Laboratory Network Research Articles

Scalable solutions for global health: the SalivaDirect model

The COVID-19 pandemic caught the world unprepared. Large-scale testing efforts were urgently needed, and diagnostic strategies had to rapidly evolve in response to unprecedented worldwide demand. However, the rollout of diagnostic testing and screening for SARS-CoV-2 was often impeded by logistical challenges, including regulatory delays, workforce shortages, laboratory bottlenecks, and supply chain disruptions. Recognizing these hurdles early on, we developed a testing approach that supported frequent, repeat testing, particularly as communities reopened. We hypothesized and experimentally demonstrated that saliva was a suitable specimen for the detection of SARS-CoV-2. This finding was advanced into the development of open-source, extraction-free reverse transcription polymerase chain reaction protocols using readily available, “off-the-shelf” reagents and equipment for the direct detection of SARS-CoV-2 in saliva (“SalivaDirect’’). Working with the US Food and Drug Administration (FDA), we established a novel regulatory framework wherein the FDA granted Emergency Use Authorization to Yale University to offer the SalivaDirect test protocol to high-complexity diagnostic laboratories (as designated by the Clinical Laboratory Improvement Amendments) with quality oversight provided by Yale. This grew into a network of more than 200 labs across the United States that, as of May 2024, resulted in over 6.5 million SARS-CoV-2 tests. By making the protocol flexible and open-source, laboratories were able to rapidly and economically scale testing using a simple, self-collected saliva specimen. Additionally, fostering a national network of laboratories enabled real-time exchanges, problem solving, and the development of community best practices. Preparing for the next pandemic, or simply the next seasonal epidemic, the SalivaDirect model of deploying a readily available, expandable solution and accompanying network provides a proven method for the successful implementation of pathogen testing in the United States and globally.

3D Digital Modeling Technology for Thermal Power Plant Boilers Based on Digital Twins

With the rapid advancement of Digital Twins (DTs) technologies, they have emerged as viable solutions for enhancing the control and optimization of thermal power combustion processes. This paper presents a pioneering approach that leverages DTs to revolutionize the combustion process control system within thermal power generating units. Focused on bridging the physical and digital realms, our research establishes DTs of the combustion process control system (CPCS), situated within the Networked Control System Laboratory (NCSLab). We propose a novel five-dimensional (5D) DTs model encompassing the physical, data, service, connection, and virtual models, thereby facilitating a comprehensive fusion of physical and digital information. By analyzing the demands and technical intricacies of the combustion process control system, we design and implement a virtual 3D model, enriching the visualization and analytical capabilities of the DT environment. Furthermore, through controlled experiments on the combustion process and rigorous comparison with offline simulations, we validate the efficacy and feasibility of our approach. Importantly, our research opens avenues for future exploration, particularly in harnessing industrial real-time data to drive the virtual 3D model. Through the integration of Artificial Intelligence (AI) techniques such as Deep Learning, we elevate the capabilities of our DT framework. This enhanced predictive analytics, dynamic optimization, human–machine interaction, and virtual model realism. This research contributes to the advancement of DT technology in the context of thermal power plants and holds promise for driving innovation and efficiency across diverse industrial sectors.

Successful Collaborations that Resulted in Increased U.S. Diagnostic Testing During the 2022 Mpox Outbreak.

The first case of mpox was detected in the United States in a Laboratory Response Network (LRN) laboratory at the Massachusetts Department of Public Health on May 17, 2022. Through previous years of smallpox preparedness efforts by the United States government, testing capacity in LRN laboratories across the United States utilizing the FDA-cleared Centers for Disease Control and Prevention (CDC) Non-variola orthopoxvirus (NVO) test was approximately 6000 tests weekly across the nation prior to the mpox outbreak. By early June 2022, the LRN laboratories had capacity to perform up to 8000 tests per week. As the outbreak expanded, cases were identified in every United States state, peaking at~3000 cases per week nationally in August 2022. Although NVO testing capacity in LRN laboratories exceeded national mpox testing demand overall, LRN testing access in some areas was challenged and test expansion was necessary. CDC engaged with partners and select commercial laboratories early to increase diagnostic testing access by allowing these commercial laboratories to utilize the NVO test. The expansion of testing to commercial laboratories increased testing availability, capacity, and volume nationwide. This was the first time that CDC shared an FDA 510k-cleared molecular test with commercial laboratories to support a public health emergency. Extensive efforts were made to ensure the CDC NVO test was used appropriately in the private sector and that the transfer process met regulatory requirements. These novel methods to expand NVO testing to commercial laboratories increased national testing capacity to 80000 mpox tests/week. Test volumes among these laboratories never exceeded this expanded capacity. The rapid increase in the nation's testing capacity, in conjunction and coordination with other public and private health efforts, helped to detect cases rapidly. These actions demonstrated the importance of highly functional and efficient public health and private sector partnerships for responding to public health emergencies.

Update on Vaccine-Derived Poliovirus Outbreaks - Worldwide, January 2023-June 2024.

Circulating vaccine-derived polioviruses (cVDPVs) can emerge and lead to outbreaks of paralytic polio as well as asymptomatic transmission in communities with a high percentage of undervaccinated children. Using data from the World Health Organization Polio Information System and Global Polio Laboratory Network, this report describes global polio outbreaks due to cVDPVs during January 2023-June 2024 and updates previous reports. During the reporting period, 74 cVDPV outbreaks were detected in 39 countries or areas (countries), predominantly in Africa. Among these 74 cVDPV outbreaks, 47 (64%) were new outbreaks, detected in 30 (77%) of the 39 countries. Three countries reported cVDPV type 1 (cVDPV1) outbreaks and 38 countries reported cVDPV type 2 (cVDPV2) outbreaks; two of these countries reported cocirculating cVDPV1 and cVDPV2. In the 38 countries with cVDPV2 transmission, 70 distinct outbreaks were reported. In 15 countries, cVDPV transmission has lasted >1 year into 2024. In Nigeria and Somalia, both countries with security-compromised areas, persistent cVDPV2 transmission has spread to neighboring countries. Delayed implementation of outbreak response campaigns and low-quality campaigns have resulted in further international spread. Countries can control cVDPV outbreaks with timely allocation of resources to implement prompt, high-quality responses after outbreak confirmation. Stopping all cVDPV transmission requires effectively increasing population immunity by overcoming barriers to reaching children.

A-207 Enhancing Healthcare Delivery Network Laboratories: The Role of Third-Party Consultants in Benchmarking and Reviewing RFP Results

Abstract Background Healthcare delivery networks, particularly laboratory services, play a critical role in patient care and diagnosis. However, ensuring the quality and efficiency of these services can be challenging due to the complex and dynamic nature of healthcare systems. Third-party consultants offer valuable expertise in benchmarking and reviewing Request for Proposal (RFP) results, which can improve the quality and cost-effectiveness of laboratory services within healthcare networks. Methods To evaluate the role of third-party consultants in enhancing healthcare delivery network laboratories, the author conducted surveys to 50 laboratory leaders with a 50% response rate and analyzed the following aspects: Benchmarking: Comparing laboratory performance metrics with industry best practices and peer institutions to identify areas for improvement. RFP Review: Utilizing subject matter experts to assess the technical and financial proposals submitted by vendors to ensure compliance with RFP requirements and to identify the most suitable vendor for the network. Emotional Procurement: Minimizing the influence of emotional factors, such as personal relationships or brand loyalty, during the RFP process. Results Improved Quality: 65% said they can save >50 hours of labor utilizing a 3rd party for RFP, thus able to focus on patient results and quality. Cost Savings: 76% of respondents said consultants can help networks reduce expenses and improve their financial performance by 10-20% above and beyond incumbent negotiations. Emotional Procurement Mitigation: While the specific statistics supporting the influence of consultants on mitigating emotional factors in procurement decisions are not readily available, the broader impact of emotions on decision-making is well-documented. Therefore, while direct statistics may be limited, the influence of emotions on procurement decisions is a recognized factor in the field of decision science and consumer behavior. Turn around time: 70% of respondents said utilizing a 3rd party can reduce the turnaround time of a sourcing event from >3 months to < 1months. Conclusions Third-party consultants can provide valuable insights and expertise in benchmarking and reviewing RFP results, leading to several benefits. They can play a crucial role in enhancing healthcare delivery network laboratories by providing valuable expertise in benchmarking, reviewing RFP results, communication and reducing turnaround time. By improving quality, reducing costs, mitigating emotional procurement based on brand loyalty, and enhancing collaboration, consultants can help networks deliver high-quality services to patients and improve their overall performance. Consultants can facilitate more focused communication and partnership development between laboratories, vendors, and other stakeholders, ensuring a seamless transition and optimal performance without scope creep. As healthcare networks continue to evolve and face new challenges, the role of third-party consultants will become increasingly important in ensuring the quality and efficiency of laboratory services, potentially resulting in $100’s of millions in cost takeout across the country.

New Model for an Open Vehicle Routing Problem to Optimize the Blood Sample Collection Process within a Network of Clinical Laboratories

New Model for an Open Vehicle Routing Problem to Optimize the Blood Sample Collection Process within a Network of Clinical Laboratories

(Key1-001) congenital disorders of glycosylation: Glycobiology at the bedside.

Congenital disorders of glycosylation (CDG) are a group of rare monogenic human disorders caused by defects in the genes encoding the proteins that generate, attach, and modify glycans, thus disrupting cellular glycosylation machinery. Over 200 CDG caused by disruptions of 189 different genes are currently known. The multi-system disease manifestations of the CDG disorders highlight the importance of glycosylation across the organ systems. Clinical manifestations of CDG tend to group among genes contributing to the same glycosylation pathways, suggesting shared pathophysiology related to the glycosylation disruptions. However, the underlying glycosylation disruptions and pathophysiologic mechanisms responsible for specific CDG clinical manifestations have been determined for only a few hypoglycosylated proteins. The Frontiers in CDG Consortium (FCDGC) is an international network of clinical sites, laboratories, and patient advocacy groups established in 2019 to improve clinical symptoms, quality of life, and life expectancy for individuals with CDG. FCDGC seeks to answer decades of unresolved questions, address knowledge gaps, develop and validate new biochemical diagnostic techniques and therapeutic biomarkers, and explore novel therapeutic options for CDG. Over the past 5years, FCDGC has launched a Natural History Study with over 300 CDG patients, discovered novel biomarkers suggesting new mechanisms of disease, and launched clinical trials aiming to restore appropriate glycosylation and targeting newly identified potential mechanisms of disease. Technical advances in glycobiology are making it increasingly possible to comprehensively catalog glycoproteomic data and to probe functional impact of altered glycosylation. My laboratory applies glycoproteomic technologies to samples from human subjects and genetic model systems to identify glycosylation abnormalities and unlock new insights from translational glycobiology. Current findings and accomplishments highlight the ongoing bottlenecks and knowledge gaps at intersections of glycobiology and clinical care requiring further investigation.

Phylo-geo haplotype network-based characterization of SARS-CoV-2 strains circulating in India (2020-2022).

Background & objectives Genetic analysis of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) strains circulating in India during 2020-2022 was carried out to understand the evolution of potentially expanding and divergent clades. Methods SARS-CoV-2 sequences (n=612) randomly selected from among the sequences of samples collected through a nationwide network of Virus Research Diagnostic Laboratories during 2020 (n=1532) and Indian sequences available in Global Initiative on Sharing All Influenza Data during March 2020-March 2022 (n=53077), were analyzed using the phylo-geo haplotype network approach with reference to the Wuhan prototype sequence. Results On haplotype analysis, 420 haplotypes were revealed from 643 segregating sites among the sequences. Haplotype sharing was noted among the strains from different geographical regions. Nevertheless, the genetic distance among the viral haplotypes from different clades could differentiate the strains into distinct haplo groups regarding variant emergence. Interpretation & conclusions The haplotype analysis revealed that the G and GR clades were co-evolved and an epicentrefor the evolution of the GH, GK and GRA clades. GH was more frequently identified in northern parts of India than in other parts, whereas GK was detected less in north India than in other parts. Thus, the network analysis facilitated a detailed illustration of the pathways of evolution and circulation of SARS-CoV-2 variants.

Two Peaks of Seasonal Influenza Epidemics - China, 2023.

Influenza is a communicable respiratory disease that causes annual epidemics and occasional unpredictable pandemics. This study examines the occurrence of two unexpected influenza peaks within the year 2023. Influenza-like illness (ILI) data were reported, and specimens of ILI were collected by designated surveillance hospitals. Positive cases were confirmed using real-time reverse transcription polymerase chain reaction (rRT-PCR) testing conducted at national surveillance network laboratories. The data were then submitted to the Chinese Influenza Surveillance Information System. From December 2022 to January 2023, influenza activity was minimal until a spring epidemic began in February, peaking in late March. The outbreak spread from the north to the south, with A(H1N1)pdm09 being the predominant strain and A(H3N2) also circulating concurrently. The positivity rate in northern and southern provincial-level administrative divisions (PLADs) reached 60.0% (week 10) and 60.2% (week 13), respectively, before dropping to below 5% from May to August. Subsequently, rates surged starting in week 41 in the south and week 44 in the north, peaking at 54.4% (week 50) and 44.0% (week 49), respectively, and remained high until the end of 2023. A(H3N2) became the prevailing strain, with a notable increase in B/Victoria lineage viruses from December, resulting in two peaks during the 2023 influenza season. The pattern of the influenza epidemic shifted due to the coronavirus disease 2019 (COVID-19) outbreak and is gradually returning to its usual seasonal and intensity patterns. It is, therefore, crucial to continuously strengthen influenza surveillance, enhance the influenza surveillance network, and lay the groundwork for advancing integrated surveillance of multiple pathogens in China.

The Global Measles and Rubella Laboratory Network Supports High-Quality Surveillance.

With 762 laboratories, the Global Measles and Rubella Laboratory Network (GMRLN) is the largest laboratory network coordinated by the World Health Organization (WHO). Like the Global Polio Laboratory Network, the GMRLN has multiple tiers, including global specialized laboratories, regional reference laboratories, national laboratories, and, in some countries, subnational laboratories. Regional networks are supervised by regional laboratory coordinators reporting to a global coordinator at WHO headquarters. Laboratories in the GMRLN have strong links to national disease control and vaccination programs. The GMRLN's goal is to support member states in obtaining timely, complete, and reliable laboratory-based surveillance data for measles and rubella as part of the strategy for achieving measles and rubella elimination. Surveillance data are reported to the national program and are included in annual reports on the status of measles and rubella elimination to national verification committees for review by regional verification commissions. Quality within the GMRLN is ensured by monitoring performance through external quality assurance programs, confirmatory and quality control testing, accreditation, and coordination of corrective action and training where needed. The overall performance of the laboratories has remained high over the years despite many challenges, particularly the COVID-19 pandemic. The GMRLN is well-positioned to support high-quality laboratory-based surveillance for measles and rubella and to transition to supporting laboratory testing for other pathogens, including vaccine-preventable diseases.

Strengthening of Vaccine-Preventable Disease (VPD) Surveillance to Enhance National Health Capacity and Security: Perspective from India.

The Government of India, in collaboration with the World Health Organization (WHO), established the National Polio Surveillance Project (NPSP) in 1997 and initiated acute flaccid paralysis (AFP) surveillance to achieve the goal of polio eradication. The WHO South-East Asia Region, comprising of 11 countries, including India, was certified as polio-free in March 2014. India was also validated to have eliminated maternal and neonatal tetanus in May 2015. Over the years, the surveillance of other vaccine-preventable diseases (VPDs) was integrated with AFP surveillance in the country. Outbreak-based measles-rubella (MR) surveillance was initiated in 2005 using AFP surveillance as a platform, case-based fever-rash (FR) surveillance started in 2021 as one of the strategies to achieve measles and rubella elimination in the country. The surveillance of diphtheria, pertussis, and neonatal tetanus was integrated with AFP surveillance in a phased manner during 2015-2022. The surveillance system for VPDs in India, supported by a laboratory network of 10 polio laboratories, 28 measles-rubella laboratories, and 20 diphtheria-pertussis laboratories, has enhanced the national health capacity and security. The setting up and expansion of the surveillance system in the country involved the important component of capacity building of personnel on various components of surveillance, including case identification, case investigation, sample collection and shipment, data analysis and public health response. These capacities have been used effectively during other emergencies, such as the recent COVID-19 pandemic, as well as during outbreaks of other diseases and natural calamities.

Applying Fuzzy Decision-Making Trial and Evaluation Laboratory and Analytic Network Process Approaches to Explore Green Production in the Semiconductor Industry

As environmental awareness grows, society emphasizes green business. Thus, semiconductor companies encompass energy-saving processes and innovative product development. This study employs the fuzzy decision-making trial and evaluation laboratory (DEMATEL) analysis method to assess the impact of four key dimensions, externalities, market orientation, green technology, and corporate social responsibility, on semiconductor companies’ green production decisions. This study uses the DEMATEL-based analytic network process (DANP) approach to rank the criteria order in green production decision-making. The results from the DEMATEL causality diagram highlight externalities as the most critical dimension influencing other dimensions of green production decisions. This study suggests that regulatory pollution punishment and subsidies emerge as the primary drivers for green production decisions. Companies adopt environmentally friendly production practices to prevent regulatory pollution penalties or reduce carbon trading costs. Additionally, the DANP results reveal that corporate image criteria in the corporate social responsibility dimension hold the utmost priority in semiconductor firms’ green production decision-making. This implies that considerations for improving a company’s image should take precedence as semiconductor companies seek shareholder support and governmental subsidies to ensure sustainable operations. Externalities arise as the secondary priority dimension in green production decision-making, aligning with the impact of externalities identified in DEMATEL findings.

Further validation of 2 nonstructural protein-specific antibody tests for diagnosis and surveillance of foot-and-mouth disease in the United States.

Foot-and-mouth disease (FMD) is a highly contagious disease of cloven-hoofed animals. FMD poses an economic threat to the livestock industry in the United States. Due to the potential use of vaccines composed of partially purified structural proteins of the FMD virus (FMDV), it is important to test samples from infected and vaccinated animals with a competitive ELISA that detects antibodies against nonstructural proteins (NSPs) of FMDV. Our study extends the diagnostic validation of the Prionics ELISA (Thermo Fisher) and the VMRD ELISA. We used diverse serum sample sets from bovine, porcine, and other cloven-hoofed animals to evaluate the analytical specificity and sensitivity, diagnostic specificity and sensitivity, and differentiation of infected from vaccinated animals (DIVA) per validation guidelines outlined by the World Organisation for Animal Health (WOAH). The 2 tests were analytically 100% accurate. The VMRD test was diagnostically more sensitive than Prionics, but Prionics was diagnostically more specific than the VMRD test. Both tests could tell if animals were infected or vaccinated. Considering these data, both VMRD and Prionics ELISAs can be used for serodetection of FMDV antibodies at the Foreign Animal Disease Diagnostic Laboratory and within the National Animal Health Laboratory Network laboratories.

Modelling transport pathways of faults with low hydraulic connectivity in mudstones with low swelling capacity

Faults in some deep mudstones have poor hydraulic connectivity owing to high normal stress on the fault planes. Designing a method for modelling solute transport pathways in such faults/fractures using available data is a critical issue vis-à-vis the safety assessment of radioactive waste disposal. In this study, faults in deep siliceous mudstones with low swelling capacity are investigated using cross-hole hydraulic and tracer tests between two boreholes. The water pressures observed during the hydraulic test are reproduced via hydraulic simulations, assuming a one-dimensional (1D) flow channel with a length 8–80 times the linear distance (4.5 m) between the two borehole test sections. This flow channel length indicates a tortuosity remarkably higher than that previously reported in discrete fracture network simulations and laboratory experiments using a single fracture (i.e. 1–5). Advection–dispersion simulations using a pipe model with a tortuosity of 8–80 reproduces a time series of tracer concentrations observed during the tracer test. The radius of the pipe simulated in the tracer test was 7–39 times the flow channel radius estimated via the hydraulic test, which is in agreement with the ratio of 5–20 previously reported based on in situ tracer and hydraulic tests of faulted/fractured rocks. The simulated longitudinal dispersivity is 1/9–1/20 of the estimated flow path lengths, in agreement with the laboratory and field tracer study values. These results indicate that transport pathways in faults with low hydraulic connectivity can be modelled using a highly tortuous 1D pipe flow path.

Comprehensive Analysis of SARS-CoV-2 Dynamics in Bangladesh: Infection Trends and Variants (2020-2023).

The first case of COVID-19 was detected in Bangladesh on 8 March 2020. Since then, the Government of Bangladesh (GoB) has implemented various measures to limit the transmission of COVID-19, including widespread testing facilities across the nation through a laboratory network for COVID-19 molecular testing. This study aimed to analyze the dynamics of SARS-CoV-2 in Bangladesh by conducting COVID-19 testing and genomic surveillance of the virus variants throughout the pandemic. Nasopharyngeal swabs were collected from authorized GoB collection centers between April 2020 and June 2023. The viral RNA was extracted and subjected to real-time PCR analysis in icddr,b's Virology laboratory. A subset of positive samples underwent whole-genome sequencing to track the evolutionary footprint of SARS-CoV-2 variants. We tested 149,270 suspected COVID-19 cases from Dhaka (n = 81,782) and other districts (n = 67,488). Of these, 63% were male. The highest positivity rate, 27%, was found in the >60 years age group, followed by 26%, 51-60 years, 25% in 41-50 years, and the lowest, 9% in under five children. Notably, the sequencing of 2742 SARS-CoV-2 genomes displayed a pattern of globally circulating variants, Alpha, Beta, Delta, and Omicron, successively replacing each other over time and causing peaks of COVID-19 infection. Regarding the risk of SARS-CoV-2 infection, it was observed that the positivity rate increased with age compared to the under-5 age group in 2020 and 2021. However, these trends did not remain consistent in 2022, where older age groups, particularly those over 60, had a lower positivity rate compared to other age groups due to vaccination. The study findings generated data on the real-time circulation of different SARS-CoV-2 variants and the upsurge of COVID-19 cases in Bangladesh, which impacted identifying hotspots and restricting the virus from further transmission. Even though there is currently a low circulation of SARS-CoV-2 in Bangladesh, similar approaches of genomic surveillance remain essential for monitoring the emergence of new SARS-CoV-2 variants or other potential pathogens that could lead to future pandemics.

Whole-genome sequencing for antimicrobial surveillance: species-specific quality thresholds and data evaluation from the network of the European Union Reference Laboratory for Antimicrobial Resistance genomic proficiency tests of 2021 and 2022.

As antimicrobial resistance (AMR) surveillance shifts to genomics, ensuring the quality of whole-genome sequencing (WGS) data produced across laboratories is critical. Participation in genomic proficiency tests (GPTs) not only increases individual laboratories' WGS capacity but also provides a unique opportunity to improve species-specific thresholds for WGS quality control (QC) by repeated resequencing of distinct isolates. Here, we present the results of the EU Reference Laboratory for Antimicrobial Resistance (EURL-AR) network GPTs of 2021 and 2022, which included 25 EU national reference laboratories (NLRs). A total of 392 genomes from 12 AMR-bacteria were evaluated based on WGS QC metrics. Two percent (n = 9) of the data were excluded, due to contamination, and 11% (n = 41) of the remaining genomes were identified as outliers in at least one QC metric and excluded from computation of the adjusted QC thresholds (AQT). Two QC metric correlation groups were identified through linear regression. Eight percent (n = 28) of the submitted genomes, from 11 laboratories, failed one or more of the AQTs. However, only three laboratories (12%) were identified as underperformers, failing across AQTs for uncorrelated QC metrics in at least two genomes. Finally, new species-specific thresholds for "N50" and "number of contigs > 200 bp" are presented for guidance in routine laboratory QC. The continued participation of NRLs in GPTs will reveal WGS workflow flaws and improve AMR surveillance data. GPT data will continue to contribute to the development of reliable species-specific thresholds for routine WGS QC, standardizing sequencing data QC and ensure inter- and intranational laboratory comparability.IMPORTANCEIllumina next-generation sequencing is an integral part of antimicrobial resistance (AMR) surveillance and the most widely used whole-genome sequencing (WGS) platform. The high-throughput, relative low-cost, high discriminatory power, and rapid turnaround time of WGS compared to classical biochemical methods means the technology will likely remain a fundamental tool in AMR surveillance and public health. In this study, we present the current level of WGS capacity among national reference laboratories in the EU Reference Laboratory for AMR network, summarizing applied methodology and statistically evaluating the quality of the obtained sequence data. These findings provide the basis for setting new and revised thresholds for quality metrics used in routine WGS, which have previously been arbitrarily defined. In addition, underperforming participants are identified and encouraged to evaluate their workflows to produce reliable results.

'You mean you're not doing it already?' A national sentinel toxico-surveillance system for detecting illicit, emerging and novel psychoactive drugs in presentations to emergency departments.

Patients presenting to the ED after using illicit drugs, including novel psychoactive substances, are a unique source of information on substances that are directly causing acute harm in the community. Conventionally, illicit drug intoxications are assessed and managed in EDs based on self-report and presenting symptoms, with no objective data on the causative agent. The Emerging Drugs Network of Australia (EDNA) is a national toxico-surveillance system that provides analytic data on these drugs, from sentinel Emergency Departments. It is a collaborative national network of emergency physicians, toxicologists, forensic laboratories and public health authorities. The key benefit of EDNA is the capacity to provide timely laboratory-confirmed toxicology data on emerging drug-related threats in the community. This leads to improvements in clinical, forensic laboratory and public health harm reduction responses, reflecting rapid translation of the research.

Public health use and lessons learned from a statewide SARS-CoV-2 wastewater monitoring program (MiNET)

The global SARS-CoV-2 monitoring effort has been extensive, resulting in many states and countries establishing wastewater-based epidemiology programs to address the spread of the virus during the pandemic. Challenges for programs include concurrently optimizing methods, training new laboratories, and implementing successful surveillance programs that can rapidly translate results for public health, and policy making. Surveillance in Michigan early in the pandemic in 2020 highlights the importance of quality-controlled data and explores correlations with wastewater and clinical case data aggregated at the state level. The lessons learned and potential measures to improve public utilization of results are discussed.The Michigan Network for Environmental Health and Technology (MiNET) established a network of laboratories that partnered with local health departments, universities, wastewater treatment plants (WWTPs) and other stakeholders to monitor SARS-CoV-2 in wastewater at 214 sites in Michigan. MiNET consisted of nineteen laboratories, twenty-nine local health departments, 6 Native American tribes, and 60 WWTPs monitoring sites representing 45 % of Michigan's population from April 6 and December 29, 2020. Three result datasets were created based on quality control criteria. Wastewater results that met all quality assurance criteria (Dataset Mp) produced strongest correlations with reported clinical cases at 16 days lag (rho = 0.866, p < 0.05).The project demonstrated the ability to successfully track SARS-CoV-2 on a large, state-wide scale, particularly data that met the outlined quality criteria and provided an early warning of increasing COVID-19 cases. MiNET is currently poised to leverage its competency to complement public health surveillance networks through environmental monitoring for new and emerging pathogens of concern and provides a valuable resource to state and federal agencies to support future responses.

Building Quality Control for Molecular Assays in the Global Measles and Rubella Laboratory Network.

More than 100 laboratories in the World Health Organization Global Measles and Rubella Laboratory Network (GMRLN) perform nucleic acid-based methods for case confirmation of measles or rubella infections and/or strain surveillance (genotyping). The quality of laboratory data is critical to ensure that diagnostic results and country reports to regional verification committees are based on accurate data. A molecular External Quality Assurance (mEQA) program was initiated by the US-CDC in 2014 to evaluate the performance of laboratories in the network. The inclusion of testing for measles and rubella viruses, with a focus on detection and genotyping, plus the diversity of assays and platforms employed required a flexible and comprehensive proficiency testing program. A stepwise introduction of new evaluation criteria gradually increased the stringency of the proficiency testing program, while giving laboratories time to implement the required changes. The mEQA program plays an important role in many processes in the GMRLN, including informing plans for the training of laboratory staff, access to reagents, and the submission of sequence data to global databases. The EQA program for Local Public Health Institutes in Japan is described as an example for national mEQA programs. As more laboratories initiate molecular testing, the mEQA will need to continue to expand and to adapt to the changing landscape for molecular testing.

Global Update on Measles Molecular Epidemiology.

Molecular surveillance of circulating measles variants serves as a line of evidence for the absence of endemic circulation and provides a means to track chains of transmission. Molecular surveillance for measles (genotyping) is based on the sequence of 450 nucleotides at the end of the nucleoprotein coding region (N450) of the measles genome. Genotyping was established in 1998 and, with over 50,000 sequence submissions to the Measles Nucleotide Surveillance database, has proven to be an effective resource for countries attempting to trace pathways of transmission. This review summarizes the tools used for the molecular surveillance of measles and describes the challenge posed by the decreased number of circulating measles genotypes. The Global Measles and Rubella Laboratory Network addressed this challenge through the development of new tools such as named strains and distinct sequence identifiers that analyze the diversity within the currently circulating genotypes. The advantages and limitations of these approaches are discussed, together with the need to generate additional sequence data including whole genome sequences to ensure the continued utility of strain surveillance for measles.