Machine learning and artificial intelligence for the diagnosis of infectious diseases in immunocompromised patients.

PURPOSE OF REVIEW: Immunocompromised patients are at high risk for infection. During the coronavirus disease (COVID-19) pandemic, immunocompromised patients exhibited increased odds of intensive care unit admission and death. Early pathogen identification is essential to mitigating infection related risk in immunocompromised patients. Artificial intelligence (AI) and machine learning (ML) have tremendous appeal to address unmet diagnostic needs. These AI/ML tools often rely on the wealth of data found in healthcare to enhance our ability to identify clinically significant patterns of disease. To this end, our review provides an overview of the current AI/ML landscape as it applies to infectious disease testing with emphasis on immunocompromised patients. RECENT FINDINGS: Examples include AI/ML for predicting sepsis in high risk burn patients. Likewise, ML is utilized to analyze complex host-response proteomic data to predict respiratory infections including COVID-19. These same approaches have also been applied for pathogen identification of bacteria, viruses, and hard to detect fungal microbes. Future uses of AI/ML may include integration of predictive analytics in point-of-care (POC) testing and data fusion applications. SUMMARY: Immunocompromised patients are at high risk for infections. AI/ML is transforming infectious disease testing and has great potential to address challenges encountered in the immune compromised population.

Recent development of nanotechnology-empowered antigen assay methods for the control of infectious diseases.

The global spread of air-borne diseases, such as Covid-19 caused by the new coronavirus (SARS-CoV-2), has significantly impacted public health and economic development worldwide. Accurate and rapid detection of pathogens is the key to controlling the spread of infection and reducing severe illness and death. Compared to nucleic acid testing, rapid antigen testing for pathogen proteins shows unique advantages such as convenience, speed, and cost-effectiveness, but its sensitivity is limited. Here, we review the latest progress in the development of immunological assay methods for infectious diseases. We summarize the principles, performance, advantages and limitations of several representative methods. We highlight recent efforts in utilizing nanotechnology to engineer biosensing interfaces, offering enhanced sensitivity while maintaining convenience for on-site diagnosis. Finally, we provide an outlook on the development of this field.

Exploring the role of secretory proteins in the human infectious diseases diagnosis and therapeutics.

Secretory proteins are playing important role during the host-pathogen interaction to develop the infection or protection into the cell. Pathogens developing infectious disease to human being are taken up by host macrophages or number of immune cells, play an important role in physiological, developmental and immunological function. At the same time, infectious agents are also secreting various proteins to neutralize the resistance caused by host cells and also helping the pathogens to develop the infection. Secretory proteins (secretome) are only developed at the time of host-pathogen interaction, therefore they become very important to develop the targeted and potential therapeutic strategies. Pathogen specific secretory proteins released during interaction with host cell provide opportunity to develop point of care and rapid diagnostic kits. Proteins secreted by pathogens at the time of interaction with host cell have also been found as immunogenic in nature and numbers of vaccines have been developed to control the spread of human infectious diseases. This chapter highlights the importance of secretory proteins in the development of diagnostic and therapeutic strategies to fight against human infectious diseases.

COVID-19 impact on EuroTravNet infectious diseases sentinel surveillance in Europe.

BACKGROUND: The COVID-19 pandemic resulted in a sharp decline of post-travel patient encounters at the European sentinel surveillance network (EuroTravNet) of travellers' health. We report on the impact of COVID-19 on travel-related infectious diseases as recorded by EuroTravNet clinics. METHODS: Travelers who presented between January 1, 2019 and September 30, 2021 were included. Comparisons were made between the pre-pandemic period (14 months from January 1, 2019 to February 29, 2020); and the pandemic period (19 months from March 1, 2020 to September 30, 2021). RESULTS: Of the 15,124 visits to the network during the 33-month observation period, 10,941 (72%) were during the pre-pandemic period, and 4183 (28%) during the pandemic period. Average monthly visits declined from 782/month (pre-COVID-19 era) to 220/month (COVID-19 pandemic era). Among non-migrants, the top-10 countries of exposure changed after onset of the COVID-19 pandemic; destinations such as Italy and Austria, where COVID-19 exposure peaked in the first months, replaced typical travel destinations in Asia (Thailand, Indonesia, India). There was a small decline in migrant patients reported, with little change in the top countries of exposure (Bolivia, Mali). The three top diagnoses with the largest overall decreases in relative frequency were acute gastroenteritis (-5.3%), rabies post-exposure prophylaxis (-2.8%), and dengue (-2.6%). Apart from COVID-19 (which rose from 0.1% to 12.7%), the three top diagnoses with the largest overall relative frequency increase were schistosomiasis (+4.9%), strongyloidiasis (+2.7%), and latent tuberculosis (+2.4%). CONCLUSIONS: A marked COVID-19 pandemic-induced decline in global travel activities is reflected in reduced travel-related infectious diseases sentinel surveillance reporting.

Role of Recent PCR Tests for Infectious Ocular Diseases: From Laboratory-Based Studies to the Clinic.

Infectious uveitis is a vision-threatening condition that requires prompt clinical diagnosis and proper treatment. However, rapid and proper diagnosis in infectious uveitis remains challenging. Several examination tests, including polymerase chain reaction (PCR) tests, are transitioning from laboratory-based basic research-level tests to bedside clinical tests, and recently tests have changed to where they can be performed right next to clinicians. In this review, we introduce an updated overview of recent studies that are representative of the current trends in clinical microbiological techniques including PCR tests for infectious uveitis.

Metagenomic Sequencing in the ICU for Precision Diagnosis of Critical Infectious Illnesses.

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2023. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2023 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .

Assessment of Urinary Biomarkers for Infectious Diseases Using Lateral Flow Assays: A Comprehensive Overview.

Screening of biomarkers is a powerful approach for providing a holistic view of the disease spectrum and facilitating the diagnosis and prognosis of the state of infectious diseases. Unaffected by the homeostasis mechanism in the human body, urine accommodates systemic changes and reflects the pathophysiological condition of an individual. Easy availability in large volumes and non-invasive sample collection have rendered urine an ideal source of biomarkers for various diseases. Infectious diseases may be communicable, and therefore early diagnosis and treatment are of immense importance. Current diagnostic approaches preclude the timely identification of clinical conditions and also lack portability. Point-of-care (POC) testing solutions have gained attention as alternative diagnostic measures due to their ability to provide rapid and on-site results. Lateral flow assays (LFAs) are the mainstay in POC device development and have attracted interest owing to their potential to provide instantaneous results in resource-limited settings. The discovery and optimization of a definitive biomarker can render POC testing an excellent platform, thus impacting unwarranted antibiotic administration and preventing the spread of infectious diseases. This Review summarizes the importance of urine as an emerging biological fluid in infectious disease research and diagnosis in clinical settings. We review the academic research related to LFAs. Further, we also describe commercial POC devices based on the identification of urinary biomarkers as diagnostic targets for infectious diseases. We also discuss the future use of LFAs in developing more effective POC tests for urinary biomarkers of various infections.

Remote Medical Scent Detection of Cancer and Infectious Diseases With Dogs and Rats: A Systematic Review.

BACKGROUND: Remote medical scent detection of cancer and infectious diseases with dogs and rats has been an increasing field of research these last 20 years. If validated, the possibility of implementing such a technique in the clinic raises many hopes. This systematic review was performed to determine the evidence and performance of such methods and assess their potential relevance in the clinic. METHODS: Pubmed and Web of Science databases were independently searched based on PRISMA standards between 01/01/2000 and 01/05/2021. We included studies aiming at detecting cancers and infectious diseases affecting humans with dogs or rats. We excluded studies using other animals, studies aiming to detect agricultural diseases, diseases affecting animals, and others such as diabetes and neurodegenerative diseases. Only original articles were included. Data about patients' selection, samples, animal characteristics, animal training, testing configurations, and performances were recorded. RESULTS: A total of 62 studies were included. Sensitivity and specificity varied a lot among studies: While some publications report low sensitivities of 0.17 and specificities around 0.29, others achieve rates of 1 sensitivity and specificity. Only 6 studies were evaluated in a double-blind screening-like situation. In general, the risk of performance bias was high in most evaluated studies, and the quality of the evidence found was low. CONCLUSIONS: Medical detection using animals' sense of smell lacks evidence and performances so far to be applied in the clinic. What odors the animals detect is not well understood. Further research should be conducted, focusing on patient selection, samples (choice of materials, standardization), and testing conditions. Interpolations of such results to free running detection (direct contact with humans) should be taken with extreme caution. Considering this synthesis, we discuss the challenges and highlight the excellent odor detection threshold exhibited by animals which represents a potential opportunity to develop an accessible and non-invasive method for disease detection.

Forty Years of Molecular Diagnostics for Infectious Diseases.

Nearly 40 years have elapsed since the invention of the PCR, with its extremely sensitive and specific ability to detect nucleic acids via in vitro enzyme-mediated amplification. In turn, more than 2 years have passed since the onset of the coronavirus disease 2019 (COVID-19) pandemic, during which time molecular diagnostics for infectious diseases have assumed a larger global role than ever before. In this context, we review broadly the progression of molecular techniques in clinical microbiology, to their current prominence. Notably, these methods now entail both the detection and quantification of microbial nucleic acids, along with their sequence-based characterization. Overall, we seek to provide a combined perspective on the techniques themselves, as well as how they have come to shape health care at the intersection of technologic innovation, pathophysiologic knowledge, clinical/laboratory logistics, and even financial/regulatory factors.

The importance of infectious disease specialists consulting on a weekly basis in a Japanese tertiary care hospital: A retrospective observational study.

Limited data are available regarding part-time infectious disease consultations (IDCs) and their importance in tertiary care teaching hospitals in Japan. This is a retrospective review of IDCs from June 2016 to March 2021 and describes IDC services provided by part-time infectious disease specialists once a week for 4 hours, and their impact on the quality of medical care, including antimicrobial stewardship. Data, such as the requesting department, requesting reasons, and final diagnoses, were analyzed. In April 2018, part-time infectious disease specialists launched consultation services and attended an antimicrobial stewardship team conference. Meropenem, tazobactam/piperacillin, and cefepime monthly days of therapy (DOT) were calculated to assess the effect of each intervention; a pre-post analysis was conducted using the Kruskal-Wallis test. Additional quality improvement (QI) projects related to infectious diseases were implemented. There were 237 IDCs during the study period. Consultations were mostly requested by the General Internal Medicine, Emergency Medicine, and Cardiology departments. The most common diagnoses were bone/joint, respiratory, and genitourinary infections. Infectious disease services, even on a part-time basis, achieve good outcomes in patient management, antimicrobial stewardship, and QI projects. DOT/1000 patient-days were reduced for meropenem and cefepime, while it increased for tazobactam/piperacillin. The DOT/1000 patient-days for the 3-antipseudomonal agents significantly decreased during this period. After implementing the QI tetanus vaccination project in the Emergency Room, the number of tetanus toxoid vaccinations per month increased.

Space-time cluster detection techniques for infectious diseases: A systematic review.

BACKGROUND: Public health organizations have increasingly harnessed geospatial technologies for disease surveillance, health services allocation, and targeting place-based health promotion initiatives. METHODS: We conducted a systematic review around the theme of space-time clustering detection techniques for infectious diseases using PubMed, Web of Science, and Scopus. Two reviewers independently determined inclusion and exclusion. RESULTS: Of 2,887 articles identified, 354 studies met inclusion criteria, the majority of which were application papers. Studies of airborne diseases were dominant, followed by vector-borne diseases. Most research used aggregated data instead of point data, and a significant proportion of articles used a repetition of a spatial clustering method, instead of using a "true" space-time detection approach, potentially leading to the detection of false positives. Noticeably, most articles did not make their data available, limiting replicability. CONCLUSION: This review underlines recent trends in the application of space-time clustering methods to the field of infectious disease, with a rapid increase during the COVID-19 pandemic.

Aptasensors for the detection of infectious pathogens: design strategies and point-of-care testing.

The epidemic of infectious diseases caused by contagious pathogens is a life-threatening hazard to the entire human population worldwide. A timely and accurate diagnosis is the critical link in the fight against infectious diseases. Aptamer-based biosensors, the so-called aptasensors, employ nucleic acid aptamers as bio-receptors for the recognition of target pathogens of interest. This review focuses on the design strategies as well as state-of-the-art technologies of aptasensor-based diagnostics for infectious pathogens (mainly bacteria and viruses), covering the utilization of three major signal transducers, the employment of aptamers as recognition moieties, the construction of versatile biosensing platforms (mostly micro and nanomaterial-based), innovated reporting mechanisms, and signal enhancement approaches. Advanced point-of-care testing (POCT) for infectious disease diagnostics are also discussed highlighting some representative ready-to-use devices to address the urgent needs of currently prevalent coronavirus disease 2019 (COVID-19). Pressing issues in aptamer-based technology and some future perspectives of aptasensors are provided for the implementation of aptasensor-based diagnostics into practical application.

CRISPR-Cas systems for diagnosing infectious diseases.

Infectious diseases are a global health problem affecting billions of people. Developing rapid and sensitive diagnostic tools is key for successful patient management and curbing disease spread. Currently available diagnostics are very specific and sensitive but time-consuming and require expensive laboratory settings and well-trained personnel; thus, they are not available in resource-limited areas, for the purposes of large-scale screenings and in case of outbreaks and epidemics. Developing new, rapid, and affordable point-of-care diagnostic assays is urgently needed. This review focuses on CRISPR-based technologies and their perspectives to become platforms for point-of-care nucleic acid detection methods and as deployable diagnostic platforms that could help to identify and curb outbreaks and emerging epidemics. We describe the mechanisms and function of different classes and types of CRISPR-Cas systems, including pros and cons for developing molecular diagnostic tests and applications of each type to detect a wide range of infectious agents. Many Cas proteins (Cas3, Cas9, Cas12, Cas13, Cas14 etc.) have been leveraged to create highly accurate and sensitive diagnostic tools combined with technologies of signal amplification and fluorescent, potentiometric, colorimetric, lateral flow assay detection and other. In particular, the most advanced platforms -- SHERLOCK/v2, DETECTR, CARMEN or CRISPR-Chip -- enable detection of attomolar amounts of pathogenic nucleic acids with specificity comparable to that of PCR but with minimal technical settings. Further developing CRISPR-based diagnostic tools promises to dramatically transform molecular diagnostics, making them easily affordable and accessible virtually anywhere in the world. The burden of socially significant diseases, frequent outbreaks, recent epidemics (MERS, SARS and the ongoing COVID-19) and outbreaks of zoonotic viruses (African Swine Fever Virus etc.) urgently need the developing and distribution of express-diagnostic tools. Recently devised CRISPR-technologies represent the unprecedented opportunity to reshape epidemiological surveillance and molecular diagnostics.

Virtual article collection on infectious diseases.

Specifically for COVID-19, we have had several recent articles on SARS-CoV-2. Sohail and Nutini reported on models working to predict the incubation period for SARS-CoV-2 and disease progression. Güler et al. wrote a review of the biophysical and biochemical properties of SARS-CoV-2 which highlighted how the virus's molecular structure allows it to interact and infect cells. These structures are also potential targets for diagnostic and treatment strategies. Lalitha Guruprasad's review on how the various human coronavirus spike proteins interact with human cell proteins and carbohydrate receptors provides further insight on coronavirus-cell interactions as well, and reviews successfully repurposed drugs to combat coronavirus-based diseases.

Clinical microbiology in detection and identification of emerging microbial pathogens: past, present and future.

Clinical microbiology has possessed a marvellous past, an important present and a bright future. Western medicine modernization started with the discovery of bacterial pathogens, and from then, clinical bacteriology became a cornerstone of diagnostics. Today, clinical microbiology uses standard techniques including Gram stain morphology, in vitro culture, antigen and antibody assays, and molecular biology both to establish a diagnosis and monitor the progression of microbial infections. Clinical microbiology has played a critical role in pathogen detection and characterization for emerging infectious diseases as evidenced by the ongoing COVID-19 pandemic. Revolutionary changes are on the way in clinical microbiology with the application of "-omic" techniques, including transcriptomics and metabolomics, and optimization of clinical practice configurations to improve outcomes of patients with infectious diseases.

Development of an IoT-integrated multiplexed digital PCR system for quantitative detection of infectious diseases.

For rapid detection of the COVID-19 infection, the digital polymerase chain reaction (dPCR) with higher sensitivity and specificity has been presented as a promising method of point-of-care testing (POCT). Unlike the conventional real-time PCR (qPCR), the dPCR system allows absolute quantification of the target DNA without a calibration curve. Although a number of dPCR systems have previously been reported, most of these previous assays lack multiplexing capabilities. As different variants of COVID-19 have rapidly emerged, there is an urgent need for highly specific multiplexed detection systems. Additionally, the advances in the Internet of Things (IoT) technology have enabled the onsite detection of infectious diseases. Here, we present an IoT-integrated multiplexed dPCR (IM-dPCR) system involving sample compartmentalization, DNA amplification, fluorescence imaging, and quantitative analysis. This IM-dPCR system comprises three modules: a plasmonic heating-based thermal cycler, a multi-color fluorescence imaging set-up, and a firmware control module. Combined with a custom-developed smartphone application built on an IoT platform, the IM-dPCR system enabled automatic processing, data collection, and cloud storage. Using a self-priming microfluidic chip, 9 RNA groups (e.g., H1N1, H3N2, IFZ B, DENV2, DENV3, DENV4, OC43, 229E, and NL63) associated with three infectious diseases (e.g., influenza, dengue, and human coronaviruses) were analyzed with higher linearity (>98%) and sensitivity (1 copy per µL). The IM-dPCR system exhibited comparable analytical accuracy to commercial qPCR platforms. Therefore, this IM-dPCR system plays a crucial role in the onsite detection of infectious diseases.

Modern Machine-Learning Predictive Models for Diagnosing Infectious Diseases.

Controlling infectious diseases is a major health priority because they can spread and infect humans, thus evolving into epidemics or pandemics. Therefore, early detection of infectious diseases is a significant need, and many researchers have developed models to diagnose them in the early stages. This paper reviewed research articles for recent machine-learning (ML) algorithms applied to infectious disease diagnosis. We searched the Web of Science, ScienceDirect, PubMed, Springer, and IEEE databases from 2015 to 2022, identified the pros and cons of the reviewed ML models, and discussed the possible recommendations to advance the studies in this field. We found that most of the articles used small datasets, and few of them used real-time data. Our results demonstrated that a suitable ML technique depends on the nature of the dataset and the desired goal. Moreover, heterogeneous data could ensure the model's generalization, while big data, many features, and a hybrid model will increase the resulting performance. Furthermore, using other techniques such as deep learning and NLP to extract vast features from unstructured data is a powerful approach to enhancing the performance of ML diagnostic models.

The Italian Mandatory Notification System: An Important Public Health Tool For Continuous Monitoring Of Infectious Diseases.

Infectious diseases still register significant morbidity and mortality worldwide. Surveillance through a mandatory notification system allows the continuous analysis of the situation even at a local level and its importance has been highlighted by the recent COVID-19 pandemic. This paper aimed to outline the importance of the mandatory notification system as a Public Health tool in the continuous monitoring of infectious diseases. To this aim, we carried out a cross-sectional study examining the notifications reported in the Italian territory of Messina, Sicily, in the period 2001-2020. The institutional websites were examined and the notification data were used to obtain the incidences. Overall, a significant reduction of the incidence notification trend was observed. Chickenpox was by far the most notified infectious disease, followed by scabies, pediculosis, and brucellosis. Outbreaks of brucellosis, measles and hepatitis A occurred. All the diseases decreased over time, except syphilis, for which a significant increase was observed. Surveillance of infectious diseases through a mandatory notification system remains a bulwark of public health despite underreporting. Our study reflects the situation of a typical high-income area, although some unexpected criticisms are highlighted. Continuous information about correct behaviors through education campaigns are crucial in order to improve the situation. Keywords: mandatory notifications, infectious diseases, surveillance, public health Corresponding author: Alessio Facciolà, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Italy. Email: afacciola@unime.it.