New Model for the COVID-19 Reported Cases and Deaths of Ghana in Accelerated Spread and Prediction of the Delayed Phase

2021 ◽  
pp. 7-26
Author(s):  
Bosson-Amedenu Senyefia ◽  
Acquah Joseph ◽  
Nyarko Christiana Cynthia ◽  
Osei Asibey Eunice ◽  
Oduro Okyireh Theodore ◽  
...  
Keyword(s):  
Optimization Techniques ◽  
Least Square ◽  
New Wave ◽  
Regression Methods ◽  
Inflection Points ◽  
Precautionary Measures ◽  
To Come ◽  
Modeling Strategy ◽  
Second Wave ◽  
Delayed Phase

There is an ongoing investigation on the transmission characteristics of COVID-19 with respect to country-based inflection points, nature of distribution and prediction of future trends. In this study, a new accelerated and delayed spread models for COVID-19 reported cases and deaths in Ghana were developed. Optimization techniques coupled with interpolations, least square and non-linear regression methods, to come out with an informed modeling strategy to predict the delayed spread for the case of Ghana were adopted. Derivative and tangent methods were also applied to determine inflection points for Ghana’s cases and death from COVID-19. The data used for the study covered the first 250 days of events and interventions of the pandemic in Ghana. It was realized that the distribution of the COVID-19 situation in Ghana followed an exponential distribution curve. A modification of the developed model to help optimize the error between observed and estimated values yielded an improvement in the prediction of the delayed phase. Our derived parameters revealed that transmission of the virus between phases depended on changes in the precautionary measures and peoples' behaviors. The study thus shows that Ghana passed her inflection point of reported cases on Sunday 19th July, 2020 and may currently be in the delayed phase characterized with a staggering trend where new infections similar in magnitude to previous infections may upsurge. The correlation between reported cases and deaths revealed linear dependence with positive deviation between accelerated and delayed phases. In conclusion, the study predicted the commencement of a new wave in Ghana after Wednesday October 28, 2020 with higher intensity than what was previously observed if timely impositions of interventions to minimize the effect of the second wave are not taken.

Does the second wave of COVID-19 undermine corporate immunity? International evidence

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huy Viet Hoang ◽  
Cuong Nguyen ◽  
Khanh Hoang
Keyword(s):  
Stock Returns ◽  
Stock Price ◽  
Fixed Effects ◽  
Management Strategies ◽  
The United States ◽  
Least Square ◽  
Content Type ◽  
The Impact ◽  
Second Wave ◽  
Practical Implications

PurposeThis study compares the impact of the COVID-19 pandemic on stock returns in the first two waves of infection across selected markets, given built-in corporate immunity before the global outbreak.Design/methodology/approachThe data are collected from listed firms in five markets that have experienced the second wave of COVID-19 contagion, namely the United States (US), Australia, China, Hong Kong and South Korea. The period of investigation in this study ranges from January 24 to August 28, 2020 to cover the first two COVID-19 waves in selected markets. The study estimates the research model by employing the ordinary least square method with fixed effects to control for the heterogeneity that may confound the empirical outcomes.FindingsThe analysis reveals that firms with larger size and more cash reserves before the COVID-19 outbreak have better stock performance under the first wave; however, these advantages impede stock resilience during the second wave. Corporate governance practices significantly influence stock returns only in the first wave as their effects fade when the second wave emerges. The results also suggest that in economies with greater power distance, although stock price depreciation was milder in the first wave, it is more intense when new cases again surge after the first wave was contained.Practical implicationsThis paper provides practical implications for corporate managers, policymakers and governments concerning crisis management strategies for COVID-19 and future pandemics.Originality/valueThis study is the first to evaluate built-in corporate immunity before the COVID-19 shock under successive contagious waves. Besides, this study accentuates the importance of cultural understanding in weathering the ongoing pandemic across different markets.

scholarly journals Epidemiological perspectives of COVID-19 in Telangana and India: a descriptive study design

2021 ◽  
Vol 8 (4) ◽  
pp. 1817
Author(s):  
Amruta Barhate ◽  
Prakash Bhatia
Keyword(s):  
Data Analysis ◽  
Study Design ◽  
Descriptive Study ◽  
Control Measures ◽  
Data Sources ◽  
Effective Control ◽  
Steady Increase ◽  
The World ◽  
To Come ◽  
Second Wave

Background: The COVID-19 pandemic has made the world to come to a standstill. What started as on 16th March 2020, as 114 confirmed cases of COVID‑19 in the country has now reached worrisome figures. The latest world scenario as per WHO as on 30th November, 2020 is as under-World data: 62,509,444 cases, deaths: 1,458,782; USA: 13,082,877 cases, deaths: 263,946; India: 9,431,691 cases, deaths 137, 139. It is evident that worldwide India is number two in case load and there’s no reason to prevent India from becoming number one unless appropriate corrective steps are taken.Methods: The present study has looked into various data sources available in public domain. The study covered a period of almost nine months i.e., from March 2020 to November 2020. The study revealed a steady increase in the number of COVID-19 cases from March 2020 with peak of pandemic occurring in the mid of September and then a steady decline of cases from October.Results: The data analysis shows that after peaking of cases in September, the epidemic will decline in a phased manner by the end of March 2021. Even though there is a decline seen from the month of October, spike of COVID-19 cases was seen in November in some of the states of India. Therefore, we can’t deny the possibility of a second wave of pandemic to occur in the month of December 2020 and January 2021.Conclusions: Hence appropriate and strict control measures have to be put in place for effective control of the Pandemic and its resurgence.

scholarly journals When All Products Are Digital: Complexity and Intangible Value in the Ecosystem of Digitizing Firms

MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1025-1058
Author(s):  
Pouya Rahmati ◽  
◽  
Ali Tafti ◽  
J. Christopher Westland ◽  
Cesar Hidalgo ◽  
...  
Keyword(s):  
Control Systems ◽  
Digital Technologies ◽  
Market Value ◽  
Positive Influence ◽  
Panel Regression ◽  
Tobin’S Q ◽  
Tobin's Q ◽  
Regression Methods ◽  
To Come ◽  
Do So

During the last four decades, digital technologies have disrupted many industries. Car control systems have gone from mechanical to digital. Telephones have changed from sound boxes to portable computers. But have the firms that digitized their products and services become more valuable than firms that didn’t? Here we introduce the construct of digital proximity, which considers the interdependent activities of firms linked in an economic network. We then explore how the digitization of products and services affects a company’s Tobin’s q—the ratio of market value over assets—a measure of the intangible value of a firm. Our panel regression methods and robustness tests suggest the positive influence of a firm’s digital proximity on its Tobin’s q. This implies that firms able to come closer to the digital sector have increased their intangible value compared to those that have failed to do so. These findings contribute a new way of measuring digitization and its impact on firm performance that is complementary to traditional measures of information technology (IT) intensity.

scholarly journals Age-stratified discrete compartment model of the COVID-19 epidemic with application to Switzerland

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Fadoua Balabdaoui ◽  
Dirk Mohr
Keyword(s):  
Infected Individual ◽  
Compartment Model ◽  
Policy Makers ◽  
Modern Health Care ◽  
Containment Measures ◽  
To Come ◽  
Second Wave ◽  
Important Basis ◽  
Day By Day ◽  
Model Based Analysis

AbstractCompartmental models enable the analysis and prediction of an epidemic including the number of infected, hospitalized and deceased individuals in a population. They allow for computational case studies on non-pharmaceutical interventions thereby providing an important basis for policy makers. While research is ongoing on the transmission dynamics of the SARS-CoV-2 coronavirus, it is important to come up with epidemic models that can describe the main stages of the progression of the associated COVID-19 respiratory disease. We propose an age-stratified discrete compartment model as an alternative to differential equation based S-I-R type of models. The model captures the highly age-dependent progression of COVID-19 and is able to describe the day-by-day advancement of an infected individual in a modern health care system. The fully-identified model for Switzerland not only predicts the overall histories of the number of infected, hospitalized and deceased, but also the corresponding age-distributions. The model-based analysis of the outbreak reveals an average infection fatality ratio of 0.4% with a pronounced maximum of 9.5% for those aged ≥ 80 years. The predictions for different scenarios of relaxing the soft lockdown indicate a low risk of overloading the hospitals through a second wave of infections. However, there is a hidden risk of a significant increase in the total fatalities (by up to 200%) in case schools reopen with insufficient containment measures in place.

scholarly journals An Empirical Investigation of Islamic Calendar Effect in Global Islamic Equity Indices

2017 ◽  
Vol 9 (6) ◽  
pp. 57 ◽  
Author(s):  
Nida Shah ◽  
Muhammad Nadeem Qureshi ◽  
Yasra Aslam
Keyword(s):  
Stock Returns ◽  
Empirical Investigation ◽  
Negative Impact ◽  
Least Square ◽  
Ordinary Least Square ◽  
Regression Methods ◽  
Significant Negative Impact ◽  
Equity Indices ◽  
The Impact ◽  
Global Stock

This study aims to explore the effect of Islamic Months specifically Ramadan and Zil-Haj on the stock returns and volatility of the Islamic Global Equity Indices. For the said purpose, the data on three Global Equity Islamic Indices including; Dow Jones Islamic Market World Index, MSCI ACWI Islamic Index, and S&P Global BMI Shariah Index are collected from 5th Jan 2011 (1st Muharram 1432 A.H.) to 12th November 2015 (30th Muharram 1437 A.H.). Ordinary Least Square (OLS) and GARCH (1,1) regression methods are applied to analyze the impact of the Islamic months on global stock returns and volatility respectively. Empirical results reveal significant negative impact of Zil-Haj on returns and volatility of Islamic Global Equity Indices. However, no significant impact of Ramadan on returns and volatility of Islamic Global Equity Indices are revealed. These findings will be fascinating and of utmost interest amidst the researchers, investors and practitioners.

Determine of Moisture Content for Rough Rice Single Kernel by Visible/NIR Spectroscopy

2014 ◽  
Vol 931-932 ◽  
pp. 1549-1554 ◽  
Author(s):  
Adcha Heman ◽  
Ching Lu Hsieh
Keyword(s):  
Moisture Content ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Regression Methods ◽  
Average Accuracy ◽  
Rough Rice ◽  
Calibration Models ◽  
Plsr Model

Moisture content (MC) of rough rice directly affects rice quality and its market value. This study applied spectroscopy both in visible 400-700 nm and NIR 700-1050 nm bands to record spectrum of rough rice single kernel (SK). Tainan No.11 medium rice randomly collected from field. After machine harvested, it was used in the tests and they were conditioned by oven to five MC levels ranging from 10.2 to 35.9%. Two regression methods, multiple linear regressions (MLR) and partial least square regression (PLSR), were applied to develop calibration models. Among 7 tested models were found that PLSR model of first differential with 21 gap points, which are rc=0.98, SEC=1.1% for calibration and rp=0.96, SEP=1.9% for prediction. The results suggested average accuracy for the best model was about 98.4% in 400-1050 nm wavelength.

‘Our bodies, our selves?’ The body as source in feminist theology

2007 ◽  
Vol 60 (3) ◽  
pp. 341-359 ◽  
Author(s):  
Jane Barter Moulaison
Keyword(s):  
Feminist Theology ◽  
The Body ◽  
Body Of Christ ◽  
Third Wave ◽  
Women's Bodies ◽  
Key Concepts ◽  
To Come ◽  
Beverly Harrison ◽  
Second Wave ◽  
The Church

AbstractThis article is, in part, an effort to come to terms with the ubiquitous celebration of embodiment in feminist discourse, and particularly within feminist theology. It will begin with a brief introduction to some of the key concepts in feminist theology and its use of the body, beginning with the body theologies of those who might now be called ‘second-wave’ theologians – Carter Heyward and Beverly Harrison. From here, I will consider postmodern feminist challenges to the reified and essentialised body as I examine what I call the subversive body in third-wave or postmodern feminism, both secular and theological. Finally, I shall move from these to an alternative construal of the importance of the body through the consideration of Christian bodily practices. Such an alternative will allow me to reflect upon what it is to become a specifically Christian body through church practices. I shall then endeavour to return to the critical concerns raised by feminism about the subjugation of women's bodies in the church as I consider the resources that might be available within the tradition itself for critical and emancipatory practices toward women and other strangers within the Body of Christ.

scholarly journals Covid-19: a catalyst for cybercrime?

2021 ◽  
Author(s):  
Mohamed Bou Sleiman ◽  
Simon Gerdemann
Keyword(s):  
Criminal Law ◽  
New Wave ◽  
The World ◽  
Second Wave

AbstractWhile the second wave of the Covid-19 pandemic is keeping the world on tenterhooks, the last few months have also led to a new wave of cybercrime. The following article analyzes the background and manifestations of pandemic-related cybercrimes and shows how our criminal law systems are able to deal with current challenges in the age of the coronavirus.

scholarly journals Comparison of six different soft computing methods in modeling evaporation in different climates

2016 ◽  
Author(s):  
Lunche Wang ◽  
Ozgur Kisi ◽  
Mohammad Zounemat-Kermani ◽  
Yiqun Gan
Keyword(s):  
Soft Computing ◽  
Computing Methods ◽  
Least Square ◽  
Support Vector ◽  
Climatic Data ◽  
Regression Methods ◽  
Soft Computing Techniques ◽  
Soft Computing Methods ◽  
Fuzzy Genetic ◽  
Different Climates

Abstract. Evaporation plays important roles in regional water resources management,terrestrial ecological process and regional climate change. This study investigated the abilities of six different soft computing methods, Multi-layer perceptron (MLP), generalized regression neural network (GRNN), fuzzy genetic (FG), least square support vector machine (LSSVM), multivariate adaptive regression spline (MARS), adaptive neuro-fuzzy inference systems with grid partition (ANFIS-GP), and two regression methods, multiple linear regression (MLR) and Stephens and Stewart model (SS) in predicting monthly Ep. Long-term climatic data at eight stations in different climates, air temperature (Ta), solar radiation (Rg), sunshine hours (Hs), relative humidity (RH) and wind speed (Ws) during 1961–2000 are used for model development and validation. The first part of applications focused on testing and comparing the model accuracies using different local input combinations. The results showed that the models have different accuracies in different climates and the MLP model performed superior to the other models in predicting monthly Ep at most stations, while GRNN model performed better in Tibetan Plateau. The accuracies of above models ranked as: MLP, GRNN, LSSVM, FG, ANFIS-GP, MARS and MLR. Generalized models were also developed and tested with data of eight stations. The overall results indicated that the soft computing techniques generally performed better than the regression methods, but MLR and SS models can be more preferred at some climatic zones instead of complex nonlinear models, for example, the BJ, CQ and HK stations.

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