SARS-CoV-2 spike S2 subunit inhibits p53 activation of p21(WAF1), TRAIL Death Receptor DR5 and MDM2 proteins in cancer cells (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and COVID-19 infection has led to worsened outcomes for patients with cancer. SARS-CoV-2 spike protein mediates host cell infection and cell-cell fusion that causes stabilization of tumor suppressor p53 protein. In-silico analysis previously suggested that SARS-CoV-2 spike interacts with p53 directly but this putative interaction has not been demonstrated in cells. We examined the interaction between SARS-CoV-2 spike, p53 and MDM2 (E3 ligase, which mediates p53 degradation) in cancer cells using an immunoprecipitation assay. We observed that SARS-CoV-2 spike protein interrupts p53-MDM2 protein interaction but did not detect SARS-CoV-2 spike bound with p53 protein in the cancer cells. We further observed that SARS-CoV-2 spike suppresses p53 transcriptional activity in cancer cells including after nutlin exposure of wild-type p53-, spike S2-expressing tumor cells and inhibits chemotherapy-induced p53 gene activation of p21(WAF1), TRAIL Death Receptor DR5 and MDM2. The suppressive effect of SARS-CoV-2 spike on p53-dependent gene activation provides a potential molecular mechanism by which SARS-CoV-2 infection may impact tumorigenesis, tumor progression and chemotherapy sensitivity. In fact, cisplatin-treated tumor cells expressing spike S2 were found to have increased cell viability as compared to control cells. Further observations on gamma-H2AX expression in spike S2-expressing cells treated with cisplatin may indicate altered DNA damage sensing in the DNA damage response pathway. The preliminary observations reported here warrant further studies to unravel the impact of SARS-CoV-2 and its various encoded proteins including spike on pathways of tumorigenesis and response to cancer therapeutics.

Associations between SARS-CoV-2 Infection or COVID-19 Vaccination and Human Milk Composition: A Multi-Omics Approach (preprint)

The risk of contracting SARS-CoV-2 via human milk-feeding is virtually non-existent. Adverse effects of COVID-19 vaccination for lactating individuals are not different from the general population, and no evidence has been found that their infants exhibit adverse effects. Yet, there remains substantial hesitation among this population globally regarding the safety of these vaccines. Herein we aimed to determine if compositional changes in milk occur following infection or vaccination, including any evidence of vaccine components. Using an extensive multi-omics approach, we found that compared to unvaccinated individuals SARS-CoV-2 infection was associated with significant compositional differences in 67 proteins, 385 lipids, and 13 metabolites. In contrast, COVID-19 vaccination was not associated with any changes in lipids or metabolites, although it was associated with changes in 13 or fewer proteins. Compositional changes in milk differed by vaccine. Changes following vaccination were greatest after 1-6 hours for the mRNA-based Moderna vaccine (8 changed proteins), 3 days for the mRNA-based Pfizer (4 changed proteins), and adenovirus-based Johnson and Johnson (13 changed proteins) vaccines. Proteins that changed after both natural infection and Johnson and Johnson vaccine were associated mainly with systemic inflammatory responses. In addition, no vaccine components were detected in any milk sample. Together, our data provide evidence of only minimal changes in milk composition due to COVID-19 vaccination, with much greater changes after natural SARS-CoV-2 infection.

Application of a High-Resolution Melt Assay for Monitoring SARS-CoV-2 Variants in Burkina Faso and Kenya (preprint)

The rapid emergence and global dissemination of SARS-CoV-2 highlighted a need for robust, adaptable surveillance systems. However, financial and infrastructure requirements for whole genome sequencing (WGS) mean most surveillance data have come from higher-resource geographies, despite unprecedented investment in sequencing in low-middle income countries (LMICs) throughout the SARS-CoV-2 pandemic. Consequently, the molecular epidemiology of SARS-CoV-2 in some LMICs is limited, and there is a need for more cost-accessible technologies to help close data gaps for surveillance of SARS-CoV-2 variants. To address this, we have developed two high-resolution melt curve (HRM) assays that target key variant-defining mutations in the SARS-CoV-2 genome, which give unique signature profiles that define different SARS-CoV-2 variants of concern (VOCs). Extracted RNA from SARS-CoV-2 positive samples collected from 205 participants (112 in Burkina Faso, 93 in Kenya) on the day of enrolment in the MALCOV study (Malaria as a Risk Factor for COVID-19) between February 2021 and February 2022 were analysed using our optimised HRM assays and compared to Next Generation Sequencing (NGS) on Oxford Nanopore MinION . With NGS as a reference, two HRM assays, HRM-VOC-1 and HRM-VOC-2, demonstrated sensitivity/specificity of 100%/99.29% and 92.86/99.39%, respectively, for detecting Alpha, 90.08%/100% and 92.31%/100% for Delta and 93.75%/100% and 100%/99.38% for Omicron. The assays described here provide a lower-cost approach (<$1 per sample) to conducting molecular epidemiology, capable of high-throughput testing. We successfully scaled up the HRM-VOC-2 assay to screen a total of 506 samples from which we were able to show the replacement of Alpha with the introduction of Delta and the replacement of Delta by the Omicron variant in this community in Kisumu, Kenya. These assays are readily adaptable and can focus on local epidemiological surveillance questions or be updated quickly to accommodate the emergence of a novel variant or adapt to novel and emerging pathogens.

A Centrality Metrics Approach to Analyzing Temporal Spread Patterns of Misinformation in Social Networks (preprint)

This study examines misinformation in social networks with well-known network science metrics. We utilize an already available dataset to analyze tweets related to COVID-19 vaccinations. The methodology we use in this study includes the creation of separate networks for retweets, replies, and mentions. We utilized various centrality metrics to assess the importance of individual tweets such as centrality metrics that primarily consider the network’s topology and connectivity, taking into account factors such as the number of connections, the importance of connections , information flow, and indirect influences. One of our objectives is to determine the length of time that tweets linked to unreliable sources exist within a network through reactions. The empirical results of our study reveal a noteworthy association: tweets that have longer durations tend to be posted by influential accounts within the network, in contrast to tweets that have shorter durations and demonstrate reduced influence. Our study contributes to the advancement of our understanding of the dynamics of misinformation spread, by our results regarding misinforma-tion persistence within social networks. Our observations show potential for informing approaches designed to address misinformation and disin-formation, especially in the setting of public health emergencies like as the current COVID-19 outbreak.

Ipsilateral or contralateral boosting of mice with mRNA vaccines confers equivalent immunity and protection against a SARS-CoV-2 Omicron strain (preprint)

Boosting with mRNA vaccines encoding variant-matched spike proteins has been implemented to mitigate their reduced efficacy against emerging SARS-CoV-2 variants. Nonetheless, in humans, it remains unclear whether boosting in the ipsilateral or contralateral arm with respect to the priming doses impacts immunity and protection. Here, we boosted K18-hACE2 mice with either monovalent mRNA-1273 (Wuhan-1 spike) or bivalent mRNA-1273.214 (Wuhan-1 + BA.1 spike) vaccine in the ipsilateral or contralateral leg relative to a two-dose priming series with mRNA-1273. Boosting in the ipsilateral or contralateral leg elicited equivalent levels of serum IgG and neutralizing antibody responses against Wuhan-1 and BA.1. While contralateral boosting with mRNA vaccines resulted in expansion of spike-specific B and T cells beyond the ipsilateral draining lymph node (DLN) to the contralateral DLN, administration of a third mRNA vaccine dose at either site resulted in similar levels of antigen-specific germinal center B cells, plasmablasts/plasma cells, T follicular helper cells and CD8+ T cells in the DLNs and the spleen. Furthermore, ipsilateral and contralateral boosting with mRNA-1273 or mRNA-1273.214 vaccines conferred similar homologous or heterologous immune protection against SARS-CoV-2 BA.1 virus challenge with equivalent reductions in viral RNA and infectious virus in the nasal turbinates and lungs. Collectively, our data show limited differences in B and T cell immune responses after ipsilateral and contralateral site boosting by mRNA vaccines that do not substantively impact protection against an Omicron strain.

Evaluation of the Potential of Urinary Volatilomic Patterns of COVID-19 Patients Infected With SARS-CoV-2 for Disease Diagnosis. An Exploratory Study (preprint)

To assess if SARS-CoV-2 infection induces changes in the urinary volatilomic fingerprint able to be used in the non-invasive COVID-19 diagnosis and management, urine samples of SARS-CoV-2 infected patients (62), recovered COVID-19 patients (30), and non-infected individuals (41) were analysed using solid-phase microextraction technique in headspace mode, combined with gas chromatography hyphenated with mass spectrometry (HS-SPME/GC-MS). In total, 101 volatile organic metabolites (VOMs) from 13 chemical families were identified, being terpenes, phenolic compounds, norisoprenoids, and ketones the most represented groups. Overall, a decrease in the levels of terpenes and phenolic compounds was observed in the control group, whereas norisoprenoids and ketones showed a significant increase. In turn, a remarkable increase was noticed in norisoprenoids and ketones and a milder increase in alcohols, furanic, and sulfur compounds in the recovery group than in the COVID-19 group. Multivariate statistical analysis identified sets of VOMs with the potential to constitute volatile signatures for COVID-19 development and progression. These signatures are composed of D-carvone, 3-methoxy-5-(trifluoromethyl)aniline (MTA), 1,1,6-trimethyl-dihydronaphthalene (TDN), 2-heptanone, and 2,5,5,8a-tetramethyl-1,2,3,5,6,7,8,8-octahydro-1-naphthalenyl ester acetate (TONEA) for COVID-19 infection and nonanoic acid, α-terpinene, β-damascenone, α-isophorone, and trans-furan linalool for patients recovering from the disease. This study provides evidence that changes in the urinary volatilomic profile triggered by SARS-CoV-2 infection constitute a promising and valuable screening and/or diagnostic and management tool for COVID-19 in clinical environment.

Multi-ancestry GWAS of diarrhea during acute SARS-CoV2 infection identifies multiple novel loci and contrasting etiological roles of irritable bowel syndrome subtypes (preprint)

A substantial proportion of acute SARSCoV2 infection cases exhibit gastrointestinal symptoms, yet the genetic determinants of these extrapulmonary manifestations are poorly understood. Using survey data from 239,866 individuals who tested positively for SARSCoV2, we conducted a multi-ancestry GWAS of 80,289 cases of diarrhea occurring during acute COVID19 infection (33.5%). Six loci (CYP7A1, LZFTl1/CCR9, TEME182, NALCN, LFNG, GCKR) met genomewide significance in a trans-ancestral analysis. The top significant GWAS hit mapped to the CYP7A1 locus, which plays an etiologic role in bile acid metabolism and is in high LD (r2= 0.93) with the SDCBP gene, which was previously implicated in antigen processing and presentation in the COVID-19 context. Another association was observed with variants in the LZTFL1/CCR9 region, which is a known locus for COVID19 susceptibility and severity. PheWAS showed a shared association across three of the six SNPs with irritable bowel syndrome (IBS) and its subtypes. Mendelian randomization showed that genetic liability to IBS-diarrhea increased (OR=1.40,95%,CI[1.33,1.47]), and liability to IBS-constipation decreased (OR=0.86, 95%CI[0.79,0.94]) the relative odds of experiencing COVID19+ diarrhea. Our genetic findings provide etiological insights into the extrapulmonary manifestations of acute SARSCoV2 infection.

Molecular epidemiology of invasive Group A Streptococcal infections before and after the COVID-19 pandemic in Switzerland (preprint)

Group A Streptococcus (GAS, aka Streptococcus pyogenes) poses a significant public health concern, causing a diverse spectrum of infections with high mortality rates. Following the COVID-19 pandemic, a resurgence of invasive GAS (iGAS) infections has been documented, necessitating efficient outbreak detection methods. Whole genome sequencing (WGS) serves as the gold standard for GAS molecular typing, albeit constrained by time and costs. This study aimed to characterize the postpandemic increased prevalence of iGAS on the molecular epidemiological level in order to assess whether new, more virulent variants have emerged, as well as to assess the performance of the rapid and cost-effective Fourier-transform infrared (FTIR) spectroscopy as an alternative to WGS for detecting and characterizing GAS transmission routes. A total of 66 iGAS strains isolated from nine Swiss hospitals during the COVID-19 post-pandemic increased GAS prevalence were evaluated and compared to 15 strains collected before and 12 during the COVID-19 pandemic. FT-IR measurements and WGS were conducted for network analysis. Demographic, clinical, and epidemiological data were collected. Skin and soft tissue infection was the most common diagnosis, followed by primary bacteremia and pneumonia. Viral co-infections were found in 25% of cases and were significantly associated with more severe disease requiring intensive care unit admission. WGS analysis did not reveal emerging GAS genetic distinct variants after the COVID-19 pandemic, indicating the absence of a pandemic-induced shift. FT-IR spectroscopy exhibited limitations in differentiating genetically distant GAS strains, yielding poor overlap with WGS-derived clusters. The emm1/ST28 gebotype was predominant in our cohort and was associated with five of the seven deaths recorded, in accordance with the molecular epidemiological data before the pandemic. Additionally, no notable shift in antibiotic susceptibility patterns was observed. Our data suggest that mainly non-pathogen related factors contributed to the recent increased prevalence of iGAS.

Mutational pressure drives enhanced release of proteasome-generated public CD8+ T cell epitopes from SARS-CoV-2 RBD of Omicron and its current lineages (preprint)

The COVID-19 pandemic was the most dramatic in the newest history with nearly 7 million deaths and global impact on mankind. Here we report binding index of 305 HLA class I molecules from 18,771 unique haplotypes of 28,104 individuals to 821 peptides experimentally observed from spike protein RBD of 5 main SARS-CoV-2 strains hydrolyzed by human proteasomes with constitutive and immune catalytic phenotypes. Our data read that 4 point mutations in the hACE2-binding region RBD496-513 of Omicron B1.1.529 strain results in a dramatic increase of proteasome-mediated release of two public HLA class I epitopes. Global population analysis of HLA class I haplotypes, specific to these peptides, demonstrated decreased mortality of human populations enriched in these haplotypes from COVID-19 after but not before December, 2021, when Omicron became dominant SARS-CoV-2 strain. Noteworthy, currently circulating BA.2.86 and JN.1 lineages contain no amino acid substitutions in RBD496-513 thus preserving identified core epitopes.

Single-cell analysis of lung epithelial cells reveals age and cell population-specific responses to SARS-CoV-2 infection in ciliated cells (preprint)

The ability of SARS-CoV-2 to evade antiviral immune signaling in the airway contributes to the severity of COVID-19 disease. Additionally, COVID-19 is influenced by age and has more severe presentations in older individuals. This raises questions about innate immune signaling as a function of lung development and age. Therefore, we investigated the transcriptome of different cell populations of the airway epithelium using pediatric and adult lung tissue samples from the LungMAP Human Tissue Core Biorepository. Specifically, lung lobes were digested and cultured into a biomimetic model of the airway epithelium on an air-liquid interface. Cells were then infected with SARS-CoV-2 and subjected to single-cell RNA sequencing. Transcriptional profiling and differential expression analysis were carried out using Seurat. The clustering analysis identified several cell populations: club cells, proliferating epithelial cells, multiciliated precursor cells, ionocytes, and two biologically distinct clusters of ciliated cells (FOXJ1high and FOXJ1low). Interestingly, the two ciliated cell clusters showed different infection rates and enrichment of processes involved in ciliary biogenesis and function; we observed a cell-type-specific suppression of innate immunity in infected cells from the FOXJ1low subset. We also identified a significant number of genes that were differentially expressed in lung cells derived from children as compared to adults, suggesting the differential pathogenesis of SARS-CoV-2 infection in children versus adults. We discuss how this work can be used to identify drug targets to modulate molecular signaling cascades that mediate an innate immune response and begin to understand differences in COVID-19 outcomes for pediatric vs. adult populations.

Broadly neutralizing antibodies against emerging delta-coronaviruses (preprint)

Porcine deltacoronavirus (PDCoV) spillovers were recently detected in children with acute undifferentiated febrile illness, underscoring recurrent zoonoses of divergent coronaviruses. To date, no vaccines or specific therapeutics are approved for use in humans against PDCoV. To prepare for possible future PDCoV epidemics, we isolated human spike (S)-directed monoclonal antibodies from transgenic mice and found that two of them, designated PD33 and PD41, broadly neutralized a panel of PDCoV variants. Cryo-electron microscopy structures of PD33 and PD41 in complex with the PDCoV receptor-binding domain and S ectodomain trimer provide a blueprint of the epitopes recognized by these mAbs, rationalizing their broad inhibitory activity. We show that both mAbs inhibit PDCoV by competitively interfering with host APN binding to the PDCoV receptor-binding loops, explaining the mechanism of viral neutralization. PD33 and PD41 are candidates for clinical advancement, which could be stockpiled to prepare for possible future PDCoV outbreaks.

Bioinformatics-Based Design Strategy and Development of an Antigen Test for SARS-CoV-2 Nucleocapsid Protein (preprint)

The continuing mutability of the SARS-CoV-2 virus can result in failures of diagnostic assays. To address this, we describe a generalizable bioinformatics-to-biology pipeline developed for calibration and quality assurance of inactivated SARS-COV-2 variant panels provided to Radical Acceleration of Diagnostics programs (RADx)-radical program awardees. Heuristic genetic analysis based on variant-defining mutations demonstrated the lowest genetic variance in the Nucleocapsid protein (Np)- C-terminal domain (CTD) across all SARS-COV-2 variants. We then employed the Shannon entropy method on (Np) sequences collected from the major variants, verifying the CTD with lower entropy (less prone to mutations) than other Np regions. Polyclonal and monoclonal antibodies were raised against this target CTD antigen and used to develop an Enzyme-linked immunoassay (ELISA) test for SARS-CoV-2. Blinded Viral Quality Assurance (VQA) panels comprising of UV-inactivated SARS CoV-2 variants (XBB.1.5, BF.7, BA.1, B.1.617.2, and WA1) and distractor respiratory viruses (CoV 229E, CoV OC43, RSV A2, RSV B, IAV H1N1, and IBV) were assembled by the RADx-rad Diagnostics core and tested using the ELISA described here. The assay tested positive for all variants with high sensitivity (Limit of Detection: 1.72-8.78 ng/mL) and negative for the distractor virus panel. Epitope mapping for the monoclonal antibodies identified a twenty amino acid antigenic peptide on the Np-CTD that an in-silico program also predicted for the highest antigenicity. This work provides a template for a bioinformatics pipeline to select genetic regions with a low propensity for mutation (low Shannon entropy) to develop robust ‘pan-variant’ antigen-based assays for viruses prone to high mutational rates.

Community-Based View on Diagnostic Imaging at the End of COVID-19 Pandemic: Online Survey-Assisted Study (preprint)

Background: Online survey-based observational cross-sectional study aimed at elucidating experience and attitudes of unstructured population regarding diagnostic imaging. Methods: Invitations to participate were distributed using mixed-mode design to deidentified residents aged 18 years and older. Main outcome measures included morbidity structure and incidence of diagnostic imaging administrations. Results: Respondents (n = 1069) aged 44.3 ± 14.4 years; 32.8% suffered from cardiovascular diseases (CVD); 9.5% had chronic respiratory pathology; 28.9% considered themselves healthy. Respondents with COVID-19 history (49.7%) reported higher rates of computed tomography (CT) (p < .0001), magnetic resonance imaging (MRI) (p < .001), and ultrasound (p < .05). COVID-19 history in CVD respondents shifted imaging administrations towards CT and MRI (p < .05). Every tenth respondent received MRI, CT, and ultrasound on paid basis; 29.0% could not pay for diagnostic procedures; 13.1% reported unavailable MRI. Professional status significantly affected the pattern of diagnostic modalities (p < .05). MRI and CT availability differed between respondents in urban and rural areas (p < .0001). History of technogenic events predisposed responders to overestimate diagnostic value of fluorography (p < .05). Conclusions: Preparedness to future pandemics requires development of community-based outreach programs focusing on people's awareness regarding medical imaging safety and diagnostic value.

The 10-year health impact, economic impact, and return on investment of the South African molecular diagnostics programme for HIV, Tuberculosis and SARS-CoV-2 (preprint)

To ensure there is adequate investment into diagnostics, an understanding of the magnitude of impact and return on investment is necessary. We therefore sought to understand the health and economic impacts of the molecular diagnostic programme in South Africa, to deepen the under-standing on the broad value of diagnostics and guide future healthcare investments. We calcu-lated the 10-year (where data were available) total cost and DALYs averted associated with molecular diagnosis of molecular TB testing (2013-2022), HIV viral load monitoring (2013-2022), early infant diagnosis of HIV infection (2013-2022), and SARS-CoV-2 testing (2020-2022). We then calculated the economic value associated with those health gains and subsequent return on investment. Since the inception of the molecular diagnostics programme in South Africa, 3,035,782 DALYs have been averted as a direct consequence of this pro-gramme. This has generated an estimated $20.5 billion in economic value due to these health gains. The return on investment varied by specific diagnostic test (19.0 for tuberculosis, 1.4 for HIV viral load testing, 64.8 for early infant diagnosis of HIV, and 2.5 for SARS-CoV-2), for an average of 9.9 for the entire molecular diagnostics programme between 2013 and 2022- or $9.9 of value for each $1 invested. The molecular diagnostics programme in South Africa gen-erated a significant amount of health gains and economic value associated with these health gains, and the return-on-investment rivals other high-impact public health interventions such as childhood vaccination. Consequently, the molecular diagnostics programme in South Africa is highly impactful, and will continue to be an excellent investment of South African public health expenditure.

A Review of Graph Neural Networks in Epidemic Modeling (preprint)

Since the onset of the COVID-19 pandemic, there has been a growing interest in studying epidemiological models. Traditional mechanistic models mathematically describe the transmission mechanisms of infectious diseases. However, they often fall short when confronted with the growing challenges of today. Consequently, Graph Neural Networks (GNNs) have emerged as a progressively popular tool in epidemic research. In this paper, we endeavor to furnish a comprehensive review of GNNs in epidemic tasks and highlight potential future directions. To accomplish this objective, we introduce hierarchical taxonomies for both epidemic tasks and methodologies, offering a trajectory of development within this domain. For epidemic tasks, we establish a taxonomy akin to those typically employed within the epidemic domain. For methodology, we categorize existing work into \textit{Neural Models} and \textit{Hybrid Models}. Following this, we perform an exhaustive and systematic examination of the methodologies, encompassing both the tasks and their technical details. Furthermore, we discuss the limitations of existing methods from diverse perspectives and systematically propose future research directions. This survey aims to bridge literature gaps and promote the progression of this promising field. We hope that it will facilitate synergies between the communities of GNNs and epidemiology, and contribute to their collective progress.

CCQM-P199b: Interlaboratory comparability study of SARS-CoV-2 RNA copy number quantification (preprint)

Nucleic acid amplification tests including reverse transcription-quantitative PCR (RT-qPCR) are used to detect RNA from Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of the Coronavirus disease 2019 (COVID-19) pandemic. Standardized measurements of RNA can facilitate comparable performance of laboratory tests in the absence of existing reference measurement systems early on in a pandemic. Interlaboratory study CCQM-P199b 'SARS-CoV-2 RNA copy number quantification' was designed to test the fitness-for-purpose of developed candidate reference measurement procedures (RMPs) for SARS-CoV-2 genomic targets in purified RNA materials, and was conducted under the auspices of the Consultative Committee for Amount of Substance: Metrology in Chemistry and Biology (CCQM) to evaluate the measurement comparability of national metrology institutes (NMIs) and designated institutes (DIs), thereby supporting international standardization. Twenty-one laboratories participated in CCQM-P199b and were requested to report the RNA copy number concentration, expressed in number of copies per microliter, of the SARS-CoV-2 nucleocapsid (N) gene partial region (NC_045512.2: 28274-29239) and envelope (E) gene (NC_045512.2: 26245-26472) (optional measurement) in samples consisting of in vitro transcribed RNA or purified RNA from lentiviral constructs. Materials were provided in two categories: lower concentration (approximately 10 x 1 - 10 x 4/uL in aqueous solution containing human RNA background) and high concentration (approximately 10 x 9/uL in aqueous solution without any other RNA background). For the measurement of N gene concentration in the lower concentration study materials, the majority of laboratories (n = 17) used one-step reverse transcription-digital PCR (RT-dPCR), with three laboratories applying two-step RT-dPCR and one laboratory RT-qPCR. Sixteen laboratories submitted results for E gene concentration. Reproducibility (% CV or equivalent) for RT-dPCR ranged from 19 % to 31 %. Measurements of the high concentration study material by orthogonal methods (isotope dilution-mass spectrometry and single molecule flow cytometry) and a gravimetrically linked lower concentration material were in a good agreement, suggesting a lack of overall bias in RT-dPCR measurements. However methodological factors such as primer and probe (assay) sequences, RT-dPCR reagents and dPCR partition volume were found to be potential sources of interlaboratory variation which need to be controlled when applying this technique. This study demonstrates that the accuracy of RT-dPCR is fit-for-purpose as a RMP for viral RNA target quantification in purified RNA materials and highlights where metrological approaches such as the use of in vitro transcribed controls, orthogonal methods and measurement uncertainty evaluation can support standardization of molecular methods.