reconstruction and time series decomposition. Data were decomposed into three distinct components: the trend component, the seasonal component, and the residual component. The trend component was used as input to construct the Long Short-Term Memory (LSTM) prediction model, while the seasonal component was used in the comparison of the periods and amplitudes. Finaly, the accuracy of the hybrid LSTM prediction model was comprehensive evaluated.ResultsThis study employed trend series of incidence numbers and incidence rates of three zoonotic diseases for modeling. The prediction results of the model showed that the predicted incidence number and incidence rate were very close to the real incidence data. Model evaluation revealed that the prediction error of the hybrid LSTM model was smaller than that of the single LSTM. Thus, these results demonstrate that using trending sequences as input sequences for the model leads to better-fitting predictive models.ConclusionsOur study successfully developed LSTM hybrid models for disease outbreak risk prediction using three zoonotic diseases as case studies. We demonstrate that the LSTM, when combined with time series decomposition, delivers more accurate results compared to conventional LSTM models using the raw data series. Disease outbreak trends can be predicted more accurately using hybrid models.

Factors influencing community engagement approaches used in Aedes aegypti management in Cairns, Australia.

An important part of preventing and managing Aedes-borne mosquito disease outbreak risk is engaging the community. Research shows that high-income countries tend to use top-down measures for Aedes mosquito management, favouring educational approaches to engage the community over participatory approaches that actively involve and empower the community in addressing disease risk. Little is known about the reasons behind the use of these approaches and how they could be strengthened. This research explores the community engagement approaches used in Aedes mosquito management in Cairns, Queensland, Australia and the factors influencing the choice of these approaches. A case study design was used, drawing on two qualitative methods-key informant, semi-structured interviews (n = 25), and a document review (n = 20). Thematic analysis was used to identify, analyse and attribute meaning from the data. Various approaches were used to engage the community, including direct interaction through door-to-door inspections, broad outreach via mass media campaigns, and community participation in a novel mosquito replacement strategy. Factors influencing the choice of these approaches included government legislative responsibilities, research-related ethical obligations, work norms within local government and public health units, the perceived importance of gaining community trust, constraints on workforce capacity, time and funding. There were multiple factors influencing the community engagement approaches used in this study. Resource constraints, institutional norms and prevailing attitudes and beliefs were identified as hindering the use of more empowering approaches to engaging the community. These barriers should be considered and addressed in the planning of Aedes mosquito management to better support community engagement in this setting. SO WHAT?: Community engagement is an important aspect of managing the Aedes mosquito disease threat. With the global increase in Aedes mosquito-borne disease risk, these findings can help other at-risk settings understand potential organisational impediments to engaging the community. This is particularly important when advocating for the inclusion of bottom-up approaches in policy, and to ensure sufficient resources are allocated to strengthen community engagement in Aedes mosquito management.

Influence of stocking density and interaction variability on disease progression of white spot syndrome virus-infected shrimp under different risk scenarios

White spot syndrome virus (WSSV), the causative agent of white spot disease (WSD), is the most significant viral pathogen affecting farmed shrimp. As the culture model for whiteleg shrimp has evolved into a higher-intensity model, the need to study the influence of stocking density on disease progression in pond culture systems has been reinforced. Therefore, we assessed WSD progression by deriving a direct correlation between seasonal disease outbreak risk, stocking density, and viral shedding rate (WSSV genome copies/L/g) using three different stocking densities: high (210 shrimp/m2), medium (140 shrimp/m2), and low (70 shrimp/m2). In Experiment 1 (three stocking densities at 25 °C) and Experiment 2 (stocking density × temperature conditions), shrimp showed relatively high cumulative mortality within the temperature range of optimal WSSV replication (23–29 °C). Notably, the mortality trend, peak viral loads, and viral shedding of WSSV-infected shrimp occurred earlier under high-density conditions, regardless of temperature. Thereafter, this study established WSD risk scenarios based on water temperature conditions and confirmed a significant difference in mortality trends between vulnerable and less vulnerable water temperature scenarios under high- and low-density conditions. The vulnerable water temperature scenario included constant (25 °C), shifting-up (20 °C to 30 °C), and shifting-down (30 °C to 20 °C) conditions, whereas the less vulnerable water temperature scenario included constant 20 °C and 30 °C conditions. Based on mortality trends, the WSD risk scenarios revealed that the times to 50 % mortality for shrimp at high, medium, and low densities were 4, 5, and 6 days post-infection (dpi) in the vulnerable water temperature scenario, and 6, 7, and 9 dpi in the less vulnerable water temperature scenario. Viral shedding variability was evaluated based on the correlation between viral loads and viral shedding rate, and linear regression analysis revealed a significant positive correlation between viral shedding rates and viral loads in shrimp, regardless of WSD risk scenarios or stocking density conditions. Notably, a relatively enhanced viral shedding rate was observed at higher stocking densities (from low- to high-density conditions) and under vulnerable water temperature scenarios. This study suggests that increased stocking density and vulnerable water temperature scenarios could induce greater interactions among WSSV-infected shrimp. It also confirmed the potential role of risk scenarios, stocking density, and viral shedding in WSD progression, providing insights into the disease outbreak mechanisms on shrimp farms.

Effects of Atractylodes macrocephala polysaccharide on growth performance, serum biochemical indexes, and intestinal microflora of largemouth bass (Micropterus salmoides)

IntroductionAs the aquaculture industry intensifies to enhance production efficiency and capacity, the risk of disease outbreaks in high-density systems, such as those for largemouth bass, has escalated. This necessitates the exploration of novel strategies for disease prevention and control. Studies have shown that Atractylodes macrocephala polysaccharide (AMP) possesses the functions of promoting growth and enhancing immune capacity, making it a potential feed additive in animal production.MethodsThis study aimed to assess the impact of AMP on the growth performance, serum biochemical indices, and intestinal flora structure of largemouth bass. A total of 360 healthy largemouth bass (mean weight: 15.25 ± 1.29 g) were randomly assigned to four groups, each with three replicates. The groups were fed diets supplemented with 0% (Group D, control group), 0.4% (Group A), 0.8% (Group B), or 1.2% (Group C) AMP for 42 days.ResultsThe results showed that the addition of an appropriate amount of AMP in the feed significantly improved the weight gain rate (WGR) and specific growth rate (SGR) of largemouth bass, reduced the feed conversion ratio (FCR), and enhanced growth performance. AMP reduced the levels of AST and ALT, indicating a hepatoprotective effect on largemouth bass, with significant differences from the control group (P < 0.05). AMP also improved the intestinal microbiota composition of largemouth bass, positively affecting intestinal health. The analysis of intestinal microbiota revealed 1,288 amplicon sequence variants (ASVs) in the intestine of largemouth bass in Group B, dominated by Firmicutes and Bacteroidota. In contrast, Group C (1.2%) had 920 ASVs, with Fusobacteriota and Firmicutes as the major components, while the relative abundance of Firmicutes was lower, showing significant differences from the control Group D. The functional analysis of intestinal microbiota based on KEGG showed significant differences (P < 0.05) among the four groups in Carbon metabolism, Biosynthesis of amino acids, and Metabolic pathways.DiscussionThe study concludes that the inclusion of AMP at 0.8% – 1.2% in the feed can enhance the growth performance and intestinal health of largemouth bass, offering a promising strategy for disease prevention and control in intensive aquaculture settings.

Integrating host biological and ecological variables to predict probability of haemosporidian infection in raptors

Variations in host traits that influence their exposure and susceptibility may impact probability of vector-transmitted diseases. Therefore, identifying the predictors of infection probability is necessary to understand the risk of disease outbreaks during expanding environmental perturbation. Here, we conducted a large survey based on microscopic examination and molecular analysis of haemosporidian parasite infection in raptors rescued at the Beijing Raptor Rescue Centre. Combining these data with biological and ecological variables of the raptors, we determined predictors that affect the probability of haemosporidian infection using generalized linear mixed models and multimodel inference. Our results showed that infection probability exhibited considerable variation across host species in raptors, and body mass, sex, and evolutionary history played relatively weaker roles in driving infection probability. Instead, activity pattern, age, geographic range size, migration distance, and nest type were important predictors of the probability of haemosporidian infection, and the role of each predictor differed in the three main haemosporidian genera (Plasmodium, Haemoproteus, and Leucocytozoon). This macro-ecological analysis will add to our understanding of host traits that influence the probability of avian haemosporidian infection and will help inform risk of emerging diseases.

Hexagonal Boron Nitride Quantum Dots Embedded on Layer-by-Layer Films for Peroxidase-Assisted Colorimetric Detection of β-Galactosidase Producing Pathogens.

Pathogen detection has become a major research area all over the world for water quality surveillance and microbial risk assessment. Therefore, designing simple and sensitive detection kits plays a key role in envisaging and evaluating the risk of disease outbreaks and providing quality healthcare settings. Herein, we have designed a facile and low-cost colorimetric sensing strategy for the selective and sensitive determination of β-galactosidase producing pathogens. The hexagonal boron nitride quantum dots (h-BN QDs) were established as a nanozyme that showed prominent peroxidase-like activity, which catalyzes 3,3',5,5'-tetramethylbenzidine (TMB) oxidation by H2O2. The h-BN QDs were embedded on a layer-by-layer assembled agarose biopolymer. The β-galactosidase enzyme partially degrades β-1,4 glycosidic bonds of agarose polymer, resulting in accessibility of h-BN QDs on the solid surface. This assay can be conveniently conducted and analyzed by monitoring the blue color formation due to TMB oxidation within 30 min. The nanocomposite was stable for more than 90 days and was showing TMB oxidation after incubating it with Escherichia coli (E. coli). The limit of detection was calculated to be 1.8 × 106 and 1.5 × 106 CFU/mL for E. coli and Klebsiella pneumonia (K. pneumonia), respectively. Furthermore, this novel sensing approach is an attractive platform that was successfully applied to detect E. coli in spiked water samples and other food products with good accuracy, indicating its practical applicability for the detection of pathogens in real samples.

Opening windows as a supplementary ventilation strategy for large classrooms in a pandemic situation: Field measurements and simulation

The coronavirus disease 2019 (COVID-19) has led to significant global health emergencies in recent years, prompting widespread recommendations across various regions for opening windows in building codes. However, official guidelines have not adequately addressed the details of window opening arrangements related to the supporting evidence from existing literature. This study investigated the risk of disease outbreaks via respiratory transmission in large university studio classrooms. It examined the effectiveness of window-door opening strategies combined with mechanical ventilation in mitigating the infection risk of respiratory diseases in such spaces. A full-scale school ventilation performance test bed was used to measure indoor airflow and CO2 distribution patterns. Comparisons were made with the numerical simulation of exhaled viral emissions. A modified Wells-Riley equation was employed to calculate inhalation exposure and disease infection risks at the room level. Measurements showed that fresh air ventilation from the mechanical system was relatively low compared to existing standards, especially in pandemic situations. The results show that opening windows can lead to a decrease to low probabilities (below 5 %) of infection risk in 85.02 % area of a classroom over an 8-h period, which demonstrates that window-opening behavior is an effective supplementary strategy for large educational spaces with mechanically ventilated systems during emergencies when active measures are insufficient for diluting diseases. Furthermore, the study reveals that maximizing outdoor air rates by opening all windows may occasionally result in adverse indoor airflow redistribution, increasing virus load from 0.0382 to 0.8926 quanta/m3 near the virus source locations.

A Flexible, Quantitative Plasmonic-Fluor Lateral Flow Assay for the Rapid Detection of Orthoebolavirus zairense and Orthoebolavirus sudanense.

Filoviruses comprise a family of single-stranded, negative-sense RNA viruses with a significant impact on human health. Given the risk for disease outbreaks, as highlighted by the recent outbreaks across Africa, there is an unmet need for flexible diagnostic technologies that can be deployed in resource-limited settings. Herein, we highlight the use of plasmonic-fluor lateral flow assays (PF-LFA) for the rapid, quantitative detection of an Ebolavirus-secreted glycoprotein, a marker for infection. Plasmonic fluors are a class of ultrabright reporter molecules that combine engineered nanorods with conventional fluorophores, resulting in improved analytical sensitivity. We have developed a PF-LFA for Orthoebolavirus zairense (EBOV) and Orthoebolavirus sudanense (SUDV) that provides estimated limits of detection as low as 0.446 and 0.641 ng/mL, respectively. Furthermore, our assay highlights a high degree of specificity between the two viral species while also maintaining a turnaround time as short as 30 min. To highlight the utility of our PF-LFA, we demonstrate the detection of EBOV infection in non-human primates. Our PF-LFA represents an enormous step forward in the development of a robust, field-deployable assay for filoviruses.

A novel goose-origin Tembusu virus exhibits pathogenicity in day-old chicks with evidence of direct contact transmission

In late 2020, an outbreak of Tembusu virus (TMUV)-associated disease occurred in a 45-day-old white Roman geese flock in Taiwan. Here, we present the identification and isolation of a novel goose-origin TMUV strain designated as NTU/C225/2020. The virus was successfully isolated using minimal-pathogen-free duck embryos. Phylogenetic analysis of the polyprotein gene showed that NTU/C225/2020 clustered together with the earliest isolates from Malaysia and was most closely related to the first Taiwanese TMUV strain, TP1906. Genomic analysis revealed significant amino acid variations among TMUV isolates in NS1 and NS2A protein regions. In the present study, we characterized the NTU/C225/2020 culture in duck embryos, chicken embryos, primary duck embryonated fibroblasts, and DF-1 cells. All host systems were susceptible to NTU/C225/2020 infection, with observable lesions. In addition, animal experiments showed that the intramuscular inoculation of NTU/C225/2020 resulted in growth retardation and hyperthermia in day-old chicks. Gross lesions in the infected chicks included hepatomegaly, hyperemic thymus, and splenomegaly. Viral loads and histopathological damage were displayed in various tissues of both inoculated and naïve co-housed chicks, confirming the direct chick-to-chick contact transmission of TMUV. This is the first in vivo study of a local TMUV strain in Taiwan. Our findings provide essential information for TMUV propagation and suggest a potential risk of disease outbreak in chicken populations.

Low biodiversity in cities boosts the risk of disease outbreak

Low biodiversity in cities boosts the risk of disease outbreak

Predicting the Risk of Verticillium Wilt in Olive Orchards Using Fuzzy Logic

Developing models to understand disease dynamics and predict the risk of disease outbreaks to facilitate decision making is an integral component of plant disease management. However, these models have not yet been developed for one of the most damaging diseases in Mediterranean olive-growing areas (verticillium wilt (VW), caused by the fungus Verticillium dahliae Kleb.), although there are parameters (e.g., level of V. dahliae inoculum in the soil, level of susceptibility of the olive cultivar, isothermality, coefficient of variation of seasonal precipitation, etc.) that have previously been correlated with the severity of the disease. Using the data from previous VW studies conducted in the Guadalquivir Valley of Andalusia (one of the most damaged areas worldwide), in this work, a set of fuzzy logic (FL) models is developed with the aforementioned disease and climatic parameters, and the results are compared with machine learning (ML) models, of known effectiveness, to predict the risk levels of VW appearance in an olive orchard. Under these conditions, both groups of models were less effective than those previously studied with simpler models or models used under controlled conditions. However, the accuracy achieved with the most efficient FL model (60%; classification system based on fuzzy rules using the Ishibuchi method with a weighting factor) was somewhat greater than the efficiency achieved with the most efficient ML model (59.0%; decision tree classifier), in addition to being more appropriate (from a practical point of view) for the incorporation into a decision support system by allowing the risk of appearance of each observation to be known by providing rules for each of the combinations of the different parameters with similar precision. Therefore, in this study, we propose the FL methodology as suitable to act as an expert system for the future creation of a decision support system for VW in olives.

Generation of porcine PK-15 cells lacking the Ifnar1 or Stat2 gene to optimize the efficiency of viral isolation

Because pigs are intermediate or amplifying hosts for several zoonotic viruses, the pig-derived PK-15 cell line is an indispensable tool for studying viral pathogenicity and developing treatments, vaccines, and preventive measures to mitigate the risk of disease outbreaks. However, we must consider the possibility of contamination by type I interferons (IFNs), such as IFNα and IFNβ, or IFN-inducing substances, such as virus-derived double-stranded RNA or bacterial lipopolysaccharides, in clinical samples, leading to lower rates of viral isolation. In this study, we aimed to generate a PK-15 cell line that can be used to isolate viruses from clinical samples carrying a risk of contamination by IFN-inducing substances. To this end, we depleted the IFN alpha and beta receptor subunit 1 (Ifnar1) gene or signal transducer and activator of transcription 2 (Stat2) gene in PK-15 cells using the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 method. Treatment of PK-15 cells lacking Ifnar1 or Stat2 with IFNβ or poly (I:C) resulted in no inhibitory effects on viral infection by a lentiviral vector, influenza virus, and Akabane virus. These results demonstrate that PK-15 cells lacking Ifnar1 or Stat2 could represent a valuable and promising tool for viral isolation, vaccine production, and virological investigations.

A Cost–Benefit Analysis of Preparing National Veterinary Services for Transboundary Animal Disease Emergencies

The natural, accidental, or deliberate release of pathogens into livestock populations carries with it a range of consequences for society, from zoonotic disease outbreaks, to changes in food security and economic welfare. An important contribution to mitigating the risk of disease outbreaks comes from having well-prepared emergency response plans and agencies with the capacity to put those plans into operation. In the case of animal disease, national Veterinary Services (VS) take a central role. Unknown and uncertain events, such as if, when and where the next disease outbreak will occur makes economic decision-making a challenge. While the costs of preparing for emergencies can be quantified in a conventional manner, the scope, scale, and likelihood of benefits actually accruing are all subject to uncertainty. This study attempts to examine the costs and benefits of preparing national VS for animal disease emergencies, including natural, accidental, or deliberate release of pathogens. Data collected as part of the World Organisation for Animal Health’s Performance of VS program for countries in East and West Africa and South East Asia were used for estimating investment costs. A state-contingent approach is used to constrain the uncertainty space in terms of disease impact. The probability of a disease event occurring and the probability of that event being contained by emergency preparation are used to describe a frontier at which investment breaks-even in a variety of scenarios. An increased probability of breaking-even on investment was found with high livestock numbers per capita and increasing intensification in livestock production systems. The method and findings provide a means to understand the benefits of preparing for uncertain events and are aimed to further the dialogue around policy development for livestock disease emergencies in lower-income countries.

The potential of resilience indicators to anticipate infectious disease outbreaks, a systematic review and guide.

To reduce the consequences of infectious disease outbreaks, the timely implementation of public health measures is crucial. Currently used early-warning systems are highly context-dependent and require a long phase of model building. A proposed solution to anticipate the onset or termination of an outbreak is the use of so-called resilience indicators. These indicators are based on the generic theory of critical slowing down and require only incidence time series. Here we assess the potential for this approach to contribute to outbreak anticipation. We systematically reviewed studies that used resilience indicators to predict outbreaks or terminations of epidemics. We identified 37 studies meeting the inclusion criteria: 21 using simulated data and 16 real-world data. 36 out of 37 studies detected significant signs of critical slowing down before a critical transition (i.e., the onset or end of an outbreak), with a highly variable sensitivity (i.e., the proportion of true positive outbreak warnings) ranging from 0.03 to 1 and a lead time ranging from 10 days to 68 months. Challenges include low resolution and limited length of time series, a too rapid increase in cases, and strong seasonal patterns which may hamper the sensitivity of resilience indicators. Alternative types of data, such as Google searches or social media data, have the potential to improve predictions in some cases. Resilience indicators may be useful when the risk of disease outbreaks is changing gradually. This may happen, for instance, when pathogens become increasingly adapted to an environment or evolve gradually to escape immunity. High-resolution monitoring is needed to reach sufficient sensitivity. If those conditions are met, resilience indicators could help improve the current practice of prediction, facilitating timely outbreak response. We provide a step-by-step guide on the use of resilience indicators in infectious disease epidemiology, and guidance on the relevant situations to use this approach.

Ultraviolet light differentially reduces viability of fish‐ and fish farm‐associated flavobacteria (families Flavobacteriaceae and Weeksellaceae)

AbstractObjectiveGlobally, flavobacteria (family Flavobacteriaceae and Weeksellaceae) are leading causes of disease‐related losses in fish‐farms and hatcheries. One route flavobacteria gain access to aquaculture facilities is via source water. Ultraviolet (UV) light treatment of source water has been effective in reducing the risk of disease outbreaks caused by nonflavobacteria; however, the UV dose required to inactivate flavobacteria has been understudied. The primary objective of this study was to examine the efficacy of UV light treatments for reducing the viability of fish‐pathogenic and fish‐associated Flavobacterium and Chryseobacterium species in a planktonic form.MethodsSixty‐five flavobacterial isolates belonging to ten Flavobacterium spp. and Chryseobacterium spp. were exposed to a low (25 mJ/cm2) and high (126 mJ/cm2) dose of UV light via a collimating beam apparatus under in vitro conditions, after which treatment efficacy was determined via culture.ResultAll assayed flavobacteria were reduced by an average of ~1000‐fold or ~100,000‐fold at the low and high UV doses, respectively; however, substantial differences in reduction at the same UV dose were noted among isolates of the same flavobacterial species, including F. psychrophilum, F. columnare, and F. oreochromis. In addition, F. psychrophilum multilocus sequence typing variants ST10 and ST78, which are two of the most widespread variants in the United States of America, were among the least susceptible to ultraviolet light.ConclusionOverall, results demonstrate that viable flavobacteria can be reduced substantially by ultraviolet doses of 25–126 mJ/cm2, suggesting such treatments represent a promising tool for minimizing flavobacterial loads in hatcheries and aquaculture facilities, thereby enhancing biosecurity and reducing the risk of epizootics.

The Protective Role of Oleuropein Aglycone against Pesticide-Induced Toxicity in a Human Keratinocytes Cell Model.

The extensive use of agricultural pesticides to improve crop quality and yield significantly increased the risk to the public of exposure to small but repeated doses of pesticides over time through various routes, including skin, by increasing the risk of disease outbreaks. Although much work was conducted to reduce the use of pesticides in agriculture, little attention was paid to prevention, which could reduce the toxicity of pesticide exposure by reducing its impact on human health. Extra virgin olive oil (EVOO), a major component of the Mediterranean diet, exerts numerous health-promoting properties, many of which are attributed to oleuropein aglycone (OleA), the deglycosylated form of oleuropein, which is the main polyphenolic component of EVOO. In this work, three pesticides with different physicochemical and biological properties, namely oxadiazon (OXA), imidacloprid (IMID), and glyphosate (GLYPHO), were compared in terms of metabolic activity, mitochondrial function and epigenetic modulation in an in vitro cellular model of human HaCaT keratinocytes to mimic the pathway of dermal exposure. The potential protective effect of OleA against pesticide-induced cellular toxicity was then evaluated in a cell pre-treatment condition. This study showed that sub-lethal doses of OXA and IMID reduced the metabolic activity and mitochondrial functionality of HaCaT cells by inducing oxidative stress and altering intracellular calcium flux and caused epigenetic modification by reducing histone acetylation H3 and H4. GLYPHO, on the other hand, showed no evidence of cellular toxicity at the doses tested. Pretreatment of cells with OleA was able to protect cells from the damaging effects of the pesticides OXA and IMID by maintaining metabolic activity and mitochondrial function at a controlled level and preventing acetylation reduction, particularly of histone H3. In conclusion, the bioactive properties of OleA reported here could be of great pharmaceutical and health interest, as they could be further studied to design new formulations for the prevention of toxicity from exposure to pesticide use.

Efficient calibration for imperfect epidemic models with applications to the analysis of COVID-19

Abstract The estimation of unknown parameters in simulations, also known as calibration, is crucial for practical management of epidemics and prediction of pandemic risk. A simple yet widely used approach is to estimate the parameters by minimising the sum of the squared distances between actual observations and simulation outputs. It is shown in this paper that this method is inefficient, particularly when the epidemic models are developed based on certain simplifications of reality, also known as imperfect models which are commonly used in practice. To address this issue, a new estimator is introduced that is asymptotically consistent, has a smaller estimation variance than the least-squares estimator, and achieves the semiparametric efficiency. Numerical studies are performed to examine the finite sample performance. The proposed method is applied to the analysis of the COVID-19 pandemic for 20 countries based on the susceptible-exposed-infectious-recovered model with both deterministic and stochastic simulations. The estimation of the parameters, including the basic reproduction number and the average incubation period, reveal the risk of disease outbreaks in each country and provide insights to the design of public health interventions.

Recent Developments in Aquaculture and Future Prospects: A Comprehensive Review

In the pursuit of promoting sustainable aquaculture production, numerous cutting-edge technologies have emerged in recent years. The utilization of effective microbes (EM) in managing water quality, the implementation of biofloc technology, aquamimicry, the inclusion of Black Soldier Fly (BSF) as an additional protein source, the use of triploidy and polyploidy, vaccines, probiotics, and prebiotics, the integration of Internet of Things (IoT) for monitoring water quality in the farm operation, the practice of monosex culture, and the application of neo-female techniques are all being employed in aquaculture operations. The advancements in these cutting-edge technologies have been focused on promoting sustainable aquaculture production, mitigating the risk of disease outbreaks, enhancing crop yields, and contributing to eco-friendly environmental initiatives. This review paper highlights the cutting-edge technologies that have emerged in the field of aquaculture in recent years, up until the present time, with a focus on advancements in fish nutrition. The advancements in aquaculture technology have been instrumental in promoting the achievement of sustainable development goals, particularly SDG-1 (no poverty) and SDG-2 (zero hunger). These goals are aimed at reducing poverty and eliminating hunger by utilizing the enhanced aquaculture production facilitated by the latest technological innovations. In the arena of aquaculture, this review paper has the potential to nourish the minds of aquaculturists and aquafarmers with a bountiful feast of knowledge. It unveils the latest technologies and developments in the realm of aquaculture, serving as a nutritious resource that can enhance the operation of cultures and promote a fruitful increase in production in the not-so-distant future.

Vaccine Hesitancy: Developing Competency in Nursing Students Through Simulation.

Many Americans are undecided about or have barriers to receiving vaccines. Complacency, confidence, convenience, misinformation, and disinformation impact vaccine hesitancy (VH). During the COVID-19 pandemic, rates for flu and routine childhood vaccinations declined globally. As vaccination rates decline, the risk of disease outbreaks increases. Nursing students need to be prepared to address VH in the clinical setting. Four simulation experiences were developed to build confidence and competency in the provision of vaccinations and addressing VH. Nursing students practiced communication skills critical to motivational interviewing, health education, health promotion, and goal setting. There were statistically significant increases in student confidence and perceived competence in vaccine administration and addressing VH through motivational interviewing. High-fidelity simulation combined with a virtual simulation was effective in developing confidence among nursing students. Students demonstrated skill in addressing VH and motivational interviewing.

Core microbiome profiles and their modification by environmental, biological, and rearing factors in aquaculture hatcheries

16S rRNA gene sequencing and bacteria- and genus-specific quantitative PCR was used to profile microbial communities and their associated functions in water, live feed (microalgae, Artemia, and rotifer), and European sea bass and gilthead sea bream larvae from hatcheries in Greece and Italy. The transfer to larvae of genus containing potential pathogens of fish was more likely with Artemia and rotifer than with microalgae or water, irrespective of geographic location. The presence of potentially pathogenic bacteria (Vibrio and Pseudoalteromonas) in the core microbiota of water, live feed, and fish larvae, the enrichment of different bacterial resistance pathways and biofilm formation, and the overall low beneficial bacteria load during larval ontogeny emphasizes the risk for disease outbreaks. The present data characterizing microbiota in commercial aquaculture hatcheries provides a baseline for the design of strategies to manage disease and to model or remediate potential adverse environmental impacts.