Search Results (332)

In this article, mathematical modeling and stability analysis of Lyme disease and its transmission dynamics using Caputo fractional-order derivatives is presented. The compartmental model has been formulated to analyze the spread of Borrelia burgdorferi virus through tick vectors and mammalian hosts. The feasible region is established, and the boundedness of the model is verified. Analytically, the disease-free equilibrium and the basic reproduction number $\left({\Re }_0\right)$ has been determined to assess outbreak potential. By virtue of the fixed-point theory, the existence and uniqueness of solutions has been established. The numerical simulations are obtained via the Runge–Kutta 4 method, demonstrating the model’s ability to capture realistic disease progression. Finally, sensitivity analysis and control strategies (tick population reduction, host vaccination, public awareness, and early treatment) are evaluated, revealing that integrated control measures significantly reduce infection rates and enhance recovery. Full article

White Spot Syndrome Virus (WSSV) is one of the most devastating viral pathogens affecting shrimp, causing severe economic losses to the global farmed shrimp trade. The globalization of live shrimp trade and waterborne transmission have facilitated the rapid spread of WSSV across major shrimp-producing countries since its initial emergence. The present review gives an updated account of WSSV biology, pathology, transmission dynamics, and recent developments in control measures. The virus, a double-stranded DNA virus of the Nimaviridae family, utilizes advanced immune evasion strategies, resulting in severe mortality. Shrimp lack adaptive immunity and hence rely predominantly on innate immunity, which is insufficient to mount an effective response against severe infections. Traditional disease control measures such as augmented biosecurity, selective breeding, and immunostimulants have, despite extensive research, achieved only limited success. New biotechnological tools such as RNA interference, CRISPR-Cas gene editing, and nanotechnology offer tremendous potential for disease mitigation. In parallel, the development of DNA and RNA vaccines targeting WSSV structural proteins, such as VP28, holds significant promise for stimulating the shrimp immune system. This review highlights the urgent need for a convergent approach to sustainable disease management in global shrimp aquaculture, with interdisciplinarity playing a pivotal role in shaping the future of WSSV control. Full article

Sphenophorus levis, commonly known as the sugarcane weevil, is one of the most important pests affecting Brazilian sugarcane crops. It has spread to all sugarcane-producing regions of Brazil, mainly through contaminated stalks. Effective control of this pest is difficult due to the protection conferred by the host plant during the larval stage. As a result, despite current control measures, S. levis populations continue to grow, and reports of new infestations remain frequent. Biotechnological control measures, such as the use of viruses, stands as a promising tool for pest control in agriculture. The aim of this study was to explore the RNA virome associated with S. levis using a viral metagenomic approach. Through the Read Annotation Tool (RAT) pipeline, we characterized, for the first time, the gut-associated viral community in adult weevils, identifying several novel viral genomes. Sphenophorus levis-associated virus (SLAV) had 12,414 nucleotides (nt); Sphenophorus levis tombus-like virus (SLTV) had 4085 nt; and the four genomic segments of Sphenophorus levis reo-like virus (SLRV) ranged from 2021 to 4386 nt. These genomes were assembled from 65,759 reads (SLAV), 114,441 reads (SLTV), and 270,384 reads (SLRV). Among the detected viral families, Partitiviridae was the most abundant. The identification of possible viral pathogens lays the foundation for future research into their potential use as biological control agents against S. levis. Full article

Efficient control measures for respiratory diseases in humans and farm animals require accurate, specific, and rapid diagnostics. Traditional PCR-based molecular diagnostics are restricted to centralized laboratories, which results in significant, potentially catastrophic delays in test results. A case in point is the recent avian flu outbreak, which has culled more than 280 million poultry birds worldwide (over 157 million in the USA alone) since 2022; has spread to other farm animals, such as cattle; has further heightened the risk of a human pandemic; and threatens food security. To enable molecular diagnosis of bird respiratory diseases at the point of need, we employ loop-mediated isothermal amplification (LAMP) in two platforms: (A) portable devices linked to a smartphone and (B) an inexpensive, disposable, electricity-free, instrument-free device with closed-tube, colorimetric detection that can be produced with minimal resources. Smartphone integration offers an unexplored opportunity for spatiotemporal disease mapping, equipping policymakers with critical data for outbreak control. Our assays demonstrated 100% sensitivity and specificity compared to the gold standard, lab-based, quantitative PCR (qPCR). We tested contrived samples of the avian flu H5N1 virus, laryngotracheitis virus (ILTV), and infectious bronchitis virus (IBV) spiked into clinical samples, achieving a detection sensitivity adequate for early infection diagnosis in under 45 min. The test is simple, requires minimal training, and can be performed without refrigeration, making it well-suited for resource-limited settings. Full article

A spatiotemporal transmission epidemic model is proposed based on human mobility, spatial factors of population migration across multiple regions, individual protection, and government quarantine measures. First, the model’s basic reproduction number and disease-free equilibrium are derived, and the relationship between the basic reproduction number in a single region and that across multiple regions is explored. Second, the global asymptotic stability of both the disease-free equilibrium and the endemic equilibrium is proved by constructing a Lyapunov function. The impact of population migration on the spread of the virus is revealed by numerical simulations, and the global sensitivity of the model parameters is analyzed for a single region. Finally, a protection isolation strategy based on the optimal path is proposed. The experimental results indicate that increasing the isolation rate, improving the treatment rate, enhancing personal protection, and reducing the infection rate can effectively prevent and control the spread of the epidemic. Population migration accelerates the spread of the virus from high-infected areas to low-infected areas, aggravating the epidemic situation. However, effective public health measures in low-infected areas can prevent transmission and reduce the basic reproduction number. Furthermore, if the inflow migration rate exceeds the outflow rate, the number of infected individuals in the region increases. Full article

Wild birds, particularly migratory waterfowl (family Anatidae), are the primary reservoir of avian influenza viruses, playing a key role in their transboundary spread. In the winter of 2016/2017, the H5N8 strain was first recorded in Serbia, with 20 outbreaks confirmed in wild birds by 2021, mostly involving mute swans in the Vojvodina region. From 2021 onward, the dominant strain was H5N1, with 38 confirmed outbreaks up to 2023, primarily affecting mute swans, black-headed gulls, and common cranes. Sporadic H5N2 outbreaks were also detected, with two cases in 2021 and 2023. Due to its rich ornithofauna, natural reserves, and habitats suitable for migratory birds, the Vojvodina region has been officially designated as a high-risk zone by the Veterinary Directorate of the Ministry of Agriculture, Forestry and Water Management of the Republic of Serbia. While sporadic cases occurred in backyard poultry, commercial farms remained unaffected. Infections peaked in autumn and early spring. Control measures included enhanced biosecurity, movement restrictions, and removal of dead birds to protect domestic poultry. Despite the circulation of avian influenza virus in wild birds, Serbia’s commercial poultry industry avoided outbreaks and major economic losses. Including outbreak data provided insight into the scale and persistence of avian influenza threats in this region. Full article

The One Health concept recognises the close interconnection between human, animal, and environmental health. In recent years, this perspective has intensified scientific focus on zoonoses. Among these, arboviruses—viruses transmitted by arthropod vectors—represent an emerging challenge, particularly in the present period strongly conditioned by climate change. Usutu virus (USUV) is a Flavivirus maintained via an enzootic bird–mosquito–bird cycle that infects other vertebrates. USUV is currently a significant animal health concern due to its expanding host range and increasing avian mortality events. Although USUV appears to be less dangerous than other emerging arboviruses in humans, the neurological disorders it can cause are alarming and increase the need for a better understanding of the spread and genetic evolution of USUV, as well as for the stronger promotion of vaccine and antiviral development. As with other arboviruses, treatment for USUV is limited to avoiding contact with mosquitoes, which is not always possible. Since vaccines do not yet exist, the use of modern OMICS sciences may provide comprehensive knowledge for developing effective control and prevention measures to avoid future pandemics and contain current epidemics. Full article

African swine fever virus (ASFV) and classical swine fever virus (CSFV) are important transboundary animal diseases (TADs) affecting swine. ASFV is a large DNA virus with a genome size of 170–190+ kilobases (kB) belonging to the family Asfarviridae, genus Asfivirus. CSFV is a single-stranded RNA virus with a genome size of approximately 12 kB, belonging to the family Flaviviridae, genus Pestivirus. Outbreaks involving either one of these viruses result in similar disease syndromes and significant economic impacts from: (i) high morbidity and mortality events; (ii) control measures which include culling and quarantine; and (iii) export restrictions of swine and pork products. Current detection methods during an outbreak provide minimal genetic information on the circulating virus strains/genotypes that are important for tracing and vaccine considerations. The increasing availability and reduced cost of next-generation sequencing (NGS) allow for the establishment of NGS protocols for the rapid identification and complete genetic characterization of outbreak strains during an investigation. NGS data provides a better understanding of viral spread and evolution, facilitating the development of novel and effective control measures. In this study, panels of primers spanning the genomes of ASFV and CSFV were independently developed to generate approximately 10 kB and 6 kB amplicons, respectively. The primer panels consisted of 19 primer pairs for ASFV and 2 primer pairs for CSFV, providing whole genome amplification of each pathogen. These primer pools were further optimized for batch pooling and thermocycling conditions, resulting in a total of 5 primer pools/reactions used for ASFV and 2 primer pairs/reactions for CSFV. The ASFV primer panel was tested on viral DNA extracted from blood collected from pigs experimentally infected with ASFV genotype I and genotype II viruses. The CSFV primer panel was tested on 11 different strains of CSFV representing the three known CSFV genotypes, and 21 clinical samples collected from pigs experimentally infected with two different genotype 1 CSF viruses. ASFV and CSFV amplicons from optimized PCR were subsequently sequenced on the Oxford Nanopore MinION platform. The targeted protocols for these viruses resulted in an average coverage greater than 1,000X for ASFV, with 99% of the genome covered, and 10,000X–20,000X for CSFV, with 97% to 99% of the genomes covered. The ASFV targeted whole genome sequencing protocol has been optimized for genotype II ASF viruses that have been responsible for the more recent outbreaks outside of Africa. The CSFV targeted whole genome sequencing protocol has universal applications for the detection of all CSFV genotypes. Protocols developed and evaluated here will be essential complementary tools for early pathogen detection and differentiation, as well as genetic characterization of these high-consequence swine viruses, globally and within the United States, should an outbreak occur. Full article

Avian influenza viruses (AIVs) pose significant risks to occupational populations engaged in poultry farming, livestock handling, and live poultry market operations due to frequent exposure to infected animals and contaminated environments. This review synthesizes evidence on AIV exposure patterns and risk factors through a comprehensive analysis of viral characteristics, host dynamics, environmental influences, and human behaviors. The main routes of transmission include direct animal contact, respiratory contact during slaughter/milking, and environmental contamination (aerosols, raw milk, shared equipment). Risks increase as the virus adapts between species, survives longer in cold/wet conditions, and spreads through wild bird migration (long-distance transmission) and live bird trade (local transmission). Recommended control measures include integrated animal–human–environment surveillance, stringent biosecurity measures, vaccination, and education. These findings underscore the urgent need for global ‘One Health’ collaboration to assess risk and implement preventive measures against potentially pandemic strains of influenza A viruses, especially in light of undetected mild/asymptomatic cases and incomplete knowledge of viral evolution. Full article

Risk zone delineation and mobility behavior control constitute critical measures in pandemic containment. Numerous studies utilize static demographic data or dynamic mobility data to calculate the high–risk zones present in cities; however, these studies fail to concurrently consider activity and mobility patterns of populations in both space and time, which results in many studies only being able to employ static geostatistical analytical methods, neglecting the transmission risks associated with human mobility. This study utilized the mobile phone signaling data of Shenzhen residents from 2019 to 2020 and developed a CP tensor decomposition algorithm to decompose the long-sequence spatiotemporal trajectory data to detect high risk zones in terms of detecting overlapped community structures. Tensor decomposition algorithms revealed community structures in 2020 and the overlapping regions among these communities. Based on the overlap in spatial distribution and the similarity in temporal rhythms of these communities, we identified regions with spatiotemporal co-location as high–risk zones. Furthermore, we calculated the degree of population mixing in these areas to indicate the level of risk. These areas could potentially lead to rapid virus spread across communities. The research findings address the shortcomings of currently used static geographic statistical methods in delineating risk zones, and emphasize the critical importance of integrating spatial and temporal dimensions within behavioral big data analytics. Future research should consider utilizing non-aggregated individual trajectories to construct tensors, enabling the inclusion of individual and environmental attributes. Full article

Background: Dental professionals were thought to have the most significant risk of coronavirus infection during the pandemic. Since the first Coronavirus Disease 2019 (COVID-19) patient was detected in Japan in January 2020, Japan has faced several waves of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections. However, no cluster of SARS-CoV-2 infections associated with dental procedures has been reported in Japan. In this study, we aimed to investigate the actual status of SARS-CoV-2 infection during the pandemic through antibody testing for dental professionals. We further investigated saliva and oral management-related aerosol to estimate the risk of virus transmission during dental procedures. Methods: SARS-CoV-2 antibody titer in the blood of dental professionals and their families was determined during the pre-vaccinated period of the SARS-CoV-2 wave to see the history of infection in Japan. Viral loads in saliva and in the aerosol generated during the oral management of COVID-19 patients were detected by RT-qPCR. Results: The antibody testing of dental healthcare providers during the early phases of the pandemic in Japan revealed low antibody positivity, which supported the low incidence of infection clusters among dental clinics. The aerosol generated during dental procedures may contain trace levels of SARS-CoV-2, indicating the risk of transmission through dental procedures is limited. Therefore, SARS-CoV-2 did not spread through dental clinics. Conclusions: Very few SARS-CoV-2 infections were observed in dental professionals who took appropriate infection control measures in the early period of the pandemic. Performing dental procedures using standard precautions seems to be sufficient to prevent SARS-CoV-2 infections. Full article

The Coronavirus Disease 2019 (COVID-19) pandemic highlighted the urgent need for effective vaccination strategies to control the virus’s spread and reduce mortality. Machine learning (ML) algorithms offer promising tools for predicting vaccine effectiveness and aiding public health decisions. This study explores the application of various ML techniques, including artificial neural network (ANN), decision tree (DT), K-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM) to model and forecast the impact of vaccination on COVID-19 mortality. The algorithms were evaluated using accuracy, precision, recall, specificity, F-measure, and area under the curve (AUC) metrics. The findings revealed that DT outperformed other ML algorithms, achieving the highest metrics across multiple evaluation criteria. It recorded an accuracy of 92.27%, precision of 92.54%, recall of 91.95%, specificity of 87.92%, F-measure of 92.24%, and an AUC of 94.50%, highlighting its exceptional predictive performance. Moreover, DT demonstrated this high level of accuracy while maintaining minimal computational time. These findings suggest that ML models, particularly DTs, can be valuable in assessing vaccine effectiveness and informing health strategies against COVID-19. Full article

Monkeypox virus (Mpox virus) is a zoonotic orthopoxvirus that has gained increased global attention due to recent outbreaks. The current review reports the latest update of Mpox cases from 25 February 2022 to 29 April 2025. It also evaluates the possible major complications in human life caused by Mpox. In early 2022, more than 40 countries reported Mpox outbreaks. As of 12 June 2024, the global case count for the 2022–2023 Mpox outbreak was 97,281 confirmed cases, in 118 countries. The World Health Organization (WHO) declared the Mpox virus, a zoonotic disease, a public health emergency of international concern (PHEIC) on 14 August 2024. Mpox symptoms include fever, headache, muscle pain, and face-to-body rashes. The review also highlights Mpox virus replication, genomics, pathology, transmission, diagnosis, and antiviral therapies. The 2022 outbreak is also discussed in detail. The coinfection of HIV in patients infected with Mpox is also discussed. The evolving Mpox epidemiology has raised concerns about the disease’s increasing spread in non-endemic countries, emphasizing the urgent need for control and prevention. The discussion on preventive measures, including vaccination, suggests that cross-protection against Mpox may be possible using orthopoxvirus-specific antibodies. Although there are no specific antiviral drugs available, certain drugs, such as tecovirimat, cidofovir, and ribavirin, are worth considering. Full article

Background: The COVID-19 pandemic highlighted the crucial role of community preventive behaviors in controlling the virus’ spread. Studies show that people’s risk perceptions and awareness significantly contribute to the containment and prevention of infections by motivating adoption of desired actions and behaviors. This study aimed at assessing the role of risk communication and factors that influenced responses during the COVID-19 pandemic in rural communities in Western Kenya. Methods: A descriptive cross-sectional study was conducted using a quantitative research approach, collecting data from 806 individuals across Kisumu, Vihiga, and Kakamega counties. Descriptive statistics were used to detail the demographic characteristics of the study population, while logistic regression analysis estimated the associations between risk communication and demographic characteristics on COVID-19 vaccine acceptance, compliance with mitigation behaviors, perceived severity, and perceived susceptibility. Results: The results showed that 55% of participants were male and 45% were female, with an average moderate compliance with safety measures (mean = 5.15). A significant portion of participants wore face masks (85.3%), practiced hand hygiene (78.9%), and avoided close contact behaviors (66.6%). Most respondents received information through mass media (86.1%) and health workers (72.9%). Compliance with COVID-19 mitigation measures was highest among those who trusted information from official institutions, health professionals, and mass media, compared to social media, with increased odds of 2.7 times and 2.5 times, respectively. Higher risk perception was significantly associated with older age groups (above 50 years), being male, and working in the private sector. Effective risk communication significantly influenced risk perception, compliance with COVID-19 measures, and vaccination acceptance. Conclusions: The findings suggest that effective risk communication strategies are critical during public health emergencies and hence implications for future public health crises. The results underscore the importance of targeted communication and tailored interventions to improve compliance and vaccine acceptance among different demographic groups, ensuring a more robust public health response during outbreaks and pandemics. Full article

The increasing spread of African swine fever (ASF) in recent years and the presence of classical swine fever (CSF) subclinical forms in endemic countries suggests that the possibility of coinfection with ASF virus (ASFV) and CSF virus (CSFV) in pigs cannot be ruled out in areas where both diseases are prevalent. Thus, rapid and reliable diagnosis through molecular testing is essential for the timely implementation of control measures to prevent the spread of these devastating swine diseases. Here, we have coupled two of the most validated PCR assays for the detection of CSFV and ASFV in a single reaction tube. The combination of the two tests for the detection of two target nucleic acids did not affect the analytical sensitivity, and the duplex RT-qPCR assay was comparable with the standard molecular techniques. The detection limits for CSFV RNA and ASFV DNA were 0.12 TCID₅₀/reaction and 0.25 TCID₅₀/reaction, respectively. The test showed high repeatability and reproducibility, the coefficient of variation was below 2%, and excellent performance was demonstrated in clinical samples. The duplex assay shows great potential to become a robust diagnostic tool for the rapid and reliable detection and differentiation of CSFV and ASFV in areas where both viruses may be circulating. Full article