Enhanced diagnosis of severe bacterial and fungal respiratory infection in children using a rapid syndromic array-case report.

Background: A microbiological cause of infection is infrequently identified in critically unwell children with a respiratory infection. Molecular diagnostic arrays provide an alternative. These tests are becoming more broadly available, but little is known about how clinicians interpret the results to impact clinical decision making. Case Description: Here we describe three cases of bacterial and fungal lower respiratory tract infection (LRTI) diagnosed in the paediatric intensive care unit (PICU) using a custom 52 respiratory pathogen TaqMan array card (TAC). Firstly, an early diagnosis of Candida albicans pneumonia was made with the support of the TAC in a trauma patient who received prolonged mechanical ventilation. The pathogen was only identified on microbiological cultures after further clinical deterioration had occurred. Secondly, a rare case of psittacosis was identified in an adolescent with acute respiratory distress, initially suspected to have multisystem inflammatory syndrome in children (MIS-C). Finally, Haemophilus influenzae pneumonia was identified in an infant with recurrent apnoeas, initially treated for meningitis. Two diagnoses would not have been established using commercially available arrays, and pathogen-specific diagnoses were established faster than that of routine microbiological culture. Conclusions: The pathogens included on molecular arrays and interpretation by a multidisciplinary team are crucial in providing value to PICU diagnostic services. Molecular arrays have the potential to enhance early pathogen-specific diagnosis of LRTI in the PICU.

Rapid Detection of Antimicrobial Resistance Genes in Critically Ill Children Using a Custom TaqMan Array Card.

Bacteria are identified in only 22% of critically ill children with respiratory infections treated with antimicrobial therapy. Once an organism is isolated, antimicrobial susceptibility results (phenotypic testing) can take another day. A rapid diagnostic test identifying antimicrobial resistance (AMR) genes could help clinicians make earlier, informed antimicrobial decisions. Here we aimed to validate a custom AMR gene TaqMan Array Card (AMR-TAC) for the first time and assess its feasibility as a screening tool in critically ill children. An AMR-TAC was developed using a combination of commercial and bespoke targets capable of detecting 23 AMR genes. This was validated using isolates with known phenotypic resistance. The card was then tested on lower respiratory tract and faecal samples obtained from mechanically ventilated children in a single-centre observational study of respiratory infection. There were 82 children with samples available, with a median age of 1.2 years. Major comorbidity was present in 29 (35%) children. A bacterial respiratory pathogen was identified in 13/82 (16%) of children, of which 4/13 (31%) had phenotypic AMR. One AMR gene was detected in 49/82 (60%), and multiple AMR genes were detected in 14/82 (17%) children. Most AMR gene detections were not associated with the identification of phenotypic AMR. AMR genes are commonly detected in samples collected from mechanically ventilated children with suspected respiratory infections. AMR-TAC may have a role as an adjunct test in selected children in whom there is a high suspicion of antimicrobial treatment failure.

A qualitative investigation of paediatric intensive care staff attitudes towards the diagnosis of lower respiratory tract infection in the molecular diagnostics era.

Background: In the past decade, molecular diagnostic syndromic arrays incorporating a range of bacterial and viral pathogens have been described. It is unclear how paediatric intensive care unit (PICU) staff diagnose lower respiratory tract infection (LRTI) and integrate diagnostic array results into antimicrobial decision-making. Methods: An online survey with eleven questions was distributed throughout paediatric intensive care societies in the UK, continental Europe and Australasia with a total of 755 members. Participants were asked to rate the clinical factors and investigations they used when prescribing for LRTI. Semi-structured interviews were undertaken with staff who participated in a single-centre observational study of a 52-pathogen diagnostic array. Results: Seventy-two survey responses were received; most responses were from senior doctors. Whilst diagnostic arrays were used less frequently than routine investigations (i.e. microbiological culture), they were of comparable perceived utility when making antimicrobial decisions. Prescribers reported that for arrays to be clinically impactful, they would need to deliver results within 6 h for stable patients and within 1 h for unstable patients to inform their immediate decision to prescribe antimicrobials. From 16 staff interviews, we identified that arrays were helpful for the diagnosis and screening of bacterial LRTI. Staff reported it could be challenging to interpret results in some cases due to the high sensitivity of the test. Therefore, results were considered within the context of the patient and discussed within the multidisciplinary team. Conclusions: Diagnostic arrays were considered of comparable value to microbiological investigations by PICU prescribers. Our findings support the need for further clinical and economic evaluation of diagnostic arrays in a randomised control trial. Trial registration: Clinicaltrials.gov, NCT04233268. Registered on 18 January 2020. Supplementary Information: The online version contains supplementary material available at 10.1007/s44253-023-00008-z.

Multiplex MinION sequencing suggests enteric adenovirus F41 genetic diversity comparable to pre-COVID-19 era.

Human adenovirus F41 causes acute gastroenteritis in children, and has recently been associated with an apparent increase in paediatric hepatitis of unknown aetiology in the UK, with further cases reported in multiple countries. Relatively little is known about the genetic diversity of adenovirus F41 in UK children; and it is unclear what, if any, impact the COVID-19 pandemic has had on viral diversity in the UK. Methods that allow F41 to be sequenced from clinical samples without the need for viral culture are required to provide the genomic data to address these questions. Therefore, we evaluated an overlapping-amplicon method of sequencing adenovirus genomes from clinical samples using Oxford Nanopore technology. We applied this method to a small sample of adenovirus-species-F-positive extracts collected as part of standard care in the East of England region in January-May 2022. This method produced genomes with >75 % coverage in 13/22 samples and >50 % coverage in 19/22 samples. We identified two F41 lineages present in paediatric patients in the East of England in 2022. Where F41 genomes from paediatric hepatitis cases were available (n=2), these genomes fell within the diversity of F41 from the UK and continental Europe sequenced before and after the 2020-2021 phase of the COVID-19 pandemic. Our analyses suggest that overlapping amplicon sequencing is an appropriate method for generating F41 genomic data from high-virus-load clinical samples, and currently circulating F41 viral lineages were present in the UK and Europe before the COVID-19 pandemic.

The rapid detection of respiratory pathogens in critically ill children.

PURPOSE: Respiratory infections are the most common reason for admission to paediatric intensive care units (PICU). Most patients with lower respiratory tract infection (LRTI) receive broad-spectrum antimicrobials, despite low rates of bacterial culture confirmation. Here, we evaluated a molecular diagnostic test for LRTI to inform the better use of antimicrobials. METHODS: The Rapid Assay for Sick Children with Acute Lung infection Study was a single-centre, prospective, observational cohort study of mechanically ventilated children (> 37/40 weeks corrected gestation to 18 years) with suspected community acquired or ventilator-associated LRTI. We evaluated the use of a 52-pathogen custom TaqMan Array Card (TAC) to identify pathogens in non-bronchoscopic bronchoalveolar lavage (mini-BAL) samples. TAC results were compared to routine microbiology testing. Primary study outcomes were sensitivity and specificity of TAC, and time to result. RESULTS: We enrolled 100 patients, all of whom were tested with TAC and 91 of whom had matching culture samples. TAC had a sensitivity of 89.5% (95% confidence interval (CI95) 66.9-98.7) and specificity of 97.9% (CI95 97.2-98.5) compared to routine bacterial and fungal culture. TAC took a median 25.8 h (IQR 9.1-29.8 h) from sample collection to result. Culture was significantly slower: median 110.4 h (IQR 85.2-141.6 h) for a positive result and median 69.4 h (IQR 52.8-78.6) for a negative result. CONCLUSIONS: TAC is a reliable and rapid adjunct diagnostic approach for LRTI in critically ill children, with the potential to aid early rationalisation of antimicrobial therapy.

Differences in epidemiology of enteropathogens in children pre- and post-rotavirus vaccine introduction in Kilifi, coastal Kenya.

BACKGROUND: Kenya introduced Rotarix® (GlaxoSmithKline Biologicals, Rixensart, Belgium) vaccination into its national immunization programme beginning July 2014. The impact of this vaccination program on the local epidemiology of various known enteropathogens is not fully understood. METHODS: We used a custom TaqMan Array Card (TAC) to screen for 28 different enteropathogens in 718 stools from children aged less than 13 years admitted to Kilifi County Hospital, coastal Kenya, following presentation with diarrhea in 2013 (before vaccine introduction) and in 2016-2018 (after vaccine introduction). Pathogen positivity rate differences between pre- and post-Rotarix® vaccination introduction were examined using both univariate and multivariable logistic regression models. RESULTS: In 665 specimens (92.6%), one or more enteropathogen was detected, while in 323 specimens (48.6%) three or more enteropathogens were detected. The top six detected enteropathogens were: enteroaggregative Escherichia coli (EAggEC; 42.1%), enteropathogenic Escherichia coli (EPEC; 30.2%), enterovirus (26.9%), rotavirus group A (RVA; 24.8%), parechovirus (16.6%) and norovirus GI/GII (14.4%). Post-rotavirus vaccine introduction, there was a significant increase in the proportion of samples testing positive for EAggEC (35.7% vs. 45.3%, p = 0.014), cytomegalovirus (4.2% vs. 9.9%, p = 0.008), Vibrio cholerae (0.0% vs. 2.3%, p = 0.019), Strongyloides species (0.8% vs. 3.6%, p = 0.048) and Dientamoeba fragilis (2.1% vs. 7.8%, p = 0.004). Although not reaching statistical significance, the positivity rate of adenovirus 40/41 (5.8% vs. 7.3%, p = 0.444), norovirus GI/GII (11.2% vs. 15.9%, p = 0.089), Shigella species (8.7% vs. 13.0%, p = 0.092) and Cryptosporidium spp. (11.6% vs. 14.7%, p = 0.261) appeared to increase post-vaccine introduction. Conversely, the positivity rate of sapovirus decreased significantly post-vaccine introduction (7.8% vs. 4.0%, p = 0.030) while that of RVA appeared not to change (27.4% vs. 23.5%, p = 0.253). More enteropathogen coinfections were detected per child post-vaccine introduction compared to before (mean: 2.7 vs. 2.3; p = 0.0025). CONCLUSIONS: In this rural Coastal Kenya setting, childhood enteropathogen infection burden was high both pre- and post-rotavirus vaccination introduction. Children who had diarrheal admissions post-vaccination showed an increase in coinfections and changes in specific enteropathogen positivity rates. This study highlights the utility of multipathogen detection platforms such as TAC in understanding etiology of childhood acute gastroenteritis in resource-limited regions.

Pathogens that Cause Illness Clinically Indistinguishable from Lassa Fever, Nigeria, 2018.

During the 2018 Lassa fever outbreak in Nigeria, samples from patients with suspected Lassa fever but negative Lassa virus PCR results were processed through custom gene expression array cards and metagenomic sequencing. Results demonstrated no single etiology, but bacterial and viral pathogens (including mixed co-infections) were detected.

Emergence of methicillin resistance predates the clinical use of antibiotics.

The discovery of antibiotics more than 80 years ago has led to considerable improvements in human and animal health. Although antibiotic resistance in environmental bacteria is ancient, resistance in human pathogens is thought to be a modern phenomenon that is driven by the clinical use of antibiotics1. Here we show that particular lineages of methicillin-resistant Staphylococcus aureus-a notorious human pathogen-appeared in European hedgehogs in the pre-antibiotic era. Subsequently, these lineages spread within the local hedgehog populations and between hedgehogs and secondary hosts, including livestock and humans. We also demonstrate that the hedgehog dermatophyte Trichophyton erinacei produces two ß-lactam antibiotics that provide a natural selective environment in which methicillin-resistant S. aureus isolates have an advantage over susceptible isolates. Together, these results suggest that methicillin resistance emerged in the pre-antibiotic era as a co-evolutionary adaptation of S. aureus to the colonization of dermatophyte-infected hedgehogs. The evolution of clinically relevant antibiotic-resistance genes in wild animals and the connectivity of natural, agricultural and human ecosystems demonstrate that the use of a One Health approach is critical for our understanding and management of antibiotic resistance, which is one of the biggest threats to global health, food security and development.

Evaluation of sample pooling using the SAMBA II SARS-CoV-2 test.

BACKGROUND: Screening of infectious asymptomatic or pre-symptomatic individuals for SARS-CoV-2 is at present a key to controling the COVID-19 pandemic. In order to expand testing capability and limit cost, pool testing of asymtomatic individuals has been proposed, provided assay performance is not significantly affected. METHODS: Combined nose and throat (N/T) swabs collected from COVID-19 infected or non-infected individuals were tested using SAMBA II individually and in pools of four (one positive and 3 negative). The evaluation was conducted by the manufacturer and an independent NHS site. Ct cycles of individual positives and pooled positives were determined by qRT-PCR. RESULTS: In 42 pools containing a single positive sample with Ct values ranging between 17 and 36, 41 pools (97.6 %) were found positive by the SARS-CoV-2 SAMBA II test. The false-negative pool by SAMBA was also negative by both reference methods used in this evaluation.The individual positive sample in this pool was positive by SAMBA (Orf only) and by one of the reference methods (S gene only, Ct 35) but negative by the second reference method indicating that the sample itself was very low viral load. All 78 pools containing 4 negative swabs were negative (100 % specificity). DISCUSSION: The preliminary data of the evaluation indicated a high level of performance in both sensitivity and specificity of the SAMBA II assay when used to test pools of 4 patient samples. The implementation of this pooled protocol can increase throughput and reduce cost/test when the prevalence of COVID is low.

Rapid Assay for Sick Children with Acute Lung infection Study (RASCALS): diagnostic cohort study protocol.

INTRODUCTION: Lower respiratory tract infection (LRTI) is the most commonly treated infection in critically ill children. Pathogens are infrequently identified on routine respiratory culture, and this is a time-consuming process. A syndromic approach to rapid molecular testing that includes a wide range of bacterial and fungal targets has the potential to aid clinical decision making and reduce unnecessary broad spectrum antimicrobial prescribing. Here, we describe a single-centre prospective cohort study investigating the use of a 52-pathogen TaqMan array card (TAC) for LRTI in the paediatric intensive care unit (PICU). METHODS AND ANALYSIS: Critically ill children with suspected LRTI will be enrolled to this 100 patient single-centre prospective observational study in a PICU in the East of England. Samples will be obtained via routine non-bronchoscopic bronchoalveolar lavage which will be sent for standard microbiology culture in addition to TAC. A blood draw will be obtained via any existing vascular access device. The primary outcomes of the study will be (1) concordance of TAC result with routine culture and 16S rRNA gene sequencing and (2) time of diagnostic result from TAC versus routine culture. Secondary outcomes will include impact of the test on total antimicrobial prescriptions, a description of the inflammatory profile of the lung and blood in response to pneumonia and a description of the clinical experience of medical and nursing staff using TAC. ETHICS AND DISSEMINATION: This study has been approved by the Yorkshire and the Humber-Bradford Leeds Research Ethics Committee (REC reference 20/YH/0089). Informed consent will be obtained from all participants. Results will be published in peer-reviewed publications and international conferences. TRIAL REGISTRATION NUMBER: NCT04233268.

Patterns of within-host genetic diversity in SARS-CoV-2.

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95.1% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within- and between-host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.

The COVID-19 pandemic has had major health impacts across the globe. The scientific community has focused much attention on finding ways to monitor how the virus responsible for the pandemic, SARS-CoV-2, spreads. One option is to perform genetic tests, known as sequencing, on SARS-CoV-2 samples to determine the genetic code of the virus and to find any differences or mutations in the genes between the viral samples. Viruses mutate within their hosts and can develop into variants that are able to more easily transmit between hosts. Genetic sequencing can reveal how genetically similar two SARS-CoV-2 samples are. But tracking how SARS-CoV-2 moves from one person to the next through sequencing can be tricky. Even a sample of SARS-CoV-2 viruses from the same individual can display differences in their genetic material or within-host variants. Could genetic testing of within-host variants shed light on factors driving SARS-CoV-2 to evolve in humans? To get to the bottom of this, Tonkin-Hill, Martincorena et al. probed the genetics of SARS-CoV-2 within-host variants using 1,181 samples. The analyses revealed that 95.1% of samples contained within-host variants. A number of variants occurred frequently in many samples, which were consistent with mutational hotspots in the SARS-CoV-2 genome. In addition, within-host variants displayed mutation patterns that were similar to patterns found between infected individuals. The shared within-host variants between samples can help to reconstruct transmission chains. However, the observed mutational hotspots and the detection of multiple strains within an individual can make this challenging. These findings could be used to help predict how SARS-CoV-2 evolves in response to interventions such as vaccines. They also suggest that caution is needed when using information on within-host variants to determine transmission between individuals.

Superspreaders drive the largest outbreaks of hospital onset COVID-19 infections.

SARS-CoV-2 is notable both for its rapid spread, and for the heterogeneity of its patterns of transmission, with multiple published incidences of superspreading behaviour. Here, we applied a novel network reconstruction algorithm to infer patterns of viral transmission occurring between patients and health care workers (HCWs) in the largest clusters of COVID-19 infection identified during the first wave of the epidemic at Cambridge University Hospitals NHS Foundation Trust, UK. Based upon dates of individuals reporting symptoms, recorded individual locations, and viral genome sequence data, we show an uneven pattern of transmission between individuals, with patients being much more likely to be infected by other patients than by HCWs. Further, the data were consistent with a pattern of superspreading, whereby 21% of individuals caused 80% of transmission events. Our study provides a detailed retrospective analysis of nosocomial SARS-CoV-2 transmission, and sheds light on the need for intensive and pervasive infection control procedures.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, presents a global public health challenge. Hospitals have been at the forefront of this battle, treating large numbers of sick patients over several waves of infection. Finding ways to manage the spread of the virus in hospitals is key to protecting vulnerable patients and workers, while keeping hospitals running, but to generate effective infection control, researchers must understand how SARS-CoV-2 spreads. A range of factors make studying the transmission of SARS-CoV-2 in hospitals tricky. For instance, some people do not present any symptoms, and, amongst those who do, it can be difficult to determine whether they caught the virus in the hospital or somewhere else. However, comparing the genetic information of the SARS-CoV-2 virus from different people in a hospital could allow scientists to understand how it spreads. Samples of the genetic material of SARS-CoV-2 can be obtained by swabbing infected individuals. If the genetic sequences of two samples are very different, it is unlikely that the individuals who provided the samples transmitted the virus to one another. Illingworth, Hamilton et al. used this information, along with other data about how SARS-CoV-2 is transmitted, to develop an algorithm that can determine how the virus spreads from person to person in different hospital wards. To build their algorithm, Illingworth, Hamilton et al. collected SARS-CoV-2 genetic data from patients and staff in a hospital, and combined it with information about how SARS-CoV-2 spreads and how these people moved in the hospital . The algorithm showed that, for the most part, patients were infected by other patients (20 out of 22 cases), while staff were infected equally by patients and staff. By further probing these data, Illingworth, Hamilton et al. revealed that 80% of hospital-acquired infections were caused by a group of just 21% of individuals in the study, identifying a 'superspreader' pattern. These findings may help to inform SARS-CoV-2 infection control measures to reduce spread within hospitals, and could potentially be used to improve infection control in other contexts.

Genomic epidemiology of COVID-19 in care homes in the east of England.

COVID-19 poses a major challenge to care homes, as SARS-CoV-2 is readily transmitted and causes disproportionately severe disease in older people. Here, 1167 residents from 337 care homes were identified from a dataset of 6600 COVID-19 cases from the East of England. Older age and being a care home resident were associated with increased mortality. SARS-CoV-2 genomes were available for 700 residents from 292 care homes. By integrating genomic and temporal data, 409 viral clusters within the 292 homes were identified, indicating two different patterns - outbreaks among care home residents and independent introductions with limited onward transmission. Approximately 70% of residents in the genomic analysis were admitted to hospital during the study, providing extensive opportunities for transmission between care homes and hospitals. Limiting viral transmission within care homes should be a key target for infection control to reduce COVID-19 mortality in this population.

Ventilator-associated pneumonia in critically ill patients with COVID-19.

BACKGROUND: Pandemic COVID-19 caused by the coronavirus SARS-CoV-2 has a high incidence of patients with severe acute respiratory syndrome (SARS). Many of these patients require admission to an intensive care unit (ICU) for invasive ventilation and are at significant risk of developing a secondary, ventilator-associated pneumonia (VAP). OBJECTIVES: To study the incidence of VAP and bacterial lung microbiome composition of ventilated COVID-19 and non-COVID-19 patients. METHODS: In this retrospective observational study, we compared the incidence of VAP and secondary infections using a combination of microbial culture and a TaqMan multi-pathogen array. In addition, we determined the lung microbiome composition using 16S RNA analysis in a subset of samples. The study involved 81 COVID-19 and 144 non-COVID-19 patients receiving invasive ventilation in a single University teaching hospital between March 15th 2020 and August 30th 2020. RESULTS: COVID-19 patients were significantly more likely to develop VAP than patients without COVID (Cox proportional hazard ratio 2.01 95% CI 1.14-3.54, p = 0.0015) with an incidence density of 28/1000 ventilator days versus 13/1000 for patients without COVID (p = 0.009). Although the distribution of organisms causing VAP was similar between the two groups, and the pulmonary microbiome was similar, we identified 3 cases of invasive aspergillosis amongst the patients with COVID-19 but none in the non-COVID-19 cohort. Herpesvirade activation was also numerically more frequent amongst patients with COVID-19. CONCLUSION: COVID-19 is associated with an increased risk of VAP, which is not fully explained by the prolonged duration of ventilation. The pulmonary dysbiosis caused by COVID-19, and the causative organisms of secondary pneumonia observed are similar to that seen in critically ill patients ventilated for other reasons.

Development and implementation of a customised rapid syndromic diagnostic test for severe pneumonia.

Background: The diagnosis of pneumonia has been hampered by a reliance on bacterial cultures which take several days to return a result, and are frequently negative. In critically ill patients this leads to the use of empiric, broad-spectrum antimicrobials and compromises good antimicrobial stewardship. The objective of this study was to establish the performance of a syndromic molecular diagnostic approach, using a custom TaqMan array card (TAC) covering 52 respiratory pathogens, and assess its impact on antimicrobial prescribing. Methods: The TAC was validated against a retrospective multi-centre cohort of broncho-alveolar lavage samples. The TAC was assessed prospectively in patients undergoing investigation for suspected pneumonia, with a comparator cohort formed of patients investigated when the TAC laboratory team were unavailable. Co-primary outcomes were sensitivity compared to conventional microbiology and, for the prospective study, time to result. Metagenomic sequencing was performed to validate findings in prospective samples. Antibiotic free days (AFD) were compared between the study cohort and comparator group. Results: 128 stored samples were tested, with sensitivity of 97% (95% confidence interval (CI) 88-100%). Prospectively, 95 patients were tested by TAC, with 71 forming the comparator group. TAC returned results 51 hours (interquartile range 41-69 hours) faster than culture and with sensitivity of 92% (95% CI 83-98%) compared to conventional microbiology. 94% of organisms identified by sequencing were detected by TAC. There was a significant difference in the distribution of AFDs with more AFDs in the TAC group (p=0.02). TAC group were more likely to experience antimicrobial de-escalation (odds ratio 2.9 (95%1.5-5.5)). Conclusions: Implementation of a syndromic molecular diagnostic approach to pneumonia led to faster results, with high sensitivity and impact on antibiotic prescribing.

Specificity and positive predictive value of SARS-CoV-2 nucleic acid amplification testing in a low-prevalence setting.

OBJECTIVES: When the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is low, many positive test results are false positives. Confirmatory testing reduces overdiagnosis and nosocomial infection and enables real-world estimates of test specificity and positive predictive value. This study estimates these parameters to evaluate the impact of confirmatory testing and to improve clinical diagnosis, epidemiological estimation and interpretation of vaccine trials. METHODS: Over 1 month we took all respiratory samples from our laboratory with a patient's first detection of SARS-CoV-2 RNA (Hologic Aptima SARS-CoV-2 assay or in-house RT-PCR platform), and repeated testing using two platforms. Samples were categorized by source, and by whether clinical details suggested COVID-19 or corroborative testing from another laboratory. We estimated specificity and positive predictive value using approaches based on maximum likelihood. RESULTS: Of 19 597 samples, SARS-CoV-2 RNA was detected in 107; 52 corresponded to first-time detection (0.27% of tests on samples without previous detection). Further testing detected SARS-CoV-2 RNA once or more ('confirmed') in 29 samples (56%), and failed to detect SARS-CoV-2 RNA ('not confirmed') in 23 (44%). Depending upon assumed parameters, point estimates for specificity and positive predictive value were 99.91-99.98% and 61.8-89.8% respectively using the Hologic Aptima SARS-CoV-2 assay, and 97.4-99.1% and 20.1-73.8% respectively using an in-house assay. CONCLUSIONS: Nucleic acid amplification testing for SARS-CoV-2 is highly specific. Nevertheless, when prevalence is low a significant proportion of initially positive results fail to confirm, and confirmatory testing substantially reduces the detection of false positives. Omitting additional testing in samples with higher prior detection probabilities focuses testing where it is clinically impactful and minimizes delay.

Performance Evaluation of the SAMBA II SARS-CoV-2 Test for Point-of-Care Detection of SARS-CoV-2.

Nucleic acid amplification for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in respiratory samples is the standard method for diagnosis. The majority of this testing is centralized and therefore has turnaround times of several days. Point-of-care (POC) testing with rapid turnaround times would allow more effective triage in settings where patient management and infection control decisions need to be made rapidly. The inclusivity and specificity of the Simple AMplification-Based Assay (SAMBA) II SARS-CoV-2 test were determined by both in silico analyses of the primers and probes and wet testing. The SAMBA II SARS-CoV-2 test was evaluated for performance characteristics. Clinical performance was evaluated in residual combined throat/nose swabs and compared to that of the Public Health England real-time PCR assay targeting the RdRp gene. The SAMBA II SARS-CoV-2 test has an analytical sensitivity of 250 copies/ml for detecting two regions of the genome (open reading frame 1ab [ORF1ab] and nucleocapsid protein [N]). The clinical performance was evaluated in 172 residual combined nose/throat swabs provided by the Clinical Microbiology and Public Health Laboratory, Addenbrooke's Hospital, Cambridge (CMPHL), which showed an estimated positive percent agreement of 98.9% (95% confidence interval [CI], 93.83 to 99.97) and negative percent agreement of 96.4% (95% CI, 89.92 to 99.26) compared to testing by the CMPHL. The data show that the SAMBA II SARS-CoV-2 test performs equivalently to the centralized testing methods, but with a shorter turnaround time of 86 to 101 min. Point-of-care tests such as SAMBA should enable rapid patient management and effective implementation of infection control measures.