Method For Influenza Research Articles

How to Determine the Early Warning Threshold Value of Meteorological Factors on Influenza through Big Data Analysis and Machine Learning.

Infectious diseases are a major health challenge for the worldwide population. Since their rapid spread can cause great distress to the real world, in addition to taking appropriate measures to curb the spread of infectious diseases in the event of an outbreak, proper prediction and early warning before the outbreak of the threat of infectious diseases can provide an important basis for early and reasonable response by the government health sector, reduce morbidity and mortality, and greatly reduce national losses. However, if only traditional medical data is involved, it may be too late or too difficult to implement prediction and early warning of an infectious outbreak. Recently, medical big data has become a research hotspot and has played an increasingly important role in public health, precision medicine, and disease prediction. In this paper, we focus on exploring a prediction and early warning method for influenza with the help of medical big data. It is well known that meteorological conditions have an influence on influenza outbreaks. So, we try to find a way to determine the early warning threshold value of influenza outbreaks through big data analysis concerning meteorological factors. Results show that, based on analysis of meteorological conditions combined with influenza outbreak history data, the early warning threshold of influenza outbreaks could be established with reasonable high accuracy.

Contamination-controlled high-throughput whole genome sequencing for influenza A viruses using the MiSeq sequencer.

Accurate full-length genomic sequences are important for viral phylogenetic studies. We developed a targeted high-throughput whole genome sequencing (HT-WGS) method for influenza A viruses, which utilized an enzymatic cleavage-based approach, the Nextera XT DNA library preparation kit, for library preparation. The entire library preparation workflow was adapted for the Sentosa SX101, a liquid handling platform, to automate this labor-intensive step. As the enzymatic cleavage-based approach generates low coverage reads at both ends of the cleaved products, we corrected this loss of sequencing coverage at the termini by introducing modified primers during the targeted amplification step to generate full-length influenza A sequences with even coverage across the whole genome. Another challenge of targeted HTS is the risk of specimen-to-specimen cross-contamination during the library preparation step that results in the calling of false-positive minority variants. We included an in-run, negative system control to capture contamination reads that may be generated during the liquid handling procedures. The upper limits of 99.99% prediction intervals of the contamination rate were adopted as cut-off values of contamination reads. Here, 148 influenza A/H3N2 samples were sequenced using the HTS protocol and were compared against a Sanger-based sequencing method. Our data showed that the rate of specimen-to-specimen cross-contamination was highly significant in HTS.

A Practical Method for Surveillance of Novel H1N1 Influenza Using Automated Hospital Data

We report a surveillance method for influenza that is based on automated hospital laboratory and pharmacy data. During the 2009 H1N1 influenza pandemic, this method was objective, easy to perform, and utilized readily available automated hospital data. This surveillance method produced results that correlated strongly with influenza-like illness surveillance data.

Rapid influenza A detection and quantitation in birds using a one-step real-time reverse transcriptase PCR and High Resolution Melting

Efficient influenza A viral surveillance of wild and domestic birds requires rapid viral detection and quantitation of high and low quality samples. Current influenza A qPCR-based detection protocols specified by CDC, OIE and USDA utilize fluorogenic hydrolysis probe based real-time reverse transcription PCR (RRT-PCR) assays for detection and quantitation. The sequence diversity of this virus, even in the conserved matrix gene M1, makes primer and probe designs challenging. In this report it was determined that false RRT-PCR positives are possible with this method. This is particularly problematic when surveying non-cultured or inactivated avian tracheal and cloacal mucosal samples with low concentrations of virus and large proportions of background nucleic acids. This report presents a modification of a one-step RRT-PCR detection method for influenza A using SYBR green intercalating dye-based target amplification detection. High Resolution Melting (HRM), amplicon size quantitation and sequence verification is used to screen for non-target amplification (false positives). The resulting protocol has the sensitivity of hydrolysis probe methods, allows for flexible primer design and verification of target amplification, and provides high confidence in positive results. A multiplex subtype detection method using the RRT-PCR HRM assay is also demonstrated. Overall, this method is both time and cost effective while providing an extra measure of confidence in surveillance results through the implementation of target verification.

Rapid Method for Detection of Influenza A and B Virus Antigens by Use of a Two-Photon Excitation Assay Technique and Dry-Chemistry Reagents

New separation-free assay methods for the rapid detection of influenza A and B virus antigens are presented. The methods employ dry-chemistry reagents and the recently developed two-photon excitation (TPX) fluorescence detection technology. According to the assay scheme, virus antigens are sandwiched by capture antibody onto polymer microspheres and fluorescently labeled antibody conjugate. Consequently, fluorescent immunocomplexes are formed on the surface of microspheres in proportion to the concentration of the analyte in the sample. The fluorescence signal from individual microspheres is measured, separation free, by means of two-photon excited fluorescence detection. In order to demonstrate the applicability of the new assay technique for virus antigen detection, methods for influenza A and B viruses were constructed. The assay method for influenza A virus applied a molecular fluorescent label, whereas the method for influenza B virus required a nanoparticle fluorescent reporter to reach sufficient clinical sensitivity. The new methods utilize a dry-chemistry approach, where all assay-specific reagents are dispensed into assay wells already in the manufacturing process of the test kits. The performance of the assay methods was tested with nasopharyngeal specimens using a time-resolved fluoroimmunoassay as a reference method. The results suggest that the new technique enables the rapid detection of influenza virus antigens with sensitivity and specificity comparable to that of the reference method. The dose-response curves showed linear responses with slopes equal to unity and dynamic assay ranges of 3 orders of magnitude. Applicability of the novel TPX technique for rapid multianalyte testing of respiratory infections is discussed.