•4 million tweets were used to identify vaccine sentiments opinions.•Positive sentiment about the COVID-19 vaccine was the dominant polarity on Twitter.•Vaccine objection and hesitancy were more than ...vaccine interest.•Content producer against vaccination were partly Twitter bots or political activists.•Well-known individuals and organizations wrote in favour of vaccination.
We identified public sentiments and opinions toward the COVID-19 vaccines based on the content of Twitter.
We retrieved 4,552,652 publicly available tweets posted within the timeline of January 2020 to January 2021. Following extraction, we identified vaccine sentiments and opinions of tweets and compared their progression by time, geographical distribution, main themes, keywords, posts engagement metrics and accounts characteristics.
We found a slight difference in the prevalence of positive and negative sentiments, with positive being the dominant polarity and having higher engagements. The amount of discussion on vaccine rejection and hesitancy was more than interest in vaccines during the course of the study, but the pattern was different in various countries. We found the accounts producing vaccine opposition content were partly Twitter bots or political activists while well-known individuals and organizations generated the content in favour of vaccination.
Understanding sentiments and opinions toward vaccination using Twitter may help public health agencies to increase positive messaging and eliminate opposing messages in order to enhance vaccine uptake.
Social media services such as Twitter are valuable sources of information for surveillance systems. A digital syndromic surveillance system has several advantages including its ability to overcome ...the problem of time delay in traditional surveillance systems. Despite the progress made with using digital syndromic surveillance systems, the possibility of tracking avian influenza (AI) using online sources has not been fully explored. In this study, a Twitter-based data analysis framework was developed to automatically monitor avian influenza outbreaks in a real-time manner. The framework was implemented to find worrisome posts and alerting news on Twitter, filter irrelevant ones, and detect the onset of outbreaks in several countries. The system collected and analyzed over 209,000 posts discussing avian influenza on Twitter from July 2017 to November 2018. We examined the potential of Twitter data to represent the date, severity and virus type of official reports. Furthermore, we investigated whether filtering irrelevant tweets can positively impact the performance of the system. The proposed approach was empirically evaluated using a real-world outbreak-reporting source. We found that 75% of real-world outbreak notifications of AI were identifiable from Twitter. This shows the capability of the system to serve as a complementary approach to official AI reporting methods. Moreover, we observed that one-third of outbreak notifications were reported on Twitter earlier than official reports. This feature could augment traditional surveillance systems and provide a possibility of early detection of outbreaks. This study could potentially provide a first stepping stone for building digital disease outbreak warning systems to assist epidemiologists and animal health professionals in making relevant decisions.
Influenza viruses cause severe respiratory infections in humans and birds, triggering global health concerns and economic burden. Influenza infection is a dynamic process involving complex biological ...host responses. The objective of this study was to illustrate global biological processes in ileum and cecal tonsils at early time points after chickens were infected with low pathogenic avian influenza virus (LPAIV) H9N2 through transcriptome analysis. Total RNA isolated from ileum and cecal tonsils of non-infected and infected layers at 12-, 24- and 72-h post-infection (hpi) was used for mRNA sequencing analyses to characterize differentially expressed genes and overrepresented pathways. Statistical analysis highlighted transcriptomic signatures significantly occurring 24 and 72 hpi, but not earlier at 12 hpi. Interferon (IFN)-inducible and IFN-stimulated gene (ISG) expression was increased, followed by continued expression of various heat-shock proteins (HSP), including HSP60, HSP70, HSP90 and HSP110. Some upregulated genes involved in innate antiviral responses included DDX60, MX1, RSAD2 and CMPK2. The ISG15 antiviral mechanism pathway was highly enriched in ileum and cecal tonsils at 24 hpi. Overall, most affected pathways were related to interferon production and the heat-shock response. Research on these candidate genes and pathways is warranted to decipher underlying mechanisms of immunity against LPAIV in chickens.
An accurate understanding of the ecology and complexity of the poultry respiratory microbiota is of utmost importance for elucidating the roles of commensal or pathogenic microorganisms in the ...respiratory tract, as well as their associations with health or disease outcomes in poultry. This comprehensive review delves into the intricate aspects of the poultry respiratory microbiota, focusing on its colonization patterns, composition, and impact on poultry health. Firstly, an updated overview of the current knowledge concerning the composition of the microbiota in the respiratory tract of poultry is provided, as well as the factors that influence the dynamics of community structure and diversity. Additionally, the significant role that the poultry respiratory microbiota plays in economically relevant respiratory pathobiologies that affect poultry is explored. In addition, the challenges encountered when studying the poultry respiratory microbiota are addressed, including the dynamic nature of microbial communities, site-specific variations, the need for standardized protocols, the appropriate sequencing technologies, and the limitations associated with sampling methodology. Furthermore, emerging evidence that suggests bidirectional communication between the gut and respiratory microbiota in poultry is described, where disturbances in one microbiota can impact the other. Understanding this intricate cross talk holds the potential to provide valuable insights for enhancing poultry health and disease control. It becomes evident that gaining a comprehensive understanding of the multifaceted roles of the poultry respiratory microbiota, as presented in this review, is crucial for optimizing poultry health management and improving overall outcomes in poultry production.
Mucosal vaccine delivery systems have paramount importance for the induction of mucosal antibody responses. Two studies were conducted to evaluate immunogenicity of inactivated AIV antigens ...encapsulated in poly(D,L-lactide-co-glycolide) (PLGA) nanoparticles (NPs). In the first study, seven groups of specific pathogen free (SPF) layer-type chickens were immunized subcutaneously at 7-days of age with different vaccine formulations followed by booster vaccinations two weeks later. Immune responses were profiled by measuring antibody (Ab) responses in sera and lachrymal secretions of vaccinated chickens. The results indicated that inactivated AIV and CpG ODN co-encapsulated in PLGA NPs (2x NanoAI+CpG) produced higher amounts of hemagglutination inhibiting antibodies compared to a group vaccinated with non-adjuvanted AIV encapsulated in PLGA NPs (NanoAI). The tested adjuvanted NPs-based vaccine (2x NanoAI+CpG) resulted in higher IgG responses in the sera and lachrymal secretions at weeks 3, 4 and 5 post-vaccination when immunized subcutaneously. The incorporation of CpG ODN led to an increase in Ab-mediated responses and was found useful to be included both in the prime and booster vaccinations. In the second study, the ability of chitosan and mannan coated PLGA NPs that encapsulated AIV and CpG ODN was evaluated for inducing antibody responses when delivered via nasal and ocular routes in one-week-old SPF layer-type chickens. These PLGA NPs-based and surface modified formulations induced robust AIV-specific antibody responses in sera and lachrymal secretions. Chitosan coated PLGA NPs resulted in the production of large quantities of lachrymal IgA and IgG compared to mannan coated NPs, which also induced detectable amounts of IgA in addition to the induction of IgG in lachrymal secretions. In both mucosal and subcutaneous vaccination approaches, although NPs delivery enhanced Ab-mediated immunity, one booster vaccination was required to generate significant amount of Abs. These results highlight the potential of NPs-based AIV antigens for promoting the induction of both systemic and mucosal immune responses against respiratory pathogens.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Sustainably feeding the next generation is often described as one of the most pressing "grand challenges" facing the 21st century. Generally, scholars propose addressing this problem by increasing ...agricultural production, investing in technology to boost yields, changing diets, or reducing food waste. In this paper, we explore whether global food production is nutritionally balanced by comparing the diet that nutritionists recommend versus global agricultural production statistics. Results show that the global agricultural system currently overproduces grains, fats, and sugars while production of fruits and vegetables and protein is not sufficient to meet the nutritional needs of the current population. Correcting this imbalance could reduce the amount of arable land used by agriculture by 51 million ha globally but would increase total land used for agriculture by 407 million ha and increase greenhouse gas emissions. For a growing population, our calculations suggest that the only way to eat a nutritionally balanced diet, save land and reduce greenhouse gas emissions is to consume and produce more fruits and vegetables as well as transition to diets higher in plant-based protein. Such a move will help protect habitats and help meet the Sustainable Development Goals.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The ongoing COVID-19 pandemic has posed a severe threat to public health worldwide. In this study, we aimed to evaluate several digital data streams as early warning signals of COVID-19 outbreaks in ...Canada, the US and their provinces and states. Two types of terms including symptoms and preventive measures were used to filter Twitter and Google Trends data. We visualized and correlated the trends for each source of data against confirmed cases for all provinces and states. Subsequently, we attempted to find anomalies in indicator time-series to understand the lag between the warning signals and real-word outbreak waves. For Canada, we were able to detect a maximum of 83% of initial waves 1 week earlier using Google searches on symptoms. We divided states in the US into two categories: category I if they experienced an initial wave and category II if the states have not experienced the initial wave of the outbreak. For the first category, we found that tweets related to symptoms showed the best prediction performance by predicting 100% of first waves about 2-6 days earlier than other data streams. We were able to only detect up to 6% of second waves in category I. On the other hand, 78% of second waves in states of category II were predictable 1-2 weeks in advance. In addition, we discovered that the most important symptoms in providing early warnings are fever and cough in the US. As the COVID-19 pandemic continues to spread around the world, the work presented here is an initial effort for future COVID-19 outbreaks.
Avian influenza viruses can cause economically devastating diseases in poultry and have the potential for zoonotic transmission. To mitigate the consequences of avian influenza, disease prediction ...systems have become increasingly important. In this study, we have proposed a framework for the prediction of the occurrence and spread of avian influenza events in a geographical area. The application of the proposed framework was examined in an Indonesian case study. An extensive list of historical data sources containing disease predictors and target variables was used to build spatiotemporal and transactional datasets. To combine disparate sources, data rows were scaled to a temporal scale of 1-week and a spatial scale of 1-degree × 1-degree cells. Given the constructed datasets, underlying patterns in the form of rules explaining the risk of occurrence and spread of avian influenza were discovered. The created rules were combined and ordered based on their importance and then stored in a knowledge base. The results suggested that the proposed framework could act as a tool to gain a broad understanding of the drivers of avian influenza epidemics and may facilitate the prediction of future disease events.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The present study was undertaken to profile and compare the cecal microbial communities in conventionally (CONV) grown and raised without antibiotics (RWA) broiler chickens. Three hundred chickens ...were collected from five CONV and five RWA chicken farms on days 10, 24, and 35 of age. Microbial genomic DNA was extracted from cecal contents, and the V4-V5 hypervariable regions of the 16S rRNA gene were amplified and sequenced. Analysis of 16S rRNA sequence data indicated significant differences in the cecal microbial diversity and composition between CONV and RWA chickens on days 10, 24, and 35 days of age. On days 10 and 24, CONV chickens had higher richness and diversity of the cecal microbiome relative to RWA chickens. However, on day 35, this pattern reversed such that RWA chickens had higher richness and diversity of the cecal microbiome than the CONV groups. On days 10 and 24, the microbiomes of both CONV and RWA chickens were dominated by members of the phylum Firmicutes. On day 35, while Firmicutes remained dominant in the RWA chickens, the microbiome of CONV chickens exhibited am abundance of Bacteroidetes. The cecal microbiome of CONV chickens was enriched with the genus Faecalibacterium, Pseudoflavonifractor, unclassified Clostridium_IV, Bacteroides, Alistipes, and Butyricimonas, whereas the cecal microbiome of RWA chickens was enriched with genus Anaerofilum, Butyricicoccu, Clostridium_XlVb and unclassified Lachnospiraceae. Overall, the cecal microbiome richness, diversity, and composition were greatly influenced by the management program applied in these farms. These findings provide a foundation for further research on tailoring feed formulation or developing a consortium to modify the gut microbiome composition of RWA chickens.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
For years, avian influenza has influenced economies and human health around the world. The emergence and spread of avian influenza virus have been uncertain and sudden. The virus is likely to spread ...through several pathways such as poultry transportation and wild bird migration. The complicated and global spread of avian influenza calls for surveillance tools for timely and reliable prediction of disease events. These tools can increase situational awareness and lead to faster reaction to events. Here, we aimed to design and evaluate a decision support framework that aids decision makers by answering their questions regarding the future risk of events at various geographical scales. Risk patterns were driven from pre-built components and combined in a knowledge base. Subsequently, questions were answered by direct queries on the knowledge base or through a built-in algorithm. The evaluation of the system in detecting events resulted in average sensitivity and specificity of 69.70% and 85.50%, respectively. The presented framework here can support health care authorities by providing them with an opportunity for early control of emergency situations.
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