Disease Control Measures Research Articles

A Review of the Management of Cholelithiasis at Buraydah Central Hospital in the Qassim Region, Saudi Arabia: A Cross-Sectional Study.

Cholelithiasis is the most common cause of gastroenterological hospitalization. Given this significant risk, perfectly managing cholelithiasis is crucial to reduce hospitalization. Unfortunately, we have not found a study on a review of the management of cholelithiasis in Saudi Arabia. Therefore, we aim to evaluate cholelithiasis concerning demographic features, presentation symptoms, predisposing risk factors, laboratory features, complications, and outcomes in the Qassim region. This cross-sectional study of all patients with a radiological diagnosis of gallstones, whether symptomatic or not, was diagnostic in 2022. The researchers fielded a preformed data collection sheet for each patient from the hospital system. Data obtained were entered into a spreadsheet and analyzed using SPSS Statistics version 23.0 (IBM Corp. Released 2015. IBM SPSS Statistics for Windows, Version 23.0. Armonk, NY: IBM Corp.). A total of 526 patients were included in the study. Most patients (116, 22.1%), were aged 38-42. The finding also indicated that most patients were females (397, 75.5%), while males were only 129 (24.5%). The study also found that the difference between women and men presenting complaints of fat intolerance and right shoulder pain was statistically significant. Women were 100 (84%) and men were 19 (16%) for fat intolerance, while for right shoulder pain, women were 50 (89.3%) and men were six (10.7%). The p-values were 0.014 and 0.011, respectively. Further, there was a statistically significant difference in terms of the complaints presented by the patients between the complicated and non-complicated cases of abdominal pain (p=0.001), nausea (p=0.001), vomiting (p=0.001), change in urine and stool color (p=0.001), and right shoulder pain (p=0.001), among other complaints (p=0.001). The study concludes that most patients affected by cholelithiasis are individuals in the middle age group, with women being more affected by the disease than men. Further, among the individuals affected by the disease, the majority of them were overweight and obese. On the other hand, the study concludes that the majority of patients who suffer more from cholelithiasis are affected mainly by other associated diseases such as hypertension, hypothyroidism, and diabetes mellitus. In conclusion, many factors may contribute to gallstone formation and the outcome of the disease and surgery. Therefore, the study recommends that health workers offer tailored education, especially targeting the highlighted factors found in this study, to create awareness of disease control measures in the general population. Also, keep in mind these factors when dealing with patients who complain of abdominal pain.

Challenges to Cannabis sativa Production from Pathogens and Microbes-The Role of Molecular Diagnostics and Bioinformatics.

The increased cultivation of Cannabis sativa L. in North America, represented by high Δ9-tetrahydrocannabinol-containing (high-THC) cannabis genotypes and low-THC-containing hemp genotypes, has been impacted by an increasing number of plant pathogens. These include fungi which destroy roots, stems, and leaves, in some cases causing a build-up of populations and mycotoxins in the inflorescences that can negatively impact quality. Viroids and viruses have also increased in prevalence and severity and can reduce plant growth and product quality. Rapid diagnosis of the occurrence and spread of these pathogens is critical. Techniques in the area of molecular diagnostics have been applied to study these pathogens in both cannabis and hemp. These include polymerase chain reaction (PCR)-based technologies, including RT-PCR, multiplex RT-PCR, RT-qPCR, and ddPCR, as well as whole-genome sequencing (NGS) and bioinformatics. In this study, examples of how these technologies have enhanced the rapidity and sensitivity of pathogen diagnosis on cannabis and hemp will be illustrated. These molecular tools have also enabled studies on the diversity and origins of specific pathogens, specifically viruses and viroids, and these will be illustrated. Comparative studies on the genomics and metabolomics of healthy and diseased plants are urgently needed to provide insight into their impact on the quality and composition of cannabis and hemp-derived products. Management of these pathogens will require monitoring of their spread and survival using the appropriate technologies to allow accurate detection, followed by appropriate implementation of disease control measures.

Application of Mathematical Models of the Dynamics of the Epidemic Acute Respiratory Viral Infections to Increase the Efficiency of Epidemiological Surveillance

Uncertainty in the calculations of forecasts of the spread of epidemic acute respiratory infections obtained using mathematical models, associated with data error and uncertainty in the choice of a model, as well as the lack of verification of modeling results by interdisciplinary teams including epidemiology specialists, prevent the correct prediction of the effectiveness of disease control measures. In this paper, we propose a solution to these problems by using a software package consisting of a family of epidemic models, methods for estimating the error of output data depending on the error of the initial morbidity data, as well as a graphical interface with the possibility of manual correction of the results of automatic calibration and generation of epidemic bulletins. The novelty of the presented study is the methodology for integrating epidemic models into software tools used by supervisory authorities, which allows to supplement weekly bulletins and annual epidemiological reports in semi-automatic mode with a quantitative interval estimation of the error of calculated indicators. The ultimate goal is to provide the supervisory authorities with informative and promptly obtained calculated data for decision-making in the field of infection control.

Environmental and Occupational Factors Associated with Leptospirosis: A Systematic Review

BackgroundLeptospirosis is a neglected emerging zoonotic disease with a profound public health impact worldwide with higher burden of disease in resource-poor countries. The environmental and occupational exposures contribute to human and animal transmission, but the interaction was less explored. A deeper understanding of the critical environmental and occupational drivers in different contexts will provide useful information for disease control and prevention measures. ObjectiveThis review aimed to summarize the potential environmental and occupational risk factors associated with leptospirosis infection. MethodsFour databases (Scopus, Web of Science, Ovid MEDLINE, EBSCOhost) were searched for articles published from 2012 to 2021. Eligible articles were assessed using a checklist for assessing the quality of the studies. The quality of the articles was assessed based on the laboratory diagnosis approach and statistical analysis method. ResultsA total of 32 studies were included in this systematic review. Water-related risk factors such as natural water as the primary water source (AOR 1.8–18.28), water-related recreational activities (AOR 2.36–10.45), flood exposure (AOR 1.54–6.04), contact with mud (AOR 1.57–4.58) and stagnant water (AOR 2.79–6.42) were associated with increased risk of leptospirosis. Infrastructural deficiencies such as un-plastered house walls and thatched houses presented a higher risk (AOR 2.71–5.17). Living in low-lying areas (AOR 1.58–3.74), on clay loam soil (OR 2.72), agricultural land (OR 2.09), and near rubber tree plantations (AOR 11.65) is associated with higher risk of leptospirosis. Contact with rats (AOR 1.4–3.5), livestock (AOR 1.3–10.4), and pigs (AOR 1.54–7.9) is associated with an increased risk of leptospirosis. Outdoor workers (AOR 1.95–3.95) and slaughterhouse workers (AOR 5.1–7.5) have higher risk of leptospirosis. ConclusionThe environmental and occupational components related to water, infrastructure, landscape, agriculture, and exposed animals play an essential role in leptospirosis transmission. The magnitude of those risk factors differs with geographical region, climate factor, urbanization and population growth, and the country’s socioeconomic status.

DNA Sensor for the Detection of Brucella spp. Based on Magnetic Nanoparticle Markers.

Due to the limitations of conventional Brucella detection methods, including safety concerns, long incubation times, and limited specificity, the development of a rapid, selective, and accurate technique for the early detection of Brucella in livestock animals is crucial to prevent the spread of the associated disease. In the present study, we introduce a magnetic nanoparticle marker-based biosensor using frequency mixing magnetic detection for point-of-care testing and quantification of Brucella DNA. Superparamagnetic nanoparticles were used as magnetically measured markers to selectively detect the target DNA hybridized with its complementary capture probes immobilized on a porous polyethylene filter. Experimental conditions like density and length of the probes, hybridization time and temperature, and magnetic binding specificity, sensitivity, and detection limit were investigated and optimized. Our sensor demonstrated a relatively fast detection time of approximately 10 min, with a detection limit of 55 copies (0.09 fM) when tested using DNA amplified from Brucella genetic material. In addition, the detection specificity was examined using gDNA from Brucella and other zoonotic bacteria that may coexist in the same niche, confirming the method's selectivity for Brucella DNA. Our proposed biosensor has the potential to be used for the early detection of Brucella bacteria in the field and can contribute to disease control measures.

The Evaluation of Collaborative Disease Prevention and Control Measures for Border Health Between Thailand and Myanmar, Laos, and Cambodia

The Evaluation of Collaborative Disease Prevention and Control Measures for Border Health Between Thailand and Myanmar, Laos, and Cambodia

Tracking SARS-CoV-2 variants during the 2023 flu season and beyond in Lebanon

BackgroundEarly SARS-CoV-2 variant detection relies on testing and genomic surveillance. The Omicron variant (B.1.1.529) has quickly become the dominant type among the previous circulating variants worldwide. Several subvariants have emerged exhibiting greater infectivity and immune evasion. In this study we aimed at studying the prevalence of the Omicron subvariants during the flu season and beyond in Lebanon through genomic screening and at determining the overall standing and trajectory of the pandemic in the country. MethodsA total of 155 SARS-CoV-2 RNA samples were sequenced, using Nanopore sequencing technology. ResultsNanopore sequencing of 155 genomes revealed their distribution over 39 Omicron variants. XBB.1.5 (23.29 %) was the most common, followed by XBB.1.9.1 (10.96 %) and XBB.1.42 (7.5 %). The first batch collected between September and November 2022, included the BA.2.75.2, BA.5.2, BA.5.2.20, BA.5.2.25 and BQ.1.1.5 lineages. Between December 2022 and January 2023, those lineages were replaced by BA.2.75.5, BN.1, BN.1.4, BQ.1, BQ.1.1, BQ.1.1.23, CH.1.1, CM.4 and XBK. Starting February 2023, we observed a gradual emergence and dominance of the recombinant XBB and its sub-lineages (XBB.1, XBB.1.5, XBB.1.5.2, XBB.1.5.3, XBB.1.9, XBB.1.9.1, XBB.1.9.2, XBB.1.16, XBB.1.22 and XBB.1.42). ConclusionsThe timely detection and characterization of SARS-CoV-2 variants is important to reduce transmission through established disease control measures and to avoid introductions into animal populations that could lead to serious public health implications.

Knowledge, attitudes, and practices (KAP) toward seasonal influenza vaccine among college students under the COVID-19 pandemic in South China.

The control measures of the coronavirus disease 2019 (COVID-19) pandemic had influenced the activity of the influenza virus, and we were wondering the knowledge, attitudes, and practices (KAP) toward seasonal influenza vaccine among college students were having at the context of the COVID-19 pandemic. Online questionnaire survey of the college students was conducted and the data was collected anonymously, cross-sectional study were used to describe the distribution of the KAP. There were 815 respondents in our study. Most participants have a high recognition of the effectiveness and safety of the influenza vaccine. However, a low awareness rate of influenza vaccine knowledge and vaccination rate (18%) against influenza was observed among college students. The education level and major would have a higher weight on the influence of KAP among the college students. Binary logistic regression analysis showed that the sex (OR = 2.163, p < .001), age (OR = 2.242, p < .001), heard of the influenza vaccine (OR = 2.655, p = .014), and "How necessary do you think vaccinating every year is?" (OR = 3.947, p < .001) of the college students were the main factors that affect the KAP on influenza vaccination. Our study provided an insight into the KAP of influenza vaccine among college students in South China. The vaccination rate and acceptability of influenza vaccine in college students are higher than that in the whole population.

Development and evaluation of a multiplex polymerase chain reaction in real-time for differential diagnosis of Moraxella-induced keratoconjunctivitis in livestock.

Infectious bovine keratoconjunctivitis (IBK) is a prevalent ocular disease that affects livestock, leading to substantial economic losses due to reduced production and culling of infected animals. Moraxella spp. is common bacterial pathogens that can cause keratoconjunctivitis in livestock. Therefore, rapid and accurate diagnosis is crucial for effective treatment and disease control. This study aimed to develop a multiplex real-time polymerase chain reaction (mRT-PCR) assay for the detection and differentiation of Moraxella bovoculi, Moraxella ovis, and Moraxella bovis. Three reference strains of Moraxella as positive controls and 36 lacrimal swab samples collected from cattle were used to evaluate the developed mRT-PCR assay DNA extraction that was performed using the RIBO-sorb DNA/RNA extraction kit. Primers and probes were designed using the SpeciesPrimer pipeline. The annealing temperature, primer and probe concentrations, and sensitivity and specificity of the assay were optimized. An mRT-PCR assay was developed to detect pathogens associated with IBK in cattle on the basis of optimized parameters. The specificity and sensitivity of this assay were confirmed using samples containing individual pathogens (O - M. ovis, B - M. bovis, and BO - M. bovoculi), combinations of two pathogens (O-B, B-BO, and O-BO), and when the DNA of all three pathogens was present in a single reaction (O-B-BO). The analytical sensitivity of mRT-PCR for detecting M. ovis and M. bovoculi DNA was 21 copies or 50 fg per reaction, whereas that for M. bovis was 210 copies or 500 fg per reaction. In addition, this assay has been tested on samples isolated from the affected eyes of cattle in the Akmola region of the Republic of Kazakhstan. For the first time in the Republic of Kazakhstan, the proposed mRT-PCR assay for the simultaneous detection of three Moraxella spp. pathogens has been developed. This assay exhibits the required specificity and high sensitivity for m RT-PCR, facilitating the timely implementation of effective measures for disease control and the prevention of economic losses. These losses are linked to a reduction in livestock breeding value, a reduction in meat and milk production, a reduction in the reproductive performance of heifers, resulting in fewer offspring, as well as costs related to the treatment of affected animals.

팬데믹과 뉴노멀 시대에 있어서 4차산업혁명과 법치주의의 과제

The post-COVID era is clearly a time requiring the convergence of law and science, navigating through both pandemic and endemic situations. The era has witnessed the implementation of stringent social measures, such as social distancing, movement and location tracking, restrictions on gatherings and protests, mandatory vaccinations, vaccine passports, business operation limits, school attendance timing restrictions, mask mandates, utilization of non-contact transactions, enforced quarantine, and lockdowns. These measures have necessitated a confluence of law and science. While South Korea has rapidly addressed this convergence from a rule-of-law perspective, there remain shortcomings in this approach. Particularly, the introduction of Fourth Industrial Revolution technologies like artificial intelligence, big data, and the Internet of Things in the post-COVID era presents new challenges to legal principles, necessitating legitimate and constitutional justifications.&#x0D; Despite the fact that various disease control measures utilizing Fourth Industrial Revolution technologies would not have been easily accepted under normal circumstances, they have been widely adopted and utilized under the public interest pretext of combating the pandemic during emergency legislative and administrative measures. While specific and concrete rules are most commonly employed in regular times, the pandemic has led to an increase in general disposals, extensive use of regulatory orders beyond legal mandates, and the deployment of administrative rules and guidelines without sufficient authorization considerations. These legislative and administrative measures, as tools in the fight against COVID-19, often failed to adequately reflect the demands of rule-of-law. Particularly, the pandemic has paved the way for the unprecedented use of Fourth Industrial Revolution technologies in this new normal era, necessitating continuous consideration of rule-of-law principles.&#x0D; From a legal theory perspective, a balanced approach is required in weighing safety and freedom, safety and discrimination, and permissible risks, harmonizing these within a risk society where science and technology challenge existing norms. Although the use of Fourth Industrial Revolution technologies and enhanced vaccination efforts have enabled us to emerge from the dire pandemic, continuous legislative and administrative efforts are needed to address the deepening digital divide.&#x0D; From a policy perspective, a critical view has been developed regarding specific measures, discussing improvements and alternatives. Topics include fine-tuning rule-of-law in response to disease control measures, adjusting to the dominance of algorithms, restoring normalcy and fundamental rights, the resilient recovery of markets, overcoming the limits of traditional regulations, utilizing self-regulation and regulated self-regulation, addressing new challenges related to various epidemic measures, data privacy, and Big Brother concerns.&#x0D; As we move from pandemic to endemic, the tasks of rule-of-law in this era are evolving. Emergency legal and administrative measures need to be re-evaluated under normal rule-of-law standards. This paper has analyzed various measures in response to the pandemic and endemic situations from legal theory and policy perspectives, arguing the need for ongoing contemplation and policy efforts towards new challenges of rule-of-law.

Revealing associations between spatial time series trends of COVID-19 incidence and human mobility: an analysis of bidirectionality and spatiotemporal heterogeneity

BackgroundUsing human mobility as a proxy for social interaction, previous studies revealed bidirectional associations between COVID-19 incidence and human mobility. For example, while an increase in COVID-19 cases may affect mobility to decrease due to lockdowns or fear, conversely, an increase in mobility can potentially amplify social interactions, thereby contributing to an upsurge in COVID-19 cases. Nevertheless, these bidirectional relationships exhibit variations in their nature, evolve over time, and lack generalizability across different geographical contexts. Consequently, a systematic approach is required to detect functional, spatial, and temporal variations within the intricate relationship between disease incidence and mobility.MethodsWe introduce a spatial time series workflow to investigate the bidirectional associations between human mobility and disease incidence, examining how these associations differ across geographic space and throughout different waves of a pandemic. By utilizing daily COVID-19 cases and mobility flows at the county level during three pandemic waves in the US, we conduct bidirectional Granger causality tests for each county and wave. Furthermore, we employ dynamic time warping to quantify the similarity between the trends of disease incidence and mobility, enabling us to map the spatial distribution of trends that are either similar or dissimilar.ResultsOur analysis reveals significant bidirectional associations between COVID-19 incidence and mobility, and we develop a typology to explain the variations in these associations across waves and counties. Overall, COVID-19 incidence exerts a greater influence on mobility than vice versa, but the correlation between the two variables exhibits a stronger connection during the initial wave and weakens over time. Additionally, the relationship between COVID-19 incidence and mobility undergoes changes in direction and significance for certain counties across different waves. These shifts can be attributed to alterations in disease control measures and the presence of evolving confounding factors that differ both spatially and temporally.ConclusionsThis study provides insights into the spatial and temporal dynamics of the relationship between COVID-19 incidence and human mobility across different waves. Understanding these variations is crucial for informing the development of more targeted and effective healthcare policies and interventions, particularly at the city or county level where such policies must be implemented. Although we study the association between mobility and COVID-19 incidence, our workflow can be applied to investigate the associations between the time series trends of various infectious diseases and relevant contributing factors, which play a role in disease transmission.

Identification and characterization of motile Aeromonas spp. isolated from farmed Nile tilapia (Oreochromis niloticus) in the Philippines.

Motile Aeromonas septicaemia (MAS) caused by motile Aeromonas species is an important disease in farmed freshwater fish due to intensification of culture and improper farm practices. This study characterized and profiled motile Aeromonas species recovered from clinically sick tilapia farmed in the Philippines, with a view to identifying targeted disease prevention and control measures against MAS in farmed tilapia species. Sixteen isolates from diseased farmed Nile tilapia were identified as Aeromonas veronii (n=14), Aeromonas caviae (n=1), and Aeromonas dhakensis (n=1). Five biochemical profiles using API 20E were exhibited by the A. veronii strains giving an unreliable identification. A high level of agreement was observed in identifying the Aeromonas strains using 16S rRNA and rpoD gene sequencing, although the latter has a higher discriminatory value. Three or more virulence genes dominated by cytotoxic enterotoxin act and aerolysin aer were detected. Different genotypes based on virulence gene clustering suggested varied mechanisms used by Aeromonas to colonize and infect or to mutualistically co-exist with the fish. Acquired multiple antibiotic resistance was found in a single A. veronii isolate. All were susceptible to enrofloxacin, oxolinic acid, florfenicol, and chloramphenicol. Tetracycline and sulfonamide resistances and class 1 integron were detected in three A. veronii isolates. Several strains of motile aeromonads, especially A. veronii, which have varied genotypes based on virulence, biochemical profile, and antibiotic resistance, are involved in MAS in natural disease outbreaks in farmed Nile tilapia in the Philippines.

Health Management in Livestock Production in Sub Saharan Countries

Purpose: The general objective of this study was to explore health management in livestock production in Sub Saharan countries.&#x0D; Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.&#x0D; Findings: The findings revealed that there exists a contextual and methodological gap relating to health management in livestock production in Sub Saharan countries. Preliminary empirical review revealed that the health management of livestock in Sub-Saharan Africa is a complex and multifaceted endeavor, influenced by a range of factors including limited access to veterinary services, inadequate nutrition management, and the effectiveness of disease control measures.&#x0D; Unique Contribution to Theory, Practice and Policy: The One Health theory, Theory of Planned Behaviour and the Diffusion of Innovations theory may be used to anchor future studies relating to livestock production. The study recommends for enhancing access to veterinary services, promoting knowledge, scaling up vaccination efforts, improving nutrition management, strengthening biosecurity measures, using gender sensitive approaches and investing in disease surveillance and rapid response.

Mycobacterium tuberculosis complex molecular networks and their regulation: Implications of strain heterogeneity on epigenetic diversity and transcriptome regulation

Tuberculosis has been a public health crisis since the 1900, which has caused the highest mortalities due to a single bacterial infection worldwide, that was recently further complicated by the Coronavirus disease 2019 pandemic. The causative agent of Tuberculosis, Mycobacterium tuberculosis, belongs to a genetically well-characterized family of strains known as the Mycobacterium tuberculosis complex, which has complicated progress made towards eradicating Tuberculosis due to pathogen-specific phenotypic differences in the members of this complex. Mycobacterium tuberculosis complex strains are genetically diverse human- and animal-adapted pathogens belonging to 7 lineages (Indo-Oceanic, East-Asian, East-African Indian, Euro-American, M. africanum West Africa 1, M. africanum West Africa 2 and Ethopia), respectively and the recently identified Lineage 8 and M. africanum Lineage 9. Genomic studies have revealed that Mycobacterium tuberculosis complex members are ∼99 % similar, however, due to selective pressure and adaptation to human host, they are prone to mutations that have resulted in development of drug resistance and phenotypic heterogeneity that impact strain virulence. Furthermore, members of the Mycobacterium tuberculosis complex have preferred geographic locations and possess unique phenotypic characteristics that is linked to their pathogenicity. Due to the recent advances in development next generation sequencing platforms, several studies have revealed epigenetic changes in genomic regions combined with “unique” gene regulatory mechanisms through non-coding RNAs that are responsible for strain-specific behaviour on in vitro and in vivo infection models. The current review provides up to date epigenetic patterns, gene regulation through non-coding RNAs, together with implications of these mechanisms in down-stream proteome and metabolome, which may be responsible for “unique” responses to infection by members of the Mycobacterium tuberculosis complex. Understanding lineage-specific molecular mechanisms during infection may provide novel drug targets and disease control measures towards World Health organization END-TB strategy.

Prevalence of Hepatitis B and Hepatitis C Viral Infections and Their Associated Factors among Diabetic Patients Visiting Debre Tabor Referral Hospital, Northwest Ethiopia, 2021: A Cross-Sectional Study.

Viral hepatitis is a global public health problem that affects millions of people each year, causing disability and death. Hepatitis B and C viruses are the most common causes of viral hepatitis and are associated with chronic liver disease, cirrhosis, and hepatocellular carcinoma. The primary site of infection for these viruses is the liver, the primary site of hormone and glucose metabolism closely linked to diabetes mellitus (DM), which is associated with increased morbidity and mortality worldwide. As a result, assessing the coexistence of viral hepatitis and DM could be important in disease management, prevention, and control measures in DM patients. The aim of our study is to assess the prevalence and associated factors of HBV and HCV among diabetes patients attending Debre Tabor Referral Hospital. An institutional-based, cross-sectional study was conducted from December 1, 2021, to February 30, 2021. A systematic sampling technique was used for selecting study participants. Serum samples were screened with a rapid test kit for hepatitis B (HBV) and hepatitis C (HCV) infections. A pretested structured questionnaire was constructed to collect the data, which were later analyzed using SPSS version 23. Inferential statistics were used to evaluate the associated risk factors for the outcome variable. A p value of <0.05 was considered statistically significant. A total of 152 diabetes patients were included in this study, with 78 (51.3%) males and 74 (48.7%) females, with a mean age of 39.24 ± 17.90 years. The prevalence of HBV and HCV was 6 (3.9%) and 2 (1.3%), respectively. Most of potential risk factors such as, histories of surgical procedures, tooth extraction, hepatitis infection in the family, blood transfusion, alcohol consumption, body tattooing, and multiple sexual partners were not statistically significant for HBV and HCV infections. In this study, no association was obtained between sociodemographic, clinical, and behavioural factors and the prevalence of hepatitis B and C viruses. Furthermore, there is no significant association detected between HBV or potential HCV infection and DM. Despite these results, continuing professional training programs on HBV and HCV infection, including increased vaccination coverage rates for HBV, are required.

Mortality burden and future projections of major risk factors for esophageal cancer in China from 1990 to 2019.

This study, based on Global Burden of Disease (GBD) data, aimed to report the long-term trend in mortality rates caused by risk factors for esophageal cancer (EC) in China from 1990 to 2019 and predict the burden of EC mortality caused by these risk factors over the next 15years. We examined six risk factors that influenced EC mortality rates in China and their respective rankings. Furthermore, we analyzed the number of deaths and crude mortality rates (CMR) caused by these risk factors for both sexes and different age groups. Age-standardized mortality rates (ASMR) and the number of deaths across all age groups were also analyzed. Finally, we utilized the Bayesian Age-Period-Cohort (BAPC) model to predict the trends in ASMR burden caused by these risk factors in the future. From 1990 to 2019, the percentage changes in ASMR for EC caused by the six risk factors in China were as follows: smoking (-33.4%), alcohol consumption (-23.0%), low fruit intake (-73.6%), low vegetable intake (-96.0%), high Body Mass Index (BMI) (25.1%), and tobacco chewing (-32.8%). In 2019, the top three risk factors contributing to EC ASMR in China were smoking, alcohol consumption, and high BMI. Overall, the ASMR for EC in China fluctuated and declined from 1990 to 2019. The most common risk factors for males were smoking and alcohol consumption, while low fruit intake and high BMI were the most common risk factors for females. The impact of these risk factors on EC mortality increased with age, except for the elderly population. BAPC analysis indicated that the influence of these risk factors on ASMR was expected to remain relatively stable in the next 15years, suggesting a continued significant burden of EC. The projected burden of EC mortality in China was expected to continue increasing steadily over the next 15years, highlighting the pressing need for disease control measures. To alleviate this burden, targeted prevention and control policies addressing risk factors for EC such as smoking, alcohol consumption, and high BMI are necessary.

Data Augmentation for Mask-Based Leaf Segmentation of UAV-Images as a Basis to Extract Leaf-Based Phenotyping Parameters

In crop protection, disease quantification parameters such as disease incidence (DI) and disease severity (DS) are the principal indicators for decision making, aimed at ensuring the safety and productivity of crop yield. The quantification is standardized with leaf organs, defined as individual scoring units. This study focuses on identifying and segmenting individual leaves in agricultural fields using unmanned aerial vehicle (UAV), multispectral imagery of sugar beet fields, and deep instance segmentation networks (Mask R-CNN). Five strategies for achieving network robustness with limited labeled images are tested and compared, employing simple and copy-paste image augmentation techniques. The study also evaluates the impact of environmental conditions on network performance. Metrics of performance show that multispectral UAV images recorded under sunny conditions lead to a performance drop. Focusing on the practical application, we employ Mask R-CNN models in an image-processing pipeline to calculate leaf-based parameters including DS and DI. The pipeline was applied in time-series in an experimental trial with five varieties and two fungicide strategies to illustrate epidemiological development. Disease severity calculated with the model with highest Average Precision (AP) shows the strongest correlation with the same parameter assessed by experts. The time-series development of disease severity and disease incidence demonstrates the advantages of multispectral UAV-imagery in contrasting varieties for resistance, as well as the limits for disease control measurements. This study identifies key components for automatic leaf segmentation of diseased plants using UAV imagery, such as illumination and disease condition. It also provides a tool for delivering leaf-based parameters relevant to optimize crop production through automated disease quantification by imaging tools.

TASER: A flexible approach for nucleic acid detection using a molecular converter

Advancing expeditious and highly responsive in vitro diagnostic techniques is paramount to ensure the efficacy of disease prevention and control measures. Although polymerase chain reaction (PCR) has historically been regarded as the preferred technique for nucleic acid detection, its application is constrained by the need for thermal cycling equipment. While isothermal amplification methods do address some of the challenges associated with PCR, the approach of quantifying amplicons has limitations in the development of highly accessible and flexible measurement of nucleic acids. In this study, we employed the translational machinery as a biological module to transform target nucleic acids into a variety of proteins. These proteins were subsequently detectable using various equipment and devices commonly accessible in various settings. These include luminometers, fluorometers, spectrophotometers, lateral flow strip sensors, and glucose meters. This approach termed target-assisted synthesis of enzyme reporters (TASER) is based on straightforward mechanisms that transform target nucleic acids into easily quantifiable proteins, thereby offering a versatile pathway for highly adaptable and cost-effective nucleic acid testing.

Evaluation of foot and mouth disease control measures: Simulating two endemic areas of Thailand.

Foot and mouth disease (FMD) is an important livestock disease in Thailand, with outbreaks occurring every year. However, the effects of FMD control measures in Thailand have received little research attention. Epidemiological models have been widely used to evaluate FMD outbreak control, but such a model has never been developed for Thailand. We constructed a stochastic between-farm transmission model to evaluate FMD control measures. The epidemiological unit of the model was the farm, which could be in different states: susceptible, latent, undetected infectious, detected infectious and recovered. The between-farm transmission was calculated by the sum of distance-dependent transmission and trade network transmission using parameters derived from FMD outbreaks in 2016-2017. We used this model to simulate the outbreaks with and without the implementation of the following control measures: culling all animals on infected farms, ring vaccination, animal movement restrictions and isolation of infected farms. The control measures were evaluated by estimating the number of secondarily infected farms and the outbreak duration for each scenario. The model was simulated in two study areas located in the Lamphaya Klang subdistrict (high farm density) and the Bo Phloi district (low farm density). The effects of control measures differed between the two study areas. When farm density was high, rigid control measures were required to prevent a major outbreak. Among all options, culling the animals on infected farms resulted in the lowest number of infected farms and the shortest outbreak duration. In contrast, for an area with a low farm density, less stringent control measures were sufficient to control the usually minor outbreaks. The results indicate that different areas require a different approach to control an outbreak of FMD.

Breeding for Late Blight Disease Resistance Varieties in Potato: A Strategic Approach for Food Security and Sustainability

Potato (Solanum tuberosum L.) is one the most important stable foods that helps to resolve the global food crisis. However, its production has been limited due to various biotic and abiotic factors. Late blight disease caused by Phytophthora infestans is one of the destructive pathogenic diseases that not only results in potato yield losses but also increase the cost of production due to huge monetary expenses the growers inquire for disease control and preventive measures. The pathogen could result in a 20-100% yield reduction depending on the susceptibility of the variety, prevailing climatic variables, preventive and control measures taken, and the pathogen load in the area. The losses in the yield resulted in hunger and starvation. Annually, the losses due to Phytophthora infestans have been estimated to be $ 12 billion globally. The use of chemicals to control the disease seems to be the most effective measure, the method is no more economically and environmentally sustainable. The development and deployment of resistant varieties remain the most sustainable approach to managing and controlling diseases to ensure food security. This review examines the significance of the late blight disease of potatoes, its control measure, and the need for disease-resistant varieties.