Urban attributes and the spread of COVID-19: The effects of density, compliance and socio-political factors in Israel

Deciphering the COVID-19 density puzzle: A meta-analysis approach

The COVID-19 pandemic has sparked widespread efforts to mitigate its transmission, raising questions about the role of urban density in the spread of the virus. Understanding how city density affects the severity of communicable diseases like COVID-19 is crucial for designing sustainable, pandemic-resilient cities. However, recent studies on this issue have yielded inconsistent and conflicting results. This study addresses this gap by employing a comprehensive meta-analytic approach, synthesizing data across diverse regions and urban contexts to offer a broader, more nuanced perspective on the impact of city density. A systematic meta-analysis was conducted, initially screening 2,452 studies from Google Scholar, Scopus, and Avery Index databases (up to August 31, 2023), and narrowing down to 63 eligible studies. Using the restricted maximum likelihood (REML) method with a random effects model, the study accounted for variations across different studies. Statistical tests, file drawer analysis, and influence measure analysis were performed, along with assessments of heterogeneity and publication bias through forest and funnel plots. Despite this extensive analysis, the findings indicate that city density has a negligible effect on the severity of COVID-19, challenging the prevailing assumptions in the literature.

A Systematic Review of Living Labs in the Context of Sustainable Development with a Focus on Bioeconomy

The living lab (LL) concept has a significant potential to drive sustainable development, particularly in the bioeconomy sector, by assisting communities in improving their quality of life whilst also considering the environmental impact. In this context, the main research question was the following: is there any specific mechanism through which living labs operate under the sustainable development concept? We reviewed 120 papers addressing this topic and performed a bibliometric analysis on the linkage between sustainability and living labs by applying the methodology of a systematic review. We concluded that living labs can drive innovation and experimentation in sustainability, which can be transposed into tangible solutions to economic, environmental, and social problems. The role of living labs in the transition to a bioeconomy is discussed and further research directions are presented.

Vaccine hesitancy throughout the COVID-19 vaccination trajectory among immigrant and non-immigrant older adults: a cohort study

OBJECTIVES

The aims of this study were to examine vaccine hesitancy for COVID-19 vaccinations, comparing immigrant and non-immigrant older adults (aged ≥60 years), after accounting for group-level and individual-level characteristics, and the interaction between immigrant and socio-economic status.

STUDY DESIGN

This study used a retrospective cohort design.

METHODS

Analyses were conducted using R version 4.3.2. Logistic regression models had the dependent variables of obtained any COVID-19 vaccinations vs not and obtained all four required COVID-19 vaccinations vs not. The linear regression model's dependent variable was the interval in days between the COVID-19 vaccination availability and the date of obtaining the first COVID-19 vaccination.

RESULTS

In the cohort of older adults (n = 35,109), immigrants were less likely than non-immigrants to obtain a single COVID-19 vaccination (P < 0.001) or the full series of required COVID-19 vaccinations (P < 0.001); however, immigrants vs non-immigrants delayed only in obtaining the first vaccination (P < 0.001) but not the remaining required COVID-19 vaccinations. In the linear regression model, a longer interval before obtaining the first COVID-19 vaccination was associated with immigrant status (P < 0.001), lower socio-economic status (SES; P < 0.001), and the interaction between immigrant status and low SES (P < 0.001), while a shorter interval was associated with preventive behaviours of obtaining seasonal influenza (P < 0.001) or pneumococcal (P < 0.001) vaccinations previously.

CONCLUSIONS

Immigrant status in general, and especially when combined with low SES, is a major risk factor for vaccination hesitancy. Reorienting immigrants to embrace preventive healthcare behaviours is key. Culturally appropriate communication campaigns may improve the dissemination of effective vaccination-related information to immigrant communities.

The impact of the covid-19 outbreak on unmet health care needs in istanbul

Background & aim

COVID-19 pandemic caused significant barriers to maintain health services. Our study determines the frequency and significant determinants of unmet health needs in Istanbul both in 2019, a pre-pandemic year, and in 2021, a pandemic year and compares the results COVID-19 era to a prior to pandemic year.

Methods

As our study is the first questing Istanbul experience, we estimate the frequencies and determinants of unmet healthcare need among +15 population using TurkStat's Income and Living Conditions Survey Data via Generalized Linear Models (GLMs).

Results

We found that the most prominent barriers were late appointment dates and financial difficulty both before and during the pandemic. According to our findings, women and those having any chronic disease become significantly more likely to have unmet health needs during the pandemic compared to pre-pandemic period. Indeed, the ones belonging to the lowest income group and having lower level perceived health were disadvantaged with higher change of unmet needs both prior to and during the pandemic. Furthermore, the frequency of the Istanbulers who had unmet healthcare needs increased more than 1.5 time during the COVID-19 pandemic.

Conclusions

As unmet healthcare needs due to COVID-19 jeopardizing the healthcare systems, it is important to comprehend the causes of unmet healthcare demands during infectious disease outbreaks in order to prioritize the right policies and protection strategies for the most vulnerable ones.

Cross-Theoretical Compliance: An Integrative Compliance Analysis of COVID-19 Mitigation Responses in Israel

To understand the question why people obey or break rules, different approaches have focused on different theories and subsets of variables. The present research develops a cross-theoretical approach that integrates these perspectives. We apply this in a survey of compliance with COVID-19 pandemic mitigation rules in Israel. The data reveal that compliance in this setting was shaped by a combination of variables originating from legitimacy, capacity, and opportunity theories (but not rational choice or social theories). This demonstrates the importance of moving beyond narrow theoretical perspectives of compliance, to a cross-theoretical understanding-in which different theoretical approaches are systematically integrated.

Noise complaints, the COVID-19 pandemic, and compact developments: evidence from five American cities

The COVID-19 continues to take its toll on human life. Even though to a less threatening extent, and insignificant to some, noise turns out to be one of its consequences without consensus. While individuals experience multiple restrictions and restrain from exuberant activities by spending most of their time at home, reducing public transportation and personal vehicles, overall, they end up reduce anthropogenic noise pressure. On another level, people continue reporting noise concerns at various degrees during the COVID-19 pandemic. To draw a bigger picture as to whether or not these complaints have increased during the COVID-19 compared to the same period last year, this research examines them in five major American cities: New York, Chicago, San Francisco, Phoenix, and Dallas. Furthermore, the study also assessed the complaint patterns, whether reported in compact or sprawled areas. The findings highlight that either the noise complaints increased or decreased during the COVID-19 crisis. Accordingly, four of the five selected cities, except San Francisco, showed a decrease in reported noise. As it turns out, compact developments correlate significantly and positively with noise complaints in all study areas, except in Phoenix. These findings call for regulating and prioritizing noise-related policies. Planners and urban designers can thus advise to sustain environmental planning and public health issues, especially in planning compact developments.

Towards building resilient cities to pandemics: A review of COVID-19 literature

With the global prevalence of COVID-19 disease, the concept of urban resilience against pandemics has drawn the attention of a wide range of researchers, urban planners, and policymakers. This study aims to identify the major dimensions and principles of urban resilience to pandemics through a systematic review focused on lessons learned from the COVID-19 pandemic and comparing different perspectives regarding resilient urban environments to such diseases. Based on the findings, the study proposes a conceptual framework and a series of principles of urban resilience to pandemics, consisting of four spatial levels: housing, neighborhoods, city, and the regional and national scales, and three dimensions of pandemic resilience: pandemic-related health requirements, environmental psychological principles, and general resilience principles. The findings show that resilient cities should be able to implement the pandemic-related health requirements, the psychological principles of the environment to reduce the stresses caused by the pandemic, and the general principles of resilience in the smart city context. This framework provides scholars and policymakers with a comprehensive understanding of resilience on different scales and assists them in making better-informed decisions.

Associations Between Built Environment Factors and SARS-CoV-2 Infections at the Neighbourhood Level in a Metropolitan Area in Germany

COVID-19-related health outcomes displayed distinct geographical patterns within countries. The transmission of SARS-CoV-2 requires close spatial proximity of people, which can be influenced by the built environment. Only few studies have analysed SARS-CoV-2 infections related to the built environment within urban areas at a high spatial resolution. This study examined the association between built environment factors and SARS-CoV-2 infections in a metropolitan area in Germany. Polymerase chain reaction (PCR)-confirmed SARS-CoV-2 infections of 7866 citizens of Essen between March 2020 and May 2021 were analysed, aggregated at the neighbourhood level. We performed spatial regression analyses to investigate associations between the cumulative number of SARS-CoV-2 infections per 1000 inhabitants (cum. SARS-CoV-2 infections) up to 31.05.2021 and built environment factors. The cum. SARS-CoV-2 infections in neighbourhoods (median: 11.5, IQR: 8.1-16.9) followed a marked socially determined north-south gradient. The effect estimates of the adjusted spatial regression models showed negative associations with urban greenness, i.e. normalized difference vegetation index (NDVI) (adjusted β =  - 35.36, 95% CI: - 57.68; - 13.04), rooms per person (- 10.40, - 13.79; - 7.01), living space per person (- 0.51, - 0.66; - 0.36), and residential (- 0.07, 0.16; 0.01) and commercial areas (- 0.15, - 0.25; - 0.05). Residential areas with multi-storey buildings (- 0.03, - 0.12; 0.06) and green space (0.03, - 0.05; 0.11) did not show a substantial association. Our results suggest that the built environment matters for the spread of SARS-CoV-2 infections, such as more spacious apartments or higher levels of urban greenness are associated with lower infection rates at the neighbourhood level. The unequal intra-urban distribution of these factors emphasizes prevailing environmental health inequalities regarding the COVID-19 pandemic.

A general urban spreading pattern of COVID-19 and its underlying mechanism

Currently, the global situation of COVID-19 is aggravating, pressingly calling for efficient control and prevention measures. Understanding the spreading pattern of COVID-19 has been widely recognized as a vital step for implementing non-pharmaceutical measures. Previous studies explained the differences in contagion rates due to the urban socio-political measures, while fine-grained geographic urban spreading pattern still remains an open issue. Here, we fill this gap by leveraging the trajectory data of 197,808 smartphone users (including 17,808 anonymous confirmed cases) in nine cities in China. We find a general spreading pattern in all cities: the spatial distribution of confirmed cases follows a power-law-like model and the spreading centroid human mobility is time-invariant. Moreover, we reveal that long average traveling distance results in a high growth rate of spreading radius and wide spatial diffusion of confirmed cases in the fine-grained geographic model. With such insight, we adopt the Kendall model to simulate the urban spreading of COVID-19 which can well fit the real spreading process. Our results unveil the underlying mechanism behind the spatial-temporal urban evolution of COVID-19, and can be used to evaluate the performance of mobility restriction policies implemented by many governments and to estimate the evolving spreading situation of COVID-19.

Changes in mobility amid the COVID-19 pandemic in Sapporo City, Japan: An investigation through the relationship between spatiotemporal population density and urban facilities

By the end of 2021, the Omicron variant of coronavirus disease 2019 had become the dominant cause of a worldwide pandemic crisis. This demands a deeper analysis to support policy makers in creating interventions that not only protect people from the pandemic but also remedy its negative effects on the economy. Thus, this study investigated people's mobility changes through the relationship between spatiotemporal population density and urban facilities. Results showed that places related to daily services, restaurants, commercial areas, and offices experienced decreased visits, with the highest decline belonging to commercial facilities. Visits to health care and production facilities were stable on weekdays but increased on holidays. Educational institutions' visits decreased on weekdays but increased on holidays. People's visits to residential housing and open spaces increased, with the rise in residential housing visits being more substantial. The results also confirmed that policy interventions (e.g., declaration of emergency and upgrade of restriction level) have a great impact on people's mobility in the short term. The findings would seem to indicate that visit patterns at service and restaurant places decreased least during the pandemic. The analysis outcomes suggest that policy makers should pay more attention to risk perception enhancement as a long-term measure. Furthermore, the study clarified the population density of each facility type in a time series. Improving model performance would be promising for tracking and predicting the spread of future pandemics.

Measuring the effects of Compactness/Sprawl on COVID 19 spread patterns at the neighborhood level

This study analyzes the compactness/sprawl index and its effects on the spread of COVID-19 in the neighborhoods of Ahvaz, Iran. Multiple Criteria Decision Making and GIS techniques were used to develop the index. Also, the effects of compactness/sprawl on COVID-19 were investigated using a regression model. It was found that when considering the number of COVID-19 cases per 1000 people, the compactness/sprawl index did not affect the spread of the disease. However, it had a low but significant effect if the raw number of cases was considered. Results also showed that the compactness index significantly affected the raw number of cases, with a coefficient of 0.291, indicating that more compact neighborhoods had more COVID-19 cases. This is unsurprising as more people live in compact areas and, therefore, the raw number of cases is also likely to be higher. In the absence of proper control measures, this could result in further contact between people, thereby, increasing the risk of virus spread. Overall, we found that compactness had a dual effect on the spread of COVID-19 in Ahvaz. We conclude that proper development and implementation of control measures in well-designed compact neighborhoods are essential for enhancing pandemic resilience.

Effects of the built environment and human factors on the spread of COVID-19: A systematic literature review

Soon after its emergence, COVID-19 became a global problem. While different types of vaccines and treatments are now available, still non-pharmacological policies play a critical role in managing the pandemic. The literature is enriched enough to provide comprehensive, practical, and scientific insights to better deal with the pandemic. This research aims to find out how the built environment and human factors have affected the transmission of COVID-19 on different scales, including country, state, county, city, and urban district. This is done through a systematic literature review of papers indexed on the Web of Science and Scopus. Initially, these databases returned 4264 papers, and after different stages of screening, we found 166 relevant papers and reviewed them. The empirical papers that had at least one case study and analyzed the effects of at least one built environment factor on the spread of COVID-19 were selected. Results showed that the driving forces can be divided into seven main categories: density, land use, transportation and mobility, housing conditions, demographic factors, socio-economic factors, and health-related factors. We found that among other things, overcrowding, public transport use, proximity to public spaces, the share of health and services workers, levels of poverty, and the share of minorities and vulnerable populations are major predictors of the spread of the pandemic. As the most studied factor, density was associated with mixed results on different scales, but about 58 % of the papers reported that it is linked with a higher number of cases. This study provides insights for policymakers and academics to better understand the dynamic roles of the non-pharmacological driving forces of COVID-19 at different levels.

Migration for Better Jobs or Better Living: Shifts in China

Traditionally, studies of mobility follow two main strands: migration driven by better jobs and by better living. However, the interactions and shifts between them are rarely addressed. In the largest-scale domestic migration, millions of Chinese movers have experienced changes in migration motivations in the past ten years. Starting with migration patterns, we attempt to explore the interaction and changes in migration motivations in a dynamic way and relate them to the evolution of socio-economic contexts. Based on the latest two population censuses (2010 and 2020) in mainland China, we built an empirical model attributing migration motivations to job and living conditions, and then estimated the model by ordinary least squares (OLS) and quadratic assignment procedure (QAP) methods. The results reveal that employment is the primary and fundamental factor, though its impact is weakening. Good living is becoming significantly influential in migration willingness, and there is an interactive effect between the factors of job and living. Furthermore, we offer an explanation of the motivation evolution as being migrants' response to socio-economic status to maximize their utility. This study contributes to the migration literature from a longitudinal lens, and appeals to a continuous focus on migration evolution in the scientific research on population geography.

Spatio-temporal distribution pattern of COVID-19 in the Northern Italy during the first-wave scenario: The role of the highway network

Background

The rapid outbreak of Coronavirus disease 2019 (COVID-19) has posed several challenges to the scientific community. The goal of this paper is to investigate the spread of COVID-19 in Northern Italy during the so-called first wave scenario and to provide a qualitative comparison with the local highway net.

Methods

Fixed a grid of days from February 27, 2020, the cumulative numbers of infections in each considered province have been compared to sequences of thresholds. As a consequence, a time-evolving classification of the state of danger in terms of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, in view of the smallest threshold overtaken by this comparison, has been obtained for each considered province. The provinces with a significant amount of cases have then been collected into matrices containing only the ones featuring a significant amount of cases.

Results

The time evolution of the classification has then been qualitatively compared to the highway network, to identify similarities and thus linking the rapid spreading of COVID-19 and the highway connections.

Conclusions

The obtained results demonstrate how the proposed model properly fits with the spread of COVID-19 along with the Italian highway transport network and could be implemented to analyze qualitatively other disease transmissions in different contexts and time periods.

The impact of geo-environmental factors on global COVID-19 transmission: A review of evidence and methodology

Studies on Coronavirus Disease 2019 (COVID-19) transmission indicate that geo-environmental factors have played a significant role in the global pandemic. However, there has not been a systematic review on the impact of geo-environmental factors on global COVID-19 transmission in the context of geography. As such, we reviewed 49 well-chosen studies to reveal the impact of geo-environmental factors (including the natural environment and human activity) on global COVID-19 transmission, and to inform critical intervention strategies that could mitigate the worldwide effects of the pandemic. Existing studies frequently mention the impact of climate factors (e.g., temperature and humidity); in contrast, a more decisive influence can be achieved by human activity, including human mobility, health factors, and non-pharmaceutical interventions (NPIs). The above results exhibit distinct spatiotemporal heterogeneity. The related analytical methodology consists of sensitivity analysis, mathematical modeling, and risk analysis. For future studies, we recommend highlighting geo-environmental interactions, developing geographically statistical models for multiple waves of the pandemic, and investigating NPIs and care patterns. We also propose four implications for practice to combat global COVID-19 transmission.

COVID-19 and the compact city: Implications for well-being and sustainable urban planning

This paper provides new evidence on the role of city planning, urban form, and built environment characteristics in health and well-being during the coronavirus disease (COVID-19) pandemic. Based on survey and geographic information systems (GIS) data from Oslo and Viken in Norway, the paper investigates changes in health and well-being due to COVID-19 and how the compact city and its characteristics relate to these changes. Findings indicate that self-reported measures of health and well-being worsened due to COVID-19. The most substantial changes were reported for life satisfaction, anxiety, and satisfaction with leisure, personal relationships, and vacations. General health, happiness, and satisfaction with income also declined during COVID-19 in comparison with pre-COVID-19 times. Overall, residents of compact neighborhoods reported lower well-being during COVID-19 compared to residents of lower-density neighborhoods. Important compact city characteristics - higher neighborhood density, reliance on public transport, smaller dwellings, and less green space - were negatively associated with well-being and health outcomes during COVID-19. In contrast, another compact city attribute, the presence of numerous local facilities, was positively linked to well-being and health during COVID-19. Based on these findings, the paper presents possible implications for sustainable urban planning and compact cities.

Urban diversity and epidemic resilience: The case of the COVID-19

The spread of the coronavirus pandemic offers a unique opportunity to improve our understanding of the role of urban planning strategies in the resilience of urban communities confronting a pandemic. This study examines the relationship between urban diversity and epidemiological resilience by empirically assessing the relation between the level of neighborhood homogeneity and the probability of being infected by the coronavirus. We focus on the ultra-Orthodox Jewish community in Israel, a relatively closed community that was disproportionately and severely affected by the pandemic. The findings indicate a monotonic but nonlinear relationship between the level of ultra-Orthodox prevalence in a neighborhood and a resident's probability of contracting COVID-19. As the fraction of ultra-Orthodox individuals in the neighborhood decreases, the fraction of infected population decreases significantly and more strongly that can be explained without recourse to urban diversity considerations. This relationship is found to be significant and strong, even when other variables are accounted for that had hitherto been perceived as central to coronavirus distribution, such as housing density, socioeconomic level of the neighborhood, and number of people per household. The findings are important and relevant to many societies around the globe in which a variety of populations have a separatist lifestyle.

A Novel Predictor for Micro-Scale COVID-19 Risk Modeling: An Empirical Study from a Spatiotemporal Perspective

Risk assessments for COVID-19 are the basis for formulating prevention and control strategies, especially at the micro scale. In a previous risk assessment model, various "densities" were regarded as the decisive driving factors of COVID-19 in the spatial dimension (population density, facility density, trajectory density, etc.). However, this conclusion ignored the fact that the "densities" were actually an abstract reflection of the "contact" frequency, which is a more essential determinant of epidemic transmission and lacked any means of corresponding quantitative correction. In this study, based on the facility density (FD), which has often been used in traditional research, a novel micro-scale COVID-19 risk predictor, facility attractiveness (FA, which has a better ability to reflect "contact" frequency), was proposed for improving the gravity model in combination with the differences in regional population density and mobility levels of an age-hierarchical population. An empirical analysis based on spatiotemporal modeling was carried out using geographically and temporally weighted regression (GTWR) in the Qingdao metropolitan area during the first wave of the pandemic. The spatiotemporally nonstationary relationships between facility density (attractiveness) and micro-risk of COVID-19 were revealed in the modeling results. The new predictors showed that residential areas and health-care facilities had more reasonable impacts than traditional "densities". Compared with the model constructed using FDs (0.5159), the global prediction ability (adjusted R2) of the FA model (0.5694) was increased by 10.4%. The improvement in the local-scale prediction ability was more significant, especially in high-risk areas (rate: 107.2%) and densely populated areas (rate in Shinan District: 64.4%; rate in Shibei District: 57.8%) during the outset period. It was proven that the optimized predictors were more suitable for use in spatiotemporal infection risk modeling in the initial stage of regional epidemics than traditional predictors. These findings can provide methodological references and model-optimized ideas for future micro-scale spatiotemporal infection modeling.