Critical Commentary: The city and the virus

Cities around the world are the epicentres of the coronavirus pandemic: both in the first wave, as the disease spread from East Asia, and now, as many countries enter a third wave of infections. These spatial patterns are still far from properly understood, though there is no shortage of possible explanations. I set out the emerging theories about cities' role in the spread of coronavirus, testing these against existing studies and new analysis for English conurbations, cities and towns. Both reveal an urbanised public health crisis, in which vulnerabilities and health impacts track (a) urban structural inequalities, and (b) wider weaknesses in institutions, their capabilities and leaders. I then turn to 'post-pandemic' visions of future cities. I argue that this framing is unhelpful: even with mass vaccination, COVID-19 is likely to remain one of many globalised endemic diseases. Instead, 'pandemic-resilient' urban places will require improved economic, social and physical infrastructure, alongside better public policy. Describing such future cities is still highly speculative: I identify five zones of change. (English) [ FROM AUTHOR] 世界各地的城市都是冠状病毒大流行的中心：无论是在第一波疫情从东亚开始传播时，还是现在许多国家进入第三波感染。尽管不乏可能的解释，但这些空间模式仍远未得到正确理解。我阐述了关于城市在冠状病毒传播中的作用的一些新理论，并根据现有研究和针对英国大都市和城镇的新分析对这些理论进行了检验。两者都揭示了城市化的公共卫生危机，其中脆弱性和健康影响与以下因素相伴随：(a) 城市结构性不平等；以及 (b) 机构、其能力和领导者的更广泛弱点。接着，我转向未来城市的后疫情时代愿景。我认为这种框架是无益的：即使进行了大规模疫苗接种，新冠肺炎仍然可能会是许多全球化的地方病之一。相反，具有"抗流行病能力"的城市场所将需要经过改良的经济、社会和物质基础设施，以及更好的公共政策。对这样的未来城市的描述仍然具有高度的推测性：我确定了五个变革区域。 (Chinese) [ FROM AUTHOR] Copyright of Urban Studies (Sage Publications, Ltd.) is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Reasons for Not Adopting COVID-19 Permitted Changes to Legal Duties: Accounts from English Local Authorities

In England, "easements,” introduced via the Coronavirus Act 2020, were brought in at the start of the pandemic to support English local authority adult social care services. They enabled local authorities to suspend some of their mandatory duties under the Care Act 2014. Easements were only adopted by eight local authorities and for short periods, and the provision was rescinded in late 2021. This article examines why a sample of 16 local authorities, some of which were statistically close to the eight local authorities that did decide to use easements, decided not to do so. It draws on data from interviews undertaken in 2021 with Directors of Adult Services and Principal Social Workers that explored their decision-making about using easements. It also outlines their preparations prior to the pandemic reaching England, how they had operated using "flexibilities” within the Care Act thus not needing to adopt easements, and their views on those authorities that had adopted them.

Problem-Based Learning, Social Sustainability, and Soccer

On Friday, March 13, 2020, academic and sport activities at a Mexican university were happening as on a normal day. However, the following Monday, students and teachers had to stay at home for an undefined period. In this work, we show how a course with problem-based learning (PBL) and social sustainability (SS) approaches was adapted to pandemic times. We start with the COVID-19 context at the Monterrey Metropolitan Area (MMA) and then provide a theoretical overview of PBL, SS, Latin American self-produced quartiers, soccer in vulnerable communities, and general aspects about pandemic times. Following this, we discuss the methodology used for reaching out to vulnerable communities in Monterrey City, Mexico, using soccer as a strategy. The students conducted a project together with a non-governmental organization (NGO) whose main task is to promote this sport practice in vulnerable communities around the world. We conclude from our study that students need pedagogical platforms that allow them to respond to the requirements of different social groups, as well as to develop skills to face real problems.

A brief overview of the issues faced by Harmful Algal Blooms along Johor straits

Urbanization of coastal areas worldwide has increased due to an increase in the global population. The production of sustainable aquaculture is greatly impacted by a surge of this urbanization. In certain countries, particularly for individuals with more limited space in metropolitan areas, such as along Johor's coastal area, aquaculture might well be a good strategy to maintain food availability (continuous production plus high-quality meals). Consequently, the adoption of aquaculture along the Johor's coastal area has lead to Harmful Algal Blooms (HAB). This paper examines the evolution of the aquaculture industry of Malaysian Johor coastal areas in relation to HABs. In addition to HABs, the aforementioned metropolitan regions confront diverse economic and geographical obstacles when attempting to increase their aquaculture production sustainably. Those problems are therefore addressed using a variety of operations as well as surveillance techniques in this brief overview. Lockdowns and border prohibitions caused by the continuous COVID-19 infection have had a global impact. These logistical difficulties in the seafood industry have increased dependency on imported supplies. It is suggested that international decision- making, supervision, and knowledge exchange can successfully solve the challenges urbanized areas have in ensuring sustainable food security through the evolution within the aquaculture sector.

El papel del subarriendo en las trayectorias residenciales de la población inmigrante: el caso del Área Metropolitana de Barcelona

El subarriendo de habitaciones es una realidad ampliamente extendida en las grandes áreas urbanas;sin embargo, la ausencia de estadísticas al respecto dificulta su análisis. Gran parte de la población inmigrante accede a una vivienda mediante esta modalidad. Por ello, en este estudio se analizan 27 entrevistas semiestructuradas para evaluar el papel del subarriendo en la trayectoria residencial de dicho colectivo en el Área Metropolitana de Barcelona. Los resultados confirman la creciente dificultad que tienen los inmigrantes que han llegado recientemente para avanzar en la escala habitacional y, más concretamente, el protagonismo del subarriendo como recurso residencial precario de dicha población, en particular en las etapas tempranas de inserción residencial, aunque no exclusivamente, pues también se ha detectado la existencia de trayectorias residenciales inversas. Se comprueba también la presencia de submercados de habitaciones a los que se accede de manera exclusiva a través de cadenas migratorias.Alternate :The subleasing of rooms is a widespread reality in large urban areas, however, the absence of statistics in this regard makes its analysis difficult. A large part of the immigrant population has access to a dwelling through this modality. Therefore, in this study, 27 semi-structured interviews are analyzed to evaluate the role of subleasing in the housing patterns of this group in the Metropolitan Area of Barcelona. The results confirm the increasing difficulty that recent immigrants have to advance in the housing scale and, more specifically, the prominence of subleasing as a precarious residential resource for the population, particularly in the early stages of residential insertion, although not exclusively, since the existence of reverse residential trajectories has also been detected. We also verify that the presence of submarkets rooms that are accessed exclusively through migratory chains.

Coarse particulate matter air quality in East Asia: implications for fine particulate nitrate

Air quality network data in China and South Korea show very high year-round mass concentrations of coarse particulate matter (PM), as inferred by the difference between PM10 and PM2.5. Coarse PM concentrations in 2015 averaged 52 µg m-3 in the North China Plain (NCP) and 23 µg m-3 in the Seoul Metropolitan Area (SMA), contributing nearly half of PM10. Strong daily correlations between coarse PM and carbon monoxide imply a dominant source from anthropogenic fugitive dust. Coarse PM concentrations in the NCP and the SMA decreased by 21 % from 2015 to 2019 and further dropped abruptly in 2020 due to COVID-19 reductions in construction and vehicle traffic. Anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate nitrate, a major contributor to PM2.5 pollution. GEOS-Chem model simulation of surface and aircraft observations from the Korea–United States Air Quality (KORUS-AQ) campaign over the SMA in May–June 2016 shows that consideration of anthropogenic coarse PM largely resolves the previous model overestimate of fine particulate nitrate. The effect is smaller in the NCP which has a larger excess of ammonia. Model sensitivity simulations for 2015–2019 show that decreasing anthropogenic coarse PM directly increases PM2.5 nitrate in summer, offsetting 80 % the effect of nitrogen oxide and ammonia emission controls, while in winter the presence of coarse PM increases the sensitivity of PM2.5 nitrate to ammonia and sulfur dioxide emissions. Decreasing coarse PM helps to explain the lack of decrease in wintertime PM2.5 nitrate observed in the NCP and the SMA over the 2015–2021 period despite decreases in nitrogen oxide and ammonia emissions. Continuing decrease of fugitive dust pollution means that more stringent nitrogen oxide and ammonia emission controls will be required to successfully decrease PM2.5 nitrate.

Estimation of NO2 emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and a machine learning technique

Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx (NOx = NO + NO2) emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from 4-year (May 2018–June 2022) TROPOspheric Monitoring Instrument (TROPOMI) observations by combining a wind-assigned anomaly approach and a machine learning (ML) method, the so-called gradient descent algorithm. This combined approach is firstly applied to the Saudi Arabian capital city of Riyadh, as a test site, and yields a total emission rate of 1.09×1026 molec. s-1. The ML-trained anomalies fit very well with the wind-assigned anomalies, with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites: over a cement plant and power plants as well as over areas along highways. Using the same approach, an emission rate of 1.99×1025 molec. s-1 is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable with the Copernicus Atmosphere Monitoring Service (CAMS) inventory.Weekly variations in NO2 emission are highly related to anthropogenic activities, such as the transport sector. The NO2 emissions were reduced by 16 % at weekends in Riyadh, and high reductions were found near the city center and in areas along the highway. An average weekend reduction estimate of 28 % was found in Madrid. The regions with dominant sources are located in the east of Madrid, where residential areas and the Madrid-Barajas airport are located. Additionally, due to the COVID-19 lockdowns, the NO2 emissions decreased by 21 % in March–June 2020 in Riyadh compared with the same period in 2019. A much higher reduction (62 %) is estimated for Madrid, where a very strict lockdown policy was implemented. The high emission strengths during lockdown only persist in the residential areas, and they cover smaller areas on weekdays compared with weekends. The spatial patterns of NO2 emission strengths during lockdown are similar to those observed at weekends in both cities. Although our analysis is limited to two cities as test examples, the method has proven to provide reliable and consistent results. It is expected to be suitable for other trace gases and other target regions. However, it might become challenging in some areas with complicated emission sources and topography, and specific NO2 decay times in different regions and seasons should be taken into account. These impacting factors should be considered in the future model to further reduce the uncertainty budget.

The Configuration of a Multi-Pronged Housing Movement in Barcelona

The housing movement that emerged in Spanish cities during the 2007–8 global financial crisis has undergone various mutations. If at first it was led by the anti-evictions fight of the Platform for People Affected by Mortgages (PAH) and the housing groups of the 15M mobilization cycle (2011–14), the successive rent crises since 2013 and during the COVID-19 pandemic (2020–22) have given rise to new activist expressions—housing/neighborhood unions (sindicats d'habitatge / de barri) and a tenants' union—in metropolitan areas such as Barcelona. These have played a central role in housing organizing during the COVID-19 pandemic. In this article we investigate the development of the housing/neighborhood unions while understanding their relationships with other housing groups in Barcelona. We first aim to know if, how, and why they have adopted, modified, or replaced the protest repertoires used by the PAH and the tenants' union and, second, to what extent the local housing movement in Barcelona evolved into a more diverse and multi-pronged configuration. Our findings indicate significant divergences between these housing organizations but also a common and complementary field of activism that eventually proved to be resilient during the COVID-19 pandemic and beyond.

A Hybrid Deep Neural Network Architecture for Day-Ahead Electricity Forecasting: Post-COVID Paradigm

Predicting energy demand in adverse scenarios, such as the COVID-19 pandemic, is critical to ensure the supply of electricity and the operation of essential services in metropolitan regions. In this paper, we propose a deep learning model to predict the demand for the next day using the "IEEE DataPort Competition Day-Ahead Electricity Demand Forecasting: Post-COVID Paradigm” database. The best model uses hybrid deep neural network architecture (convolutional network–recurrent network) to extract spatial-temporal features from the input data. A preliminary analysis of the input data was performed, excluding anomalous variables. A sliding window was applied for importing the data into the network input. The input data was normalized, using a higher weight for the demand variable. The proposed model's performance was better than the models that stood out in the competition, with a mean absolute error of 2361.84 kW. The high similarity between the actual demand curve and the predicted demand curve evidences the efficiency of the application of deep networks compared with the classical methods applied by other authors. In the pandemic scenario, the applied technique proved to be the best strategy to predict demand for the next day.

Digital economic activity and resilience for metros and small businesses during Covid-19

The Covid-19 pandemic had an unequal impact across businesses and communities and rapidly accelerated digital trends in the economy. What role, then, did website use play in community resilience and small business outcomes? This article examines a new source of population data on domain name hosts to provide a unique measure of digital economic activity within communities. Seventy-five percent are commercial, including online-only, brick-and-mortar, small, and microbusinesses. With geolocated data on 20 million US domain name hosts, we investigate how their density (per 100 people) affected economic outcomes in the nation's largest metros during the pandemic. Using monthly time series data for the 50 largest metropolitan areas, the domain host data is merged with the US Census Small Business Pulse Surveys and Chetty et al.'s Opportunity Insights data. Results indicate metros with higher concentrations of businesses with an online presence experienced more positive economic perceptions and outcomes from April to December 2020. This high-frequency, granular data on digital economic activity suggests that digitally enabled small and microbusinesses played an important role in local economic resilience and demonstrates how commercial data can be used to generate new insights in a fast-changing environment.Plain English SummaryNew data show websites were a resource for small business and community resilience in Covid-19. While some studies have shown how digital technologies helped businesses during the pandemic, little research has examined how website use during this time affected communities and their small businesses. Data on the number of domain name hosts (per 100 people) provides a measure of the prevalence of website use in a community. Seventy-five percent of these domain name sites are commercial, primarily small, and microbusinesses. We examine economic outcomes for the 50 largest metros from April to December 2020, including credit and debit card spending, small business revenues and openings, and the perceptions of small business owners. With monthly data and across multiple measures, we find that this digital economic activity positively affected the resilience of communities and small businesses. These findings suggest that policies for an inclusive and effective recovery should consider support for digital skills and effective website use for small and microbusinesses.

A Tale of Two Cities: COVID-19 Vaccine Hesitancy as a Result of Racial, Socioeconomic, Digital, and Partisan Divides

The unprecedented COVID-19 pandemic has drawn great attention to the issue of vaccine hesitancy, as the acceptance of the innovative RNA vaccine is relatively low. Studies have addressed multiple factors, such as socioeconomic, political, and racial backgrounds. These studies, however, rely on survey data from participants as part of the population. This study utilizes the actual data from the U.S. Census Bureau as well as actual 2020 U.S. presidential election results to generate four major category of factors that divide the population: socioeconomic status, race and ethnicity, access to technology, and political identification. This study then selects a region in a traditionally democratic state (Capital Region in New York) and a region in a traditionally republican state (Houston metropolitan area in Texas). Statistical analyses such as correlation and geographically weighted regression reveal that factors such as political identification, education attainment, and non-White Hispanic ethnicity in both regions all impact vaccine acceptance significantly. Other factors, such as poverty and particular minority races, have different influences in each region. These results also highlight the necessity of addressing additional factors to further shed light on vaccine hesitancy and potential solutions according to identified factors.

Behavioral changes of preventive activities of influenza among children in satellite cities of a metropolitan area of Tokyo, Japan, by the COVID-19 pandemic.

OBJECTIVE: In children in a metropolitan area of Tokyo, Japan, behavioral change and influenza infection associated with the frequency of nonpharmaceutical interventions (NPI) was assessed from the 2018-2019 season (Preseason) and the 2020-2021 season (coronavirus disease 2019 [COVID-19] season). METHODS: We conducted an exclusive survey among children attending preschool, elementary school, and junior high school in the Toda and Warabi regions, Japan, during the 2018-2019 (Preseason, distributed via mail) and 2020-2021 seasons (COVID-19 season, conducted online). The proportion of preventive activities (hand washing, face mask-wearing, and vaccination) was compared in the Preseason with that of the COVID-19 season. The multivariate logistic regression model was further applied to calculate the adjusted odds ratio (AOR) with 95% confidence intervals (CIs) for influenza infection associated with NPI frequency (hand washing and face mask wearing) in each Preseason and COVID-19 season. RESULTS: The proportion of vaccinated children who carried out hand washing and face mask wearing was remarkably higher during the COVID-19 season (48.8%) than in the Preseason (18.2%). A significant influenza infection reduction was observed among children who washed hands and wore face masks simultaneously (AOR, 0.87; 95% CI, 0.76-0.99; P = 0.033). CONCLUSIONS: A strong interest and performance in the intensive measures for the prevention of influenza under the COVID-19 pandemic was demonstrated. Positive association was observed from a combination of NPI, hand washing, and face mask-wearing and influenza infection. This study's findings could help in activities or preventive measures against influenza and other communicable diseases in children.

BUILDING HUMAN SECURITY IN MEXICALI, BAJA CALIFORNIA (2010‑2020)

This article aims to analyze social inequality and public security in Mexicali Metropolitan Area from a Human Security approach. The research methodology, carried out in the summer of 2021, is mix methods, with qualitative, quantitative, and cartographic technics. It is based on official data, international organizations reports, media outlets while Google Earth and Mapinfo are mapping tools. The document is divided into the following sections: introduction, conceptual framework, methodology, and qualitative and quantitative description of social inequality and insecurity in the Mexicali Metropolitan Area (MMA). Subsequently, the main argument is addressed, supported by statistics and thematic maps. Finally, the closing considerations are presented.

The preferred location of coworking spaces in Italy: an empirical investigation in urban and peripheral areas

With a rising globalization of the economy and society, the digital transformation, and the economic downturn started in 2008, working is becoming less dependent on distance, location, and time. These are some of the reasons that have fostered the development and diffusion of new working spaces like coworking spaces. The paper aims at exploring the location determinants of coworking spaces, an issue that has been less developed by the literature up to now. By focusing on the 549 coworking spaces located in Italy at the year 2018, the paper investigates the location factors of such workplaces, and the attractiveness of large cities as well as peripheral areas. The results of the descriptive statistics and the econometric analysis (a Zero-Inflated Negative Binomial model is applied) confirm that coworking is mainly an urban phenomenon, since coworking spaces tend to be knowledge-intensive places for creative people. Specifically, the municipalities showing higher innovation and entrepreneurial environment (i.e. major cities) are preferred locations. Besides, it is discussed whether coworking spaces may contribute to fostering the development of peripheral and inner areas in Italy, especially during the Covid-19 pandemic where the share of teleworkers outside metropolitan areas has massively increased.

Desafíos y oportunidades en una metrópolis contraurbanizada. Movilidad regional en tiempos de COVID-19

In a profoundly unequal metropolis, daily mobility strategies allow the development of interpersonal assistance and support networks, as well as access to strategic resources/services that secure an adequate quality of life. According to this premise, I explored the increase in socioeconomic/health vulnerability and conflicts that emerged from mobility restrictions for containment and prevention of COVID-19 infections in the Metropolitan Region of Córdoba (Argentina) during 2020. I analyzed statistics, technical studies and press testimonials to characterize the socio-functional structure of the region, its daily mobility patterns and how the latter were transformed due to those restrictions. Finally, I characterized its impact on people's quality of life. The results show that the contradictions between those restrictions and the daily mobility patterns (structured by counter-urbanization and daily swaying migration that characterize the region) aggravate existing vulnerability and create new risks that affect the entire population, but specially the most impoverished groups, youth and women. This affirms the importance of incorporating regional daily mobility as a strategic factor in the development of effective, sustainable and inclusive health policies. © 2022 Universidad Nacional de Colombia. All rights reserved.

The impact of COVID-19 on home value in major Texas cities

PurposeThis study aims to analyze the impact of COVID-19 on housing price within four major metropolitan areas in Texas: Austin, Dallas, Houston and San Antonio. The analysis intends to understand economic and mobility drivers behind the housing market under the inclusion of fixed and random effects.Design/methodology/approachThis study used a linear mixed effects model to assess the socioeconomic and housing and transport-related factors contributing to median home prices in four major cities in Texas and to capture unobserved factors operating at spatial and temporal level during the COVID-19 pandemic.FindingsThe regression results indicated that an increase in new COVID-19 cases resulted in an increase in housing price. Additionally, housing price had a significant and negative relationship with the following variables: business cycle index, mortgage rate, percent of single-family homes, population density and foot traffic. Interestingly, unemployment claims did not have a significant impact on housing price, contrary to previous COVID-19 housing market related literature.Originality/valuePrevious literature analyzed the housing market within the first phase of COVID-19, whereas this study analyzed the effects of the COVID-19 throughout the entirety of 2020. The mixed model includes spatial and temporal analyses as well as provides insight into how quantitative-based mobility behavior impacted housing price, rather than relying on qualitative indicators such as shutdown order implementation.

Automatic detection and classification of land subsidence in deltaic metropolitan areas using distributed scatterer InSAR and Oriented R-CNN

Multi-temporal interferometric synthetic aperture radar (InSAR) is an effective tool for measuring large-scale land subsidence. However, the measurement points generated by InSAR are too many to be manually analyzed, and automatic subsidence detection and classification methods are still lacking. In this study, we developed an oriented R-CNN deep learning network to automatically detect and classify subsidence bowls using InSAR measurements and multi-source ancillary data. We used 541 Sentinel-1 images acquired during 2015–2021 to map land subsidence of the Guangdong-Hong Kong-Macao Greater Bay Area by resolving persistent and distributed scatterers. Multi-source data related to land subsidence, including geological and lithological, land cover, topographic, and climatic data, were incorporated into deep learning, allowing the local subsidence to be classified into seven categories. The results showed that the oriented R-CNN achieved an average precision (AP) of 0.847 for subsidence detection and a mean AP (mAP) of 0.798 for subsidence classification, which outperformed the other three state-of-the-art methods (Rotated RetinaNet, R3Det, and ReDet). An independent effect analysis showed that incorporating all datasets improved the AP by 11.2% for detection and the mAP by 73.9% for classification, respectively, compared with using InSAR measurements only. Combining InSAR measurements with globally available land cover and digital elevation model data improved the AP for subsidence detection to 0.822, suggesting that our methods can be potentially transferred to other regions, which was further validated this using a new dataset in Shanghai. These results improve the understanding of deltaic subsidence and facilitate geohazard assessment and management for sustainable environments. • Land subsidence of the GBA from 2015 to 2021 was measured by PS/DS detection. • The oriented R-CNN was applied to automatically identify local subsidence. • Incorporating multi-source data improved the performance of subsidence detection. • COVID-19 lockdown ceased groundwater extraction and decelerated subsidence. [ABSTRACT FROM AUTHOR] Copyright of Remote Sensing of Environment is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Racial disparities at rural and urban juvenile detention centers: Unanticipated findings since COVID-19's reduction in juvenile assessments

Studies on racial disparity within the juvenile justice system have demonstrated continued disproportionate minority contact (DMC) and racial and ethnic disparity (RED) issues throughout each decision point, especially at earlier stages. Yet, most research has centered on urban areas, with minimal attention given to youth-of-color in rural jurisdictions. As such, the current study utilized juvenile intake and assessment data from a rural Midwestern state, focused on racial and ethnic disparities prior to and per-COVID-19. Using data from a rural state, we examine the monthly counts of juveniles assessed at juvenile intake centers with an interrupted time-series design to explore whether the pandemic's impact differed by race or ethnicity. Our findings do not support the claim that the pandemic has exacerbated racial or ethnic disparity. Yet, trends suggest white and non-Hispanic youth, as well as youth in rural jurisdictions, are presenting at juvenile intake centers at less reduced rates than their youth-of-color and urban counterparts, per-COVID-19. The results show the pandemic has radically reduced assessments to the juvenile justice system, though this impact is not equally distributed. While intersectional comparisons are not possible at this time, policy implications and future directions are provided. [ABSTRACT FROM AUTHOR] Copyright of Journal of Crime & Justice is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Olympic Games, media coverage and brand image/performance from fan and gender perspectives

PurposeThe purpose of this paper is to explore and test certain assumptions concerning the role of the media in its coverage of the Olympic Games, US men's and women's basketball in particular, and its perceived impact on brand image of the athletes' performance from a fan's motivational and financial perspective.Design/methodology/approachUses and gratifications theory and sport fan motivation scales were used to identify potential impacts of media coverage and branding on athletic performance. Based on a study of 143 working professionals that identified themselves as Olympic sport fans in the Pittsburgh, PA metropolitan area, several hypotheses were tested.FindingsThe most to least important factor-based constructs found from a PCA (Principal Components Analysis)/factor analysis included competitiveness, fan commitment, media connections, media impacts, demographics and financial impacts. When using the construct athletic performance at the Olympic level as the dependent variable, results suggested that competitiveness, media connections and fan commitment were significant for males only, while only media connections for significant for females. Males were found to be more player-centric than females, willing to be more focused on the competitive nature of the Olympic Games and to dedicate more money for such activities.Originality/valueFocusing on Olympic Games and associated athletes' competitive nature opens a unique perspective from fan's gender perspective.

Population Redistribution Trends in Nonmetropolitan America, 2010 to 2021

Given the turbulent conditions of the early 21st century and the release of data from the 2020 Census, it is an appropriate time to examine contemporary population redistribution trends in nonmetropolitan America. Analysis centers on the major demographic components of population change: migration;and natural increase. The analysis demonstrates that the turbulent economic, social, and now epidemiological conditions of recent years altered traditional demographic trends in nonmetropolitan America. For the first time in history, nonmetropolitan America lost population between 2010 and 2020 because of shifts in migration trends and diminishing natural increase. In contrast, post‐censal population estimates suggest that nonmetropolitan population gains exceeded those in metropolitan areas for the first time in 50 years between 2020 and 2021. The recent widespread nonmetropolitan population increases are the result of substantial net migration gains that offset the growing natural decrease fostered by COVID‐19. Sustained net migration gains in nonmetro areas provides a demographic lifeline to many counties that would otherwise face depopulation because of accelerating natural decrease. Whether these migration patterns can be sustained remains to be seen.