COVID-19 vaccines as boosters or first doses: Simulating scenarios to minimize infections and deaths. (preprint)

Public health authorities face the issue of optimal vaccine distribution during spread of pandemics. In this paper, we study the optimal way to distribute a finite stock of COVID-19 doses between first or second doses for unvaccinated individuals and third doses (booster shots) for fully vaccinated individuals. We introduce a novel compartmental model that accommodates for vaccinated populations. This Booster model is implemented to simulate two prototypes of populations: one with a highly infected and highly vaccinated proportion, and another with a low infected and vaccinated percentage. We namely use sample data from Russia and Djibouti respectively. Our findings show that, to minimize the deaths for the first type of populations, around one quarter of the vaccines should be employed as booster shots and the rest as first and second doses. On the other hand, the second type of populations can minimize their number of deaths by mainly focusing on administering the initial two doses, rather than giving any booster shots. The novel Booster model allows us to study the effect of the third dose on a community and provides a useful tool to draw public policies on the distribution of vaccines during pandemics.

A Comparative Experimental and Computational Study on the Nature of the Pangolin-CoV and COVID-19 Omicron (preprint)

The relationship between pangolin-CoV and SARS-CoV-2 has been a subject of debate. Further evidence of a special relationship between the two viruses can be found by the fact that all known COVID-19 viruses have abnormally hard outer shell (low M disorder; i.e., low content of intrinsically disordered residues in the membrane (M) protein) that so far was found in CoVs associated with burrowing animals, such as rabbits and pangolins, in which transmission involves virus remaining in buried feces for a long time. While a hard outer shell is necessary for viral survival, a harder inner shell could also help. For this reason, the N disorder range of pangolin-CoVs, not bat-CoVs, more closely matches that of SARS-CoV-2 especially when Omicron is included. The low N disorder (i.e., low content of intrinsically disordered residues in the nucleocapsid (N) protein), first observed in pangolin-CoV-2017 amd later in Omicron, is associated with attenuation according to the Shell-Disorder-Model. Our experimental study revealed that pangolin-CoV-2017 and SARS-CoV-2 Omicron (XBB.1.16 subvariant) show similar attenuations with respect to viral growth and plaque formation. Subtle differences have been observed that are consistent with disorder-centric computational analysis.

Exercise Intolerance in Long Covid After 24 Months From Severe Acute Disease: is There Room for Improvement? (preprint)

Introduction: Long COVID is a complex and multisystemic condition, where dyspnea, fatigue, post-exertional malaise, cognitive impairment, decreased functional capacity, and deterioration in quality of life are the most incident clinical features. Few studies have reported cardiopulmonary alterations 24 months after severe COVID-19 infection.  Objective: to evaluate the functional capacity of individuals with persistent symptoms after severe COVID-19 infection compared to control individuals without symptomatic COVID or mild COVID after 24 months.  Methods: This is a case-control study assessing 34 individuals divided into 2 groups (severe COVID-19 with long COVID and a control group consisting of asymptomatic/mild acute COVID-19 with no long COVID) regarding functional capacity by 6-minute walk test (6MWT) associated with gas analysis, spirometry, respiratory muscle strength and quality of life. Results: During the 6MWT, an important lower heart rate (HR) was observed for the COVID group, with greater exertional perception, a significant decrease in the distance covered, and a low value of O2 uptake (V̇O2) and minute ventilation, in addition to very low quality of life scores, especially in aspects of functional capacity and physical limitations.  Conclusion: individuals who have severe COVID-19 and persist with symptoms have low functional capacity, low V̇O2, low HR behavior, and low quality of life. 

Accumulation dynamics of defective genomes during experimental evolution of two betacoronaviruses (preprint)

Virus-encoded replicases often generate aberrant RNA genomes, known as defective viral genomes (DVGs). When coinfected with a helper virus providing necessary proteins, DVGs can multiply and spread. While DVGs depend on the helper virus for propagation, they can disrupt infectious virus replication, impact immune responses, and affect viral persistence or evolution. Understanding the dynamics of DVGs alongside standard viral genomes during infection remains unclear. To address this, we conducted a long-term experimental evolution of two betacoronaviruses, the human coronavirus OC43 (HCoV-OC43) and the murine hepatitis virus (MHV), in cell culture at both high and low multiplicities of infection (MOI). We then performed RNA-seq at regular time intervals, reconstructed DVGs, and analyzed their accumulation dynamics. Our findings indicate that DVGs evolved to exhibit greater diversity and abundance, with deletions and insertions being the most common types. Notably, some high MOI deletions showed very limited temporary existence, while others became prevalent over time. We observed differences in DVG abundance between high and low MOI conditions in HCoV-OC43 samples. The size distribution of HCoV-OC43 genomes with deletions differed between high and low MOI passages. In low MOI lineages, short and long DVGs were most common, with an additional cluster in high MOI lineages which became more prevalent along evolutionary time. MHV also showed variations in DVG size distribution at different MOI conditions, though less pronounced compared to HCoV-OC43, suggesting a more random distribution of DVG sizes. We identified hotspot regions for deletions that evolved at high MOI, primarily within cistrons encoding structural and accessory proteins. In conclusion, our study illustrates the widespread formation of DVGs during betacoronavirus evolution, influenced by MOI and cell- and virus-specific factors.

Identification of Promising SARS-CoV-2 Main Protease (Mpro) and Spike Protein Inhibitors From Edible Mushroom: A Computational Approach (preprint)

Coronaviruses infect lungs leading to death due to asphyxiation. SARS-CoV-2 is treated by targeting symptoms, repurposing drugs and plasma therapy. Several synthetic drugs are being prescribed that cause major side effects in liver, kidney and heart. Therefore new compounds with low toxicity must be investigated. We have identified antiviral compounds like Eritadenine, Gallic Acid, Ergosterol Peroxide and Pleuran from various edible mushrooms such as Lentinula edodes , Agaricus bisporus , Pleutorus ostreatus and Hericium erinaceus with evidence of literature review. The docking and simulation studies with the targets of SARS-CoV-2 such as Main Protease (M Pro) and Spike Protein were highly successful. In silico ADMET studies further proved that these compounds are druggable with low toxicity. These compounds have potential to prevent the cellular entry to prohibit assembly of new viruses inside the cell. But further studies are required to substantiate their bioactivity claim by in vitro and in vivo assay methods.

Adversity Builds Character? Restricted health service utilization and subsequent positive self-care behavior during the early COVID-19 pandemic in China (preprint)

Background During the COVID-19 pandemic, the reallocation of health resources and the restrictions on daily life imposed by epidemic prevention and control measures to some extent have severely affected the healthcare demand of the general population, but those impacts on adults’ self-care behavior and daily lives remain unclear. This study aimed to investigate the effect of restricted health service utilization arising from the COVID-19 pandemic on self-care behavior among different populations, particularly vulnerable groups, the correlations between restricted health service utilization and self-care behavior were also quantified and compared by subgroup analysis.Methods Data on demographics, socioeconomic, health status, and self-care behavior were collected in “The Early China COVID-19 Survey”, it is a cross-sectional anonymous online survey of the general population in China. Self-care behavior was measured by four indicators: weight control(WC), physical activity(PA), prevention behavior(PB) and Online medical consultation(OMC). The multiple linear models and binary logistic regression were used to examine whether restricted health service utilization (RHSU) is associated with self-care behaviors; also, adjusted multivariate logistic regression was used to analyse subgroup heterogeneity.Results In total, 8,428 adult participants completed the survey, the mean OMC score was 1.51(SD 1.34), the mean PB score was 18.17 (SD 3.44), and the proportion of participants who engaged in WC and PA was 42.30% and 62.57%, respectively. According to the multiple regression model, the RHSU was significantly positively correlated with all four indicators of self-care(WC: OR = 1.34, p < 0.001, PA: OR = 1.34, p < 0.05, MC: OR = 1.30, p < 0.001, PB:coef = 0.16, p < 0.05). Also we observed some significant differences in the intensity of this relationship by subgroup analysis, precisely, OMC(high vs moderate vs. low infection-risk level: OR = 1.48; 1.41; 1.19, p < 0.1), PA(high vs Moderate and low infection-risk level: OR = 1.51, p < 0.05), PB(Chronic disease groups vs no: coef = 0.46;0.1, p < 0.05).Conclusions Restricted health service utilization due to the pandemic had positive correlations with self-care behavior outcomes, and the intensity of partial correlation was significantly different in the subgroups of living area infection risk levels and chronic diseases. These findings have practical value for improving self-care behavior in adult populations during the pandemic.

Testing condensation capture to monitor the airborne microbiome (preprint)

Humans are constantly shedding millions of microbes into their environment, including pathogens like the virus that causes COVID-19. Unfortunately, monitoring aerosolized microbes is difficult due to low biomass and rapid sample degradation. But condensing water out of the air to capture the microbes within it may be a way to side-step these problems. To test this, researchers collected aerosols over the course of 8 hours in a laboratory setting via condensation or active impingement. The condensation method was highly efficient and had a yield of over 95% compared to expected values. There were no significant differences in the microbial community composition collected using the condensation method compared to impingement. More than 70% of the identified microbes belonged to the Streptophyta and Pseudomonadales taxa. While this work did not assess viability, it suggests that condensation of atmospheric humidity is a suitable method to capture airborne microbes and could potentially be utilized to surveil airborne microbial communities in sensitive indoor settings. Further work could provide insight into the efficacy of this new tool to investigate airborne microbes in more variable settings and assess the potential of pairing condensation with microfluidic sensing devices.

ACP-Dnnel: Anti-coronavirus Peptides Prediction based on Deep Neural Network Ensemble Learning (preprint)

Background The ongoing COVID-19 pandemic has caused global economic crisis and dramatic loss of human life. There is an urgent need for safe and efficient anti-coronavirus infection drugs. Anti-coronavirus peptides (ACovPs) can inhibit coronavirus infection. With high-efficiency, low-toxicity, and broad-spectrum inhibitory effects on coronaviruses, they are promising candidates to be developed into a new type of anti-coronavirus drug. Experiment is the traditional way of ACovPs identification, which is less efficient and more expensive. With the accumulation of experimental data on ACovPs, computational prediction provides a cheaper and faster way to find anti-coronavirus peptides candidates.Methods In this study, we integrated several state-of-the-art machine learning methodologies to build nine classification models for the prediction of ACovPs. These models were pretrained using deep neural networks, and the performance of our ensemble model, ACP-Dnnel, was evaluated across three datasets and independent dataset.Results The highest accuracy of ACP-Dnnel reaches 98%, and the MCC value exceeds 0.9. On three different datasets, its average accuracy is 96.33%. After the latest independent data set validation, ACP-Dnnel improved at MCC, Sn and ACC values by 10.1%, 16.4% and 7.3% respectively. It is suggested that ACP-Dnnel can be helpful for the laboratory identification of ACovPs, speeding up the anti-coronavirus peptide drug discovery and development. We constructed the web server of anti-coronavirus peptides prediction and it is available at http://150.158.148.228:5000/.

An Agent-Based Model for COVID-19 in Bangladesh (preprint)

BackgroundThe COVID-19 pandemic, that has resulted in millions of deaths and hundreds of millions of cases worldwide, continues to affect the lives, health and economy of various countries including Bangladesh. Despite the high proportion of asymptomatic cases and relatively low mortality, the viruss spread had been a significant public health problem for densely populated Bangladesh. With the healthcare system at stress, understanding the disease dynamics in the unique Bangladesh context became essential to guide policy decisions. MethodsWith a goal to capture the COVID-19 disease dynamics, we developed two stochastic Agent-Based Models (ABMs) considering the key characteristics of COVID-19 in Bangladesh, which vastly differ from the developed countries. We have implemented our ABMs extending the popular (but often inadequate) SIR model, where the infected population is sub-divided into Asymptomatic, Mild Symptomatic and Severe Symptomatic populations. One crucial issue in Bangladesh is the lack of enough COVID-19 tests as well as unwillingness of people to do the tests resulting in much less number of official positive cases than the actual reality. Although not directly relevant to the epidemiological process, our model attempts to capture this crucial aspect while calibrating against official daily test-positive cases. Our first model, ABM-BD, divides the population into age-groups that interact among themselves based on an aggregated Contact Matrix. Thus ABM-BD considers aggregate agents and avoids direct agent level interactions as the number of agents are prohibitively large in our context. We also implement a scaled down model, ABM-SD, that is capable of simulating agent level interactions. ResultsABM-BD was quite well-calibrated for Dhaka: the Mean Absolute Percentage Error (MAPE) between official and forecasted cases was 1.845 approximately during the period between April 4, 2020 and March 31, 2021. After an initial model validation, we conducted a number of experiments - including retrospective scenario analysis, and hypothetical future scenario analysis. For example, ABM-BD has demonstrated the trade off between a strict lockdown with low infections and a relaxed lockdown with reduced burden on the economy. Leveraging the true agent level interaction capability of ABD-SD, we have also successfully analyzed the relative severity of different strains thereby (confidently) capturing the effect of different virus mutations. ConclusionsOur models have adequately captured the COVID-19 disease transmission dynamics in Bangladesh. This is a useful tool to forecast the impact of interventions to assist policymakers in planning appropriate COVID response. Our models will be particularly useful in a resource constrained setting in countries like Bangladesh where the population size is huge.

Effects of hydrometeorological and other factors on SARS-CoV-2 reproduction number in three contiguous countries of Tropical Andean South America: a spatiotemporally disaggregated time series analysis. (preprint)

Background: The COVID-19 pandemic has caused societal disruption globally and South America has been hit harder than other lower-income regions. This study modeled effects of 6 weather variables on district-level SARS-CoV-2 reproduction numbers (Rt) in three contiguous countries of Tropical Andean South America (Colombia, Ecuador, and Peru), adjusting for environmental, policy, healthcare infrastructural and other factors. Methods: Daily time-series data on SARS-CoV-2 infections were sourced from health authorities of the three countries at the smallest available administrative level. Rt values were calculated and merged by date and unit ID with variables from a Unified COVID-19 dataset and other publicly available sources for May - December 2020. Generalized additive mixed effects models were fitted. Findings: Relative humidity and solar radiation were inversely associated with SARS-CoV-2 Rt. Days with radiation above 1,000 KJ/m2 saw a 1.3%, and those with humidity above 50%, a 1.0% reduction in Rt. Transmission was highest in densely populated districts, and lowest in districts with poor healthcare access and on days with least population mobility. Temperature, region, aggregate government policy response and population age structure had little impact. The fully adjusted model explained 3.9% of Rt variance. Interpretation: Dry atmospheric conditions of low humidity increase, and higher solar radiation decrease district-level SARS-CoV-2 reproduction numbers, effects that are comparable in magnitude to population factors like lockdown compliance. Weather monitoring could be incorporated into disease surveillance and early warning systems in conjunction with more established risk indicators and surveillance measures.

Healthcare workers perceptions and medically approved COVID-19 infection risk: understanding the mental health dimension of the pandemic. A German hospital case study (preprint)

Introduction. This study analyses how healthcare workers (HCWs) perceived risks, protection and preventive measures during the COVID-19 pandemic in relation to medically approved risks and organisational measures. The aim is to explore blind spots of pandemic protection and make mental health needs of HCWs visible. Methods. We have chosen an optimal-case scenario of a high-income country with a well-resourced hospital sector and low HCW infection rate at the organisational level to explore governance gaps in HCW protection. A German multi-method hospital study at Hannover Medical School served as empirical case; document analysis, expert information and survey data (n=1163) were collected as part of a clinical study into SARS-CoV-2 serology testing during the second wave of the pandemic (November 2020-February 2021). Selected survey items included perceptions of risks, protection and preventive measures. Descriptive statistical analysis and regression were undertaken for gender, profession and COVID-19 patient care. Results. The results reveal a low risk of 1% medically approved infections among participants, but a much higher mean personal risk estimate of 15%. The majority (68.4%) expressed some to very strong fear of acquiring infection at the workplace. Individual protective behaviour and compliance with protective workplace measures were estimated as very high. Yet only about half of the respondents felt strongly protected by the employer; 12% even perceived no or little protection. Gender and contact with COVID-19 patients had no significant effect on the estimations of infection risks and protective workplace behaviour, but nursing was correlated with higher levels of personal risk estimations and fear of infection. Conclusions. A strong mismatch between low medically approved risk and personal risk perceptions of HCWs brings stressors and threats into view, that may be preventable through better information and risk communication and through investment in mental health and inclusion in pandemic preparedness plans.

Psychosocial factors associated with mental health and quality of life during the COVID-19 pandemic among low-income urban dwellers in Peninsular Malaysia (preprint)

Background and aimsThe mental well-being among low-income urban populations is arguably challenged more than any other population amid the COVID-19 pandemic. This study investigates factors associated with depression and anxiety symptoms, and quality of life among Malaysias multi-ethnic urban lower-income communities. MethodsThis is a community-based house-to-house survey conducted from September to November 2020 at the Petaling district in Selangor, Malaysia. Five hundred and four households were identified using random sampling, and heads of eligible households were recruited. Inclusion criteria were age [≥] 18 years with monthly household income [≤]RM6960 (estimated USD 1600) without acute psychiatric illness. The PHQ-9, GAD-7 and EQ-5D were used for depression, anxiety, and quality of life. Multivariable logistic regression was performed for the final analysis. ResultsA total of 432 (85.7%) respondents with a mean age of 43.1 years completed the survey. Mild to severe depression was detected in 29.6%, mild to severe anxiety in 14.7%, and problematic quality of life in 27.8% of respondents. Factors associated with mild to severe depression were younger age, chronic health conditions, past stressful events, lack of communication gadgets and lack of assets or commercial property. While respiratory diseases, marital status, workplace issues, financial constraints, absence of investments, substance use and lack of rental income were associated with mild to severe anxiety. Not attributing poverty to structural issues, help-seeking from professionals, and self-stigma were barriers, while resiliency facilitated good psychological health. Problematic quality of life was associated with depression, older age, unemployment, cash shortage, hypertension, diabetes, stressful life events and low health literacy. ConclusionsA higher proportion had reported mild to severe anxiety and depression symptoms in the sampled urban poor population than previous pre-pandemic reports. The psychosocial determinants should inform policy and direct future research within this underserved population.

Avoiding false positive SARS-CoV-2 rapid antigen test results with point-of-care molecular testing on residual test buffer (preprint)

Objectives: Antigen-based rapid diagnostic tests (Ag-RDTs) have been widely used for the detection of SARS-CoV-2 during the Covid-19 pandemic. In settings of low disease prevalence, such as asymptomatic community testing, national guidelines recommend molecular confirmation of positive Ag-RDT results. This often requires patients to be recalled for repeat specimen recollection and subsequent testing in reference laboratories. This project assessed the use of a point-of-care molecular method for SARS-CoV-2 detection on-site at a volunteer-led asymptomatic community testing site, using the residual test buffer (RTB) from positive Ag-RDTs. Methods: The Abbott COVID-19 ID NOW assay was performed on RTB from two Ag-RDTs: the Abbott Panbio COVID-19 Ag Rapid Test Device and the BTNX Rapid Response COVID-19 Antigen Rapid Test Device. All RTBs were tested using real-time RT-PCR at a reference laboratory using the ThermoFisher TaqPath COVID-19 Combo kit which was used to assign positive Ag-RDTs results as true or false positives. Analytical specificity of the ID NOW was assessed with a panel of various respiratory organisms. Results: Of 419 positive Ag-RDTs from 5148 tests performed, ID NOW testing of the RTB was positive in 100% of the samples characterized as true positives by RT-PCR. No SARS-CoV-2 detections by ID NOW were observed from 10 specimens characterized as false positive Ag-RDTs, or from contrived specimens with various respiratory organisms. Conclusions: The use of on-site molecular testing on RTB provides a suitable option for rapid confirmatory testing of positive Ag-RDTs, thereby obviating the need for specimen recollection for molecular testing at local reference laboratories.

The BNT162b2 mRNA SARS-CoV-2 vaccine induces transient afucosylatedIgG1 in naive but not antigen-experienced vaccinees (preprint)

The onset of severe SARS-CoV-2 infection is characterized by the presence of afucosylated IgG1 responses against the viral spike (S) protein, which can trigger exacerbated inflammatory responses. Here, we studied IgG glycosylation after BNT162b2 SARS-CoV-2 mRNA vaccination to explore whether vaccine-induced S protein expression on host cells also generates afucosylated IgG1 responses. SARS-CoV-2 naive individuals initially showed a transient afucosylated anti-S IgG1 response after the first dose, albeit to a lower extent than severely ill COVID-19 patients. In contrast, previously infected, antigen-experienced individuals had low afucosylation levels, which slightly increased after immunization. Afucosylation levels after the first dose correlated with low fucosyltransferase 8 (FUT8) expression levels in a defined plasma cell subset. Remarkably, IgG afucosylation levels after primary vaccination correlated significantly with IgG levels after the second dose. Further studies are needed to assess efficacy, inflammatory potential, and protective capacity of afucosylated IgG responses.

Monospecific and bispecific monoclonal SARS-CoV-2 neutralizing antibodies that maintain potency against B.1.617 (preprint)

COVID-19 pathogen SARS-CoV-2 has infected hundreds of millions and caused over 5 million deaths to date. Although multiple vaccines are available, breakthrough infections occur especially by emerging variants. Effective therapeutic options such as monoclonal antibodies (mAbs) are still critical. Here, we report the development, cryo-EM structures, and functional analyses of mAbs that potently neutralize SARS-CoV-2 variants of concern. By high-throughput single cell sequencing of B cells from spike receptor binding domain (RBD) immunized animals, we identified two highly potent SARS-CoV-2 neutralizing mAb clones that have single-digit nanomolar affinity and low-picomolar avidity, and generated a bispecific antibody. Lead antibodies showed strong inhibitory activity against historical SARS-CoV-2 and several emerging variants of concern. We solved several cryo-EM structures at ~3 Angstrom resolution of these neutralizing antibodies in complex with prefusion spike trimer ectodomain, and revealed distinct epitopes, binding patterns, and conformations. The lead clones also showed potent efficacy in vivo against authentic SARS-CoV-2 in both prophylactic and therapeutic settings. We also generated and characterized a humanized antibody to facilitate translation and drug development. The humanized clone also has strong potency against both the original virus and the B.1.617.2 Delta variant. These mAbs expand the repertoire of therapeutics against SARS-CoV-2 and emerging variants.

Elucidating design principles for engineering cell-derived vesicles to inhibit SARS-CoV-2 infection (preprint)

The ability of pathogens to develop drug resistance is a global health challenge. The SARS-CoV-2 virus presents an urgent need wherein several variants of concern resist neutralization by monoclonal antibody therapies and vaccine-induced sera. Decoy nanoparticles--cell-mimicking particles that bind and inhibit virions--are an emerging class of therapeutics that may overcome such drug resistance challenges. To date, we lack quantitative understanding as to how design features impact performance of these therapeutics. To address this gap, here we perform a systematic, comparative evaluation of various biologically-derived nanoscale vesicles, which may be particularly well-suited to sustained or repeated administration in the clinic due to low toxicity, and investigate their potential to inhibit multiple classes of model SARS-CoV-2 virions. A key finding is that such particles exhibit potent antiviral efficacy across multiple manufacturing methods, vesicle subclasses, and virus-decoy binding affinities. In addition, these cell-mimicking vesicles effectively inhibit model SARS-CoV-2 variants that evade monoclonal antibodies and recombinant protein-based decoy inhibitors. This study provides a foundation of knowledge that may guide the design of decoy nanoparticle inhibitors for SARS-CoV-2 and other viral infections.

A kinetic model considering the decline of antibody level and vaccination of COVID-19 (preprint)

In order to evaluate the decline in antibody levels and the impact of vaccination on the spread of the epidemic, we establish COVID-19 dynamic models that consider the decline in antibody levels and the effects of vaccination, and retrospectively evaluate the epidemic situation in England. Based on the epidemic data in England from September 1 to October 31, 2020, considering the continuous decline in the antibody level of COVID-19 recovers, an improved SEIR infectious disease dynamics model that considers the reinfection of recovers due to the decline in antibody levels is established. The kinetic parameters of the SEIR model are obtained by fitting. On this basis, a SEIRV infectious disease dynamic model with vaccination is established to study the impact of different vaccination rates and vaccine failure rates on the development of the epidemic in England. We obtain the lower the vaccine failure rate, the fewer new cases. When the vaccination rate is fixed at 0.005 (equivalent to 250000 people vaccinated every day), the peak of the epidemic will decrease with the decrease of vaccine failure rate. The peak value when the failure rate is 0.001 is 81.4% lower than the peak value when the failure rate is 0.01, and the peak value when the failure rate is 0.01 is 89.5% lower than the peak value when the failure rate is 0.02. When the failure rate is less than 0.01, the peak time will advance with the decrease of failure rate; when the failure rate is greater than 0.01, the peak time will be delayed with the decrease of failure rate; when the failure rate is 0.01, the peak time is 528 days later than that when the failure rate is 0.001 and 295 days later than that when the failure rate is 0.05. On the 60th day of vaccination, the vaccine failure rate of 0.002 decreases the number of cases by 5.8% compared with the vaccine failure rate of 0.01; on the 70th day of vaccination, the vaccine failure rate of 0.002 reduces the number of cases by 9.1% compared with the vaccine failure rate of 0.01. Therefore, with the extension of time, the vaccine with low failure rate has a more obvious effect on reducing the number of cases than the vaccine with high failure rate. When the vaccine failure rate is fixed at 0.005, we study the impact of different vaccination rates on the spread of the epidemic in England, the result shows that the peak of epidemic situation decreases with the increase of vaccination rate, and the peak time advance with the increase of vaccination rate, when the vaccination rate is 0.025, the peak decreases by 74.8% and the peak time was 114 days earlier than that when the vaccination rate is 0.005.Therefore, the higher the vaccine efficiency and vaccination rate, the lower the peak of the epidemic. On the basis of improving the effectiveness of vaccines, increasing the vaccination rate is of practical significance for controlling the spread of the epidemic.

Peptide-antibody Fusions Engineered by Phage Display Exhibit Ultrapotent and Broad Neutralization of SARS-CoV-2 Variants (preprint)

The COVID-19 pandemic has been exacerbated by the emergence of variants of concern (VoCs). Many VoC mutations are found in the viral spike protein (S-protein), and are thus implicated in host infection and response to therapeutics. Bivalent neutralizing antibodies (nAbs) targeting the S-protein receptor-binding domain (RBD) are promising therapeutics for COVID-19, but are limited due to low potency and vulnerability to RBD mutations found in VoCs. To address these issues, we used naive phage-displayed peptide libraries to isolate and optimize 16-residue peptides that bind to the RBD or the N-terminal domain (NTD) of the S-protein. We fused these peptides to the N-terminus of a moderate affinity nAb to generate tetravalent peptide-IgG fusions, and showed that both classes of peptides were able to improve affinities for the S-protein trimer by >100-fold (apparent KD <1 pM). Critically, cell-based infection assays with a panel of six SARS-CoV-2 variants demonstrate that an RBD-binding peptide was able to enhance the neutralization potency of a high-affinity nAb >100-fold. Moreover, this peptide-IgG was able to neutralize variants that were resistant to the same nAb in the bivalent IgG format. To show that this approach is general, we fused the same peptide to a clinically approved nAb drug, and showed that it rescued neutralization against a resistant variant. Taken together, these results establish minimal peptide fusions as a modular means to greatly enhance affinities, potencies, and breadth of coverage of nAbs as therapeutics for SARS-CoV-2.

Immunoglobulin G1 Fc glycosylation as an early hallmark of severe COVID-19 (preprint)

Background Immunoglobulin G1 (IgG1) effector functions are impacted by the structure of fragment crystallizable (Fc) tail-linked N-glycans. Low fucosylation levels on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein specific (anti-S) IgG1 has been described as a hallmark of severe coronavirus disease 2019 (COVID-19) and may lead to activation of macrophages via immune complexes thereby promoting inflammatory responses, altogether suggesting involvement of IgG1 Fc glycosylation modulated immune mechanisms in COVID-19. Methods In this prospective, observational single center cohort study, IgG1 Fc glycosylation was analyzed by liquid chromatography - mass spectrometry following affinity capturing from serial plasma samples of 159 SARS-CoV-2 infected patients. Findings At baseline close to disease onset, anti-S IgG1 glycosylation was highly skewed when compared to total plasma IgG1. A rapid, general reduction in glycosylation skewing was observed during the disease course. Low anti-S IgG1 galactosylation and sialylation as well as high bisection were early hallmarks of disease severity, whilst high galactosylation and sialylation and low bisection were found in patients with low disease severity. In line with these observations, anti-S IgG1 glycosylation correlated with various inflammatory markers. Interpretation Association of low galactosylation, sialylation as well as high bisection with disease severity suggests that Fc-glycan modulated interactions contribute to disease mechanism. Further studies are needed to understand how anti-S IgG1 glycosylation may contributes to disease mechanism and to evaluate its biomarker potential. Funding This project received funding from the European Commission's Horizon2020 research and innovation program for H2020-MSCA-ITN IMforFUTURE, under grant agreement number 721815.

Child and caregiver mental health during COVID-19 (preprint)

There are urgent calls for research into the mental health consequences of living through the COVID-19 pandemic. We describe caregiver and child mental health over 12 months using Australias only nationally representative, repeated cross-sectional survey of caregivers with children (0-17 years). N=2020 caregivers in June 2020, N=1434 in September 2020, and N=2508 in July 2021 provided data. Caregivers rated their mental health (Kessler-6), and impacts of the pandemic on their own and their childrens mental health. Data were weighted using national distribution of age, gender, number of children, state/territory and neighbourhood-level disadvantage. Mental health measures worsened over time. There was an unequal distribution of impacts based on caregiver gender, child age and family socioeconomic characteristics. Negative impacts were more common with current or cumulative lockdown. The indirect impacts of COVID-19 are real and concerning. Mental health must be central to the immediate and ongoing pandemic responses for families and children. What is known about this topic?- The global evidence shows that, for general adult populations, psychological distress peaked in the first months of the COVID-19 pandemic before appearing to rebound. - Less is known about long-term mental health consequences of living through the pandemic, especially for caregivers and children. There are urgent calls for research. - Due to low infection rates, Australias experience can provide insight into the mental health impacts of lockdown without the compounding direct harms of the virus. What this study adds- From June 2020 to July 2021, caregivers reported declining mental health and increasing negative mental health impacts of COVID-19 for themselves and their children. - There was an unequal distribution of mental health impacts based on caregiver gender, child age and family socioeconomic characteristics. - Lockdown (current or cumulative) was detrimental for caregivers and childrens mental health. Pandemic response and recovery planning must consider families mental health.