Diagnosis Of Infectious Diseases Research Articles

Metal Nanoparticle-Based Biosensors for the Early Diagnosis of Infectious Diseases Caused by ESKAPE Pathogens in the Fight against the Antimicrobial-Resistance Crisis.

The species included in the ESKAPE group (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and the genus Enterobacter) have a high capacity to develop antimicrobial resistance (AMR), a health problem that is already among the leading causes of death and could kill 10 million people a year by 2050. The generation of new potentially therapeutic molecules has been insufficient to combat the AMR "crisis", and the World Health Organization (WHO) has stated that it will seek to promote the development of rapid diagnostic strategies. The physicochemical properties of metallic nanoparticles (MNPs) have made it possible to design biosensors capable of identifying low concentrations of ESKAPE bacteria in the short term; other systems identify antimicrobial susceptibility, and some have been designed with dual activity in situ (bacterial detection and antimicrobial activity), which suggests that, in the near future, multifunctional biosensors could exist based on MNPs capable of quickly identifying bacterial pathogens in clinical niches might become commercially available. This review focuses on the use of MNP-based systems for the rapid and accurate identification of clinically important bacterial pathogens, exhibiting the necessity for exhaustive research to achieve these objectives. This review focuses on the use of metal nanoparticle-based systems for the rapid and accurate identification of clinically important bacterial pathogens.

Photodynamic Inactivation as a Promising Method of Combating Resistant Strains of Staphylococci

Relevance. The development of antimicrobial drugs and alternative methods, technologies and means of prevention, diagnosis and treatment of human infectious diseases caused by antibiotic-resistant microorganisms is one of the priorities of ensuring the biological safety of the country. Aims. To evaluate the bactericidal activity of tetrapyrrole macroheterocycles (porphyrins) at different light irradiation durations in relation to staphylococci, in vitro. Materials and methods. Studied strains of microorganisms: museum strains of microorganisms – S. aureus ATCC 29213, S. epidermidis ATCC 14990 and antibiotic-resistant strains of bacteria of the genus Staphylococcus (n=18) isolated from clinical biomaterial and from environmental objects in a medical organization. The studied chemical compounds are three different compounds of water-soluble asymmetrically substituted porphyrins containing heterocyclic fragments on the periphery of the porphyrin cycle (residues of benzoxazole, N-methylbenzimidazole and benzothiazole). Results. The activity of all three porphyrin compounds in relation to museum strains of staphylococcus and 77.8% of clinical antibiotic-resistant strains (n=14; 95% CI 20.1-97.5) turned out to be maximal (complete lysis) after 10 minutes of irradiation. Conclusions. The tested tetrapyrrole macroheterocycles (porphyrins) exhibit bactericidal activity against museum and clinical strains of staphylococcus, with different levels of antibiotic resistance, which determines Keywords: antibiotic resistance, water-soluble porphyrin, photodynamic inactivation, photosensitizer, photochemistry, staphylococci No conflict of interest to declare.

A Critical Review in Infectious Disease and Mathematical Modelling

Infectious diseases control and prevention relies on a thorough understanding of the factors determining transmission. The transmission dynamics of infectious diseases is susceptible to changes governed by several factors, whose recognition is critical for the rational development of strategies for prevention and control, as well as for developing health policies. This article summarizes the fundamental principles of infectious disease transmission and compartmental models. Basic principles of infectious disease diagnosis, reasons for formulating the infectious diseases and historical facts on epidemics are also reviewed.

Clinical usefulness of metagenomic next-generation sequencing for Talaromyces marneffei diagnosis in China: a retrospective study.

Metagenomic next-generation sequencing (mNGS) has been widely used in the diagnosis of infectious diseases. However, studies on Talaromyces marneffei detection using mNGS remain scarce. Therefore, this study aimed to explore the diagnostic performance of mNGS in T. marneffei. Between March 2021 and June 2023, patients who were discharged with a final diagnosis of talaromycosis, or confirmed T. marneffei infection by mNGS, culture or pathological examination were included in the study. Culture and mNGS were performed simultaneously for all patients. Clinical data were retrieved for analysis. A total of 78 patients were enrolled, with 40 in the talaromycosis group and 38 in the suspected-talaromycosis group. In the talaromycosis group, mNGS showed a higher positivity rate(40/40, 100.0%) compared to culture(34/40, 85.0%)(P = 0.111). All patients in the suspected-talaromycosis group tested negative via culture, while mNGS yielded positive results. The T. marneffei reads in the talaromycosis group were significantly higher than in the suspected-talaromycosis group (4399 vs. 28, P < 0.001). In the suspected-talaromycosis group, of the four patients with low reads who did not receive antifungal therapy, one died and one lung lesion progressed; most patients(31/34, 91.2%) recovered after receiving appropriate antifungal therapy. mNGS proves to be a rapid and highly sensitive method for detecting T. marneffei. Higher reads of T. marneffei correspond to a higher likelihood of infection. However, cases with low reads necessitate a comprehensive approach, integrating clinical manifestations, laboratory tests, and imaging examinations to confirm T. marneffei infection.

Infections in patients with mantle cell lymphoma.

Advancements in treatments have significantly improved the prognosis for mantle cell lymphoma (MCL), and there is a growing population of survivors with an increased susceptibility to infections. We assessed the incidence of infections by clinical characteristics and treatment both before and after MCL diagnosis in Sweden. Patients with a diagnosis of MCL ≥ 18 years between 2007 and 2019 were included, along with up to 10 matched comparators. Infectious disease diagnosis and anti-infective drug dispensation were identified by the National Patient and the Prescribed Drug Registers, respectively. Patients and comparators were followed from the diagnosis/matching date until death, emigration, or June 30, 2020. Overall, 1559 patients and 15,571 comparators were followed for a median duration of 2.9 and 5 years, respectively. The infection rate among patients was twofold higher, RRadj = 2.14 (2.01-2.27), contrasted to the comparator group. There was a notable rise in infection rates already 4 years before MCL diagnosis, which reached a fourfold increase in the first year after diagnosis and persisted significantly increased for an additional 8 years. Among patients, 69% (n = 1080) experienced at least one infection during the first year of follow-up. Influenza, pneumonia, other bacterial infections, urinary tract infections, and acute upper respiratory infections were the most frequent. Notably, MCL remained to be the primary leading cause of death among patients (57%, n = 467/817). Infections as the main cause of death were rare (2.6%, n = 21). Our study highlights the importance of thoroughly assessing infectious morbidity when appraising new treatments. Further investigations are warranted to explore strategies for reducing infectious disease burden.

Methodological evaluation of systematic reviews based on the use of artificial intelligence systems in chest radiography

IntroductionIn recent years, systems that use artificial intelligence (AI) in medical imaging have been developed, such as the interpretation of chest X-ray to rule out pathology. This has produced an increase in systematic reviews (SR) published on this topic. This article aims to evaluate the methodological quality of SRs that use AI for the diagnosis of thoracic pathology by simple chest X-ray. Material and methodsSRs evaluating the use of AI systems for the automatic reading of chest X-ray were selected. Searches were conducted (from inception to May 2022): PubMed, EMBASE, and the Cochrane Database of Systematic Reviews. Two investigators selected the reviews. From each SR, general, methodological and transparency characteristics were extracted. The PRISMA statement for diagnostic tests (PRISMA-DTA) and AMSTAR-2 were used. A narrative synthesis of the evidence was performed. Protocol registry: Open Science Framework: https://osf.io/4b6u2/. ResultsAfter applying the inclusion and exclusion criteria, 7 SRs were selected (mean of 36 included studies per review). All the included SRs evaluated “deep learning” systems in which chest X-ray was used for the diagnosis of infectious diseases. Only 2 (29%) SRs indicated the existence of a review protocol. None of the SRs specified the design of the included studies or provided a list of excluded studies with their justification. Six (86%) SRs mentioned the use of PRISMA or one of its extensions. The risk of bias assessment was performed in 4 (57%) SRs. One (14%) SR included studies with some validation of AI techniques. Five (71%) SRs presented results in favour of the diagnostic capacity of the intervention. All SRs were rated "critically low" following AMSTAR-2 criteria. ConclusionsThe methodological quality of SRs that use AI systems in chest radiography can be improved. The lack of compliance in some items of the tools used means that the SRs published in this field must be interpreted with caution.

Prognostic risk stratification using C-reactive protein, albumin, and associated inflammatory biomarkers in patients with advanced cancer in palliative care

PurposeTo evaluate the prognostic value of C-reactive protein (CRP), albumin, CRP/albumin ratio (CAR), and modified Glasgow Prognostic Score (mGPS) at different thresholds in patients with advanced cancer in palliative care. MethodsProspective cohort study with patients evaluated at a palliative care unit in Brazil between July 2016 and March 2020. We included patients ≥ 20 years old, both sexes, able to provide the necessary information or accompanied by someone able to do so, and Karnofsky Performance Status ≥ 30 %. The exclusion criteria were the absence of laboratory data and previous diagnosis of autoimmune and infectious diseases. The thresholds analyzed were: CRP < 5 vs. 5-10 vs. > 10 mg/L, albumin < 2.4 vs. 2.4-2.9 vs. 3.0-3.5 vs. > 3.5 g/dL; CAR <1.2 vs. 1.2–2.0 vs. > 2.0, and mGPS equal to 0 vs. 1 vs. 2. Kaplan-Meier curves and Cox regression models (with hazard ratios [HR] and 95% confidence interval [CI]) were used to evaluate prognostic value, and the concordance statistic (C-statistic) was used to evaluate the predictive accuracy of these thresholds to predict death within 90 days. ResultsA total of 1,877 patients were included. Median overall survival was 51 (19;124) days and decreased in line with the deterioration of the inflammatory biomarkers. According to the Cox regression models, HR increased as the thresholds worsened (CRP: 1.74 [95% CI, 1.50-2.02] to 2.30 [95% CI, 2.00-2.64]; albumin: 1.77 [95% CI, 1.52-2.07] to 2.60 [95% CI, 2.15-3.14]; CAR: 1.47 [95% CI, 1.21-1.77] to 2.35 [95% CI, 2.05-2.69]; mGPS: 1.78 [95% CI, 1.40-2.23] to 1.89 [95% CI, 1.65-2.15]). All the inflammatory biomarkers evaluated showed discriminatory accuracy for predicting death (C-statistic >0.70), with CAR as the best parameter (C-statistic: 0.80). ConclusionOur results suggest that CRP, albumin, CAR, and mGPS can be used as clinically meaningful biomarkers to stratify patients with advanced cancer in palliative care according to the severity of these indicators.

Functional probes for the diagnosis and treatment of infectious diseases

AbstractInfectious diseases present significant challenges to global health, thereby extensively affecting both human society and the economy. In recent years, functional probes have demonstrated remarkable potential as crucial biomedical media for the research and treatment of infectious diseases. Their applications in the realm of infectious diseases include pathogen detection, exploration of biological mechanisms, and development of anti‐infective drugs. This review provides a concise introduction to the severity, classification, and pathogenesis of infectious diseases. Subsequently, we examined the distinctiveness and design strategies of functional probes for diagnosing and treating infectious diseases, shedding light on their design rationale using typical examples. We discuss the current status and challenges associated with the clinical implementation of functional probes. Furthermore, we explored the prospects of using these probes for the diagnosis and treatment of infectious diseases. This review aims to offer novel insights into the design of diagnostic probes for infectious diseases and broaden their applications in disease treatment.

Bacterial DNA enrichment for low-inoculum fracture-related infection diagnostic using high-throughput sequencing

One of the main barriers for the implementation of metagenomic sequencing in routine diagnosis of infectious diseases is the presence of host DNA. While several enrichment methods are likely to overcome this issue, their effectiveness for specimens such as bone in the case of chronic infections remains to be determined. We compared the relevance of two methods for bacterial DNA enrichment when compared to a reference protocol during pretreatment of bone samples from fracture-related infections before HTS by both Illumina Miseq and Oxford Nanopore Technology (ONT). The bacterial/human DNA ratio was higher for either protocols than the reference technique (p = 0.00012), without any significant difference between them. HTS sensitivity over culture ranged from 21.7 % to 85 %. The ability of the studied protocols to improve the bacterial/human DNA ratio depends on the sequencing technique employed. In this context, there is room for improvement in enhancing the sensitivity of HTS for diagnostic purpose.

Programmable DNA Nanomachine Integrated with Electrochemically Controlled Atom Transfer Radical Polymerization for Antibody Detection at Picomolar Level.

The quantitative detection of antibodies is crucial for the diagnosis of infectious and autoimmune diseases, while the traditional methods experience high background signal noise and restricted signal gain. In this work, we have developed a highly efficient electrochemical biosensor by constructing a programmable DNA nanomachine integrated with electrochemically controlled atom transfer radical polymerization (eATRP). The sensor works by binding the target antidigoxin antibody (anti-Dig) to the epitope of the recognization probe, which then initiates the cascaded strand displacement reaction on a magnetic bead, leading to the capture of cupric oxide (CuO) nanoparticles through magnetic separation. After CuO was dissolved, the eATRP initiators were attached to the electrode based on the CuΙ-catalyzed azide-alkyne cycloaddition. The subsequent eATRP reaction results in the formation of long electroactive polymers (poly-FcMMA), producing an amplified current response for sensitive detection of anti-Dig. This method achieved a detection limit at clinically relevant picomolar concentration in human serum, offering a sensitive, convenient, and cost-effective tool for detecting various biomarkers in a wide range of applications.

A gamepad-like nucleic acid testing device for rapid detection of SARS-CoV-2 via visible nested recombinase polymerase amplification

Nucleic acid tests are essential for the accurate diagnosis and control of infectious diseases. However, current assays are not easily scalable for a large population, due to the requirement of laboratory settings or special equipment. Here, we developed an integrated box for instant nucleic acid screening which fully integrates nucleic acid release, amplification, and results visualization for self-service standalone test. Importantly, the operation of the box runs on a novel gamepad-like interface, which allows deployment of the box in home settings and operation by users without any prior professional training. The performance of the box is empowered by an RNA extraction-free sample inactivation process and nested recombinase polymerase amplification chemistry and exhibits sensitivity comparable to reverse transcription-quantitative polymerase chain reaction with high specificity for severe acute respiratory syndrome coronavirus 2 RNA in a reaction time of 30 minutes directly from fresh swab sample to results. These innovations make the box a novel platform for a convenient, accurate, and deployable point-of-care testing scheme.

Point-of-care testing of Pseudomonas aeruginosa using PCN-222(Pt) prepared by nanoconfinement-guided protocol to catalyze gas generation reaction

BackgroundPathogenic bacteria are keeping threatening global public health since they can cause many infectious diseases. The traditional microorganism identification and molecular diagnostic techniques are insufficiently sensitive, time-consuming, or expensive. Thus it is of great interest to establish pressure signal-based sensing platforms for point-of-care testing of pathogenic bacteria to achieve timely diagnosis of infectious diseases. Rational design and synthesis of nano-sized probes with high peroxidase-mimicking activity have been a long-term cherished goal for improving the sensitivity of pressure signal-based sensing methods. ResultsGuided by nanoconfinement effect, PCN-222(Pt) was prepared by confining Pt clusters within the channels of a zirconium porphyrin MOFs material termed as PCN-222. In comparison to regular platinum nanoparticles, palladium@platinum core-shell nanodendrites, and platinum-coated gold nanoparticles, the prepared PCN-222(Pt) displayed superior peroxidase-mimicking activity with outstanding efficiency for catalyzing the decay of H2O2 to produce O2. Thus it was used as a pressure signal probe to establish a sensitive method on a hydrogel pellets platform for analyzing Pseudomonas aeruginosa (P. aeruginosa), for which polymyxin B and a phage termed as JZ1 were used as recognition agents for the target pathogen. P. aeruginosa was quantified with a handheld pressure meter within a broad range of 2.2 × 102–2.2 × 107 cfu mL−1. This method was used to quantify P. aeruginosa in various biological and food samples with acceptable accuracy and reliability. SignificanceThe proposed nanoconfinement-guided protocol provides a novel approach for rational design and preparation of nano-sized probes with high peroxidase-mimicking activity for catalyzing gas-generation reaction. Thus this study opens an avenue for establishment of sensitive pressure signal-based sensing methods for pathogenic bacteria, which shows broad application prospects in medical diagnosis of infectious diseases.

Integrated High-Throughput Centrifugal Microfluidic Chip Device for Pathogen Detection On-Site.

An integrated and high-throughput device for pathogen detection is crucial in point-of-care testing (POCT), especially for early diagnosis of infectious diseases and preventing the spread of infection. We developed an on-site testing platform that utilizes a centrifugal microfluidic chip and automated device to achieve high-throughput detection. The low-power (<32 W), portable (220 mm × 220 mm × 170 mm, 4 kg) device can complete bacterial lysis, nucleic acid extraction and purification, loop-mediated isothermal amplification (LAMP) reaction, and real-time fluorescence detection. Magnetic beads for nucleic acid adsorption can be mixed by applying electromagnetic fields and centrifugal forces, and the efficiency of nucleic acid extraction is improved by 60% compared to the no-mixing group. The automated nucleic acid extraction process achieves equivalent nucleic acid extraction efficiency in only 40% of the time consumed using the kit protocol. By designing the valve system and disc layout, the maximum speed required for the centrifugal microfluidic chip is reduced to 1500 rpm, greatly reducing the equipment power consumption and size. In detecting E. coli, our platform achieves a limit of detection (LOD) of 102 CFU/mL in 60 min. In summary, our active centrifugal microfluidic platform provides a solution for the integration of complex biological assays on turntables, with great potential in the application of point-of-care diagnosis.

Application of a Machine Learning-Based Classification Approach for Developing Host Protein Diagnostic Models for Infectious Disease

In recent years, infectious disease diagnosis has increasingly turned to host-centered approaches as a complement to pathogen-directed ones. The former, however, typically requires the interpretation of complex multiple biomarker datasets to arrive at an informative diagnostic outcome. This report describes a machine learning (ML)-based classification workflow that is intended as a template for researchers seeking to apply ML approaches for developing host-based infectious disease biomarker classifiers. As an example, we built a classification model that could accurately distinguish between three disease etiology classes: bacterial, viral, and normal in human sera using host protein biomarkers of known diagnostic utility. After collecting protein data from known disease samples, we trained a series of increasingly complex Auto-ML models until arriving at an optimized classifier that could differentiate viral, bacterial, and non-disease samples. Even when limited to a relatively small training set size, the model had robust diagnostic characteristics and performed well when faced with a blinded sample set. We present here a flexible approach for applying an Auto-ML-based workflow for the identification of host biomarker classifiers with diagnostic utility for infectious disease, and which can readily be adapted for multiple biomarker classes and disease states.

Metagenomic next-generation sequencing reveals co-infection with Legionella pneumophila and Fusobacterium necrophorum in a patient with severe pneumonia: a case report

BackgroundLegionella pneumonia is one of the most severe types of atypical pneumonia, impairing multiple organ systems, posing a threat to life. Diagnosing Legionella pneumonia is challenging due to difficulties in culturing the bacteria and limitations in immunoassay sensitivity and specificity.Case presentationThis paper reports a rare case of sepsis caused by combined infection with Legionella pneumophila and Fusobacterium necrophorum, leading to respiratory failure, acute kidney injury, acute liver injury, myocardial damage, and electrolyte disorders. In addition, we systematically reviewed literature on patients with combined Legionella infections, analyzing their clinical features, laboratory results and diagnosis.ConclusionsFor pathogens that require prolonged incubation periods and are less sensitive to conventional culturing methods, metagenomic next-generation sequencing (mNGS) can be a powerful supplement to pathogen screening and plays a significant role in the auxiliary diagnosis of complex infectious diseases.

A Clinical Bacterial Dataset for Deep Learning in Microbiological Rapid On-Site Evaluation

Microbiological Rapid On-Site Evaluation (M-ROSE) is based on smear staining and microscopic observation, providing critical references for the diagnosis and treatment of pulmonary infectious disease. Automatic identification of pathogens is the key to improving the quality and speed of M-ROSE. Recent advancements in deep learning have yielded numerous identification algorithms and datasets. However, most studies focus on artificially cultured bacteria and lack clinical data and algorithms. Therefore, we collected Gram-stained bacteria images from lower respiratory tract specimens of patients with lung infections in Chinese PLA General Hospital obtained by M-ROSE from 2018 to 2022 and desensitized images to produce 1705 images (4,912 × 3,684 pixels). A total of 4,833 cocci and 6,991 bacilli were manually labelled and differentiated into negative and positive. In addition, we applied the detection and segmentation networks for benchmark testing. Data and benchmark algorithms we provided that may benefit the study of automated bacterial identification in clinical specimens.

Surpassing the natural limits of serological diagnostic tests

Serological tests have an important and irreplaceable role in the diagnosis of infectious diseases, both for individual patients and society. They indirectly identify the causative pathogen through the capture of antibodies, which contrasts with the direct detection by antigen and molecular biology tests that are also limited to active infections. Within point-of-care platforms, serodiagnostic assays can support immediate decisions in patient care and contain the spread of disease as they do not require highly trained personnel or dedicated infrastructure. By employing serodiagnosis, health officials can proactively respond and eliminate emerging health risks. Larger sample numbers can be screened in other formats for surveillance as well as securing donated blood supplies. Furthermore, an assay can be designed to detect any immunoglobulin from IgM to IgG and its subclasses, to IgA and IgE. However, most serological assays employ natural proteins as the defining antibody-capturing reagent, which compromises their performance by limiting the two critical parameters of a serodiagnostic test: specificity and sensitivity. To surpass this natural limitation, we have repurposed the β-barrel of fluorescent proteins to receive epitope sequences that dependably produce high-performing designer immunological reagents. Consequently, serodiagnosis can be conducted more accurately at a lower cost.

The clinical application and laboratory management of molecular genetic diagnosis in children's hospital

AbstractBackgroundMolecular diagnostic technology is the foundation of precision medicine, which has the advantages of good specificity, high sensitivity, strong targeting, rapiddiagnosis, etc. It has a wide range of applications in the field of pediatrics. However, molecular diagnostic technology is characterized by complicated experimental operation, high difficulty in data analysis and interpretation, in consistent standards among laboratories, and difficult standardization of technical processes. Enhancing the application value of molecular diagnostic technology in pediatrics and promoting the high‐quality development of the discipline requires careful consideration by relevant management and professionals.MethodsThis study firstly outlines the development history of molecular diagnostic technology. Then, it analyzes the application of molecular diagnostic technology in the field of pediatrics. Finally, it explores the countermeasures for the management of molecular diagnostic laboratories.ResultsThis study highlights the importance of molecular diagnostic technology in providing information and decision‐making basis for disease prevention, prediction,diagnosis, treatment and regression. It has a wide range of applications in the molecular diagnosis of pediatric hereditary diseases, malignant tumors and infectious diseases. In addition, the countermeasures for the management of molecular diagnostic laboratories are proposed from the five aspects of laboratory, personnel team construction, standardized management,multidisciplinary cross‐discipline, research and translation, safety managementand ethical supervision, and management upgrading and modernization.ConclusionsMolecular diagnostic technology, as the basis of precision medicine, has become one of the important frontier fields in the development of contemporary pediatric medicine. Enhanced laboratory capacity in molecular diagnostic techniques can improve outcomes in the prevention, prediction, diagnosis, treatment, prognosis and research of pediatricdiseases, and lay the groundwork for child healthcare.

Diagnostic and Prognostic Ability of Pancreatic Stone Protein: A Scoping Review.

Pancreatic stone protein (PSP) is an acute-phase reactant mainly produced in response to stress. Its diagnostic and prognostic accuracy for several types of infection has been studied in several clinical settings. The aim of the current review was to assess all studies examining a possible connection of pancreatic stone protein levels with the severity and possible complications of patients diagnosed with infection. We performed a systematic search in PubMed, Scopus, the Cochrane Library and Clinicaltrials.gov to identify original clinical studies assessing the role of pancreatic stone protein in the diagnosis and prognosis of infectious diseases. We identified 22 eligible studies. Ten of them provided diagnostic aspects, ten studies provided prognostic aspects, and another two studies provided both diagnostic and prognostic information. The majority of the studies were performed in an intensive care unit (ICU) setting, five studies were on patients who visited the emergency department (ED), and three studies were on burn-injury patients. According to the literature, pancreatic stone protein has been utilized in patients with different sites of infection, including pneumonia, soft tissue infections, intra-abdominal infections, urinary tract infections, and sepsis. In conclusion, PSP appears to be a useful point-of-care biomarker for the ED and ICU due to its ability to recognize bacterial infections and sepsis early. Further studies are required to examine PSP's kinetics and utility in specific populations and conditions.

Optimizing Early Diagnosis of Infectious Diseases in Migrant and Refugee Children: An Overview of Best Practices and Strategies.

Optimizing Early Diagnosis of Infectious Diseases in Migrant and Refugee Children: An Overview of Best Practices and Strategies.