Threshold conditions for curbing COVID-19 with a dynamic zero-case policy derived from 101 outbreaks in China.

By 31 May 2022, original/Alpha, Delta and Omicron strains induced 101 outbreaks of COVID-19 in mainland China. Most outbreaks were cleared by combining non-pharmaceutical interventions (NPIs) with vaccines, but continuous virus variations challenged the dynamic zero-case policy (DZCP), posing questions of what are the prerequisites and threshold levels for success? And what are the independent effects of vaccination in each outbreak? Using a modified classic infectious disease dynamic model and an iterative relationship for new infections per day, the effectiveness of vaccines and NPIs was deduced, from which the independent effectiveness of vaccines was derived. There was a negative correlation between vaccination coverage rates and virus transmission. For the Delta strain, a 61.8% increase in the vaccination rate (VR) reduced the control reproduction number (CRN) by about 27%. For the Omicron strain, a 20.43% increase in VR, including booster shots, reduced the CRN by 42.16%. The implementation speed of NPIs against the original/Alpha strain was faster than the virus's transmission speed, and vaccines significantly accelerated the DZCP against the Delta strain. The CRN ([Formula: see text]) during the exponential growth phase and the peak time and intensity of NPIs were key factors affecting a comprehensive theoretical threshold condition for DZCP success, illustrated by contour diagrams for the CRN under different conditions. The DZCP maintained the [Formula: see text] of 101 outbreaks below the safe threshold level, but the strength of NPIs was close to saturation especially for Omicron, and there was little room for improvement. Only by curbing the rise in the early stage and shortening the exponential growth period could clearing be achieved quickly. Strengthening China's vaccine immune barrier can improve China's ability to prevent and control epidemics and provide greater scope for the selection and adjustment of NPIs. Otherwise, there will be rapid rises in infection rates and an extremely high peak and huge pressure on the healthcare system, and a potential increase in excess mortality.

The analysis of cathepsin L that mediates cellular SARS-CoV-2 infection leading to COVID-19 in head and neck squamous cell carcinoma.

The vulnerability of the oral cavity to SARS-CoV-2 infection is well-known, and cancer patients are at a higher risk of COVID-19, emphasizing the need to prioritize this patient population. Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignant cancers associated with early metastasis and poor prognosis. It has been established that cancerous tissues express Cathepsin L (CTSL), a proteinase that regulates cancer progression and SARS-CoV-2 entry. Therefore, it is essential to evaluate the correlation between disease outcomes and CTSL expression in cancer tissues and predict the susceptibility of cancer patients to SARS-CoV-2. In this study, we used transcriptomic and genomic data to profile CTSL expression in HNSCC and developed a CTSL signature that could reflect the response of HNSCC patients to chemotherapy and immunotherapy. Additionally, we investigated the relationship between CTSL expression and immune cell infiltration and established CTSL as a potential carcinogenic factor for HNSCC patients. These findings could aid in understanding the mechanisms underlying the increased susceptibility of HNSCC patients to SARS-CoV-2 and contribute to the development of therapy for both HNSCC and COVID-19.

Exploring COVID-19 transmission patterns and key factors during epidemics caused by three major strains in Asia.

The COVID-19 epidemic has lasted for more than two years since the outbreak in late 2019. An urgent and challenging question is how to systematically evaluate epidemic developments in different countries, during different periods, and to determine which measures that could be implemented are key for successful epidemic prevention. In this study, SBD distance-based K-shape clustering and hierarchical clustering methods were used to analyse epidemics in Asian countries. For the hierarchical clustering, epidemic time series were divided into three periods (epidemics induced by the Original/Alpha, Delta and Omicron variants separately). Standard deviations, the Hurst index, mortality rates, peak value of confirmed cases per capita, average growth rates, and the control efficiency of each period were used to characterize the epidemics. In addition, the total numbers of cases in the different countries were analysed by correlation and regression in relation to 15 variables that could have impacts on COVID-19. Finally, some suggestions on prevention and control measures for each category of country are given. We found that the total numbers of cases per million of a population, total deaths per million and mortality rates were highly correlated with the proportion of people aged over 65 years, the prevalence of multiple diseases, and the national GDP. We also found significant associations between case numbers and vaccination rates, health expenditures, and stringency of control measures. Vaccinations have played a positive role in COVID-19, with a gradual decline in mortality rates in later periods, and are still playing protective roles against the Delta and Omicron strains. The stringency of control measures taken by a government is not an indicator of the appropriateness of a country's response to the outbreak, and a higher index does not necessarily mean more effective measures; a combination of factors such as national vaccination rates, the country's economic foundation and the availability of medical equipment is also needed. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

Study protocol for a randomised controlled trial of diacerein versus placebo to treat knee osteoarthritis with effusion-synovitis (DICKENS).

BACKGROUND: There is an unmet need for treatments for knee osteoarthritis (OA). Effusion-synovitis is a common inflammatory phenotype of knee OA and predicts knee pain and structural degradation. Anti-inflammatory therapies, such as diacerein, may be effective for this phenotype. While diacerein is recommended for alleviating pain in OA patients, evidence for its effectiveness is inconsistent, possibly because studies have not targeted patients with an inflammatory phenotype. Therefore, we will conduct a multi-centre, randomised, placebo-controlled double-blind trial to determine the effect of diacerein on changes in knee pain and effusion-synovitis over 24 weeks in patients with knee OA and magnetic resonance imaging (MRI)-defined effusion-synovitis. METHODS: We will recruit 260 patients with clinical knee OA, significant knee pain, and MRI-detected effusion-synovitis in Hobart, Melbourne, Adelaide, and Perth, Australia. They will be randomly allocated to receive either diacerein (50mg twice daily) or identical placebo for 24 weeks. MRI of the study knee will be performed at screening and after 24 weeks of intervention. The primary outcome is improvement in knee pain at 24 weeks as assessed by a 100-mm visual analogue scale (VAS). Secondary outcomes include improvement in volumetric (ml) and semi-quantitative (Whole-Organ Magnetic Resonance Imaging Score, 0-3) measurements of effusion-synovitis using MRI over 24 weeks, and improvement in knee pain (VAS) at 4, 8, 12, 16, and 20 weeks. Intention-to-treat analyses of primary and secondary outcomes will be performed as the primary analyses. Per protocol analyses will be performed as the secondary analyses. DISCUSSION: This study will provide high-quality evidence to determine whether diacerein improves pain, changes disease trajectory, and slows disease progression in OA patients with effusion-synovitis. If diacerein proves effective, this has the potential to significantly benefit the substantial proportion (up to 60%) of knee OA patients with an inflammatory phenotype. TRIAL REGISTRATION: Australian and New Zealand Clinical Trial Registry ACTRN12618001656224 . Registered on 08 October 2018.

Estimate the incubation period of coronavirus 2019 (COVID-19).

COVID-19 is an infectious disease that presents unprecedented challenges to society. Accurately estimating the incubation period of the coronavirus is critical for effective prevention and control. However, the exact incubation period remains unclear, as COVID-19 symptoms can appear in as little as 2 days or as long as 14 days or more after exposure. Accurate estimation requires original chain-of-infection data, which may not be fully available from the original outbreak in Wuhan, China. In this study, we estimated the incubation period of COVID-19 by leveraging well-documented and epidemiologically informative chain-of-infection data collected from 10 regions outside the original Wuhan areas prior to February 10, 2020. We employed a proposed Monte Carlo simulation approach and nonparametric methods to estimate the incubation period of COVID-19. We also utilized manifold learning and related statistical analysis to uncover incubation relationships between different age and gender groups. Our findings revealed that the incubation period of COVID-19 did not follow general distributions such as lognormal, Weibull, or Gamma. Using proposed Monte Carlo simulations and nonparametric bootstrap methods, we estimated the mean and median incubation periods as 5.84 (95% CI, 5.42-6.25 days) and 5.01 days (95% CI 4.00-6.00 days), respectively. We also found that the incubation periods of groups with ages greater than or equal to 40 years and less than 40 years demonstrated a statistically significant difference. The former group had a longer incubation period and a larger variance than the latter, suggesting the need for different quarantine times or medical intervention strategies. Our machine-learning results further demonstrated that the two age groups were linearly separable, consistent with previous statistical analyses. Additionally, our results indicated that the incubation period difference between males and females was not statistically significant.

Estimate the incubation period of coronavirus 2019 (COVID-19)

COVID-19 is an infectious disease that presents unprecedented challenges to society. Accurately estimating the incubation period of the coronavirus is critical for effective prevention and control. However, the exact incubation period remains unclear, as COVID-19 symptoms can appear in as little as 2 days or as long as 14 days or more after exposure. Accurate estimation requires original chain-of-infection data, which may not be fully available from the original outbreak in Wuhan, China. In this study, we estimated the incubation period of COVID-19 by leveraging well-documented and epidemiologically informative chain-of-infection data collected from 10 regions outside the original Wuhan areas prior to February 10, 2020. We employed a proposed Monte Carlo simulation approach and nonparametric methods to estimate the incubation period of COVID-19. We also utilized manifold learning and related statistical analysis to uncover incubation relationships between different age and gender groups. Our findings revealed that the incubation period of COVID-19 did not follow general distributions such as lognormal, Weibull, or Gamma. Using proposed Monte Carlo simulations and nonparametric bootstrap methods, we estimated the mean and median incubation periods as 5.84 (95% CI, 5.42–6.25 days) and 5.01 days (95% CI 4.00–6.00 days), respectively. We also found that the incubation periods of groups with ages greater than or equal to 40 years and less than 40 years demonstrated a statistically significant difference. The former group had a longer incubation period and a larger variance than the latter, suggesting the need for different quarantine times or medical intervention strategies. Our machine-learning results further demonstrated that the two age groups were linearly separable, consistent with previous statistical analyses. Additionally, our results indicated that the incubation period difference between males and females was not statistically significant.

The relationship between leisure activities and the mental health of college students during the COVID-19 pandemic

Despite the benefits of leisure activities for mental health, very little is known about the link between leisure activities and mental health of college students during the COVID-19 pandemic. To fill this knowledge gap, this study sought to examine the relationship between leisure activities and mental health during the COVID-19 pandemic and lockdown. A cross-sectional online survey of 30 Chinese provinces was conducted from March 9 to 25. The Zung's Self-Rating Anxiety Scale and Self-Rating Depression Scale were conducted to measure mental health, while the duration of leisure activities was used to evaluate leisure. Results of logistic regression showed the impact of leisure activities on self-rated mental health depends on types of leisure activities. Reading and calligraphy are beneficial to self-rated mental health while online activities are not. Self-rated mental health is associated with leisure activities. More college students with self-reported anxiety symptoms like to participate in hobbies and outdoor physical activities, while college students who reported depression are reluctant to participate in most leisure activities. Females, postgraduates incline to participate in more types of leisure activities, and students living in urban areas are reluctant to join outdoor physical activities. Besides, these groups are more likely to have self-reported mental illness symptoms.

Relationship between SARS-CoV-2 nucleocapsid protein and N gene and its application in antigen testing kits evaluation.

More than forty antigen testing kits have been approved to response the prevalence of SARS-CoV-2 and its variant strains. However, the approved antigen testing kits are not capable of quantitative detection. Here, we successfully developed a lateral flow immunoassay based on colloidal gold nanoparticles (CGNP-based LFIA) for nucleocapsid (N) protein of SARS-CoV-2 quantitative detection. Delta strain (NMDC60042793) of SARS-CoV-2 have been cultured and analyzed by our developed digital PCR and LFIA methods to explore the relationship between N protein amount and N gene level. It indicated that the linear relationship (y = 47 ×) between N protein molecule number and N gene copy number exhibited very well (R2 = 0.995), the virus titers and N protein amount can be roughly estimated according to nucleic acid testing. Additionally, detection limits (LODs) of nine approved antigen testing kits also have been evaluated according to the Guidelines for the registration review of 2019-nCoV antigen testing reagents. Only three antigen testing kits had LODs as stated in the instructions, the LODs of Kits have been converted into the N gene and N protein levels, according to the established relationships among virus titer vers. N gene and antigen. Results demonstrated that the sensitivity of nucleic acid testing is at least 1835 times higher than that of antigen testing. We expect that the relationship investigation and testing kits evaluation have the important directive significance to precise epidemic prevention.

Buchwald-Hartwig coupled conjugated microporous polymer for efficient removal COVID-19 antiviral drug famciclovir from waters: Adsorption behavior and mechanism.

The consumption of famciclovir (FCV) has been increased dramatically since the outbreak of coronavirus in 2019, and the pollution and harm of FCV in waters are concerned. Here, by utilizing aryl halides on 2, 4, 6-tris(4-bromophenyl)- 1, 3, 5-triazine (BPT) and primary amine groups on benzidine (BZ), a novel conjugated microporous polymer, namely BPT-BZ-CMP, was synthesized by Buchwald-Hartwig coupling reaction and applied in the removal of FCV from aqueous solution firstly. The synthesized BPT-BZ-CMP were characterized by various methods, including FTIR, SEM, BET, and Zeta-potential. Due to the micropore structure and high specific surface area, it took only 30 min for BPT-BZ-CMP to adsorb FCV to reach an equilibrium, and the maximum adsorption capacity was 347.8 mg·g-1. The Liu and pseudo-second-order kinetic models properly fit the adsorption equilibrium and kinetic data, respectively. The adsorption process was a spontaneous process, and the hydrogen bonding, π-π interaction and C-H···π interaction enhanced the adsorption of FCV on BPT-BZ-CMP. BPT-BZ-CMP maintained a good adsorption capacity after four consecutive adsorption-desorption cycle experiments. This study confirmed the potential of BPT-BZ-CMP as efficient sorbent to remove FCV from aqueous solutions.

The oral manifestations and related mechanisms of COVID-19 caused by SARS-CoV-2 infection.

Coronavirus disease 2019 (COVID-19) was reported to be associated with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection, and patients present mostly with respiratory symptoms. There have been an increasing number of reports on oral manifestations, and some of these signs are informative in terms of identifying SARS-CoV-2 infection. The goal of present study was to review and synthesize the clinical characteristics and underlying mechanisms of COVID-19 oral manifestations, as well as to evaluate the factors influencing SARS-CoV-2 infectivity, in order to conduct further in-depth investigations and help clinicians diagnose COVID-19 patients exhibiting oral symptoms.

Using machine learning models to predict the duration of the recovery of COVID-19 patients hospitalized in Fangcang shelter hospital during the Omicron BA. 2.2 pandemic.

Background: Factors that may influence the recovery of patients with confirmed SARS-CoV-2 infection hospitalized in the Fangcang shelter were explored, and machine learning models were constructed to predict the duration of recovery during the Omicron BA. 2.2 pandemic. Methods: A retrospective study was conducted at Hongqiao National Exhibition and Convention Center Fangcang shelter (Shanghai, China) from April 9, 2022 to April 25, 2022. The demographics, clinical data, inoculation history, and recovery information of the 13,162 enrolled participants were collected. A multivariable logistic regression model was used to identify independent factors associated with 7-day recovery and 14-day recovery. Machine learning algorithms (DT, SVM, RF, DT/AdaBoost, AdaBoost, SMOTEENN/DT, SMOTEENN/SVM, SMOTEENN/RF, SMOTEENN+DT/AdaBoost, and SMOTEENN/AdaBoost) were used to build models for predicting 7-day and 14-day recovery. Results: Of the 13,162 patients in the study, the median duration of recovery was 8 days (interquartile range IQR, 6-10 d), 41.31% recovered within 7 days, and 94.83% recovered within 14 days. Univariate analysis showed that the administrative region, age, cough medicine, comorbidities, diabetes, coronary artery disease (CAD), hypertension, number of comorbidities, CT value of the ORF gene, CT value of the N gene, ratio of ORF/IC, and ratio of N/IC were associated with a duration of recovery within 7 days. Age, gender, vaccination dose, cough medicine, comorbidities, diabetes, CAD, hypertension, number of comorbidities, CT value of the ORF gene, CT value of the N gene, ratio of ORF/IC, and ratio of N/IC were related to a duration of recovery within 14 days. In the multivariable analysis, the receipt of two doses of the vaccination vs. unvaccinated (OR = 1.118, 95% CI = 1.003-1.248; p = 0.045), receipt of three doses of the vaccination vs. unvaccinated (OR = 1.114, 95% CI = 1.004-1.236; p = 0.043), diabetes (OR = 0.383, 95% CI = 0.194-0.749; p = 0.005), CAD (OR = 0.107, 95% CI = 0.016-0.421; p = 0.005), hypertension (OR = 0.371, 95% CI = 0.202-0.674; p = 0.001), and ratio of N/IC (OR = 3.686, 95% CI = 2.939-4.629; p < 0.001) were significantly and independently associated with a duration of recovery within 7 days. Gender (OR = 0.736, 95% CI = 0.63-0.861; p < 0.001), age (30-70) (OR = 0.738, 95% CI = 0.594-0.911; p < 0.001), age (>70) (OR = 0.38, 95% CI = 0292-0.494; p < 0.001), receipt of three doses of the vaccination vs. unvaccinated (OR = 1.391, 95% CI = 1.12-1.719; p = 0.0033), cough medicine (OR = 1.509, 95% CI = 1.075-2.19; p = 0.023), and symptoms (OR = 1.619, 95% CI = 1.306-2.028; p < 0.001) were significantly and independently associated with a duration of recovery within 14 days. The SMOTEEN/RF algorithm performed best, with an accuracy of 90.32%, sensitivity of 92.22%, specificity of 88.31%, F1 score of 90.71%, and AUC of 89.75% for the 7-day recovery prediction; and an accuracy of 93.81%, sensitivity of 93.40%, specificity of 93.81%, F1 score of 93.42%, and AUC of 93.53% for the 14-day recovery prediction. Conclusion: Age and vaccination dose were factors robustly associated with accelerated recovery both on day 7 and day 14 from the onset of disease during the Omicron BA. 2.2 wave. The results suggest that the SMOTEEN/RF-based model could be used to predict the probability of 7-day and 14-day recovery from the Omicron variant of SARS-CoV-2 infection for COVID-19 prevention and control policy in other regions or countries. This may also help to generate external validation for the model.

Antibody response after vaccination against SARS-CoV-2 in adults with hematological malignancies: a systematic review and meta-analysis.

Vaccines against SARS-CoV-2 have shown remarkable efficacy and thus constitute an important preventive option against coronavirus disease 2019 (COVID-19), especially in fragile patients. We aimed to systematically analyze the outcomes of patients with hematological malignancies who received vaccination and to identify specific groups with differences in outcomes. The primary end point was antibody response after full vaccination (2 doses of mRNA or one dose of vector- based vaccines). We identified 49 studies comprising 11,086 individuals. Overall risk of bias was low. The pooled response for hematological malignancies was 64% (95% confidence interval [CI]: 59-69; I²=93%) versus 96% (95% CI: 92-97; I²=44%) for solid cancer and 98% (95% CI: 96-99; I²=55%) for healthy controls (P<0.001). Outcome was different across hematological malignancies (P<0.001). The pooled response was 50% (95% CI: 43-57; I²=84%) for chronic lymphocytic leukemia, 76% (95% CI: 67-83; I²=92%) for multiple myeloma, 83% (95% CI: 69-91; I²=85%) for myeloproliferative neoplasms, 91% (95% CI: 82-96; I²=12%) for Hodgkin lymphoma, and 58% (95% CI: 44-70; I²=84%) for aggressive and 61% (95% CI: 48-72; I²=85%) for indolent non-Hodgkin lymphoma. The pooled response for allogeneic and autologous hematopoietic cell transplantation was 82% and 83%, respectively. Being in remission and prior COVID-19 showed significantly higher responses. Low pooled response was identified for active treatment (35%), anti-CD20 therapy ≤1 year (15%), Bruton kinase inhibition (23%), venetoclax (26%), ruxolitinib (42%), and chimeric antigen receptor T-cell therapy (42%). Studies on timing, value of boosters, and long-term efficacy are needed. This study is registered with PROSPERO (clinicaltrials gov. Identifier: CRD42021279051).

A Review of Bioactive Compounds against Porcine Enteric Coronaviruses.

Pig diarrhea is a universal problem in the process of pig breeding, which seriously affects the development of the pig industry. Porcine enteric coronaviruses (PECoVs) are common pathogens causing diarrhea in pigs, currently including transmissible gastroenteritis virus (TGEV), porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV) and swine acute diarrhea syndrome coronavirus (SADS-CoV). With the prosperity of world transportation and trade, the spread of viruses is becoming wider and faster, making it even more necessary to prevent PECoVs. In this paper, the host factors required for the efficient replication of these CoVs and the compounds that exhibit inhibitory effects on them were summarized to promote the development of drugs against PECoVs. This study will be also helpful in discovering general host factors that affect the replication of CoVs and provide references for the prevention and treatment of other CoVs.

Accurate quantification of SARS-CoV-2 RNA by isotope dilution mass spectrometry and providing a correction of reverse transcription efficiency in droplet digital PCR.

The novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 505 million confirmed cases, including over 6 million deaths. Reference materials (RMs) of SARS-CoV-2 RNA played a crucial role in performance evaluation and quality control of testing laboratories. As the potential primary characterization method of RMs, reverse transcription digital PCR (RT-dPCR) measures the copy number of RNA, but the accuracy of reverse transcription (RT) efficiency has yet to be confirmed. This study established a method of enzymatic digestion followed by isotope dilution mass spectrometry (IDMS), which does not require an RT reaction, to quantify in vitro-transcribed SARS-CoV-2 RNA. RNA was digested to nucleotide monophosphate (NMP) within 15 min and analyzed by IDMS within 5 min. The consistency among the results of four different NMPs demonstrated the reliability of the proposed method. Compared to IDMS, the quantitative result of RT-dPCR turned out to be about 10% lower, possibly attributed to the incompleteness of the reverse transcription process. Therefore, the proposed approach could be valuable and reliable for quantifying RNA molecules and evaluating the RT efficiency of RT-based methods.

Assessing Age-Specific Vaccination Strategies and Post-vaccination Reopening Policies for COVID-19 Control Using SEIR Modeling Approach.

As the availability of COVID-19 vaccines, it is badly needed to develop vaccination guidelines to prioritize the vaccination delivery in order to effectively stop COVID-19 epidemic and minimize the loss. We evaluated the effect of age-specific vaccination strategies on the number of infections and deaths using an SEIR model, considering the age structure and social contact patterns for different age groups for each of different countries. In general, the vaccination priority should be given to those younger people who are active in social contacts to minimize the number of infections, while the vaccination priority should be given to the elderly to minimize the number of deaths. But this principle may not always apply when the interaction of age structure and age-specific social contact patterns is complicated. Partially reopening schools, workplaces or households, the vaccination priority may need to be adjusted accordingly. Prematurely reopening social contacts could initiate a new outbreak or even a new pandemic out of control if the vaccination rate and the detection rate are not high enough. Our result suggests that it requires at least nine months of vaccination (with a high vaccination rate > 0.1%) for Italy and India before fully reopening social contacts in order to avoid a new pandemic.

Controlling Multiple COVID-19 Epidemic Waves: An Insight from a Multi-scale Model Linking the Behaviour Change Dynamics to the Disease Transmission Dynamics.

COVID-19 epidemics exhibited multiple waves regionally and globally since 2020. It is important to understand the insight and underlying mechanisms of the multiple waves of COVID-19 epidemics in order to design more efficient non-pharmaceutical interventions (NPIs) and vaccination strategies to prevent future waves. We propose a multi-scale model by linking the behaviour change dynamics to the disease transmission dynamics to investigate the effect of behaviour dynamics on COVID-19 epidemics using game theory. The proposed multi-scale models are calibrated and key parameters related to disease transmission dynamics and behavioural dynamics with/without vaccination are estimated based on COVID-19 epidemic data (daily reported cases and cumulative deaths) and vaccination data. Our modeling results demonstrate that the feedback loop between behaviour changes and COVID-19 transmission dynamics plays an essential role in inducing multiple epidemic waves. We find that the long period of high-prevalence or persistent deterioration of COVID-19 epidemics could drive almost all of the population to change their behaviours and maintain the altered behaviours. However, the effect of behaviour changes fades out gradually along the progress of epidemics. This suggests that it is essential to have not only persistent, but also effective behaviour changes in order to avoid subsequent epidemic waves. In addition, our model also suggests the importance to maintain the effective altered behaviours during the initial stage of vaccination, and to counteract relaxation of NPIs, it requires quick and massive vaccination to avoid future epidemic waves.

Evaluation of factors contributing to variability of qualitative and quantitative proficiency testing for SARS-CoV-2 nucleic acid detection.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to unprecedented social and economic disruption. Many nucleic acid testing (NAT) laboratories in China have been established to control the epidemic better. This proficiency testing (PT) aims to evaluate the participants' performance in qualitative and quantitative SARS-CoV-2 NAT and to explore the factors that contribute to differences in detection capabilities. Two different concentrations of RNA samples (A, B) were used for quantitative PT. Pseudovirus samples D, E (different concentrations) and negative sample (F) were used for qualitative PT. 50 data sets were reported for qualitative PT, of which 74.00% were entirely correct for all samples. Forty-two laboratories participated in the quantitative PT. 37 submitted all gene results, of which only 56.76% were satisfactory. For qualitative detection, it is suggested that laboratories should strengthen personnel training, select qualified detection kits, and reduce cross-contamination to improve detection accuracy. For quantitative detection, the results of the reverse transcription digital PCR (RT-dPCR) method were more comparable and reliable than those of reverse transcription quantitative PCR (RT-qPCR). The copy number concentration of ORF1ab and N in samples A and B scattered in 85, 223, 50, and 106 folds, respectively. The differences in the quantitative result of RT-qPCR was mainly caused by the non-standard use of reference materials and the lack of personnel operating skills. Comparing the satisfaction of participants participating in both quantitative and qualitative proficiency testing, 95.65% of the laboratories with satisfactory quantitative results also judged the qualitative results correctly, while 85.71% of the laboratories with unsatisfactory quantitative results were also unsatisfied with their qualitative judgments. Therefore, the quantitative ability is the basis of qualitative judgment. Overall, participants from hospitals reported more satisfactory results than those from enterprises and universities. Therefore, surveillance, daily qualitiy control and standardized operating procedures should be strengthened to improve the capability of SARS-CoV-2 NAT.

Ending the COVID-19 pandemic: We still have a long way to go.

Spread of the severe acute respiratory syndrome coronavirus 2 B.1.1.529 (Omicron) variant, which led to increased global hospitalizations for coronavirus disease 2019, generated concern about immune evasion and the duration of protection from vaccines, and undermined humanity's confidence in ending the epidemic. The sudden mutation and origin of Omicron is even more of a mystery. The article highlights the virological characteristics and possible origins of Omicron and the global threats and challenges it poses, as well as strategies to deal with it.