Computational modeling of fractional COVID-19 model by Haar wavelet collocation Methods with real data.

This study explores the use of numerical simulations to model the spread of the Omicron variant of the SARS-CoV-2 virus using fractional-order COVID-19 models and Haar wavelet collocation methods. The fractional order COVID-19 model considers various factors that affect the virus's transmission, and the Haar wavelet collocation method offers a precise and efficient solution to the fractional derivatives used in the model. The simulation results yield crucial insights into the Omicron variant's spread, providing valuable information to public health policies and strategies designed to mitigate its impact. This study marks a significant advancement in comprehending the COVID-19 pandemic's dynamics and the emergence of its variants. The COVID-19 epidemic model is reworked utilizing fractional derivatives in the Caputo sense, and the model's existence and uniqueness are established by considering fixed point theory results. Sensitivity analysis is conducted on the model to identify the parameter with the highest sensitivity. For numerical treatment and simulations, we apply the Haar wavelet collocation method. Parameter estimation for the recorded COVID-19 cases in India from 13 July 2021 to 25 August 2021 has been presented.

Health systems and nutrition in the time of COVID-19.

As infection rates rise, job losses increase and workers leave cities to walk back home, and there is a silent hunger and nutrition crisis striking the country. Those who will bear the brunt of this are the already vulnerable-namely, children, adolescent girls, nursing and expectant mothers-now denied even basic calories. Among these are some who are also suffering huge weight losses because of the 15 days of high fever. This tragedy will play out in various horrifying ways in the future and must be addressed with urgency. Our stimulus package promises loans, which will take time to reach the poor, and a meager ration of cereals and pulses, while hunger and insufficient nutrition are immediate problems as Raghuram Rajan pointed out recently.

Analysis of fractional COVID-19 epidemic model under Caputo operator.

The article deals with the analysis of the fractional COVID-19 epidemic model (FCEM) with a convex incidence rate. Keeping in view the fading memory and crossover behavior found in many biological phenomena, we study the coronavirus disease by using the noninteger Caputo derivative (CD). Under the Caputo operator (CO), existence and uniqueness for the solutions of the FCEM have been analyzed using fixed point theorems. We study all the basic properties and results including local and global stability. We show the global stability of disease-free equilibrium using the method of Castillo-Chavez, while for disease endemic, we use the method of geometrical approach. Sensitivity analysis is carried out to highlight the most sensitive parameters corresponding to basic reproduction number. Simulations are performed via first-order convergent numerical technique to determine how changes in parameters affect the dynamical behavior of the system.

Extinction and persistence of a stochastic delayed Covid-19 epidemic model.

We formulated a Coronavirus (COVID-19) delay epidemic model with random perturbations, consisting of three different classes, namely the susceptible population, the infectious population, and the quarantine population. We studied the proposed problem to derive at least one unique solution in the positive feasweible region of the non-local solution. Sufficient conditions for the extinction and persistence of the proposed model are established. Our results show that the influence of Brownian motion and noise on the transmission of the epidemic is very large. We use the first-order stochastic Milstein scheme, taking into account the required delay of infected individuals.

COVID-19 Model with High- and Low-Risk Susceptible Population Incorporating the Effect of Vaccines.

It is a known fact that there are a particular set of people who are at higher risk of getting COVID-19 infection. Typically, these high-risk individuals are recommended to take more preventive measures. The use of non-pharmaceutical interventions (NPIs) and the vaccine are playing a major role in the dynamics of the transmission of COVID-19. We propose a COVID-19 model with high-risk and low-risk susceptible individuals and their respective intervention strategies. We find two equilibrium solutions and we investigate the basic reproduction number. We also carry out the stability analysis of the equilibria. Further, this model is extended by considering the vaccination of some non-vaccinated individuals in the high-risk population. Sensitivity analyses and numerical simulations are carried out. From the results, we are able to obtain disease-free and endemic equilibrium solutions by solving the system of equations in the model and show their global stabilities using the Lyapunov function technique. The results obtained from the sensitivity analysis shows that reducing the hospitals' imperfect efficacy can have a positive impact on the control of COVID-19. Finally, simulations of the extended model demonstrate that vaccination could adequately control or eliminate COVID-19.

The SQEIRP Mathematical Model for the COVID-19 Epidemic in Thailand

The spread of COVID-19 started in late December 2019 and is still ongoing. Many countries around the world have faced an outbreak of COVID-19, including Thailand, which must keep an eye on the spread and find a way to deal with this extreme outbreak. Of course, we are unable to determine the number of people who will contract this disease in the future. Therefore, if there is a tool that helps to predict the outbreak and the number of people infected, it will be able to find preventive measures in time. This paper aims to develop a mathematical model suitable for the lifestyle of the Thai population facing the COVID-19 situation. It has been established that after close contact with an infected person, a group of individuals will be quarantined and non-quarantined. If they contract COVID-19, they will enter the incubation period of the infection. The incubation period is divided into the quarantine class and the exposed class. Afterwards, both classes will move to the hospitalized infected class and the infected class, wherein the infected class is able to spread the disease to the surrounding environment. This study describes both classes in the SQEIRP model based on the population segmentation that was previously discussed. After that, the positive and bounded solutions of the model are examined, and we consider the equilibrium point, as well as the global stability of the disease-free point according to the Castillo-Chavez method. The SQEIRP model is then numerically analyzed using MATLAB software version R2022a. The cumulative percentage of hospitalized and non-hospitalized infections after 7 days after the commencement of the infection was determined to be 11 and 34 percent of the entire population, respectively. The Next-Generation Matrix approach was used to calculate the Basic Reproduction Numbers (R0). The SQEIRP model's R0 was 3.78, indicating that one infected individual can result in approximately three additional infections. The results of this SQEIRP model provide a preliminary guide to identifying trends in population dynamics in each class.

Development and implementation of a sustainable COVID-19 training package for healthcare workers: Experience from a teaching hospital of North India.

Background: With the impending threat of future COVID-19 waves, it is imperative that teaching hospitals develop, implement, and evaluate a systematic training program to render HCW elastic in delivering COVID-19 related services. We present our experience in developing, implementing, and evaluating a sustainable and scalable COVID-19 patient management training package for healthcare workers. Materials and Methods: A mixed-methods study design was used. Rapid assessment to understand the need of the trainees and identify the available resources was done followed by planning of the training module and its implementation. The program was evaluated for effectiveness and sustainability. Data analysis was done using descriptive statistics and qualitative data generated from open-ended questions in the feedback forms and the discussions were analyzed using rapid content analysis. Results: A total of 66.8% of the doctors and 18.9% of the nurses were trained by online synchronous mode while 55.0% of the nursing officers and 47.1% of the nursing orderlies and paramedical staff were trained in onsite skill development sessions. Need assessment identified that healthcare workers were ill-prepared to use medical devices such as Bipap machines, ventilators, and oxygen delivery devices. The participants mentioned that the multidisciplinary approach and video-based demonstrations facilitated their online learning while the incremental learning approach, easy-to-understand terminology and hands-on experience facilitated their onsite skill development sessions. Conclusion: The COVID-19 training package developed was multidisciplinary, effective, sustainable, and scalable in a resource-limited setting. We suggest that this model can be adapted by healthcare organizations to develop and implement such training packages for their healthcare workers.

Effect of convalescent plasma therapy on mortality in moderate-to-severely Ill COVID-19 patients.

INTRODUCTION: The role of plasma therapy in the management of the COVID-19, pandemic has been speculated. However, in view of the varied response regarding its effectiveness from various multicenter studies, there is a need to conduct more single center population-specific studies. We, thus, aimed to assess the role of convalescent plasma therapy in COVID-19 patient management in a single -center. METHODS: This retrospective study was conducted using records of all COVID-19 patients who received plasma therapy over a period of 6 months in a dedicated COVID-19 hospital in Delhi. Information pertaining to transfusion, disease severity, associated comorbidities, the treatment given and patient outcome were recorded. Data was analyzed using SPSSv23. RESULTS: Of the141 patients who received plasma therapy, 62% were discharged after treatment. Mortality was found to be significantly higher in patients > 60 years of age (p < 0.001), those with severe COVID-19 infection (p < 0.05) and pre-existing renal disease (p < 0.05). The admission-transfusion interval was significantly correlated to mortality and was a sensitive parameter for predicting outcome at cut off value of < 5 days (p < 0.001). There was no significant association of mortality with patient blood group, plasma antibody levels or donor hemoglobin levels. CONCLUSIONS: We report improvement and recovery in a large number of patients who received convalescent plasma within the first 5 days of hospitalization with moderate to severe disease. Further research to compare dosage and administration protocols to delineate role of CCP in survival of COVID-19 patients is needed before it is prematurely shelved.

Exploring Educational Planning, Teacher Beliefs, and Teacher Practices During the Pandemic: A Study of Science and Technology-Based Universities in China.

With the spread of the COVID-19 pandemic worldwide, university teachers are coping with and adjusting to online teaching platforms. In this concurrent mixed-methods study, 10 science and technology universities as the research sites were first chosen, and educational planning in these sites during the pandemic was examined; then, eight selected teacher participants in these sites were interviewed to report how their beliefs and practices changed during the pandemic echoing the examined educational planning. The results show that educational planning and policies assisted teachers in accommodating the new demands and changes during the pandemic; teachers' beliefs and practices generally echoed the educational planning and policies, with certain tensions still existing. The discussion part of the study is centered around emergency remote teaching and planning, tensions between teacher beliefs and practices, and the shift from emergency remote teaching to regular, sustainable online schooling. The study provides administrators and teacher educators with insights on how emergency remote teaching can be planned and implemented during an unprecedented time.

Modeling and analysis of a fractional anthroponotic cutaneous leishmania model with Atangana-Baleanu derivative.

Very recently, Atangana and Baleanu defined a novel arbitrary order derivative having a kernel of non-locality and non-singularity, known as AB derivative. We analyze a non-integer order Anthroponotic Leshmania Cutaneous (ACL) problem exploiting this novel AB derivative. We derive equilibria of the model and compute its threshold quantity, i.e. the so-called reproduction number. Conditions for the local stability of the no-disease as well as the disease endemic states are derived in terms of the threshold quantity. The qualitative analysis for solution of the proposed problem have derived with the aid of the theory of fixed point. We use the predictor corrector numerical approach to solve the proposed fractional order model for approximate solution. We also provide, the numerical simulations for each of the compartment of considered model at different fractional orders along with comparison with integer order to elaborate the importance of modern derivative. The fractional investigation shows that the non-integer order derivative is more realistic about the inner dynamics of the Leishmania model lying between integer order.

Extinction and stationary distribution of a stochastic COVID-19 epidemic model with time-delay.

We reformulate a stochastic epidemic model consisting of four human classes. We show that there exists a unique positive solution to the proposed model. The stochastic basic reproduction number R0s is established. A stationary distribution (SD) under several conditions is obtained by incorporating stochastic Lyapunov function. The extinction for the proposed disease model is obtained by using the local martingale theorem. The first order stochastic Runge-Kutta method is taken into account to depict the numerical simulations.

Fractional dynamics and stability analysis of COVID-19 pandemic model under the harmonic mean type incidence rate.

In this research, COVID-19 model is formulated by incorporating harmonic mean type incidence rate which is more realistic in average speed. Basic reproduction number, equilibrium points, and stability of the proposed model is established under certain conditions. Runge-Kutta fourth order approximation is used to solve the deterministic model. The model is then fractionalized by using Caputo-Fabrizio derivative and the existence and uniqueness of the solution are proved by using Banach and Leray-Schauder alternative type theorems. For the fractional numerical simulations, we use the Adam-Moulton scheme. Sensitivity analysis of the proposed deterministic model is studied to identify those parameters which are highly influential on basic reproduction number.

Hybrid Method for Simulation of a Fractional COVID-19 Model with Real Case Application

In this research, we provide a mathematical analysis for the novel coronavirus responsible for COVID-19, which continues to be a big source of threat for humanity. Our fractional-order analysis is carried out using a non-singular kernel type operator known as the Atangana-Baleanu-Caputo (ABC) derivative. We parametrize the model adopting available information of the disease from Pakistan in the period 9 April to 2 June 2020. We obtain the required solution with the help of a hybrid method, which is a combination of the decomposition method and the Laplace transform. Furthermore, a sensitivity analysis is carried out to evaluate the parameters that are more sensitive to the basic reproduction number of the model. Our results are compared with the real data of Pakistan and numerical plots are presented at various fractional orders.

Stochastic COVID-19 SEIQ epidemic model with time-delay.

In this work, we consider an epidemic model for corona-virus (COVID-19) with random perturbations as well as time delay, composed of four different classes of susceptible population, the exposed population, the infectious population and the quarantine population. We investigate the proposed problem for the derivation of at least one and unique solution in the positive feasible region of non-local solution. For one stationary ergodic distribution, the necessary result of existence is developed by applying the Lyapunov function in the sense of delay-stochastic approach and the condition for the extinction of the disease is also established. Our obtained results show that the effect of Brownian motion and noise terms on the transmission of the epidemic is very high. If the noise is large the infection may decrease or vanish. For validation of our obtained scheme, the results for all the classes of the problem have been numerically simulated.

Use of Multiple Low Cost Carbon Dioxide Sensors to Measure Exhaled Breath Distribution with Face Mask Type and Wearing Behaviour.

The use of cloth face coverings and face masks has become widespread in light of the COVID-19 pandemic. This paper presents a method of using low cost wirelessly connected carbon dioxide (CO2) sensors to measure the effects of properly and improperly worn face masks on the concentration distribution of exhaled breath around the face. Four types of face masks are used in two indoor environment scenarios. CO2 as a proxy for exhaled breath is being measured with the Sensirion SCD30 CO2 sensor, and data are being transferred wirelessly to a base station. The exhaled CO2 is measured in four directions at various distances from the head of the subject, and interpolated to create spatial heat maps of CO2 concentration. Statistical analysis using the Friedman's analysis of variance (ANOVA) test is carried out to determine the validity of the null hypotheses (i.e., distribution of the CO2 is same) between different experiment conditions. Results suggest CO2 concentrations vary little with the type of mask used; however, improper use of the face mask results in statistically different CO2 spatial distribution of concentration. The use of low cost sensors with a visual interpolation tool could provide an effective method of demonstrating the importance of proper mask wearing to the public.

Fractional optimal control of COVID-19 pandemic model with generalized Mittag-Leffler function.

In this paper, we consider a fractional COVID-19 epidemic model with a convex incidence rate. The Atangana-Baleanu fractional operator in the Caputo sense is taken into account. We establish the equilibrium points, basic reproduction number, and local stability at both the equilibrium points. The existence and uniqueness of the solution are proved by using Banach and Leray-Schauder alternative type theorems. For the fractional numerical simulations, we use the Toufik-Atangana scheme. Optimal control analysis is carried out to minimize the infection and maximize the susceptible people.

A review of resource management and self-reliance for sustainable development of India under COVID-19 scenario.

The rapid spread of COVID-19 pandemic has caused a severe disorder in the global economy. The sudden imposition of lockdown is expected to largely impact the global as well as Indian economy. To overcome serious economic fallouts, the honorable Prime Minister of India, Sri Narendra Modi in his address to the nation called for "Atmanirbhar Bharat Abhiyan" or "Self-reliant India" as self-reliance would help in making pragmatic developments of the economy. According to WHO, COVID-19 is a new strain found among humans that are caused by SARS-CoV-2, mainly a respiratory tract infection. As a consequence, the COVID-19 pandemic gives India a unique situation to face this period of crisis boldly for optimum utilization of the available resources, and shift towards a more resilient and sustainable economy. Attainment of self-reliance and sustainable resource management will also help the nation to overcome various global challenges. The present study mainly focuses on two objectives: Firstly, to understand the different possibilities which will secure India to become self-reliant; and secondly, to know the prospects of self-reliant of India in the post-COVID-19 scenario. It has to be kept in mind that Covid-19 may not be the last viral infection that the world might see. Therefore, Novel Coronavirus sets a distinctive chance for India and the countries alike to utilize the available resources strategically and transform its dreams of "local" India into "Glocal" India for a better and brighter future of her people.

Rapid transition to online teaching program during COVID-19 lockdown: Experience from a medical college of India.

BACKGROUND: COVID-19 pandemic has forced medical colleges around the world to shift to online teaching. There is hardly any evidence regarding such rapid transitions to online teaching, especially from resource-poor settings. We share our experience of developing an online teaching program based on teachers' and students' feedback. MATERIALS AND METHODS: A mixed methods study was conducted during the COVID-19 lockdown period in a public-funded medical institute of India. Online feedback was obtained 3 weeks after the beginning of emergency remote teaching. The responses by the students and teachers shaped the final online teaching program which reinforced the perceived strengths and addressed the weaknesses. Observations were made for the proportion of scheduled lectures delivered through digital platform and students' attendance in the 1st week and last week of the study period. RESULTS: Feedback was obtained from 367 students and 56 teachers. Around three-fourths of the students (76.7%) and teachers (73.2%) were satisfied with online teaching. The themes generated for benefits of online teaching were similar for both students and teachers, but the perceived challenges differed. Students found online teaching more stressful, and teachers were apprehensive of the new technology and lack of a controlled environment. CONCLUSIONS: A rapid transition to development and implementation of an online teaching program was found to be feasible and acceptable to the primary stakeholders. Not only the content but student engagement and supportive environment for both students and teachers are essential requirements in the context of an online undergraduate teaching program.

Covid-19 Pandemic: Resumption of Orthopedic Care and Medical Education.

Covid-19 is a respiratory disease caused by coronavirus 2 (SARS-CoV-2) first identified in Wuhan, China (December 2019). The disease rapidly crossed the barrier of countries, continents and spread globally. Non-pharmaceutical measures such as social distancing, face mask, frequent hand washing and use of sanitizer remained the best available option to prevent the spread of disease. OPD, IPD admissions, elective O. Ts were curtailed. Orthopedic care was only limited to emergency and semi-urgent procedures like necrotizing fasciitis, open fracture, and compartment syndrome. These measures were taken to preserve infrastructure and manpower to manage covid-19 pandemic. The children were thought to have a low susceptibility to covid-19 as compared to an adult. Deferring the patient during pandemic has led to high orthopedic disease burden, morbidity and disease-related sequelae, hence elective care must be resumed with modified hospital infrastructure. Resumption of elective/emergent orthopedic care should be slow, phasic and strategic, much similar to unlocking. Cases must be stratified depending on covid status and severity. Dedicated O.Ts with neutral/negative pressure and HEPA filter for covid positive and suspected patients are to be used. All symptomatic and suspected patients should be investigated for covid-19 by RT-PCR, blood counts and CT scan. Regional anaesthesia should be preferred to General anaesthesia. Power drill/saw/burr/pulse lavage should be minimized to avoid aerosol generation. Postoperatively continuous surveillance and monitoring to be done for covid related symptoms. Medical institutes rapidly shifted to the online mode of education. Blended learning (virtual & physical) and imparting skills have to be continued in post covid phase with equitable distribution of teaching hours to students of different years.