Dose-response and type-dependent effects of antiviral drugs in anaerobic digestion of waste-activated sludge for biogas production.

In the context of the COVID-19 pandemic, antiviral drugs (AVDs) were heavily excreted into wastewater and subsequently enriched in sewage sludge due to their widespread use. The potential ecological risks of AVDs have attracted increasing attention, but information on the effects of AVDs on sludge anaerobic digestion (AD) is limited. In this study, two typical AVDs (lamivudine and ritonavir) were selected to investigate the responses of AD to AVDs by biochemical methane potential tests. The results indicated that the effects of AVDs on methane production from sludge AD were dose- and type-dependent. The increased ritonavir concentration (0.05-50 mg/kg TS) contributed to an 11.27-49.43% increase in methane production compared with the control. However, methane production was significantly decreased at high lamivudine doses (50 mg/kg TS). Correspondingly, bacteria related to acidification were affected when exposed to lamivudine and ritonavir. Acetoclastic and hydrotropic methanogens were inhibited at a high lamivudine dose, while ritonavir enriched methylotrophic and hydrotropic methanogens. Based on the analysis of intermediate metabolites, the inhibition of lamivudine and the promotion of ritonavir on acidification and methanation were confirmed. In addition, the existence of AVDs could affect sludge properties. Sludge solubilization was inhibited when exposed to lamivudine and enhanced by ritonavir, perhaps caused by their different structures and physicochemical properties. Moreover, lamivudine and ritonavir could be partially degraded by AD, but 50.2-68.8% of AVDs remained in digested sludge, implying environmental risks.

ACE2 in male genitourinary and endocrine systems: Does COVID-19 really affect these systems?

The virus that causes COVID-19(Corona Virus Disease 2019), SARS-CoV-2(Severe Acute Respiratory Syndrome Coronavirus 2), is causing a worldwide pandemic, posing a substantial threat to human health. Patients show signs of pneumonia, ARDS, shock, acute cardiac injury, acute kidney injury and other complications. The SARS-CoV-2 receptor is angiotensin converting enzyme 2 (ACE2), which is an important component of the renin-angiotensin system (RAS). In addition, TMPRSS2 or other cofactors are needed to allow the virus to enter the host. Clinical patients have exhibited varying degrees of genitourinary and endocrine system damage, and some studies have also reported potential risks to the genitourinary and endocrine systems. This article reviews the mechanism underlying SARS-CoV-2 infection and the current studies on the male genitourinary and endocrine systems and proposes that more attention should be directed towards human reproductive and endocrine health during the SARS-CoV-2 epidemic.

Using Real-Time PCR Fluorescence Reaction Values to Improve SARS-CoV-2 Virus Detection and Benefit Clinical Decision-Making.

This study aimed to compare the SARS-CoV-2 nucleic acid detection results of the BD MAX™ System and other platforms to formulate an optimized laboratory verification process. The re-examination of 400 samples determined as positive by BD MAX™ indicated that the inconsistency rate between BD MAX™ and the other platforms was 65.8%; the inconsistency rate of single-gene-positive results was as high as 99.2%. A receiver operating characteristic curve was drawn for the relative light unit (RLU) values of samples positive for a single gene, and RLU 800 was used as the cutoff. After setting the retest standard as single-gene positive and RLU ≥ 800, the number of the 260 BD MAX™ single-gene positives that needed to be confirmed again was 36 (13.8%) and the number that could be directly reported as negative was 224 (86.2%). This verification process can shorten the reporting period and speed up the epidemic adjustment time and turnover rate of special wards, thereby improving SARS-CoV-2 detection efficiency and clinical decision-making.

Seasonal trends in COVID-19 cases, hospitalizations, and mortality in the United States and Europe.

Determining whether SARS-CoV-2 exhibits seasonality like other respiratory viruses is critical for public health planning. We evaluated whether COVID-19 rates follow a seasonal pattern using time series models. We used time series decomposition to extract the annual seasonal component of COVID-19 case, hospitalization, and mortality rates from March 2020 through December 2022 for the United States and Europe. Models were adjusted for a country-specific stringency index to account for confounding by various interventions. Despite year-round disease activity, we identified seasonal spikes in COVID-19 from approximately November through April for all outcomes and in all countries. Our results support employing annual preventative measures against SARS-CoV-2, such as administering seasonal booster vaccines in a similar timeframe as those in place for influenza. Whether certain high-risk individuals may need more than one COVID-19 vaccine booster dose each year will depend on factors like vaccine durability against severe illness and levels of year-round disease activity.

Epidemiological characteristics of the B.1.526 SARS-CoV-2 variant.

To characterize the epidemiological properties of the B.1.526 SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) variant of interest, here we used nine epidemiological and population datasets and model-inference methods to reconstruct SARS-CoV-2 transmission dynamics in New York City, where B.1.526 emerged. We estimated that B.1.526 had a moderate increase (15 to 25%) in transmissibility, could escape immunity in 0 to 10% of previously infected individuals, and substantially increased the infection fatality risk (IFR) among adults 65 or older by >60% during November 2020 to April 2021, compared to estimates for preexisting variants. Overall, findings suggest that new variants like B.1.526 likely spread in the population weeks before detection and that partial immune escape (e.g., resistance to therapeutic antibodies) could offset prior medical advances and increase IFR. Early preparedness for and close monitoring of SARS-CoV-2 variants, their epidemiological characteristics, and disease severity are thus crucial to COVID-19 (coronavirus disease 2019) response.

Development and Evaluation of a Novel One-Step RT-qPCR Targeting the Vero Gene for the Identification of False-Positive Results Caused by Inactivated Virus Vaccine Contamination.

To identify false-positive SARS-CoV-2 test results caused by novel coronavirus inactivated vaccine contamination, a novel RT-qPCR targeting the ORF1ab and N genes of SARS-CoV-2 and Vero gene was developed. The amplification efficiency, precision, and lower limit of detection (LLOD) of the RT-qPCR assay were determined. A total of 346 clinical samples and 132 environmental samples were assessed, and the diagnostic performance was evaluated. The results showed that the amplification efficiency of the ORF1ab, N, and Vero genes was 95%, 97%, and 93%, respectively. The coefficients of variation of Ct values at a concentration of 3 × 104 copies/mL were lower than 5%. The LLOD for the ORF1ab, N, and Vero genes reached 8.0, 3.3, and 8.2 copies/reaction, respectively. For the 346 clinical samples, our RT-qPCR assay identified SARS-CoV-2-positive and SARS-CoV-2-negative samples with a sensitivity of 100.00% and a specificity of 99.30% and novel coronavirus inactivated vaccine-contaminated samples with a sensitivity of 100% and a specificity of 100%. For the environmental samples, our RT-qPCR assay identified novel coronavirus inactivated vaccine-contaminated samples with a sensitivity of 88.06% and a specificity of 95.38%. In conclusion, the RT-qPCR assay we established can be used to diagnose COVID-19 and, to a certain extent, false-positive results due to vaccine contamination.

Contact tracing reveals community transmission of COVID-19 in New York City.

Understanding SARS-CoV-2 transmission within and among communities is critical for tailoring public health policies to local context. However, analysis of community transmission is challenging due to a lack of high-resolution surveillance and testing data. Here, using contact tracing records for 644,029 cases and their contacts in New York City during the second pandemic wave, we provide a detailed characterization of the operational performance of contact tracing and reconstruct exposure and transmission networks at individual and ZIP code scales. We find considerable heterogeneity in reported close contacts and secondary infections and evidence of extensive transmission across ZIP code areas. Our analysis reveals the spatial pattern of SARS-CoV-2 spread and communities that are tightly interconnected by exposure and transmission. We find that locations with higher vaccination coverage and lower numbers of visitors to points-of-interest had reduced within- and cross-ZIP code transmission events, highlighting potential measures for curtailing SARS-CoV-2 spread in urban settings.

COVID-19 pandemic dynamics in South Africa and epidemiological characteristics of three variants of concern (Beta, Delta, and Omicron).

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) have been key drivers of new coronavirus disease 2019 (COVID-19) pandemic waves. To better understand variant epidemiologic characteristics, here we apply a model-inference system to reconstruct SARS-CoV-2 transmission dynamics in South Africa, a country that has experienced three VOC pandemic waves (i.e. Beta, Delta, and Omicron BA.1) by February 2022. We estimate key epidemiologic quantities in each of the nine South African provinces during March 2020 to February 2022, while accounting for changing detection rates, infection seasonality, nonpharmaceutical interventions, and vaccination. Model validation shows that estimated underlying infection rates and key parameters (e.g. infection-detection rate and infection-fatality risk) are in line with independent epidemiological data and investigations. In addition, retrospective predictions capture pandemic trajectories beyond the model training period. These detailed, validated model-inference estimates thus enable quantification of both the immune erosion potential and transmissibility of three major SARS-CoV-2 VOCs, that is, Beta, Delta, and Omicron BA.1. These findings help elucidate changing COVID-19 dynamics and inform future public health planning.

Do investors herd in a volatile market? Evidence of dynamic herding in Taiwan, China, and US stock markets

This article investigates whether investors exhibit herd behavior in a high market volatility state. A modified herding model with the Kalman filter and GARCH methodology is used to estimate the time-variation herding corresponding to each influential event. Our proposed model provides comprehensive results for the relationship between investor herding and the market state, which has been argued in the previous literature. We find that investors indeed herd in volatile markets, including the 2001 dot.com bubble and the 2009 global financial crisis. However, in recent years, anti-herding is prevalent and herding is slight even in turbulent markets, such as the 2020 Covid-19 pandemic.

COVID-19 pandemic dynamics in India, the SARS-CoV-2 Delta variant and implications for vaccination.

The Delta variant is a major SARS-CoV-2 variant of concern first identified in India. To better understand COVID-19 pandemic dynamics and Delta, we use multiple datasets and model-inference to reconstruct COVID-19 pandemic dynamics in India during March 2020-June 2021. We further use the large discrepancy in one- and two-dose vaccination coverage in India (53% versus 23% by end of October 2021) to examine the impact of vaccination and whether prior non-Delta infection can boost vaccine effectiveness (VE). We estimate that Delta escaped immunity in 34.6% (95% CI: 0-64.2%) of individuals with prior wild-type infection and was 57.0% (95% CI: 37.9-75.6%) more infectious than wild-type SARS-CoV-2. Models assuming higher VE among non-Delta infection recoverees, particularly after the first dose, generated more accurate predictions than those assuming no such increases (best-performing VE setting: 90/95% versus 30/67% baseline for the first/second dose). Counterfactual modelling indicates that high vaccination coverage for first vaccine dose in India combined with the boosting of VE among recoverees averted around 60% of infections during July-mid-October 2021. These findings provide support to prioritizing first-dose vaccination in regions with high underlying infection rates, given continued vaccine shortages and new variant emergence.

Interactions among common non-SARS-CoV-2 respiratory viruses and influence of the COVID-19 pandemic on their circulation in New York City.

BACKGROUND: Non-pharmaceutical interventions (NPIs) and voluntary behavioral changes during the COVID-19 pandemic have influenced the circulation of non-SARS-CoV-2 respiratory infections. We aimed to examine interactions among common non-SARS-CoV-2 respiratory virus and further estimate the impact of the COVID-19 pandemic on these viruses. METHODS: We analyzed incidence data for seven groups of respiratory viruses in New York City (NYC) during October 2015 to May 2021 (i.e., before and during the COVID-19 pandemic). We first used elastic net regression to identify potential virus interactions and further examined the robustness of the found interactions by comparing the performance of Seasonal Auto Regressive Integrated Moving Average (SARIMA) models with and without the interactions. We then used the models to compute counterfactual estimates of cumulative incidence and estimate the reduction during the COVID-19 pandemic period from March 2020 to May 2021, for each virus. RESULTS: We identified potential interactions for three endemic human coronaviruses (CoV-NL63, CoV-HKU, and CoV-OC43), parainfluenza (PIV)-1, rhinovirus, and respiratory syncytial virus (RSV). We found significant reductions (by ~70-90%) in cumulative incidence of CoV-OC43, CoV-229E, human metapneumovirus, PIV-2, PIV-4, RSV, and influenza virus during the COVID-19 pandemic. In contrast, the circulation of adenovirus and rhinovirus was less affected. CONCLUSIONS: Circulation of several respiratory viruses has been low during the COVID-19 pandemic, which may lead to increased population susceptibility. It is thus important to enhance monitoring of these viruses and promptly enact measures to mitigate their health impacts (e.g., influenza vaccination campaign and hospital infection prevention) as societies resume normal activities.

Factors affecting the transmission of SARS-CoV-2 in school settings.

BACKGROUND: Several studies have reported SARS-CoV-2 outbreaks in schools, with a wide range of secondary attack rate (SAR; range: 0-100%). We aimed to examine key risk factors to better understand SARS-CoV-2 transmission in schools. METHODS: We collected records of 35 SARS-CoV-2 school outbreaks globally published from January 2020 to July 2021 and compiled information on hypothesized risk factors. We utilized the directed acyclic graph (DAG) to conceptualize risk mechanisms, used logistic regression to examine each risk-factor group, and further built multirisk models. RESULTS: The best-fit model showed that the intensity of community transmission (adjusted odds ratio [aOR]: 1.11, 95% CI: 1.06-1.16, for each increase of 1 case per 10 000 persons per week) and individualism (aOR: 2.72, 95% CI: 1.50-4.95, above vs. below the mean) was associated higher risk, whereas preventive measures (aOR: 0.25, 95% CI: 0.19-0.32, distancing and masking vs. none) and higher population immunity (aOR: 0.57, 95% CI: 0.46-0.71) were associated with lower risk of SARS-CoV-2 transmission in schools. Compared with students in high schools, the aOR was 0.47 (95% CI: 0.23-0.95) for students in preschools and 0.90 (95% CI: 0.76-1.08) for students in primary schools. CONCLUSIONS: Preventive measures in schools (e.g., social distancing and mask wearing) and communal efforts to lower transmission and increase vaccination uptake (i.e., vaccine-induced population immunity) in the community should be taken to collectively reduce transmission and protect children in schools.

SARS-CoV-2 E484K Mutation Narrative Review: Epidemiology, Immune Escape, Clinical Implications, and Future Considerations.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread rapidly over the world and claimed million lives. The virus evolves constantly, and a swarm of mutants is a now major concern globally. Distinct variants could have independently converged on same mutation, despite being detected in different geographic regions, which suggested it could confer an evolutionary advantage. E484K has rapidly emerged and has frequently been detected in several SARS-CoV-2 variants of concern. In this study, we review the epidemiology and impact of E484K, its effects on neutralizing effect of several monoclonal antibodies, convalescent plasma, and post-vaccine sera.

Effects of simeprevir on the replication of SARS-CoV-2 in vitro and in transgenic hACE2 mice.

In a bid to contain the current COVID-19 (coronavirus disease 2019) pandemic, various countermeasures have been applied. To date, however, there is a lack of an effective drug for the treatment of COVID-19. Through molecular modelling studies, simeprevir, a protease inhibitor approved for the management of hepatitis C virus infection, has been predicted as a potential antiviral against SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), the causative agent of COVID-19. Here we assessed the efficacy of simeprevir against SARS-CoV-2 both in vitro in Vero E6 cells and in vivo in a human angiotensin-converting enzyme 2 (hACE2) transgenic mouse model. The results showed that simeprevir could inhibit SARS-CoV-2 replication in Vero E6 cells with a half-maximal effective concentration (EC50) of 1.41 ± 0.12 µM. In a transgenic hACE2 mouse model of SARS-CoV-2 infection, intraperitoneal administration of simeprevir at 10 mg/kg/day for 3 consecutive days failed to suppress viral replication. These findings collectively imply that simeprevir does not inhibit SARS-CoV-2 in vivo and therefore do not support its application as a treatment against COVID-19 at a dosage of 10 mg/kg/day.

Interactions between virus surrogates and sewage sludge vary by viral analyte: Recovery, persistence, and sorption.

Sewage sludge, as a reservoir of viruses, may pose threats to human health. Understanding how virus particles interact with sludge is the key to controlling virus exposure and transmission. In this study, we investigated the recovery, survivability, and sorption of four typical virus surrogates with different structures (Phi6, MS2, T4, and Phix174) in sewage sludge. The most effective elution method varies by viral analyte, while the ultrafiltration method could significantly reduce the recovery loss for all four viruses. Compared with nonenveloped viruses, the poor recoveries of Phi6 during elution (<15%) limited its efficient detection. The inactivation kinetics of four viruses in solid-containing sludge were significantly faster than those in solid-removed samples at 25 °C, indicating that the solid fraction of sludge played an important role in virus inactivation. Although enveloped Phi6 was more vulnerable in both solid-removed and solid-containing sludge samples, it could remain viable for several hours at 25 °C and several days at 4 °C, which may pose an infection risk during sludge collection, transportation, and treatment process. The adsorption and desorption behavior of viruses in sludge could be affected by virus envelope structure, capsid proteins, and virus particle size. Phi6 adsorption to sludge was great with log KF of 6.51 ± 0.53, followed by Phix174, MS2, and T4. Additionally, more than 95% of Phi6, MS2, and T4 adsorbed to sludge were strongly bound, and a considerable fraction of strongly-bound virus was confirmed to retain viability. These results shed light on the environmental behavior of viruses in sewage sludge and provide a theoretical basis for the risk assessment for sludge treatment and disposal.

Pain during and after coronavirus disease 2019: Chinese perspectives.

The coronavirus disease 2019 (COVID-19) global pandemic poses a major threat to human health and health care systems. Urgent prevention and control measures have obstructed patients' access to pain treatment, and many patients with pain have been unable to receive adequate and timely medical services. Many patients with COVID-19 report painful symptoms including headache, muscle pain, and chest pain during the initial phase of the disease. Persistent pain sequela in patients with COVID-19 has a physical or mental impact and may also affect the immune, endocrine, and other systems. However, the management and treatment of neurological symptoms such as pain are often neglected for patients hospitalized with COVID-19. Based on the China's early experience in the management of COVID-19 symptoms, the possible negative effects of pre-existing chronic pain in patients with COVID-19 and the challenges of COVID-19 prevention and control bring to the diagnosis and treatment of chronic pain are discussed. This review calls to attention the need to optimize pain management during and after COVID-19.

COVID-19 Screening for Hospitalized Patients: The Role of Expanded Hospital Surveillance in a Low Prevalence Setting.

PURPOSE: The COVID-19 pandemic poses a serious threat to healthcare workers and hospitalized patients. Early detection of COVID-19 cases is essential to control the spread in healthcare facilities. However, real-world data on the screening criteria for hospitalized patients remain scarce. We aimed to explore whether patients with negative results of pre-hospital screening for COVID-19 should be rescreened after admission in a low-prevalence (less than 3% of the world average) setting. PATIENTS AND METHODS: We retrospectively included patients in central Taiwan who were negative at the first screening but were newly diagnosed with pneumonia or had a body temperature above 38 degrees Celsius during their hospitalization. Each patient might be included as an eligible case several times, and the proportions of cases who were rescreened for COVID-19 and those diagnosed with COVID-19 were calculated. A logistic regression model was constructed to identify factors associated with rescreening. Reverse transcription-polymerase chain reaction tests were used to confirm the diagnosis of COVID-19. RESULTS: A total of 3549 cases eligible for COVID-19 rescreening were included. There were 242 cases (6.8%) who received rescreening. In the multivariable analysis, cases aged 75 years or older, those with potential exposure to SARS-CoV-2, or patients visiting specific departments, such as the Cardiovascular Center and Department of Neurology, were more likely to be rescreened. None was diagnosed with COVID-19 after rescreening. There was no known cluster infection outbreak in the hospital or in the local community during the study period and in the following two months. CONCLUSION: In Taiwan, a country with a low COVID-19 prevalence, it was deemed safe to rescreen only high-risk hospitalized patients. This strategy was effective and reduced unnecessary costs.

Development of a model-inference system for estimating epidemiological characteristics of SARS-CoV-2 variants of concern.

To support COVID-19 pandemic planning, we develop a model-inference system to estimate epidemiological properties of new SARS-CoV-2 variants of concern using case and mortality data while accounting for under-ascertainment, disease seasonality, non-pharmaceutical interventions, and mass-vaccination. Applying this system to study three variants of concern, we estimate that B.1.1.7 has a 46.6% (95% CI: 32.3-54.6%) transmissibility increase but nominal immune escape from protection induced by prior wild-type infection; B.1.351 has a 32.4% (95% CI: 14.6-48.0%) transmissibility increase and 61.3% (95% CI: 42.6-85.8%) immune escape; and P.1 has a 43.3% (95% CI: 30.3-65.3%) transmissibility increase and 52.5% (95% CI: 0-75.8%) immune escape. Model simulations indicate that B.1.351 and P.1 could outcompete B.1.1.7 and lead to increased infections. Our findings highlight the importance of preventing the spread of variants of concern, via continued preventive measures, prompt mass-vaccination, continued vaccine efficacy monitoring, and possible updating of vaccine formulations to ensure high efficacy.