A comprehensive analysis of the mutational landscape of the newly emerging Omicron (B.1.1.529) variant and comparison of mutations with VOCs and VOIs.

The Omicron variant is spreading rapidly throughout several countries. Thus, we comprehensively analyzed Omicron's mutational landscape and compared mutations with VOC/VOI. We analyzed SNVs throughout the genome, and AA variants (NSP and SP) in VOC/VOI, including Omicron. We generated heat maps to illustrate the AA variants with high mutation prevalence (> 75% frequency) of Omicron, which demonstrated eight mutations with > 90% prevalence in ORF1a and 29 mutations with > 75% prevalence in S-glycoprotein. A scatter plot for Omicron and VOC/VOI's cluster evaluation was computed. We performed a risk analysis of the antibody-binding risk among four mutations (L452, F490, P681, D614) and observed three mutations (L452R, F490S, D614G) destabilized antibody interactions. Our comparative study evaluated the properties of 28 emerging mutations of the S-glycoprotein of Omicron, and the ΔΔG values. Our results showed K417N with minimum and Q954H with maximum ΔΔG value. Furthermore, six important RBD mutations (G339D, S371L, N440K, G446S, T478K, Q498R) were chosen for comprehensive analysis for stabilizing/destabilizing properties and molecular flexibility. The G339D, S371L, N440K, and T478K were noted as stable mutations with 0.019 kcal/mol, 0.127 kcal/mol, 0.064 kcal/mol, and 1.009 kcal/mol. While, G446S and Q498R mutations showed destabilizing results. Simultaneously, among six RBD mutations, G339D, G446S, and Q498R mutations increased the molecular flexibility of S-glycoprotein. This study depicts the comparative mutational pattern of Omicron and other VOC/VOI, which will help researchers to design and deploy novel vaccines and therapeutic antibodies to fight against VOC/VOI, including Omicron.

Computational identification of potential inhibitory compounds in Indian medicinal and aromatic plant species against major pathogenicity determinants of SARS-CoV-2.

SARS-CoV-2 (COVID-19) viral pandemic has been reported across 223 countries and territories. Globalized vaccination programs alongside administration of repurposed drugs will assumingly confer a stronger and longer individual specific immune protection. However, considering possible recurrence of the disease via new variants, a conveniently deliverable phytopharmaceutical drug might be the best option for COVID-19 treatment. In the current study, the efforts have been made to identify potential leads for inhalation therapy as nasal swabs have been reported to transfer viral load prominently. In that direction, 2363 Essential oil (EOs) compounds from Indian medicinal and aromatic plants were screened through docking analysis and potential candidates were shortlisted that can interfere with viral pathogenicity. The main protease (Mpro) of SARS-CoV-2 interacted closely with jatamansin (JM), 6,7-dehydroferruginol (FG) and beta-sitosterol (BS), while Papain-like Protease (PLpro) with friedelane-3-one (F3O) and lantadene D (LD) independently. Reduced Lantadene A (LAR) exhibited preferable interaction with RNA-dependent-RNA-polymerase (RdRp) whereas Lantadene A (LA) with RdRp and spike-glycoprotein (SG-pro) both target proteins. When compared against highest binding affinity conformations of well-known inhibitors of targets, these prioritized compounds conferred superior or comparable SARS-CoV-2 protein inhibition. Additionally, promising results were noted from pharmacokinetics prediction for all shortlisted compounds. Besides, molecular dynamics simulation for 100 ns in two replicates and binding free energy analysis revealed the stability of complexes with optimum compactness. To the best of our knowledge, the current investigation is a unique initial attempt whereby EO compounds have been computationally screened, irrespective of their known medicinal properties to fight COVID-19 infection.Communicated by Ramaswamy H. Sarma.

Delta variant (B.1.617.2) of SARS-CoV-2: current understanding of infection, transmission, immune escape, and mutational landscape.

The Delta variant is one of the alarming variants of the SARS-CoV-2 virus that have been immensely detrimental and a significant cause of the prolonged pandemic (B.1.617.2). During the SARS-CoV-2 pandemic from December 2020 to October 2021, the Delta variant showed global dominance, and afterwards, the Omicron variant showed global dominance. Delta shows high infectivity rate which accounted for nearly 70% of the cases after December 2020. This review discusses the additional attributes that make the Delta variant so infectious and transmissible. The study also focuses on the significant mutations, namely the L452R and T478K present on the receptor-binding domain of spike (S)-glycoprotein, which confers specific alterations to the Delta variant. Considerably, we have also highlighted other notable factors such as the immune escape, infectivity and re-infectivity, vaccine escape, Ro number, S-glycoprotein stability, cleavage pattern, and its binding affinity with the host cell receptor protein. We have also emphasized clinical manifestations, symptomatology, morbidity, and mortality for the Delta variant compared with other significant SARS-CoV-2 variants. This review will help the researchers to get an elucidative view of the Delta variant to adopt some practical strategies to minimize the escalating spread of the SARS-CoV-2 Delta variant.

Integrative Bioinformatics Approaches Indicate a Particular Pattern of Some SARS-CoV-2 and Non-SARS-CoV-2 Proteins.

Pattern recognition plays a critical role in integrative bioinformatics to determine the structural patterns of proteins of viruses such as SARS-CoV-2. This study identifies the pattern of SARS-CoV-2 proteins to depict the structure-function relationships of the protein alphabets of SARS-CoV-2 and COVID-19. The assembly enumeration algorithm, Anisotropic Network Model, Gaussian Network Model, Markovian Stochastic Model, and image comparison protein-like alphabets were used. The distance score was the lowest with 22 for "I" and highest with 40 for "9". For post-processing and decision, two protein alphabets "C" (PDB ID: 6XC3) and "S" (PDB ID: 7OYG) were evaluated to understand the structural, functional, and evolutionary relationships, and we found uniqueness in the functionality of proteins. Here, models were constructed using "SARS-CoV-2 proteins" (12 numbers) and "non-SARS-CoV-2 proteins" (14 numbers) to create two words, "SARS-CoV-2" and "COVID-19". Similarly, we developed two slogans: "Vaccinate the world against COVID-19" and "Say no to SARS-CoV-2", which were made with the proteins structure. It might generate vaccine-related interest to broad reader categories. Finally, the evolutionary process appears to enhance the protein structure smoothly to provide suitable functionality shaped by natural selection.

Structural Landscape of nsp Coding Genomic Regions of SARS-CoV-2-ssRNA Genome: A Structural Genomics Approach Toward Identification of Druggable Genome, Ligand-Binding Pockets, and Structure-Based Druggability.

SARS-CoV-2 has a single-stranded RNA genome (+ssRNA), and synthesizes structural and non-structural proteins (nsps). All 16 nsp are synthesized from the ORF1a, and ORF1b regions associated with different life cycle preprocesses, including replication. The regions of ORF1a synthesizes nsp1 to 11, and ORF1b synthesizes nsp12 to 16. In this paper, we have predicted the secondary structure conformations, entropy & mountain plots, RNA secondary structure in a linear fashion, and 3D structure of nsp coding genes of the SARS-CoV-2 genome. We have also analyzed the A, T, G, C, A+T, and G+C contents, GC-profiling of these genes, showing the range of the GC content from 34.23 to 48.52%. We have observed that the GC-profile value of the nsp coding genomic regions was less (about 0.375) compared to the whole genome (about 0.38). Additionally, druggable pockets were identified from the secondary structure-guided 3D structural conformations. For secondary structure generation of all the nsp coding genes (nsp 1-16), we used a recent algorithm-based tool (deep learning-based) along with the conventional algorithms (centroid and MFE-based) to develop secondary structural conformations, and we found stem-loop, multi-branch loop, pseudoknot, and the bulge structural components, etc. The 3D model shows bound and unbound forms, branched structures, duplex structures, three-way junctions, four-way junctions, etc. Finally, we identified binding pockets of nsp coding genes which will help as a fundamental resource for future researchers to develop RNA-targeted therapeutics using the druggable genome.

The rapid emergence of multiple sublineages of Omicron (B.1.1.529) variant: Dynamic profiling via molecular phylogenetics and mutational landscape studies.

PURPOSE: The recent Omicron (B.1.1.529) variant poses a significant threat to global health. This variant has spread worldwide, and several sublineages have rapidly emerged. Study tried to analyze the microevolution of this variant. METHODS: We studied the molecular phylogenetics, divergence, geographical distributions, frequencies, risk mutations for antibody affinity, and mutational landscape for Omicron sublineages using in silico analysis and statistical models. The risk mutation of spike for nAb affinity was analyzed and illustrated by statistical plots. Finally, the mutational properties of the spike mutations and their stability were predicted and demonstrated. RESULTS: First, we studied the microevolutionary Omicron sublineages using molecular phylogenetics. Simultaneously, we revealed divergence events of the Omicron sublineages and observed the lowest minimum divergence of 51 in clade 21K and the highest maximum divergence of 90 in clade 21L. We have demonstrated cluster analyses, geographical distributions, frequencies of Omicron and its sublineages. Finally, we evaluated the mutational landscape of the Omicron sublineages. In this mutational study, we performed a genome-wide analysis of general mutations, mutations in the non-spike genome, and spike mutations of Omicron sublineages. The risk mutation of S-glycoprotein for nAb affinity has been analyzed for Omicron sublineages. Here, we found that some sublineages have all four significant highly destabilizing mutations. Such sublineages are BA.1 (G446S, E484A, T95I, and D614G), BA.2 (H655Y, Q493R, G493S, and D614G), BA.4 (N501Y, Y505H, N969K, and D614G), and BA.2.75 (Q454H, T547K, N764K, D614G and G446S). Finally, from the mutation stability prediction through ΔΔG, we observed that BA.1 and BA.4 had two destabilizing and two stabilizing mutations. Similarly, BA.2, BA.5, and BA.2.12.1 have one destabilizing and three stabilizing mutations. However, all four mutations in BA.2.75 are stabilizing mutations. CONCLUSIONS: Our molecular phylogenetic studies provided a deeper understanding of the microevolution of sublineages and the creation of Omicron. Similarly, this study might help scientists develop pan-coronavirus vaccines that consider their mutational properties.

Therapeutic Role of Neutralizing Antibody for the Treatment against SARS-CoV-2 and Its Emerging Variants: A Clinical and Pre-Clinical Perspective.

Since early 2020, the entire world has been facing a disastrous outbreak of the SARS-CoV-2 virus, with massive reporting of death and infections per day. Medical practitioners adopted certain measures such as convalescent plasma therapy, antibody treatment, and injecting vaccines to eradicate the pandemic. In this review, we have primarily focused on the neutralizing antibodies presently under pre-clinical and clinical trials, focusing on their structures, binding affinity, mechanism of neutralization, and advantages over other therapeutics. We have also enlisted all the nAbs against SARS-CoV-2 and its emerging variants in different phases of clinical trials (phase-1, phase-II, and phase-III). The efficacy of administering antibody cocktails over the normal antibodies and their efficacy for the mutant variants of the SARS-CoV-2 virus in minimizing viral virulence is discussed. The potent neutralizing antibodies have eliminated many of the common problems posed by several other therapeutics. A common mechanism of the antibodies and their relevant sources have also been listed in this review.

Impact of the 2019 Coronavirus Infectious Disease (COVID-19) pandemic on onset to door time and admissions of new onset acute ischemic stroke in a tertiary care level hospital in North India

Context: Coronavirus infectious disease (COVID-19) pandemic disrupted the already marginalized healthcare provision in resource limited countries like India. Aims: This study compared onset to door time and temporal trends of admissions to seek medical care in new onset acute ischaemic stroke during the COVID-19 period with a representative pre-COVID-19 period in rural background. Settings and Design: Prospective Cross-sectional study in a tertiary level hospital in North India. Methods and Material: Study included new onset acute ischaemic stroke admitted within first 2 weeks of symptoms onset. Subjects were divided into: Group A – Pre-COVID-19 stroke, Group B – Non-COVID-19 Stroke, and Group C - Stroke, positive for COVID-19. Detailed epidemiological, clinical profile, onset to door time and temporal trends of admissions were recorded. Statistical Analysis Used: Chi square/Fisher’s exact test and Independent Samples T test or Mann–Whitney U test were used for categorical and continuous variables. Results: Onset to door time in new onset acute ischaemic stroke was significantly prolonged by 6 h in COVID-19 period (median (interquartile range), 19 (12–27) h) as compared with pre-COVID-19 period. Admissions of new onset acute ischaemic stroke were significantly less in COVID-19 period. Comorbidities and severity of stroke (mean National Institutes of Health Stroke Scale, 20 ± 4) were more during the COVID-19 period. Incidence and mortality of COVID-19 positive new onset acute ischaemic stroke were 0.95% and 38%. Conclusions: Onset to door time in new onset acute ischaemic stroke was significantly prolonged in COVID-19 as compared with pre-COVID-19 period. The admissions were fewer with more severity and comorbidities in COVID-19 period. COVID-19 positive stroke patients had more severity and mortality as compared with non-COVID-19 stroke.

Omicron (B.1.1.529) - A new heavily mutated variant: Mapped location and probable properties of its mutations with an emphasis on S-glycoprotein.

Omicron, another SARS-CoV-2 variant, has been recorded and reported as a VoC. It has already spread across >30 countries and is a highly mutated variant. We tried to understand the role of mutations in the investigated variants by comparison with previous characterized VoC. We have mapped the mutations in Omicron S-glycoprotein's secondary and tertiary structure landscape using bioinformatics tools and statistical software and developed different models. In addition, we analyzed the effect of diverse mutations in antibody binding regions of the S-glycoprotein on the binding affinity of the investigated antibodies. This study has chosen eight significant mutations in Omicron (D614G, E484A, N501Y, Q493K, K417N, S477N, Y505H G496S), and seven of them are located in the RBD region. We also performed a comparative analysis of the ΔΔG score of these mutations to understand the stabilizing or destabilizing properties of the investigated mutations. The analysis outcome shows that D614G, Q493K, and S477N mutations are stable mutations with ΔΔG scores of 0.351 kcal/mol, 0.470 kcal/mol, and 0.628 kcal/mol, respectively, according to DynaMut estimations. While other mutations (E484A, N501Y, K417N, Y505H, G496S) showed destabilizing results. The D614G, E484A, N501Y, K417N, Y505H, and G496S mutations increased the molecular flexibility of S-glycoprotein to interact with the ACE2 receptor, increasing the variant's infectivity. Our study will contribute to research on the SARS-CoV-2 variant, Omicron, by providing information on the mutational pattern and exciting properties of these eight significant mutations, such as antibody escape and infectivity quotient (stabilizing or destabilizing; increased or decreased molecular flexibility of S-glycoprotein to interact with the human ACE2 receptor).

B.1.1.7 (Alpha) variant is the most antigenic compared to Wuhan strain, B.1.351, B.1.1.28/triple mutant and B.1.429 variants.

The rapid spread of the SARS-CoV-2 virus and its variants has created a catastrophic impact worldwide. Several variants have emerged, including B.1.351 (Beta), B.1.1.28/triple mutant (P.1), B.1.1.7 (Alpha), and B.1.429 (Epsilon). We performed comparative and comprehensive antigenicity mapping of the total S-glycoprotein using the Wuhan strain and the other variants and identified 9-mer, 15-mer, and 20-mer CTL epitopes through in silico analysis. The study found that 9-mer CTL epitope regions in the B.1.1.7 variant had the highest antigenicity and an average of the three epitope types. Cluster analysis of the 9-mer CTL epitopes depicted one significant cluster at the 70% level with two nodes (KGFNCYFPL and EGFNCYFPL). The phage-displayed peptides showed mimic 9-mer CTL epitopes with three clusters. CD spectra analysis showed the same band pattern of S-glycoprotein of Wuhan strain and all variants other than B.1.429. The developed 3D model of the superantigen (SAg)-like regions found an interaction pattern with the human TCR, indicating that the SAg-like component might interact with the TCR beta chain. The present study identified another partial SAg-like region (ANQFNSAIGKI) from the S-glycoprotein. Future research should examine the molecular mechanism of antigen processing for CD8+ T cells, especially all the variants' antigens of S-glycoprotein.

Emerging mutations in the SARS-CoV-2 variants and their role in antibody escape to small molecule-based therapeutic resistance.

Several clinical trials started during the COVID-19 pandemic to discover effective therapeutics led to identify a few candidates from the major clinical trials. However, in the past several months, quite a few SARS-CoV-2 variants have emerged with significant mutations. Major mutations in the S-glycoprotein and other parts of the genome have led to the antibody's escape to small molecule-based therapeutic resistance. The mutations in S-glycoprotein trigger the antibody escape/resistance, and mutations in RdRp might cause remdesivir resistance. The article illustrates emerging mutations that have resulted in antibody escape to therapeutics resistance. In this direction, the article illustrates presently developed neutralizing antibodies (with their preclinical, clinical stages) and antibody escapes and associated mutations. Finally, owing to the RdRp mutations, the antiviral small molecules resistance is illustrated.

Efficacy of facemasks in mitigating respiratory exposure to submicron aerosols.

We designed a novel experimental set-up to pseudo-simultaneously measure size-segregated filtration efficiency (ηF), breathing resistance (ηP) and potential usage time (tB) for 11 types of face protective equipment (FPE; four respirators; three medical; and four handmade) in the submicron range. As expected, the highest ηF was exhibited by respirators (97 ± 3%), followed by medical (81 ± 7%) and handmade (47 ± 13%). Similarly, the breathing resistance was highest for respirators, followed by medical and handmade FPE. Combined analysis of efficiency and breathing resistance highlighted trade-offs, i.e. respirators showing the best overall performance across these two indicators, followed by medical and handmade FPE. This hierarchy was also confirmed by quality factor, which is a performance indicator of filters. Detailed assessment of size-segregated aerosols, combined with the scanning electron microscope imaging, revealed material characteristics such as pore density, fiber thickness, filter material and number of layers influence their performance. ηF and ηP showed an inverse exponential decay with time. Using their cross-over point, in combination with acceptable breathability, allowed to estimate tB as 3.2-9.5 h (respirators), 2.6-7.3 h (medical masks) and 4.0-8.8 h (handmade). While relatively longer tB of handmade FPE indicate breathing comfort, they are far less efficient in filtering virus-laden submicron aerosols compared with respirators.

Altered gut microbiota patterns in COVID-19: Markers for inflammation and disease severity.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to a severe respiratory illness and alters the gut microbiota, which dynamically interacts with the human immune system. Microbiota alterations include decreased levels of beneficial bacteria and augmentation of opportunistic pathogens. Here, we describe critical factors affecting the microbiota in coronavirus disease 2019 (COVID-19) patients. These include, such as gut microbiota imbalance and gastrointestinal symptoms, the pattern of altered gut microbiota composition in COVID-19 patients, and crosstalk between the microbiome and the gut-lung axis/gut-brain-lung axis. Moreover, we have illustrated the hypoxia state in COVID-19 associated gut microbiota alteration. The role of ACE2 in the digestive system, and control of its expression using the gut microbiota is discussed, highlighting the interactions between the lungs, the gut, and the brain during COVID-19 infection. Similarly, we address the gut microbiota in elderly or co-morbid patients as well as gut microbiota dysbiosis of in severe COVID-19. Several clinical trials to understand the role of probiotics in COVID-19 patients are listed in this review. Augmented inflammation is one of the major driving forces for COVID-19 symptoms and gut microbiome disruption and is associated with disease severity. However, understanding the role of the gut microbiota in immune modulation during SARS-CoV-2 infection may help improve therapeutic strategies for COVID-19 treatment.

Continent-wide evolutionary trends of emerging SARS-CoV-2 variants: dynamic profiles from Alpha to Omicron.

The ongoing SARS-CoV-2 evolution process has generated several variants due to its continuous mutations, making pandemics more critical. The present study illustrates SARS-CoV-2 evolution and its emerging mutations in five directions. First, the significant mutations in the genome and S-glycoprotein were analyzed in different variants. Three linear models were developed with the regression line to depict the mutational load for S-glycoprotein, total genome excluding S-glycoprotein, and whole genome. Second, the continent-wide evolution of SARS-CoV-2 and its variants with their clades and divergence were evaluated. It showed the region-wise evolution of the SARS-CoV-2 variants and their clustering event. The major clades for each variant were identified. One example is clade 21K, a major clade of the Omicron variant. Third, lineage dynamics and comparison between SARS-CoV-2 lineages across different countries are also illustrated, demonstrating dominant variants in various countries over time. Fourth, gene-wise mutation patterns and genetic variability of SARS-CoV-2 variants across various countries are illustrated. High mutation patterns were found in the ORF10, ORF6, S, and low mutation pattern E genes. Finally, emerging AA point mutations (T478K, L452R, N501Y, S477N, E484A, Q498R, and Y505H), their frequencies, and country-wise occurrence were identified, and the highest event of two mutations (T478K and L452R) was observed.

Risk factors for mortality in kidney transplant recipients with COVID-19: a single centre experience and case-control study.

BACKGROUND: COVID-19 infection is considered to cause high mortality in kidney transplant recipients (KTR). Old age, comorbidities and acute kidney injury are known risk factors for increased mortality in KTR. Nevertheless, mortality rates have varied across different regions. Differences in age, comorbidities and varying standards of care across geographies may explain some variations. However, it is still unclear whether post-transplant duration, induction therapy, antirejection therapy and co-infections contribute to increased mortality in KTR with COVID-19. The present study assessed risk factors in a large cohort from India. METHODS: A matched case-control study was performed to analyze risk factors for death in KTR (N = 218) diagnosed with COVID-19 between April 2020 to July 2021 at the study centre. Cases were KTR who died (non-survivors, N = 30), whereas those who survived were taken as controls (survivors, N = 188). RESULTS: A high death-to-case ratio of 13.8% was observed amongst study group KTR infected with COVID-19. There was a high incidence (12.4%) of co-infections, with cytomegalovirus being the most common co-infection among non-survivors. Diarrhea, co-infection, high oxygen requirement, and need for mechanical ventilation were significantly associated with mortality on regression analyses. Antirejection therapy, lymphopenia and requirement for renal replacement therapy were associated with worse outcomes. CONCLUSIONS: The mortality was much higher in KTR who required mechanical ventilation and had co-infections. Mortality did not vary with the type of transplant, post-transplant duration and usage of depletion induction therapy. An aggressive approach has to be taken for an early diagnosis and therapeutic intervention of associated infections.

A Detailed Overview of Immune Escape, Antibody Escape, Partial Vaccine Escape of SARS-CoV-2 and Their Emerging Variants With Escape Mutations.

The infective SARS-CoV-2 is more prone to immune escape. Presently, the significant variants of SARS-CoV-2 are emerging in due course of time with substantial mutations, having the immune escape property. Simultaneously, the vaccination drive against this virus is in progress worldwide. However, vaccine evasion has been noted by some of the newly emerging variants. Our review provides an overview of the emerging variants' immune escape and vaccine escape ability. We have illustrated a broad view related to viral evolution, variants, and immune escape ability. Subsequently, different immune escape approaches of SARS-CoV-2 have been discussed. Different innate immune escape strategies adopted by the SARS-CoV-2 has been discussed like, IFN-I production dysregulation, cytokines related immune escape, immune escape associated with dendritic cell function and macrophages, natural killer cells and neutrophils related immune escape, PRRs associated immune evasion, and NLRP3 inflammasome associated immune evasion. Simultaneously we have discussed the significant mutations related to emerging variants and immune escape, such as mutations in the RBD region (N439K, L452R, E484K, N501Y, K444R) and other parts (D614G, P681R) of the S-glycoprotein. Mutations in other locations such as NSP1, NSP3, NSP6, ORF3, and ORF8 have also been discussed. Finally, we have illustrated the emerging variants' partial vaccine (BioNTech/Pfizer mRNA/Oxford-AstraZeneca/BBIBP-CorV/ZF2001/Moderna mRNA/Johnson & Johnson vaccine) escape ability. This review will help gain in-depth knowledge related to immune escape, antibody escape, and partial vaccine escape ability of the virus and assist in controlling the current pandemic and prepare for the next.

Impact of self-efficacy and sense of coherence on tobacco cessation motivation and readiness among slum dwellers in Ajmer city during COVID-19 health emergency.

Background: Tobacco cessation motivation majorly depends on self-efficacy and sense of coherence. Hence the aim and objective of the present study was to explore how self-efficacy (SE) in addition to sense of coherence (SOC) affected tobacco cessation motivation and readiness among slum dwellers during the COVID-19 health emergency. Materials and Methods: The ongoing research was a cross-sectional, descriptive questionnaire study. The research started in November and ended in December 2020. The research took place in primary health centres located in Ajmer's urban slums. In this analysis, east, west, north and south directions of Ajmer were chosen at random from each direction, and each slum had an associated primary health centre (PHC). From these 16 PHCs, people coming from slum areas were interviewed. The questionnaire consisted of demographic details, tobacco motivation and readiness, SOC and SE. Results: The majority of study participants (178, 56.7%) were not seriously considering reducing their tobacco intake. The majority of study subjects had poor sense of coherence {137 (43.6%)}, self-efficacy {141 (44.9%)} and tobacco cessation motivation and readiness {156 (49.7%)}. Using the logistic regression model, it was discovered that study participants with high SE and a high SOC had a substantial impact on successful tobacco cessation motivation and readiness (P = 0.01*), (P = 0.00*). Conclusion: It was concluded that the study participants with high self-efficacy and high sense of coherence had a significant impact on good tobacco cessation motivation and readiness.