As the world grapples with the problem of the coronavirus disease 2019 (COVID-19) pandemic and its devastating effects, scientific groups are working towards solutions to mitigate the effects of the virus. This paper aimed to collate information on COVID-19 prediction models. A systematic literature review is reported, based on a manual search of 1,196 papers published from January to December 2020. Various databases such as Google Scholar, Web of Science, and Scopus were searched. The search strategy was formulated and refined in terms of subject keywords, geographical purview, and time period according to a predefined protocol. Visualizations were created to present the data trends according to different parameters. The results of this systematic literature review show that the study findings are critically relevant for both healthcare managers and prediction model developers. Healthcare managers can choose the best prediction model output for their organization or process management. Meanwhile, prediction model developers and managers can identify the lacunae in their models and improve their data-driven approaches.

Goal: Quality of Work Life (QWL) draws more attention in the present context, and it is a multidimensional construct. The oil and gas industries have realized the significance of employees' QWL to retain and attract a talented workforce in the competitive job market. This study examines the status of QWL of employees in the LPG Bottling Industry.Design / Methodology / Approach: A measuring scale was designed and validated to evaluate the employees QWL working in the LPG bottling plant. The data for the study was gathered from 435 employees working in four LPG bottling industries. Using Exploratory Factor Analysis (EFA), predominant components of QWL are identified. With the Confirmatory Factor Analysis (CFA), the designed scale is validated. With percentage analysis and chi-square analysis, the data was analyzed, and meaningful inferences were drawn.Results: EFA and CFA resulted in four components of QWL with 19 items representing superior model fit. The model fit indices reported from the model namely Chi-Square value = 399.020; CMIN = 2.978, AGFI = 0.900; CFI = 0.937; GFI = 0.915; IFI = 0.938; NFI = 0.909; TLI = 0.920 and RMSEA = 0.068 are in the acceptable range. 51.5% of the respondents expressed to be satisfied with present condition of QWL. The research outcome revealed that among demographical characteristics, nature of activities significantly impacts on the status of QWL of employees. Limitations of the investigation:The data was collected from 435 employees working in four industries because of time constraints.Practical implications: This research's outcome will help the policymakers of LPG Bottling industries to implement QWL interventions for improving the work-life of employees.Originality / Value: The present paper is one among the few studies carried out in the oil and gas sector as minimal research has been done in this area.

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