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The study deals with three factors of general nature and their impact on the economic security of the region's periphery. The essence of regional periphery economic security is described. Processes such as digitalization, urbanization and COVID-19 are considered and their impact on the economic security of the region's periphery is described. These factors are considered separately, and the characteristics of positive and negative effects coming from them are presented. The relationship between all three factors is revealed, and the influence of these processes in the aggregate is described. It was found that, cumulatively, the effect of digitalization, urbanization and COVID-19 on the economic security of the region's periphery is changing and may acquire a completely different nature than the impact of factors individually.

Understanding how countries' socio-economic, environmental, health status, and climate factors have influenced the dynamics of COVID-19 is essential for public health, particularly in Africa. This study explored the relationships between African countries' COVID-19 cases and deaths and their socio-economic, environmental, health, clinical, and climate variables. It compared the performance of Ordinary Least Square (OLS) regression, the spatial lag model (SLM), the spatial error model (SEM), and the conditional autoregressive model (CAR) using statistics such as the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Root Mean Square Error (RMSE), and coefficient of determination ( R 2 ). Results showed that the SEM with the 10-nearest neighbours matrix weights performed better for the number of cases, while the SEM with the maximum distance matrix weights performed better for the number of deaths. For the cases, the number of tests followed by the adjusted savings, Gross Domestic Product (GDP) per capita, dependence ratio, and annual temperature were the strongest covariates. For deaths, the number of tests followed by malaria prevalence, prevalence of communicable diseases, adjusted savings, GDP, dependence ratio, Human Immunodeficiency Virus (HIV) prevalence, and moisture index of the moistest quarter play a critical role in explaining disparities across countries. This study illustrates the importance of accounting for spatial autocorrelation in modelling the dynamics of the disease while highlighting the role of countries' specific factors in driving its dynamics. [ABSTRACT FROM AUTHOR]

Background and Objectives: Many studies have analyzed the impact of rurality on the incidence and consequences of COVID-19 infection. However, these studies have not considered the impact of different numbers of nursing homes in rural, semi-urban, or urban areas. Our objective was to analyze the effect of the factor of rurality on the incidence and mortality of COVID-19 while accounting for the impact of the variable of nursing home residency. In addition, we performed a comparative analysis of the infected population in semi-urban and rural areas. Methods: We first analyzed COVID-19 infection in all populations in the Balaguer Primary Health Care Area before examining the impact of rurality using Bayesian logistic regression analysis, specifically excluding the population living in nursing homes. We also performed an epidemiological and clinical analysis comparing rural and semi-urban areas. Results: We found higher incidence of and higher relative and absolute mortality from COVID-19 infection in semi-urban areas than in rural areas. After excluding nursing home residents from our sample, the Bayesian analysis indicated that rurality was not protective against COVID-19 infection or mortality. The incidence rates, specific mortality rates, and case fatality rates were similar in semi-urban and rural areas. All comorbidities, except chronic obstructive pulmonary disease, were associated with higher mortality, while no symptoms were associated with higher mortality. Conclusions: Excluding the population residing in nursing homes from the analysis, we found that rurality was not a protective factor against either infection or mortality during the first COVID-19 wave. Our Bayesian model analysis confirmed that rurality alone did not enhance survival among residents of rural areas. [ABSTRACT FROM AUTHOR]

The emergence of new techniques in both microbial biotechnology and artificial intelligence (AI) is opening up a completely new field for monitoring and sometimes even controlling the evolution of pathogens. However, the now famous generative AI extracts and reorganizes prior knowledge from large datasets, making it poorly suited to making predictions in an unreliable future. In contrast, an unfamiliar perspective can help us identify key issues related to the emergence of new technologies, such as those arising from synthetic biology, whilst revisiting old views of AI or including generative AI as a generator of abduction as a resource. This could enable us to identify dangerous situations that are bound to emerge in the not‐too‐distant future, and prepare ourselves to anticipate when and where they will occur. Here, we emphasize the fact that amongst the many causes of pathogen outbreaks, often driven by the explosion of the human population, laboratory accidents are a major cause of epidemics. This review, limited to animal pathogens, concludes with a discussion of potential epidemic origins based on unusual organisms or associations of organisms that have rarely been highlighted or studied. [ABSTRACT FROM AUTHOR]

Simple Summary: This paper reviews key issues regarding the spread of diseases that affect both humans and animals, known as zoonotic diseases. These diseases, which make up about 70% of all new and existing diseases, are increasingly interconnected with factors like the environment, society, and economics. The term "zoonoses" is discussed beyond just veterinary medicine, emphasizing its complex nature influenced by human activities and climate change. Bioethical principles and strategies for preventing these diseases are proposed. A case study on animal slaughter during disasters highlights ethical challenges in how we manage health across species, leading to discussions on "zoonoethics". The paper also explores how these diseases emerge and the ethical and political issues around antimicrobial resistance (AMR), with recommendations for tackling AMR. The management of these diseases will require the adoption and acceleration of the "One Health" approach, which recognizes the interconnectedness and interdependence between human, animal, and environmental health. This paper presents a critical review of key issues related to the emergence of new networks for the spread of zoonotic diseases amid the mass extinction of species. Zoonotic and infectious diseases account for approximately 70% of new and existing diseases affecting humans and animals. The initial section argues that the term "zoonoses" should not be confined to single-cause events within veterinary medicine. Instead, zoonoses should be viewed as complex, systemic phenomena shaped by interrelated factors, including environmental, sociocultural, and economic elements, influenced by anthropogenic climate change. The second section presents bioethical principles and potential strategies for those engaged in zoonotic disease prevention. The third section uses the slaughter of animals in disaster settings as a case study to illustrate the need for further clarification of normative and interspecies justice conflicts in One Health ethics. This section concludes with an outlook on "zoonoethics". Section four develops the analysis of the interlinked elements that trigger zoonoses and examines antimicrobial resistance (AMR) from an ethical and political standpoint, concluding with policy recommendations for addressing AMR. Section five offers a critical reflection, integrating contributions from zoonoethics, human ecology, and the ecotheological turn. Finally, section six concludes with a call to action and policy recommendations for an inclusive, intercultural, and gender-sensitive One Health approach. [ABSTRACT FROM AUTHOR]

Context: The global impact of the SARS-CoV-2 pandemic has been uneven, with some regions experiencing significant excess mortality while others have been relatively unaffected. Yet factors which predict this variation remain enigmatic, particularly at large spatial scales. Objectives: We aimed to uncover the key drivers of excess mortality across countries and regions to help understand the factors contributing to the varied impacts of the pandemic worldwide. Methods: We used spatially explicit Bayesian models that integrate environmental, socio-demographic and endemic disease data at the country level to provide robust global estimates of excess SARS-CoV-2 mortality (P-scores) for the years 2020 and 2021. Results: We find that urbanization, gross domestic product (GDP) and spatial patterns are strong predictors of excess mortality, with countries characterized by low GDP but high urbanization experiencing the highest levels of excess mortality. Intriguingly, we also observed that the prevalence of malaria and human immunodeficiency virus (HIV) are associated with country-level SARS-CoV-2 excess mortality in Africa and the Western Pacific, whereby countries with low HIV prevalence but high malaria prevalence tend to have lower levels of excess mortality. While these associations are correlative in nature at the macro-scale, they emphasize that patterns of endemic disease and socio-demographic factors are needed to understand the global dynamics of SARS-CoV-2. Conclusions: Our study identifies factors associated with variation in excess mortality across countries, providing insights into why some were more impacted by the pandemic than others. By understanding these predictors, we can better inform global outbreak management strategies, such as targeting medical resources to highly urban countries with low GDP and high HIV prevalence to reduce mortality during future outbreaks. [ABSTRACT FROM AUTHOR]

The spread and severity of COVID-19 within the European regions have been highly heterogeneous, with significant differences in both the number of infected persons and mortality across regions. This paper improves the weak ability of welfare variables, such as the HDI, to explain COVID-19 mortality. We propose a novel 'Epidemiological Risk Index', including environmental quality, global interaction, health system infrastructure, and population characteristics, which provides a better explanation of pandemic mortality in European regions. We deal with spatial interdependence in COVID-19 mortality by using spatial lagged covariates and Geographical Weighted Regressions. The findings in this study call attention to the influence of epidemiological factors in addition to purely development factors in explaining the severity of COVID-19. [ABSTRACT FROM AUTHOR]

Indoor environment is the less studied environ-ment in the context of its ecosystem services. But, in this unprecedented time of urbanization and Covid-19, people spend most of their times at indoor environment. This study conducted a systematic review of studies that aim: a) to provide a systematic review on ecosystem services provided by indoor environment towards livable human environment; b) to analyze the research gap; and c) to develop a framework of Livable Human Indoor Environment. The results show that indoor ecosystem services play a very significant roles towards human well-being especially in term of psychology, health and emotion. This review also identifies some limitations such as method used in the analyze papers was only focus on the review study, plus most the papers were from developed country (UK, USA, China, etc.). This study de-veloped a framework that can guide in policymaking, urban planning, and indoor built strategy, that can improve the livability of human indoor environment. [ABSTRACT FROM AUTHOR]

The United Nations currently estimates that over half of the global population has lived in cities since 2017 and that this proportion is continuing to grow, particularly in the Global South. While urbanization is not new, increased population density combined with accelerating rates of (re)emerging and noncommunicable diseases as well as growing economic disparities has created new challenges to human health and well-being. Here, I examine peri-urban communities, peripheral settlements on the edges of urban areas populated by rural people, and argue that these areas are often overlooked, despite becoming increasingly common. Thus, human biologists should move beyond categorizing these spaces as transitional. Using unplanned, peri-urban communities around Lima, Peru as a case study, I detail the complexity of political ecological factors that impact infectious disease risk and rates in peri-urban communities. Using disease mechanisms, I demonstrate the importance of a biocultural approach and a political ecology perspective when investigating infectious disease. I highlight how human biologists and anthropologists are uniquely positioned to explore the heterogeneity of infectious disease patterns and pathways in an increasingly urbanized world., (© 2024 Wiley Periodicals LLC.)

Purpose: Recent literature has highlighted the overlapping contribution of demographic characteristics and spatial factors to urban-rural disparities in SARS-CoV-2 transmission and outcomes. Yet the interplay between individual characteristics, hospitalisation, and spatial factors for urban-rural disparities in COVID-19 mortality have received limited attention. Methods: To fill this gap, we use national surveillance data collected by the European Centre for Disease Prevention and Control and we fit a generalized linear model to estimate the association between COVID-19 mortality and the individuals' age, sex, hospitalisation status, population density, share of the population over the age of 60, and pandemic wave across urban, intermediate and rural territories. Findings: We find that in what type of territory individuals live (urban-intermediate-rural) accounts for a significant difference in their probability of dying given SARS-COV-2 infection. Hospitalisation has a large and positive effect on the probability of dying given SARS-CoV-2 infection, but with a gradient across urban, intermediate and rural territories. For those living in rural areas, the risk of dying is lower than in urban areas but only if hospitalisation was not needed; while for those who were hospitalised in rural areas the risk of dying was higher than in urban areas. Conclusions: Together with individuals' demographic characteristics (notably age), hospitalisation has the largest effect on urban-rural disparities in COVID-19 mortality net of other individual and regional characteristics, including population density and the share of the population over 60. [ABSTRACT FROM AUTHOR]

Air pollution poses a persuasive threat to global health, demonstrating widespread detrimental effects on populations worldwide. Exposure to pollutants, notably particulate matter with a diameter of 2.5 µm (PM2.5), has been unequivocally linked to a spectrum of adverse health outcomes. A nuanced understanding of the relationship between them is crucial for implementing effective policies. This study employs a comprehensive investigation, utilizing the extended health production function framework alongside the system generalized method of moments (SGMM) technique, to scrutinize the interplay between air pollution and health outcomes. Focusing on a panel of the top twenty polluted nations from 2000 to 2021, the findings yield substantial insights. Notably, PM2.5 concentration emerges as a significant factor, correlating with a reduction in life expectancy by 3.69 years and an increase in infant mortality rates by 0.294%. Urbanization is found to increase life expectancy by 0.083 years while concurrently decreasing infant mortality rates by 0.00022%. An increase in real per capita gross domestic product corresponds with an improvement in life expectancy by 0.21 years and a decrease in infant mortality rates by 0.00065%. Similarly, an elevated school enrollment rate is associated with a rise in life expectancy by 0.17 years and a decline in infant mortality rates by 0.00032%. However, a higher population growth rate is found to modestly decrease life expectancy by 0.019 years and slightly elevate infant mortality rates by 0.000016%. The analysis reveals that per capita greenhouse gas emissions exert a negative impact, diminishing life expectancy by 0.486 years and elevating infant mortality rates by 0.00061%, while per capita energy consumption marginally reduces life expectancy by 0.026 years and increases infant mortality rates by 0.00004%. Additionally, economic volatility shock presents a notable decrement in life expectancy by 0.041 years and an increase in infant mortality rates by 0.000045%, with inflationary shock further exacerbating adverse health outcomes by lowering life expectancy by 0.70 years and elevating infant mortality rates by 0.00025%. Moreover, the study scrutinizes the role of institutional quality, revealing a constructive impact on health outcomes. Specifically, the institutional quality index is associated with an increase in life expectancy by 0.66% and a decrease in infant mortality rates by 0.0006%. Extending the analysis to examine the nuanced dimensions of institutional quality, the findings discern that economic institutions wield a notably stronger positive influence on health outcomes compared to political and institutional governance indices. Finally, the results underscore the pivotal moderating role of institutional quality in mitigating the deleterious impact of PM2.5 concentration on health outcomes, counterbalancing the influence of external shocks, and improving the relationships between explanatory variables and health outcome indicators. These findings offer critical insights for guiding evidence-based policy implications, with a focus on fostering resilient, sustainable, and health-conscious societies. [ABSTRACT FROM AUTHOR]

Hierarchical diagnosis and treatment (HDT) is an important exploration direction to alleviate the rising pressure of health expenses and medical insurance fund expenditure in China, and to maintain and protect the public health in this country. In recent years, the construction of compact county medical communities (CCMC) has become the primary approach for implementing the HDT. Utilizing the quasi-natural experiment of the pilot project of CCMC in Sichuan Province in 2019, coupled with county-level data extracted from the ' Sichuan Provincial Health Statistics Yearbook ' spanning the years 2008 to 2021, this research evaluates the effect of the pilot project of CCMC on promoting HDT under the medical insurance package payment model. The results show that the pilot project of CCMC has significantly increased the number of consultations per capita of medical and health institutions in pilot counties by 0.434 times, of which the number of consultations per capita of primary medical institutions has increased by 0.340 times; the number of hospitalizations per capita in public hospitals and primary medical institutions in pilot counties increased significantly, and the surgery rate of inpatients in public hospitals increased by 5% compared to before the pilot. There was no significant impact on the allocation of medical facilities and human resources in the pilot counties. Therefore, the construction of CCMC under the medical insurance package payment mode has promoted the realization of the county-level HDT. These findings provide valuable insights for healthcare policy, especially in developing and implementing effective strategies for HDT in county-level medical institutions. [ABSTRACT FROM AUTHOR]

Aim: Compare roles of nurses and midwives and physicians in reducing COVID‐19 deaths measured with a case fatality ratio. Background: The roles and responsibilities of different health disciplines to the COVID‐19 pandemic vary. While more difficult to measure, objective assessments of discipline contributions of nurses and midwives and physicians can be viewed through statistical analysis. Methods: Population‐level data are analysed with scatter plots, bivariate correlations, partial correlation and multiple linear regression models to illustrate the contributions of nurses and midwives and physicians in reducing COVID‐19 deaths. The role of nurses and midwives and physicians in protecting the community against COVID‐19 deaths is explored and compared using competing effects of affluence, age and urbanization. Data analysis software programs include Excel v.2016, SPSS v.28 and Fisher r‐to‐z transformation. Results: Nurses and midwives reduce COVID‐19 deaths significantly more than physicians. This difference remains while controlling for physician care, economic affluence, median age and urbanization individually or in combination. In contrast, the role of physicians in reducing COVID‐19 deaths is less independent than nurses and midwives. Linear regression results insinuate when nursing and physician care are collated together with other predicting factors, physicians' contribution to community protection against COVID‐19 case fatality ratio is statistically explained by nursing and midwifery care. Discussion: Unlike physicians, the nursing and midwifery workforce is bigger and located throughout all healthcare system levels and, therefore, is more accessible to the community. This is an important point in explaining the contribution of nurses and midwives to reducing COVID‐19 deaths when compared with physicians. Conclusion: This study suggests that, worldwide, the nursing and midwifery workforce may play a more significant role in protecting the community against COVID‐19 deaths than physicians. Implications for health policy, nursing and midwifery practice: The findings from this study offer a unique perspective for health authorities to further understand the complementary and independent role of the nursing and midwifery workforce in respect of the healthcare team. This study suggests the importance of a broader range of healthcare services, especially during the pandemic, for example, COVID‐19. With the permission of health authorities, the nursing and midwifery workforce should have further extension of their scope of practice in situations such as pandemics due to their broader access to the community. [ABSTRACT FROM AUTHOR]

Based on archival research and interviews with state officials and state-affiliated academics, this article argues that the Chinese state's decision to slow down rural land transfer since 2017 is a Polanyian countermovement against the adverse consequences of earlier, excessive labor and land commodification. The central government's drive for land consolidation is contingent upon and structurally constrained by the process of rural labor commodification. By focusing on connections between land and labor and situating agrarian transformation under the context of national capital accumulation, this study examines land beyond agriculture and argues for the continued importance of the classical Agrarian Questions. [ABSTRACT FROM AUTHOR]

The need to make more accurate grain demand (GD) forecasting has become a major topic in the current international grain security discussion. Our research aims to improve short-term GD prediction by establishing a multi-factor model that integrates the key factors: shifts in dietary structures, population size and age structure, urbanization, food waste, and the impact of COVID-19. These factors were not considered simultaneously in previous research. To illustrate the model, we projected China's annual GDP from 2022 to 2025. We calibrated key parameters such as conversion coefficients from animal foods to feed grain, standard person consumption ratios, and population size using the latest surveys and statistical data that were either out of date or missing in previous research. Results indicate that if the change in diets continued at the rate as observed during 2013–2019 (scenario 1), China's GD is projected to be 629.35 million tons in 2022 and 658.16 million tons in 2025. However, if diets shift to align with the recommendations in the Dietary Guideline for Chinese Residents 2022 (scenario 2), GD would be lower by 5.9–11.1% annually compared to scenario 1. A reduction in feed grain accounts for 68% of this change. Furthermore, for every 1 percentage point increase in the population adopting a balanced diet, GD would fall by 0.44–0.73 million tons annually during that period. Overlooking changes in the population age structure could lead to an overprediction of annual GDP by 3.8% from 2022 to 2025. With an aging population, China's GD would fall slightly, and adopting a balanced diet would not lead to an increase in GD but would have positive impacts on human health and the environment. Our sensitivity analysis indicated that reducing food waste, particularly cereal, livestock, and poultry waste, would have significant effects on reducing GD, offsetting the higher demand due to rising urbanization and higher incomes. These results underscore the significance of simultaneous consideration of multiple factors, particularly the dietary structure and demographic composition, resulting in a more accurate prediction of GD. Our findings should be useful for policymakers concerning grain security, health, and environmental protection. [ABSTRACT FROM AUTHOR]

• This paper analyses the co-occurrence of urban heat and COVID-19 pandemic. • Impacts of COVID-19 on urban heat challenges include urban temperature anomalies, variations in air pollutant concentrations, unbalanced energy development, and thermal health risks. • The occurrence of COVID-19 reshaped the method to investigate urban heat challenges. • Learning from the COVID-19 is an inevitable course to build a more resilient urban system. Cities, the main place of human settlements, are under various mega challenges such as climate change, population increase, economic growth, urbanization, and pandemic diseases, and such challenges are mostly interlinked. Urban heat, due to heatwaves and heat islands, is the combined effect of climate change and urbanization. The COVID-19 is found to be a critical intervention of urban heat. However, the interrelationship between COVID-19 and urban heat has not been fully understood, constraining urban planning and design actions for improving the resilience to the dual impacts of heat and the pandemic. To close this research gap, this paper conducted a review on the co-occurrence of urban heat and the COVID-19 pandemic for a better understanding of their synergies, conflicts or trade-offs. The research involves a systematic review of urban temperature anomalies, variations in air pollutant concentrations, unbalanced energy development, and thermal health risks during the pandemic lockdown. In addition, this paper further explored data sources and analytical methods adopted to screen and identify the interventions of COVID-19 to urban heat. Overall, this paper is of significance for understanding the impact of COVID-19 on urban heat and provides a reference for coping with urban heat and the pandemic simultaneously. The world is witnessing the co-existence of heat and the pandemic, even in the post-pandemic era. This study can enlighten city managers, planners, the public, and researchers to collaborate for constructing a robust and resilient urban system for dealing with more than one challenges. [ABSTRACT FROM AUTHOR]

Digital platforms operating on a global scale (social media, commerce, services, e-government and e-management services) are increasingly critical means for communication, exchange, and daily life, even without a direct use of platforms or connected devices. Their growing ecosystem and locally specific variations increase possibilities for data collection and targeting specific user profiles. Work life has become increasingly dependent on platforms including, for example, Microsoft's power platform, Google cloud, or the Apple iOS system. But also within community services and urban development, platforms are increasingly forming a firm component that may be for submitting taxes, getting health services, reporting suspicious activities in the neighborhood, profiling a political campaign, monitoring energy performances, or providing new employment opportunities. We argue that these processes in fact describe a specific kind of urbanization that is driven and administered through the digital means of platform technologies. This process of platform urbanization imbues every aspect of the urban environment and has experienced an acceleration during the recent pandemic. This contribution introduces the concept of platform urbanization and investigates the implications on citizenship and its digital realm, followed by an attempt to expand its conception. To bolster our argument, we discuss the case of Singapore, where the monitoring and control of the virus spread expedited the nation's digitization efforts and where platform corollaries of the pandemic were seamlessly incorporated into an increasingly digital urban environment. In what follows, the last section brings about a series of questions addressing an urban digital citizenship scenario within platform urbanization as a space of empowerment, inclusion and participation. [ABSTRACT FROM AUTHOR]

This study examines the impact of green innovation, sustainable economic growth, and carbon emission on public health issues in Saudi Arabia. As Saudi Arabia is struggling to increase human development that also incorporates public health, it is important to understand the determinant factors and significant solutions to curtail public health issues. The study pioneers investigation into the role of green innovation aimed at countering public health problems caused by environmental damage. For econometric estimates, a non-linear autoregressive distributed lagged approach is used, which confirms that economic growth and carbon emissions are the main sources of public health issues in Saudi Arabia. Further, the empirical results demonstrate that greater attention to green innovation, education, and health spending plays a significant role in minimizing health issues. The positive shock in green innovation is helpful in terms of reducing public health issues. The findings are significant for policy suggestions; some recommendations are as follows: (i) The Saudi government needs to enhance funding in research and development to increase green innovation within the country. (ii) Education and health sector should be improved and increase it outreach throughout the country. [ABSTRACT FROM AUTHOR]

The spatial distribution of the COVID‐19 infection rate in the city of Palma (Balearic Islands) is analyzed from the geolocation of positive cases by census tract and its relationship with socioeconomic variables is evaluated. Data on infections have been provided by the Health Service of the Ministry of Health and Consumption of the Government of the Balearic Islands. The study combines several methods of analysis: spatial autocorrelation, calculation of the Gini index and least squares regression, and weighted geographical regression. The results show that the pandemic comprised five waves in the March 2020–March 2022 period, corresponding to the months of April 2020, August 2020, December 2020, July 2021, and January 2022. Each wave shows a particular geographical distribution pattern, however, the second and third waves show higher levels of spatial concentration. In this sense, the second wave, affecting the peripheral neighborhoods of the eastern part of the city. The Gini index confirms geographical imbalances in the distribution of infections in the first waves of the pandemic. In addition, the regression models indicate that the most significant socioeconomic variables in the prediction of COVID‐19 infection are average income, percentage of children under 18 years of age, average size of the household, and percentage of single‐person households. The study shows that economic imbalances in the city have had a clear influence on the spatial pattern of pandemic distribution. It shows the need to implement spatial justice policies in income distribution to balance the effects of the pandemic. Plain Language Summary: The article analyses the spatio‐temporal pattern of the COVID‐19 pandemic in Palma (Mallorca, Balearic Islands, Spain) based on positive case counts. A study is carried out at the census tract level relating the incidence of the pandemic to socio‐economic variables. The results show that the incidence of the pandemic has been very unequal at the geographical level. Neighborhoods in the eastern periphery of the city have been the most affected. These areas also concentrate low income levels, small dwellings and households with large numbers of members. Concentration indices confirm these imbalances. The second wave of infection is the one that shows the clearest pattern of concentration of cases. The lack of spatial justice and the contrasts between the west (rich) and east (poor) of the city are revealed. Key Points: The COVID‐19 pandemic in Palma had a concentrated pattern in the peripheral neighborhoods of the eastern part of the cityGini index confirms the geographical imbalances in the distribution of the infection, specially in the first waves of the pandemiaHousehold characteristics (average income, percentage of single‐person, percentage of children under 18 years, average size) explain spatial COVID‐19 pattern [ABSTRACT FROM AUTHOR]

Worldwide, the role of nursing workforce in reducing COVID-19 case fatality ratio (CFR) is analyzed with scatter plots, Pearson's r and nonparametric, partial correlation and multiple linear regression models. The potential confounders, median age, health expenditure, physician density, and urbanization were incorporated for calculating the independent role of nursing workforce in protecting against COVID-19 CFR. The study findings suggested that (1) the nursing workforce inversely and significantly correlates with COVID-19 CFR; (2) this relationship remained independent of the confounding effects of each individual confounder or their combination; (3) Nursing workforce was the only variable identified as a significant contributor for reducing COVID-19 CFR, when it was incorporated into stepwise regression model with health expenditure, median age, physician density, and urbanization for analyzing their individual predicting effects on COVID-19 CFR. A strong message for the health authorities is that, although in shortage, nursing workforce showed their significant role in reducing COVID-19 deaths worldwide. This study highlights that the role of nursing workforce should be incorporated into population health research., (© 2024 The Authors. Nursing & Health Sciences published by John Wiley & Sons Australia, Ltd.)

Bangladesh is one of the most densely populated countries in the world struggling to prevent COVID-19 (coronavirus disease 2019). This study employed correlation, cluster analysis, and multiple linear regression analyses using district-wise COVID-19 infection and socioeconomic data. It is observed that there is a strong positive correlation (r = 0.876, P <.001) between population density and COVID-19, explaining a 60% variation in Bangladesh. The relationship between urbanization and COVID-19 is also positively strong (r = 0.802, P <.001). Urban settlements have a higher risk of spreading diseases due to the enormous population density. For future planning to prevent COVID-19 and other related infectious diseases, population density should be considered a risk factor. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has led to a re-examination of the urban space, and the field of planning and architecture is no exception. In this study, a conditional generative adversarial network (CGAN) is used to construct a method for deriving the distribution of urban texture through the distribution hotspots of the COVID-19 epidemic. At the same time, the relationship between urban form and the COVID-19 epidemic is established, so that the machine can automatically deduce and calculate the appearance of urban forms that are prone to epidemics and may have high risks, which has application value and potential in the field of planning and design. In this study, taking Macau as an example, this method was used to conduct model training, image generation, and comparison of the derivation results of different assumed epidemic distribution degrees. The implications of this study for urban planning are as follows: (1) there is a correlation between different urban forms and the distribution of epidemics, and CGAN can be used to predict urban forms with high epidemic risk; (2) large-scale buildings and high-density buildings can promote the distribution of the COVID-19 epidemic; (3) green public open spaces and squares have an inhibitory effect on the distribution of the COVID-19 epidemic; and (4) reducing the volume and density of buildings and increasing the area of green public open spaces and squares can help reduce the distribution of the COVID-19 epidemic. [ABSTRACT FROM AUTHOR]

This paper investigates the air quality in 107 Italian provinces in the period 2014–2019 and the association between exposure to nine outdoor air pollutants and the COVID-19 spread and related mortality in the same areas. The methods used were negative binomial (NB) regression, ordinary least squares (OLS) model, and spatial autoregressive (SAR) model. The results showed that (i) common air pollutants—nitrogen dioxide (NO2), ozone (O3), and particulate matter (PM2.5 and PM10)—were highly and positively correlated with large firms, energy and gas consumption, public transports, and livestock sector; (ii) long-term exposure to NO2, PM2.5, PM10, benzene, benzo[a]pyrene (BaP), and cadmium (Cd) was positively and significantly correlated with the spread of COVID-19; and (iii) long-term exposure to NO2, O3, PM2.5, PM10, and arsenic (As) was positively and significantly correlated with COVID-19 related mortality. Specifically, particulate matter and Cd showed the most adverse effect on COVID-19 prevalence; while particulate matter and As showed the largest dangerous impact on excess mortality rate. The results were confirmed even after controlling for eighteen covariates and spatial effects. This outcome seems of interest because benzene, BaP, and heavy metals (As and Cd) have not been considered at all in recent literature. It also suggests the need for a national strategy to drive down air pollutant concentrations to cope better with potential future pandemics. [ABSTRACT FROM AUTHOR]