CITIES 2022 Preface

CITIES International Conference is an annual international conference organized by the Urban and Regional Planning Department of Institut Teknologi Sepuluh Nopember (ITS Surabaya). The conference, which debuted in 2005, serves as a platform for academics and practitioners to present, disseminate, and discuss research results in the field of urban and regional planning. Through the efforts of all involved, CITIES has grown from a primarily national conference to one that attracts a diverse, worldwide audience from the Asian, European, Australian, and American continents.CITIES International Conference 2022 will focus on the theme "Future Challenges of the System of Cities”. This theme is important because cities do not grow in isolation, but have interdependent relationships with regions, countries and continents on a larger scale. These relationships must be studied in depth to ensure that urban areas can grow evenly without causing negative effect in the surrounding area. Additionally, this theme also prompts us to examine why production and consumption activities are concentrated or distributed in urban areas of different sizes and compositions. Furthermore, this theme also leads us to explore why the gap between cities, in terms of both skills to income, must be addressed in a measured and careful manner.With this need in mind, CITIES International Conference 2022 is designed to be a meeting place for stakeholders, including academics, researchers, practitioners and bureaucrats, both within and beyond national boundaries. The conference aims to disseminate research results and practical experiences at local, national and global levels, and to share insight and recommendations on improving the quality of city system in the future.CITIES International Conference 2022 was organized in collaboration with the World Planning School Congress (WPSC) and the Asian Planning School Association (APSA) as a joint congress from August 30th to September 2nd, 2022. Due to the COVID-19 pandemic and travel restrictions caused by high numbers of cases, especially in Indonesia, the event was held virtually using the Zoom platform.List of Sponsor Funding Acknowledgements, Committees, Rundown Cities International Conference 2022 "Future Challenges of the System Of Cities”, Conference Photograps are available in this Pdf.

National approaches for citizen data management in response to COVID-19: An overview and implications of contact tracing apps in 21 countries

The COVID-19 pandemic brings the topic of citizen data management (CDAMA) into the public eye. This study is one of the first attempts to analyze the national approaches for CDAMA applied by governments of different countries and continents in public sectors. The study first conducts a systematic overview of the representative contact tracing apps in 21 countries of four continents, collecting information of the four aspects of the CDAMA system. It then summarizes and analyzes the various governments' approaches to the CDAMA system applied by different countries and continents based on the app overview. We found that governments' priority between national safety (i.e., public health in this study) and citizen privacy is different in terms of their national approaches for CDAMA. For example, governments of Asian countries are more intrusive and hold a stricter attitude in their national CDAMA approach than countries elsewhere. Our study has contributions both theoretically and practically. Theoretically, it fills the literature gap about data management by discussing the data management in governments;practically, the study provides the background information as well as implications for future debates and discussions on governments' data management system and citizen data use.

Europe: Continent Of Conspiracies. Conspiracy Theories In And About Europe

Overall, the book illustrates how Europe's constructed others - and notably our very understanding of the idea of Europe (and not-Europe) - has historically been and is still being shaped through conspiracy theories. Various chapters, particularly those written by Eirikur Bergmann and by Estrella Gualda - which are, respectively, about the "Eurabia Conspiracy Theory" and about the 'Metaphors of Invasion and how Europe is imagined as endangered by Islamisation' - explore the position of Islam as the absolute "other" in different conspiracy theories I à la i Great Replacement. This amalgam is not only increasingly active in the streets and in the Internet, but also in the European Union (EU) Parliament and in the national and regional parliaments of the member states. [Extracted from the article]

Explainable features responsible for the high or low spread of SARS-CoV-2: Africa in view.

The low spread of the global pandemic in Africa has raised concerns. Consequently, many commentators have misconstrued concerns suspecting weather, and immunity to be prime reasons. This study investigates the factors associated with the high and low spread of the SARS-CoV-2 (also known as COVID-19) and employs graphical Bayesian models to investigate feature interactions and causality. Through experimentation with the Bayesian framework, we propose that: (i) the proportion of people within the country population who test positive for SARS-CoV-2 and a country's test capacity cause the rate of spread of the virus [i.e., P(S|P) and P(S|T)] (ii) poverty gaps, welfare and freedom of the press directly cause the spread of the virus [i.e., P(S|E), P(S|W), and P(S|R)] (iii) Government effectiveness serves as a parent to poverty gaps and welfare [ i.e., P(E|G) and P(W|G)] and voice and accountability serve as a parent to freedom of the press [i.e., P(R|V)]. For the output, we "dichotomized" regions based on the "share of global infection rate" metric (SGIR) that implicitly accounts for a given region's population, and we find that - out of two hundred and nineteen countries investigated, one hundred and twenty-seven have SGIR ≥ 1%, and the majority (44 out 58 - 75.86%) of Africa countries (as of 12th February 2021) have SGIR < 1%. With Africa in the mirror, the study shows that only 2.2% of the Africa population has been tested for SARS-CoV-2 and finds that the low proportion of population tested [i.e., P(S|P)] for SARS-CoV-2 is the cause of the low spread (i.e., cases reported) of SARS-CoV-2 in Africa. Similarly, the fragmented socioeconomic statuses [i.e., P(S|E)] among citizens leads to socioeconomic distancing, causing socio-class gaps between the rich and poor/average citizens, ensuring low interaction in social space, thus limiting the spread.

Analysis of the Effects of Lockdown on Staff and Students at Universities in Spain and Colombia Using Natural Language Processing Techniques.

The aim of this study is to analyze the effects of lockdown using natural language processing techniques, particularly sentiment analysis methods applied at large scale. Further, our work searches to analyze the impact of COVID-19 on the university community, jointly on staff and students, and with a multi-country perspective. The main findings of this work show that the most often related words were "family", "anxiety", "house", and "life". Besides this finding, we also have shown that staff have a slightly less negative perception of the consequences of COVID-19 in their daily life. We have used artificial intelligence models such as swivel embedding and a multilayer perceptron as classification algorithms. The performance that was reached in terms of accuracy metrics was 88.8% and 88.5% for students and staff, respectively. The main conclusion of our study is that higher education institutions and policymakers around the world may benefit from these findings while formulating policy recommendations and strategies to support students during this and any future pandemics.

COVID-19 challenges and employees' stress: mediating role of family-life disturbance and work-life imbalance

Purpose: The paper focuses on examining the relationship between challenges caused by COVID-19 pandemic and employees' stress through the mediating role of family-life disturbance and work-life imbalance. Design/methodology/approach: A total of 1,556 respondents from 45 countries across all continents were included in this survey. Statistical techniques such as exploratory factor analysis (EFA), confirmatory factor analysis (CFA), correlations, multiple regression and bootstrapping were used to analyse the data. Findings: The results depicted that COVID-19 challenges induced stress among employees. In combination with this, family-life disturbance and work-life imbalance mediated the relationship between COVID-19 challenges and employees' stress individually as well as serially. The paper further suggests some recommendations to mitigate the impact of COVID-19 challenges on employees' stress. Research limitations/implications: The major limitation of the study was in the data collection process. As the data were collected during the time period of pandemic, so, limited respondents were approached. Also, the international and cross-sectional design of the study can limit the applicability of the results. Practical implications: The study suggests organizations and HR managers to help in balancing family and work-life of employees, so that their mind can be kept stress free. Originality/value: The study has added knowledge to the existing literature of stress created due to the COVID-19 pandemic by explaining the serial mediation of family-life disturbance and work-life imbalance between the relationship of COVID-19 challenges and employees' stress. © 2022, Emerald Publishing Limited.

COVID-19 Vaccine Acceptance among Social Media Users: A Content Analysis, Multi-Continent Study

Vaccine hesitancy (VH) is defined as a delayed in acceptance or refusal of vaccines despite availability of vaccination services. This multinational study examined user interaction with social media about COVID-19 vaccination. The study analyzed social media comments in 24 countries from five continents. In total, 5856 responses were analyzed;83.5% of comments were from Facebook, while 16.5% were from Twitter. In Facebook, the overall vaccine acceptance was 40.3%;the lowest acceptance rates were evident in Jordan (8.5%), Oman (15.0%), Senegal (20.0%) and Morocco (20.7%) and the continental acceptance rate was the lowest in North America 22.6%. In Twitter, the overall acceptance rate was (41.5%);the lowest acceptance rate was found in Oman (14.3%), followed by USA (20.5%), and UK (23.3%) and the continental acceptance rate was the lowest in North America (20.5%), and Europe (29.7%). The differences in vaccine acceptance across countries and continents in Facebook and Twitter were statistically significant. Regarding the tone of the comments, in Facebook, countries that had the highest number of serious tone comments were Sweden (90.9%), USA (61.3%), and Thailand (58.8%). At continent level, serious comments were the highest in Asia (58.4%), followed by Africa (46.2%) and South America (46.2%). In Twitter, the highest serious tone was reported in Egypt (72.2%) while at continental level, the highest proportion of serious comments was observed in Asia (59.7%), followed by Europe (46.5%). The differences in tone across countries and continents in Facebook and Twitter and were statistically significant. There was a significant association between the tone and the position of comments. We concluded that the overall vaccine acceptance in social media was relatively low and varied across the studied countries and continents. Consequently, more in-depth studies are required to address causes of such VH and combat infodemics.

Analysis of the Effects of Lockdown on Staff and Students at Universities in Spain and Colombia Using Natural Language Processing Techniques

The aim of this study is to analyze the effects of lockdown using natural language processing techniques, particularly sentiment analysis methods applied at large scale. Further, our work searches to analyze the impact of COVID-19 on the university community, jointly on staff and students, and with a multi-country perspective. The main findings of this work show that the most often related words were “family”, “anxiety”, “house”, and “life”. Besides this finding, we also have shown that staff have a slightly less negative perception of the consequences of COVID-19 in their daily life. We have used artificial intelligence models such as swivel embedding and a multilayer perceptron as classification algorithms. The performance that was reached in terms of accuracy metrics was 88.8% and 88.5% for students and staff, respectively. The main conclusion of our study is that higher education institutions and policymakers around the world may benefit from these findings while formulating policy recommendations and strategies to support students during this and any future pandemics.

The Clustering Structure of the COVID-19 Outbreak in Global Scale

Spreading of novel coronavirus disease started in China and moved to Korea and Japan, then several countries in Europe, and the last step to the countries in the North and South American continents. Since the virus spread worldwide, we simultaneously use all available daily confirmed cases, recovered cases, and death data to cluster countries in time and spatial dimensions after adjusting for population. For this aim, time-series clustering with the dynamic time warping method is implemented and relevant clusters are marked on the world maps for a better visual understanding in this paper. Grouping countries will give an idea of the spread of the virus, guide decision-makers to implement future prevention vaccination policies, and help them generate global solutions against new virus variants. One of the main results obtained from the cluster analysis is that the European, North and South American continents have homogeneous structures regarding the number of daily confirmed cases per million and relatively more heterogeneous regarding the daily number of recoveries per million such that the overwhelming majority of countries are in the very high cluster. The absence of countries from the low or middle clusters indicates that these continents have to fight the virus more fiercely. African and Asian continents are heterogeneous in all cases. Therefore, these continents should focus on country-specific protections to fight against the virus.

Exploring the use of operational excellence methodologies in the era of COVID-19: perspectives from leading academics and practitioners

Purpose>This paper aims to present the results of a study carried out by the authors in the form of research interviews on the topic: “Exploring the use of operational excellence methodologies in the era of COVID-19.”Design/methodology/approach>A qualitative interview approach was utilized by interviewing a panel of leading academics and practitioners who are familiar with operation excellence methodologies.Findings>Operational excellence methodologies are proven and can be utilized in pandemic situations to improve efficiency in the healthcare system and preparedness for pandemics.Research limitations/implications>One limitation of this research was that most of the interviewees who participated in this study came from Europe, North America, South America and Asia, representing four continents. It would have been better to have different views from other continents such as Australia and Africa. Also, the interviews were short and at a high level. There is an opportunity for further study and analysis.Practical implications>Operational excellence methodologies are proven and can be utilized in pandemic situations to improve efficiency in the healthcare system and preparedness for pandemics.Originality/value>The paper provides an excellent resource for those people to get an insight into the value of the application of operations excellence methodologies in pandemic situations to aid healthcare process improvement and aid public and patient safety.

The global case fatality rate of coronavirus disease 2019 by continents and national income: A meta-analysis.

The aim of this study is to provide a more accurate representation of COVID-19's case fatality rate (CFR) by performing meta-analyses by continents and income, and by comparing the result with pooled estimates. We used multiple worldwide data sources on COVID-19 for every country reporting COVID-19 cases. On the basis of data, we performed random and fixed meta-analyses for CFR of COVID-19 by continents and income according to each individual calendar date. CFR was estimated based on the different geographical regions and levels of income using three models: pooled estimates, fixed- and random-model. In Asia, all three types of CFR initially remained approximately between 2.0% and 3.0%. In the case of pooled estimates and the fixed model results, CFR increased to 4.0%, by then gradually decreasing, while in the case of random-model, CFR remained under 2.0%. Similarly, in Europe, initially, the two types of CFR peaked at 9.0% and 10.0%, respectively. The random-model results showed an increase near 5.0%. In high-income countries, pooled estimates and fixed-model showed gradually increasing trends with a final pooled estimates and random-model reached about 8.0% and 4.0%, respectively. In middle-income, the pooled estimates and fixed-model have gradually increased reaching up to 4.5%. in low-income countries, CFRs remained similar between 1.5% and 3.0%. Our study emphasizes that COVID-19 CFR is not a fixed or static value. Rather, it is a dynamic estimate that changes with time, population, socioeconomic factors, and the mitigatory efforts of individual countries.

Sentiment Analysis in Indian Sub-continent during COVID-19 Second Wave using Twitter Data

In Indian sub-continent COVID-19 second wave started in early March 2021 and its effect was more lethal than the first wave, the confirmed cases and the death rate was higher than in the first wave. Unlike the national lockdown in 2020, this year different states have started imposing lockdown like restrictions spanning April-June 2021. This paper investigates the sentiments of the people using twitter messages during early period of the second wave. Two-weeks data is manually annotated and several machine learning models were built. The best performing models were used to predict sentiments for the next 2-3 weeks and analysis is presented. Predictions of public, commercial libraries were also analysed in the same context. © 2021 IEEE.

Constant 12 and reflexivity 472319 hahslm on the geography of the earth in the economic era of covid

The purpose of this research is to analyze the geographical shape of the earth’s face with the 472319 Hahslm patterns in geomorphology. Earth undergoes the process of forming water and soil so that it becomes a continent and an archipelago. The composition of the sea and land is 7:3. The object of this study is the shape of the sea and land on earth and the Quran 13.31. This research was conducted by studying literature from books, journals, electronic media, and earth globes, and world atlases. The methodology used is descriptive-analytical. The method used is reflexivity, similarity, and dynivity with the formula 472319 Hahslm. The result obtained is the process of changing the shape of the earth’s surface towards a pattern of worship by the meaning of the holy book in the form of cutting the earth according to the meaning of the Quran. The Quran formula 13.31 forms an arrangement of 444 in the form of letter number 13, namely 1+3=4, and from 31, namely 3+1=4. The third pattern 4 is obtained from the number of letters hijaiyaj in the word for cutting the earth as many as 13 letters meaning 1 + 3 = 4. The geomorphological reflectivity of the earth resembles the pattern of 444. With the composition of the oceans and lands of 7:3 which has a difference of four from 7-3=4. In the formula, 472319 Hahslm derived from the Quran 15.87 means the Quran in the form of 6438 verses. The second meaning of 4 is obtained from the multiplication of 7 and 2, namely 7x2=14 by taking the first four words of the fourteenth phrase. And the third meaning of 4 from addition is 3+1+9=13 where the root of digit 13 is 1+3=4. The second geography of the earth is at number 4 from the geomorphology of the continents of Asia, Africa, Europe, and Australia which forms a hand pattern of 319. With the tips of small fingers located in parts of countries that have islands located in the eastern to southeastern Asian continents such as parts of Russia, Japan, Korea, China, and the Philippines. Meanwhile, the Southeast Asian region forms the index finger or pattern 1 which has a similarity to the shape of the Indonesian archipelago with the tip being large in Australia and New Zealand. Big finger thumb or pattern 9 has similarities with mainland India, Pakistan, Bangladesh in South Asia. While the Americas have similarities with pattern 7 or V for South America and pattern 2 for North America. Waters and islands are needed in a pandemic that has an economic effect. The conclusion is that the geography of the earth forms 472319 show the earth is worshiping even during the Covid economic era.

Implications derived from S-protein variants of SARS-CoV-2 from six continents.

The spike (S) protein is a critical determinant of the infectivity and antigenicity of SARS-CoV-2. Several mutations in the S protein of SARS-CoV-2 have already been detected, and their effect in immune system evasion and enhanced transmission as a cause of increased morbidity and mortality are being investigated. From pathogenic and epidemiological perspectives, S proteins are of prime interest to researchers. This study focused on the unique variants of S proteins from six continents: Asia, Africa, Europe, Oceania, South America, and North America. In comparison to the other five continents, Africa had the highest percentage of unique S proteins (29.1%). The phylogenetic relationship implies that unique S proteins from North America are significantly different from those of the other five continents. They are most likely to spread to the other geographic locations through international travel or naturally by emerging mutations. It is suggested that restriction of international travel should be considered, and massive vaccination as an utmost measure to combat the spread of the COVID-19 pandemic. It is also further suggested that the efficacy of existing vaccines and future vaccine development must be reviewed with careful scrutiny, and if needed, further re-engineered based on requirements dictated by new emerging S protein variants.

SARS-Cov2: a meta-analysis of symptom distribution by continent in 7310 adult COVID-19 infected patients.

There is recent evidence that suggests that there are multiple strains of coronavirus in different parts of the world. Moreover, scientist have noted multiple mutations and postulated that these changes might increase the infective rate of the virus. However literature on varying severity of disease based on these strains is absent. In this meta-analysis, we have made an attempt to correlate the symptoms in different continents with respect to various studied strains of virus. We searched three databases, PubMed, EMBASE and EMCARE to identify studies reporting symptoms of COVID-19. All articles published between December 2019 and May 2020 was included in this meta-analysis. A total of 56 studies consisted of 7310 patients were included in the meta-analysis. Mean age of patients varied from 22 to 69.8 years. The pooled proportion of male patients was 52%. Highest incidence of fever (76%) and cough (56%) was noted in Chinese population. Sore throat (29%) was most common in Asian population. Upper respiratory tract symptom like Rhinorrhoea, Anosmia and dysgeusia (32%, 47% and 39%) were well documented in European population as compared to the other continents. Nausea and diarrhoea were more common in European (17%, 19%) and Australian (12%, 16%) population. Dyspnoea and fatigue were consistently similar in all the continents. We postulate that different mutations in COVID-19 virus may vary its pathogenicity and screening symptoms across all the continents should be not be generalised but continent-specific. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13337-021-00699-y.

Continent-Wide Analysis of COVID 19: Total Cases, Deaths, Tests, Socio-Economic, and Morbidity Factors Associated to the Mortality Rate, and Forecasting Analysis in 2020-2021.

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in China in December 2019 and has become a pandemic that resulted in more than one million deaths and infected over 35 million people worldwide. In this study, a continent-wide analysis of COVID-19 cases from 31st December 2019 to 14th June 2020 was performed along with socio-economic factors associated with mortality rates as well as a predicted future scenario of COVID-19 cases until the end of 2020. METHODS: Epidemiological and statistical tools such as linear regression, Pearson's correlation analysis, and the Auto Regressive Integrated Moving Average (ARIMA) model were used in this study. RESULTS: This study shows that the highest number of cases per million population was recorded in Europe, while the trend of new cases is lowest in Africa. The mortality rates in different continents were as follows: North America 4.57%, Europe 3.74%, South America 3.87%, Africa 3.49%, Oceania and Asia less than 2%. Linear regression analysis showed that hospital beds, GDP, diabetes, and higher average age were the significant risk factors for mortality in different continents. The forecasting analysis since the first case of COVID-19 until 1st January 2021 showed that the worst scenario at the end of 2020 predicts a range from 0 to 300,000 daily new cases and a range from 0 to 16,000 daily new deaths. CONCLUSION: Epidemiological and clinical features of COVID-19 should be better defined, since they can play an import role in future strategies to control this pandemic.

Forecasting the Spreading of COVID-19 across Nine Countries from Europe, Asia, and the American Continents Using the ARIMA Models.

Since mid-November 2019, when the first SARS-CoV-2-infected patient was officially reported, the new coronavirus has affected over 10 million people from which half a million died during this short period. There is an urgent need to monitor, predict, and restrict COVID-19 in a more efficient manner. This is why Auto-Regressive Integrated Moving Average (ARIMA) models have been developed and used to predict the epidemiological trend of COVID-19 in Ukraine, Romania, the Republic of Moldova, Serbia, Bulgaria, Hungary, USA, Brazil, and India, these last three countries being otherwise the most affected presently. To increase accuracy, the daily prevalence data of COVID-19 from 10 March 2020 to 10 July 2020 were collected from the official website of the Romanian Government GOV.RO, World Health Organization (WHO), and European Centre for Disease Prevention and Control (ECDC) websites. Several ARIMA models were formulated with different ARIMA parameters. ARIMA (1, 1, 0), ARIMA (3, 2, 2), ARIMA (3, 2, 2), ARIMA (3, 1, 1), ARIMA (1, 0, 3), ARIMA (1, 2, 0), ARIMA (1, 1, 0), ARIMA (0, 2, 1), and ARIMA (0, 2, 0) models were chosen as the best models, depending on their lowest Mean Absolute Percentage Error (MAPE) values for Ukraine, Romania, the Republic of Moldova, Serbia, Bulgaria, Hungary, USA, Brazil, and India (4.70244, 1.40016, 2.76751, 2.16733, 2.98154, 2.11239, 3.21569, 4.10596, 2.78051). This study demonstrates that ARIMA models are suitable for making predictions during the current crisis and offers an idea of the epidemiological stage of these regions.