scholarly journals Modeling and analysis of COVID-19 new deaths using tree-based ensemble

2021 ◽  
Author(s):  
Ibrahim Abaker Targio Hashem ◽  
Raja Sher Afgun Usmani ◽  
Asad Ali Shah ◽  
Abdulwahab Ali Almazroi ◽  
Muhammad Bilal
Keyword(s):  
Infectious Disease ◽  
United States ◽  
Random Forest ◽  
Economic Activity ◽  
The United States ◽  
Gradient Boosting ◽  
Health Crisis ◽  
Modeling And Analysis ◽  
Extreme Gradient Boosting ◽  
The World

The COVID-19 pandemic has emerged as the world's most serious health crisis, affecting millions of people all over the world. The majority of nations have imposed nationwide curfews and reduced economic activity to combat the spread of this infectious disease. Governments are monitoring the situation and making critical decisions based on the daily number of new cases and deaths reported. Therefore, this study aims to predict the daily new deaths using four tree-based ensemble models i.e., Gradient Tree Boosting (GB), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Voting Regressor (VR) for the three most affected countries, which are the United States, Brazil, and India. The results showed that VR outperformed other models in predicting daily new deaths for all three countries. The predictions of daily new deaths made using VR for Brazil and India are very close to the actual new deaths, whereas the prediction of daily new deaths for the United States still needs to be improved.<br>

scholarly journals Modeling and analysis of COVID-19 new deaths using tree-based ensemble

2021 ◽  
Author(s):  
Ibrahim Abaker Targio Hashem ◽  
Raja Sher Afgun Usmani ◽  
Asad Ali Shah ◽  
Abdulwahab Ali Almazroi ◽  
Muhammad Bilal
Keyword(s):  
Infectious Disease ◽  
United States ◽  
Random Forest ◽  
Economic Activity ◽  
The United States ◽  
Gradient Boosting ◽  
Health Crisis ◽  
Modeling And Analysis ◽  
Extreme Gradient Boosting ◽  
The World

The COVID-19 pandemic has emerged as the world's most serious health crisis, affecting millions of people all over the world. The majority of nations have imposed nationwide curfews and reduced economic activity to combat the spread of this infectious disease. Governments are monitoring the situation and making critical decisions based on the daily number of new cases and deaths reported. Therefore, this study aims to predict the daily new deaths using four tree-based ensemble models i.e., Gradient Tree Boosting (GB), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Voting Regressor (VR) for the three most affected countries, which are the United States, Brazil, and India. The results showed that VR outperformed other models in predicting daily new deaths for all three countries. The predictions of daily new deaths made using VR for Brazil and India are very close to the actual new deaths, whereas the prediction of daily new deaths for the United States still needs to be improved.<br>

Keeping the flu at bay: Methods for detecting and containing infectious disease

2009 ◽  
Vol 7 (4) ◽  
pp. 9
Author(s):  
Atresha Karra, JD ◽  
Emily Cornette, JD
Keyword(s):  
Infectious Disease ◽  
United States ◽  
Disease Control ◽  
The United States ◽  
Communicable Diseases ◽  
World Health ◽  
Reporting Requirements ◽  
The World ◽  
Control And Prevention ◽  
Health Organization

This article focuses on the existing methods for tracking and restricting the spread of communicable diseases, both within United States borders and across nations. It will first describe the roles played by the United States’ Centers for Disease Control and Prevention and the World Health Organization and will then explore how communicable diseases across the world are identified and monitored. This will be followed by a discussion of US and world reporting requirements and methods. Finally, the article will discuss the tactics used by the United States to control the spread of disease.

Observations on the Structure of World Trade and Payments

1956 ◽  
Vol 8 (4) ◽  
pp. 534-559
Author(s):  
Herbert B. Woolley
Keyword(s):  
United States ◽  
Economic Activity ◽  
Foreign Relations ◽  
The United States ◽  
American People ◽  
Economic Policies ◽  
Economic Relations ◽  
The World ◽  
Systematic Understanding ◽  
The Impact

EVENTS intimately linked to our foreign relations have profoundly affected the level of economic activity in the United States and the character of our economic progress and stability. They cannot be disregarded by those concerned with the level of economic activity in this country. Furthermore, those concerned with the economic policies of the United States must also be concerned with the impact of those policies upon the rest of the world because of the great importance of the United States in the world economy, and because of the link between economic, political, and military events at home and abroad. Since the United States cannot ignore the far-reaching and indirect effect of its policies and decisions, the American people and their government require a detailed and systematic understanding of the economic interrelationships among all countries of the world. Even more, to exercise the international leadership which our great size and resources impose upon us, we must be in a position to assess the effect of developments and actions everywhere upon the political and economic strength of the free world. This article considers a few of the salient features of world economic relations which should always be kept in mind in assessing economic policy alternatives.

scholarly journals IMPACT OF COVID 19 ON THE INDIAN STOCK MARKET

2021 ◽  
Vol 23 (07) ◽  
pp. 1085-1090
Author(s):  
Harsh Vikram Arora ◽  
Keyword(s):  
United States ◽  
Stock Market ◽  
Financial Markets ◽  
Stock Price ◽  
Stock Exchange ◽  
The United States ◽  
World Health ◽  
Health Crisis ◽  
The World ◽  
The Impact

The COVID19 pandemic which came unprecedentedly has brought forward a lot of confusion and unrest in the world. There are a lot of changes with regard to the global landscape in multiple ways. SARS-CoV-2 is the primary virus, which is the root contributor to the COVID19 outbreak, which started in Wuhan, Hubei Province, China, in December 2019. It did not take much time to spread across the world. This pandemic has resulted in a universal health crisis, along with a major decline in the global economy. One of the major reasons for the fluctuation in the stock price is supply and demand. When the number of people who want to sell their stocks outnumbers those who want to purchase it, the stock price drops. Due to the result in the gap, the financial markets will suffer in the short duration, but in the long run, markets will correct themselves and would increase again. There is a sharp decline in the stock price because of the pandemic. The current scenario has resulted in a world health crisis which has contributed to global and economic crises. Almost all financial markets across the world have been affected by the recent health crisis, with stock and bond values falling gradually and severely. In the United States, the Dow Jones and S& P 500 indices have fallen by more than 20%. The Shanghai Stock Exchange and the New York Dow Jones Stock Exchange both indicate that they had a significant impact on China’s and the United States’ financial markets. The primary purpose of this paper is to determine the impact of COVID19 on stock markets. The rapid spread of the virus has left a major impact on the global financial markets. There is a link between the pandemic and the stock market, and this has been studied in this paper. Along with it, an attempt is taken to compare stock price returns in pre-COVID19 and post-COVID19 scenarios. The stock market in India faced uncertainty during the pandemic, according to the findings.

scholarly journals Prediction of West Nile Virus using Ensemble Classifiers

2019 ◽  
Vol 9 (1) ◽  
pp. 3744-3749
Keyword(s):  
West Nile Virus ◽  
Random Forest ◽  
Learning Algorithm ◽  
Traditional Approach ◽  
The United States ◽  
Gradient Boosting ◽  
Ensemble Classifiers ◽  
Human Beings ◽  
West Nile ◽  
Extreme Gradient Boosting

West Nile Virus (WNV) is a disease caused by mosquitoes where human beings get infected by the mosquito’s bite. The disease is considered to be a serious threat to the society especially in the United States where it is frequently found in localities having water bodies. The traditional approach is to collect the traps of mosquitoes from a locality and check whether they are infected with virus. If there is a virus found then that locality is sprayed with pesticides. But this process is very time consuming and requires a lot of financial support. Machine learning methods can provide an efficient approach to predict the presence of virus in a locality using data related to the location and weather. This paper uses the dataset present in Kaggle which includes information related to the traps found in the locality and also about the information related to the locality’s weather. The dataset is found to be imbalanced hence Synthetic Minority Over sampling Technique (SMOTE), an upsampling method, is used to sample the dataset to balance it. Ensemble learning classifiers like random forest, gradient boosting and Extreme Gradient Boosting (XGB). The performance of ensemble classifiers is compared with the performance of the best supervised learning algorithm, SVM. Among the models, XGB gave the highest F-1 score of 92.93 by performing marginally better than random forest (92.78) and also SVM (91.16).

scholarly journals Amend Pandemic Preparedness Legislation to Prioritize Diagnostic Test Development and Deployment

2020 ◽  
Vol 17 (02) ◽  
Author(s):  
Grace Chesmore ◽  
Kelsey Diffley ◽  
Lirong Shi
Keyword(s):  
United States ◽  
Economic Impact ◽  
Diagnostic Test ◽  
Diagnostic Testing ◽  
The United States ◽  
Rapid Testing ◽  
Pandemic Preparedness ◽  
Health Crisis ◽  
The World ◽  
Federal Response

As the world becomes increasingly globalized, the propensity of pandemics, such as COVID-19, increases. The United States Pandemic and All-Hazards Preparedness and Advancing Innovation Act of 2019 (PAHPAI) details the federal response to a health crisis including pandemics. The PAHPAI has hindered the nation’s response to COVID-19 due to its lack of emphasis on diagnostic testing (Burr 2019). Rapid testing is critical to slowing the spread of this disease. Ample testing will identify infected populations and will allow communities to take necessary precautions such as staying home and avoiding contact with others. Widespread shelter in place would not be necessary to control the spread of the virus, therefore reducing the economic impact of the pandemic. We propose Congress amends the PAHPAI to institute an improved testing response for future pandemics.

The Contagion Next Time

2021 ◽  
Author(s):  
Sandro Galea
Keyword(s):  
United States ◽  
Global Health ◽  
Public Good ◽  
Socioeconomic Inequality ◽  
The United States ◽  
Poor Health ◽  
Health Crisis ◽  
The World ◽  
American Society

In a few short months, COVID-19 devastated the world and, in particular, the United States. Yet America was already in poor health before COVID-19 appeared. Racism, marginalization, socioeconomic inequality—the failure to address these forces left America vulnerable to COVID-19 and the ensuing global health crisis it became. This book articulates the foundational forces shaping health in American society and how they can be strengthened to prevent the next outbreak from becoming a pandemic. Because while no one could have predicted that a pandemic would strike when it did, we did know that a pandemic would strike, sooner or later. The book challenges Americans to tackle the deep-rooted obstacles preventing them from becoming a truly vibrant and equitable nation, reminding them of what they seemed to have forgotten: that health is a public good worth protecting.

Chapter II. The World Economy

1982 ◽  
Vol 100 ◽  
pp. 51-64
Keyword(s):  
United States ◽  
Economic Activity ◽  
World Economy ◽  
The United States ◽  
Oecd Countries ◽  
Total Output ◽  
The World

In the United States in particular, the long-awaited upturn in economic activity has been further postponed even though inflation has been running below the rates that had generally been expected. Industry in the OECD countries may well have produced less in the first quarter of 1982 than in any quarter of 1981, and we no longer expect their total output to increase by more than about ½ per cent for the year.

Conclusion: Summary and Recommendations

CNS Spectrums ◽  
2008 ◽  
Vol 13 (S10) ◽  
pp. 13-14 ◽  
Author(s):  
John W. Newcomer ◽  
Henry A. Nasrallah ◽  
Roger S. McIntyre ◽  
Charles H. Hennekens ◽  
Suzanne Vogel-Scibilia
Keyword(s):  
Infectious Disease ◽  
United States ◽  
Cardiovascular Disease ◽  
Cause Of Death ◽  
Metabolic Disorders ◽  
Developed Countries ◽  
The United States ◽  
Special Population ◽  
The Us ◽  
The World

Cardiovascular disease (CVD) remains the number one cause of death in the United States and most developed countries and is expected to remain so for much of this century. Rates of obesity have increased 2–4-fold over the last 2 decades in the US and this condition is linked with early development of hypertension, hyperlipidemia, diabetes, and atherosclerosis. The prevalence of diabetes is also increasing, and the rise of diabetes in young people 18–29 years of age was 40% in the period between 1990 and 2001. The World Heart Federation (WHF) has estimated that CVD will become the number one cause of death in the world by 2020, surpassing infectious disease in developing countries. Metabolic disorders are on the rise in general. However, as highlighted in the discussions presented in this supplement, patients with serious mental illness appear to represent a special population who are particularly vulnerable, with rates that surpass the general population.

scholarly journals Exploring temporal varying demographic and economic disparities in COVID-19 infections in four U.S. areas: based on OLS, GWR, and random forest models

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Junfeng Jiao ◽  
Yefu Chen ◽  
Amin Azimian
Keyword(s):  
Public Health ◽  
United States ◽  
Random Forest ◽  
The United States ◽  
Ordinary Least Squares ◽  
Public Health Services ◽  
Health Crisis ◽  
Economic Disparities ◽  
Random Forest Models ◽  
Recovery Resources

AbstractAlthough studies have previously investigated the spatial factors of COVID-19, most of them were conducted at a low resolution and chose to limit their study areas to high-density urbanized regions. Hence, this study aims to investigate the economic-demographic disparities in COVID-19 infections and their spatial-temporal patterns in areas with different population densities in the United States. In particular, we examined the relationships between demographic and economic factors and COVID-19 density using ordinary least squares, geographically weighted regression analyses, and random forest based on zip code-level data of four regions in the United States. Our results indicated that the demographic and economic disparities are significant. Moreover, several areas with disadvantaged groups were found to be at high risk of COVID19 infection, and their infection risk changed at different pandemic periods. The findings of this study can contribute to the planning of public health services, such as the adoption of smarter and comprehensive policies for allocating economic recovery resources and vaccines during a public health crisis.

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