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Background: The forecasting of Coronavirus Disease-19 (COVID-19) dynamics is a centrepiece in evidence-based disease management. Numerous approaches that use mathematical modelling have been used to predict the outcome of the pandemic, including data-driven models, empirical and hybrid models. This study was aimed at prediction of COVID-19 evolution in India using a model based on autoregressive integrated moving average (ARIMA). Material and Methods: Real-time Indian data of cumulative cases and deaths of COVID-19 was retrieved from the Johns Hopkins dashboard. The dataset from 11 March 2020 to 25 June 2020 (n = 107 time points) was used to fit the autoregressive integrated moving average model. The model with minimum Akaike Information Criteria was used for forecasting. The predicted root mean square error (PredRMSE) and base root mean square error (BaseRMSE) were used to validate the model. Results: The ARIMA (1,3,2) and ARIMA (3,3,1) model fit best for cumulative cases and deaths, respectively, with minimum Akaike Information Criteria. The prediction of cumulative cases and deaths for next 10 days from 26 June 2020 to 5 July 2020 showed a trend toward continuous increment. The PredRMSE and BaseRMSE of ARIMA (1,3,2) model were 21,137 and 166,330, respectively. Similarly, PredRMSE and BaseRMSE of ARIMA (3,3,1) model were 668.7 and 5,431, respectively. Conclusion: It is proposed that data on COVID-19 be collected continuously, and that forecasting continue in real time. The COVID-19 forecast assist government in resource optimisation and evidence-based decision making for a subsequent state of affairs.

Intro duction: Awake fiberoptic bronchoscope-guided intubation is the preferred airway management strategy in a patient with a difficult airway and limited mouth opening. The aim is to compare the efficacy of nebulization and airway nerve block using lignocaine to provide airway anesthesia in awake patients using fiberoptic bronchoscope for nasal intubation to make the patient comfortable, cooperative, and agreeable. Methods: In this randomized, prospective, single-blinded study, sixty adult patients scheduled for oral cancer surgeries were divided into two equal groups. Nebulization with 4% lignocaine (10 ml) was performed in Group N, and superior bilateral laryngeal and trans-laryngeal recurrent laryngeal nerve blocks used 2% lignocaine (2 ml) were given in Group B. Nasotracheal intubation using fiberoptic bronchoscope were performed. Intravenous midazolam and fentanyl were used for sedation and analgesia. We recorded the ease of intubation, coughing episodes, vocal cord status, hemodynamic variables, patient recall, and lignocaine toxicity. Student's t-test and Chi-square tests were used for appropriate data. Statistical significance was considered for P < 0.05 (SPSS Version 20, IBM, USA). Results: The intubation time was shorter with better intubating conditions in Group B (120.3 ± 42.6 s) than Group N (200.4 ± 60.3 s) (P < 0.001). Cough severity and patient recall for untoward effects were lower in Group B. Intubation were done successfully in all patients. Conclusion: Airway nerve blocks provided better airway anesthesia characterized by easier fiberoptic intubation and patient comfort than lignocaine nebulization. Nebulization can be considered a suitable alternative when nerve blocks are not feasible due to distorted neck anatomy.

Background: Since the outbreak of coronavirus disease-19 (COVID-19) research has been continued to explore multiple facets of the disease. The objective of the present study was to evaluate the relationship between blood group phenotypes and COVID-19 susceptibility. Methods: In this retrospective observational study 132 hospitalised COVID-19 patients were enrolled from the Swai Man Singh (SMS) Medical Hospital in Jaipur, India after receiving approval from the Institutional ethics committee. The ABO, Rh and Kell blood group phenotypes along with demographic data of the patients were recorded. The observed proportions of 'A', 'B', 'AB', 'O', 'Rh' and 'Kell' blood groups in COVID-19 patients were compared against the expected proportions (the null hypothesis) of the general population using Pearson's Chi-squared test and partition analysis. Results: There were significant differences between observed and expected frequency for the ABO and Kell blood phenotypes. Further partition analysis of ABO phenotypes showed that the group 'A' phenotypes were more susceptible to COVID-19. The Kell negatives were also more susceptible. The blood groups 'AB', 'B', 'O' and 'Rh' showed no significant difference for susceptibility to COVID-19. Conclusion: The study shows a relationship between ABO, Rh and Kell blood groups and COVID-19 susceptibility. The application of these relationships in clinics should be explored in future studies.