Comparison of real-time RT-PCR, shell vial culture, and conventional cell culture for the detection of the pandemic influenza A (H1N1) in hospitalized patients

Border Control for Infectious Respiratory Disease Pandemics: A Modelling Study for H1N1 and Four Strains of SARS-CoV-2

Post-pandemic economic recovery relies on border control for safe cross-border movement. Following the COVID-19 pandemic, we investigate whether effective strategies generalize across diseases and variants. For four SARS-CoV-2 variants and influenza A-H1N1, we simulated 21 strategy families of varying test types and frequencies, quantifying expected transmission risk, relative to no control, by strategy family and quarantine length. We also determined minimum quarantine lengths to suppress relative risk below given thresholds. SARS-CoV-2 variants showed similar relative risk across strategy families and quarantine lengths, with at most 2 days' between-variant difference in minimum quarantine lengths. ART-based and PCR-based strategies showed comparable effectiveness, with regular testing strategies requiring at most 9 days. For influenza A-H1N1, ART-based strategies were ineffective. Daily ART testing reduced relative risk only 9% faster than without regular testing. PCR-based strategies were moderately effective, with daily PCR (0-day delay) testing requiring 16 days for the second-most stringent threshold. Viruses with high typical viral loads and low transmission risk given low viral loads, such as SARS-CoV-2, are effectively controlled with moderate-sensitivity tests (ARTs) and modest quarantine periods. Viruses with low typical viral loads and substantial transmission risk at low viral loads, such as influenza A-H1N1, require high-sensitivity tests (PCR) and longer quarantine periods.

Detection Methods for H1N1 Virus

Influenza A virus H1N1, a respiratory virus transmitted via droplets and responsible for the global pandemic in 2009, belongs to the Orthomyxoviridae family, a single-negative-stranded RNA. It possesses glycoprotein spikes neuraminidase (NA), hemagglutinin (HA), and a matrix protein named M2. The Covid-19 pandemic affected the world population belongs to the respiratory virus category is currently mutating, this can also be observed in the case of H1N1 influenza A virus. Mutations in H1N1 can enhance the viral capacity which can lead to another pandemic. This virus affects children below 5 years, pregnant women, old age people, and immunocompromised individuals due to its high viral capacity. Its early detection is necessary for the patient's recovery time. In this book chapter, we mainly focus on the detection methods for H1N1, from traditional ones to the most advance including biosensors, RT-LAMP, multi-fluorescent PCR.

Use of Saliva Swab for Detection of Influenza Virus in Patients Admitted to an Emergency Department

Nasopharyngeal (NP) specimens are commonly used for the detection of influenza, but saliva swabs are easier to obtain and cause less discomfort to the patients. The objective of this study was to evaluate the usefulness of saliva swab specimens for the diagnosis of influenza compared with NP specimens. Influenza virus detection rate in saliva and NP swabs was compared in adult patients admitted to an emergency department from January to March 2020, using the Xpert Xpress Flu/respiratory syncytial virus (RSV) test. Cycle threshold (C_T) values were evaluated in all the cases. Among the 82 patients recruited, 19 had an influenza-positive diagnostic test result (11 influenza A and 8 influenza B). Overall, the agreement between saliva and NP swabs results was 97.6% (80/82; κ = 0.929; 95% confidence interval [CI], 0.832 to 1.0). There was no significant difference in the influenza detection rate between saliva swab and NP specimens (20.7% [17/82] versus 23.2% [19/82]; P = 0.5). There were only two discordant results (influenza B in an NP and false negative in a saliva sample). Manual inspection of the amplification curves showed that influenza RNA had been amplified in saliva with high C_Ts (C_T of 40) that the test reported as a negative result. The overall sensitivity and specificity for saliva was 89.5% (73.0% to 100%) and 100% (99.2% to 100%), respectively. In all the cases, the same influenza virus (A/B) was detected. Median C_T values were significantly lower in NP (31; interquartile range [IQR], 21.0 to 32.0) than in saliva (33; IQR, 23.0 to 38.0) (P = 0.001) specimens. Saliva swabs have high sensitivity and specificity for the detection of influenza virus by the Xpert Xpress Flu/RSV test and a high overall agreement and C_T correlation with NP specimens. Saliva swab is a feasible specimen type for influenza testing that might be easily self-collected with minimal equipment and discomfort.

IMPORTANCE Early detection of influenza virus is important for guiding antiviral and antibacterial treatment for infection control and public health measures. We have observed that saliva swab specimens have high sensitivity and specificity for the detection of influenza by the Xpert Xpress Flu/respiratory syncytial virus (RSV) test and high overall agreement and C_T correlation with nasopharyngeal specimens. Saliva swab may therefore be a feasible specimen type for influenza testing that can be easily self-collected with minimal equipment and discomfort.

The Epistemology of a Positive SARS-CoV-2 Test

We investigate the epistemological consequences of a positive polymerase chain reaction SARS-CoV test for two relevant hypotheses: (i) V is the hypothesis that an individual has been infected with SARS-CoV-2; (ii) C is the hypothesis that SARS-CoV-2 is the cause of flu-like symptoms in a given patient. We ask two fundamental epistemological questions regarding each hypothesis: First, how much confirmation does a positive test lend to each hypothesis? Second, how much evidence does a positive test provide for each hypothesis against its negation? We respond to each question within a formal Bayesian framework. We construe degree of confirmation as the difference between the posterior probability of the hypothesis and its prior, and the strength of evidence for a hypothesis against its alternative in terms of their likelihood ratio. We find that test specificity-and coinfection probabilities when making inferences about C-were key determinants of confirmation and evidence. Tests with < 87% specificity could not provide strong evidence (likelihood ratio > 8) for V against ¬V regardless of sensitivity. Accordingly, low specificity tests could not provide strong evidence in favor of C in all plausible scenarios modeled. We also show how a positive influenza A test disconfirms C and provides weak evidence against C in dependence on the probability that the patient is influenza A infected given that his/her symptoms are not caused by SARS-CoV-2. Our analysis points out some caveats that should be considered when attributing symptoms or death of a positively tested patient to SARS-CoV-2.

Progression and Trends in Virus from Influenza A to COVID-19: An Overview of Recent Studies

Influenza is a highly known contagious viral infection that has been responsible for the death of many people in history with pandemics. These pandemics have been occurring every 10 to 30 years in the last century. The most recent global pandemic prior to COVID-19 was the 2009 influenza A (H1N1) pandemic. A decade ago, the H1N1 virus caused 12,500 deaths in just 19 months globally. Now, again, the world has been challenged with another pandemic. Since December 2019, the first case of a novel coronavirus (COVID-19) infection was detected in Wuhan. This infection has risen rapidly throughout the world; even the World Health Organization (WHO) announced COVID-19 as a worldwide emergency to ensure human health and public safety. This review article aims to discuss important issues relating to COVID-19, including clinical, epidemiological, and pathological features of COVID-19 and recent progress in diagnosis and treatment approaches for the COVID-19 infection. We also highlight key similarities and differences between COVID-19 and influenza A to ensure the theoretical and practical details of COVID-19.

The perspectives of biomarker-based electrochemical immunosensors, artificial intelligence and the Internet of Medical Things toward COVID-19 diagnosis and management

The World Health Organization (WHO) has declared the COVID-19 an international health emergency due to the severity of infection progression, which became more severe due to its continuous spread globally and the unavailability of appropriate therapy and diagnostics systems. Thus, there is a need for efficient devices to detect SARS-CoV-2 infection at an early stage. Nowadays, the reverse transcription polymerase chain reaction (RT-PCR) technique is being applied for detecting this virus around the globe; however, factors such as stringent expertise, long diagnostic times, invasive and painful screening, and high costs have restricted the use of RT-PCR methods for rapid diagnostics. Therefore, the development of cost-effective, portable, sensitive, prompt and selective sensing systems to detect SARS-CoV-2 in biofluids at fM/pM/nM concentrations would be a breakthrough in diagnostics. Immunosensors that show increased specificity and sensitivity are considerably fast and do not imply costly reagents or instruments, reducing the cost for COVID-19 detection. The current developments in immunosensors perhaps signify the most significant opportunity for a rapid assay to detect COVID-19, without the need of highly skilled professionals and specialized tools to interpret results. Artificial intelligence (AI) and the Internet of Medical Things (IoMT) can also be equipped with this immunosensing approach to investigate useful networking through database management, sharing, and analytics to prevent and manage COVID-19. Herein, we represent the collective concepts of biomarker-based immunosensors along with AI and IoMT as smart sensing strategies with bioinformatics approach to monitor non-invasive early stage SARS-CoV-2 development, with fast point-of-care (POC) diagnostics as the crucial goal. This approach should be implemented quickly and verified practicality for clinical samples before being set in the present times for mass-diagnostic research.

Incorporating Real-time Influenza Detection Into the Test-negative Design for Estimating Influenza Vaccine Effectiveness: The Real-time Test-negative Design (rtTND)

With rapid and accurate molecular influenza testing now widely available in clinical settings, influenza vaccine effectiveness (VE) studies can prospectively select participants for enrollment based on real-time results rather than enrolling all eligible patients regardless of influenza status, as in the traditional test-negative design (TND). Thus, we explore advantages and disadvantages of modifying the TND for estimating VE by using real-time, clinically available viral testing results paired with acute respiratory infection eligibility criteria for identifying influenza cases and test-negative controls prior to enrollment. This modification, which we have called the real-time test-negative design (rtTND), has the potential to improve influenza VE studies by optimizing the case-to-test-negative control ratio, more accurately classifying influenza status, improving study efficiency, reducing study cost, and increasing study power to adequately estimate VE. Important considerations for limiting biases in the rtTND include the need for comprehensive clinical influenza testing at study sites and accurate influenza tests.

Derivation and Validation of a Clinical Decision Guideline for Influenza Testing in 4 US Emergency Departments

BACKGROUND

An accurate diagnosis of influenza is essential for appropriate antiviral treatment, in accordance with Centers for Disease Control and Prevention (CDC) guidelines. However, no clear guidance exists on which patients should be tested. We sought to develop a clinical decision guideline (CDG) to inform influenza testing decisions for those adult emergency department (ED) patients deemed appropriate for antiviral treatment by CDC guidelines.

METHODS

A prospective cohort study was performed at 4 US EDs. From November 2013 to April 2014, we enrolled adult ED patients with fever or respiratory symptoms who met criteria for antiviral treatment, per 2013 CDC guidelines. All patients were tested for influenza using polymerase chain reaction. Data were randomly split into derivation (80%) and validation (20%) data sets. A discrete set of independent variables was selected by logistic regression, using the derivation set to create a scoring system, with a target sensitivity of at least 90%. The derived CDG was then validated.

RESULTS

Of 1941 enrolled participants, 183 (9.4%) had influenza. The derived CDG included new or increased cough (2 points), headache (1 point), subjective fever (1 point), and triage temperature >100.4°C (1 point), with a score of ≥3 indicating influenza testing was warranted. The CDG had a sensitivity and specificity of 94.1% and 36.6%, respectively, in the derivation set and of 91.5% and 34.6%, respectively, in the validation set.

CONCLUSIONS

A CDG with high sensitivity was derived and validated. Incorporation into practice could standardize testing for high-risk patients in adult EDs during influenza seasons, potentially improving diagnoses and treatment.

CLINICAL TRIAL REGISTRATION

NCT01947049.

Detection methods for influenza A H1N1 virus with special reference to biosensors: a review

H1N1 (Swine flu) is caused by influenza A virus, which is a member of Orthomyxoviridae family. Transmission of H1N1 occurs from human to human through air or sometimes from pigs to humans. The influenza virus has different RNA segments, which can reassert to make new virus strain with the possibility to create an outbreak in unimmunized people. Gene reassortment is a process through which new strains are emerging in pigs, as it has specific receptors for both human influenza and avian influenza viruses. H1N1 binds specifically with an α-2,6 glycosidic bond, which is present in human respiratory tract cells as well as in pigs. Considering the fact of fast multiplication of viruses inside the living cells, rapid detection methods need an hour. Currently, WHO recommended methods for the detection of swine flu include real-time PCR in specific testing centres that take 3-4 h. More recently, a number of methods such as Antigen-Antibody or RT-LAMP and DNA biosensors have also been developed that are rapid and more sensitive. This review describes the various challenges in the diagnosis of H1N1, and merits and demerits of conventional vis-à-vis latest methods with special emphasis on biosensors.

Hemagglutinin gene based biosensor for early detection of swine flu (H1N1) infection in human

Hemagglutinin (HA) is a glycoprotein found on the surface of influenza A subtype virus H1N1 which play a major role in infection to the human by binding the virus to cells with sialic acid on the membrane of upper respiratory tract or erythrocytes. Based on sequence of HA gene an impedimetric biosensor was developed by immobilizing amino labeled single stranded DNA probe onto cysteine modified gold surface of the screen printed electrode for early and rapid detection of H1N1 (Swine flu) in human. The electrochemical impedance was recorded after hybridization of probe with single stranded cDNA (ss-cDNA) of H1N1 patient samples in presence of redox couple. All available methods for detection of H1N1 including RT-PCR are either expensive or time consuming. However, impedimetric biosensor is not only highly specific for H1N1 virus but also can detect as low as 0.004 ng (limit of detection) ss-cDNA in 6 µL only in 30 min. The sensitivity of the sensor was 3750 Ω cm^-2 ng^-1 of DNA. The biosensor was well characterized using surface cyclic voltammetry, validated with patient samples and compared with existing methods. The sensor can be used in hospitals, diagnostic centres as well as in remote areas for early and rapid diagnosis.

Role of the Clinical Microbiology Laboratory in Antimicrobial Stewardship

For adequate antimicrobial stewardship, microbiology needs to move from the laboratory to become physically and verbally amenable to the caregivers of an institution. Herein, we describe the contributions of our microbiology department to the antimicrobial stewardship program of a large teaching hospital as 10 main points ranging from the selection of patients deemed likely to benefit from a fast track approach, to their clinical samples, or the rapid reporting of results via a microbiology hotline, to rapid searches for pathogens and susceptibility testing. These points should serve as guidelines for similar programs designed to decrease the unnecessary use of antimicrobials.

Simultaneous detection of eight swine reproductive and respiratory pathogens using a novel GeXP analyser-based multiplex PCR assay

A new high-throughput GenomeLab Gene Expression Profiler (GeXP) analyser-based multiplex PCR assay was developed for the detection of eight reproductive and respiratory pathogens in swine. The reproductive and respiratory pathogens include North American porcine reproductive and respiratory syndrome virus (PRRSV-NA), classical swine fever virus (CSFV), porcine circovirus 2 (PCV-2), swine influenza virus (SIV) (including H1 and H3 subtypes), porcine parvovirus (PPV), pseudorabies virus (PRV) and Japanese encephalitis virus (JEV). Nine pairs of specific chimeric primers were designed and used to initiate PCRs, and one pair of universal primers was used for subsequent PCR cycles. The specificity of the GeXP assay was examined using positive controls for each virus. The sensitivity was evaluated using serial ten-fold dilutions of in vitro-transcribed RNA from all of the RNA viruses and plasmids from DNA viruses. The GeXP assay was further evaluated using 114 clinical specimens and was compared with real-time PCR/single RT-PCR methods. The specificity of the GeXP assay for each pathogen was examined using single cDNA/DNA template. Specific amplification peaks of the reproductive and respiratory pathogens were observed on the GeXP analyser. The minimum copies per reaction detected for each virus by the GeXP assay were as follows: 1000 copies/μl for PRV; 100 copies/μl for CSFV, JEV, PCV-2 and PPV; and 10 copies/μl for SIV-H1, SIV-H3 and PRRSV-NA. Analysis of 114 clinical samples using the GeXP assay demonstrated that the GeXP assay had comparable detection to real-time PCR/single RT-PCR. This study demonstrated that the GeXP assay is a new method with high sensitivity and specificity for the identification of these swine reproductive and respiratory pathogens. The GeXP assay may be adopted for molecular epidemiological surveys of these reproductive and respiratory pathogens in swine populations.

Direct Detection of Influenza A and B Viruses in Less Than 20 Minutes Using a Commercially Available Rapid PCR Assay

We compared an FDA-cleared rapid (<20 min) PCR assay (Cobas Liat; Roche Diagnostics) to our routine influenza A and B real-time PCR assay (Simplexa Flu A/B & RSV Direct; Focus Diagnostics) using respiratory swabs (n = 197). The Cobas Liat influenza A and B assays demonstrated sensitivities of 99.2% (123/124) and 100% (23/23), respectively, while showing a specificity of 100% for each target.

Effects of imperfect test sensitivity and specificity on observational studies of influenza vaccine effectiveness

BACKGROUND

The recently developed test-negative design is now standard for observational studies of influenza vaccine effectiveness (VE). It is unclear how influenza test misclassification biases test-negative VE estimates relative to VE estimates from traditional cohort or case-control studies.

METHODS

We simulated populations whose members may develop acute respiratory illness (ARI) due to influenza and to non-influenza pathogens. In these simulations, vaccination reduces the risk of influenza but not of non-influenza ARI. Influenza test sensitivity and specificity, risks of influenza and non-influenza ARI, and VE were varied across the simulations. In each simulation, we estimated influenza VE using a cohort design, a case-control design, and a test-negative design.

RESULTS

In the absence of influenza test misclassification, all three designs accurately estimated influenza VE. In the presence of misclassification, all three designs underestimated VE. Bias in VE estimates was slightly greater in the test-negative design than in cohort or case-control designs. Assuming the use of highly sensitive and specific reverse-transcriptase polymerase chain reaction tests for influenza, bias in the test-negative studies was trivial across a wide range of realistic values for VE.

DISCUSSION

Although influenza test misclassification causes more bias in test-negative studies than in traditional cohort or case-control studies, the difference is trivial for realistic combinations of attack rates, test sensitivity/specificity, and VE.

An algorithm to diagnose influenza infection: evaluating the clinical importance and impact on hospital costs of screening with rapid antigen detection tests

Rapid antigen detection tests (RADTs) are immunoassays that produce results in 15 min or less, have low sensitivity (50 %), but high specificity (95 %). We studied the clinical impact and laboratory savings of a diagnostic algorithm for influenza infection using RADTs as a first-step technique during the influenza season. From January 15th to March 31st 2014, we performed a diagnostic algorithm for influenza infection consisting of an RADT for all respiratory samples received in the laboratory. We studied all the patients with positive results for influenza infection, dividing them into two groups: Group A with a negative RADT but positive reference tests [reverse transcription polymerase chain reaction (RT-PCR) and/or culture] and Group B with an initial positive RADT. During the study period, we had a total of 1,156 patients with suspicion of influenza infection. Of them, 217 (19 %) had a positive result for influenza: 132 (11 %) had an initial negative RADT (Group A) and 85 (7 %) had a positive RADT (Group B). When comparing patients in Group A and Group B, we found significant differences, as follows: prescribed oseltamivir (67 % vs. 82 %; p = 0.02), initiation of oseltamivir before 24 h (89 % vs. 97 %; p = 0.03), antibiotics prescribed (89 % vs. 67 %; p = <0.01), intensive care unit (ICU) admissions after diagnosis (23 % vs. 14 %; p = 0.05), and need for supplementary oxygen (61 % vs. 47 %; p = 0.01). An influenza algorithm including RADTs as the first step improves the time of administration of proper antiviral therapy, reduces the use of antibiotics and ICU admissions, and decreases hospital costs.

Detection of new bunyavirus RNA by reverse transcription-loop-mediated isothermal amplification

Severe fever with thrombocytopenia syndrome (SFTS) is a newly emerging and epidemic infectious disease in central and northeast China. It is caused by New Bunyavirus and carries an average 12% case fatality rate. Early and rapid detection is critical for prevention and control of New Bunyavirus infection, since no vaccine or antiviral drugs are currently available, and prevention requires careful attention to control of the suspected tick vector. In this study, a simple and sensitive reverse transcription-loop-mediated isothermal amplification (RT-LAMP) assay was developed for rapid detection of New Bunyavirus. The detection limit of the RT-LAMP assay was approximately 10(3) 50% tissue culture infective doses/ml of New Bunyavirus in culture supernatants, and no cross-reactive amplification of other viruses known to cause similar clinical manifestations was observed. The assay was further evaluated using 138 specimens from clinically suspected SFTS and 40 laboratory-proven hantavirus infection with fever and renal syndrome patients, and the assay exhibited 97% agreement compared to real-time RT-PCR and conventional RT-PCR. Using real-time RT-PCR as the diagnostic gold standard, RT-LAMP was 99% sensitive and 100% specific. The RT-LAMP assay could become a useful alternative in clinical diagnosis of SFTS caused by New Bunyavirus, especially in resource-limited hospitals or rural clinics of China.

Microdroplet sandwich real-time rt-PCR for detection of pandemic and seasonal influenza subtypes

As demonstrated by the recent 2012/2013 flu epidemic, the continual emergence of new viral strains highlights the need for accurate medical diagnostics in multiple community settings. If rapid, robust, and sensitive diagnostics for influenza subtyping were available, it would help identify epidemics, facilitate appropriate antiviral usage, decrease inappropriate antibiotic usage, and eliminate the extra cost of unnecessary laboratory testing and treatment. Here, we describe a droplet sandwich platform that can detect influenza subtypes using real-time reverse-transcription polymerase chain reaction (rtRT-PCR). Using clinical samples collected during the 2010/11 season, we effectively differentiate between H1N1p (swine pandemic), H1N1s (seasonal), and H3N2 with an overall assay sensitivity was 96%, with 100% specificity for each subtype. Additionally, we demonstrate the ability to detect viral loads as low as 10⁴ copies/mL, which is two orders of magnitude lower than viral loads in typical infected patients. This platform performs diagnostics in a miniaturized format without sacrificing any sensitivity, and can thus be easily developed into devices which are ideal for small clinics and pharmacies.

Tools to detect influenza virus

In 2009, pandemic influenza A (H1N1) virus (H1N1 09) started to spread quickly in many countries. It causes respiratory infection with signs and symptoms of common infectious agents. Thus, clinicians sometimes may miss the H1N1 patient. Clinical laboratory tests are important for the diagnosis of the H1N1 infection. There are several tests available, however, the rapid test and direct fluorescence antigen test are unable to rule out the influenza virus infection and viral culture test is time consuming. Therefore, nucleic acid amplification techniques based on reverse transcription polymerase chain reaction assays are regarded as a specific diagnosis to confirm the influenza virus infection. Although the nucleic acid-based techniques are highly sensitive and specific, the high mutation rate of the influenza RNA-dependent RNA polymerase could limit the utility of the techniques. In addition, their use depends on the availability, cost and throughput of the diagnostic techniques. To overcome these drawbacks, evaluation and development of the techniques should be continued. This review provides an overview of various techniques for specific diagnosis of influenza infection.

Evaluation of virus isolation, one-step real-time reverse transcription polymerase chain reaction assay, and two rapid influenza diagnostic tests for detecting canine Influenza A virus H3N8 shedding in dogs

Sustained transmission of canine Influenza A virus (CIV) H3N8 among U.S. dogs underscores the threat influenza continues to pose to canine health. Because rapid and accurate detection of infection is critical to the diagnosis and control of CIV, the 2 main objectives of the current study were to estimate and compare the sensitivities of CIV testing methods on canine swab samples and to evaluate the performance of Flu Detect™ (Synbiotics Corp., Kansas City, MO) for detecting CIV nasal shedding in high-risk shelter dogs. To address the first objective, nasal and pharyngeal swab samples were collected from 124 shelter and household dogs seen by Colorado State University Veterinary Teaching Hospital clinicians for canine infectious respiratory disease between April 2006 and March 2007 and tested for CIV shedding using virus isolation, the rapid influenza diagnostic test Directigen Flu A+B™ (BD Diagnostic Systems, Sparks, MD), and real-time reverse transcription polymerase chain reaction (RT-PCR). For the second objective, 1,372 dogs with unknown respiratory health status were sampled from 6 U.S. shelters from December 2009 to November 2010. Samples were tested for presence of CIV using real-time RT-PCR and Flu Detect. Using a stochastic latent class modeling approach, the median sensitivities of virus isolation, rapid influenza diagnostic test, and real-time RT-PCR were 72%, 65%, and 95%, respectively. The Flu Detect test performed poorly for detecting CIV nasal shedding compared to real-time RT-PCR. In conclusion, the real-time RT-PCR has the highest sensitivity for detecting virus nasal shedding and can be used as a rapid diagnostic test for CIV.

Rethinking approaches to improve the utilization of nucleic acid amplification tests for detection and characterization of influenza A in diagnostic and reference laboratories

Influenza A virus (IFVA) is a significant cause of respiratory infections worldwide and was also responsible for a recent pandemic in 2009. Laboratory identification of IFVA can guide antiviral therapy, assist in cohorting of patients and prevent antibiotic use. Characterization of the virus can track the emergence of novel strains, identify resistance and determine how circulating strains match with vaccine components. The gold standard for detection and characterization of IFVA is nucleic acid amplification technology (e.g., reverse transcriptase PCR [RT-PCR]), which must contend with a constantly evolving viral genome. Although molecular technology has been available for over two decades, there is still an operational gap between assay design and utilization of these tests for the diagnosis and characterization of IFVA. This review will discuss issues surrounding the implementation and use of RT-PCR for the identification and characterization of IFVA, and speculate on why RT-PCR has not been used more widely in clinical laboratories or moved closer to the patient. Newer, less widely used technologies that may change our laboratory practices will be identified and the authors will close with an attempt to identify some future applications of RT-PCR-based technologies for the detection and characterization of IFVA.

New approaches for influenza vaccination of healthcare workers

PURPOSE OF REVIEW

Vaccination of healthcare workers (HCWs) against influenza is an important component of infection control in healthcare settings but HCW vaccination rates remain low. Here we review current and emerging strategies for influenza vaccination of HCWs.

RECENT FINDINGS

Professional organizations have recommended annual influenza vaccination for HCWs since 1984, but HCW vaccination rates have improved minimally. Recent studies indicate that comprehensive influenza vaccination programs have failed to achieve adequate influenza vaccination rates for HCWs in spite of allocating substantial resources to HCW vaccination programs. Mandatory HCW influenza vaccination programs have been introduced and clearly outperform traditional comprehensive vaccination programs. Some argue that mandatory vaccination programs infringe on HCW autonomy, and introduction of mandatory vaccination programs can be controversial. Public reporting of institutional HCW influenza vaccination rates is another strategy to achieve high vaccination rates, as HCW influenza vaccination may be used in the future as a quality and safety metric.

SUMMARY

HCW influenza vaccination in the setting of a comprehensive infection control program is a core patient-safety practice. Mandatory HCW influenza vaccination and public reporting of HCW vaccination rates will complement one another in achieving substantial gains for HCW influenza vaccination programs.