Increased viral load in patients infected with severe acute respiratory syndrome coronavirus 2 Omicron variant in the Republic of Korea

BACKGROUND

Coronavirus disease 2019 (COVID-19) has been declared a global pandemic owing to the rapid spread of the causative agent, severe acute respiratory syndrome coronavirus 2. Its Delta and Omicron variants are more transmissible and pathogenic than other variants. Some debates have emerged on the mechanism of variants of concern. In the COVID-19 wave that began in December 2021, the Omicron variant, first reported in South Africa, became identifiable in most cases globally. The aim of this study was to provide data to inform effective responses to the transmission of the Omicron variant.

METHODS

The Delta variant and the spike protein D614G mutant were compared with the Omicron variant. Viral loads from 5 days after symptom onset were compared using epidemiological data collected at the time of diagnosis.

RESULTS

The Omicron variant exhibited a higher viral load than other variants, resulting in greater transmissibility within 5 days of symptom onset.

CONCLUSION

Future research should focus on vaccine efficacy against the Omicron variant and compare trends in disease severity associated with its high viral load.

Guidelines for the Laboratory Diagnosis of Monkeypox in Korea

While the coronavirus disease 2019 pandemic is ongoing, monkeypox has been rapidly spreading in non-endemic countries since May 2022. Accurate and rapid laboratory tests are essential for identifying and controlling monkeypox. Korean Society for Laboratory Medicine and the Korea Disease Prevention and Control Agency have proposed guidelines for diagnosing monkeypox in clinical laboratories in Korea. These guidelines cover the type of tests, selection of specimens, collection of specimens, diagnostic methods, interpretation of test results, and biosafety. Molecular tests are recommended as confirmatory tests. Skin lesion specimens are recommended for testing in the symptomatic stage, and the collection of both blood and oropharyngeal swabs is recommended in the presymptomatic or prodromal stage.

Recent increase in the detection of human parainfluenza virus during the coronavirus disease-2019 pandemic in the Republic of Korea

BACKGROUND

Since the onset of the coronavirus disease-2019 (COVID-19) pandemic, the prevalence of respiratory infectious diseases, particularly, the flu epidemic, has considerably decreased. The low detection rate and decreased number of specimens have hindered the implementation of the Korea Influenza and Respiratory Viruses Surveillance System (KINRESS), a sentinel surveillance system. Most patients with influenza-like illness visit the COVID-19 screening clinic; therefore, the number of samples collected in sentinel surveillance has decreased by more than 50%. Thus, the Korea Disease Control and Prevention Agency supplemented sentinel surveillance with non-sentinel surveillance by private medical diagnostic centers. We report here a delayed and unprecedented high detection of human parainfluenza virus (hPIV) in the Republic of Korea during the COVID-19 pandemic through sentinel and non-sentinel surveillance. We also examined the causes and implications of the changes in prevalence of hPIV.l METHODS: We collected data for 56,984 and 257,217 samples obtained through sentinel and non-sentinel surveillance, respectively. Eight viruses were confirmed using real-time reverse transcription-polymerase chain reaction (PCR) or real-time PCR. Some specimens from the sentinel surveillance were used for genetic characterization of hPIV type 3.

RESULTS

In 2020, hPIV was rarely detected; however, it was detected in August 2021. The detection rate continued to increase considerably in September and reached over 70% in October, 2021. The detection rate of hPIV3 was significantly higher in infants and preschoolers aged 0-6 years in both sentinel and non-sentinel surveillance. Detection of hPIV was delayed in metropolitan areas compared to that in suburban regions. The hemagglutinin-neuraminidase sequences of hPIV3 generated in 2021 were not distinct from those detected prior to the COVID-19 pandemic.

CONCLUSIONS

The operation of non-sentinel and sentinel surveillance to monitor respiratory viruses could sensitively detect an unprecedented revival of hPIV in the Republic of Korea during the COVID-19 pandemic.

Guidelines for Mobile Laboratories for Molecular Diagnostic Testing of COVID-19

With the rapid spread of the coronavirus disease (COVID-19), the need for rapid testing and diagnosis and consequently, the demand for mobile laboratories have increased. Despite this need, there are no clear guidelines for the operation, maintenance, or quality control of mobile laboratories. We provide guidelines for the operation, management, and quality control of mobile laboratories, and specifically for the implementation and execution of COVID-19 molecular diagnostic testing. These practical guidelines are primarily based on expert opinions and a laboratory accreditation inspection checklist. The scope of these guidelines includes the facility, preoperative evaluation, PCR testing, internal and external quality control, sample handling, reporting, laboratory personnel, biosafety level, and laboratory safety management. These guidelines are useful for the maintenance and operation of mobile laboratories not only in normal circumstances but also during public health crises and emergencies.

Update of Guidelines for Laboratory Diagnosis of COVID-19 in Korea

Korean Society for Laboratory Medicine and the Korea Disease Prevention and Control Agency have announced guidelines for diagnosing coronavirus disease (COVID-19) in clinical laboratories in Korea. With the ongoing pandemic, we propose an update of the previous guidelines based on new scientific data. This update includes recommendations for tests that were not included in the previous guidelines, including the rapid molecular test, antigen test, antibody test, and self-collected specimens, and a revision of the previous recommendations. This update will aid clinical laboratories in performing laboratory tests for diagnosing COVID-19.

Molecular Dynamics Studies on the Structural Stability Prediction of SARS-CoV-2 Variants Including Multiple Mutants

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused the Coronavirus Disease (COVID-19) pandemic worldwide. The spike protein in SARS-CoV-2 fuses with and invades cells in the host respiratory system by binding to angiotensin-converting enzyme 2 (ACE2). The spike protein, however, undergoes continuous mutation from a D614G single mutant to an omicron variant, including multiple mutants. In this study, variants, including multiple mutants (double, triple mutants, B.1.620, delta, alpha, delta_E484Q, mu, and omicron) were investigated in patients. The 3D structure of the full-length spike protein was used in conformational analysis depending on the SARS-CoV-2 variants. The structural stability of the variant types was analyzed based on the distance between the receptor-binding domain (RBD) of each chain in the spike protein and the binding free energy between the spike protein and bound ACE2 in the one-, two-, and three-open-complex forms using molecular dynamics (MD) simulation. Omicron variants, the most prevalent in the recent history of the global pandemic, which consist of 32 mutations, showed higher stability in all open-complex forms compared with that of the wild type and other variants. We suggest that the conformational stability of the spike protein is the one of the important determinants for the differences in viral infectivity among variants, including multiple mutants.

Increase in Viral Load in Patients With SARS-CoV-2 Delta Variant Infection in the Republic of Korea

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread rapidly, causing in COVID-19 being declared a global pandemic by the World Health Organization. The key variants include alpha, beta, gamma, and delta; these exhibit high viral transmission, pathogenicity, and immune evasion mechanisms. The delta variant, first confirmed in India, was detected in the majority of COVID-19 patients at the recent wave in the Republic of Korea. Here, the features of the delta variant were compared to the earlier waves, with focus on increased transmissibility. The viral load, from the initial days of infection to 14 days later, was compared based on epidemiological data collected at the time of confirmed diagnosis. The increased viral load observed in the delta variant-led infections influences the scale of the wave, owing to the increased rate of transmission. Infections caused by the delta variant increases the risk of hospitalization within 14 days after symptom onset, and the high viral load correlates with COVID-19 associated morbidity and mortality. Therefore, the future studies should compare the trend of disease severity caused by the high viral load of delta variant with previous waves and analyze the vaccine effects in light of the delta variant of fourth wave.

Genomic epidemiology reveals the reduction of the introduction and spread of SARS-CoV-2 after implementing control strategies in Republic of Korea, 2020

Genomic epidemiology is a core component in investigating the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, the efficacy of control strategies in South Korea was evaluated using genomic epidemiology based on viral genome sequences of 2,065 SARS-CoV-2 cases identified in South Korea from January 2020 to December 2020. Phylogenetic analysis revealed that the majority of viruses introduced from inbound travelers did not further spread throughout South Korea; however, four distinct subgroups (KR.1–4, belonging to B.1.497, B.1, K.1 and B.41) of viruses caused local epidemics. After the introduction of enhanced social distancing, the viral population size and daily case numbers decreased, and KR.2–4 subgroups were extinguished from South Korea. Nevertheless, there was a subsequent increase in KR.1 subgroups after the downgrading of social distancing level. These results indicate that the international traveler quarantine system implemented in South Korea along with social distancing measures efficiently reduced the introduction and spread of SARS-CoV-2, but it was not completely controlled. An improvement of control strategies will be required to better control SARS-CoV-2, its variants, and future pandemic viruses.

Corrigendum to: Genomic epidemiology reveals the reduction of the introduction and spread of SARS-CoV-2 after implementing control strategies in Republic of Korea, 2020

[This corrects the article DOI: 10.1093/ve/veab077.].

Viral Shedding among Re-Positive Severe Acute Respiratory Syndrome Coronavirus-2 Positive Individuals in Republic of Korea

This study investigated the infectivity of severe acute respiratory syndrome (SARS-CoV-2) in individuals who re-tested positive for SARS-CoV-2 RNA after recovering from their primary illness. We investigated 295 individuals with re-positive SARS-CoV-2 polymerase chain reaction (PCR) test results and 836 of their close contacts. We attempted virus isolation in individuals with re-positive SARS-CoV-2 PCR test results using cell culture and confirmed the presence of neutralizing antibodies using serological tests. Viral culture was negative in all 108 individuals with re-positive SARS-CoV-2 PCR test results in whom viral culture was performed. Three new cases of SARS-CoV-2 infection were identified among household contacts using PCR. Two of the three new cases had had contact with the index patient during their primary illness, and all three had antibody evidence of past infection. Thus, there was no laboratory evidence of viral shedding and no epidemiological evidence of transmission among individuals with re-positive SARS-CoV-2 PCR test results.

Pooling Upper Respiratory Specimens for Rapid Mass Screening of COVID-19 by Real-Time RT-PCR

To validate the specimen-pooling strategy for real-time reverse transcription PCR detection of severe acute respiratory syndrome coronavirus 2, we generated different pools including positive specimens, reflecting the distribution of cycle threshold values at initial diagnosis. Cumulative sensitivities of tested pool sizes suggest pooling of <6 specimens for surveillance by this method.

Detection and Isolation of SARS-CoV-2 in Serum, Urine, and Stool Specimens of COVID-19 Patients from the Republic of Korea

Objectives

Coronavirus Disease-19 (COVID-19) is a respiratory infection characterized by the main symptoms of pneumonia and fever. It is caused by the novel coronavirus severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2), which is known to spread via respiratory droplets. We aimed to determine the rate and likelihood of SARS-CoV-2 transmission from COVID-19 patients through non-respiratory routes.

Methods

Serum, urine, and stool samples were collected from 74 hospitalized patients diagnosed with COVID-19 based on the detection of SARS-CoV-2 in respiratory samples. The SARS-CoV-2 RNA genome was extracted from each specimen and real-time reverse transcription polymerase chain reaction performed. CaCo-2 cells were inoculated with the specimens containing the SARS-COV-2 genome, and subcultured for virus isolation. After culturing, viral replication in the cell supernatant was assessed.

Results

Of the samples collected from 74 COVID-19 patients, SARS-CoV-2 was detected in 15 serum, urine, or stool samples. The virus detection rate in the serum, urine, and stool samples were 2.8% (9/323), 0.8% (2/247), and 10.1% (13/129), and the mean viral load was 1,210 ± 1,861, 79 ± 30, and 3,176 ± 7,208 copy/μL, respectively. However, the SARS-CoV-2 was not isolated by the culture method from the samples that tested positive for the SARS-CoV-2 gene.

Conclusion

While the virus remained detectable in the respiratory samples of COVID-19 patients for several days after hospitalization, its detection in the serum, urine, and stool samples was intermittent. Since the virus could not be isolated from the SARS-COV-2-positive samples, the risk of viral transmission via stool and urine is expected to be low.

COVID-19 Molecular Testing in Korea: Practical Essentials and Answers From Experts Based on Experiences of Emergency Use Authorization Assays

Coronavirus disease 2019 (COVID-19) is a respiratory disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Early detection of COVID-19 and immediate isolation of infected patients from the naive population are important to prevent further pandemic spread of the infection. Real-time reverse transcription (RT)-PCR to detect SARS-CoV-2 RNA is currently the most reliable diagnostic method for confirming COVID-19 worldwide. Guidelines for clinical laboratories on the COVID-19 diagnosis have been recently published by Korean Society for Laboratory Medicine and the Korea Centers for Disease Control and Prevention. However, these formal guidelines do not address common practical laboratory issues related to COVID-19 real-time RT-PCR testing and their solutions. Therefore, this guideline is intended as a practical and technical supplement to the “Guidelines for Laboratory Diagnosis of COVID-19 in Korea”.

Guidelines for Laboratory Diagnosis of Coronavirus Disease 2019 (COVID-19) in Korea

The outbreak of coronavirus disease 2019 (COVID-19), which began in December 2019, is still ongoing in Korea, with >9,000 confirmed cases as of March 25, 2020. COVID-19 is a severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) infection, and real-time reverse transcription-PCR is currently the most reliable diagnostic method for COVID-19 around the world. Korean Society for Laboratory Medicine and the Korea Centers for Disease Prevention and Control propose guidelines for diagnosing COVID-19 in clinical laboratories in Korea. These guidelines are based on other related domestic and international guidelines, as well as expert opinions and include the selection of test subjects, selection of specimens, diagnostic methods, interpretation of test results, and biosafety.

The Possibility of TBC1D21 as a Candidate Gene for Teat Numbers in Pigs

Based on a quantitative traits locus (QTL) study using a F₂ intercross between Landrace and Korean native pigs, a significant QTL affecting teat numbers in SSC7 was identified. The strong positional candidate gene, TBC1D21, was selected due to its biological function for epithelial mesenchymal cell development. Sequence analysis revealed six single nucleotide polymorphisms (SNPs) in the TBC1D21 gene. Among these, two SNP markers, one silent mutation (SNP01) for g.13,050A>G and one missense mutation (SNP04) for c.829A>T (S277C), were genotyped and they showed significant associations with teat number traits (p value = 6.38E-05 for SNP01 and p value = 1.06E-07 for SNP04 with total teat numbers). Further functional validation of these SNPs could give valuable information for understanding the teat number variation in pigs.

Genome-wide association study identifies quantitative trait loci affecting hematological traits in an F2 intercross between Landrace and Korean native pigs

Changes affecting the status of health and robustness can bring about physiological alterations including hematological parameters in swine. To identify quantitative trait loci (QTL) associated with eight hematological traits (one leukocyte trait, six erythrocyte traits and one platelet trait), we conducted a genome-wide association study using the PorcineSNP60K BeadChip in a resource population derived from an intercross between Landrace and Korean native pigs. A total of 36 740 SNPs from 816 F2 progeny were analyzed for each blood-related trait after filtering for quality control. Data were analyzed by the genome-wide rapid association using mixed model and regression (GRAMMAR) approach. A total of 257 significant SNPs (P < 1.36 × 10(-6) ) on SSC3, 6, 8, 13 and 17 were identified for blood-related traits in this study. Interestingly, the genomic region between 17.9 and 130 Mb on SSC8 was found to be significantly associated with red blood cell, mean corpuscular volume and mean corpuscular hemoglobin. Our results include the identification of five significant SNPs within five candidate genes (KIT, IL15, TXK, ARAP2 and ERG) for hematopoiesis. Further validation of these identified SNPs could give valuable information for understanding the variation of hematological traits in pigs.

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F(2) intercross between Landrace and Korean native pigs. Eight blood-related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F(2) progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome-wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood-related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker-assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.

A new statistical framework for parameter subset selection and optimal parameter estimation in the activated sludge model

A new model-calibration method has been proposed to solve the problems associated with parameter subset selection and parameter estimation of the activated sludge model (ASM). We propose the use of a statistical methodology for reasonable parameter selection and parameter estimation that consists of sensitivity analysis, similarity measures, hierarchical clustering and response surface methods (RSM). The introduction of effluent quality index (EQI) can reduce all of the outputs of the ASM model into one factor. The EQI was used to calculate a sensitivity matrix. Then, the hierarchical clustering algorithm was used for parameter subset selection. This selection was based on a similarity measure using the sensitivity matrix and was used to reduce the number of model parameters by selecting only one parameter per cluster group (parameter subset selection step). Lastly, a RSM analysis was conducted in order to determine the optimal parameter values. This study was conducted in order to develop a new statistical framework that can greatly reduce the computational effort required to find the optimal solution by reducing the number of parameters. The experimental results indicated that the calibrated model can improve the prediction quality of the ASM model and the efficiency of the modeling.

Sewage sludge reduction and system optimization in a catalytic ozonation process

The main objective of this study was to suggest a feasible, effective process for the reduction of sewage sludge using ozone oxidation catalysed by metal ion. A series of lab-scale experiments was conducted to select a suitable catalyst and its proper dose to achieve optimum sludge reduction. Using a central composite design under response surface methodology (RSM), system optimization with respect to sludge reduction and cost-effectiveness was performed by varying the independent parameters: dosages of ozone and ions. Five metal ions, Mn2+, Fe2+, Zn2+, CU2+, and Al3+1, were tested, and the manganese ion showed the highest sludge reduction, as measured by a decrease in total suspended solids. The ozone/Mn combination achieved approximately twice as much sludge reduction as the ozonation alone. Furthermore, the Mn dose of 10 mg/g-TS (total solids) resulted in the highest sludge reduction efficiency among the different doses, which ranged from 0 to 20 mg-Mn/g-TS. The predicted efficiency of sewage sludge reduction using the RSM was found to agree well with the experimental results, and the statistical analyses predicted optimum ranges for the doses of ozone and Mn ions, taking into account the overall cost for sewage sludge treatment.

A systematic approach to data-driven modeling and soft sensing in a full-scale plant

The well-known mathematical modeling and neural networks (NNs) methods have limitations to incorporate the key process characteristics at the wastewater treatment plants (WWTPs) which are complex, non-stationary, temporal correlation, and nonlinear systems. In this study, a systematic methodology of NNs modeling which can be efficiently included in the key modeling information of the WWTPs is performed by selecting the temporal effect of the hydraulics based on multi-way principal components analysis (MPCA). The proposed method is applied for modeling wastewater quality of a full-scale plant, which is a Daewoo nutrient removal (DNR) process. Through the experimental results in a full-scale plant, the efficiency of the proposed method is evaluated and the prediction capability is highly improved by the inclusion of the hydraulics term due to the optimized structure of neural networks.

Sensor validation and reconciliation for a partial nitrification process

Wastewater treatment plants (WWTP) are notorious for poor data quality and sensor reliability due to the hostile environment in which the measurement equipment has to function. In this paper, a structured residual approach with maximum sensitivity (SRAMS) based on the redundancy of the measurements is used to detect, identify and reconstruct single and multiple sensor faults in a single reactor for high activity ammonia removal over nitrite (SHARON) process. SRAMS is based on inferences, which are insensitive to the faults in the sensor of interest and sensitive to faults in the other sensors. It is used for four types of sensor failure detection: bias, drift, complete failure and precision degradation. The application of sensor validation shows that single and multiple sensor faults can be detected and that the fault magnitude and fault type can be estimated by the reconstruction scheme. This sensor validation method is not limited by the type or application of the considered sensors. The methodology can thus easily be applied for sensor surveillance of other continuously measuring sensors and analysers.

Dynamic monitoring system for full-scale wastewater treatment plants

This paper proposes a new process monitoring method using dynamic independent component analysis (ICA), ICA is a recently developed technique to extract the hidden factors that underlie sets of measurements, whereas principal component analysis (PCA) is a dimensionality reduction technique in terms of capturing the variance of the data. Its goal is to find a linear representation of non-Gaussian data so that the components are statistically independent. PCA aims at finding PCs that are uncorrelated and are linear combinations of the observed variables, while ICA is designed to separate the ICs that are independent and constitute the observed variables. The dynamic ICA monitoring method is applying ICA to the augmenting matrix with time-lagged variables. The dynamic monitoring method was applied to detect and monitor disturbances in a full-scale biological wastewater treatment (WWTP), which is characterized by a variety of dynamic and non-Gaussian characteristics. The dynamic ICA method showed more powerful monitoring performance on a WWTP application than the dynamic PCA method since it can extract source signals which are independent of time and cross-correlation of variables.

New monitoring technique with an ICA algorithm in the wastewater treatment process

A new monitoring method using independent component analysis (ICA) is suggested for the wastewater treatment process (WWTP). ICA is an extension of PCA (Principal Component Analysis). While PCA can only impose independence up to the second order (mean and variance) with constraint on the direction vectors to be orthogonal, ICA imposes statistical independence up to more than second order on the individual component and has no orthogonal condition. When the variables have the Gaussian distribution, PCA itself provides a satisfactory result in monitoring performance. However, the measured variables are not often normally distributed. In this case, ICA can provide better monitoring results than PCA since ICA is based on the assumption that the latent variables are not normally distributed. In this paper, the ICA monitoring algorithm with kernel density estimation was applied to fault detection and diagnosis of the wastewater simulation benchmark. ICA with kernel density estimation gives better results than PCA in disturbance detection in spite of severe periodic features of the wastewater plant.

Disturbance detection and isolation in the activated sludge process

This paper proposes a new fault detection and isolation (FDI) method. This method monitors the distribution of process data and detects changes in this distribution, which reflect changes in the corresponding operating condition. A modified dissimilarity index and a FDI technique are defined to quantitatively evaluate the difference between data sets. This technique considers the importance of each transformed variable in the multivariate system. The FDI technique is applied to a benchmark simulation and to data from a real wastewater treatment plant. Simulation results show that it immediately detects disturbances and automatically distinguishes between serious and minor anomalies for various types of fault. The method not only detects the disturbances, but also isolates the scale of the disturbance, facilitating the interpretation of the disturbance source. The proposed monitoring technique is found to be appropriate for analyzing the biological wastewater treatment process, which is characterized by a variety of fault and disturbance sources and non-stationary characteristics.

Closed-loop identification and control application for dissolved oxygen concentration in a full-scale coke wastewater treatment plant

The objective of this paper is to apply a closed-loop identification to actual dissolved oxygen control system in the coke wastewater treatment plant. It approximates the dissolved oxygen dynamics to a high order model using the integral transform method and reduces it to the first-order plus time delay (FOPTD) or second-order plus time delay (SOPTD) for the PID controller tuning. To experiment the process identification on the real plant, a simple set-point change of the speed of surface aerator under the closed-loop control without any mode change was used as an activation signal of the identification. The full-scale experimental results show a good identification performance and a good tracking ability for set-point change. As a result of improved control performance, the fluctuation of dissolved oxygen concentration variation has been decreased and the electric power saving has been accomplished.

A new rehabilitation training system for postural balance control using virtual reality technology

A new rehabilitation training system, designated as a virtual cycling system, was developed to improve postural balance control by combining virtual reality (VR) technology with a bicycle. Several parameters including path deviation, path deviation velocity, cycling time, and head movement were extracted and evaluated to quantify the extent of control. The system was effective as a training device and, in addition, the technology might have a wider applicability to the rehabilitation field.