Genome sequencing and analysis of genomic diversity in the locally transmitted SARS-CoV-2 in Pakistan.

Surveillance of genetic diversity of the SARS-CoV-2 is extremely important to detect the emergence of more infectious and deadly strains of the virus. In this study, we evaluated mutational events in the SARS-CoV-2 genomes through whole genome sequencing. The samples were collected from COVID-19 patients in different major cities of Pakistan during the four waves of the pandemic (May 2020 to July 2021) and subjected to whole genome sequencing. Using in silico and machine learning tools, the viral mutational events were analyzed, and variants of concern and of interest were identified during each of the four waves. The overall mutation frequency (mutations per genome) increased during the course of the pandemic from 12.19 to 23.63, 31.03, and 41.22 in the first, second, third, and fourth waves, respectively. We determined that the viral strains rose to higher frequencies in local transmission. The first wave had three most common strains B.1.36, B.1.160, and B.1.255, the second wave comprised B.1.36 and B.1.247 strains, the third wave had B.1.1.7 (Alpha variant) and B.1.36 strains, and the fourth waves comprised B.1.617.2 (Delta). Intriguingly, the B.1.36 variants were found in all the waves of the infection indicating their survival fitness. Through phylogenetic analysis, the probable routes of transmission of various strains in the country were determined. Collectively, our study provided an insight into the evolution of SARS-CoV-2 lineages in the spatiotemporal local transmission during different waves of the pandemic, which aided the state institutions in implementing adequate preventive measures.

Implementation of lean Six-Sigma project in enhancing health care service quality during COVID-19 pandemic.

The recent outbreak of coronavirus (COVID-19) pandemic has exposed the weakness of the existing healthcare facilities in developing countries, and Pakistan has no exception. The increasing amount of patients has made this condition more vulnerable to failure. It became difficult for health care management to handle the surge of patients. This case study is based on the XYZ hospital system of Pakistan. The hospital initiates passive immunization as a savior in the absence of a vaccine. The process initiates numerous challenges as the same facility was using for passive immunization and routine operations of the hospital. DMAIC lean sig-sigma problem-solving methodology has been adopted to Define, Measure, Analyze, Implement and Control the improvement process for smooth special and routine activities. The staff and patients were interviewed, their issues were listed, and a comprehensive solution was suggested to deal with operational uncertainties. The results identified various factors through VOC and SIPOC processes, prioritized using fishbone diagram, analyzed through Kano model, and finally proposed process improvement by incorporating Kaizen process improvement methodology. Other industries could use this set of tools to evaluate and optimize routine problems, which ultimately enhances the quality and reduces cost.

Comprehensive comparative genomic and microsatellite analysis of SARS, MERS, BAT-SARS, and COVID-19 coronaviruses.

The coronavirus disease 2019 (COVID-19) pandemic has spread around the globe very rapidly. Previously, the evolution pattern and similarity among the COVID-19 causative organism severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and causative organisms of other similar infections have been determined using a single type of genetic marker in different studies. Herein, the SARS-CoV-2 and related ß coronaviruses Middle East respiratory syndrome coronavirus (MERS-CoV), SARS-CoV,  bat coronavirus (BAT-CoV) were comprehensively analyzed using a custom-built pipeline that employed phylogenetic approaches based on multiple types of genetic markers including the whole genome sequences, mutations in nucleotide sequences, mutations in protein sequences, and microsatellites. The whole-genome sequence-based phylogeny revealed that the strains of SARS-CoV-2 are more similar to the BAT-CoV strains. The mutational analysis showed that on average MERS-CoV and BAT-CoV genomes differed at 134.21 and 136.72 sites, respectively, whereas the SARS-CoV genome differed at 26.64 sites from the reference genome of SARS-CoV-2. Furthermore, the microsatellite analysis highlighted a relatively higher number of average microsatellites for MERS-CoV and SARS-CoV-2 (106.8 and 107, respectively), and a lower number for SARS-CoV and BAT-CoV (95.8 and 98.5, respectively). Collectively, the analysis of multiple genetic markers of selected ß viral genomes revealed that the newly born SARS-COV-2 is closely related to BAT-CoV, whereas, MERS-CoV is more distinct from the SARS-CoV-2 than BAT-CoV and SARS-CoV.