Mathematical modelling and analysis of COVID-19 and tuberculosis transmission dynamics.

In this paper, a mathematical model for assessing the impact of COVID-19 on tuberculosis disease is proposed and analysed. There are pieces of evidence that patients with Tuberculosis (TB) have more chances of developing the SARS-CoV-2 infection. The mathematical model is qualitatively and quantitatively analysed by using the theory of stability analysis. The dynamic system shows endemic equilibrium point which is stable when R 0 < 1 and unstable when R 0 > 1 . The global stability of the endemic point is analysed by constructing the Lyapunov function. The dynamic stability also exhibits bifurcation behaviour. The optimal control theory is used to find an optimal solution to the problem in the mathematical model. The sensitivity analysis is performed to clarify the effective parameters which affect the reproduction number the most. Numerical simulation is carried out to assess the effect of various biological parameters in the dynamic of both tuberculosis and COVID-19 classes. Our simulation results show that the COVID-19 and TB infections can be mitigated by controlling the transmission rate γ .

Mathematical modelling and analysis of COVID-19 and tuberculosis transmission dynamics

In this paper, a mathematical model for assessing the impact of COVID-19 on tuberculosis disease is proposed and analysed. There are pieces of evidence that patients with Tuberculosis (TB) have more chances of developing the SARS-CoV-2 infection. The mathematical model is qualitatively and quantitatively analysed by using the theory of stability analysis. The dynamic system shows endemic equilibrium point which is stable when

Adverse effects after first and second dose of covishield and covaxin: A longitudinal study.

Background: COVID-19 vaccines have been rolled out recently in several parts of the world. Although the protective efficacy is frequently discussed, little is known about the factors associated with COVID-19 vaccine adverse effects. The study was conducted with the aim to evaluate the occurrence of adverse events following immunization (AEFI) with two doses of covishield and covaxin and to assess factors associated with these adverse effects. Methods: A longitudinal study was conducted for a period of three months in the adults above 18 years of age attending rural health training center (RHTC) either to receive their first or second dose of covishield or covaxin. After vaccination, the participants were observed at the health facility for 30 min for any AEFI and also followed up telephonically on seventh day from vaccination. Data was collected on predesigned and pretested questionnaire and appropriate statistical tests were applied. Results: Out of 532 participants, 250 (47%) came for their first dose while 282 (53%) came for second dose. In both the groups maximum participation was seen by males and those belonging to age group 18-30 years. Majority of the participants reported local tenderness (39.3%) after first dose of covaxin and fever (30.5%) after first dose of covishield. Mainly significant association was observed after vaccination in participants with comorbidities. Conclusion: The short-term adverse events with both the vaccines were observed, but these were mild and short lived. In this context, our study becomes more relevant in disseminating short-term safety data post vaccination. This will help individuals in their decision to accept vaccination.

Nitrogen dioxide as proxy indicator of air pollution from fossil fuel burning in New Delhi during lockdown phases of COVID-19 pandemic period: impact on weather as revealed by Sentinel-5 precursor (5p) spectrometer sensor.

There has been a long-lasting impact of the lockdown imposed due to COVID-19 on several fronts. One such front is climate which has seen several implications. The consequences of climate change owing to this lockdown need to be explored taking into consideration various climatic indicators. Further impact on a local and global level would help the policymakers in drafting effective rules for handling challenges of climate change. For in-depth understanding, a temporal study is being conducted in a phased manner in the New Delhi region taking NO2 concentration and utilizing statistical methods to elaborate the quality of air during the lockdown and compared with a pre-lockdown period. In situ mean values of the NO2 concentration were taken for four different dates, viz. 4th February, 4th March, 4th April, and 25th April 2020. These concentrations were then compared with the Sentinel (5p) data across 36 locations in New Delhi which are found to be promising. The results indicated that the air quality has been improved maximum in Eastern Delhi and the NO2 concentrations were reduced by one-fourth than the pre-lockdown period, and thus, reduced activities due to lockdown have had a significant impact. The result also indicates the preciseness of Sentinel (5p) for NO2 concentrations.

The Effectiveness of SARS-CoV-2 Vaccination in Preventing Severe Illness and Death - Real-world Data from a Cohort of Patients Hospitalized with COVID-19.

Background: While long-term studies on the correlates of protection, vaccine effectiveness, and enhanced surveillance are awaited for SARS-CoV-2 vaccine, studies on breakthrough infections help understand the nature and course of this illness among vaccinated individuals and guide in public health preparedness. This study aims to compare the differences in the hospitalization outcomes SARS-CoV-2 infection of fully vaccinated individuals with with those of unvaccinated and partially vaccinated individuals. Materials and Methods: Single institution observational cohort study. This study compared the differences in clinical, biochemical parameters and the hospitalization outcomes of 53 fully vaccinated individuals with those of unvaccinated (1464) and partially vaccinated (231) individuals, among a cohort of 2,080 individuals hospitalized with SARS-CoV-2 infection. Descriptive statistics and propensity-score weighted multivariate logistic regression analysis adjusting for clinical and laboratory parameters were used to compare the differences and to identify factors associated with outcomes. Results: Completing the course of vaccination protected individuals from developing severe COVID-19 as evidenced by lower proportions of those with hypoxia, abnormal levels of inflammatory markers, requiring ventilatory support, and death compared to unvaccinated and partially vaccinated individuals. There were no differences in these outcomes among patients who received either vaccine type approved in India. Conclusions: Efforts should be made to improve the vaccination rates as a timely measure to prepare for the upcoming waves of this highly transmissible pandemic. Vaccination rates of the communities may also guide in the planning of the health needs and appropriate use of medical resources.

Impact of quarantine on fractional order dynamical model of Covid-19.

In this paper, a Covid-19 dynamical transmission model of a coupled non-linear fractional differential equation in the Atangana-Baleanu Caputo sense is proposed. The basic dynamical transmission features of the proposed system are briefly discussed. The qualitative as well as quantitative results on the existence and uniqueness of the solutions are evaluated through the fixed point theorem. The Ulam-Hyers stability analysis of the suggested system is established. The two-step Adams-Bashforth-Moulton (ABM) numerical method is employed to find its numerical solution. The numerical simulation is performed to accesses the impact of various biological parameters on the dynamics of Covid-19 disease.

ROX index: A non-invasive tool in monitoring and guiding oxygen therapy in a critically ill patients-A narrative review

The use of the high-flow nasal cannula (HFNC) for oxygen therapy in patients with acute hypoxemic respiratory failure has increased dramatically in recent years, owing to the numerous advantages it has over the other modalities. The respiratory rate-oxygenation (ROX) index was created as a monitoring tool for the appropriate use of the HFNC. It is gaining popularity as a critical monitoring tool due to its non-invasive nature and the ability to be performed at the bedside. To write this review we searched for the original peer-reviewed journal articles using search engines such as Cochrane Library, Google Scholar, and PubMed for evidence of the utility of this index in clinical practice. Despite having many advantages as well as limitations, the ROX index has been shown to have a moderate but useful predictive value/capacity and diagnostic accuracy in detecting HFNC-assisted oxygen therapy failure or success. Further high-quality prospective studies and trials might bring more clarity regarding performance under variable flow rates of HFNC, the acquisition time intervals, cut-off value/limit, and standardization of the index. The ROX index being a non-invasive, simple, and bedside tool could prove a very promising tool to assess the effectiveness, progress and outcome of the HFNC therapy.

Effect of Indoor Bioaerosols (Fungal) Exposure on the Health of Post-COVID-19 Patients and Possible Mitigation Strategies

Bioaerosols are present everywhere around us, either on surfaces or in the air. Depending on their nature, these bioaerosols have positive or negative impacts on our bodies. Our immune system always creates a balance in our health system in response to these bioaerosols. If our body's immune system is compromised for a while, it could have many severe health complications. A good example is in patients who recovered from COVID-19 during the COVID-19 pandemic. During treatment, many drugs like dexamethasone, tocilizumob, itolizumab, and steroids were extensively used that suppressed the immune system, resulting in many fungal infections. In this review, we summarise the various studies carried out throughout the globe regarding fungal infection, including Mucormycetes (black fungus), Candida spp., Aspergillus fumigatus, and pneumocystis jirovecii. The patient disease history and treatment details were also examined so as to develop the risk of mortality. Populations with other pre-existing diseases such as diabetes and asthma are more vulnerable to infection. These infections spread at a very high rate and have a high risk of mortality in patients who have recovered from COVID-19. Earnest attention is needed regarding the treatment procedure of COVID-19 patients and for the follow-up of recovered patients. Here, we suggest some treatment methods that will help prevent infection in patients who have recovered from COVID-19 or in immunosuppressed bodies. [ FROM AUTHOR] Copyright of COVID is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

A Correlation Analysis of Peripheral Oxygen Saturation and Arterial Oxygen Saturation Among COVID-19 Patients.

Background and objective It has been observed that peripheral oxygen saturation (SpO2) measured by pulse oximeter is consistently lower than arterial oxygen saturation (SaO2) measured directly by blood gas analysis. In this study, we aimed to evaluate the correlation between SpO2 and SaO2, and SpO2 and partial pressure of oxygen (PaO2), and compare the SpO2/FiO2 (SF) and PaO2/FiO2 (PF) ratios in patients with coronavirus disease 2019 (COVID-19). Methods In this observational study, SpO2 was recorded and arterial blood gas analysis was performed among 70 COVID-19 patients presenting on room air (FiO2 = 0.21). SaO2 and PaO2 were recorded from arterial blood gas analysis. The SF and PF ratios were then calculated. Results The strength of correlations between SpO2 and SaO2, and SpO2 and PaO2, were significant (p<0.001) and moderately positive [Pearson coefficient (r) = 0.68, 0.53]. SpO2 value (85%), i.e., SF ratio (404.7 or below), was the best estimate for mild ARDS (acute respiratory distress syndrome) [PF ratio (300 or below)] with a sensitivity of 80.6% and specificity of 53%. Conclusion A pulse oximeter is a vital tool in the diagnosis and management of COVID-19. In our study, SpO2 was found to have a positive correlation with SaO2 and PaO2 with acceptable sensitivity but low specificity in estimating mild ARDS. Therefore, pulse oximetry can be used as a tool for the early diagnosis of mild COVID-19 ARDS as per the given considerations and clinical correlation.

Preface

This comprises investigations on novel theoretical and experimental research on the synthesis, properties, and characterization of polymers, as well as studies on existing theoretical and experimental research. This conference was the result of prior encounters with similar forums in which scientists, scholars and engineers were encouraged to share their perspectives through discussions. The development of science and technology makes the people of the world able to live better by enjoying various facilities resulting from the discoveries and inventions of scientists. [Extracted from the article] Copyright of High Performance Polymers is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Airway management, procedural data, and in-hospital mortality records of patients undergoing surgery for mucormycosis associated with coronavirus disease (COVID-19).

PURPOSE: Although unexpected airway difficulties are reported in patients with mucormycosis, the literature on airway management in patients with mucormycosis associated with Coronavirus disease is sparse. METHODS: In this retrospective case record review of 57 patients who underwent surgery for mucormycosis associated with coronavirus disease, we aimed to evaluate the demographics, airway management, procedural data, and in-hospital mortality records. RESULTS: Forty-one (71.9%) patients had a diagnosis of sino-nasal mucormycosis, fourteen (24.6%) patients had a diagnosis of rhino-orbital mucormycosis, and 2 (3.5%) patients had a diagnosis of palatal mucormycosis. A total of 44 (77.2%) patients had co-morbidities. The most common co-morbidities were diabetes mellitus in 42 (73.6%) patients, followed by hypertension in 21 (36.8%) patients, and acute kidney injury in 14 (28.1%) patients. We used the intubation difficulty scale score to assess intubating conditions. Intubation was easy to slightly difficult in 53 (92.9%) patients. In our study, mortality occurred in 7 (12.3%) patients. The median (range) mortality time was 60 (27-74) days. The median (range) time to hospital discharge was 53.5 (10-85) days. The median [interquartile range] age of discharged versus expired patients was 47.5 [41,57.5] versus 64 [47,70] years (P = 0.04), and median (interquartile range) D-dimer levels in discharged versus expired patients was 364 [213, 638] versus 2448 [408,3301] ng/mL (P = 0.03). CONCLUSION: In patients undergoing surgery for mucormycosis associated with the coronavirus disease, airway management was easy to slightly difficult in most patients. Perioperative complications can be minimized by taking timely and precautionary measures.

COVID-19 pandemic: A pragmatic plan for ayurveda intervention.

World community is facing an unprecedented pandemic of novel corona virus disease (COVID-19) caused by Severe Acute Respiratory Syndrome Corona virus 2 (SARS-CoV- 2). The disease has spread globally with more than 1.43 million confirmed cases and 82,100 deaths as of April 8, 2020. Despite worldwide efforts to contain it, the pandemic is continuing to spread for want of a clinically-proven prophylaxis and therapeutic strategy. The dimensions of pandemic require an urgent harnessing of all knowledge systems available globally. Utilization of Traditional Chinese Medicine in Wuhan to treat COVID-19 cases sets the example demonstrating that traditional health care can contribute to treatment of these patients successfully. Drawing on the Ayurveda classics, contemporary scientific studies, and experiential knowledge on similar clinical settings, here we propose a pragmatic plan for intervention in India. We provide a plan for graded response, depending on the stage of infection among individuals, in a population. Notwithstanding the fact that no system of medicine has any evidence-based treatment for COVID-19 as yet, clinical interventions are required to be put in place. Therefore, pragmatic strategy proposed here for Ayurveda system of medicine requires immediate implementation. It will facilitate learning, generate evidence and shall be a way forward.

Silent Hypoxia in Coronavirus disease-2019: Is it more dangerous? -A retrospective cohort study.

Background: Hypoxia in patients with COVID-19 is one of the strongest predictors of mortality. Silent hypoxia is characterised by the presence of hypoxia without dyspnoea. Silent hypoxia has been shown to affect the outcome in previous studies. Methods: This was a retrospective study of a cohort of patients with SARS-CoV-2 infection who were hypoxic at presentation. Clinical, laboratory and treatment parameters in patients with silent hypoxia and dyspnoeic hypoxia were compared. Multivariate logistic regression models were fitted to identify the factors predicting mortality. Results: Among 2080 patients with COVID-19 admitted to our hospital, 811 patients were hypoxic with SpO2 <94% at the time of presentation. Among them, 174 (21.45%) did not have dyspnoea since the onset of COVID-19 symptoms. Further, 5.2% of patients were completely asymptomatic for COVID-19 and were found to be hypoxic only on pulse oximetry. The case fatality rate in patients with silent hypoxia was 45.4% as compared to 40.03% in dyspnoeic hypoxic patients (P = 0.202). The odds ratio of death was 1.1 (95% CI: 0.41-2.97) in the patients with silent hypoxia after adjusting for baseline characteristics, laboratory parameters, treatment and in-hospital complications, which did not reach statistical significance (P = 0.851). Conclusion: Silent hypoxia may be the only presenting feature of COVID-19. As the case fatality rate is comparable between silent and dyspnoeic hypoxia, it should be recognised early and treated as aggressively. Because home isolation is recommended in patients with COVID-19, it is essential to use pulse oximetry in the home setting to identify these patients.

Comparison between C-MAC and King Vision video laryngoscope (channelled blade) for tracheal intubation in aerosol-prevention intubation box for COVID-19 patients: A manikin-based study.

Background and Aims: The risk of contracting infection while intubating a coronavirus disease 2019 (COVID-19)-positive patient can be reduced by the use of personal protective equipment (PPE), video laryngoscope (VL) and aerosol-preventing intubation box. We compared two VLs (C-MAC and King Vision laryngoscope [KVL]) for ease of intubation and time taken to intubate the manikin using an intubation box. Methods: This randomised study involved healthcare workers having experience in using both C-MAC and KVL. After explaining the study and five practice sessions, a total of 63 volunteers were included; 61 participants gave consent and were enroled. The participants were allowed to intubate initially with one VL as per random sequence. Each participant performed three tracheal intubations with each device (C-MAC VL and KVL) on a manikin using an aerosol-prevention box over the head end at the time of intubation. Results: Time taken, percentage of glottic opening (POGO) score and the number of attempts taken for successful intubation with C-MAC and KVL were comparable in any of the three attempts (P > 0.05). The participants reported more difficulty in using KVL compared to C-MAC, and insertion of laryngoscope blade into the mouth of manikin for intubation was easy in group C-MAC compared to KVL in all three intubations (P < 0.01). Conclusion: C-MAC and KVL take comparable time for successful intubation under COVID-19 simulation conditions. But C-MAC is more user-friendly.

Clinical features, demography, and predictors of outcomes of SARS-CoV-2 infection at a tertiary care hospital in India: A cohort study.

BACKGROUND: The "second wave" of the COVID-19 pandemic hit India from early April 2021 to June 2021. We describe the clinical features, treatment trends, and baseline laboratory parameters of a cohort of patients with SARS-CoV-2 infection and their association with the outcome. METHODS: This was a retrospective cohort study. Multivariate logistic regression models were fitted to identify clinical and biochemical predictors of developing hypoxia, deterioration during the hospital stay, and death. RESULTS: A total of 2080 patients were included. The case fatality rate was 19.5%. Among the survivors, the median duration of hospital stay was 8 (5-11) days. Out of 853 (42.3%%) of patients who had COVID-19 acute respiratory distress syndrome at presentation, 340 (39.9%) died. Patients aged >45 years had higher odds of death as compared to the 18-44 years age group. Vaccination reduced the odds of death by 40% (odds ratio [OR] [95% confidence interval [CI]]: 0.6 [0.4-0.9], P = 0.032). Patients with hyper inflammation at baseline as suggested by leukocytosis (OR [95% CI]: 2.1 [1.5-3.1], P < 0.001), raised d-dimer >500 mg/dL (OR [95% CI]: 3.2 [2.2-4.7], P < 0.001), and raised C-reactive peptide >0.5 mg/L (OR [95% CI]: 3.7 [2.2-13], P = 0.037) had higher odds of death. Patients who were admitted in the 2nd week had lower odds and those admitted in the 3rd week had higher odds of death. CONCLUSION: This study shows that vaccination status and early admission during the inflammatory phase can change the course of illness of these patients. Improving vaccination rates and early admission of patients with moderate and severe COVID-19 can improve the outcomes.

Self-limiting severe neutropenia in a patient with COVID-19.

Neutropenia is a rare haematological complication of COVID-19 infection in immunocompetent patients. There is sparse literature on neutropenia in patients with COVID-19, except a few case reports. We encountered a similar case in an intensive care unit that developed severe neutropenia on day 24 of illness. Neutropenia resolved spontaneously on 4th day of its appearance. The patient was isolated and kept under close observation, antibiotics were upgraded and strict asepsis was maintained. Thus, we observed in a patient with no comorbidities and uncomplicated neutropenia that strict measures to prevent infection may suffice and the undue risk of hematopoietic therapy can be avoided. An expert opinion should always be sought in such cases as the presence of complications may require an aggressive approach.

Short-Term Statistical Forecasts of COVID-19 Infections in India.

COVID-19 cases in India have been steadily increasing since January 30, 2020 and have led to a government-imposed lockdown across the country to curtail community transmission with significant impacts on societal systems. Forecasts using mathematical-epidemiological models have played and continue to play an important role in assessing the probability of COVID-19 infection under specific conditions and are urgently needed to prepare health systems for coping with this pandemic. In many instances, however, access to dedicated and updated information, in particular at regional administrative levels, is surprisingly scarce considering its evident importance and provides a hindrance for the implementation of sustainable coping strategies. Here we demonstrate the performance of an easily transferable statistical model based on the classic Holt-Winters method as means of providing COVID-19 forecasts for India at different administrative levels. Based on daily time series of accumulated infections, active infections and deaths, we use our statistical model to provide 48-days forecasts (28 September to 15 November 2020) of these quantities in India, assuming little or no change in national coping strategies. Using these results alongside a complementary SIR model, we find that one-third of the Indian population could eventually be infected by COVID-19, and that a complete recovery from COVID-19 will happen only after an estimated 450 days from January 2020. Further, our SIR model suggests that the pandemic is likely to peak in India during the first week of November 2020.

Modeling factors affecting online learning adoption: mediating role of attitude

PurposeThe study aims to model the factors influencing online learning adoption by Indian students as well as examine the mediating effect of attitude on the proposed relationships.Design/methodology/approachA survey was conducted online using a well-structured questionnaire. The target respondents of the study were students of undergraduate and postgraduate courses in India. Structural equation modeling was employed on a final sample of 402 respondents to test the proposed hypotheses.FindingsThe results reveal that there is a significant impact of the perceived usefulness, perceived ease of use, social influence, peer influence and self-esteem on attitude toward online learning. Further, attitude significantly mediates the impact of these factors on intention to adopt online learning.Originality/valueThe study is one of the initial attempts in the backdrop of the pandemic to examine the mediating role of attitude in affecting intention to adopt online learning by university students in India.

Molecular hydrogen as an adjuvant therapy may be associated with increased oxygen saturation and improved exercise tolerance in a COVID-19 patient.

Administration of molecular hydrogen dissolved in water to patient with COVID-19-like symptoms may improve oxygen levels and exercise capacity.

Model-based ensembles: Lessons learned from retrospective analysis of COVID-19 infection forecasts across 10 countries.

Mathematical models of different types and data intensities are highly used by researchers, epidemiologists, and national authorities to explore the inherently unpredictable progression of COVID-19, including the effects of different non-pharmaceutical interventions. Regardless of model complexity, forecasts of future COVID-19 infections, deaths and hospitalization are associated with large uncertainties, and critically depend on the quality of the training data, and in particular how well the recorded national or regional numbers of infections, deaths and recoveries reflect the the actual situation. In turn, this depends on, e.g., local test and abatement strategies, treatment capacities and available technologies. Other influencing factors including temperature and humidity, which are suggested by several authors to affect the spread of COVID-19 in some countries, are generally only considered by the most complex models and further serve to inflate the uncertainty. Here we use comparative and retrospective analyses to illuminate the aggregated effect of these systematic biases on ensemble-based model forecasts. We compare the actual progression of active infections across ten of the most affected countries in the world until late November 2020 with "re-forecasts" produced by two of the most commonly used model types: (i) a compartment-type, susceptible-infected-removed (SIR) model; and (ii) a statistical (Holt-Winters) time series model. We specifically examine the sensitivity of the model parameters, estimated systematically from different subsets of the data and thereby different time windows, to illustrate the associated implications for short- to medium-term forecasting and for probabilistic projections based on (single) model ensembles as inspired by, e.g., weather forecasting and climate research. Our findings portray considerable variations in forecasting skill in between the ten countries and demonstrate that individual model predictions are highly sensitive to parameter assumptions. Significant skill is generally only confirmed for short-term forecasts (up to a few weeks) with some variation across locations and periods.