scholarly journals Country transition index based on hierarchical clustering to predict next COVID-19 waves

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ricardo A. Rios ◽  
Tatiane Nogueira ◽  
Danilo B. Coimbra ◽  
Tiago J. S. Lopes ◽  
Ajith Abraham ◽  
...  

AbstractCOVID-19 has widely spread around the world, impacting the health systems of several countries in addition to the collateral damage that societies will face in the next years. Although the comparison between countries is essential for controlling this disease, the main challenge is the fact of countries are not simultaneously affected by the virus. Therefore, from the COVID-19 dataset by the Johns Hopkins University Center for Systems Science and Engineering, we present a temporal analysis on the number of new cases and deaths among countries using artificial intelligence. Our approach incrementally models the cases using a hierarchical clustering that emphasizes country transitions between infection groups over time. Then, one can compare the current situation of a country against others that have already faced previous waves. By using our approach, we designed a transition index to estimate the most probable countries’ movements between infectious groups to predict next wave trends. We draw two important conclusions: (1) we show the historical infection path taken by specific countries and emphasize changing points that occur when countries move between clusters with small, medium, or large number of cases; (2) we estimate new waves for specific countries using the transition index.

Author(s):  
Meg Miller

This review provides an overview of 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository compiled by the Johns Hopkins University Center for Systems Science and Engineering. It provides a background of how the repository was compiled, the data included and how the repo is being made use of in a Canadian academic library context.


Author(s):  
Nilson C. Roberty ◽  
Lucas S. F. de Araujo

Based on the SIR model that divides the population into susceptible, infected and removed individuals, data about the evolution of the pandemic compiled by the Johns Hopkins University Center for Systems Science and Engineering (JHUCSSE) are integrated into the numerical system solution. The system parameters Rate of Contact β, Basic Reproduction Number R0 and Removal Rate γ, also named Rate of Decay, are determined according to a ridge regression approach and a mobile statistical scheme with different averages. Data is automatically downloaded from https://raw.githubusercontent.com/CSSEGISandData/COVID-19. The main Python libraries used are Numpy, Pandas, Skit-Learn, Requests and Urllib.


2021 ◽  
Author(s):  
Duc Nguyen ◽  
Nghia Vo ◽  
Thinh Nguyen ◽  
Khuong Nguyen ◽  
Quang Nguyen ◽  
...  

Abstract From the end of 2019, one of the most serious and largest spread pandemics occurred in Wuhan (China) named Coronavirus (COVID-19). As reported by the World Health Organization, there are currently more than 100 million infectious cases with an average mortality rate of about five percent all over the world. To avoid serious consequences on people’s lives and the economy, policies and actions need to be suitably made in time. To do that, the authorities need to know the future trend in the development process of this pandemic. This is the reason why forecasting models play an important role in controlling the pandemic situation. However, the behavior of this pandemic is extremely complicated and difficult to be analyzed, so that an effective model is not only considered on accurate forecasting results but also the explainable capability for human experts to take action pro-actively. With the recent advancement of Artificial Intelligence (AI) techniques, the emerging Deep Learning (DL) models have been proving highly effective when forecasting this pandemic future from the huge historical data. However, the main weakness of DL models is lacking the explanation capabilities. To overcome this limitation, we introduce a novel combination of the Susceptible-Infectious-Recovered-Deceased (SIRD) compartmental model and Variational Autoencoder (VAE) neural network known as BeCaked. With pandemic data provided by the Johns Hopkins University Center for Systems Science and Engineering, our model achieves 0.98 R2 and 0.012 MAPE at world level with 31-step forecast and up to 0.99 R2 and 0.0026 MAPE at country level with 15-step forecast on predicting daily infectious cases. Not only enjoying high accuracy, but BeCaked also offers useful justifications for its results based on the parameters of the SIRD model. Therefore, BeCaked can be used as a reference for authorities or medical experts to make on-time right decisions.


Author(s):  
Musa Kamarul Imran ◽  
Wan Nor Ariffin ◽  
Mohd Mohd Hafiz ◽  
Subhi Jamiluddin ◽  
Noor Atinah Ahmad ◽  
...  

To quantify the time-varying reproduction number (Rt) for Malaysia using the COVID-19 incidence data., we used data the from the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus repository. Day 1 was taken from the first assumed local transmission of COVID-19. Data was split into four intervals: a) Interval 1: from Day 1 to Day 10 MCO 1, b) Interval 2: from Day 1 to Day 10 MCO 2, c) Interval 3: from Day 1 to Day 10 MCO 3 and d) Interval 4: from Day 1 to Day 10 MCO 4. We estimated the Rt using the EpiEstim package. The means for Rt at Day 1, Day 5 and Day 10 for all MCOs ranged between 0.665 to 1.147. The average Rt gradually decreased in MCO 1 and MCO 2. However, Rt increased in MCO 3 before stabilized around 0.8 in MCO 4. MCO 1 and MCO 2 which were stricter coincide with the gradual reduction of Rt. However, the more relaxed MCO 3 and MCO 4 correspond to a slight increase in the Rt before it stabilized.


Author(s):  
Kenneth Bitrus David ◽  
Naomi Thomas ◽  
Joan Kuyet Solomon

COVID-19 outbreak which originated from Wuhan, a city in China has spread to over 180 countries in the world, disrupting several sectors of the human life, and causing deaths. This unprecedented event has affected 55 countries in Africa in different ways. This study aims to outline the current epidemiological data of COVID-19 in Africa. The number of confirmed cases and deaths in Africa was obtained from COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. Mortality rate and daily cumulative index were calculated for each country. The mortality rate in Africa is low compared to other Continents regardless of the high Daily Cumulative Index recorded.


Author(s):  
Katherine Simbaña-Rivera ◽  
Lenin Gómez-Barreno ◽  
Jhon Guerrero ◽  
Fernanda Simbaña-Guaycha ◽  
Raúl Fernández ◽  
...  

AbstractBackgroundThe relentless advance of the SARS-CoV-2 virus pandemic has resulted in a significant burden on countries, regardless of their socio-economic conditions. The virus has infected more than 2.5 million people worldwide, causing to date more than 150,000 deaths in over 210 countries.ObjectiveThe aim of this study was to describe the trends in cases, tests and deaths related to novel coronavirus disease (COVID-19) in Latin American and Caribbean (LAC) countries.MethodologyData were retrieved from the WHO-Coronavirus Disease (COVID-2019) situation reports and the Center for Systems Science and Engineering (CSSE) databases from Johns Hopkins University. Descriptive statistics including death rates, cumulative mortality and incidence rates, as well as testing rates per population at risk were performed. A comparison analysis among countries with ≥50 confirmed cases was performed from February 26th, 2020 to April 8th, 2020.ResultsBrazil had the greatest number of cases and deaths in the region. Panama experienced a rapid increase in the number of confirmed cases with Trinidad and Tobago, Bolivia and Honduras having the highest case fatality rates. Panama and Chile conducted more tests per million inhabitants and more tests per day per million inhabitants, followed by Uruguay and El Salvador. Dominican Republic, Bolivia, Ecuador and Brazil had the highest positive test rates.ConclusionsThe COVID-19 disease pandemic caused by the SARS-CoV-2 virus has progressed rapidly in LAC countries. Some countries have been affected more severely than others, with some adopting similar disease control methods to help slow down the spread of the virus. With limited testing and other resources, social distancing is needed to help alleviate the strain on already stretched health systems.


Author(s):  
Federick Jonathan ◽  
Magdalena Ariance Ineke Pakereng

Dalam pengembangan perangkat lunak, terdapat banyak teknik dan pendekatan yang digunakan untuk menghasilkan perangkat lunak yang handal. Kualitas perangkat lunak sangat bergantung pada pengujian perangkat lunak. Namun tidak semua pengembang peduli dengan tahapan pengujian pada sebuah perangkat lunak. Penelitian ini bertujuan untuk mengetahui pengaruh dari menerapkan proses pengujian dalam mengembangkan perangkat lunak dengan menggunakan metode TDD. Pada Metode TDD, pengembangan perangkat lunak dimulai dengan menulis test case terlebih dahulu lalu kemudian menulis kode. Pada artikel ini, dikembangkan aplikasi mobile dengan menerapkan metode TDD. Perangkat lunak yang dikembangkan adalah berupa sistem informasi mengenai data laporan kasus COVID-19. Data diambil dari Johns Hopkins University The Center of Systems Science and Engineering (JHU CSSE). Hasil penerapan metode TDD menunjukkan bahwa fungsi dan fitur dari perangkat lunak yang dibangun dapat bekerja dan terintegrasi dengan baik antar satu sama lain. Kode yang dihasilkan dari penerapan TDD juga menjadi rapih karena dilakukannya proses refactoring. In Software Engineering, there are many techniques and approaches that can be used to build a reliable software. The quality of a software relies mostly on the software testing process. However, not many developers are bothered with the testing step of a software. The purpose of this article is to learn the results from implementing a testing process on software developmenty. In TDD, the development is started by writing test case first and then writing code. This article developed a mobile application by applying TDD in the process. The android application that had been developed is an information system about report cases on COVID-19. The cases are coming from Johns Hopkins University The Center of Systems Science and Engineering (JHU CSSE). The result of using TDD in development proves that all functions and features of the developed application are working and integrated well.


1986 ◽  
Vol 25 (1) ◽  
pp. 93-95
Author(s):  
Najam-us- Saqib

Jamaica, known in the world for her rich deposits of bauxite ore, is a small Caribbean country with an area of 10991 square kilometers and a population of just over two million individuals. This beautifu11and, which was described by Columbus as "The fairest isle that eyes have beheld" has developed a remarkably diversified manufacturing sector starting from a modest industrial base. Jamaica's manufacturing industry enjoyed a respectable growth rate of about 6 percent per annum during the good old days of the euphoric '50s and '60s. However, those bright sunny days ''when to live was bliss" were followed by the chilling winter of much subdued progress. The rise and fall of growth have aroused considerable interest among economists and policy• makers. The book under review probes the causes of this behaviour by analysing key characteristics of Jamaican manufacturing sector and tracing its path of evolution.


1982 ◽  
Vol 21 (3) ◽  
pp. 255-257
Author(s):  
Zafar Mahmood

The world in its politico-economic aspects is run by policy-makers who have an academic background in law or public administration or other related social disciplines including economics. Only rarely would a majority of the policy-makers be trained in economics. In the making of economic policy, the basic choices before the policy-makers are political and they transcend the narrow concerns of economists regarding optimal use of resources. These considerations in no way downgrade the relevance of economic analysis in economic policy-making and for the training of policy-maker in economics. Policy-makers need economic council to understand fully the implications of alternative policy options. In this book, Wolfson attempts to educate policy-makers in the areas of public finance and development strategy. The analysis avoids technicalities and is kept to a simple level to make it understandable to civil servants, law-makers and members of the executive branch whom Wolfson refers to as policy-makers. Simplicity of analysis is not the only distinguishing mark of this book. Most other books on public finance are usually addressed to traditional public finance issues relating to both the revenue and expenditure sides of the budget and neglect an overall mix of issues dealing with the interaction of fiscal policy with economic development. Wolfson in this book explicitly deals with these issues.


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