ABSTRACT
The COVID-19 crisis in the restaurant and bar industry is affecting an industry that has been under significant pressure before. Using the concept of organizational resilience from a spatial perspective, we analyze how individual/ company factors and regional factors influence owner's assessment of resilience in the German restaurant and bar industry. Findings from an online survey with 445 owners and managers and 46 qualitative interviews in Germany show that enterprises in peripheral locations are perceived as more resilient Similarly, the age of the respondents, the ownership of property and the provision of delivery and takeaway service play a positive role in enterprises being seen as resilient, while, owner-managed enterprises, financing by loans or credit, and lower ex-ante sales reduce the likelihood of the assessment of resilience. Overall, the study contributes to the evolving strand of research that aims to analyze the resilience of enterprises from a spatial perspective.
ABSTRACT
While COVID-19 is a global pandemic, different countries have experienced different morbidity and mortality patterns. We employ retrospective and prospective space-time permutation analysis on COVID-19 positive records across different municipalities in Sweden from March 2020 to February 2021, using data provided by the Swedish Public Health Agency. To the best of our knowledge, this is the first study analyzing nationwide COVID-19 space-time clustering in Sweden, on a season-to-season basis. Our results show that different municipalities within Sweden experienced varying extents of season-dependent COVID-19 clustering in both the spatial and temporal dimensions. The reasons for the observed differences could be related to the differences in the earlier exposures to the virus, the strictness of the social restrictions, testing capabilities and preparedness. By profiling COVID-19 space-time clusters before the introduction of vaccines, this study contributes to public health efforts aimed at containing the virus by providing plausible evidence in evaluating which epidemiologic interventions in the different regions could have worked and what could have not worked.
ABSTRACT
The Covid-19 has presented an unprecedented challenge to public health worldwide. However, residents in different countries showed diverse levels of Covid-19 awareness during the outbreak and suffered from uneven health impacts. This study analyzed the global Twitter data from January 1st to June 30(th), 2020, to answer two research questions. What are the linguistic and geographical disparities of public awareness in the Covid-19 outbreak period reflected on social media? Does significant association exist between the changing Covid-19 awareness and the pandemic outbreak? We established a Twitter data mining framework calculating the Ratio index to quantify and track awareness. The lag correlations between awareness and health impacts were examined at global and country levels. Results show that users presenting the highest Covid-19 awareness were mainly those tweeting in the official languages of India and Bangladesh. Asian countries showed more disparities in awareness than European countries, and awareness in Eastern Europe was higher than in central Europe. Finally, the Ratio index had high correlations with global mortality rate, global case fatality ratio, and country-level mortality rate, with 21-31, 35-42, and 13-18 leading days, respectively. This study yields timely insights into social media use in understanding human behaviors for public health research.
ABSTRACT
During the COVID-19 emergency, cities around the world introduced measures to guarantee physical distancing that restricted access to urban parks and green areas, with potentially negative effects on citizens' health and wellbeing. This study aims at providing insights to manage access to urban green space in physical distancing times, when the risk of crowding should be avoided. Using the city of Trento (Italy) as a case study, the study simulates policy scenarios corresponding to different restrictions and assesses their effects on green space access and crowding. Policy scenarios are obtained by combining different distances that people are allowed to travel, different types of green areas available for public use (only urban parks or parks and schoolyards), and different target populations (all residents or only people with no private gardens). The results unveil the trade-off between access and crowding of green areas, and can be used to suggest policy interventions and regulations that can be adopted in an emergency. Particularly, the study shows that: i) The relationship between distance threshold and the percentage of people with access to green areas is non-linear, and this should be carefully considered when proposing travel restrictions;ii) Changing the maximum travel distance does not produce major effects on the number of crowded green areas, hence additional or alternative measures need to be adopted;iii) Off-the-shelf measures, such as opening schoolyards, are beneficial and can be implemented rapidly in an emergency. Finally, the study reveals "hotspots" of green space deprivation/overcrowding in the city that should be addressed by urban planning to ensure that green space continues to benefit citizens also during emergency conditions.
ABSTRACT
Currently, coronavirus disease 2019 (COVID-19) remains a global pandemic, but the prevention and control of the disease in various countries have also entered the normalization stage. To achieve economic recovery and avoid a waste of resources, different regions have developed prevention and control strategies according to their social, economic, and medical conditions and culture. COVID-19 disparities under the interaction of various factors, including interventions, need to be analyzed in advance for effective and precise prevention and control. Considering the United States as the study case, we investigated statistical and spatial disparities based on the impact of the county-level social vulnerability index (SVI) on the COVID-19 infection rate. The county-level COVID-19 infection rate showed very significant heterogeneity between states, where 67% of county-level disparities in COVID-19 infection rates come from differences between states. A hierarchical linear model (HLM) was adopted to examine the moderating effects of state-level social distancing policies on the influence of the county-level SVI on COVID-19 infection rates, considering the variation in data at a unified level and the interaction of various data at different levels. Although previous studies have shown that various social distancing policies inhibit COVID-19 transmission to varying degrees, this study explored the reasons for the disparities in COVID-19 transmission under various policies. For example, we revealed that the state-level restrictions on the internal movement policy significantly attenuate the positive effect of county-level economic vulnerability indicators on COVID-19 infection rates, indirectly inhibiting COVID-19 transmission. We also found that not all regions are suitable for the strictest social distancing policies. We considered the moderating effect of multilevel covariates on the results, allowing us to identify the causes of significant group differences across regions and to tailor measures of varying intensity more easily. This study is also necessary to accomplish targeted preventative measures and to allocate resources.
ABSTRACT
Referring to a total lockdown due to COVID-19 in Metropolitan France, this study investigates the geospatial correlation between nighttime light emission and the relative change of NO2 air pollution (dNO(2) %). To address the research problem, near-surface NO2 data and nighttime light data were implemented. Stable night lights were obtained for a long period on average (2014-2019) using Day-Night Band (DNB) data from the Visible Infrared Imaging Radiometer Suite (VIIRS). The relative change in tropospheric NO2 was calculated using Sentinel-5P satellite data from the Tropospheric Monitoring Instrument (TROPOMI). The dNO(2) calculation was performed considering an equivalent reference period (April 2019) to the major lockdown period in France (April 2020). The correlation between the variables DNB nighttime lights and dNO(2) was tested with a statistical T-test. The findings revealed an intense phenomenon of decreasing NO2 air pollution in France (decreases by -25% to -50%). Decreases < -50% were mainly recorded in the greater Paris metropolitan area, in Alsace, and other locations. The results showed a strong and statistically significant inverse geospatial correlation between the two variables under anti-COVID-19 control measures. The higher was the emission of nighttime lights, the higher was the degree of tropospheric NO2 decrease in the regions of France (R-2 =0.72). It is concluded that employing remote sensing techniques, DNB nighttime light is a reliable indicator to estimate the degree of air decontamination. DNB as an independent variable is recommended for future research on changes in the concentration of other pollutant gases.
ABSTRACT
Like every other continent in the world, Antarctica has been affected by the COVID-19 pandemic, in an imagined as well as a practical sense. Antarctica is a mediated experience;that is, most of us experience the place through films, novels, music, visual arts and the media. We present an analysis of media articles from eight countries over three time periods - pre-COVID-19 outbreak (October-December 2019), shortly after the pandemic hit the headlines (March-May 2020) and when the virus was established (October-December 2020) - to discover how COVID-19 may have changed Antarctic discourse. Our study shows that representations of Antarctica have been affected by the pandemic, in some instances reinforcing existing ideas and in other cases bringing new ideas to the fore. Based on our findings, we believe that COVID-19 has begun to change representations of Antarctica, stepping us away from the prevailing Antarctic hero narrative and providing a more contemporary understanding of the Antarctic experience. We argue that this may increase our motivation to engage with Antarctic issues, with associated implications for future global stewardship of the region.
ABSTRACT
Visitor Site Guidelines are the principal instruments guiding tourist activities and behaviour at intensively visited sites. These instruments attempt to minimize tourist impacts on Antarctic wildlife, including penguins. However, some recommendations still need to be reinforced by empirical research. Although penguins have enjoyed considerable research attention, a knowledge gap still exists regarding penguins' behavioural responses to realistic tourist activities, including talking sound, viewing distance and movement speed. To fill this gap, we conducted a series of experiments to simulate these activities on two penguin species breeding at an intensively visited site during the 2019-2020 season. We performed 106 replicates of passive and active human presence treatments. Responses varied between species, but active human presence consistently triggered significantly higher responses of strong vigilance behaviour. Our results reinforce Visitor Site Guidelines' recommendations of keeping quiet, moving slowly and increasing viewing distance if changes in behaviour are observed. We also recommend adopting a more conservative viewing distance in the early breeding season. Additional management-orientated empirical studies are needed, including on different species, sites and stages of the breeding season, as such results are valuable for strengthening tourism guidelines and assessing the efficacy of management measures under a post-COVID-19 scenario of increasing Antarctic tourism.
ABSTRACT
As of the beginning of September 2021, the COVID-19 outbreak has lasted for more than 1.5 years in Indonesia, especially on Java and Bali islands. Yogyakarta Special Region, Indonesia, is one of the areas that continued to impose restrictions on community activities at the highest level for that period. This is due to the high rate of COVID-19 spread in this region. In this paper, the influence of landscape and meteorological parameters on the spread of COVID-19 risk in Yogyakarta is investigated. This study utilises primary and secondary data obtained from observation, remote-sensing-image interpretation, literature study and data documented by several agencies. The data were statistically analysed using simple linear regression and Geographic Information System (GIS) analysis utilising the average nearest neighbour. The results show that the variation in landscape and meteorological parameters in the Yogyakarta area does not have a significant impact on the spread of COVID-19. Ease of accessibility in various areas of Yogyakarta is able to overcome landscape barriers. This affects the random distribution pattern of COVID-19, clustering in plain areas that facilitate population mobility rather than in mountainous, volcanic or karst areas. Also, meteorological conditions with small variations do not impact the spread of COVID-19. In summary, this study shows that ease of mobility in a medium-wide area can encourage the spread of COVID-19 in various regions even though there are variations in its terrain and climate.
ABSTRACT
The COVID-19 pandemic resulted in profound changes in mobility patterns and altered travel behaviors locally and globally. As a result, movement metrics have widely been used by researchers and policy makers as indicators to study, model, and mitigate the impacts of the COVID-19 pandemic. However, the veracity and variability of these mobility metrics have not been studied. This paper provides a systematic review of mobility and social distancing metrics available to researchers during the pandemic in 2020 in the United States. Twenty-six indices across nine different sources are analyzed and assessed with respect to their spatial and temporal coverage as well as sample representativeness at the county-level. Finally global and local indicators of spatial association are computed to explore spatial and temporal heterogeneity in mobility patterns. The structure of underlying changes in mobility and social distancing is examined in different US counties and across different data sets. We argue that a single measure might not describe all aspects of mobility perfectly.