ABSTRACT
The purpose of the present paper is to investigate the long-run and short-run relationships between the loss of employment and the Covid-19 pandemic in Malaysia’s labour market. The Covid-19 measures in-clude the number of Covid-19 new cases, the number of Covid-19 new deaths, the number of total Covid-19 cases and the Covid-19 fear index. Using cointegration analysis, we found that the loss of employment exhibit long-run relationships with the four Covid-19 measures. Our short-run analysis using the PGARCH-M model able to captures the volatility and clustering of the variability in the loss of employment. The PGARCH-M model shows evidence of the leverage effects or asymmetric effects which suggest that the positive shocks (good news) increase volatility in the loss of employment, more than the negative shocks (bad news) in a crisis situation. © 2022,Revista Portuguesa de Estudos Regionais.All Rights Reserved
ABSTRACT
In this paper, we use daily administrative data from January 25, 2020 to December 31, 2020 to examine the relationship between job losses and the Malaysian lockdown measures. The Auto Regressive Distributed Lag (ARDL) approach is used to estimate both the long-run and short-run models. The results of the Bounds F-test for cointegration reveal that there is a long-run link between job losses and the Malaysian government lockdown measures (both linear and non-linear). The positive association between job loss and lockdown measures shows that as the lockdown gets tighter, more people will lose their jobs. However, as time passes, especially in conjunction with the government stimulus package programmes, job losses decrease.
ABSTRACT
Corona viruses are a group of RNA viruses that cause infection in humans and animals. In human Corona viruses cause respiratory tract infections ranging from mild to critical illness. Corona virus disease 2019 (COVID-19) is caused by strain of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2). The disease was first identified in Wuhan city, of China, in December 2019 and since spread all around the world. In Bangladesh first case has been declared by Institute of Epidemiology, Disease Control and Research (IEDCR) in 8th March, 2020 and first death on 18th march in an ICU and by 13th December total 489,178 cases and 7,020 deaths occurred in this country. The main objective of this study was to determine the Demographic and Clinical Profile of COVID-19 ICU patients in Bangladesh. This retrospective descriptive study on clinical profile along with short term treatment outcomes of COVID-19 patients conducted from COVID-19 dedicated Intensive care unit of Bangabandhu Sheikh Mujib Medical University (BSMMU), Bangladesh during July 2020 to November 2020. Total 300 ICU patients was included in this study. The age range of the patients was from 15 to 91 years. The highest percentage of patients about 49.00%, which was 147 patients were belonged to 61-75 years age group. The patients mean age was 62.80 years. Regarding gender distribution, among those 300 patients;77.00% which is 231 were male and only 23.00% which is 69 were female. Patients admitted with symptoms like, respiratory distress/shortness of breath (100.00%), persistent worsening cough (60.00%), fatigue (55.00%) and fever (40.00%). Patients were also present with sore throat (35.00%), rhinorrhea (30.00%), altered mental status (20.00%), diarrhoea (10.00%) and chest pain (5.00%). Regarding co-morbidities, around half of the patients were suffering from Diabetes (60.22%) and Hypertension (53.44%). Significant amount of patients were also suffering from chronic obstructive pulmonary disease (27.00%) and bronchial asthma (16.78%). Ischemic heart disease was (10.33%), chronic kidney disease (10.89%), hypothyroidism (9.78%) and multiple co-morbidities (15.12%) at the time of admission. Mortality rate in this case were 71.00% and most of the death cases were in between 61 to 75 years of age group (40.00%). After improvement 27.00% patients were transferred to cabin for further management. We could discharge to home directly only 2.00% of patients.
ABSTRACT
Introduction: SARS-CoV2, first reported in December 2019 in Wuhan as COVID-19 causing respiratory illness, rapidly evolved into a pandemic owing to its very high infectivity. There is insufficient evidence about if and how smoking affects the risk of COVID-19 infection, and the reports on whether smoking increases or reduces the risk of respiratory infections, are contradictory. Therefore, the current study was designed to determine the effects of nicotine consumption on the infectivity of COVID-19. Methods: We performed in silico computer simulation-based study. The structures of SARS-CoV2spike ectodomain, and its receptor ACE2, were obtained from PDB. The structure of nicotine and its metabolites NNK and NNAL were obtained from the PubChem chemical database. After optimization, they were interacted using AutoDock 4.2, to see the effect of nicotine, NNK, or NNAL presence on the docking of viral spike protein to its receptor ACE2. Results: ACE2 vs spike protein interaction results were used as a control (ZDOCK score 1498.484, with four hydrogen bonds). The NNK+ACE2 vs spike protein docking formed 10 hydrogen bonds with the highest ZDOCK score of 1515.564. NNAL+ ACE2 vs spike protein interaction formed eleven hydrogen bonds with the ZDOCK score of 1499.371. Nicotine+ACE2 vs spike protein docking showed the lowest ZDOCK score of 1496.302 and formed 8 hydrogen bonds. Whereas, NNK+spike vs ACE2 interaction had a ZDOCK score of 1498.490 and formed eight hydrogen bonds. NNAL+spike vs ACE2 docking formed eleven hydrogen bonds with a ZDOCK score of 1498.482. And Nicotine+spike vs ACE2 interaction showed a ZDOCK score of 1498.488 and formed 9 hydrogen bonds. Conclusions: The binding of nicotine to either spike of virus or its receptor ACE2 is not affecting the viral docking with the receptor. But binding of NNK, a metabolite of nicotine, is facilitating the viral docking with its receptor indicating that smoking may increase the risk of COVID-19 infection.
ABSTRACT
In this empirical note, we examine the relationship between the loss of employment and lockdown measures undertaken by the Malaysian government during the Covid-19 pandemic outbreak over the period from 25 January 2020 to 10 September 2020. By using cointegration analysis, our results suggest that there are both long-run and short-run relationships between loss of employment and lockdown measures in Malaysia. Lockdown measures show positive impact on the number of workers who lost their jobs during the pandemic. The loss of employment increases by 0.35% to 1.1% for every 1% increase in the lockdown measures. © 2021 Penerbit Universiti Kebangsaan Malaysia. All rights reserved.