Infection detection revolution: Harnessing AI-powered image analysis to combat infectious diseases.

Infectious diseases wield significant influence on global mortality rates, largely due to the challenge of gauging their severity owing to diverse symptomatology. Each nation grapples with its unique obstacles in combatting these diseases. This study delves into three distinct decision-making methodologies for medical diagnostics employing Neutrosophic Hypersoft Set (NHSS) and Plithogenic Hypersoft Set (PHSS), extensions of the Hypersoft set. It introduces state-of-the-art AI-driven techniques to enhance the precision of medical diagnostics through the analysis of medical imagery. By transforming these images into the aforementioned sets, the analysis becomes more refined, facilitating more accurate diagnoses. The study advocates various courses of action, including isolation, home or specialized center quarantine, or hospitalization for further treatment. The novelty in this study utilizes cutting-edge AI methods to enhance medical imaging, transforming them into accurate diagnostic tools, marking a significant change in how infectious diseases are addressed. By combining machine learning and pattern recognition, it offers the potential to overhaul healthcare worldwide, facilitating accurate diagnoses and customized treatment plans, ultimately reducing the global burden of infectious diseases on mortality rates.

Aptamers: precision tools for diagnosing and treating infectious diseases.

Infectious diseases represent a significant global health challenge, with bacteria, fungi, viruses, and parasitic protozoa being significant causative agents. The shared symptoms among diseases and the emergence of new pathogen variations make diagnosis and treatment complex. Conventional diagnostic methods are laborious and intricate, underscoring the need for rapid, accurate techniques. Aptamer-based technologies offer a promising solution, as they are cost-effective, sensitive, specific, and convenient for molecular disease diagnosis. Aptamers, which are single-stranded RNA or DNA sequences, serve as nucleotide equivalents of monoclonal antibodies, displaying high specificity and affinity for target molecules. They are structurally robust, allowing for long-term storage without substantial activity loss. Aptamers find applications in diverse fields such as drug screening, material science, and environmental monitoring. In biomedicine, they are extensively studied for biomarker detection, diagnostics, imaging, and targeted therapy. This comprehensive review focuses on the utility of aptamers in managing infectious diseases, particularly in the realms of diagnostics and therapeutics.

Diagnostics for detection and surveillance of priority epidemic-prone diseases in Africa: an assessment of testing capacity and laboratory strengthening needs.

In 2023, Africa experienced 180 public health emergencies, of which 90% were infectious diseases and 75% were related to zoonotic diseases. Testing capacity for epidemic-prone diseases is essential to enable rapid and accurate identification of causative agents, and for action to prevent disease spread. Moreover, testing is pivotal in monitoring disease transmission, evaluating public health interventions and informing targeted resource allocation during outbreaks. An online, self-assessment survey was conducted in African Union Member States to identify major challenges in testing for epidemic-prone diseases. The survey assessed current capacity for diagnosing priority epidemic-prone diseases at different laboratory levels. It explored challenges in establishing and maintaining testing capacity to improve outbreak response and mitigate public health impact. Survey data analysed diagnostic capacity for priority infectious diseases, diagnostic technologies in use, existing surveillance programmes and challenges limiting diagnostic capacity, by country. The survey result from 15 Member States who responded to the survey, showed high variability in testing capacity and technologies across countries and diverse factors limiting testing capacity for certain priority diseases like dengue and Crimean-Congo haemorrhagic fever. At the same time diagnostic capacity is better for coronavirus disease 2019 (COVID-19), polio, and measles due to previous investments. Unfortunately, many countries are not utilizing multiplex testing, despite its potential to improve diagnostic access. The challenges of limited laboratory capacity for testing future outbreaks are indeed significant. Recent disease outbreaks in Africa have underscored the urgent need to strengthen diagnostic capacity and introduce cost-effective technologies. Small sample sizes and differing disease prioritisation within each country limited the analysis. These findings suggest the benefits of evaluating laboratory testing capacity for epidemic-prone diseases and highlight the importance of effectively addressing challenges to detect diseases and prevent future pandemics.

An Ontology to Bridge the Clinical Management of Patients and Public Health Responses for Strengthening Infectious Disease Surveillance: Design Science Study.

BACKGROUND: Novel surveillance approaches using digital technologies, including the Internet of Things (IoT), have evolved, enhancing traditional infectious disease surveillance systems by enabling real-time detection of outbreaks and reaching a wider population. However, disparate, heterogenous infectious disease surveillance systems often operate in silos due to a lack of interoperability. As a life-changing clinical use case, the COVID-19 pandemic has manifested that a lack of interoperability can severely inhibit public health responses to emerging infectious diseases. Interoperability is thus critical for building a robust ecosystem of infectious disease surveillance and enhancing preparedness for future outbreaks. The primary enabler for semantic interoperability is ontology. OBJECTIVE: This study aims to design the IoT-based management of infectious disease ontology (IoT-MIDO) to enhance data sharing and integration of data collected from IoT-driven patient health monitoring, clinical management of individual patients, and disparate heterogeneous infectious disease surveillance. METHODS: The ontology modeling approach was chosen for its semantic richness in knowledge representation, flexibility, ease of extensibility, and capability for knowledge inference and reasoning. The IoT-MIDO was developed using the basic formal ontology (BFO) as the top-level ontology. We reused the classes from existing BFO-based ontologies as much as possible to maximize the interoperability with other BFO-based ontologies and databases that rely on them. We formulated the competency questions as requirements for the ontology to achieve the intended goals. RESULTS: We designed an ontology to integrate data from heterogeneous sources, including IoT-driven patient monitoring, clinical management of individual patients, and infectious disease surveillance systems. This integration aims to facilitate the collaboration between clinical care and public health domains. We also demonstrate five use cases using the simplified ontological models to show the potential applications of IoT-MIDO: (1) IoT-driven patient monitoring, risk assessment, early warning, and risk management; (2) clinical management of patients with infectious diseases; (3) epidemic risk analysis for timely response at the public health level; (4) infectious disease surveillance; and (5) transforming patient information into surveillance information. CONCLUSIONS: The development of the IoT-MIDO was driven by competency questions. Being able to answer all the formulated competency questions, we successfully demonstrated that our ontology has the potential to facilitate data sharing and integration for orchestrating IoT-driven patient health monitoring in the context of an infectious disease epidemic, clinical patient management, infectious disease surveillance, and epidemic risk analysis. The novelty and uniqueness of the ontology lie in building a bridge to link IoT-based individual patient monitoring and early warning based on patient risk assessment to infectious disease epidemic surveillance at the public health level. The ontology can also serve as a starting point to enable potential decision support systems, providing actionable insights to support public health organizations and practitioners in making informed decisions in a timely manner.

Barriers to implementation of rapid identification and antimicrobial susceptibility testing technologies in the clinical microbiology laboratory: an American perspective.

Clinical microbiology laboratories are responsible for confirming the aetiology of infectious diseases and providing antimicrobial susceptibility testing results. Traditional culture-based testing can be augmented by more rapid testing modalities to provide clinically actionable information as quickly as possible. Despite improvements in patient outcomes, many clinical microbiology laboratories are facing challenges to in-sourcing these technologies. Depending on a multitude of factors, including size, location and patient population served, these barriers may affect some laboratories and hospital systems to greater or lesser extents than others. It will be up to each individual facility to ascertain its ability to overcome barriers. To aid in this self-assessment, we present for thoughtful consideration a discussion of the barriers to implementation of rapid identification and antimicrobial susceptibility testing technologies, with specific attention to matters of financial cost, staff expertise, operational issues and stakeholder buy-in.

Diagnostic performance of metagenomic sequencing in patients with suspected infection: a large-scale retrospective study.

Background: Metagenomic next-generation sequencing (mNGS) has been widely reported to identify pathogens in infectious diseases (IDs). In this work, we intended to investigate the diagnostic value and clinical acceptance of paired-samples mNGS as compared to the culture method. Methods: A total of 361 patients with suspected infection were retrospectively included. With reference to the clinical diagnosis, we compared the diagnostic performance and clinical acceptance in pathogen detection between mNGS and culture tests. Moreover, the pathogen concordance of paired blood and respiratory tract (RT) samples in mNGS assay was investigated. Results: Among 511 samples, 62.04% were shown to be pathogen positive by mNGS, and that for clinical diagnosis was 51.86% (265/511). When compared to culture assay (n = 428), mNGS had a significantly higher positivity rate (51.87% vs. 33.18%). With reference to the clinical diagnosis, the sensitivity of mNGS outperformed that of culture (89.08% vs. 56.72%). Importantly, mNGS exhibited a clinically accepted rate significantly superior to that of culture. In addition, the mNGS result from 53 paired blood and RT samples showed that most pairs were pathogen positive by both blood and RT, with pathogens largely being partially matched. Conclusion: Through this large-scale study, we further illustrated that mNGS had a clinically accepted rate and sensitivity superior to those of the traditional culture method in diagnosing infections. Moreover, blood and paired RT samples mostly shared partial-matched positive pathogens, especially for pathogens with abundant read numbers in RT, indicating that both blood and RT mNGS can aid the identification of pathogens for respiratory system infection.

[New progress in laboratory detection of respiratory infectious diseases in children].

Respiratory infectious disease has become ahead of all the children's diseases, with the trend of continuously increasing global incidence, antimicrobial resistance and simultaneous infection with multiple pathogens. Diagnosis of this disease is mainly based on clinical symptoms and pathogenic detection. However, there are some differences in clinical manifestations, progression and prognosis between pediatric patients and adults, which prompting clinical diagnosis mainly depending on clinical laboratory test. Therefore, fast, convenient and accurate methods are urgently needed to clarify the type of infectious pathogen and carry out differentiated treatment, and reduce the burden on families and public health-care systems in schools. This article aims to elaborate the laboratory methods of children's respiratory infectious diseases and explore the opportunities and challenges, which can provide ideas for prevention, early screening and diagnosis, prognosis and treatment monitoring.

Detection strategies of infectious diseases via peptide-based electrochemical biosensors.

Infectious diseases have threatened human life for as long as humankind has existed. One of the most crucial aspects of fighting against these infections is diagnosis to prevent disease spread. However, traditional diagnostic methods prove insufficient and time-consuming in the face of a pandemic. Therefore, studies focusing on detecting viruses causing these diseases have increased, with a particular emphasis on developing rapid, accurate, specific, user-friendly, and portable electrochemical biosensor systems. Peptides are used integral components in biosensor fabrication for several reasons, including various and adaptable synthesis protocols, long-term stability, and specificity. Here, we discuss peptide-based electrochemical biosensor systems that have been developed over the last decade for the detection of infectious diseases. In contrast to other reports on peptide-based biosensors, we have emphasized the following points i) the synthesis methods of peptides for biosensor applications, ii) biosensor fabrication approaches of peptide-based electrochemical biosensor systems, iii) the comparison of electrochemical biosensors with other peptide-based biosensor systems and the advantages and limitations of electrochemical biosensors, iv) the pros and cons of peptides compared to other biorecognition molecules in the detection of infectious diseases, v) different perspectives for future studies with the shortcomings of the systems developed in the past decade.

Focus, vigilance, resilience: towards stronger infectious disease surveillance, threat detection and response in the EU/EEA.

This perspective summarises and explains the long-term surveillance framework 2021-2027 for infectious diseases in the European Union/European Economic Area (EU/EEA) published in April 2023. It shows how shortcomings in the areas of public health focus, vigilance and resilience will be addressed through specific strategies in the coming years and how these strategies will lead to stronger surveillance systems for early detection and monitoring of public health threats as well as informing their effective prevention and control. A sharper public health focus is expected from a more targeted list of notifiable diseases, strictly public-health-objective-driven surveillance standards, and consequently, leaner surveillance systems. Vigilance should improve through mandatory event reporting, more automated epidemic intelligence processing and increased use of genomic surveillance. Finally, EU/EEA surveillance systems should become more resilient by modernising the underlying information technology infrastructure, expanding the influenza sentinel surveillance system to other respiratory viruses for better pandemic preparedness, and increasingly exploiting potentially more robust alternative data sources, such as electronic health records and wastewater surveillance. Continued close collaboration across EU/EEA countries will be key to ensuring the full implementation of this surveillance framework and more effective disease prevention and control.

Outbreak detector: a web application to boost disease surveillance systems and timely detection of infectious disease epidemics.

OBJECTIVE: Digital technologies have improved the performance of surveillance systems through early detection of outbreaks and epidemic control. The aim of this study is to introduce an outbreak detection web application called OBDETECTOR (Outbreak Detector), which as a professional web application has the ability to process weekly or daily reported data from disease surveillance systems and facilitates the early detection of disease outbreaks. RESULTS: OBDETECTOR generates a histogram that exhibits the trend of infection within a time range selected by the user. The output comprises red triangles and plus signs, where the former denotes outbreak days determined by the algorithm applied to the data, and the latter represents days identified as outbreaks by the researcher. The graph also displays threshold values and its symbols enable researchers to compute evaluation criteria for outbreak detection algorithms, including sensitivity and specificity. OBDETECTOR allows users to modify algorithm parameters based on their research objectives immediately after loading data. The implementation of automatic web applications results in immediate reporting, precise analysis, and prompt alert notification. Moreover, Public Health authorities and other stakeholders of surveillance can benefit from the widespread accessibility and user-friendliness of these tools, enhancing their knowledge and skills for better engagement in surveillance programs.

Clinical effects of non-pharmaceutical interventions for COVID-19 on other nationally notifiable infectious diseases in South Korea.

BACKGROUND/AIMS: This study aimed to assess the impact of non-pharmaceutical interventions (NPIs) implemented during the COVID-19 pandemic on nationally notifiable infectious diseases (NNIDs) in South Korea. METHODS: Long-term data on seven NNIDs from 2018 to 2021 were analyzed to identify trends and change points using a change point detection technique. The timings of the NPI implementations were compared to the identified change points to determine their association. RESULTS: Varicella, mumps, and scarlet fever showed a significant decrease in incidence following the implementation of NPIs during the COVID-19 pandemic. These diseases, which are primarily transmitted through respiratory droplets, demonstrated a clear response to NPIs. However, carbapenem-resistant Enterobacterales (CRE) showed an increasing trend unrelated to the timing of NPI implementation, suggesting the complex nature of controlling healthcare-associated infections. Hepatitis A, hepatitis C, and scrub typhus did not show significant changes associated with NPIs, likely due to their non-respiratory route of transmission. CONCLUSION: NPIs effectively controlled NNIDs, particularly those transmitted through respiratory infections. However, the impact varied depending on the disease. Understanding the effectiveness and limitations of NPIs is crucial for developing comprehensive public health strategies during infectious disease outbreaks.

A Digital Approach to Improve Infection Screening Among Solid Organ Transplant Candidates.

BACKGROUND: Pretransplant infection screening (IS) of potential organ recipients is essential to optimal outcome of solid organ transplantation (SOT). METHODS: A pre-post study was performed during 2020-2023 to investigate the impact of the STREAM (Solid organ TRansplant stEwArdship and Multidisciplinary approach) intervention to improve IS in SOT. The intervention, performed in 2022, included the implementation of IS through educational meetings, local guidelines, and the availability of a digital screening tool. The objective of the study was the assessment of IS completion, including a list of 17 laboratory tests and the investigation of vaccination status. The reduction of unnecessary tests was also analyzed. The test of proportions and a multilevel multivariate Poisson regression model were used to compare IS completion before and after STREAM. infectious diseases (ID) consultation and urgent evaluation were investigated as predictors of IS completion. RESULTS: A total of 171 patients were enrolled, including liver (44%), heart (32%), and kidney (24%) transplant candidates. Mean age was 56 ± 11 years, and most patients (77%) were males. Ninety-five (56%) patients were included before the intervention and 76 (44%) after STREAM. IS completion increased after STREAM (IRR 1.41, p < 0.001) with significant improvement recorded for seven (39%) IS items. Unnecessary tests decreased by 43% after the intervention. ID consultation (IRR 1.13, p = 0.02) and urgent evaluation (p = 0.68, p < 0.001) were predictors of IS improvement. CONCLUSIONS: STREAM was successful in improving IS completion. Further research is needed to investigate the impact of this intervention on posttransplant infections.

Clinical diagnostic value of targeted next­generation sequencing for infectious diseases (Review).

As sequencing technology transitions from research to clinical settings, due to technological maturity and cost reductions, metagenomic next­generation sequencing (mNGS) is increasingly used. This shift underscores the growing need for more cost­effective and universally accessible sequencing assays to improve patient care and public health. Therefore, targeted NGS (tNGS) is gaining prominence. tNGS involves enrichment of target pathogens in patient samples based on multiplex PCR amplification or probe capture with excellent sensitivity. It is increasingly used in clinical diagnostics due to its practicality and efficiency. The present review compares the principles of different enrichment methods. The high positivity rate of tNGS in the detection of pathogens was found in respiratory samples with specific instances. tNGS maintains high sensitivity (70.8­95.0%) in samples with low pathogen loads, including blood and cerebrospinal fluid. Furthermore, tNGS is effective in detecting drug­resistant strains of Mycobacterium tuberculosis, allowing identification of resistance genes and guiding clinical treatment decisions, which is difficult to achieve with mNGS. In the present review, the application of tNGS in clinical settings and its current limitations are assessed. The continued development of tNGS has the potential to refine diagnostic accuracy and treatment efficacy and improving infectious disease management. However, further research to overcome technical challenges such as workflow time and cost is required.

Aptamer and aptasensor technology for diagnosis of infectious diseases: A mini review.

BACKGROUND: Aptamers are not so new a concept, however, it is scarcely discussed by medical fraternity. Aptamers are potent, new identification molecules set to rope in a new technique in the diagnostic arena. Aptamers have started almost a revolution in diagnostic assays since their discovery in the 90s. (Radu S. Current and previous disease outbreaks around the world, U.S. News & World Report. 2020 Mar 13 [cited 2024 Jun 17]. Available from: https://www.usnews.com/news/best-countries/slideshows/20-pandemic-and-epidemic-diseases-according-to-who) provides an overview of pandemics and epidemics as reported by the WHO. It is interesting to note that several endemic and epidemic diseases viz. Chikungunya, Cholera, Crimean-Congo haemorrhagic fever, Ebola virus disease, Hendra virus infection, Influenza, Lassa fever, Marburg virus disease, Meningitis, MERS-CoV (Middle East Respiratory Syndrome Corona Virus), Monkeypox, Nipah virus infection, Novel coronavirus, Plague, Rift Valley fever, SARS (Severe Acute Respiratory Syndrome), Smallpox, Tularaemia, Yellow fever, and Zika virus disease have been identified by the WHO and are being explored for applicability of aptamer technology in their identification. OBJECTIVES: One of the most important necessities to control epidemic or pandemic diseases is early diagnosis. However, the majority of the diagnostic tests for these diseases are available only in tertiary care centres. The objective of this review is to discuss the potential of aptamer technology to provide undemanding, simple, specific, sensitive, and cost-effective diagnostic assays that are useable in remote and field conditions. CONTENT: Here, we discuss recent advances and approaches in aptamer and aptamer engineering useful in the diagnosis of infectious and non-infectious conditions. This review also discusses a few sensing discoveries which are a gift of advanced engineering and technology using optical and electrochemical aptasensors. It's still a long way to go, and we need to take into account the technological challenges being faced by aptamer-aptasensor technology.

A modified quality control protocol for infectious disease serology based on the Westgard rules.

When traditional statistical quality control protocols, represented by the Westgard protocol were applied to infectious disease serology, the rejection limits were questioned because of the high rejection probability. We first define the probability of false rejection (Pfr) and error detection (Ped) for infectious disease serology. QC data in 6 months were collected and the Pfr of each rule in the Westgard protocol and Rilibak protocol was evaluated. Then, as improvements, we chose different rules for negative and positive QC data to constitute an asymmetric protocol, furthermore, while reagent lot changes, the mean value of QC protocol is reset with the first 15 QC results of new lot reagent. QC materials and Standard Reference Materials were tested synchronously in the next 6 months, to verify whether the Pfr and Ped of the asymmetric protocol could meet the requirement. Protocol 1 exhibited the higher level of rejection rate among the two protocols, especially after reagent lot changes; Pfr below the lower control limit (LCL) was 1.39-21.78 times higher than the upper control limit (UCL); false rejections were more likely to occur in negative QC data, with Pfr-total of 27-65%. The asymmetric protocol can significantly reduce the proportion of analytes with Pfr by over 20%. Systematic error due to reagent lot changes and random error due to routine QC data variation were considered potential factors for excessive Pfr. Asymmetric QC protocol that can reduce Pfr by different control limits for negative and positive QC data.