Slight reduction in SARS-CoV-2 exposure viral load due to masking results in a significant reduction in transmission with widespread implementation

Masks and respirators for prevention of respiratory infections: a state of the science review

SUMMARYThis narrative review and meta-analysis summarizes a broad evidence base on the benefits-and also the practicalities, disbenefits, harms and personal, sociocultural and environmental impacts-of masks and masking. Our synthesis of evidence from over 100 published reviews and selected primary studies, including re-analyzing contested meta-analyses of key clinical trials, produced seven key findings. First, there is strong and consistent evidence for airborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory pathogens. Second, masks are, if correctly and consistently worn, effective in reducing transmission of respiratory diseases and show a dose-response effect. Third, respirators are significantly more effective than medical or cloth masks. Fourth, mask mandates are, overall, effective in reducing community transmission of respiratory pathogens. Fifth, masks are important sociocultural symbols; non-adherence to masking is sometimes linked to political and ideological beliefs and to widely circulated mis- or disinformation. Sixth, while there is much evidence that masks are not generally harmful to the general population, masking may be relatively contraindicated in individuals with certain medical conditions, who may require exemption. Furthermore, certain groups (notably D/deaf people) are disadvantaged when others are masked. Finally, there are risks to the environment from single-use masks and respirators. We propose an agenda for future research, including improved characterization of the situations in which masking should be recommended or mandated; attention to comfort and acceptability; generalized and disability-focused communication support in settings where masks are worn; and development and testing of novel materials and designs for improved filtration, breathability, and environmental impact.

COVID-19: did the masks work?

During the early stages of the COVID-19 pandemic, we called for mandatory public masking to 'flatten the curve'. We helped formulate a national standard (SWiFT 19) for barrier facemasks, and, using a novel laser-based approach, we determined that mask efficacy is dependent on both fabric and fit; with both variables being inversely related. Herein, we take a retrospective view of the role of masks during the pandemic and surmise that, on the balance of evidence to date, masks were effective at stemming the spread of SARS-CoV-2 and may well be an effective early control strategy for potential future respiratory pandemics.

Efficacy of facemasks in preventing transmission of COVID-19 in non-healthcare settings: A scoping review

Background

During the COVID-19 pandemic, an abundance of literature relating to the efficacy of face masks on reducing transmission of COVID-19 in non-healthcare settings emerged.

Aim/objective

The aim of this scoping review was to allow the identification of: types of evidence conducted in this area; knowledge gaps and common concepts relating to mask efficacy in non-healthcare settings.

Methods

A comprehensive literature search was conducted in PubMed, CINAHL, MEDLINE, Embase and the Irish Management Institute bibliographic database on December 15th, 2021. All types of face masks were included. Of 722 records, 16 were included after full text screening.

Findings/results

Themes from an adapted model of Howard et al. framework were used to group results and identify common concepts. The grouped thematic results were then applied to the socio-ecological model. This illustrated the multifactorial elements determining the efficacy of masks themselves while also illustrating how other factors such as individual behaviours, social interactions, settings and national policy can influence the degree of the protective effect.

Discussion

The findings from this scoping review indicate that an abundance of experimental literature is available indicating that masks are effective at preventing COVID-19 transmission but their degree of efficacy is impacted by external factors. This review highlights that the quality of the evidence available is low.

Examining the relationship between COVID-19 and Bell's palsy: Experience of a single tertiary care center

BACKGROUND

While the etiology of Bell's palsy (BP) is largely unknown, current evidence shows it may occur secondary to the immune response following a viral infection. Recently, BP has been reported as a clinical manifestation of coronavirus disease (COVID-19).

OBJECTIVES

To investigate an association between COVID-19 infection and BP. Additionally, to evaluate the need for COVID-19 testing in patients who present with BP.

METHODS

Hospital records of patients who presented to a single tertiary care center with BP in 2020 and 2021 were reviewed for presenting symptoms, demographics, COVID-19 infection and vaccination status.

RESULTS

There was no statistically significant difference between patients with BP who had a positive or negative COVID test in terms of sex, BMI, age, race, smoking history or alcohol use. All 7 patients with BP and a positive COVID test were unvaccinated. Of the total cohort of 94 patients, 82 % were unvaccinated at the time of the study. None of the 17 patients who were vaccinated had a positive COVID test. A history of BP showed no statistical significance (10.3 % vs 14.3 %, p-value 0.73).

CONCLUSION

We discovered a limited cohort of patients who underwent COVID-19 testing at the time of presentation for BP. Though there have been recent studies suggesting a COVID-19 and BP, we were unable to clearly identify a relationship between COVID-19 and BP. Interestingly, all patients with facial paralysis and COVID-19 were unvaccinated. To further study this relationship, we recommend consideration of a COVID-19 test for any patient that presents with facial paralysis.

Analysis of the risk and pre-emptive control of viral outbreaks accounting for within-host dynamics: SARS-CoV-2 as a case study

In the era of living with COVID-19, the risk of localised SARS-CoV-2 outbreaks remains. Here, we develop a multiscale modelling framework for estimating the local outbreak risk for a viral disease (the probability that a major outbreak results from a single case introduced into the population), accounting for within-host viral dynamics. Compared to population-level models previously used to estimate outbreak risks, our approach enables more detailed analysis of how the risk can be mitigated through pre-emptive interventions such as antigen testing. Considering SARS-CoV-2 as a case study, we quantify the within-host dynamics using data from individuals with omicron variant infections. We demonstrate that regular antigen testing reduces, but may not eliminate, the outbreak risk, depending on characteristics of local transmission. In our baseline analysis, daily antigen testing reduces the outbreak risk by 45% compared to a scenario without antigen testing. Additionally, we show that accounting for heterogeneity in within-host dynamics between individuals affects outbreak risk estimates and assessments of the impact of antigen testing. Our results therefore highlight important factors to consider when using multiscale models to design pre-emptive interventions against SARS-CoV-2 and other viruses.

Modelling the viral dynamics of the SARS-CoV-2 Delta and Omicron variants in different cell types

We use viral kinetic models fitted to viral load data from in vitro studies to explain why the SARS-CoV-2 Omicron variant replicates faster than the Delta variant in nasal cells, but slower than Delta in lung cells, which could explain Omicron's higher transmission potential and lower severity. We find that in both nasal and lung cells, viral infectivity is higher for Omicron but the virus production rate is higher for Delta, with an estimated approximately 200-fold increase in infectivity and 100-fold decrease in virus production when comparing Omicron with Delta in nasal cells. However, the differences are unequal between cell types, and ultimately lead to the basic reproduction number and growth rate being higher for Omicron in nasal cells, and higher for Delta in lung cells. In nasal cells, Omicron alone can enter via a TMPRSS2-independent pathway, but it is primarily increased efficiency of TMPRSS2-dependent entry which accounts for Omicron's increased activity. This work paves the way for using within-host mathematical models to understand the transmission potential and severity of future variants.

The effect of shortening the quarantine period and lifting the indoor mask mandate on the spread of COVID-19: a mathematical modeling approach

In this paper, we present a mathematical model to assess the impact of reducing the quarantine period and lifting the indoor mask mandate on the spread of Coronavirus Disease 2019 (COVID-19) in Korea. The model incorporates important epidemiological parameters, such as transmission rates and mortality rates, to simulate the transmission of the virus under different scenarios. Our findings reveal that the impact of mask wearing fades in the long term, which highlights the crucial role of quarantine in controlling the spread of the disease. In addition, balancing the confirmed cases and costs, the lifting of mandatory indoor mask wearing is cost-effective; however, maintaining the quarantine period remains essential. A relationship between the disease transmission rate and vaccine efficiency was also apparent, with higher transmission rates leading to a greater impact of the vaccine efficiency. Moreover, our findings indicate that a higher disease transmission rate exacerbates the consequences of early quarantine release.

Education and COVID-19 excess mortality

We study the role of education during the COVID-19 epidemic in Italy. We compare excess mortality in 2020 and 2021 compared to the pre-pandemic mortality between municipalities with different shares of educated residents. We find that education initially played a strong protective role, which however quickly faded out. After pondering several alternative explanations, we tentatively interpret this finding as the outcome of the interplay between education, information and public health communication, whose availability and coherence varied along the epidemic.

Quantitative Analysis of SARS-CoV-2 Antibody Levels in Cancer Patients Post Three Doses of Immunization and Prior to Breakthrough COVID-19 Infections

(1) Background: COVID-19 vaccine effectiveness should be carefully evaluated and explicitly defined. To our knowledge, this is the first report to quantitatively evaluate humoral responses post 3 doses of SARS-CoV-2 immunization and prior to breakthrough COVID-19 infection in Canadian cancer patients. (2) Methods: In a prospective cohort study, we enrolled 185 cancer participants post COVID-19 vaccination in Kingston, Ontario, Canada. IgG antibodies against the SARS-CoV-2 spike receptor-binding domain were quantified by immunoassay post three doses of immunization. With the COVID-19 rapid antigen test and polymerase chain reaction (PCR), 16 breakthrough infections were identified. Results: Following SARS-CoV-2 vaccination (including BNT162b2, AZD1222, and mRNA-1273), the mean serum anti-spike protein antibody level was 197.2 BAU/mL (binding antibody unit, SD ± 393.9), 1335.9 BAU/mL (±3337.8), and 3164.8 BAU/mL (±6500.9) post the first, second, and third dose of vaccination. Observed differences were significant (p ≤ 0.001). The average antibody level of 3164.8 BAU/mL post the third dose was 89.9 times that of the seroconversion level (35.2 BAU/mL). This indicates that most vaccines approved are effective in producing robust antibody responses. In 11 breakthrough cases confirmed by PCR, prior to infection, the average antibody concentration was 3675.6 BAU/mL with the highest concentration being 9107.4 BAU/mL. Compared with this average antibody concentration of 3675.6 BAU/mL (104.4 times that of the seroconversion concentration), 0% of single dosed, 9.6% of double vaccinated, and 29.5% of triple vaccinated cancer patients had higher SARS-CoV-2 antibody levels. When patients were split into hematological and solid cancer, the hematological cancer group demonstrated lower serological responses than the solid cancer group in the first and second doses (first dose, average concentration 11.1 vs. 201.4 BAU/mL, respectively, p < 0.05; second dose, average concentration 441.5 vs. 1725.9 BAU/mL, respectively, p < 0.05). There was no difference in the third dose level (1756.3 vs. 2548.0 BAU/mL, p = 0.21). (4) Conclusions: Most vaccines were effective in producing robust antibody responses when more than one dose was given, and the more doses the higher the serological response. Likely due to the highly contagious nature of SARS-CoV-2 variants, a significant number of participants had SARS-CoV-2 antibody responses lower than the average antibody concentration prior to the known breakthrough infections. Additional vaccination is likely required to ensure immunity against infection by SARS-CoV-2.

Identifiability of parameters in mathematical models of SARS-CoV-2 infections in humans

Determining accurate estimates for the characteristics of the severe acute respiratory syndrome coronavirus 2 in the upper and lower respiratory tracts, by fitting mathematical models to data, is made difficult by the lack of measurements early in the infection. To determine the sensitivity of the parameter estimates to the noise in the data, we developed a novel two-patch within-host mathematical model that considered the infection of both respiratory tracts and assumed that the viral load in the lower respiratory tract decays in a density dependent manner and investigated its ability to match population level data. We proposed several approaches that can improve practical identifiability of parameters, including an optimal experimental approach, and found that availability of viral data early in the infection is of essence for improving the accuracy of the estimates. Our findings can be useful for designing interventions.

Multi-scale modelling reveals that early super-spreader events are a likely contributor to novel variant predominance

The emergence of new SARS-CoV-2 variants of concern (VOC) has hampered international efforts to contain the COVID-19 pandemic. VOCs have been characterized to varying degrees by higher transmissibility, worse infection outcomes and evasion of vaccine and infection-induced immunologic memory. VOCs are hypothesized to have originated from animal reservoirs, communities in regions with low surveillance and/or single individuals with poor immunologic control of the virus. Yet, the factors dictating which variants ultimately predominate remain incompletely characterized. Here we present a multi-scale model of SARS-CoV-2 dynamics that describes population spread through individuals whose viral loads and numbers of contacts (drawn from an over-dispersed distribution) are both time-varying. This framework allows us to explore how super-spreader events (SSE) (defined as greater than five secondary infections per day) contribute to variant emergence. We find stochasticity remains a powerful determinant of predominance. Variants that predominate are more likely to be associated with higher infectiousness, an SSE early after variant emergence and ongoing decline of the current dominant variant. Additionally, our simulations reveal that most new highly infectious variants that infect one or a few individuals do not achieve permanence in the population. Consequently, interventions that reduce super-spreading may delay or mitigate emergence of VOCs.

Determinants of SARS-CoV-2 Contagiousness in Household Contacts of Symptomatic Adult Index Cases

Background

Identifying determinants of the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) transmission in settings of contagion is fundamental to inform containment strategies. We assessed SARS-CoV-2 cycle threshold value (Ct) from the first diagnostic nasal-pharyngeal swab of symptomatic index cases and which demographic or clinical characteristics among cases and contacts are associated with transmission risk within households.

Methods

This is a retrospective prevalence study on secondary SARS-CoV-2 cases (SC) among the household contacts of symptomatic adult index cases randomly sampled from all the SARS-CoV-2-positive diagnostic nasopharyngeal swabs analyzed at our regional referral hospital (Amedeo di Savoia Hospital, Turin, Italy) in March, 2020. Index cases underwent a telephone survey to collect their demographic and clinical data and all their household contacts. The Ct value of RdRp gene from the first diagnostic swab of index cases was recorded and index cases were grouped according to Ct tertiles (A < first tertile, first ≤ B ≤ second tertile, C ≥ second tertile). Post hoc analysis was performed in SC as well as contacts that did not undergo SARS-CoV-2 testing but developed compatible signs and symptoms. Non-parametric tests and generalized linear models were run.

Results

Index (n = 72) and contact (n = 164) median age was 54 (48-63) and 32 (20-56) years, respectively. A total of 60, 50, and 54 subjects were contacts of group A, B, and C index cases, respectively; 35.9% of contacts were SC. Twenty-four further subjects (14.6%) met the criteria for symptom-based likely positive SC. The secondary attack rate was 36.0% (28.6-43.4), assuming a mean incubation period of 5 days and a maximum infectious period of 20 days. SC prevalence differed between Ct groups (53.3% A, 32.0% B, 20.4% C; p < 0.001). No difference in SC was found according to sex, presence of signs/symptoms, and COVID-19 severity of index cases, or according to contacts' sex and number per household. The age of both index cases [aOR 4.52 (1.2-17.0) for 60 vs. ≤45 years old] and contacts [aOR 3.66 (1.3-10.6) for 60 vs. ≤45years old] and the Ct of the index [aOR 0.17 (0.07-0.4) for Ct ≥ 31.8 vs. Ct < 24.4] independently associated with SC risk. Sensitivity analysis including symptoms-based likely positive SC supported all the previous results.

Conclusion

In confined transmission settings such as households, PCR Ct values may inform on the contagiousness of infected subjects and age may modulate transmission/contagion risk.

Considerations for the Safe Operation of Schools During the Coronavirus Pandemic

During the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, providing safe in-person schooling has been a dynamic process balancing evolving community disease burden, scientific information, and local regulatory requirements with the mandate for education. Considerations include the health risks of SARS-CoV-2 infection and its post-acute sequelae, the impact of remote learning or periods of quarantine on education and well-being of children, and the contribution of schools to viral circulation in the community. The risk for infections that may occur within schools is related to the incidence of SARS-CoV-2 infections within the local community. Thus, persistent suppression of viral circulation in the community through effective public health measures including vaccination is critical to in-person schooling. Evidence suggests that the likelihood of transmission of SARS-CoV-2 within schools can be minimized if mitigation strategies are rationally combined. This article reviews evidence-based approaches and practices for the continual operation of in-person schooling.

Mathematical Modeling of Vaccines That Prevent SARS-CoV-2 Transmission

SARS-CoV-2 vaccine clinical trials assess efficacy against disease (VEDIS), the ability to block symptomatic COVID-19. They only partially discriminate whether VEDIS is mediated by preventing infection completely, which is defined as detection of virus in the airways (VESUSC), or by preventing symptoms despite infection (VESYMP). Vaccine efficacy against transmissibility given infection (VEINF), the decrease in secondary transmissions from infected vaccine recipients, is also not measured. Using mathematical modeling of data from King County Washington, we demonstrate that if the Moderna (mRNA-1273QS) and Pfizer-BioNTech (BNT162b2) vaccines, which demonstrated VEDIS > 90% in clinical trials, mediate VEDIS by VESUSC, then a limited fourth epidemic wave of infections with the highly infectious B.1.1.7 variant would have been predicted in spring 2021 assuming rapid vaccine roll out. If high VEDIS is explained by VESYMP, then high VEINF would have also been necessary to limit the extent of this fourth wave. Vaccines which completely protect against infection or secondary transmission also substantially lower the number of people who must be vaccinated before the herd immunity threshold is reached. The limited extent of the fourth wave suggests that the vaccines have either high VESUSC or both high VESYMP and high VEINF against B.1.1.7. Finally, using a separate intra-host mathematical model of viral kinetics, we demonstrate that a 0.6 log vaccine-mediated reduction in average peak viral load might be sufficient to achieve 50% VEINF, which suggests that human challenge studies with a relatively low number of infected participants could be employed to estimate all three vaccine efficacy metrics.

ACE2 Receptor-Modified Algae-Based Microrobot for Removal of SARS-CoV-2 in Wastewater

The coronavirus SARS-CoV-2 can survive in wastewater for several days with a potential risk of waterborne human transmission, hence posing challenges in containing the virus and reducing its spread. Herein, we report on an active biohybrid microrobot system that offers highly efficient capture and removal of target virus from various aquatic media. The algae-based microrobot is fabricated by using click chemistry to functionalize microalgae with angiotensin-converting enzyme 2 (ACE2) receptor against the SARS-CoV-2 spike protein. The resulting ACE2-algae-robot displays fast (>100 μm/s) and long-lasting (>24 h) self-propulsion in diverse aquatic media including drinking water and river water, obviating the need for external fuels. Such movement of the ACE2-algae-robot offers effective "on-the-fly" removal of SARS-CoV-2 spike proteins and SARS-CoV-2 pseudovirus. Specifically, the active biohybrid microrobot results in 95% removal of viral spike protein and 89% removal of pseudovirus, significantly exceeding the control groups such as static ACE2-algae and bare algae. These results suggest considerable promise of biologically functionalized algae toward the removal of viruses and other environmental threats from wastewater.

Timing HIV infection with a simple and accurate population viral dynamics model

Clinical trials for HIV prevention can require knowledge of infection times to subsequently determine protective drug levels. Yet, infection timing is difficult when study visits are sparse. Using population nonlinear mixed-effects (pNLME) statistical inference and viral loads from 46 RV217 study participants, we developed a relatively simple HIV primary infection model that achieved an excellent fit to all data. We also discovered that Aptima assay values from the study strongly correlated with viral loads, enabling imputation of very early viral loads for 28/46 participants. Estimated times between infecting exposures and first positives were generally longer than prior estimates (average of two weeks) and were robust to missing viral upslope data. On simulated data, we found that tighter sampling before diagnosis improved estimation more than tighter sampling after diagnosis. Sampling weekly before and monthly after diagnosis was a pragmatic design for good timing accuracy. Our pNLME timing approach is widely applicable to other infections with existing mathematical models. The present model could be used to simulate future HIV trials and may help estimate protective thresholds from the recently completed antibody-mediated prevention trials.