Predicting Covid-19 Infections Prevalence Using Linear Regression Tool

Ali, Syed Tahir; Shah, Pankaj; Abeer,; Iftikhar,; Imran, Muhammad; Khan, M. R.; Majad,; Mansoor,; Feroz, Adeel; Mirza,; Muhammad, Muhammad; Bilal, B

doi:10.18006/2020.8(spl-1-sars-cov-2).s01.s08

Cited by 4 publications

(3 citation statements)

References 14 publications

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“…1 Given that SARS-CoV-2 infected millions and killed hundreds of thousands of people in virtually every country on the planet, the COVID-19 pandemic has put the entire scientific community on high alert 2 .The pandemic situation puts great weight on the use of scientific calculations to be used as linear regression tools or machine learning models to estimate the number of cases. 3,4 Up to October 2021, the top three countries with the highest number of infected cases are US, India, and Brazil. 2 A thorough list of COVID-19 pulmonary and non-pulmonary manifestations has been documented [5][6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

Relationship between COVID-19 and Human Gut Microbiome, Nutritional Factors, Type 2 Diabetes, and Obesity

Abdel-Gawad

Ali

Azab

et al. 2022

Journal of Advanced Pharmacy Research

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The current coronavirus disease (COVID-19) pandemic poses a significant challenge for human microbiota researchers around the world, as the causes and long-term repercussions of infection at the gastrointestinal (GI) level are still unknown. Original research publications, clinical investigations, epidemiological reports, and review-type articles about human intestine infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the possible repercussions on the microbiota were reviewed in the current study. Furthermore, the following aspects of COVID-19 have been discussed: Epidemiology, human sensitivity, the impact of dietary habits on the intestinal microbiota, and the impact of comorbid metabolic disorders like obesity, inflammatory bowel disease (IBD), and diabetes on the intestinal microbiota. According to the studies, health, age, and nutritional condition are linked to specific bacterial populations in the gut, which may influence the clinical course of COVID-19 infection. Changes in the faecal microbiota were linked to the severity of SARS-CoV-2 and COVID-19 infections. Patients with metabolic and GI issues are likely to have a moderate-to-high risk of SARS-CoV-2 infection, implying that gut dysbiosis plays a direct role in COVID-19 severity. However, further work is needed to identify COVID-19's initial GI symptoms so that early management can be attempted.

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Section: Introductionmentioning

confidence: 99%

Relationship between COVID-19 and Human Gut Microbiome, Nutritional Factors, Type 2 Diabetes, and Obesity

Abdel-Gawad

Ali

Azab

et al. 2022

Journal of Advanced Pharmacy Research

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“…Especially countries with weak economies, limited resources, and poorly developed health system are in big trouble [ 1 – 3 ]. However, the prevalence rates of infection in developed countries like the USA and several other countries are very high [ 4 , 5 ]. But, these countries have ample healthcare facilities for patients to compensate for their technology and research and provide better protection to their frontline medical practitioners.…”

Section: Introductionmentioning

confidence: 99%

Stem cell therapies and benefaction of somatic cell nuclear transfer cloning in COVID-19 era

et al. 2021

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Background The global health emergency of COVID-19 has necessitated the development of multiple therapeutic modalities including vaccinations, antivirals, anti-inflammatory, and cytoimmunotherapies, etc. COVID-19 patients suffer from damage to various organs and vascular structures, so they present multiple health crises. Mesenchymal stem cells (MSCs) are of interest to treat acute respiratory distress syndrome (ARDS) caused by SARS-CoV-2 infection. Main body Stem cell-based therapies have been verified for prospective benefits in copious preclinical and clinical studies. MSCs confer potential benefits to develop various cell types and organoids for studying virus-human interaction, drug testing, regenerative medicine, and immunomodulatory effects in COVID-19 patients. Apart from paving the ways to augment stem cell research and therapies, somatic cell nuclear transfer (SCNT) holds unique ability for a wide range of health applications such as patient-specific or isogenic cells for regenerative medicine and breeding transgenic animals for biomedical applications. Being a potent cell genome-reprogramming tool, the SCNT has increased prominence of recombinant therapeutics and cellular medicine in the current era of COVID-19. As SCNT is used to generate patient-specific stem cells, it avoids dependence on embryos to obtain stem cells. Conclusions The nuclear transfer cloning, being an ideal tool to generate cloned embryos, and the embryonic stem cells will boost drug testing and cellular medicine in COVID-19.

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“…Several methods can be used to make a forecast or prediction, namely Linear Regression and Polynomial Regression. Linear Regression is a statistical analysis that models the relationship of several variables according to the form of an explicit linear equation relationship [8]. Meanwhile, Polynomial Regression is a linear regression model formed by adding the influence of each predictor variable (X) raised to the k-order [9].…”

mentioning

confidence: 99%

Prediction Model for Covid-19 Cases in Indonesia Using Linear Regression and Polynomial Regression Methods

Rakhman,

Cahyana,

Rahmat

et al. 2023

ECSIT

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The World Health Organization on March 11, 2020, declared Coronavirus Disease 2019 (Covid-19) a pandemic. Covid-19 is a disease caused by a new type of coronavirus, namely Sars-CoV-2, which affects the respiratory system. Until now, positive confirmed cases of Covid-19 in Indonesia are still occurring every day. This study aims to predict the addition of Covid-19 cases in Indonesia. The data is sourced from the public API page covid19.go.id in the form of an additional number of Covid-19 cases in Indonesia by 122 lines of data. Predictions are made using linear regression and polynomial regression methods as comparisons. Evaluation of the linear regression method obtains a value of R2 = 0.57, while the polynomial regression method obtains a value of R2 = 0.84. Based on these evaluations, the polynomial regression method yields better results than the linear regression method. The prediction of Covid-19 cases in Indonesia from January to March 2022 using the polynomial regression methods predicts that the addition of Covid-19 cases will rise again.

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Predicting Covid-19 Infections Prevalence Using Linear Regression Tool

Cited by 4 publications

References 14 publications

Relationship between COVID-19 and Human Gut Microbiome, Nutritional Factors, Type 2 Diabetes, and Obesity

Relationship between COVID-19 and Human Gut Microbiome, Nutritional Factors, Type 2 Diabetes, and Obesity

Stem cell therapies and benefaction of somatic cell nuclear transfer cloning in COVID-19 era

Prediction Model for Covid-19 Cases in Indonesia Using Linear Regression and Polynomial Regression Methods

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