Are leading urban centers predisposed to global risks- A analysis of the global south from COVID-19 perspective

Understanding Vaccine Hesitancy in U.S. Prisons: Perspectives from a Statewide Survey of Incarcerated People

Much of the American response to the COVID-19 pandemic was characterized by a divergence between general public opinion and public health policy. With little attention paid to individuals incarcerated during this time, there is limited direct evidence regarding how incarcerated people perceived efforts to mediate the harms of COVID-19. Prisons operate as a microcosm of society in many ways but they also face unique public health challenges. This study examines vaccine hesitancy-and acceptance-among a sample of individuals incarcerated within adult prisons in Pennsylvania. Using administrative records as well as rich attitudinal data from a survey of the incarcerated population, this study identifies a variety of social and historical factors that are-and are not-associated with an incarcerated person's willingness to receive the COVID-19 vaccine. Our findings highlight vaccination challenges unique to the carceral context and offer policy recommendations to improve trust in credible health messengers and health service provision for this often overlooked but vulnerable population.

Urban Health Scholarship and Practice in the Post-Pandemic Era

The COVID-19 pandemic highlighted several challenges that cities face that can affect the health of urban populations. These challenges are an opportunity for sharpening of our urban health scholarship, to rethink the questions the field should be asking, and how the answers to those questions should guide practice. The central role of inequities in cities, the politics of urban health, communication for health, the deployment of health care, and the future of urban living are all areas that merit attention by scholars and practitioners in the field in coming decades.

COVID-19 resilience index in European Union countries based on their risk and readiness scale

Addressing risks and pandemics at a country level is a complex task that requires transdisciplinary approaches. The paper aims to identify groups of the European Union countries characterized by a similar COVID-19 Resilience Index (CRI). Developed in the paper CRI index reflects the countries' COVID-19 risk and their readiness for a crisis situation, including a pandemic. Moreover, the study detects the factors that significantly differentiate the distinguished groups. According to our research, Bulgaria, Hungary, Malta, and Poland have the lowest COVID-19 Resilience Index score, with Croatia, Greece, Czechia, and Slovakia following close. At the same time, Ireland and Scandinavian countries occupy the top of the leader board, followed by Luxemburg. The Kruskal-Wallis test results indicate four COVID-19 risk indicators that significantly differentiate the countries in the first year of the COVID-19 pandemic. Among the significant factors are not only COVID-19-related factors, i.e., the changes in residential human mobility, the stringency of anti-COVID-19 policy, but also strictly environmental factors, namely pollution and material footprint. It indicates that the most critical global environmental issues might be crucial in the phase of a future pandemic. Moreover, we detect eight readiness factors that significantly differentiate the analysed country groups. Among the significant factors are the economic indicators such as GDP per capita and labour markets, the governance indicators such as Rule of Law, Access to Information, Implementation and Adaptability measures, and social indicators such as Tertiary Attainment and Research, Innovation, and Infrastructure.

Pandemic vulnerability index of US cities: A hybrid knowledge-based and data-driven approach

Cities become mission-critical zones during pandemics and it is vital to develop a better understanding of the factors that are associated with infection levels. The COVID-19 pandemic has impacted many cities severely; however, there is significant variance in its impact across cities. Pandemic infection levels are associated with inherent features of cities (e.g., population size, density, mobility patterns, socioeconomic condition, and health & environment), which need to be better understood. Intuitively, the infection levels are expected to be higher in big urban agglomerations, but the measurable influence of a specific urban feature is unclear. The present study examines 41 variables and their potential influence on the incidence of COVID-19 infection cases. The study uses a multi-method approach to study the influence of variables, classified as demographic, socioeconomic, mobility and connectivity, urban form and density, and health and environment dimensions. This study develops an index dubbed the pandemic vulnerability index at city level (PVI-CI) for classifying the pandemic vulnerability levels of cities, grouping them into five vulnerability classes, from very high to very low. Furthermore, clustering and outlier analysis provides insights on the spatial clustering of cities with high and low vulnerability scores. This study provides strategic insights into levels of influence of key variables upon the spread of infections, along with an objective ranking for the vulnerability of cities. Thus, it provides critical wisdom needed for urban healthcare policy and resource management. The calculation method for the pandemic vulnerability index and the associated analytical process present a blueprint for the development of similar indices for cities in other countries, leading to a better understanding and improved pandemic management for urban areas, and more resilient planning for future pandemics in cities across the world.

COVID-19 Patterns in Araraquara, Brazil: A Multimodal Analysis

The epidemiology of COVID-19 presented major shifts during the pandemic period. Factors such as the most common symptoms and severity of infection, the circulation of different variants, the preparedness of health services, and control efforts based on pharmaceutical and non-pharmaceutical interventions played important roles in the disease incidence. The constant evolution and changes require the continuous mapping and assessing of epidemiological features based on time-series forecasting. Nonetheless, it is necessary to identify the events, patterns, and actions that were potential factors that affected daily COVID-19 cases. In this work, we analyzed several databases, including information on social mobility, epidemiological reports, and mass population testing, to identify patterns of reported cases and events that may indicate changes in COVID-19 behavior in the city of Araraquara, Brazil. In our analysis, we used a mathematical approach with the fast Fourier transform (FFT) to map possible events and machine learning model approaches such as Seasonal Auto-regressive Integrated Moving Average (ARIMA) and neural networks (NNs) for data interpretation and temporal prospecting. Our results showed a root-mean-square error (RMSE) of about 5 (more precisely, a 4.55 error over 71 cases for 20 March 2021 and a 5.57 error over 106 cases for 3 June 2021). These results demonstrated that FFT is a useful tool for supporting the development of the best prevention and control measures for COVID-19.

Community response to COVID-19: The case of rental housing cooperatives in Melbourne, Australia and Choluteca, Honduras

COVID-19 and its restrictions have had widely documented negative impacts for private and social rental sectors, internationally. Limited evidence exists about how the pandemic effects were experienced in alternative forms of renting such as housing cooperatives. Rental cooperatives, recognised for their principles of democratic control, education and training and concern for community, may offer different outcomes for members than more individually-oriented rental forms. This paper seeks to explore whether and how COVID-19 was responded to within cooperative rental housing models, and if the pandemic posed a challenge to cooperative principles. Using a social practices approach, the analysis first identifies cooperative members' formal and informal responses to COVID-19, and second explores the meaning of such activities in the pandemic context in Australia and Honduras cooperatives. The continuity of usual housing cooperative practices and pandemic measures were analysed via in-depth interviews with 15 residents. Findings indicate that cooperative responses acted to reduce negative impacts of the pandemic or to find effective solutions. Rental housing cooperative residents' lived experiences during the COVID-19 pandemic, invite us to reflect on the role of housing cooperatives in the housing sector, the importance of collaborative housing models and the relevance of housing-based community resilience.

Experiencing Public Spaces in Southern Chile: Analysing the Effects of the Built Environment on Walking Perceptions

In Latin American cities, the built environment is facing crucial challenges in the 21st century, not only in terms of the redesign of the physical environment, but also how to remodel public spaces as healthier places for walking and social interaction. The objective of this article is to evaluate the effects of the built environment on walking perceptions in a central neighbourhood in the intermediate city of Valdivia, Chile. The methodology integrates quantitative and qualitative methods to explore which elements of the physical built environment ease and hinder walkability. Depthmap software and Simpson's Diversity Index are used to evaluate connectivity and diversity of land uses at street level. Additionally, the People Following method and 26 walking interviews are conducted using the Natural Go-Along technique to analyse pedestrians' perceptions about their mobility environment. The results show that the factors that promote walkability mainly include streets with high connectivity values, wide pavements, diversity of greening, and facade characteristics of buildings with architectural heritage causing tranquillity, longing, and happiness. On the contrary, factors that inhibit walkability are related to poor-quality and narrow sidewalks, cars parked on sidewalks, dirty streets, and motorized traffic and vehicular noise causing negative emotions in walking perceptions such as tiredness, anger, disgust, discomfort, and insecurity, with negative effects on the well-being of residents that vary according to age and gender. Finally, recommendations are oriented to improve public spaces in central areas in southern Chile, to address moving towards more liveable and inclusive environments and support well-being through urban design in these types of context.

Predicting COVID-19 Infections in Eswatini Using the Maximum Likelihood Estimation Method

COVID-19 country spikes have been reported at varying temporal scales as a result of differences in the disease-driving factors. Factors affecting case load and mortality rates have varied between countries and regions. We investigated the association between socio-economic, weather, demographic and health variables with the reported cases of COVID-19 in Eswatini using the maximum likelihood estimation method for count data. A generalized Poisson regression (GPR) model was fitted with the data comprising 15 covariates to predict COVID-19 risk in the whole of Eswatini. The results show that the variables that were key determinants in the spread of the disease were those that included the proportion of elderly above 55 years at 98% (95% CI: 97–99%) and the proportion of youth below the age of 35 years at 8% (95% CI: 1.7–38%) with a pseudo R-square of 0.72. However, in the early phase of the virus when cases were fewer, results from the Poisson regression showed that household size, household density and poverty index were associated with reported COVID-19 cases in the country. We then produced a disease-risk map of predicted COVID-19 in Eswatini using variables that were selected by the regression model at a 5% significance level. The map could be used by the country to plan and prioritize health interventions against COVID-19. The identified areas of high risk may be further investigated to find out the risk amplifiers and assess what could be done to prevent them.

Effects of COVID-19 restriction measures in Indonesia: A comparative spatial and policy analysis of selected urban agglomerations

With higher densities, urban agglomerations account for the fastest rates of COVID-19 transmission. In Indonesia, one of the most rapidly urbanizing regions in the world, the national government issues overall policy on the pandemic. However, implementation is often contingent on local governments. Many policies aim to stem the spread of infection by controlling people's mobility or regulating their daily activities. Urban agglomerations are a strategic site of investigation in this light, because they consist of interconnected communities governed by various levels and jurisdictions. This paper analyzes the effects of policy interventions relative to confirmed cases in the seven major urban agglomerations in Indonesia (totaling 30 municipal/district governments). Data were collected from confirmed and fatality trends from March to mid-October 2020, which were contrasted with corresponding policies for each jurisdiction. By sorting the indicators of the spread of the pandemic and its corresponding control measures, we reach conclusions about which dimensions served to curb or trigger the surge of COVID-19 clusters. The analysis unsurprisingly shows that within each agglomeration, the main cities continue to represent the highest number of confirmed cases despite variations between them. This study also highlights two key findings. First, the effectiveness of distancing measures depends considerably on the capacity of governments to implement restrictions. For example, budget limitations resulted in uneven implementation of national mandates by decentralized authority. Facilities and services at different locations also influence our understanding of disease transmission. Second, people's ability and willingness to engage with a policy regime is contingent upon personal values or economic constraints. The study shows that viewing the spatial distribution of COVID-19 at the scale of urban agglomerations helps to explain key aspects of transmission and policy, pointing to recommendations about pursuing certain protocols. Nevertheless, key challenges remain to meet the full potential of this analytical approach, due to relatively low levels of testing and inadequate data collection measures in Indonesia.