Examining the interplay between face mask usage, asymptomatic transmission, and social distancing on the spread of COVID-19

Oscillating spatiotemporal patterns of COVID-19 in the United States

COVID-19 case rates in the US wax and wane in wave-like patterns over time, but the spatial patterns of these temporal epidemic waves have not been well characterized. By analyzing state- and county-level COVID-19 case rate data for spatiotemporal decomposition modes and oscillatory patterns, we demonstrate that the transmission dynamics of COVID-19 feature recurrent spatiotemporal patterns. In addition to the well-recognized national-level annual mid-winter surges, we demonstrate a prominent but previously unrecognized six-month north-south oscillation in the eastern US (Eastern US COVID-19 Oscillator-EUCO) that gives rise to regional sub-epidemics and travelling epidemic waves. We also demonstrate a second less prominent pattern that oscillates east-west in the northern US (Northern US COVID-19 Oscillator-NUCO). The drivers of these newly recognized oscillatory epidemic patterns remain to be elucidated.

Dimensions of Alexithymia and Identification of Emotions in Masked and Unmasked Faces

Alexithymia, a multifaceted personality construct, is known to be related to difficulties in the decoding of emotional facial expressions, especially in case of suboptimal stimuli. The present study investigated whether and which facets of alexithymia are related to impairments in the recognition of emotions in faces with face masks. Accuracy and speed of emotion recognition were examined in a block of faces with and a block of faces without face masks in a sample of 102 healthy individuals. The order of blocks varied between participants. Emotions were recognized better and faster in unmasked than in masked faces. Recognition performance was worst and slowest for participants starting the task with masked faces. In the whole sample, there were no correlations of alexithymia facets with accuracy and speed of emotion recognition for masked and unmasked faces. In participants starting the task with masked faces, the facet externally oriented thinking was positively correlated with reaction latencies of correct responses for masked faces. Our findings indicate that an externally oriented thinking style could be linked to a less efficient identification of emotions from faces wearing masks when task difficulty is high and support the utility of a facet approach in alexithymia research.

Identifying the interplay between protective measures and settings on the SARS-CoV-2 transmission using a Bayesian network

Contact tracing played a crucial role in minimizing the onward dissemination of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) in the recent pandemic. Previous studies had also shown the effectiveness of preventive measures such as mask-wearing, physical distancing, and exposure duration in reducing SARS-CoV-2 transmission. However, there is still a lack of understanding regarding the impact of various exposure settings on the spread of SARS-CoV-2 within the community, as well as the most effective preventive measures, considering the preventive measures adherence in different daily scenarios. We aimed to evaluate the effect of individual protective measures and exposure settings on the community transmission of SARS-CoV-2. Additionally, we aimed to investigate the interaction between different exposure settings and preventive measures in relation to such SARS-CoV-2 transmission. Routine SARS-CoV-2 contact tracing information was supplemented with additional data on individual measures and exposure settings collected from index patients and their close contacts. We used a case-control study design, where close contacts with a positive test for SARS-CoV-2 were classified as cases, and those with negative results classified as controls. We used the data collected from the case-control study to construct a Bayesian network (BN). BNs enable predictions for new scenarios when hypothetical information is introduced, making them particularly valuable in epidemiological studies. Our results showed that ventilation and time of exposure were the main factors for SARS-CoV-2 transmission. In long time exposure, ventilation was the most effective factor in reducing SARS-CoV-2, while masks and physical distance had on the other hand a minimal effect in this ventilation spaces. However, face masks and physical distance did reduce the risk in enclosed and unventilated spaces. Distance did not reduce the risk of infection when close contacts wore a mask. Home exposure presented a higher risk of SARS-CoV-2 transmission, and any preventive measures posed a similar risk across all exposure settings analyzed. Bayesian network analysis can assist decision-makers in refining public health campaigns, prioritizing resources for individuals at higher risk, and offering personalized guidance on specific protective measures tailored to different settings or environments.

Epidemic modelling suggests that in specific circumstances masks may become more effective when fewer contacts wear them

BACKGROUND

The effectiveness of non-pharmaceutical interventions to control the spread of SARS-CoV-2 depends on many contextual factors, including adherence. Conventional wisdom holds that the effectiveness of protective behaviours, such as wearing masks, increases with the number of people who adopt them. Here we show in a simulation study that this is not always true.

METHODS

We use a parsimonious network model based on the well-established empirical facts that adherence to such interventions wanes over time and that individuals tend to align their adoption strategies with their close social ties (homophily).

RESULTS

When these assumptions are combined, a broad dynamic regime emerges in which the individual-level reduction in infection risk for those adopting protective behaviour increases as adherence to protective behaviour decreases. For instance, at 10 % coverage, we find that adopters face nearly a 30 % lower infection risk than at 60 % coverage. Based on surgical mask effectiveness estimates, the relative risk reduction for masked individuals ranges from 5 % to 15 %, or a factor of three. This small coverage effect occurs when the outbreak is over before the pathogen is able to invade small but closely knit groups of individuals who protect themselves.

CONCLUSIONS

Our results confirm that lower coverage reduces protection at the population level while contradicting the common belief that masking becomes ineffective at the individual level as more people drop their masks.

Exploring the Impact of the COVID-19 Pandemic on Twitter in Japan: Qualitative Analysis of Disrupted Plans and Consequences

BACKGROUND

Despite being a pandemic, the impact of the spread of COVID-19 extends beyond public health, influencing areas such as the economy, education, work style, and social relationships. Research studies that document public opinions and estimate the long-term potential impact after the pandemic can be of value to the field.

OBJECTIVE

This study aims to uncover and track concerns in Japan throughout the COVID-19 pandemic by analyzing Japanese individuals' self-disclosure of disruptions to their life plans on social media. This approach offers alternative evidence for identifying concerns that may require further attention for individuals living in Japan.

METHODS

We extracted 300,778 tweets using the query phrase Corona-no-sei ("due to COVID-19," "because of COVID-19," or "considering COVID-19"), enabling us to identify the activities and life plans disrupted by the pandemic. The correlation between the number of tweets and COVID-19 cases was analyzed, along with an examination of frequently co-occurring words.

RESULTS

The top 20 nouns, verbs, and noun plus verb pairs co-occurring with Corona no-sei were extracted. The top 5 keywords were graduation ceremony, cancel, school, work, and event. The top 5 verbs were disappear, go, rest, can go, and end. Our findings indicate that education emerged as the top concern when the Japanese government announced the first state of emergency. We also observed a sudden surge in anxiety about material shortages such as toilet paper. As the pandemic persisted and more states of emergency were declared, we noticed a shift toward long-term concerns, including careers, social relationships, and education.

CONCLUSIONS

Our study incorporated machine learning techniques for disease monitoring through the use of tweet data, allowing the identification of underlying concerns (eg, disrupted education and work conditions) throughout the 3 stages of Japanese government emergency announcements. The comparison with COVID-19 case numbers provides valuable insights into the short- and long-term societal impacts, emphasizing the importance of considering citizens' perspectives in policy-making and supporting those affected by the pandemic, particularly in the context of Japanese government decision-making.

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.

The effect of Covid-19 emergence on religiosity: Evidence from Singapore

How do people deal with events they cannot control? Religious beliefs and practices are common responses to uncontrollable situations. We analyzed the responses of Singaporeans surveyed between November 2019 and March 2020-just before and just after Covid-19 hit the region-to understand how the beliefs and actions of both religious and non-religious people were affected by the emergence of the previously unknown virus. We find that after the emergence of Covid-19, religious respondents reported significantly higher levels of belief and service attendance frequency, while prayer frequency was not affected. We argue that the decrease in perceived controllability over people's lives explains these results. We discuss the implications of our findings for understanding the dynamics of religious beliefs and practices during times of uncertainty.

REAL-TIME MECHANISTIC BAYESIAN FORECASTS OF COVID-19 MORTALITY

The COVID-19 pandemic emerged in late December 2019. In the first six months of the global outbreak, the U.S. reported more cases and deaths than any other country in the world. Effective modeling of the course of the pandemic can help assist with public health resource planning, intervention efforts, and vaccine clinical trials. However, building applied forecasting models presents unique challenges during a pandemic. First, case data available to models in real time represent a nonstationary fraction of the true case incidence due to changes in available diagnostic tests and test-seeking behavior. Second, interventions varied across time and geography leading to large changes in transmissibility over the course of the pandemic. We propose a mechanistic Bayesian model that builds upon the classic compartmental susceptible-exposed-infected-recovered (SEIR) model to operationalize COVID-19 forecasting in real time. This framework includes nonparametric modeling of varying transmission rates, nonparametric modeling of case and death discrepancies due to testing and reporting issues, and a joint observation likelihood on new case counts and new deaths; it is implemented in a probabilistic programming language to automate the use of Bayesian reasoning for quantifying uncertainty in probabilistic forecasts. The model has been used to submit forecasts to the U.S. Centers for Disease Control through the COVID-19 Forecast Hub under the name MechBayes. We examine the performance relative to a baseline model as well as alternate models submitted to the forecast hub. Additionally, we include an ablation test of our extensions to the classic SEIR model. We demonstrate a significant gain in both point and probabilistic forecast scoring measures using MechBayes, when compared to a baseline model, and show that MechBayes ranks as one of the top two models out of nine which regularly submitted to the COVID-19 Forecast Hub for the duration of the pandemic, trailing only the COVID-19 Forecast Hub ensemble model of which which MechBayes is a part.

The interplay of social constraints and individual variation in risk tolerance in the emergence of superspreaders

Individual host behaviours can drastically impact the spread of infection through a population. Differences in the value individuals place on both socializing with others and avoiding infection have been shown to yield emergent homophily in social networks and thereby shape epidemic outcomes. We build on this understanding to explore how individuals who do not conform to their social surroundings contribute to the propagation of infection during outbreaks. We show how non-conforming individuals, even if they do not directly expose a disproportionate number of other individuals themselves, can become functional superspreaders through an emergent social structure that positions them as the functional links by which infection jumps between otherwise separate communities. Our results can help estimate the potential success of real-world interventions that may be compromised by a small number of non-conformists if their impact is not anticipated, and plan for how best to mitigate their effects on intervention success.

Role of masks in mitigating viral spread on networks

Masks have remained an important mitigation strategy in the fight against COVID-19 due to their ability to prevent the transmission of respiratory droplets between individuals. In this work, we provide a comprehensive quantitative analysis of the impact of mask-wearing. To this end, we propose a novel agent-based model of viral spread on networks where agents may either wear no mask or wear one of several types of masks with different properties (e.g., cloth or surgical). We derive analytical expressions for three key epidemiological quantities: The probability of emergence, the epidemic threshold, and the expected epidemic size. In particular, we show how the aforementioned quantities depend on the structure of the contact network, viral transmission dynamics, and the distribution of the different types of masks within the population. Through extensive simulations, we then investigate the impact of different allocations of masks within the population and tradeoffs between the outward efficiency and inward efficiency of the masks. Interestingly, we find that masks with high outward efficiency and low inward efficiency are most useful for controlling the spread in the early stages of an epidemic, while masks with high inward efficiency but low outward efficiency are most useful in reducing the size of an already large spread. Last, we study whether degree-based mask allocation is more effective in reducing the probability of epidemic as well as epidemic size compared to random allocation. The result echoes the previous findings that mitigation strategies should differ based on the stage of the spreading process, focusing on source control before the epidemic emerges and on self-protection after the emergence.

Overconfidence at the time of COVID-19:Does it lead to laxer attitudes?

BACKGROUND

Health education campaigns often aim to create awareness by increasing objective knowledge about pathogens, such as COVID-19. However, the present paper proposes that confidence in one's knowledge more than knowledge is a significant factor that leads to a laxer attitude toward COVID-19 and hence lower support for protective measures and reduced intention to comply with preemptive behaviors.

METHODS

We tested two hypotheses in three studies conducted between 2020 and 2022. In Study 1, we assessed participants' level of knowledge and confidence, as well as attitudes toward COVID-19. In Study 2, we tested the relation between fear of COVID-19 and protective behaviors. In Study 3, we used an experimental approach to show the causal effect of overconfidence on fear of COVID-19. In addition to manipulating overconfidence and measuring fear of COVID-19, we also measured prophylactic behaviors.

RESULTS

In Study 1, more overconfident participants had a laxer attitude toward COVID-19. While knowledge had an increasing effect on worry, confidence in said knowledge significantly decreased worry about COVID-19. In Study 2, participants who were more worried about COVID-19 were more likely to engage in protective behaviors (e.g., wearing masks). In Study 3, we show that when overconfidence was experimentally diminished, fear of COVID-19 increased. The results support our claim that the effect of overconfidence on attitudes toward COVID-19 is causal in nature. Moreover, the results show that people with higher fear of COVID-19 are more likely to wear masks, use hand sanitizers, avoid crowded places or social gatherings, and get vaccinated.

CONCLUSIONS

Managing adherence to public health measures is critical when it comes to highly infectious diseases. Our findings suggest that efficient information campaigns to increase adherence to public health measures should focus on calibrating people's confidence in their knowledge about COVID-19 to prevent the spread of the virus.

Spreading dynamics in networks under context-dependent behavior

In some systems, the behavior of the constituent units can create a "context" that modifies the direct interactions among them. This mechanism of indirect modification inspired us to develop a minimal model of context-dependent spreading. In our model, agents actively impede (favor) or not diffusion during an interaction, depending on the behavior they observe among all the peers in the group within which that interaction occurs. We divide the population into two behavioral types and provide a mean-field theory to parametrize mixing patterns of arbitrary type-assortativity within groups of any size. As an application, we examine an epidemic-spreading model with context-dependent adoption of prophylactic tools such as face masks. By analyzing the distributions of groups' size and type-composition, we uncover a rich phenomenology for the basic reproduction number and the endemic state. We analytically show how changing the group organization of contacts can either facilitate or hinder epidemic spreading, eventually moving the system from the subcritical to the supercritical phase and vice versa, depending mainly on sociological factors, such as whether the prophylactic behavior is hardly or easily induced. More generally, our work provides a theoretical foundation to model higher-order contexts and analyze their dynamical implications, envisioning a broad theory of context-dependent interactions that would allow for a new systematic investigation of a variety of complex systems.

Covering the Distance: A Study of Parent and Teen Attitudes on COVID-19 Mitigation Measures During the COVID-19 Pandemic

Background The Unity® Consortium surveyed teens and parents and guardians of teens across the country at three distinct time points or waves during the COVID-19 pandemic to assess participant attitudes and beliefs regarding COVID-19 mitigation guidelines, such as mask-wearing and physical distancing. Methodology A third-party market research company conducted 15-minute, online surveys from nationally representative panels. Surveys were conducted at three distinct time points or waves (August 2020, February 2021, and June 2021) with 300 teens aged 13-18 years in each wave and 593/531/500 parents and guardians of teens aged 13-18 years in each wave, respectively. Participants responded using a five-point Likert scale (strongly agree to strongly disagree) on their COVID-19 experiences, including the perceived importance of strictly following mask-wearing and/or social distancing guidelines and the perceived effectiveness of mask-wearing and social distancing in preventing the spread of COVID-19. Data were analyzed for differences across waves and demographic variables. Statistical analyses included frequencies, analysis of variance (ANOVA), and t-tests/z-tests. Results While significantly more parents and teens in Waves 2 and 3 knew someone who was hospitalized or died due to COVID-19 compared to Wave 1, significantly fewer in Wave 3 reported experiencing a lot or some stress and worry regarding the pandemic. By Wave 3, 58% of teens and 56% of parents had received at least one dose of a COVID-19 vaccine. Despite changes in experiences over time, a significant majority of parents and teens consistently agreed on the importance and effectiveness of social distancing and masking guidelines against the spread of COVID-19. In Wave 3, the demographic variables significantly associated with agreement on importance included race (Black (92%) > White (80%)), community type (urban (91%) > suburban (79%) and rural (73%)), and positive vaccination status of parents and teens (92%/89%) > not vaccinated (73%/73%), respectively). The demographic variables significantly associated with agreement on effectiveness included race (Black (91%) > White (81%)), community type (urban (89%) > suburban (83%) and rural (71%)), and positive vaccination status of parents and teens (94%/90% > not vaccinated (72%/70%), respectively). Conclusions This study into the perceived importance and perceived effectiveness of mitigation strategies during the COVID-19 pandemic revealed differences in attitudes among sociodemographic groups. Understanding these differences can help shape how adherence to public health guidelines in a pandemic is promoted.

The WE SENSE study protocol: A controlled, longitudinal clinical trial on the use of wearable sensors for early detection and tracking of viral respiratory tract infections

Background

Viral respiratory tract infections (VRTI) are extremely common. Considering the profound social and economic impact of COVID-19, it is imperative to identify novel mechanisms for early detection and prevention of VRTIs, to prevent future pandemics. Wearable biosensor technology may facilitate this. Early asymptomatic detection of VRTIs could reduce stress on the healthcare system by reducing transmission and decreasing the overall number of cases. The aim of the current study is to define a sensitive set of physiological and immunological signature patterns of VRTI through machine learning (ML) to analyze physiological data collected continuously using wearable vital signs sensors.

Methods

A controlled, prospective longitudinal study with an induced low grade viral challenge, coupled with 12 days of continuous wearable biosensors monitoring surrounding viral induction. We aim to recruit and simulate a low grade VRTI in 60 healthy adults aged 18–59 years via administration of live attenuated influenza vaccine (LAIV). Continuous monitoring with wearable biosensors will include 7 days pre (baseline) and 5 days post LAIV administration, during which vital signs and activity-monitoring biosensors (embedded in a shirt, wristwatch and ring) will continuously monitor physiological and activity parameters. Novel infection detection techniques will be developed based on inflammatory biomarker mapping, PCR testing, and app-based VRTI symptom tracking. Subtle patterns of change will be assessed via ML algorithms developed to analyze large datasets and generate a predictive algorithm.

Conclusion

This study presents an infrastructure to test wearables for the detection of asymptomatic VRTI using multimodal biosensors, based on immune host response signature.

CliniclTrials.govregistration:NCT05290792

Implementation barriers and facilitators to a COVID-19 intervention in Bangladesh: The benefits of engaging the community for the delivery of the programme

BACKGROUND

BRAC (Bangladesh Rural Advancement Committee), the largest NGO globally, implemented a community-based comprehensive social behavior communication intervention to increase community resilience through prevention, protection, and care for COVID-19. We conducted implementation research to assess fidelity and explore the barriers and facilitators of this intervention implementation.

METHODS

We adopted a concurrent mixed-method triangulation design. We interviewed 666 members of 60 Community Corona Protection Committees (CCPCs) and 80 members of 60 Community Support Teams (CSTs) through multi-stage cluster sampling using a structured questionnaire. The qualitative components relied on 54 key informant interviews with BRAC implementers and government providers.

RESULTS

The knowledge about wearing mask, keeping social distance, washing hands and COVID-19 symptoms were high (on average more than 70%) among CCPC and CST members. While 422 (63.4%) CCPC members reported they 'always' wear a mask while going out, 69 (86.3%) CST members reported the same practice. Only 247 (37.1%) CCPC members distributed masks, and 229 (34.4%) donated soap to the underprivileged population during the last two weeks preceding the survey. The key facilitators included influential community members in the CCPC, greater acceptability of the front-line health workers, free-of-cost materials, and telemedicine services. The important barriers identified were insufficient training, irregular participation of the CCPC members, favouritism of CCPC members in distributing essential COVID-19 preventive materials, disruption in supply and shortage of the COVID-19 preventative materials, improper use of handwashing station, the non-compliant attitude of the community people, challenges to ensure home quarantine, challenges regarding telemedicine with network interruptions, lack of coordination among stakeholders, the short duration of the project.

CONCLUSIONS

Engaging the community in combination with health services through a Government-NGO partnership is a sustainable strategy for implementing the COVID-19 prevention program. Engaging the community should be promoted as an integral component of any public health intervention for sustainability. Engagement structures should incorporate a systems perspective to facilitate the relationships, ensure the quality of the delivery program, and be mindful of the heterogeneity of different community members concerning capacity building. Finally, reaching out to the underprivileged through community engagement is also an effective mechanism to progress through universal health coverage.

Application of Electrospun Water-Soluble Synthetic Polymers for Multifunctional Air Filters and Face Masks

The worsening of air quality is an urgent human health issue of modern society. The outbreak of COVID-19 has made the improvement of air quality even more imperative, both for the general achievement of major health gains and to reduce the critical factors in the transmission of airborne diseases. Thus, the development of solutions for the filtration of airborne pollutants is pivotal. Electrospinning has gained wide attention as an effective fabrication technique for preparing ultrafine fibers which are specifically tailored for air filtration. Nevertheless, the utilization of harmful organic solvents is the major barrier for the large-scale applicability of electrospinning. The use of water-soluble synthetic polymers has attracted increasing attention as a 'green' solution in electrospinning. We reported an overview of the last five years of the scientific literature on the use of water-soluble synthetic polymers for the fabrication of multifunctional air filters layers. Most of recent studies have focused on polyvinyl alcohol (PVA). Various modifications of electrospun polymers have been also described. The use of water-soluble synthetic polymers can contribute to the scalability of electrospinning and pave the way to innovative applications. Further studies will be required to fully harness the potentiality of these 'greener' electrospinning processes.

Nanomaterials to combat SARS-CoV-2: Strategies to prevent, diagnose and treat COVID-19

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and the associated coronavirus disease 2019 (COVID-19), which severely affect the respiratory system and several organs and tissues, and may lead to death, have shown how science can respond when challenged by a global emergency, offering as a response a myriad of rapid technological developments. Development of vaccines at lightning speed is one of them. SARS-CoV-2 outbreaks have stressed healthcare systems, questioning patients care by using standard non-adapted therapies and diagnostic tools. In this scenario, nanotechnology has offered new tools, techniques and opportunities for prevention, for rapid, accurate and sensitive diagnosis and treatment of COVID-19. In this review, we focus on the nanotechnological applications and nano-based materials (i.e., personal protective equipment) to combat SARS-CoV-2 transmission, infection, organ damage and for the development of new tools for virosurveillance, diagnose and immune protection by mRNA and other nano-based vaccines. All the nano-based developed tools have allowed a historical, unprecedented, real time epidemiological surveillance and diagnosis of SARS-CoV-2 infection, at community and international levels. The nano-based technology has help to predict and detect how this Sarbecovirus is mutating and the severity of the associated COVID-19 disease, thereby assisting the administration and public health services to make decisions and measures for preparedness against the emerging variants of SARS-CoV-2 and severe or lethal COVID-19.

Factors associated with COVID-19 masking behavior: an application of the Health Belief Model

Wearing a face mask is effective in minimizing the spread of coronavirus disease 2019 (COVID-19) among unvaccinated individuals and preventing severe illness among the vaccinated. Country, state and local guidelines promote, and at times mandate, mask-wearing despite it being publicly perceived as an individual's choice. Guided by the Health Belief Model (HBM), structural equation modeling was used to analyze longitudinal data in a sample of US adults aged 18-49 years to identify constructs that contribute to face mask-wearing. Results indicated that perceived COVID-19 severity, perceived masking benefits and self-efficacy were positively associated with masking behavior, and masking barriers were negatively associated with masking behavior. Perceived susceptibility to COVID-19 and cues to action were nonsignificant correlates of masking behavior. These results' theoretical and practical implications contribute to the literature on the HBM and the COVID-19 pandemic. Future directions and limitations are discussed.

Nanotechnology Transition Roadmap toward Multifunctional Stimuli-Responsive Face Masks

In recent times, the use of personal protective equipment, such as face masks or respirators, is becoming more and more critically important because of common pollution; furthermore, face masks have become a necessary element in the global fight against the COVID-19 pandemic. For this reason, the main mission of scientists has become the development of face masks with exceptional properties that will enhance their performance. The versatility of electrospun polymer nanofibers has determined their suitability as a material for constructing "smart" filter media. This paper provides an overview of the research carried out on nanofibrous filters obtained by electrospinning. The progressive development of the next generation of face masks whose unique properties can be activated in response to a specific external stimulus is highlighted. Thanks to additional components incorporated into the fiber structure, filters can, for example, acquire antibacterial or antiviral properties, self-sterilize the structure, and store the energy generated by users. Despite the discovery of several fascinating possibilities, some of them remain unexplored. Stimuli-responsive filters have the potential to become products of large-scale availability and great importance to society as a whole.

Materials analysis and image-based modelling of transmissibility and strain behaviour in approved face mask microstructures

Comparisons are made between six different approved face masks concerning their particle transmissibility allied to mechanical properties. The latter involves material testing and stretch or strain behaviour under load. SEM and X-ray elemental analyses showed contrasting structures between random and ordered fibre orientations. These constitute the mask designs where transmissibility is to be minimised. Airflow velocity measurement enabled filtration to be measured between the different mask designs, from two to six layers of different fabrics in combination. SEM provided the fibre diameter and pore size of each mask layer, up to a maximum of six. Stretching each complete mask showed its elasticity and recovery behaviour on an energy basis. The energy conversion involved in mask straining involves areas enclosed within steady and cyclic load-extension plots. Thus, the work done in extending a mask and the energy recovered from its release identified a hysteresis associated with an irrecoverable permanent stretch to the mask fabric. Failure of individual layers, which occurred successively in extended stretch tests, appeared as a drop in a load-extension response. That change is associated with permanent damage to each mask and friction contact within the rearrangement of loose fibre weaves. Masks with the greatest number of layers reduced particle transmissibility. However, woven or ordered mask fabrics in two layers with different orientations provided comparable performance. Simulation of each mechanical response, velocity streamlining and fibre distribution within the mask layers are also presented.

A critical review on the role of leakages in the facemask protection against SARS-CoV-2 infection with consideration of vaccination and virus variants

The protection provided by facemasks has been extensively investigated since the beginning of the SARS-CoV-2 outbreak, focusing mostly on the filtration efficiency of filter media for filtering face pieces (FFP), surgical masks, and cloth masks. However, faceseal leakage is a major contributor to the number of potentially infectious airborne droplets entering the respiratory system of a susceptible individual. The identification of leaking spots and the quantification of leaking flows are crucial to estimate the protection provided by facemasks. This study presents a critical review on the measurement and calculation of facemask leakages and a quantitative analysis of their role in the risk of SARS-CoV-2 infection. It shows that the pairing between the mask dimensions and the wearer's face is essential to improve protection efficiency, especially for FFP2 masks, and summarizes the most common leaking spots at the interface between the mask and the wearer's face. Leakage is a crucial factor in the calculation of the protection provided by facemasks and outweighs the filtration performances. The fit factors measured among mask users were summarized for different types of face protection. The reviewed data were integrated into a computational model to compare the mitigation impact of facemasks with vaccination with consideration of new variants of SARS-CoV-2. Combining a high adoption rate of facemasks and a high vaccination rate is crucial to efficiently control the spread of highly infectious variants.

SAfE transport: wearing face masks significantly reduces the spread of COVID-19 on trains

COVID-19 has had a substantial impact globally. It spreads readily, particularly in enclosed and crowded spaces, such as public transport carriages, yet there are limited studies on how this risk can be reduced. We developed a tool for exploring the potential impacts of mitigation strategies on public transport networks, called the Systems Analytics for Epidemiology in Transport (SAfE Transport). SAfE Transport combines an agent-based transit assignment model, a community-wide transmission model, and a transit disease spread model to support strategic and operational decision-making. For this simulated COVID-19 case study, the transit disease spread model incorporates both direct (person-to-person) and fomite (person-to-surface-to-person) transmission modes. We determine the probable impact of wearing face masks on trains over a seven day simulation horizon, showing substantial and statistically significant reductions in new cases when passenger mask wearing proportions are greater than 80%. The higher the level of mask coverage, the greater the reduction in the number of new infections. Also, the higher levels of mask coverage result in an earlier reduction in disease spread risk. These results can be used by decision makers to guide policy on face mask use for public transport networks.

Evaluation of Alternative Transport Media for RT-qPCR-Based SARS-CoV-2 Testing

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), is still rapidly spreading as of March 2022. An accurate and rapid molecular diagnosis is essential to determine the exact number of confirmed cases. Currently, the viral transport medium (VTM) required for testing is in short supply due to a sharp increase in the laboratory tests performed, and alternative VTMs are needed to alleviate the shortage. Guanidine thiocyanate-based media reportedly inactivate SARS-CoV-2 and are compatible with quantitative reverse transcription polymerase chain reaction (RT-qPCR) assays, but the compatibility and the viral detection capacity have not been fully validated. To evaluate the guanidine thiocyanate-based Gene Transport Medium (GeneTM) as an alternative VTM, we prepared 39 SARS-CoV-2-positive and 7 SARS-CoV-2-negative samples in GeneTM, eNAT™, and phosphate-buffered saline (PBS). The cycle threshold (Ct) values of three SARS-CoV-2 targets (the S, RdRP, and N genes) were analyzed using RT-qPCR testing. The comparison of Ct values from the positive samples showed a high correlation (R2= 0.95–0.96) between GeneTM and eNAT™, indicating a comparable viral detection capacity. The delta Ct values of the SARS-CoV-2 genes in each transport medium were maintained for 14 days at cold (4°C) or room (25°C) temperatures, suggesting viral samples were stably preserved in the transport media for 14 days. Together, GeneTM is a potential alternative VTM with comparable RT-qPCR performance and stability to those of standard media.

The suitability and usability of a tool to assess contact status from COVID-19 exposures in the workplace

OBJECTIVE

To assess the usability of a self-assessment COVID-19 exposure tool for workplaces.

METHODS

A COVID-19 exposure tool for workplaces was developed using five risk criteria. Public Health Unit (PHU) assessors who administered the tool documented when they administered the tool, the time taken for finalisation of the assessment and ease of administration. The System Usability Scale was used for workplace managers' perceptions on tool use. Data were assessed using both quantitative and qualitative analysis.

RESULTS

Eighty-four workplaces used the tool to assess COVID-19 exposure risk. Of those, the outcome provided by the tool did not require modification by the PHU assessor in 70% of workplaces. Eighty per cent of the assessments were completed by the next day. PHU assessors rated the overall ease of administration of the tool as 'easy' or 'very easy' for 85% of workplaces and indicated they would employ the tool across a number of settings including complex workplaces. The mean System Usability Scale was 82. Workplace managers were predominately positive regarding its suitability.

CONCLUSION

The tool provides an easy-to-use assessment of SARS-CoV-2 exposure in the workplace.

IMPLICATIONS FOR PUBLIC HEALTH

The tool's adoption will empower workplace managers and improve the capacity of public health units to prevent further transmission of SARS-CoV-2 in workplaces.

Surgical face masks do not impair the decoding of facial expressions of negative affect more severely in older than in younger adults

Surgical face masks reduce the spread of airborne pathogens but also disturb the flow of information between individuals. The risk of getting seriously ill after infection with SARS-COV-2 during the present COVID-19 pandemic amplifies with age, suggesting that face masks should be worn especially during face-to-face contact with and between older people. However, the ability to accurately perceive and understand communication signals decreases with age, and it is currently unknown whether face masks impair facial communication more severely in older people. We compared the impact of surgical face masks on dynamic facial emotion recognition in younger (18–30 years) and older (65–85 years) adults (N = 96) in an online study. Participants watched short video clips of young women who facially expressed anger, fear, contempt or sadness. Faces of half of the women were covered by a digitally added surgical face mask. As expected, emotion recognition accuracy declined with age, and face masks reduced emotion recognition accuracy in both younger and older participants. Unexpectedly, the effect of face masks did not differ between age groups. Further analyses showed that masks also reduced the participants’ overall confidence in their emotion judgements, but not their performance awareness (the difference between their confidence ratings for correct and incorrect responses). Again, there were no mask-by-age interactions. Finally, data obtained with a newly developed questionnaire (attitudes towards face masks, atom) suggest that younger and older people do not differ in how much they feel impaired in their understanding of other people’s emotions by face masks or how useful they find face masks in confining the COVID-19 pandemic. In sum, these findings do not provide evidence that the impact of face masks on the decoding of facial signals is disproportionally larger in older people.

Evaluation of the effects of meteorological factors on COVID-19 prevalence by the distributed lag nonlinear model

Background

Although numerous studies have explored the impact of meteorological factors on the epidemic of COVID-19, their relationship remains controversial and needs to be clarified.

Methods

We assessed the risk effect of various meteorological factors on COVID-19 infection using the distributed lag nonlinear model, based on related data from July 1, 2020, to June 30, 2021, in eight countries, including Portugal, Greece, Egypt, South Africa, Paraguay, Uruguay, South Korea, and Japan, which are in Europe, Africa, South America, and Asia, respectively. We also explored associations between COVID-19 prevalence and individual meteorological factors by the Spearman’s rank correlation test.

Results

There were significant non-linear relationships between both temperature and relative humidity and COVID-19 prevalence. In the countries located in the Northern Hemisphere with similar latitudes, the risk of COVID-19 infection was the highest at temperature below 5 ℃. In the countries located in the Southern Hemisphere with similar latitudes, their highest infection risk occurred at around 15 ℃. Nevertheless, in most countries, high temperature showed no significant association with reduced risk of COVID-19 infection. The effect pattern of relative humidity on COVID-19 depended on the range of its variation in countries. Overall, low relative humidity was correlated with increased risk of COVID-19 infection, while the high risk of infection at extremely high relative humidity could occur in some countries. In addition, relative humidity had a longer lag effect on COVID-19 than temperature.

Conclusions

The effects of meteorological factors on COVID-19 prevalence are nonlinear and hysteretic. Although low temperature and relative humidity may lower the risk of COVID-19, high temperature or relative humidity could also be associated with a high prevalence of COVID-19 in some regions.

Diversity in valuing social contact and risk tolerance leading to the emergence of homophily in populations facing infectious threats

How self-organization leads to the emergence of structure in social populations remains a fascinating and open question in the study of complex systems. One frequently observed structure that emerges again and again across systems is that of self-similar community, i.e., homophily. We use a game theoretic perspective to explore a case in which individuals choose affiliation partnerships based on only two factors: the value they place on having social contacts, and their risk tolerance for exposure to threat derived from social contact (e.g., infectious disease, threatening ideas, etc.). We show how diversity along just these two influences is sufficient to cause the emergence of self-organizing homophily in the population. We further consider a case in which extrinsic social factors influence the desire to maintain particular social ties, and show the robustness of emergent homophilic patterns to these additional influences. These results demonstrate how observable population-level homophily may arise out of individual behaviors that balance the value of social contacts against the potential risks associated with those contacts. We present and discuss these results in the context of outbreaks of infectious disease in human populations. Complementing the standard narrative about how social division alters epidemiological risk, we here show how epidemiological risk may deepen social divisions in human populations.

Misinformation can prevent the suppression of epidemics

The effectiveness of non-pharmaceutical interventions, such as mask-wearing and social distancing, as control measures for pandemic disease relies upon a conscientious and well-informed public who are aware of and prepared to follow advice. Unfortunately, public health messages can be undermined by competing misinformation and conspiracy theories, spread virally through communities that are already distrustful of expert opinion. In this article, we propose and analyse a simple model of the interaction between disease spread and awareness dynamics in a heterogeneous population composed of both trusting individuals who seek better quality information and will take precautionary measures, and distrusting individuals who reject better quality information and have overall riskier behaviour. We show that, as the density of the distrusting population increases, the model passes through a phase transition to a state in which major outbreaks cannot be suppressed. Our work highlights the urgent need for effective interventions to increase trust and inform the public.

Interactions of Co, Cu, and non-metal phthalocyanines with external structures of SARS-CoV-2 using docking and molecular dynamics

The new coronavirus, SARS-CoV-2, caused the COVID-19 pandemic, characterized by its high rate of contamination, propagation capacity, and lethality rate. In this work, we approach the use of phthalocyanines as an inhibitor of SARS-CoV-2, as they present several interactive properties of the phthalocyanines (Pc) of Cobalt (CoPc), Copper (CuPc) and without a metal group (NoPc) can interact with SARS-CoV-2, showing potential be used as filtering by adsorption on paints on walls, masks, clothes, and air conditioning filters. Molecular modeling techniques through Molecular Docking and Molecular Dynamics were used, where the target was the external structures of the virus, but specifically the envelope protein, main protease, and Spike glycoprotein proteases. Using the g_MM-GBSA module and with it, the molecular docking studies show that the ligands have interaction characteristics capable of adsorbing the structures. Molecular dynamics provided information on the root-mean-square deviation of the atomic positions provided values between 1 and 2.5. The generalized Born implicit solvation model, Gibbs free energy, and solvent accessible surface area approach were used. Among the results obtained through molecular dynamics, it was noticed that interactions occur since Pc could bind to residues of the active site of macromolecules, demonstrating good interactions; in particular with CoPc. Molecular couplings and free energy showed that S-gly active site residues interacted strongly with phthalocyanines with values ​​of - 182.443 kJ/mol (CoPc), 158.954 kJ/mol (CuPc), and - 129.963 kJ/mol (NoPc). The interactions of Pc's with SARS-CoV-2 may predict some promising candidates for antagonists to the virus, which if confirmed through experimental approaches, may contribute to resolving the global crisis of the COVID-19 pandemic.

Anti-COVID-19 Nanomaterials: Directions to Improve Prevention, Diagnosis, and Treatment

Following the announcement of the outbreak of COVID-19 by the World Health Organization, unprecedented efforts were made by researchers around the world to combat the disease. So far, various methods have been developed to combat this "virus" nano enemy, in close collaboration with the clinical and scientific communities. Nanotechnology based on modifiable engineering materials and useful physicochemical properties has demonstrated several methods in the fight against SARS-CoV-2. Here, based on what has been clarified so far from the life cycle of SARS-CoV-2, through an interdisciplinary perspective based on computational science, engineering, pharmacology, medicine, biology, and virology, the role of nano-tools in the trio of prevention, diagnosis, and treatment is highlighted. The special properties of different nanomaterials have led to their widespread use in the development of personal protective equipment, anti-viral nano-coats, and disinfectants in the fight against SARS-CoV-2 out-body. The development of nano-based vaccines acts as a strong shield in-body. In addition, fast detection with high efficiency of SARS-CoV-2 by nanomaterial-based point-of-care devices is another nanotechnology capability. Finally, nanotechnology can play an effective role as an agents carrier, such as agents for blocking angiotensin-converting enzyme 2 (ACE2) receptors, gene editing agents, and therapeutic agents. As a general conclusion, it can be said that nanoparticles can be widely used in disinfection applications outside in vivo. However, in in vivo applications, although it has provided promising results, it still needs to be evaluated for possible unintended immunotoxicity. Reviews like these can be important documents for future unwanted pandemics.

An Update on the Status of Vaccine Development for SARS-CoV-2 Including Variants. Practical Considerations for COVID-19 Special Populations

The progress in the development of various vaccine platforms against SARS-CoV-2 have been rather remarkable owing to advancement in molecular and biologic sciences. Most of the current vaccines and those in development focus on targeting the viral spike proteins by generating antibodies of varying spectrum. These vaccines represent a variety of platforms including whole virus vaccines, viral vector vaccines, nucleic acid vaccines representing RNA, DNA, and their hybrid forms.The therapeutic efficacy of these vaccines varies owing to their pharmacodynamic individualities. COVID-19 variants are capable of inducing different pathologic responses and some of which may be resistant to antibodies generated by current vaccines. The current clinical use of these vaccines has been through emergency use authorization until recently. Moreover, the efficacy and safety of these vaccines have been tested in substantial numbers of individuals but studies in special populations that better reflect the global population are pending results. These specialized populations include young children, immunocompromised patients, pregnant individuals, and other specialized groups. Combination approaches, molecularly modified vaccination approaches, and vaccines conferring longer periods of immunity are being currently being investigated, as well as pharmacovigilance studies.The continual transformation of SARS-CoV-2 and its variants are of concern along with the breakthrough infections. These considerations pose new challenges for the development of vaccination platforms. For this purpose, booster doses, combination vaccine approaches, and other modalities are being discussed. This review provides an updated account of currently available vaccines and those in advanced development with reference to their composition and mechanisms of action.A discussion on the use of vaccines in special populations including immunocompromised patients, pregnant women and other specialized populations are also included.

Face masks reduce interpersonal distance in virtual reality

During the COVID-19 pandemic several behavioral measures have been implemented to reduce viral transmission. While these measures reduce the risk of infections, they may also increase risk behavior. Here, we experimentally investigate the influence of face masks on physical distancing. Eighty-four participants with or without face masks passed virtual agents in a supermarket environment to reach a target while interpersonal distance was recorded. Agents differed in wearing face masks and age (young, elderly). In addition, situational constraints varied in whether keeping a distance of 1.5 m required an effortful detour or not. Wearing face masks (both self and other) reduced physical distancing. This reduction was most prominent when keeping the recommended distance was effortful, suggesting an influence of situational constraints. Similarly, increased distances to elderly were only observed when keeping a recommended distance was effortless. These findings highlight contextual constraints in compensation behavior and have important implications for safety policies.

Social distancing practice and associated factors in response to COVID-19 pandemic at West Guji Zone, Southern Ethiopia, 2021: A community based cross-sectional study

BACKGROUND

Curtailing physical contact between individuals reduces transmission and spread of the disease. Social distancing is an accepted and effective strategy to delay the disease spread and reduce the magnitude of outbreaks of pandemic COVID-19. However, no study quantified social distancing practice and associated factors in the current study area. Therefore, the study aimed to assess social distancing practice and associated factors in response to COVID-19 pandemic in West Guji Zone, Southern Ethiopia, 2020.

METHODS AND MATERIALS

A Community based cross-sectional study design was conducted among randomly selected 410 household members of Bule Hora Town, West Guji Zone. Data were collected by pre-tested interviewer administered structured questionnaire adapted from previous peer reviewed articles. The data were coded and entered in to Epi data version 3.5 and analyzed by SPSS version 23. The bivariate and multivariate logistic regressions analysis was done to identify factors associated with social distancing practice. Adjusted odds ratio with 95% confidence interval and p value <0.05 were used to declare statistical significance.

RESULT

Out of 447 planned samples, 410 participants were successfully interviewed and included into final analysis; making the response rate of 91.7%. The median (±IQR) age of study participants was 28(±9) years. In this study, 38.3% [95% CI: 33.5%, 43.1%)] of the study participants have good social distancing practices for the prevention of COVID-19. Age group 26-30 years [AOR = 2.56(95% CI: 1.18-5.54)] and 31-35 years [AOR = 3.57(95%CI: 1.56-8.18)], employed [AOR = 6.10(95%CI: 3.46-10.74)],poor knowledge [AOR = 0.59 (95% CI:0.36-0.95)], negative attitude [AOR = 0.55 (95% CI:0.31-0.95)] and low perceived susceptibility [AOR = 0.33(95%CI: 0.20-0.54)] were significantly associated with good social distancing practice.

CONCLUSION

Social distancing practice is relatively poor in the study area. The knowledge and attitude level of participants were identified to be the major factors for the observed poor social distancing practice. Sustained efforts to improve awareness and attitudes towards COVID-19 prevention might improve adherence to social distancing practices.

Attitudes and Intentions toward COVID-19 Vaccination among Health Professions Students and Faculty in Qatar

A population's desire to take the COVID-19 vaccine is an important predictor of a country's future pandemic management. This cross-sectional study examines the impact of psychological and sociodemographic factors on attitudes toward and intentions to take the COVID-19 vaccine among students and faculty at four colleges of health professions and sciences at Qatar University. The data were collected through an online survey using Google Forms. The survey was distributed through various online platforms. Data analysis was conducted using Stata 16. Of the 364 participants, 9.89% expressed a high mistrust of vaccine safety, and 21.7% were uncertain about their levels of trust; 28% expressed strong worries about unforeseen side effects, whereas 54.95% expressed moderate worries. Furthermore, 7.69% expressed strong concerns and 39.84% showed moderate concerns about commercial profiteering. Approximately 13% of the participants expressed a strong preference towards natural immunity, whilst 45.33% appeared to believe that natural immunity might be better than a vaccine. Importantly, 68.13% of the participants intended to receive the COVID-19 vaccine once it became available, compared to 17.03% who were uncertain and 14.83% who were unwilling to be vaccinated. Our findings differ from the data on vaccine hesitancy among the general population of Qatar. We argue that this gap is due to scientific knowledge and domain of education. Furthermore, although knowledge and awareness may affect vaccine attitudes, mental health and sociodemographic factors play a role in shaping attitudes towards vaccines.