Emergence Of Diseases Research Articles

Powdery mildew caused by Erysiphe corylacearum: An emerging problem on hazelnut in Italy.

Erysiphe corylacearum has recently been reported in northern Italy (Piedmont) and other European countries as the causal agent of a new emerging powdery mildew on hazelnut. This disease is much more dangerous than the common hazelnut powdery mildew caused by Phyllactinia guttata as it significantly reduces yield and quality of hazelnuts. This study aimed to perform morphological and molecular characterization of the fungal isolates from powdery mildew-infected plants in the Piedmont Italian region. Additionally, genetic diversity studies and pathogenicity tests were conducted. Thirty-six fungal isolates originating from symptomatic hazelnut plants exhibiting specific powdery mildew symptoms on the superior leaf side were identified morphologically as E. corylacearum. Single- and multilocus sequence typing of five loci (ITS, rpb2, CaM, GAPDH and GS) assigned all isolates as E. corylacearum. Multilocus and GAPDH phylogenetic studies resulted in the most efficient characterization of E. corylacearum. Studied fungal isolates were able to cause new emerging powdery mildew disease by fulfilling Koch's postulates. The emergence of powdery mildew disease in Italy revealed the E. corylacearum subgrouping, population expansion, and high nucleotide similarity with other recently identified E. corylacearum hazelnut isolates. To contain this harmful disease and inhibit the fungus spread into new geographical zones, it will be necessary to implement more rigorous monitoring in neighboring hazelnut plantations near infected hazelnuts, use sustainable fungicides and search for new biocontrol agents.

Human movement and environmental barriers shape the emergence of dengue

Understanding how emerging infectious diseases spread within and between countries is essential to contain future pandemics. Spread to new areas requires connectivity between one or more sources and a suitable local environment, but how these two factors interact at different stages of disease emergence remains largely unknown. Further, no analytical framework exists to examine their roles. Here we develop a dynamic modelling approach for infectious diseases that explicitly models both connectivity via human movement and environmental suitability interactions. We apply it to better understand recently observed (1995-2019) patterns as well as predict past unobserved (1983-2000) and future (2020-2039) spread of dengue in Mexico and Brazil. We find that these models can accurately reconstruct long-term spread pathways, determine historical origins, and identify specific routes of invasion. We find early dengue invasion is more heavily influenced by environmental factors, resulting in patchy non-contiguous spread, while short and long-distance connectivity becomes more important in later stages. Our results have immediate practical applications for forecasting and containing the spread of dengue and emergence of new serotypes. Given current and future trends in human mobility, climate, and zoonotic spillover, understanding the interplay between connectivity and environmental suitability will be increasingly necessary to contain emerging and re-emerging pathogens.

Development of a novel Colorimetric Assay for the rapid diagnosis of Coronavirus disease 2019 from nasopharyngeal samples.

Emergence of Coronavirus disease 2019 (COVID-19) pandemic has posed a huge threat to public health. Rapid and reliable test to diagnose infected subjects is crucial for disease spread control. We developed a colorimetric test for COVID-19 detection using a Colorimetric Assay based on thiol-linked RNA modified gold nanoparticles (AuNPs) and oligonucleotide probes. This method was conducted on RNA from 200 pharyngeal swab samples initially tested by Real-Time polymerase chain reaction (RT-PCR) as gold standard. A specific oligonucleotide probe designed based on ORF1ab of COVID-19 was functionalized with AuNPs-probe conjugate. The exposure of AuNP-probe to isolated RNA samples was tested using hybridization. In this comparative study, the colorimetric functionalized AuNPs assay exhibited a detection limit of 25copies/µL. It was higher in comparison to the RT-PCR method, which could only detect 15copies/µL. The results demonstrated 100% specificity and 96% sensitivity for the developed method. Herein, we developed an incredibly rapid, simple and cost-effective Colorimetric Assay lasting approximately 30min which could process considerably higher number of COVID-19 samples compared to the RT-PCR. This AuNP-probe conjugate colorimetric method could be considered the optimum alternatives for conventional diagnostic tools especially in over-populated and/or low-income countries.

The Role of Urban Disaster Risk Management in Major Catastrophic Events: A Case Study of Resilience in Chinese Cities During the COVID-19 Pandemic

The emergence of infectious diseases has historically influenced urban development, necessitating the evolution of urban planning toward greater disaster resilience. The COVID-19 pandemic, in particular, has revealed weaknesses in modern urban planning and governance, emphasizing the need for enhanced urban resilience and disaster risk management. For China, as urban populations continue to grow, urban resilience and disaster risk management have become focal points for urban planners and policymakers, ensuring that cities can rapidly adapt and effectively respond to various challenges. This study summarizes a series of emergency measures adopted by the Chinese government during the COVID-19 pandemic and analyzes their effectiveness. China's response, characterized by early intervention, social distancing, extensive testing, and advanced tracking technologies, effectively curtailed the virus's spread, especially in Hubei province and its capital, Wuhan. Despite these successes, the paper identifies areas where China's urban resilience could be improved, including coordination of emergency plans, information dissemination, and social cohesion, among other aspects, to better confront future challenges.

Forecasting the level of biological risks of the emergence and spread of infectious and parasitic potato diseases

The article discusses the issues of determining the level of occurrence biological risks, as well as the spread of infectious and parasitic diseases of potato according to the parameters of the transmission mechanisms and routes. Most pathogens are characterized by a high (26.1%) and very high (43.5%) level of risk. It has been established that in the latter group, 75% of infectious and parasitic diseases of potato have a mycotic etiology, 15 – helminthic, 10% – bacterial. There are no pathogens of infectious and parasitic potato diseases of viral etiology in this group. The average score for the very high-risk group is 10.8. In the low-risk group the most of potato diseases pathogens have a bacterial etiology (80%), medium – bacterial (44.5%) and mycotic (33.3%), high – viral (66.6%).

Diversity, evolution, and emergence of fish viruses.

The production of aquatic animals has more than doubled over the last 50 years and is anticipated to continually increase. While fish are recognized as a valuable and sustainable source of nutrition, particularly in the context of human population growth and climate change, the rapid expansion of aquaculture coincides with the emergence of highly pathogenic viruses that often spread globally through aquacultural practices. Here, we provide an overview of the fish virome and its relevance for disease emergence, with a focus on the insights gained through metagenomic sequencing, noting potential areas for future study. In particular, we describe the diversity and evolution of fish viruses, for which the majority have no known disease associations, and demonstrate how viruses emerge in fish populations, most notably at an expanding domestic-wild interface. We also show how wild fish are a powerful and tractable model system to study virus ecology and evolution more broadly and can be used to identify the major factors that shape vertebrate viromes. Central to this is a process of virus-host co-divergence that proceeds over many millions of years, combined with ongoing cross-species virus transmission.

Markov modeling on dynamic state space for genetic disorders and infectious diseases with mutations: Probabilistic framework, parameter estimation, and applications

Abstract The emergence and dynamic prevalence of genetic disorders and infectious diseases with mutations pose significant challenges for public health interventions. This study investigated the parameter estimation approach and the application of the dynamic state-space Markov modeling of these conditions. Using extensive simulations, the model demonstrated robust parameter estimation performance, with biases and mean-squared errors decreasing as sample size increased. Applying the model to COVID-19 data revealed distinct temporal patterns for each variant, highlighting their unique emergence, peak dominance, and decline or persistence trajectories. Despite the absence of clear trends in the data, the model exhibited a remarkable accuracy in predicting future prevalence trends for most variants, showcasing its potential for real-time monitoring and analysis. While some discrepancies were observed for specific variants, these findings suggest the model’s promise as a valuable tool for informing public health strategies. Further validation with larger datasets and exploration of incorporating additional factors hold the potential for enhancing the model’s generalizability and applicability to other evolving diseases.

Aguhyper: a hyperledger-based electronic health record management framework

The increasing importance of healthcare records, particularly given the emergence of new diseases, emphasizes the need for secure electronic storage and dissemination. With these records dispersed across diverse healthcare entities, their physical maintenance proves to be excessively time-consuming. The prevalent management of electronic healthcare records (EHRs) presents inherent security vulnerabilities, including susceptibility to attacks and potential breaches orchestrated by malicious actors. To tackle these challenges, this article introduces AguHyper, a secure storage and sharing solution for EHRs built on a permissioned blockchain framework. AguHyper utilizes Hyperledger Fabric and the InterPlanetary Distributed File System (IPFS). Hyperledger Fabric establishes the blockchain network, while IPFS manages the off-chain storage of encrypted data, with hash values securely stored within the blockchain. Focusing on security, privacy, scalability, and data integrity, AguHyper’s decentralized architecture eliminates single points of failure and ensures transparency for all network participants. The study develops a prototype to address gaps identified in prior research, providing insights into blockchain technology applications in healthcare. Detailed analyses of system architecture, AguHyper’s implementation configurations, and performance assessments with diverse datasets are provided. The experimental setup incorporates CouchDB and the Raft consensus mechanism, enabling a thorough comparison of system performance against existing studies in terms of throughput and latency. This contributes significantly to a comprehensive evaluation of the proposed solution and offers a unique perspective on existing literature in the field.

From the COVID-19 lockdown to the new normal: Two-year changes in daily stress and positive event processes.

The emergence of the novel COVID-19 disease and the social distancing measures implemented to curb its spread affected most aspects of daily life. Past work suggests that during times of more severe stress, people respond to daily stressors with relatively higher negative affect. However, little is known about how people responded to daily stressors and positive events at different moments in time during the COVID-19 pandemic. Thus, we examined longitudinal changes in daily event-related affect (covariation of daily stressors or positive events with same-day affect) from Spring 2020 (wave 1) to 2022 (wave 2). The sample consisted of 324 adults aged 18-80 (mean=52years; 89% women) from the US and Canada who completed weeklong daily diaries at both waves. The results revealed improvements in affective well-being, stressor-related affect (i.e., smaller fluctuations in affect on stressor days vs. nonstressor days), and positive event-related affect (i.e., lower negative affect on days with vs. without positive events). Furthermore, as people gradually resumed their social activities from 2020 to 2022, people reported being exposed to an increased frequency of both stressors and positive events. This study highlights the potential influence of socio-historical phenomena, such as an ongoing pandemic, on the events that people encounter and how they emotionally respond to them.

How Attitudes Toward Online Learning Changes During Pandemic, and Reasons Behind It

This paper aim to understand peoples attitude toward online learning and find the reason behind it. The emergence of new coronavirus disease has revolutionized every aspect of people's lives. During the pandemic, all those who try to receive education, students, have to study online. Online learning has become a famous topic during a pandemic. People receive online education and this research is trying to find what are peoples attitude towards this new form of education and does this attitude change during pandemic. At same time, social media are heavily used as a platform for people to express their emotions. In this research, data from posts of Twitter users under the topic of online learning are analyzed using sentiment analysis and MDCOR. The results of sentiment analysis tell us the attitudes change during the pandemic and MDCOR shows potential reason behind it.

Wildfire Ashes from the Wildland-Urban Interface Alter Vibrio vulnificus Growth and Gene Expression.

Climate change-induced stressors are contributing to the emergence of infectious diseases, including those caused by marine bacterial pathogens such as Vibrio spp. These stressors alter Vibrio temporal and geographical distribution, resulting in increased spread, exposure, and infection rates, thus facilitating greater Vibrio-human interactions. Concurrently, wildfires are increasing in size, severity, frequency, and spread in the built environment due to climate change, resulting in the emission of contaminants of emerging concern. This study aimed to understand the potential effects of urban interface wildfire ashes on Vibrio vulnificus (V. vulnificus) growth and gene expression using transcriptomic approaches. V. vulnificus was exposed to structural and vegetation ashes and analyzed to identify differentially expressed genes using the HTSeq-DESeq2 strategy. Exposure to wildfire ash altered V. vulnificus growth and gene expression, depending on the trace metal composition of the ash. The high Fe content of the vegetation ash enhanced bacterial growth, while the high Cu, As, and Cr content of the structural ash suppressed growth. Additionally, the overall pattern of upregulated genes and pathways suggests increased virulence potential due to the selection of metal- and antibiotic-resistant strains. Therefore, mixed fire ashes transported and deposited into coastal zones may lead to the selection of environmental reservoirs of Vibrio strains with enhanced antibiotic resistance profiles, increasing public health risk.

Investigation of SARS-CoV-2 infection in domesticated animals from COVID-19 affected households in Bangladesh

The emergence and rapid global spread of the novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has sparked significant interest in understanding its zoonotic origins. This study aims to investigate animal and environmental samples in Bangladesh to identify the zoonotic source and reverse zoonosis of SARS-CoV-2. This research adopted a comprehensive approach to gather and analyze samples from various animal species, including cattle, sheep, goats, cats, and dogs that are peridomestic in nature or remain in close contact, ensuring biosafety and avoiding cross-contamination. SARS-CoV-2 or related coronaviruses were identified using immunological detection and real-time reverse transcription-polymerase chain reaction (RT-qPCR). A total of 1028 samples from different regions of Bangladesh were collected from cattle (552), sheep (135), goats (112), cats (118), and dogs (111), of which 465 were rectal, 363 nasal swabs, and 200 blood samples. The samples were collected from those areas where there were human records of COVID-19 during July 2021- December 2022. The blood samples were collected and immediately used for antibody screening. No positive samples were found in both antibody test screens and RT-qPCR in fecal and nasal swab samples. The study indicated no COVID-19 infection was found in domestic animals and pets despite staying in close contact with COVID-19 patients or households, suggesting a limited risk of transmission from these animals to humans within the studied context. It's possible that domestic animals are not significantly involved in the COVID-19 epidemic in natural environment exposure conditions.

Impact of pandemic mobility restrictions on kidney transplant patients' experience: lessons on quality of care.

Patient perspectives on their post-operative health are acknowledged as valuable healthcare outcomes and should be scrupulously considered when designing interventions for patient-centered healthcare. Yet, following the COVID-19 lockdown and in the absence of standardized guidelines on how to best provide virtual chronic care to kidney transplant recipients, little is known about how this unique population coped and managed to comply with public health indications during confinement. This study addresses this shortcoming by examining the experiences of patients from a tertiary hospital in Spain during the initial weeks of the lockdown decreed by the national government. Specifically, we focus our attention on the perceptions and experiences of these patients by retrieving robust qualitative and quantitative data: the former based on a thematic analysis of focus group transcripts, the latter obtained from a large-scale survey. Our findings identify opportunities for improvement in the quality of care and point to the provisions that might be made when facing future pandemics or lockdown-requiring situations. As healthcare services navigate evolving landscapes, our findings on the experience of kidney transplant recipients should enable hospital services to improve the quality of care they are able to provide to such patients during periods of restricted mobility, especially those associated with future disease emergencies, and considering that home confinement is often part of the natural course of post-operative care of these patients.

Emergence of Cardiovascular Diseases and Inclusive Organization of Care in the Health District of Biyem-Assi, Yaounde Cameroon

Healthcare financing is one of the major challenges that faces the emergence of non-communicable diseases. This study describes and analyzes the inclusive organization of cardiovascular disease care in Biyem-Assi Health District. From December 2022 to February 2023, we conducted a qualitative study in the Biyem-Assi Health District. Medical anthropology research techniques were used to collect data through interview guides. The sample consisted of patients admitted and followed during the study period. The epidemiological variables studied included age, sex, diagnosis, length of hospital stay, lifestyle, socioeconomic status, knowledge, and modalities of cardiovascular disease (CVD) management, as well as practices aimed at eradicating this scourge. Cardiovascular disease mortality is currently the highest. It affects a young population, so diagnosis is often made late. Very few international technical and financial partners have a real strategy to support prevention and management programs for non-communicable diseases, especially cardiovascular diseases. Faced with the growing incidence of cardiovascular diseases in sub-Saharan Africa, mainly in Cameroon, it is urgent to develop a response or rethink a new organization of cardiovascular disease care, involving and mobilizing numerous technical and financial partners, public authorities, and directly concerned healthcare professionals.

Micromobility systems and disease transmission: a spatially explicit agent-based approach

We propose a novel micro-level and spatially explicit agent-based modeling framework dubbed TranEpiSim to model the spread of infectious diseases through micromobility systems and a baseline population in an urban area. A case study is conducted on the Chicago City public bikesharing system to demonstrate the ability of the model to isolate the role of transportation as a vector and assess the efficacy of the model. Results show that the emergence of viral disease through micromobility transportation is possible, but the overall impact of the system on the disease dynamics in a worst-case scenario, especially with the current size of the system, is rather small. The proposed model offers a comprehensive approach to estimate the impact of micromobility (and more generally, specific transportation modes) on disease spread by considering infections that occur both at destinations and in/on transportation vehicles and infrastructure. The spatial pattern for the risk of exposure shows a higher risk in the central business district and north of it, where most of the shared bike transportation occurs. Because of its intrinsic features, the proposed framework is uniquely placed to assess the efficacy of interventions and make trade-offs between competing scenarios when dealing with epidemics.

Global stability analysis and modelling onchocerciasis transmission dynamics with control measures

ABSTRACT Background: Onchocerciasis infection is one of the neglected tropical diseases targeted for eradication by 2030. The disease is usually transmitted to humans through the bites of black flies. These black flies mostly breed near well-oxygenated fast-running water bodies. The disease is common in mostly remote agricultural villages near rivers and streams. Objective: In this study, a deterministic model describing the infection dynamics of human onchocerciasis disease with control measures is presented. Methods: We derived the model’s reproductive number and used a stability theorem of a Metzler matrix to show that disease-free equilibrium is both locally and globally asymptotically stable whenever the reproductive number is less than one. Parameter contribution was conducted using sensitivity analysis. The model endemic equation is shown to be a cubic polynomial in the presence of infected immigrants and a quadratic form in their absence. Results: When the inflow of infected immigrants is null, the model endemic equation may admit a unique equilibrium if the reproductive number is greater than one, or admits multiple endemic equilibria if the reproductive number is less than unity. We carried out a sensitivity analysis to identify the significant parameters that contribute to onchocerciasis spread. Conclusion: Onchocerciasis disease can be eradicated if the importation of infected immigrants is properly monitored. The integration of the One Health concept in the public health system is key in tackling the emergence and spread of diseases.

Modeling the transmission dynamics of COVID-19 with genetically resistant humans

The emergence of a coronavirus disease (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus (SARS-COV 2) has caused an unprecedented global societal and public health crisis. A mathematical model that incorporates an individual’s ability to resist COVID-19 infection is considered to study the dynamics of COVID-19. Detection and testing for COVID-19 in individuals who has ability to resist the infection, proper preventive measures, and timely medical care are essential in managing and controlling COVID-19 outbreak. These allows us to make quantifiable predictions about the effects of testing utilization on the COVID-19 prevalence. First, we analyze the disease-free state of the COVID-19 model, calculate the baseline control reproduction number, and obtain the local stability of disease-free equilibrium. The model is calibrated using data obtained from Nigeria Centre for Disease Control and key parameters of the model are estimated. Sensitivity analysis is carried out to investigate the influence of the parameters in curtailing the disease. Numerical simulations are then used to explore the behavior of the model solutions involving the novel variable (genetically resistant humans) and control measures. Our results suggest that strict intervention effort (early detection of genetically resistant individuals, testing and isolation of the infected individuals) is required for quick suppression of the disease.

Phytophthora and Phytopythium species associated with walnut dieback in plantations of northern Patagonia, Argentina

AbstractThe walnut industry in Argentina has grown in recent years, especially in northern Patagonia. However, this expansion has also brought new challenges, including the emergence of diseases threatening the health and productivity of walnut plantations. One of the most important diseases affecting walnut crops worldwide is ‘ink disease’ or ‘walnut dieback'. The aim of this study was to characterize ink disease, identify the aetiological agents, and estimate its incidence in walnut orchards of northern Patagonia, Argentina. Symptomatic trees were observed in the seven surveyed walnut orchards, showing a range of symptoms, including chlorosis and wilting, stem cankers and desiccation. In vivo assay and molecular analyses revealed that not only Phytophthora (P.) but also Phytopythium (Ph.) species are the causal agents of the disease, with P. drechsleri, Ph. mercuriale and Ph. vexans being the most virulent over the commonly used rootstock Juglans hindsii. Notably, Ph. vexans was the most frequently isolated pathogen, suggesting its prevalence and potential impact on the regional walnut industry. Overall, this study provides critical insights into the prevalence and impact of Phytophthora and Phytopythium species on walnut health in northern Patagonia. The presence of multiple pathogenic oomycete species raises concerns about the health of walnut orchards, as well as the potential risk of pathogen transmission to other fruit crops in the region. The findings will help growers to develop better cultural practices and implement measures to guarantee the sustainability of the walnut industry in Patagonia.

306 Awardee Talk: Characterization and surveillance testing of problematic pathogens within the livestock industry using metagenomic and long read sequencing

Abstract With increased intensification of livestock production, the rate of disease susceptibility and emergence of pathogens has increased. Currently in the beef cattle industry, infectious bovine keratoconjunctivitis (IBK), is a problematic disease that is not well understood where vaccines have shown to have low efficacy. This is partly due to the lack of understanding of the ocular microbiome, where IBK disease progression may be a result of a polymicrobial disease due to certain bacterial and/or viral taxa predisposing the animal to infection. To understand the microbial ecology of IBK we used metagenomic shotgun sequencing to characterize the bovine ocular microbiome and virome. Infected and healthy beef calves were sampled before, during, and after IBK infection and shotgun metagenomic sequencing was performed to identify microbial changes during IBK infection. Preliminary data showed that we were able to identify 230 contigs consisting of bacteriophages such as Escherichia virus, Bacillus virus, Corynebacterium virus, and Mycoplasma virus. Out of the 230 bacteriophages, 213 of them are lytic phages. Additionally, preliminary data showed bacteria contigs such as Moraxella bovoculi, and Mycoplasma bovoculi Like IBK, the rate of disease emergence has increased in the last decade. As such, rapid in-field surveillance tools are greatly needed to monitor the emergence of known and unknown pathogens for early intervention. Current tools such as RT-PCR and enzyme linked immunosorbent assay (ELISA) require previous genomic knowledge to detect pathogens and are limited to the pathogen of interest. We have developed a long-read sequencing-based surveillance tool that eliminates the need of prior knowledge to detect both bacterial and viral pathogens simultaneously. The approach we developed can rapidly and accurately identify pathogens within clinical samples in as short as 12 h from sample collection to results. Here we present sequence-based microbiome studies and tools to help understand disease etiology and develop novel surveillance tools to improve food security within the livestock industry.

Investigation of severe acute respiratory syndrome coronavirus 2 infection status in solid organ transplant recipients treated with tixagevimab/cilgavimab

IntroductionTixagevimab and cilgavimab (T/C) are neutralizing antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can be used to prevent SARS-CoV-2 infection in solid organ transplant (SOT) recipients. However, their neutralizing activity against recent variants was reduced, raising concerns regarding the emergence of breakthrough coronavirus diseases 2019 (COVID-19). This study aimed to investigate the status of the COVID-19 breakthrough after T/C administration. MethodsWe retrospectively investigated breakthrough COVID-19 in SOT recipients administered T/C at Kyoto University Hospital, Japan, from November 2022 to March 2023. Patients were monitored for 6 months after T/C administration. SARS-CoV-2 infection was diagnosed using polymerase chain reaction or antigen tests. The monthly incidence rates of SARS-CoV-2 infection were calculated using the person–time method. ResultsT/C were administered to 67 SOT recipients (liver, 16; lung, 36; and kidney, 15), of whom five were infected with SARS-CoV-2. All five cases were classified as mild, and none of these patients required admission to the intensive care unit (ICU) or died. All infected individuals tested positive for SARS-CoV-2 after March 2023, when T/C-resistant subvariant strains became predominant. The monthly incidence rate of SARS-CoV-2 infection, calculated using the person–time method, suggested an increasing trend. ConclusionsDuring the T/C-resistant variant epidemic, SARS-CoV-2 infections were identified even after T/C administration, suggesting that the prophylactic effects of T/C were invalid. Therefore, emerging variants must be carefully monitored and characterized to determine appropriate antiviral strategies, such as the use of suitable neutralizing antibodies.