ABSTRACT
This study presents a mathematical analysis of the coronavirus spread in Pakistan by analyzing the (COVID-19) situation in six provinces, including Gilgit Baltistan, Azad Jammu Kashmir and federal capital (seven zones) individually. The influence of each province and the Federal Capital territory is then observed over the other territories. By subdividing the associated data into confirmed cases, death cases, and recovery cases, the dependence of the (COVID-19) situation from one province to the other provinces is investigated. Since the worsening circumstance in the neighboring countries were considered as a catalyst to initiate the outburst in Pakistan, it seemed necessary to have an understanding of the situation in neighboring countries, particularly, Iran, India, and Bangladesh. Exploratory data analysis is utilized to understand the behavior of confirmed cases, death cases, and recovery cases data of (COVID-19) in Pakistan. Also, an understanding of the pandemic spread during different waves of (COVID-19) is obtained. Depending on the individual situation in each of the provinces, it is expected to have a different ARIMA model in each case. Hunt for the most suitable ARIMA models is an essential part of this study. The time-series data forecasts by processing the most suitable ARIMA models to observe the influence of one territory over the other. Moreover, forecasting for the month of August 2021 is performed and a possible correlation with actual data is determined. Linear, multiple regression, and exponential models have been applied and the best-fitted model is acquired. The information obtained from such analysis can be employed to vary possible parameters and variables in the system to achieve optimal performance. © 2022 The Authors.
ABSTRACT
BACKGROUND: Coronavirus disease 2019 (COVID-19) is a multisystem disorder and haematological abnormalities are frequently documented in affected patients. METHODS: This retrospective study included 549 patients hospitalized with COVID-19 from 1st June to 15th July 2020 at Pak Emirates hospital, Rawalpindi Pakistan. p<0.05 was considered statistically significant. RESULTS: Median age was 60 years (range 12-94 years), males 442 (80.5%) and females 107 (19.5%). There was no patient with mild illness, 181 (32.9%) had moderate, 158 (28.7%) severe and 210 (38.2%) patients had critical disease. Patients with severe and critical disease had lower absolute lymphocyte count (ALC) and platelets (p<0.001 for both) while higher white blood cell count (WBC), neutrophil lymphocyte ratio (NLR), C-reactive protein (CRP), interleukin-6 (IL-6) and lactate dehydrogenase levels (LDH) levels (all p<0.001). Overall survival of study cohort was 83.2% (n=457). Median haemoglobin and platelet count were significantly lower (p<0.001) while WBC, ANC, NLR, prothrombin time (PT), activated partial thromboplastin time (APTT), ferritin, IL-6, LDH were significantly higher (p<0.001) for patients who died. On multivariate logistic regression analysis WBC count>10x109/l (odds ratio [OR] 2.19 [95% CI 1.3-4.2] p=0.01), NLR>9 (OR 3.4 [95% CI 0.87-6.8], p<0.001), platelets<150x109/l (OR 3.9 [95% CI 1.4-9.8] p<0.001), CRP >100;(OR 4.1[95% CI 0.78-10.9] p<0.001) and ferritin >1000 (OR 5.3 [95% CI 1.9- 13.5], p<0.001) were associated with increased risk of death in patients with COVID-19. CONCLUSION: Monitoring of haematological, coagulation and inflammatory parameters provide reliable, convenient, rapid and cost-effective method for predicting disease severity, complications and prognosis of COVID-19 patients.
ABSTRACT
Most retailers are currently undergoing a major transformation in the process of becoming omnichannel retailers. This case addresses the challenges of an Irish company in the transition from an offline focused retailer to an omnichannel company. Building on its strong expertise in traditional offline retail, the company is aiming to establish itself as an omnichannel retailer that allows for increasing its customer base in Ireland and overseas. The case describes actual challenges along the journey, including the strategic, operational, and technological challenges. It provides an opportunity for students to discuss and understand the practical aspects of the retail transformation process and the linkage between technology and business strategy. The case enables discussions on the multiple aspects in the process of transformation toward omnichannel retail and promotes the development of innovative solutions for transferring customer experience provided in offline retail to online platforms. © Association for Information Technology Trust 2021.