scholarly journals Real-time neural network based predictor for cov19 virus spread

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243189
Author(s):  
Michał Wieczorek ◽  
Jakub Siłka ◽  
Dawid Połap ◽  
Marcin Woźniak ◽  
Robertas Damaševičius
Keyword(s):  
Prediction Model ◽  
Real Time ◽  
Prediction Models ◽  
Numerical Data ◽  
Real Data ◽  
Future Trend ◽  
World Health ◽  
Number Of Patients ◽  
The World ◽  
Health Organization

Since the epidemic outbreak in early months of 2020 the spread of COVID-19 has grown rapidly in most countries and regions across the World. Because of that, SARS-CoV-2 was declared as a Public Health Emergency of International Concern (PHEIC) on January 30, 2020, by The World Health Organization (WHO). That’s why many scientists are working on new methods to reduce further growth of new cases and, by intelligent patients allocation, reduce number of patients per doctor, what can lead to more successful treatments. However to properly manage the COVID-19 spread there is a need for real-time prediction models which can reliably support various decisions both at national and international level. The problem in developing such system is the lack of general knowledge how the virus spreads and what would be the number of cases each day. Therefore prediction model must be able to conclude the situation from past data in the way that results will show a future trend and will possibly closely relate to the real numbers. In our opinion Artificial Intelligence gives a possibility to do it. In this article we present a model which can work as a part of an online system as a real-time predictor to help in estimation of COVID-19 spread. This prediction model is developed using Artificial Neural Networks (ANN) to estimate the future situation by the use of geo-location and numerical data from past 2 weeks. The results of our model are confirmed by comparing them with real data and, during our research the model was correctly predicting the trend and very closely matching the numbers of new cases in each day.

scholarly journals Visual Data Analysis and Simulation Prediction for COVID-19 in Saudi Arabia Using SEIR Prediction Model

2021 ◽  
Vol 17 (08) ◽  
pp. 154
Author(s):  
Shakir Khan
Keyword(s):  
Machine Learning ◽  
Saudi Arabia ◽  
Prediction Models ◽  
Preventive Measures ◽  
Future Trend ◽  
Control Measures ◽  
World Health ◽  
Seir Model ◽  
The World ◽  
Health Organization

<p>The World Health Organization (WHO) reported the COVID-19 epidemic a global health emergency on January 30 and confirmed its transformation into a pandemic on March 11. China has been the hardest hit since the virus's outbreak, which may date back to late November. Saudi Arabia realized the danger of the Coronavirus in March 2020, took the initiative to take a set of pre-emptive decisions that preceded many countries of the world, and worked to harness all capabilities to confront the outbreak of the epidemic. Several researchers are currently using various mathematical and machine learning-based prediction models to estimate this pandemic's future trend. In this work, the SEIR model was applied to predict the epidemic situation in Saudi Arabia and evaluate the effectiveness of some epidemic control measures, and finally, providing some advice on preventive measures.</p>

scholarly journals A PIECEWISE GROWTH MODEL FOR MODELING THE ACCUMULATED NUMBER OF COVID-19 CASES IN THE CITY OF CAMPO GRANDE

2021 ◽  
Vol 39 (1) ◽  
pp. 240
Author(s):  
Erlandson Ferreira SARAIVA ◽  
Leandro SAUER ◽  
Basílio De Bragança PEREIRA ◽  
Carlos Alberto de Bragança PEREIRA
Keyword(s):  
Growth Model ◽  
Health Department ◽  
World Health ◽  
Mathematical Study ◽  
Number Of Patients ◽  
Technical Report ◽  
The World ◽  
The Government ◽  
Health Organization ◽  
The City

In December of 2019, a new coronavirus was discovered in the city of Wuhan, China. The World Health Organization officially named this coronavirus as COVID-19. Since its discovery, the virus has spread rapidly around the world and is currently one of the main health problems, causing an enormous social and economic burden. Due to this, there is a great interest in mathematical models capable of projecting the evolution of the disease in countries, states and/or cities. This interest is mainly due to the fact that the projections may help the government agents in making decisions in relation to the prevention of the disease. By using this argument, the health department of the city (HDC) of Campo Grande asked the UFMS for the development of a mathematical study to project the evolution of the disease in the city. In this paper, we describe a modeling procedure used to fit a piecewise growth model for the accumulated number of cases recorded in the city. From the fitted model, we estimate the date in which the pandemic peak is reached and project the number of patients who will need treatment in intensive care units. Weekly, was sent to HDC a technical report describing the main results.

scholarly journals Predicting the Epidemiological Outbreak of the Coronavirus Disease 2019 (COVID-19) in Saudi Arabia

2020 ◽  
Vol 17 (12) ◽  
pp. 4568 ◽  
Author(s):  
Dabiah Alboaneen ◽  
Bernardi Pranggono ◽  
Dhahi Alshammari ◽  
Nourah Alqahtani ◽  
Raja Alyaffer
Keyword(s):  
Saudi Arabia ◽  
Real Time ◽  
World Health ◽  
Logistic Growth ◽  
Final Phase ◽  
Time Data ◽  
Local Prediction ◽  
The World ◽  
Real Time Data ◽  
Health Organization

The coronavirus diseases 2019 (COVID-19) outbreak continues to spread rapidly across the world and has been declared as pandemic by World Health Organization (WHO). Saudi Arabia was among the countries that was affected by the deadly and contagious virus. Using a real-time data from 2 March 2020 to 15 May 2020 collected from Saudi Ministry of Health, we aimed to give a local prediction of the epidemic in Saudi Arabia. We used two models: the Logistic Growth and the Susceptible-Infected-Recovered for real-time forecasting the confirmed cases of COVID-19 across Saudi Arabia. Our models predicted that the epidemics of COVID-19 will have total cases of 69,000 to 79,000 cases. The simulations also predicted that the outbreak will entering the final-phase by end of June 2020.

scholarly journals Epidemiological Models of SARS-CoV-2 (COVID-19) to Control the Transmission Based on Current Evidence: A Systematic Review

2020 ◽  
Author(s):  
Swati Arora ◽  
Rishabh Jain ◽  
Harendra Pal Singh
Keyword(s):  
Real Data ◽  
World Health ◽  
Current Evidence ◽  
Epidemiological Models ◽  
Medical Supplies ◽  
The World ◽  
The Usa ◽  
Novel Coronavirus ◽  
Health Organization ◽  
The Uk

In Wuhan city of China, an episode of novel coronavirus (COVID-19) happened. during late December and it has quickly spread to all places in the world. Until May 29, 2020, cases were high in the USA with 1.7 Million, Russia with approximately 387 thousand, the UK with 271 thousand confirmed cases. Everybody on the planet is anxious to know when the coronavirus pandemic will end. In this scourge, most nations force extreme medication measures to contain the spread of COVID-19. Modeling has been utilized broadly by every national government and the World Health Organization in choosing the best procedures to seek after in relieving the impacts of COVID-19. Many epidemiological models are studied to understand the spread of the illness and its prediction to find maximum capacity for human-to-human transmission so that control techniques can be adopted. Also, arrangements for the medical facilities required such as hospital beds and medical supplies can be made in advance. Many models are used to anticipate the results keeping in view the present scenario. There is an urgent need to study the various models and their impacts. In this study, we present a systematic literature review on epidemiological models for the outbreak of novel coronavirus in India. The epidemiological dynamics of COVID-19 is also studied. Here, In addition, an attempt to take out the results from the exploration and comparing it with the real data. The study helps to choose the models that are progressive and dependable to predict and give legitimate methods for various strategies.

scholarly journals WINNING THE WAR AGAINST COVID-19 IN MALAYSIA: AN ACHIEVABLE GOAL?

2020 ◽  
Vol 20 (1) ◽  
pp. 148-149
Author(s):  
Mohd Hafiz Jaafar ◽  
Amirah Azzeri
Keyword(s):  
Public Health ◽  
Public Health Emergency ◽  
World Health ◽  
Cumulative Number ◽  
Healthcare Resources ◽  
Epidemic Curve ◽  
Number Of Patients ◽  
The World ◽  
Achievable Goal ◽  
Health Organization

The World Health Organization (WHO) has initially categorised COVID-19 infection as a Public Health Emergency of International Concern (PHEIC) in late January 2020 and later on declared the outbreak as a pandemic on March 11, 2020. On February 4, 2020 the first Malaysian positive COVID-19 patients was detected. It was estimated through a thorough decision tree technique, cumulatively 22,000 positive patients were expected to be infected nationwide. At the current rate of disease detection, screening yield and clinical capacity in Malaysia, the identification of the positive patients will have to be continuously done until middle of May 2020. In addition, a prediction with the forecasted testing capacity was also conducted. In contrast with the earlier estimation, massive testing causes the number of positive patients to be saturated earlier, by the end of April 2020. Based on the projection, 346, 307 cumulative tests will be conducted with 225,100 cumulative positive cases will be identified. Of the numbers, the cumulative number of patients in care would be 17,631 with 705 cumulative number of admission to intensive care unit and 353 cumulative patients required for ventilator. The cumulative death and cumulative discharge are expected to be 394 and 6008 respectively. Currently, it is challenging for Malaysia to flatten the epidemic curve due to the constraints of healthcare resources. These challenges potentially highlight the need for realistic strategies with regard to the country’s capacity.

Units of Measure

2009 ◽  
Author(s):  
Phil B. Fontanarosa ◽  
Stacy Christiansen
Keyword(s):  
International System ◽  
Scientific Information ◽  
Numerical Data ◽  
World Health ◽  
Biomedical Publication ◽  
System Of Units ◽  
The World ◽  
Industry And Commerce ◽  
Biomedical Publications ◽  
Health Organization

The presentation of quantitative scientific information is an integral component of biomedical publication. Accurate communication of scientific knowledge and presentation of numerical data require a scientifically informative system for reporting units of measure. The International System of Units (Le Système International d'Unités or SI) represents a modified version of the metric system that has been established by international agreement and currently is the official measurement system of most nations of the world.1 The SI promotes uniformity of quantities and units, minimizes the number of units and multiples used in other measurement systems, and can express virtually any measurement in science, medicine, industry, and commerce. In 1977, the World Health Organization recommended the adoption of the SI by the international scientific community. Since then, many biomedical publications throughout the world have adopted SI units as their preferred and primary method for reporting scientific measurements...

scholarly journals SARS-CoV-2 in Pregnancy: A Comprehensive Summary of Current Guidelines

2020 ◽  
Vol 9 (5) ◽  
pp. 1521 ◽  
Author(s):  
Kavita Narang ◽  
Eniola R. Ibirogba ◽  
Amro Elrefaei ◽  
Ayssa Teles Abrao Trad ◽  
Regan Theiler ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
World Health ◽  
Limited Data ◽  
Global Pandemic ◽  
Serious Infection ◽  
Number Of Patients ◽  
The World ◽  
Health Organization ◽  
Current Guidelines ◽  
In Pregnancy

Since the declaration of the global pandemic of COVID-19 by the World Health Organization on 11 March 2020, we have continued to see a steady rise in the number of patients infected by SARS-CoV-2. However, there is still very limited data on the course and outcomes of this serious infection in a vulnerable population of pregnant patients and their fetuses. International perinatal societies and institutions including SMFM, ACOG, RCOG, ISUOG, CDC, CNGOF, ISS/SIEOG, and CatSalut have released guidelines for the care of these patients. We aim to summarize these current guidelines in a comprehensive review for patients, healthcare workers, and healthcare institutions. We included 15 papers from 10 societies through a literature search of direct review of society’s websites and their journal publications up till 20 April 2020. Recommendations specific to antepartum, intrapartum, and postpartum were abstracted from the publications and summarized into Tables. The summary of guidelines for the management of COVID-19 in pregnancy across different perinatal societies is fairly consistent, with some variation in the strength of recommendations. It is important to recognize that these guidelines are frequently updated, as we continue to learn more about the course and impact of COVID-19 in pregnancy.

Constrictive Pericarditis Associated with Coronavirus Disease 2019 (COVID-19): A Case Report

2020 ◽  
Vol 20 ◽  
Author(s):  
SeyedAhmad SeyedAlinaghi ◽  
Maryam Ghadimi ◽  
Mehrnaz Asadi Gharabaghi ◽  
Fereshteh Ghiasvand
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Constrictive Pericarditis ◽  
World Health ◽  
Respiratory Condition ◽  
Global Pandemic ◽  
Number Of Patients ◽  
The World ◽  
Progressive Respiratory Failure ◽  
Health Organization

: Since December 2019, there has been an increasing number of patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) around the world. As of March 2020, the World Health Organization declared a global pandemic. To our best knowledge, this is the first report of a patient with SARS-CoV-2 infection presenting with constrictive pericarditis, possibly from the COVID infection. She was presented after a week of fever, persistent dry cough, and diarrhea. She received a single dose of hydroxychloroquine 400 mg, Oseltamivir 75 mg every 12 hours, lopinavir/ritonavir (Kaletra) 400/100 mg every 12 hours, and levofloxacin 750 mg daily. After 24 hours, she was immediately transferred to the Intensive Care Unit (ICU) because of dyspnea and progressive respiratory failure with a drop of the O2 saturation to 70%. After a week of progress, her respiratory condition deteriorated again. She was re-admitted to the ICU and she expired. She died due to isolated constrictive pericarditis, most probably caused by SARS-CoV-2.

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