Enterovirus D68 outbreak detection through a syndromic disease epidemiology network

Clinical and molecular epidemiology of enterovirus D68 from 2013 to 2020 in Shanghai

Enterovirus D68 (EV-D68) is an emerging pathogen that has caused outbreaks of severe respiratory disease worldwide, especially in children. We aim to investigate the prevalence and genetic characteristics of EV-D68 in children from Shanghai. Nasopharyngeal swab or bronchoalveolar lavage fluid samples collected from children hospitalized with community-acquired pneumonia were screened for EV-D68. Nine of 3997 samples were EV-D68-positive. Seven of nine positive samples were sequenced and submitted to GenBank. Based on partial polyprotein gene (3D) or complete sequence analysis, we found the seven strains belong to different clades and subclades, including three D1 (detected in 2013 and 2014), one D2 (2013), one D3 (2019), and two B3 (2014 and 2018). Overall, we show different clades and subclades of EV-D68 spread with low positive rates (0.2%) among children in Shanghai between 2013 and 2020. Amino acid mutations were found in the epitopes of the VP1 BC and DE loops and C-terminus; similarity analysis provided evidence for recombination as an important mechanism of genomic diversification. Both single nucleotide mutations and recombination play a role in evolution of EV-D68. Genetic instability within these clinical strains may indicate large outbreaks could occur following cumulative mutations.

Molecular Amplification and Cell Culturing Efficiency for Enteroviruses' Detection in Cerebrospinal Fluids of Algerian Patients Suffering from Meningitis

Enteroviruses (EVs) represent a major cause of viral meningitis, being responsible for nearly 1 billion infections each year worldwide. Several techniques were developed to obtain better diagnostic results of EV infections. Herein, we evaluated the efficiency of EV detection through isolation on both Rhabdomyosarcoma (RD) and Vero cell line cultures, conventional reverse transcription-polymerase chain reaction (RT-PCR) and real-time RT-PCR. Thus, 50 cerebrospinal fluid (CSF) samples belonging to patients suspected to have viral meningitis in northern Algeria were collected, anonymously numbered from 1 to 50 and subjected to the above-mentioned techniques for EV detection. Using real-time RT-PCR, 34 CSF samples were revealed to be positive for viral origin of meningitis (68%). Thirteen of them were positive when the conventional RT-PCR was used (26%), and only three samples gave positive results when the cell culture technique was used (6%). Surprisingly, two cell culture-positive CSF samples, namely, 31 and 39, were negative using RT-PCR directly on the original samples. However, they turned to be positive when amplification was carried out on their corresponding cell culture supernatant. The cell-cultured viral isolates were then identified by sequencing their viral genome's VP1 regions. All of them were revealed to belong to the echovirus 27 strain. This investigation demonstrates that RT-PCR techniques are often more sensitive, accurate and much faster, providing reliable results within a clinically acceptable timeframe. However, viral isolation on cell cultures remains crucial to obtain enough viral load for serological tests or even to avoid the rare, but existing, false negative PCR.

Conventional and advanced detection techniques of foodborne pathogens: A comprehensive review

Foodborne pathogens are a major public health concern and have a significant economic impact globally. From harvesting to consumption stages, food is generally contaminated by viruses, parasites, and bacteria, which causes foodborne diseases such as hemorrhagic colitis, hemolytic uremic syndrome (HUS), typhoid, acute, gastroenteritis, diarrhea, and thrombotic thrombocytopenic purpura (TTP). Hence, early detection of foodborne pathogenic microbes is essential to ensure a safe food supply and to prevent foodborne diseases. The identification of foodborne pathogens is associated with conventional (e.g., culture-based, biochemical test-based, immunological-based, and nucleic acid-based methods) and advances (e.g., hybridization-based, array-based, spectroscopy-based, and biosensor-based process) techniques. For industrial food applications, detection methods could meet parameters such as accuracy level, efficiency, quickness, specificity, sensitivity, and non-labor intensive. This review provides an overview of conventional and advanced techniques used to detect foodborne pathogens over the years. Therefore, the scientific community, policymakers, and food and agriculture industries can choose an appropriate method for better results.

A Hierarchical Genotyping Framework Using DNA Melting Temperatures Applied to Adenovirus Species Typing

Known genetic variation, in conjunction with post-PCR melting curve analysis, can be leveraged to provide increased taxonomic detail for pathogen identification in commercial molecular diagnostic tests. Increased taxonomic detail may be used by clinicians and public health decision-makers to observe circulation patterns, monitor for outbreaks, and inform testing practices. We propose a method for expanding the taxonomic resolution of PCR diagnostic systems by incorporating a priori knowledge of assay design and sequence information into a genotyping classification model. For multiplexed PCR systems, this framework is generalized to incorporate information from multiple assays to increase classification accuracy. An illustrative hierarchical classification model for human adenovirus (HAdV) species was developed and demonstrated ~95% cross-validated accuracy on a labeled dataset. The model was then applied to a near-real-time surveillance dataset in which deidentified adenovirus detected patient test data from 2018 through 2021 were classified into one of six adenovirus species. These results show a marked change in both the predicted prevalence for HAdV and the species makeup with the onset of the COVID-19 pandemic. HAdV-B decreased from a pre-pandemic predicted prevalence of up to 40% to less than 5% in 2021, while HAdV-A and HAdV-F species both increased in predicted prevalence.

Evaluation of the QIAstat-Dx RP2.0 and the BioFire FilmArray RP2.1 for the Rapid Detection of Respiratory Pathogens Including SARS-CoV-2

Point-of-care syndromic panels allow for simultaneous and rapid detection of respiratory pathogens from nasopharyngeal swabs. The clinical performance of the QIAstat-Dx Respiratory SARS-CoV-2 panel RP2.0 (QIAstat-Dx RP2.0) and the BioFire FilmArray Respiratory panel RP2.1 (BioFire RP2.1) was evaluated for the detection of SARS-CoV-2 and other common respiratory pathogens. A total of 137 patient samples were retrospectively selected based on emergency department admission, along with 33 SARS-CoV-2 positive samples tested using a WHO laboratory developed test. The limit of detection for SARS-CoV-2 was initially evaluated for both platforms. The QIAstat-Dx RP2.0 detected SARS-CoV-2 at 500 copies/mL and had a positive percent agreement (PPA) of 85%. The BioFire RP2.1 detected SARS-CoV-2 at 50 copies/mL and had a PPA of 97%. Both platforms showed a negative percent agreement of 100% for SARS-CoV-2. Evaluation of analytical specificity from a range of common respiratory targets showed a similar performance between each platform. The QIAstat-Dx RP2.0 had an overall PPA of 82% (67–100%) in clinical samples, with differences in sensitivity depending on the respiratory target. Both platforms can be used to detect acute cases of SARS-CoV-2. While the QIAstat-Dx RP2.0 is suitable for detecting respiratory viruses within a clinical range, it has less analytical and clinical sensitivity for SARS-CoV-2 compared to the BioFire RP2.1.

Epidemiological dynamics of enterovirus D68 in the United States and implications for acute flaccid myelitis

Acute flaccid myelitis (AFM) recently emerged in the United States as a rare but serious neurological condition since 2012. Enterovirus D68 (EV-D68) is thought to be a main causative agent, but limited surveillance of EV-D68 in the United States has hampered the ability to assess their causal relationship. Using surveillance data from the BioFire Syndromic Trends epidemiology network in the United States from January 2014 to September 2019, we characterized the epidemiological dynamics of EV-D68 and found latitudinal gradient in the mean timing of EV-D68 cases, which are likely climate driven. We also demonstrated a strong spatiotemporal association of EV-D68 with AFM. Mathematical modeling suggested that the recent dominant biennial cycles of EV-D68 dynamics may not be stable. Nonetheless, we predicted that a major EV-D68 outbreak, and hence an AFM outbreak, would have still been possible in 2020 under normal epidemiological conditions. Nonpharmaceutical intervention efforts due to the ongoing COVID-19 pandemic are likely to have reduced the sizes of EV-D68 and AFM outbreaks in 2020, illustrating the broader epidemiological impact of the pandemic.

The Effects of Social Distancing Policies on Non-SARS-CoV-2 Respiratory Pathogens

Background

The initial focus of the US public health response to coronavirus disease 2019 (COVID-19) was the implementation of numerous social distancing policies. While COVID-19 was the impetus for imposing these policies, it is not the only respiratory disease affected by their implementation. This study aimed to assess the impact of social distancing policies on non-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) respiratory pathogens typically circulating across multiple US states.

Methods

Linear mixed-effect models were implemented to explore the effects of 5 social distancing policies on non-SARS-CoV-2 respiratory pathogens across 9 states from January 1 through May 1, 2020. The observed 2020 pathogen detection rates were compared week by week with historical rates to determine when the detection rates were different.

Results

Model results indicate that several social distancing policies were associated with a reduction in total detection rate, by nearly 15%. Policies were associated with decreases in pathogen circulation of human rhinovirus/enterovirus and human metapneumovirus, as well as influenza A, which typically decrease after winter. Parainfluenza viruses failed to circulate at historical levels during the spring. The total detection rate in April 2020 was 35% less than the historical average. Many of the pathogens driving this difference fell below the historical detection rate ranges within 2 weeks of initial policy implementation.

Conclusions

This analysis investigated the effect of multiple social distancing policies implemented to reduce transmission of SARS-CoV-2 on non-SARS-CoV-2 respiratory pathogens. These findings suggest that social distancing policies may be used as an impactful public health tool to reduce communicable respiratory illness.

Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin-angiotensin-aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.

Epidemiological dynamics of enterovirus D68 in the US: implications for acute flaccid myelitis

The lack of active surveillance for enterovirus D68 (EV-D68) in the US has hampered the ability to assess the relationship with predominantly biennial epidemics of acute flaccid myelitis (AFM), a rare but serious neurological condition. Using novel surveillance data from the BioFire® Syndromic Trends (Trend) epidemiology network, we characterize the epidemiological dynamics of EV-D68 and demonstrate strong spatiotemporal association with AFM. Although the recent dominant biennial cycles of EV-D68 dynamics may not be stable, we show that a major EV-D68 epidemic, and hence an AFM outbreak, would still be possible in 2020 under normal epidemiological conditions. Significant social distancing due to the ongoing COVID-19 pandemic could reduce the size of an EV-D68 epidemic in 2020, illustrating the potential broader epidemiological impact of the pandemic.

Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused thousands of deaths worldwide, including >18,000 in New York City (NYC) alone. The sudden emergence of this pandemic has highlighted a pressing clinical need for rapid, scalable diagnostics that can detect infection, interrogate strain evolution, and identify novel patient biomarkers. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs, plus a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, bacterial, and viral profiling. We applied both technologies across 857 SARS-CoV-2 clinical specimens and 86 NYC subway samples, providing a broad molecular portrait of the COVID-19 NYC outbreak. Our results define new features of SARS-CoV-2 evolution, nominate a novel, NYC-enriched viral subclade, reveal specific host responses in interferon, ACE, hematological, and olfaction pathways, and examine risks associated with use of ACE inhibitors and angiotensin receptor blockers. Together, these findings have immediate applications to SARS-CoV-2 diagnostics, public health, and new therapeutic targets.