Facemasks simple but powerful weapons to protect against COVID-19 spread: Can they have sides effects?

Rain, rain, go away, come again another day: do climate variations enhance the spread of COVID-19?

The spread of infectious diseases was further promoted due to busy cities, increased travel, and climate change, which led to outbreaks, epidemics, and even pandemics. The world experienced the severity of the 125 nm virus called the coronavirus disease 2019 (COVID-19), a pandemic declared by the World Health Organization (WHO) in 2019. Many investigations revealed a strong correlation between humidity and temperature relative to the kinetics of the virus's spread into the hosts. This study aimed to solve the riddle of the correlation between environmental factors and COVID-19 by applying RepOrting standards for Systematic Evidence Syntheses (ROSES) with the designed research question. Five temperature and humidity-related themes were deduced via the review processes, namely 1) The link between solar activity and pandemic outbreaks, 2) Regional area, 3) Climate and weather, 4) Relationship between temperature and humidity, and 5) the Governmental disinfection actions and guidelines. A significant relationship between solar activities and pandemic outbreaks was reported throughout the review of past studies. The grand solar minima (1450-1830) and solar minima (1975-2020) coincided with the global pandemic. Meanwhile, the cooler, lower humidity, and low wind movement environment reported higher severity of cases. Moreover, COVID-19 confirmed cases and death cases were higher in countries located within the Northern Hemisphere. The Blackbox of COVID-19 was revealed through the work conducted in this paper that the virus thrives in cooler and low-humidity environments, with emphasis on potential treatments and government measures relative to temperature and humidity. HIGHLIGHTS: • The coronavirus disease 2019 (COIVD-19) is spreading faster in low temperatures and humid area. • Weather and climate serve as environmental drivers in propagating COVID-19. • Solar radiation influences the spreading of COVID-19. • The correlation between weather and population as the factor in spreading of COVID-19.

Analysis and dynamical transmission of Covid-19 model by using Caputo-Fabrizio derivative

The SARS-CoV-2 pandemic is an urgent problem with unpredictable properties and is widespread worldwide through human interactions. This work aims to use Caputo-Fabrizio fractional operators to explore the complex action of the Covid-19 Omicron variant. A fixed-point theorem and an iterative approach are used to prove the existence and singularity of the model’s system of solutions. Laplace transform is used to generalize the fractional order model for stability and unique solution of the iterative scheme. A numerical scheme is also constructed by using an exponential law kernel for the computational and simulation of the Covid-19 Model. The graphs demonstrate that the fractional model of Covid-19 is accurate. In the sense of Caputo-Fabrizio, one can obtain trustworthy information about the model in either an integer or non-integer scenario. This sense also provides useful information about the model’s complexity.

Evaluation of the bacterial contamination of face masks worn by personnel in a center of COVID 19 hospitalized patients: A cross-sectional study

Background

During the Coronavirus Pandemic, the use of masks has increased significantly. The lack of control on hygiene protocols and the need to use PPE properly increases the spread of bacterial infection. The purpose of this study was to investigate the degree of contamination and frequency of bacterial species isolated from surgical and N95 masks used by hospital personnel.

Methods

A total number of 175 masks were collected from staff working in Sina hospital (Hamadan province, Iran) during the first six months of 2022. The bacterial contamination of masks were evaluated and identified using biochemical kits. Antimicrobial susceptibility testing of the isolates were done using Kirby-Bauer methods and MIC were assessed for each isolate against different disinfectants (Sodium hypochlorite 5%, Hydrogen Peroxide 3%, Ethanol 70% and Deconex).

Results

Of 175 masks, 471 bacterial isolates were detected including 9 species. The most prevalent strain were Coagulase negative Staphylococcus (28%) followed by Acinetobacter (20.8%) and Pseudomonas (13.8%), while, Klebsiealla and Enterococcus were the least frequent species with the rate of 3.8% and 1.2%, respectively. The results of MIC methods indicated that all 471 strains were resistant to ehtanol70% and sensitive to hydrogen peroxide 3%. Furthermore, the mean average of Deconex inhibitory effect is lower than Sodium hypochlorite 5%.

Conclusions

According to the results of this study, there was a high prevalence of CoNS, Acinetobacter and Pseudomonas in hospital with a high resistance pattern against antibiotics especially Ampicillin and disinfectants.

Volatile sulfide compounds and oral microorganisms on the inner surface of masks in individuals with halitosis during COVID-19 pandemic

Mask-wearing is still recommended owing to the continuing impact of the COVID-19 pandemic. Within the closed chamber created by the mask, people are increasingly self-aware of their oral malodor. In this prospective and cross-sectional study, we aimed to measure volatile sulfide compound (VSC) levels in patients with halitosis and investigate the oral microbiome profile on the inner surface of their KF94 masks. We also investigated which oral microbiota increases VSC levels and whether the oral microbiomes of oral saliva and mask are correlated. A total of 50 subjects (41 women, average age 38.12 ± 12.58 years old) were included in the study, 25 healthy subjects and 25 patients with halitosis who wore masks for more than 3 h. The dominant bacterial species, bacterial profile, and Shannon diversity index of whole unstimulated saliva and the inner surface of the mask were investigated. The bacterial 16S ribosomal RNA genes of the major oral bacterial species were analyzed using real-time PCR. Gas chromatography was used to measure hydrogen sulfide (H₂S) and methyl mercaptan (CH₃SH), which are representative VSCs. The total bacterial DNA copy number was significantly higher in the saliva sample than in the mask sample (p < 0.001), and the average value was 276 times greater. Shannon diversity index was also significantly higher in saliva than in the inner surface of the mask (2.62 ± 0.81 vs. 1.15 ± 1.52, p < 0.001). The most common Gram-negative and Gram-positive species in the masks were Porphyromonas gingivalis (Pg) and Lactobacillus casei (Lc), respectively. The bacterial species with significant positive correlations between saliva and mask samples were Prevotella intermedia (Pi) (r = 0.324, p = 0.022), Eikenella corrodens (r = 0.309, p = 0.029), Lc (r = 0.293, p = 0.039), and Parvimonas micra (Pm) (r = 0.366, p = 0.009). The mean value of CH₃SH was significantly higher in the halitosis group than in the non-halitosis group (17.84 ± 29.00 vs. 3.84 ± 10.57 ppb, p = 0.031). In the halitosis group, the DNA copy numbers and VSC levels showed highly positive correlation coefficients in the order Pg, Treponema denticola (Td), Tannerella forsythia (Tf), Pi, and Prevotella nigrescens (Pn) (all p < 0.05). Regarding bacterial profiles of the mask, Td was strongly correlated with CH₃SH (r = 0.414, p = 0.040) and total VSCs (r = 0.374, p = 0.033) only in halitosis group. Mask-wearing time was strongly correlated with total VSCs, H₂S, and CH₃SH (all r > 0.8, p < 0.001). Oral bacteria, whose association with halitosis has been identified, increased VSC levels in mask-wearing subjects during the COVID-19 pandemic, particularly the number of Gram-negative anaerobes such as Pg and Td. Mask-wearing time was a major factor in increasing VSC levels. The study results suggest that people with halitosis could control these Gram-negative bacteria by improving oral hygiene and regularly changing masks.

Exercise-induced expression of SARS-CoV-2 entry receptors: impact of mask modality, sex, and exercise intensity

BACKGROUND

Wearing a facemask affects physiological responses to exercise. We explored how exercising with a facemask affects the expression of SARS-CoV-2 entry receptor (angiotensin-converting enzyme 2 [ACE2]) and some associated genes (angiotensin type-1 receptors [AT<inf>1</inf>R]; Mas receptor [MasR]; hypoxia-inducible factor 1α [HIF-1α]; endothelial nitric oxide synthase [eNOS]) among healthy males and females.

METHODS

One hundred forty-four apparently healthy individuals (72 females; age: 30±6) were allocated to three mask groups of 48 (N95, Surgical, No Mask) with two exercise subgroups for each mask for both sexes. Participants in each experimental group performed either a submaximal (walking with no grade) or maximal (a modified Bruce Protocol) treadmill exercise test. Blood samples were collected before and after each exercise test and used to analyze the mRNA expression of the genes studied.

RESULTS

The post-exercise expression of genes examined were comparable between Surgical, N95, and No Mask (P>0.05). ACE2 was significantly greater in Surgical and N95 against No Mask at baseline and following moderate-intensity exercise (P<0.05). Whilst similar expressions were noted for MasR and eNOS (P>0.05), AT<inf>1</inf>R was greater in N95 than Surgical following high-intensity exercise (P<0.05). HIF-1α following either exercise intensity was significantly lower in N95 than Surgical (P<0.05). AT<inf>1</inf>R and HIF-1α were similar between Surgical and N95 against No Mask (P>0.05). ACE2 and AT<inf>1</inf>R were significantly higher in either mask modality than No Mask in males at baseline and postexercise (P<0.05). HIF-1α, MasR, and eNOS expressions were comparable between all mask groups in either sex (P<0.05).

CONCLUSIONS

Our findings suggest that wearing a facemask does not differentiate the gene expression of SARS-CoV-2 entry receptor following exercise among both sexes.

Passengers' self-protective intentions while using ride-hailing services during the COVID-19 pandemic

In the transport context, there has been limited research examining passengers' health-protective behaviour while travelling during a health-related crisis such as COVID-19. This study develops a conceptual model aiming to explore determinants associated with passengers' self-protective intentions using the context of ride-hailing services in Vietnam. Ride-hailing services are popular in countries where public transport is underdeveloped. The conceptual model is based on perceived risk and self-efficacy as the main predictor of self-protective intentions when using ride-hailing services. In addition, the proposed conceptual model explores the direct and indirect impact of subjective knowledge and the perceived effectiveness of preventive measures on self-protective intentions. The proposed conceptual model was tested on a large sample of ride-hailing users in Vietnam (n = 527). The structural equation modelling (SEM) analysis results indicate that self-efficacy has the highest total impact on self-protective behaviour, followed by subject knowledge and perceived effectiveness of preventive measures. Self-efficacy also plays a fully mediating role in the linkage between the perceived effectiveness of preventive measures implemented by ride-hailing organisations and the intention to engage in self-protective behaviour. The results of this study expand the current understanding of ride-hailing passengers' health-protective behaviour and contribute to the transport and public health literature.

COMPARATIVE ASSESSMENT OF BACTERIAL PERMEABILITY OF A PERSONAL PROTECTIVE RESPIRATORY EQUIPMENT AT DIFFERENT DURATIONS OF ITS CONTINUOUS OPERATION

OBJECTIVE

The aim: To establish the level of antibacterial protection of the studied personal protective respiratory equipment set and its main components and compare antibacterial resistance of the personal protective respiratory equipment set in the presence and absence of filtering components.

PATIENTS AND METHODS

Materials and methods: The proposed methodology for assessing biological protection parameters is based on testing the permeability of personal respiratory protection equipment for bacteria by the method of serial dilutions. Also additional culturing of separate components of the protective set on a separate media is carried out. The experiment was also repeated in the absence of filtering elements and when they were replaced by gauze masks.

RESULTS

Results: The use of a fully equipped pneumatic helmet counteracted the penetration of the bacterial aerosol, which was manifested in the absence of growth on the media. The results obtained with the full configuration, as well as the indicators of the spread of bacteria when removing the filter elements and replacing them with gauze masks, showed that the device creates sufficient positive air pressure inside. The latter becomes a restraining factor that does not allow microorganisms to penetrate through the lower circuit.

CONCLUSION

Conclusions: Increasing the duration of continuous operation of the conceptual model up to 24 hours, increasing the bacterial load on the filters do not lead to a deterioration in the properties of antibacterial protection. Bacterial aerosol did not penetrate into the inner space of pneumatic helmet.

Polyvinylidene fluoride multi-scale nanofibrous membrane modified using N-halamine with high filtration efficiency and durable antibacterial properties for air filtration

HYPOTHESIS

Particulate matter (PM) pollution and the coronavirus (COVID-19) pandemic have increased demand for protective masks. However, typical protective masks only intercept particles and produce peculiar odors if worn for extended periods owing to bacterial growth. Therefore, new protective materials with good filtration and antibacterial capabilities are required.

EXPERIMENTS

In this study, we prepared multi-scale polyvinylidene fluoride (PVDF) nanofibrous membranes for efficient filtration and durable antibacterial properties via N-halamine modification.

FINDINGS

The N-halamine-modified nanofibrous membrane (PVDF-PAA-TMP-Cl) had sufficient active chlorine content (800 ppm), and the tensile stress and strain were improved compared with the original membrane, from 6.282 to 9.435 MPa and from 51.3 % to 56.4 %, respectively. To further improve the interception efficiency, ultrafine nanofibers (20-35 nm) were spun on PVDF-PAA-TMP-Cl nanofibrous membranes, and multi-scale PVDF-PAA-TMP-Cl nanofibrous membranes were prepared. These membranes exhibited good PM_0.3 interception (99.93 %), low air resistance (79 Pa), promising long-term PM_2.5 purification ability, and high bactericidal efficiency (>98 %). After ten chlorination cycles, the antibacterial efficiency against Escherichia coli and Staphylococcus aureus exceeded 90 %; hence, the material demonstrated highly efficient filtration and repeatable antibacterial properties. The results of this study have implications for the development of air and water filtration systems and multi-functional protective materials.

Study of fractional order dynamics of nonlinear mathematical model

This manuscript is devoted to establishing some theoretical and numerical results for a nonlinear dynamical system under Caputo fractional order derivative. Further, the said system addresses an infectious disease like COVID-19. The proposed system involves natural death rates of susceptible, infected and recovered classes respectively. By using nonlinear analysis feasible region and boundedness have been established first in this study. Global and Local stability analysis along with basic reproduction number have also addressed by using the next generation matrix method. Upon using the fixed point approach, existence and uniqueness of the approximate solution for the mentioned problem has also investigated. Some stability results of Hyers-Ulam (H-U) type have also discussed. Further for numerical treatment, we have exercised two numerical schemes including modified Euler method (MEM) and nonstandard finite difference (NSFD) method. Further the two numerical schemes have also compared with respect to CPU time. Graphical presentations have been displayed corresponding to different fractional order by using some real data.

To study the transmission dynamic of SARS-CoV-2 using nonlinear saturated incidence rate

In this work, we construct a new SARS-CoV-2 mathematical model of SQIR type. The considered model has four compartments as susceptible S , quarantine Q , infected I and recovered R . Here saturated nonlinear incidence rate is used for the transmission of the disease. We formulate our model first and then the disease-free and endemic equilibrium (EE) are calculated. Further, the basic reproduction number is computed via the next generation matrix method. Also on using the idea of Dulac function, the global stability for the proposed model is discussed. By using the Routh-Hurwitz criteria, local stability is investigated. Through nonstandard finite difference (NSFD) scheme, numerical simulations are performed. Keeping in mind the significant importance of fractional calculus in recent time, the considered model is also investigated under fractional order derivative in Caputo sense. Finally, numerical interpretation of the model by using various fractional order derivatives are provided. For fractional order model, we utilize fractional order NSFD method. Comparison with some real data is also given.

The Effects of Wearing a 3-Ply or KN95 Face Mask on Cerebral Blood Flow and Oxygenation

BACKGROUND

The SARS-CoV-2 virus has impacted life in many ways, one change being the use of face masks. Their effect on MRI-based measurements of cerebral oxygen levels with quantitative susceptibility mapping (QSM) and cerebral blood flow (CBF) is not known.

PURPOSE

This study investigated whether wearing a face mask leads to changes in CBF and cerebral venous oxygen saturation measured with MRI.

STUDY TYPE

Repeated-measures cohort study.

POPULATION

A total of 16 healthy volunteers (eight male, eight female; 22-36 years) were recruited for the 3-ply study. Ten of the 16 participants (five male, five female; 23-36 years) took part in the KN95 study.

FIELD STRENGTH/SEQUENCE

A 3 T, single-delay 3D gradient-and spin-echo pseudo-continuous arterial spin labeling (pCASL) scan for CBF quantification, and gradient-echo for QSM and oxygenation quantification.

ASSESSMENT

Gray matter CBF and magnetic susceptibility were assessed by masking the pCASL CBF map and the QSM map to the T₁ -weighted gray matter tissue segmentation. Venous oxygenation was determined from venous segmentation of QSM maximum intensity projections.

STATISTICAL TESTS

Paired Student's t-tests and Cohen's d effect sizes were used to compare the face mask and no face mask scans for gray matter CBF, gray matter magnetic susceptibility, and cerebral venous oxygen saturation. Standard t-tests were used to assess whether the order of scanning with and without a mask had any impact. A statistical cut off of P < 0.05 was used.

RESULTS

The 3-ply masks increased gray matter CBF from an average of 43.99 mL/(100 g*min) to 46.81 mL/(100 g*min). There were no significant changes in gray matter magnetic susceptibility (P = 0.07), or cerebral venous oxygen saturation (P = 0.36) for the 3-ply data set. The KN95 masks data set showed no statistically significant changes in gray matter CBF (P = 0.52) and magnetic susceptibility (P = 0.97), or cerebral venous oxygen saturation (P = 0.93).

DATA CONCLUSION

The changes in blood flow and oxygenation due to face masks are small. Only CBF increased significantly due to wearing a 3-ply mask.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 3.

Experimental and numerical evaluation of a new visor concept with aerodynamic sealing to protect medical professionals from contaminated droplets and aerosols

The fast spreading of the SARS-CoV-2 virus led to a significant increase in the demand for personal protective equipment (PPE). Healthcare professionals, mainly dentists, work near the patients, increasing their risk of infection. This paper investigates the effectiveness of an air-curtain sealing effect in a newly designed visor developed to reduce the risk of contracting a respiratory infection. This PPE was developed by computational fluid dynamics (CFD) modeling. CFD results show that the aerodynamic sealing in this PPE device effectively protects the user's face by 43% from a contaminated environment. The experiments considered two different tests: one using a tracer gas (CO₂ ) to simulate a gaseous contaminant inside and outside the PPE face shield and a second test using smoke to simulate aerosol transport and evaluate the PPE efficiency. The particle concentration within the aerodynamically sealed PPE was evaluated and compared with the protection efficiency of other PPE. Results show similar protection levels for particles in the 1-5 μm range between the prototype and a KN95 respirator. The combined use of this novel PPE with aerodynamic sealing and a physical mask (KN95 or surgical) produced protection efficiency values within the range of 57%-70% for particles greater than 0.5 μm. This study reveals the potential of using an air curtain combined with a face shield to reduce the risks from contaminated environments.

Fractal-fractional operator for COVID-19 (Omicron) variant outbreak with analysis and modeling

The fractal-fraction derivative is an advanced category of fractional derivative. It has several approaches to real-world issues. This work focus on the investigation of 2nd wave of Corona virus in India. We develop a time-fractional order COVID-19 model with effects of disease which consist system of fractional differential equations. Fractional order COVID-19 model is investigated with fractal-fractional technique. Also, the deterministic mathematical model for the Omicron effect is investigated with different fractional parameters. Fractional order system is analyzed qualitatively as well as verify sensitivity analysis. The existence and uniqueness of the fractional-order model are derived using fixed point theory. Also proved the bounded solution for new wave omicron. Solutions are derived to investigate the influence of fractional operator which shows the impact of the disease on society. Simulation has been made to understand the actual behavior of the OMICRON virus. Such kind of analysis will help to understand the behavior of the virus and for control strategies to overcome the disseise in community.

Does wearing a mask while exercising amid COVID-19 pandemic affect hemodynamic and hematologic function among healthy individuals? Implications of mask modality, sex, and exercise intensity

OBJECTIVES

We investigated how wearing a mask - and its modality (surgical vs. N95) - affect hemodynamic and hematologic function in males and females across two exercise intensities (submaximal (SUB) and maximal (MAX)).

METHODS

144 individuals participated in the present study and were randomly allocated to three mask groups of 48 (N95, SURGICAL, and NO MASK) with two exercise subgroups for each mask group (MAX, n = 24; SUB, n = 24) for both sexes. Participants in each experimental group (N95SUB, N95MAX; SURSUB, SURMAX; SUB, MAX) were assessed for their hemodynamic and hematologic function at baseline and during recovery after exercise.

RESULTS

No significant differences were noted for either hemodynamic or hematologic function at post-exercise as compared to baseline with regard to mask modality (P > 0.05). Heart rate (HR) for maximal intensity were significantly greater at 1 min post-exercise in N95 as compared to SURGICAL (P < 0.05). No differences were noted for hemodynamic and hematologic function with N95 and SURGICAL compared to NOMASK for either intensity (P > 0.05). Females showed significantly greater HR values at 1 min post-exercise in N95 as compared to NO MASK, but no significant differences were noted for hematological function between sexes (P > 0.05).

CONCLUSION

Our findings show that wearing a face mask (N95/surgical) while exercising has no detrimental effects on hemodynamic/hematologic function in both males and females, and suggest that wearing a mask, particularly a surgical mask, while exercising during the ongoing pandemic is safe and poses no risk to individual's health. Future studies examining physiological responses to chronic exercise with masks are warranted.

Modeling of COVID-19 spread with self-isolation at home and hospitalized classes

This work examines the impacts of self-isolation and hospitalization on the population dynamics of the Corona-Virus Disease. We developed a new nonlinear deterministic model eight classes compartment, with self-isolation and hospitalized being the most effective tools. There are (Susceptible S C ( t ) , Exposed E ( t ) , Asymptomatic infected I A ( t ) , Symptomatic infected A S ( t ) , Self-isolation T M ( t ) , Hospitalized T H ( t ) , Healed H ( t ) , and Susceptible individuals previously infected H C ( t ) ). The expression of basic reproduction number R 0 comes from the next-generation matrix method. With suitably constructed Lyapunov functions, the global asymptotic stability of the non-endemic equilibria Σ 0 for R 0 < 1 and that of endemic equilibria Σ ∗ for R 0 > 1 are established. The computed value of R 0 = 3 . 120277403 proves the endemic level of the epidemic. The outbreak will lessen if a policy is enforced like self-isolation and hospitalization. This is related to those policies that can reduce the number of direct contacts between infected and susceptible individuals or waning immunity individuals. Various simulations are presented to appreciate self-isolation at home and hospitalized strategies if applied sensibly. By performing a global sensitivity analysis, we can obtain parameter values that affect the model through a combination of Latin Hypercube Sampling and Partial Rating Correlation Coefficients methods to determine the parameters that affect the number of reproductions and the increase in the number of COVID cases. The results obtained show that the rate of self-isolation at home and the rate of hospitalism have a negative relationship. On the other hand, infections will decrease when the two parameters increase. From the sensitivity of the results, we formulate a control model using optimal control theory by considering two control variables. The result shows that the control strategies minimize the spread of the COVID infection in the population.

A new versatile modification of the Rayleigh distribution for modeling COVID-19 mortality rates

The aim of this paper is to specify a new flexible statistical model to analyze COVID-19 mortality rates in Italy and Canada. A new versatile lifetime distribution with four parameters is proposed by using the exponentiated generalized class of distributions and the gull alpha power Rayleigh distribution to form the exponentiated generalized gull alpha power Rayleigh (EGGAPR) distribution. This new distribution is characterized by a tractable cumulative distribution function. To estimate the unknown parameters of the proposed distribution the maximum likelihood estimation method is used. In evaluating the effectiveness of the MLE method graphical displays of the Monte Carlo simulation are presented. The EGGAPR distribution is compared to its sub-models which include the exponentiated gull alpha Rayleigh distribution, the gull alpha Rayleigh distribution, exponentiated generalized Rayleigh distribution, exponentiated Rayleigh distribution and the Rayleigh distribution. Different measures of goodness-of-fit are used to investigate whether the EGGAPR distribution is more flexible and fit than its sub-models in modeling COVID-19 mortality rates.

Mathematical modeling and stability analysis of the COVID-19 with quarantine and isolation

The present paper focuses on the modeling of the COVID-19 infection with the use of hospitalization, isolation and quarantine. Initially, we construct the model by spliting the entire population into different groups. We then rigorously analyze the model by presenting the necessary basic mathematical features including the feasible region and positivity of the problem solution. Further, we evaluate the model possible equilibria. The theoretical expression of the most important mathematical quantity of major public health interest called the basic reproduction number is presented. We are taking into account to study the disease free equilibrium by studying its local and global asymptotical analysis. We considering the cases of the COVID-19 infection of Pakistan population and find the parameters using the estimation with the help of nonlinear least square and have R 0 ≈ 1 . 95 . Further, to determine the influence of the model parameters on disease dynamics we perform the sensitivity analysis. Simulations of the model are presented using estimated parameters and the impact of various non-pharmaceutical interventions on disease dynamics is shown with the help of graphical results. The graphical interpretation justify that the effective utilization of keeping the social-distancing, making the quarantine of people (or contact-tracing policy) and to make hospitalization of confirmed infected people that dramatically reduces the number of infected individuals (enhancing the quarantine or contact-tracing by 50% from its baseline reduces 84% in the predicted number of confirmed infected cases). Moreover, it is observed that without quarantine and hospitalization the scenario of the disease in Pakistan is very worse and the infected cases are raising rapidly. Therefore, the present study suggests that still, a proper and effective application of these non-pharmaceutical interventions are necessary to curtail or minimize the COVID-19 infection in Pakistan.

Towards an Approach for Filtration Efficiency Estimation of Consumer-Grade Face Masks Using Thermography

Due to the increasing need for continuous use of face masks caused by COVID-19, it is essential to evaluate the filtration quality that each face mask provides. In this research, an estimation method based on thermal image processing was developed; the main objective was to evaluate the effectiveness of different face masks while being used during breathing. For the acquisition of heat distribution images, a thermographic imaging system was built; moreover, a deep learning model detected the leakage percentage of each face mask with a mAP of 0.9345, recall of 0.842 and F1-score of 0.82. The results obtained from this research revealed that the filtration effectiveness depended on heat loss through the manufacturing material; the proposed estimation method is simple, fast, and can be replicated and operated by people who are not experts in the computer field.

The Complex Systems for Conflict Interaction Modelling to Describe a Non-Trivial Epidemiological Situation

This study investigates a complex system that describes a non-trivial epidemiological model with integrated internal conflict (interregional migration) on the example of cyclic migration using the software. JetBrains PyCharm Community Edition 2020.3.3, a free and open-source integrated development environment (IDE) in the Python programming language, was chosen as the software development tool. The Matplotlib 3.5 library was used to display the modelling results graphically. The integration of internal conflict into the model revealed significant and notable changes in its behavior. This study’s results prove that not only the characteristics of the interaction factors but also the size of the values determine the direction of migration concerning relation to competitors.

Processing and Quality Control of Masks: A Review

It is clear that viruses, especially COVID-19, can cause infection and injure the human body. These viruses can transfer in different ways, such as in air transfer, which face masks can prevent and reduce. Face masks can protect humans through their filtration function. They include different types and mechanisms of filtration whose performance depends on the texture of the fabric, the latter of which is strongly related to the manufacturing method. Thus, scientists should enrich the information on mask production and quality control by applying a wide variety of tests, such as leakage, dynamic respiratory resistance (DBR), etc. In addition, the primary manufacturing methods (meltblown, spunlaid, drylaid, wetlaid and airlaid) and new additive manufacturing (AM) methods (such as FDM) should be considered. These methods are covered in this study.

Smart facemask for wireless CO2 monitoring

The use of facemasks by the general population is recommended worldwide to prevent the spread of SARS-CoV-2. Despite the evidence in favour of facemasks to reduce community transmission, there is also agreement on the potential adverse effects of their prolonged usage, mainly caused by CO2 rebreathing. Herein we report the development of a sensing platform for gaseous CO2 real-time determination inside FFP2 facemasks. The system consists of an opto-chemical sensor combined with a flexible, battery-less, near-field-enabled tag with resolution and limit of detection of 103 and 140 ppm respectively, and sensor lifetime of 8 h, which is comparable with recommended FFP2 facemask usage times. We include a custom smartphone application for wireless powering, data processing, alert management, results displaying and sharing. Through performance tests during daily activity and exercise monitoring, we demonstrate its utility for non-invasive, wearable health assessment and its potential applicability for preclinical research and diagnostics.

Improving compliance with physical distancing across religious cultures in Israel

BACKGROUND

Physical distancing contains the corona virus, but compliance with physical distancing across religious minorities in Israel has been shown to be relatively poorer than in the majority population. This study tests the power of messages as drivers of willingness to comply with physical distancing across religious minorities in Israel during the first wave of the COVID-19 from March till June 2020.

METHODS

896 Israeli Muslims, Druze, Bedouins, Jewish Orthodox, Christians, and Jewish Seculars participated in this conjoint-based experimental design. The size of the total sample and of the subgroups is consistent with the suggested size in conjoint analysis studies, particularly when aiming at stability of coefficients rather than stability of means. The dependent variable was 'willingness to comply'. Independent variables were known contributors to compliance: perceived risk, practices of physical distancing, ways to assure compliance, and the agent communicating the policy.

RESULTS

A regression analysis indicated minor differences in the power of messages across groups despite dramatic cultural differences amongst them. We identified three distinct mindsets that transcend religious cultures from the responses of the study subjects to various messages and named them "pandemic observers," "obedient followers," and "sensitive interpreters." Compliance of "Pandemic Observers" (n = 306) may be improved by messages such as, "Dangerous virus spreading wildly" and "Health experts suggest what to do but the government is reactive rather than proactive" (β = 14, p < .005). Compliance of "Obedient Followers" (n = 242) may be driven by the messages "Socialize and work only from home, using the internet, e.g. zoom/Skype" and "Everyone should stay 2 m. (6 ft.) apart" (β = 16, p < .0050). Compliance of "Sensitive Interpreters" (n = 249) may be improved by messages such as, "Only people who are 60 and over are to be allowed to buy groceries during first 2 h from opening" and by using the media to publicize the official health policy (β = 8; p < .005).

CONCLUSIONS

Mindset-assignment reflects how people think rather than their religious affiliation. A personal viewpoint identifier was developed to predict mindset-assignment and enable health authorities to enhance compliance through mindset-tailored messages for members of each mindset segment. We recommend that health authorities and policy makers consider these different personality types, which range across religious minorities and emphasize the messages that each type responds to in developing and implementing a communication plan to improve physical distancing as an important public health measure.

A mathematical model for human-to-human transmission of COVID-19: a case study for Turkey's data

In this study, a mathematical model for simulating the human-to-human transmission of the novel coronavirus disease (COVID-19) is presented for Turkey's data. For this purpose, the total population is classified into eight epidemiological compartments, including the super-spreaders. The local stability and sensitivity analysis in terms of the model parameters are discussed, and the basic reproduction number, R₀, is derived. The system of nonlinear ordinary differential equations is solved by using the Galerkin finite element method in the FEniCS environment. Furthermore, to guide the interested reader in reproducing the results and/or performing their own simulations, a sample solver is provided. Numerical simulations show that the proposed model is quite convenient for Turkey's data when used with appropriate parameters.

Modeling third waves of Covid-19 spread with piecewise differential and integral operators: Turkey, Spain and Czechia

Several collected data representing the spread of some infectious diseases have demonstrated that the spread does not really exhibit homogeneous spread. Clear examples can include the spread of Spanish flu and Covid-19. Collected data depicting numbers of daily new infections in the case of Covid-19 from countries like Turkey, Spain show three waves with different spread patterns, a clear indication of crossover behaviors. While modelers have suggested many mathematical models to depicting these behaviors, it becomes clear that their mathematical models cannot really capture the crossover behaviors, especially passage from deterministic resetting to stochastics. Very recently Atangana and Seda have suggested a concept of piecewise modeling consisting in defining a differential operator piece-wisely. The idea was first applied in chaos and outstanding patterns were captured. In this paper, we extend this concept to the field of epidemiology with the aim to depict waves with different patterns. Due to the novelty of this concept, a different approach to insure the existence and uniqueness of system solutions are presented. A piecewise numerical approach is presented to derive numerical solutions of such models. An illustrative example is presented and compared with collected data from 3 different countries including Turkey, Spain and Czechia. The obtained results let no doubt for us to conclude that this concept is a new window that will help mankind to better understand nature.

Functionalized Masks: Powerful Materials against COVID-19 and Future Pandemics

The outbreak of COVID-19 revealed the vulnerability of commercially available face masks. Without having antibacterial/antiviral activities, the current masks act only as filtering materials of the aerosols containing microorganisms. Meanwhile, in surgical masks, the viral and bacterial filtration highly depends on the electrostatic charges of masks. These electrostatic charges disappear after 8 h, which leads to a significant decline in filtration efficiency. Therefore, to enhance the masks' protection performance, fabrication of innovative masks with more advanced functions is in urgent demand. This review summarizes the various functionalizing agents which can endow four important functions in the masks including i) boosting the antimicrobial and self-disinfectant characteristics via incorporating metal nanoparticles or photosensitizers, ii) increasing the self-cleaning by inserting superhydrophobic materials such as graphenes and alkyl silanes, iii) creating photo/electrothermal properties by forming graphene and metal thin films within the masks, and iv) incorporating triboelectric nanogenerators among the friction layers of masks to stabilize the electrostatic charges and facilitating the recharging of masks. The strategies for creating these properties toward the functionalized masks are discussed in detail. The effectiveness and limitation of each method in generating the desired properties are well-explained along with addressing the prospects for the future development of masks.

On fractional approaches to the dynamics of a SARS-CoV-2 infection model including singular and non-singular kernels

Covid-19 (2019-nCoV) disease has been spreading in China since late 2019 and has spread to various countries around the world. With the spread of the disease around the world, much attention has been paid to epidemiological knowledge. This knowledge plays a key role in understanding the pattern of disease transmission and how to prevent a larger population from contracting it. In the meantime, one should not overlook the significant role that mathematical descriptions play in epidemiology. In this paper, using some known definitions of fractional derivatives, which is a relatively new definition in differential calculus, and then by employing them in a mathematical framework, the effects of these tools in a better description of the epidemic of a SARS-CoV-2 infection is investigated. To solve these problems, efficient numerical methods have been used which can provide a very good approximation of the solution of the problem. In addition, numerical simulations related to each method will be provided in solving these models. The results obtained in each case indicate that the used approximate methods have been able to provide a good description of the problem situation.

Fluid dynamics of respiratory droplets in the context of COVID-19: Airborne and surfaceborne transmissions

The World Health Organization has declared COVID-19 a global pandemic. Several countries have experienced repeated periods of major spreading over the last two years. Many people have lost their lives, employment, and the socioeconomic situation has been severely impacted. Thus, it is considered to be one of the major health and economic disasters in modern history. Over the last two years, several researchers have contributed significantly to the study of droplet formation, transmission, and lifetime in the context of understanding the spread of such respiratory infections from a fluid dynamics perspective. The current review emphasizes the numerous ways in which fluid dynamics aids in the comprehension of these aspects. The biology of the virus, as well as other statistical studies to forecast the pandemic, is significant, but they are not included in this review.

A novel mathematical model for COVID-19 with remedial strategies

Coronavirus (COVID-19) outbreak from Wuhan, Hubei province in China and spread out all over the World. In this work, a new mathematical model is proposed. The model consists the system of ODEs. The developed model describes the transmission pathways by employing non constant transmission rates with respect to the conditions of environment and epidemiology. There are many mathematical models purposed by many scientists. In this model, "α E " and "α I ", transmission coefficients of the exposed cases to susceptible and infectious cases to susceptible respectively, are included. " δ " as a governmental action and restriction against the spread of coronavirus is also introduced. The RK method of order four (RK4) is employed to solve the model equations. The results are presented for four countries i.e., Pakistan, Italy, Japan, and Spain etc. The parametric study is also performed to validate the proposed model.

N95 respirator mask breathing leads to excessive carbon dioxide inhalation and reduced heat transfer in a human nasal cavity

Face masks and respirators are used to filter inhaled air, which may contain airborne droplets and high particulate matter (PM) concentrations. The respirators act as a barrier to the inhaled and exhaled air, which may change the nasal airflow characteristics and air-conditioning function of the nose. This study aims to investigate the nasal airflow dynamics during respiration with and without an N95 respirator driven by airflow through the nasal cavity to assess the effect of the respirator on breathing conditions during respiration. To achieve the objective of this study, transient computational fluid dynamics simulations have been utilized. The nasal geometry was reconstructed from high-resolution Computed Tomography scans of a healthy 25-year-old female subject. The species transport method was used to analyze the airflow, temperature, carbon dioxide (CO₂), moisture content (H₂O), and temperature distribution within the nasal cavity with and without an N95 respirator during eight consecutive respiration cycles with a tidal volume of 500 ml. The results demonstrated that a respirator caused excessive CO₂ inhalation by approximately 7 × greater per breath compared with normal breathing. Furthermore, heat and mass transfer in the nasal cavity was reduced, which influences the perception of nasal patency. It is suggested that wearers of high-efficiency masks that have minimal porosity and low air exchange for CO₂ regulation should consider the amount of time they wear the mask.

Modeling the survival times of the COVID-19 patients with a new statistical model: A case study from China

Over the past few months, the spread of the current COVID-19 epidemic has caused tremendous damage worldwide, and unstable many countries economically. Detailed scientific analysis of this event is currently underway to come. However, it is very important to have the right facts and figures to take all possible actions that are needed to avoid COVID-19. In the practice and application of big data sciences, it is always of interest to provide the best description of the data under consideration. The recent studies have shown the potential of statistical distributions in modeling data in applied sciences, especially in medical science. In this article, we continue to carry this area of research, and introduce a new statistical model called the arcsine modified Weibull distribution. The proposed model is introduced using the modified Weibull distribution with the arcsine-X approach which is based on the trigonometric strategy. The maximum likelihood estimators of the parameters of the new model are obtained and the performance these estimators are assessed by conducting a Monte Carlo simulation study. Finally, the effectiveness and utility of the arcsine modified Weibull distribution are demonstrated by modeling COVID-19 patients data. The data set represents the survival times of fifty-three patients taken from a hospital in China. The practical application shows that the proposed model out-classed the competitive models and can be chosen as a good candidate distribution for modeling COVID-19, and other related data sets.

Complex mathematical SIR model for spreading of COVID-19 virus with Mittag-Leffler kernel

This paper investigates a new model on coronavirus-19 disease (COVID-19), that is complex fractional SIR epidemic model with a nonstandard nonlinear incidence rate and a recovery, where derivative operator with Mittag-Leffler kernel in the Caputo sense (ABC). The model has two equilibrium points when the basic reproduction number R 0 > 1 ; a disease-free equilibrium E 0 and a disease endemic equilibrium E 1 . The disease-free equilibrium stage is locally and globally asymptotically stable when the basic reproduction number R 0 < 1 , we show that the endemic equilibrium state is locally asymptotically stable if R 0 > 1 . We also prove the existence and uniqueness of the solution for the Atangana-Baleanu SIR model by using a fixed-point method. Since the Atangana-Baleanu fractional derivative gives better precise results to the derivative with exponential kernel because of having fractional order, hence, it is a generalized form of the derivative with exponential kernel. The numerical simulations are explored for various values of the fractional order. Finally, the effect of the ABC fractional-order derivative on suspected and infected individuals carefully is examined and compared with the real data.

A two-phase dynamic contagion model for COVID-19

In this paper, we propose a continuous-time stochastic intensity model, namely, two-phase dynamic contagion process (2P-DCP), for modelling the epidemic contagion of COVID-19 and investigating the lockdown effect based on the dynamic contagion model introduced by Dassios and Zhao [24]. It allows randomness to the infectivity of individuals rather than a constant reproduction number as assumed by standard models. Key epidemiological quantities, such as the distribution of final epidemic size and expected epidemic duration, are derived and estimated based on real data for various regions and countries. The associated time lag of the effect of intervention in each country or region is estimated. Our results are consistent with the incubation time of COVID-19 found by recent medical study. We demonstrate that our model could potentially be a valuable tool in the modeling of COVID-19. More importantly, the proposed model of 2P-DCP could also be used as an important tool in epidemiological modelling as this type of contagion models with very simple structures is adequate to describe the evolution of regional epidemic and worldwide pandemic.

Transmission dynamics of SARS-CoV-2: A modeling analysis with high-and-moderate risk populations

Nigeria is second to South Africa with the highest reported cases of COVID-19 in sub-Saharan Africa. In this paper, we employ an SEIR-based compartmental model to study and analyze the transmission dynamics of SARS-CoV-2 outbreaks in Nigeria. The model incorporates different group of populations (that is, high- and- moderate risk populations) and is use to investigate the influence on each population on the overall transmission dynamics.The model, which is fitted well to the data, is qualitatively analyzed to evaluate the impacts of different schemes for controlstrategies. Mathematical analysis reveals that the model has two equilibria; i.e., disease-free equilibrium (DFE) which is local asymptotic stability (LAS) if the basic reproduction number (R 0 ) is less than 1; and unstable forR 0 > 1 , and an endemic equilibrium (EE) which is globally asymptotic stability (LAS) wheneverR 0 > 1 . Furthermore, we find that the model undergoes a phenomenon of backward bifurcation (BB, a coexistence of stable DFE and stable EE even if theR 0 < 1 ). We employ Partial Rank Correlation coefficients (PRCCs) for sensitivity analyses to evaluate the model's parameters. Our results highlight that proper surveillance, especially movement of individuals from high risk to moderate risk population, testing, as well as imposition of other NPIs measures are vital strategies for mitigating the COVID-19 epidemic in Nigeria. Besides, in the absence of an exact solution for the proposed model, we solve the model with the well-known ODE45 numerical solver and the effective numerical schemes such as Euler (EM), Runge-Kutta of order 2 (RK-2), and Runge-Kutta of order 4 (RK-4) in order to establish approximate solutions and to show the physical features of the model. It has been shown that these numerical schemes are very effective and efficient to establish superb approximate solutions for differential equations.

Mathematical analysis and optimal control interventions for sex structured syphilis model with three stages of infection and loss of immunity

In this study, we develop a nonlinear ordinary differential equation to study the dynamics of syphilis transmission incorporating controls, namely prevention and treatment of the infected males and females. We obtain syphilis-free equilibrium (SFE) and syphilis-present equilibrium (SPE). We obtain the basic reproduction number, which can be used to control the transmission of the disease, and thus establish the conditions for local and global stability of the syphilis-free equilibrium. The stability results show that the model is locally asymptotically stable if the Routh-Hurwitz criteria are satisfied and globally asymptotically stable. The bifurcation analysis result reveals that the model exhibits backward bifurcation. We adopted Pontryagin's maximum principle to determine the optimality system for the syphilis model, which was solved numerically to show that syphilis transmission can be optimally best control using a combination of condoms usage and treatment in the primary stage of infection in both infected male and female populations.

Global transmission dynamic of SIR model in the time of SARS-CoV-2

This current work studies a new mathematical model for SARS-CoV-2. We show how immigration, protection, death rate, exposure, cure rate and interaction of infected people with healthy people affect the population. Our model is SIR model, which has three classes including susceptible, infected and recovered respectively. Here, we find the basic reproduction number and local stability through jacobean matrix. Lyapunvo function theory is used to calculate the global stability for the problem under investigation. Also a nonstandard finite difference sachem (NSFDS) is used to simulate the results.

On nonlinear classical and fractional order dynamical system addressing COVID-19

This work studies a new SEIR type mathematical model for SARS-CoV-2. We show how immigration, protection, death rate, exposure, cure rate and interaction of infected people with healthy people affect the population. Our model has four classes including susceptible, exposed, infected and recovered respectively. Here, we find the basic reproduction number and local stability through jacobean matrix. Lyapunov function theory is used to calculate the global stability for the problem under investigation. Also an attempt is made to derive some numerical interpretation under fractional derivative by using fractional order nonstandard finite difference (NSFD) sachem. The graphical presentations are given for some real data.

Carbon dioxide increases with face masks but remains below short-term NIOSH limits

BACKGROUND AND PURPOSE

COVID-19 pandemic led to wide-spread use of face-masks, respirators and other personal protective equipment (PPE) by healthcare workers. Various symptoms attributed to the use of PPE are believed to be, at least in part, due to elevated carbon-dioxide (CO2) levels. We evaluated concentrations of CO2 under various PPE.

METHODS

In a prospective observational study on healthy volunteers, CO2 levels were measured during regular breathing while donning 1) no mask, 2) JustAir® powered air purifying respirator (PAPR), 3) KN95 respirator, and 4) valved-respirator. Serial CO2 measurements were taken with a nasal canula at a frequency of 1-Hz for 15-min for each PPE configuration to evaluate whether National Institute for Occupational Safety and Health (NIOSH) limits were breached.

RESULTS

The study included 11 healthy volunteers, median age 32 years (range 16-54) and 6 (55%) men. Percent mean (SD) changes in CO2 values for no mask, JustAir® PAPR, KN95 respirator and valve respirator were 0.26 (0.12), 0.59 (0.097), 2.6 (0.14) and 2.4 (0.59), respectively. Use of face masks (KN95 and valved-respirator) resulted in significant increases in CO2 concentrations, which exceeded the 8-h NIOSH exposure threshold limit value-weighted average (TLV-TWA). However, the increases in CO2 concentrations did not breach short-term (15-min) limits. Importantly, these levels were considerably lower than the long-term (8-h) NIOSH limits during donning JustAir® PAPR. There was a statistically significant difference between all pairs (p < 0.0001, except KN95 and valved-respirator (p = 0.25). However, whether increase in CO2 levels are clinically significant remains debatable.

CONCLUSION

Although, significant increase in CO2 concentrations are noted with routinely used face-masks, the levels still remain within the NIOSH limits for short-term use. Therefore, there should not be a concern in their regular day-to-day use for healthcare providers. The clinical implications of elevated CO2 levels with long-term use of face masks needs further studies. Use of PAPR prevents relative hypercapnoea. However, whether PAPR should be advocated for healthcare workers requiring PPE for extended hours needs to evaluated in further studies.

Extinction and persistence of a stochastic SIRV epidemic model with nonlinear incidence rate

In this paper, a stochastic SIRV epidemic model with general nonlinear incidence and vaccination is investigated. The value of our study lies in two aspects. Mathematically, with the help of Lyapunov function method and stochastic analysis theory, we obtain a stochastic threshold of the model that completely determines the extinction and persistence of the epidemic. Epidemiologically, we find that random fluctuations can suppress disease outbreak, which can provide us some useful control strategies to regulate disease dynamics. In other words, neglecting random perturbations overestimates the ability of the disease to spread. The numerical simulations are given to illustrate the main theoretical results.

Optimal Control of Mathematical modeling of the spread of the COVID-19 pandemic with highlighting the negative impact of quarantine on diabetics people with Cost-effectiveness

As of November 14, 2020, the number of people infected with the COVID-19 disease has reached more than 54 million people worldwide and more than 1323196 people have died, according to the World Health Organization. This requires many countries to impose a health emergency or quarantine, which has had positive results in reducing the spread of the COVID-19 pandemic, and it has also had negative economic, social and health effects. So, we suggest a mathematical model for the dynamics of how COVID-19 disease is spread, as well as a mathematical modeling for the dynamics of diabetes, then highlight the negative effect of quarantine has on the health of diabetics. Pontryagin's maximum principle is used to characterize the optimal controls, and the optimality system is solved by an iterative method. Finally, some numerical simulations are performed to verify the theoretical analysis using MATLAB.

Evaluation of the effect of n95 face mask used by healthcare professionals on choroidal thickness

PURPOSE

We aimed to show the changes in choroidal thickness (CT) with spectral domain optical coherence tomography (SD-OCT) after prolonged use of N95 mask.

METHOD

The healthcare workers who use the N95 face-mask, between 30-50 years of age who have best corrected visual acuity (BCVA) ≥10/10, spherical or cylindrical refraction errors less than 2 diopters, with normal intra ocular pressure (IOP), axial length (AL) between 22-24 mm included in the study. The choroid was imaged with enhanced depth imaging (EDI) techniques using SD-OCT. CT was measured, subfoveal, at 1000 μm nasal and temporal of the center of the fovea. Measurements were first made after wearing the N95 mask for at least 2 h without removing it and repeated 15 min after removing.

RESULTS

After 2 h of the N95 mask using without removal, the mean subfoveal CT was 293.56 ± 76.12(min:185, max:479), the mean temporal CT was 253.81 ± 63.48(min:172, max:384), the mean nasal CT was 239.18 ± 53.92(min:139, max:356). Fifteen minutes after removal of the N95 mask, the mean subfoveal CT was 250.56 ± 52.48(min:172, max:397), the mean temporal was 218.40 ± 53.58(min:129, max:354), the mean nasal CT was 210.67 ± 53.31(min:132, max:366). The differences in subfoveal, temporal and nasal CT between 2 h of N95 mask use and 15 min after removal of the mask were statistically significant (p < 0.05 for each).

CONCLUSION

Hypercapnia due to prolonged use of the N95 mask may cause choroidal hemodynamic changes and transient increased choroidal thickness.

Mathematical analysis and simulation of a stochastic COVID-19 Lévy jump model with isolation strategy

This paper investigates the dynamics of a COVID-19 stochastic model with isolation strategy. The white noise as well as the Lévy jump perturbations are incorporated in all compartments of the suggested model. First, the existence and uniqueness of a global positive solution are proven. Next, the stochastic dynamic properties of the stochastic solution around the deterministic model equilibria are investigated. Finally, the theoretical results are reinforced by some numerical simulations.

Investigation of the dynamics of COVID-19 with a fractional mathematical model: A comparative study with actual data

One of the greatest challenges facing the humankind nowadays is to confront that emerging virus, which is the Coronavirus (COVID-19), and therefore all organizations have to unite in order to tackle that the transmission risk of this virus. From this standpoint, the scientific researchers have to find good mathematical models that do describe the transmission of such virus and contribute to reducing it in one way or another, where the study of COVID-19 transmission dynamics by mathematical models is very important for analyzing and controlling this disease propagation. Thus, in the current work, we present a new fractional-order mathematical model that describes the dynamics of COVID-19. In the proposed model, the total population is divided into eight classes, in addition to three compartments used to estimate the parameters and initial values. The effective reproduction number ( R 0 ) is derived by next generation matrix (NGM) method and all possible equilibrium points and their stability are investigated in details. We used the reported data (from January 23, 2020, to November 21, 2020) from the National Health Commission (NHC) of China to estimate the parameters and initial conditions (ICs) which suggested for our model. Simulation outcomes demonstrate that the fractional order model (FOM) represents behaviors that follow the real data more accurately than the integer-order model. The current work enhances the recent reported results of Zu et al. published in THE LANCET (doi:10.2139/ssrn.3539669).

Recent advances in nanomaterials based biosensors for point of care (PoC) diagnosis of Covid-19 - A minireview

Early diagnosis and ultrahigh sample throughput screening are the need of the hour to control the geological spread of the COVID-19 pandemic. Traditional laboratory tests such as enzyme-linked immunosorbent assay (ELISA), reverse transcription polymerase chain reaction (RT-PCR) and computed tomography are implemented for the detection of COVID-19. However, they are limited by the laborious sample collection and processing procedures, longer wait time for test results and skilled technicians to operate sophisticated facilities. In this context, the point of care (PoC) diagnostic platform has proven to be the prospective approach in addressing the abovementioned challenges. This review emphasizes the mechanism of viral infection spread detailing the host-virus interaction, pathophysiology, and the recent advances in the development of affordable PoC diagnostic platforms for rapid and accurate diagnosis of COVID-19. First, the well-established optical and electrochemical biosensors are discussed. Subsequently, the recent advances in the development of PoC biosensors, including lateral flow immunoassays and other emerging techniques, are highlighted. Finally, a focus on integrating nanotechnology with wearables and smartphones to develop smart nanobiosensors is outlined, which could promote COVID-19 diagnosis accessible to both individuals and the mass population at patient care.

Mathematical analysis of COVID-19 by using SIR model with convex incidence rate

This paper is about a new COVID-19 SIR model containing three classes; Susceptible S(t), Infected I(t), and Recovered R(t) with the Convex incidence rate. Firstly, we present the subject model in the form of differential equations. Secondly, "the disease-free and endemic equilibrium" is calculated for the model. Also, the basic reproduction number R 0 is derived for the model. Furthermore, the Global Stability is calculated using the Lyapunov Function construction, while the Local Stability is determined using the Jacobian matrix. The numerical simulation is calculated using the Non-Standard Finite Difference (NFDS) scheme. In the numerical simulation, we prove our model using the data from Pakistan. "Simulation" means how S(t), I(t), and R(t) protection, exposure, and death rates affect people with the elapse of time.

Caputo SIR model for COVID-19 under optimized fractional order

Everyone is talking about coronavirus from the last couple of months due to its exponential spread throughout the globe. Lives have become paralyzed, and as many as 180 countries have been so far affected with 928,287 (14 September 2020) deaths within a couple of months. Ironically, 29,185,779 are still active cases. Having seen such a drastic situation, a relatively simple epidemiological SIR model with Caputo derivative is suggested unlike more sophisticated models being proposed nowadays in the current literature. The major aim of the present research study is to look for possibilities and extents to which the SIR model fits the real data for the cases chosen from 1 April to 15 March 2020, Pakistan. To further analyze qualitative behavior of the Caputo SIR model, uniqueness conditions under the Banach contraction principle are discussed and stability analysis with basic reproduction number is investigated using Ulam-Hyers and its generalized version. The best parameters have been obtained via the nonlinear least-squares curve fitting technique. The infectious compartment of the Caputo SIR model fits the real data better than the classical version of the SIR model (Brauer et al. in Mathematical Models in Epidemiology 2019). Average absolute relative error under the Caputo operator is about 48% smaller than the one obtained in the classical case ( ν = 1 ). Time series and 3D contour plots offer social distancing to be the most effective measure to control the epidemic.