Research on COVID-19 Virus Spreading Statistics based on the Examples of the Cases from Different Countries

Gondauri, Davit; Mikautadze, Ekaterine; Batiashvili, Mikheil

doi:10.29333/ejgm/7869

Cited by 59 publications

(50 citation statements)

References 11 publications

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“…It is worth noticing that many studies have considered very low recovery rate for the UK, for example Khafaie & Rahim (2020) has considered a recovery rate of 1.64% by 23 March 2020 in the UK. However, in the current study, due to the lack of available data on the recovery rate in UK, the global recovery rate of 53.38% is considered ( Gondauri, Mikautadze & Batiashvili, 2020 ). Therefore, the R 0 values can be estimated using the average R t value defined for different scenarios and the global recovery rate of 53.38%.…”

Section: Methodsmentioning

confidence: 99%

Sensitivity analysis of the infection transmissibility in the UK during the COVID-19 pandemic

Biglarbeigi¹,

Ng²,

Finlay³

et al. 2021

PeerJ

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The coronavirus (COVID-19) outbreak started in December 2019 and rapidly spread around the world affecting millions of people. With the growth of infection rate, many countries adopted different policies to control the spread of the disease. The UK implemented strict rules instructing individuals to stay at home except in some special circumstances starting from 23 March 2020. Accordingly, this study focuses on sensitivity analysis of transmissibility of the infection as the effects of removing restrictions, for example by returning different occupational groups to their normal working environment and its effect on the reproduction number in the UK. For this reason, available social contact matrices are adopted for the population of UK to account for the average number of contacts. Different scenarios are then considered to analyse the variability of total contacts on the reproduction number in the UK as a whole and each of its four nations. Our data-driven retrospective analysis shows that if more than 38.5% of UK working-age population return to their normal working environment, the reproduction number in the UK is expected to be higher than 1. However, analysis of each nation, separately, shows that local reproduction number in each nation may be different and requires more adequate analysis. Accordingly, we believe that using statistical methods and historical data can provide good estimation of local transmissibility and reproduction number in any region. As a consequence of this analysis, efforts to reduce the restrictions should be implemented locally via different control policies. It is important that these policies consider the social contacts, population density, and the occupational groups that are specific to each region.

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Section: Methodsmentioning

confidence: 99%

Sensitivity analysis of the infection transmissibility in the UK during the COVID-19 pandemic

Biglarbeigi¹,

Ng²,

Finlay³

et al. 2021

PeerJ

View full text Add to dashboard Cite

show abstract

“…COVID-19 was detected in December 2019 which later developed into a pandemic as it made an extensive change (Gondauri, Mikautadze, & Batiashvili, 2020) that affected not only Wuhan, China but all other countries around the globe. COVID-19 brought a plight into the sphere causing for health emergencies, socio-econmic recession, and academic disentanglement along the progression of the virus transmission.…”

Section: Introductionmentioning

confidence: 99%

Facing COVID-19 through Emergency Online Education Anchored in Khan’s Framework: Case of Philippine Teachers in Xi’an, China

Toquero

Talidong

2021

European Journal of Interactive Multimedia and Education

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COVID-19 affected not only the lifestyle and socioeconomic conditions of the people worldwide but also the governing affairs of the process of education. To limit the transmission of COVID-19 in the educational sector, teachers worldwide immediately diverted from face-to-face education to a virtual-based education. This abrupt paradigm shift in education posits a challenge to the teachers who are accustomed to the conventional settings as they embark to emergency online teaching classes. Although distance education is a normalcy in many of the institutions globally, it is still new to the context of the Philippine teachers. In this account, an empirical study on the experiences of the Philippine teachers in Xi'an, China was explored to examine the benefits, challenges, and process in the implementation of emergency online education. Results revealed that emergency online teaching fosters benefits to the teachers and learners during this emergency situation. However, the teachers experience challenges dealing with technical issues, lack of instructional design, and other factors which disrupt emergency online education. This article offers positive and negative standpoints of the application of emergency online teaching to address the unprecedented educational issues brought by the pandemic.

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“…The results found that sex, region, and infection reasons affected on both recovered and deceased cases, while birth year only affected on deceased cases. Gondauri et al (2020) considered the chain-binomial type of Bailey's model for studying and analyzing the correlation between the total volumes of COVID-19 virus spread and recovery from the different countries. Most of the study investigates the COVID-19 cases based on various regression and time series models because these models are frequently applied to examine the growth or trend of any disease.…”

Section: Introductionmentioning

confidence: 99%

Study the Trend Pattern in COVID-19 using Spline-Based Time Series Model: A Bayesian Paradigm

Agiwal¹,

Kumar²,

Yip³

2020

Preprint

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A vast majority of the countries is under the economic and health crises due to the current epidemic of coronavirus disease 2019 (COVID-19). The present study analyzes the COVID-19 using time series, which is an essential gizmo for knowing the enlargement of infection and its changing behavior, especially the trending model. We have considered an autoregressive model with a non-linear time trend component that approximately converted into the linear trend using the spline function. The spline function split the COVID-19 series into different piecewise segments between respective knots and fitted the linear time trend. First, we obtain the number of knots with its locations in the COVID-19 series and then the estimation of the best-fitted model parameters are determined under Bayesian setup. The results advocate that the proposed model/methodology is a useful procedure to convert the non-linear time trend into a linear pattern of newly coronavirus case for various countries in the pandemic situation of COVID-19.

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Research on COVID-19 Virus Spreading Statistics based on the Examples of the Cases from Different Countries

Cited by 59 publications

References 11 publications

Sensitivity analysis of the infection transmissibility in the UK during the COVID-19 pandemic

Sensitivity analysis of the infection transmissibility in the UK during the COVID-19 pandemic

Facing COVID-19 through Emergency Online Education Anchored in Khan’s Framework: Case of Philippine Teachers in Xi’an, China

Study the Trend Pattern in COVID-19 using Spline-Based Time Series Model: A Bayesian Paradigm

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