The Reduction of SARS-CoV-2 RNA Concentration in the Presence of Sewer Biofilms

Wastewater surveillance has been widely used to track the prevalence of SARS-CoV-2 in communities. Although some studies have investigated the decay of SARS-CoV-2 RNA in wastewater, understanding about its fate during wastewater transport in real sewers is still limited. This study aims to assess the impact of sewer biofilms on the dynamics of SARS-CoV-2 RNA concentration in naturally contaminated real wastewater (raw influent wastewater without extra SARS-CoV-2 virus/gene seeding) using a simulated laboratory-scale sewer system. The results indicated that, with the sewer biofilms, a 90% concentration reduction of the SARS-CoV-2 RNA was observed within 2 h both in wastewater of gravity (GS, gravity-driven sewers) and rising main (RM, pressurized sewers) sewer reactors. In contrast, the 90% reduction time was 8–26 h in control reactors without biofilms. The concentration reduction of SARS-CoV-2 RNA in wastewater was significantly more in the presence of sewer biofilms. In addition, an accumulation of c.a. 260 and 110 genome copies/cm2 of the SARS-CoV-2 E gene was observed in the sewer biofilm samples from RM and GS reactors within 12 h, respectively. These results confirmed that the in-sewer concentration reduction of SARS-CoV-2 RNA in wastewater was likely caused by the partition to sewer biofilms. The need to investigate the in-sewer dynamic of SARS-CoV-2 RNA, such as the variation of RNA concentration in influent wastewater caused by biofilm attachment and detachment, was highlighted by the significantly enhanced reduction rate of SARS-CoV-2 RNA in wastewater of sewer biofilm reactors and the accumulation of SARS-CoV-2 RNA in sewer biofilms. Further research should be conducted to investigate the in-sewer transportation of SARS-CoV-2 and their RNA and evaluate the role of sewer biofilms in leading to underestimates of COVID-19 prevalence in communities.

A trimeric spike-based COVID-19 vaccine candidate induces broad neutralization against SARS-CoV-2 variants.

COVID-19 pandemic caused by SARS-CoV-2 infection has an impact on global public health and social economy. The emerging immune escape of SARS-CoV-2 variants pose great challenges to the development of vaccines based on original strains. The development of second-generation COVID-19 vaccines to induce immune responses with broad-spectrum protective effects is a matter of great urgency. Here, a prefusion-stabilized spike (S) trimer protein based on B.1.351 variant was expressed and prepared with CpG7909/aluminum hydroxide dual adjuvant to investigate the immunogenicity in mice. The results showed that the candidate vaccine could induce a significant receptor binding domain-specific antibody response and a substantial interferon-γ-mediated immune response. Furthermore, the candidate vaccine also elicited robust cross-neutralization against the pseudoviruses of the original strain, Beta variant, Delta variant and Omicron variant. The vaccine strategy of S-trimer protein formulated with CpG7909/aluminum hydroxide dual adjuvant may be considered a means to increase vaccine effectiveness against future variants.

TransMUSE: Transferable Traffic Prediction in MUlti-Service Edge Networks.

The Covid-19 pandemic has forced the workforce to switch to working from home, which has put significant burdens on the management of broadband networks and called for intelligent service-by-service resource optimization at the network edge. In this context, network traffic prediction is crucial for operators to provide reliable connectivity across large geographic regions. Although recent advances in neural network design have demonstrated potential to effectively tackle forecasting, in this work we reveal based on real-world measurements that network traffic across different regions differs widely. As a result, models trained on historical traffic data observed in one region can hardly serve in making accurate predictions in other areas. Training bespoke models for different regions is tempting, but that approach bears significant measurement overhead, is computationally expensive, and does not scale. Therefore, in this paper we propose TransMUSE (Transferable Traffic Prediction in MUlti-Service Edge Networks), a novel deep learning framework that clusters similar services, groups edge-nodes into cohorts by traffic feature similarity, and employs a Transformer-based Multi-service Traffic Prediction Network (TMTPN), which can be directly transferred within a cohort without any customization. We demonstrate that TransMUSE exhibits imperceptible performance degradation in terms of mean absolute error (MAE) when forecasting traffic, compared with settings where a model is trained for each individual edge node. Moreover, our proposed TMTPN architecture outperforms the state-of-the-art, achieving up to 43.21% lower MAE in the multi-service traffic prediction task. To the best of our knowledge, this is the first work that jointly employs model transfer and multi-service traffic prediction to reduce measurement overhead, while providing fine-grained accurate demand forecasts for edge services provisioning.

Predicting the correct dose in children: Role of computational Pediatric Physiological-based pharmacokinetics modeling tools.

The pharmacokinetics (PKs) and safety of medications in particular groups can be predicted using the physiologically-based pharmacokinetic (PBPK) model. Using the PBPK model may enable safe pediatric clinical trials and speed up the process of new drug research and development, especially for children, a population in which it is relatively difficult to conduct clinical trials. This review summarizes the role of pediatric PBPK (P-PBPK) modeling software in dose prediction over the past 6 years and briefly introduces the process of general P-PBPK modeling. We summarized the theories and applications of this software and discussed the application trends and future perspectives in the area. The modeling software's extensive use will undoubtedly make it easier to predict dose prediction for young patients.

Neutralization mechanism of a human antibody with pan-coronavirus reactivity including SARS-CoV-2.

Frequent outbreaks of coronaviruses underscore the need for antivirals and vaccines that can counter a broad range of coronavirus types. We isolated a human antibody named 76E1 from a COVID-19 convalescent patient, and report that it has broad-range neutralizing activity against multiple α- and ß-coronaviruses, including the SARS-CoV-2 variants. 76E1 also binds its epitope in peptides from γ- and δ-coronaviruses. 76E1 cross-protects against SARS-CoV-2 and HCoV-OC43 infection in both prophylactic and therapeutic murine animal models. Structural and functional studies revealed that 76E1 targets a unique epitope within the spike protein that comprises the highly conserved S2' site and the fusion peptide. The epitope that 76E1 binds is partially buried in the structure of the SARS-CoV-2 spike trimer in the prefusion state, but is exposed when the spike protein binds to ACE2. This observation suggests that 76E1 binds to the epitope at an intermediate state of the spike trimer during the transition from the prefusion to the postfusion state, thereby blocking membrane fusion and viral entry. We hope that the identification of this crucial epitope, which can be recognized by 76E1, will guide epitope-based design of next-generation pan-coronavirus vaccines and antivirals.

Artificial neural network-based estimation of COVID-19 case numbers and effective reproduction rate using wastewater-based epidemiology.

As a cost-effective and objective population-wide surveillance tool, wastewater-based epidemiology (WBE) has been widely implemented worldwide to monitor the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentration in wastewater. However, viral concentrations or loads in wastewater often correlate poorly with clinical case numbers. To date, there is no reliable method to back-estimate the coronavirus disease 2019 (COVID-19) case numbers from SARS-CoV-2 concentrations in wastewater. This greatly limits WBE in achieving its full potential in monitoring the unfolding pandemic. The exponentially growing SARS-CoV-2 WBE dataset, on the other hand, offers an opportunity to develop data-driven models for the estimation of COVID-19 case numbers (both incidence and prevalence) and transmission dynamics (effective reproduction rate). This study developed artificial neural network (ANN) models by innovatively expanding a conventional WBE dataset to include catchment, weather, clinical testing coverage and vaccination rate. The ANN models were trained and evaluated with a comprehensive state-wide wastewater monitoring dataset from Utah, USA during May 2020 to December 2021. In diverse sewer catchments, ANN models were found to accurately estimate the COVID-19 prevalence and incidence rates, with excellent precision for prevalence rates. Also, an ANN model was developed to estimate the effective reproduction number from both wastewater data and other pertinent factors affecting viral transmission and pandemic dynamics. The established ANN model was successfully validated for its transferability to other states or countries using the WBE dataset from Wisconsin, USA.

The Evolution Model of Public Risk Perception Based on Pandemic Spreading Theory under Perspective of COVID-19

After the occurrence of public health emergencies, due to the uncertainty of the evolution of events and the asymmetry of pandemic information, the public’s risk perception will fluctuate dramatically. Excessive risk perception often causes the public to overreact to emergencies, resulting in irrational behaviors, which have a negative impact on economic development and social order. However, low-risk perception will reduce individual awareness of prevention and control, which is not conducive to the implementation of government pandemic prevention and control measures. Therefore, it is of great significance to accurately evaluate public risk perception for improving government risk management. This paper took the evolution of public risk perception based on the COVID-19 region as the research object. First, we analyze the characteristics of infectious diseases in the evolution of public risk perception of public health emergencies. Second, we analyze the characteristics of risk perception transmission in social networks. Third, we establish the dynamic model of public risk perception evolution based on SEIR, and the evolution mechanism of the public risk perception network is revealed through simulation experiments. Finally, we provide policy suggestions for government departments to deal with public health emergencies based on the conclusions of this study.

Comprehensive mapping of binding hot spots of SARS-CoV-2 RBD-specific neutralizing antibodies for tracking immune escape variants.

BACKGROUND: The receptor-binding domain (RBD) variants of SARS-CoV-2 could impair antibody-mediated neutralization of the virus by host immunity; thus, prospective surveillance of antibody escape mutants and understanding the evolution of RBD are urgently needed. METHODS: Using the single B cell cloning technology, we isolated and characterized 93 RBD-specific antibodies from the memory B cells of four COVID-19 convalescent individuals in the early stage of the pandemic. Then, global RBD alanine scanning with a panel of 19 selected neutralizing antibodies (NAbs), including several broadly reactive NAbs, was performed. Furthermore, we assessed the impact of single natural mutation or co-mutations of concern at key positions of RBD on the neutralization escape and ACE2 binding function by recombinant proteins and pseudoviruses. RESULTS: Thirty-three amino acid positions within four independent antigenic sites (1 to 4) of RBD were identified as valuable indicators of antigenic changes in the RBD. The comprehensive escape mutation map not only confirms the widely circulating strains carrying important immune escape RBD mutations such as K417N, E484K, and L452R, but also facilitates the discovery of new immune escape-enabling mutations such as F486L, N450K, F490S, and R346S. Of note, these escape mutations could not affect the ACE2 binding affinity of RBD, among which L452R even enhanced binding. Furthermore, we showed that RBD co-mutations K417N, E484K, and N501Y present in B.1.351 appear more resistant to NAbs and human convalescent plasma from the early stage of the pandemic, possibly due to an additive effect. Conversely, double mutations E484Q and L452R present in B.1.617.1 variant show partial antibody evasion with no evidence for an additive effect. CONCLUSIONS: Our study provides a global view of the determinants for neutralizing antibody recognition, antigenic conservation, and RBD conformation. The in-depth escape maps may have value for prospective surveillance of SARS-CoV-2 immune escape variants. Special attention should be paid to the accumulation of co-mutations at distinct major antigenic sites. Finally, the new broadly reactive NAbs described here represent new potential opportunities for the prevention and treatment of COVID-19.

Improving Public Toilet Environment and Hygiene Practices in an Asian City: Voices From Hong Kong Residents.

Toilet hygiene is an important preventive measure for infectious diseases, including severe acute respiratory syndrome (SARS) and COVID-19. This study explored public's opinions on improving toilet environment and hygiene practices in Hong Kong. A mixed-method approach was applied. We conducted 4 focus groups plus 3 individual interviews among the Hong Kong Chinese, followed by a questionnaire survey with 300 respondents recruited from various districts. Difference in response distributions between groups with different demographics was tested by Pearson χ2 test. Instead of advocating for advanced toilet facilities, respondents were mostly concerned about basic hygiene issues. Malfunctioning facilities resulting from poor toilet management, such as clogged toilets, stained facilities, and problematic flushing systems, were most cited as barriers to toilet hygiene practices. Three quarters of the survey respondents expressed concerns over worn and poorly maintained toilets, shortage of janitors, and cleansing supplies. However, respondents who were older (P < .001), less educated (P < .001), and had lower income (P = .001) were significantly more likely to find hygiene conditions in public toilets satisfactory. The findings reflected the substandard of the current provisions as a developed city in Asia. Enhanced efforts by the government to maintain basic toilet supplies and facilities is the key to improving public compliance to toilet hygiene practices.

China's practice to prevent and control COVID-19 in the context of large population movement.

BACKGROUND: The emerging infectious disease, coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), poses a serious threat in China and worldwide. Challenged by this serious situation, China has taken many measures to contain its transmission. This study aims to systematically review and record these special and effective practices, in hope of benefiting for fighting against the ongoing worldwide pandemic. METHODS: The measures taken by the governments was tracked and sorted on a daily basis from the websites of governmental authorities (e.g. National Health Commission of the People's Republic of China). And the measures were reviewed and summarized by categorizations, figures and tables, showing an ever-changing process of combating with an emerging infectious disease. The population shift levels, daily local new diagnosed cases, daily mortality and daily local new cured cases were used for measuring the effect of the measures. RESULTS: The practices could be categorized into active case surveillance, rapid case diagnosis and management, strict follow-up and quarantine of persons with close contacts, and issuance of guidance to help the public understand and adhere to control measures, plus prompt and effective high-level policy decision, complete activation of the public health system, and full involvement of the society. Along with the measures, the population shift levels, daily local new diagnosed cases, and mortality were decreased, and the daily local new cured cases were increased in China. CONCLUSIONS: China's practices are effective in controlling transmission of SARS-CoV-2. Considering newly occurred situations (e.g. imported cases, work resumption), the control measures may be adjusted.