Background: The Hajj is the largest annual gathering in the world, and it is a very important event for every Muslim. Makkah annually receives three million pilgrims who perform Hajj. Although precautionary measures have been taken in Saudi Arabia to slow down the spread of COVID-19, such as locking down the most affected cities, practicing social distancing, and applying the infection-control precautions, the number of cases has increased. The total confirmed number of cases in Makkah was 10,709 with 127 deaths as of May 16, 2020. Aims of the study: Forecasting the COVID-19 progression in the city of Makkah will help the policymakers decide if the Hajj will be able to operate this year. Thus, to see a clear picture of the fight against COVID-19 for the economy and healthcare industry in Saudi Arabia, specifically in Makkah, the SIR model will predict COVID-19 progression in the city of Makkah. Method: The Susceptible, Infected, and Recovered (SIR) model has been used to track the transmission dynamics and growth among the city of Makkah. The growth index was calculated, according to the data from March 16 until May 9. The estimated vital epidemiological parameters, such as forecasting works and transmission rates, were done. Result: The data showed an interesting result about the peak of the disease progression. It is projected to occur around the 12th day after running the model. According to the model, the peak time will be around the 22nd of May. Then, the number of cases will start to decrease. Conclusion: Using the SIR model, the result predicts the disease progression peak and an estimated end of COVID-19 in the city of Makkah to help the policymakers decide if the Hajj will be able to operate this year.
This paper is evaluating whether education or the standard of living in a country helped citizens to stay at home during COVID-19 pandemic. The study implemented a cross-sectional regression on Google mobility trend reports as of 29th March, 2020 which include the mobility trends in retail and recreation, grocery and pharmacy, park, transit station, workplace and residential areas along with real GDP per capita as a proxy for standard of living and Education Index to approximate the level of education. The cross-sectional regression included 123 countries as a sample for the study. The study found that education index, park mobility trends and workplace mobility trends were significate variables in explaining the changes in residential area. However, real GDP per capita was not significate. The study concluded that standard of living is not a significate variable in changing the percentage of people who stayed at home. Moreover, education index has a negative impact on staying at home. Meaning, for each one-point increase in education index, the percentage change for citizens staying at home decreases by 0.087. Although, our result indicates that individual's education has a negative effect, this result can be explained by the decline of political trust in demarcate government were education index is high.
The study intends to investigate if the stock market in Saudi Arabia follows the weak form of market efficiency using daily data from Tadawul All Share Index (TASI). The daily data was collected from January 2012 to January 2019. The study employed different of tests types such as: autocorrelation, unit root test, runs test, and variance decomposition test that are used to assess the daily data of the Saudi stock market. The results from autocorrelation, unit root test, runs test, and variance decomposition test indicate that the Saudi stock market does not follow the weak form of market efficiency. However, future studies are required to understand variations in the Saudi stock market prices. Additionally, the results recommend conducting further studies to test the semistrong form of efficient market hypothesis in Saudi Arabia.Moreover, future studies also need to focus on the adoption of correction and regulations by the policymakers in the Saudi stock market.Contribution/ Originality: This study contributes to the existing literature on emerging stock markets in general and particularly to the Saudi market since the majority of the studies are done in developed countries with well-organized stock markets. Also, it includes a new period where new regulations were adopted by the Saudi stock market.
Background: Saudi Arabia is one of the countries affected by COVID-19 pandemic. This will lead to negative impacts in many sectors. Saudi Arabia not only plays an important role on the economical side because it is the leading country in oil production, but also because it is considered the heart of the Islamic countries. Although protective measures have been implemented in Saudi Arabia, the number of COVID-19 cases has increased. Aims of the study: This study aimed to employ SIR model to forecast the peak of COVID-19 progression and an estimation of it is end in Saudi Arabia. Method: Based on the World Health Organization data on COVID-19 progression in Saudi Arabia from March 3rd to April 29th, 2020, we reliably estimate the constant parameters and make predictions on the inflection point and potential ending time. Susceptible, Infected, and Recovered are the main components of the SIR model that were used to run the analysis. Result: The data showed an interesting result about the peak of the disease progression. It is projected to occur around the 20th day after running the model. According to the model, the peak time will be around the 20th of May. Then the cases will decrease until the 55th day, which is around June 20th. Conclusion: The result predicts a second peak and an estimation end of COVID-19 in Saudi Arabia. This data can inform the policy makers, who should try to contain the virus, to be prepared for what is coming next.
It is well known that uncertainty and various measures implemented by the government, such as lockdown, social distancing, and travel restrictions during the COVID-19 pandemic, severely impacted low-income households in Bangladesh. This situation forced them to put forward various mechanisms to cope with the devastating situation caused by the pandemic. This paper focuses on the impact of the COVID-19 epidemic on the quality of life (QoL) of low-income households, their survival coping mechanisms, and the impact of the coping mechanisms on their QoL. From 1 October 2021 to 30 December 2021, primary data from 1279 households were collected through online and offline surveys from different divisions of Bangladesh, and were used to analyze the income-generation, transfer, and cost-minimization practices adopted by the households during the pandemic. The Statistical Package for Social Science (SPSS) version 25 was utilized for data analysis. We employed multivariate and regression statistical techniques to achieve the study objectives. The investigation found that QoL declined significantly due to the COVID-19 crisis. The findings also confirmed that coping mechanisms adopted by households varied according to demographic characteristics, and the QoL deteriorated significantly more in those households that adopted more coping mechanisms relative to others, regardless of socio-demographic features. The findings emphasize the importance of recording grounded survey data to track and gather information on the QoL of low-income households during the pandemic, and of constructing evidence-based policy responses. Furthermore, the study contributes to enriching the existing literature on the impact of the corona pandemic, and can serve as a source for potential studies. This study contributes to a clearer picture of the effects of COVID-19 trauma. This survey-based empirical study provides an understanding of the initial micro-level effects of COVID-19 in Bangladesh. This study gives a synopsis of the extent to which Bangladeshi households adopted mechanisms to deal with the COVID-19 crisis and the effects of the adoption of these mechanisms on quality of life.
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