COVID-19 case fatality rates across Southeast Asian countries (SEA): a preliminary estimate using a simple linear regression model

PurposeThe purpose of this study was to determine COVID-19 preliminary case fatality rates (CFR) across Southeast Asian (SEA) countries.Design/methodology/approachThe study accessed the data on COVID-19 accumulated cases of fatalities and infections across SEA countries from the World Health Organization (WHO) website, covering the early days of March to May 21, 2020. The approach involved the computation of the CFR using the simple linear regression model. The slope of the regression line was the estimate of the CFR at a 95% confidence interval. The study also reviewed the different approaches of the SEA countries in dealing with the pandemic.FindingsAs of May 21, 2020, Singapore, Indonesia and the Philippines were the top three SEA countries with the highest record of COVID-19 infections. Brunei had one fatality, while Cambodia, Laos, Timor-Leste and Viet Nam had nil fatalities. Indonesia and the Philippines had the highest CFR with 6.66 and 6.59%, with R2 of 97.95 and 99.43%, respectively. Singapore had the lowest CFR (0.068%) despite high infections.Originality/valueIncreased CFR in Indonesia and the Philippines suggests that COVID-19 in the two countries is rising at an alarming rate. Strict implementation of shared management approaches to control the pandemic is seen to be closely associated with the decrease of CFR.

Pengaruh Modal Terhadap Pendapatan Pedagang (Studi kasus: Pasar Angso Duo Kota Jambi)

research aims to find out the effect of variable capital on the income of traders in Angso Duo Market Jambi City. The study used primary data by disseminating qusioners to 92 respondents. The method used in this study is a simple linear regression method. while econoetry analysis using a simple linear regression model is carried out to identify the variables that affect. Variables used are capital variables as free variables and income variables as bound variables. The results of the analysis showed that the capital had a positive effect on the earnings of Angso Duo Market traders. This means that if the market trader increases his capital, then the income of the market trader will also increase.

A randomised controlled trial of the influence of Non-native English accents on Examiners’ scores in OSCEs

BackgroundObjective Structured Clinical Examinations (OSCEs) are important aspects of assessment in medical education. There are anecdotes that students with non-native English accents (NNEA) may be marked negatively due to unconscious bias. It is imperative to minimise the examiners’ bias so that the difference in the scores reflects students’ clinical competence. Research in shows NNEAs can cause stereotyping, often leading to the speaker being negatively judged. However, no medical education study has looked at the influence of NNEAs in assessment.MethodsThis is a randomised, single - blinded controlled trial. Four videos of one mock OSCE station were produced. A professional actor played a medical student. Two near identical scripts were prepared. Two videos showed the actor speaking with an Indian accent and two videos showed the actor speaking without the accent in either script. Forty-two UK OSCE examiners were recruited and randomly assigned to two groups. They watched two videos online, each with either script, with and without the NNEA. Checklist item scores were analysed with descriptive statistics and simple linear regression model. Global scores were analysed with descriptive statistics and logistic ordinal regression model.ResultsThirty-two examiners completed the study. The average scores for the checklist items (41.6 points) did not change when the accent variable was changed. Simple linear regression model showed no statistically significant relationship between the accent and the scores (Regression coefficient = 0.032, p = 0.982). For the global scores received by the videos with the NNEA, there were one less ‘Good’ grade and one more ‘Fail’ grade compared to the ones without the NNEA. Logistical ordinal regression model on global scores showed, examiners were more likely to mark the student more negatively (p < 0.0001) but also more positively (p < 0.0001) when the NNEA was present.ConclusionsExaminers could be biased either positively or negatively towards NNEAs when giving global scores. Further research is required to consider the nature of this bias. More discussion is warranted to consider how the accent should be considered in current medical education assessment.

PM2.5 Concentration Estimation Based on Image Processing Schemes and Simple Linear Regression

Fine aerosols with a diameter of less than 2.5 microns (PM2.5) have a significant negative impact on human health. However, their measurement devices or instruments are usually expensive and complicated operations are required, so a simple and effective way for measuring the PM2.5 concentration is needed. To relieve this problem, this paper attempts to provide an easy alternative approach to PM2.5 concentration estimation. The proposed approach is based on image processing schemes and a simple linear regression model. It uses images with a high and low PM2.5 concentration to obtain the difference between these images. The difference is applied to find the region with the greatest impact. The approach is described in two stages. First, a series of image processing schemes are employed to automatically select the region of interest (RoI) for PM2.5 concentration estimation. Through the selected RoI, a single feature is obtained. Second, by employing the single feature, a simple linear regression model is used and applied to PM2.5 concentration estimation. The proposed approach is verified by the real-world open data released by Taiwan’s government. The proposed scheme is not expected to replace component analysis using physical or chemical techniques. We have tried to provide a cheaper and easier way to conduct PM2.5 estimation with an acceptable performance more efficiently. To achieve this, further work will be conducted and is summarized at the end of this paper.

ANALISIS PERKEMBANGAN DAN ELASTISITAS TRANSMISI HARGA ABALON (HALIOTIS ASININA) DI KABUPATEN BUTON

This study aims to analyze the prize development and the price transmission elasticity of abalone in Buton Regency. This study was conducted in June – July 2015 with a survey method. Analysis of price developments and elasticity of price transmission is done by a simple linear regression model. The results showed that each added one period, abalone prices decreased by Rp. 9501 each kilogram. Pricetransmission elasticity show in the level consumers prices has been not fully transmitted to the level of fisherman with vale ofelasticityis 0,11 indicated that when the selling pricein the level consumers increased by 1% then the selling pricein the levelfisherman will increase of 0,11%, or moere easly can be defined that if the selling pricein the level consumers increase, the selling pricein the levelfisherman will also be increase.