Scaling law of COVID-19 cases and city size and its evolution over time

Urban scaling law quantifies the disproportional growth of urban indicators with urban population size, which is one of the simple rules behind the complex urban system. Infectious diseases are closely related to social interactions that intensify in large cities, resulting in a faster speed of transmission in large cities. However, how this scaling relationship varies in an evolving pandemic is rarely investigated and remains unclear. Here, taking the COVID- 19 epidemic in the United States as an example, we collected daily added cases and deaths from January 2020 to June 2022 in more than three thousand counties to explore the scaling law of COVID- 19 cases and city size and its evolution over time. Results show that COVID- 19 cases super- linearly scaled with population size, which means cases increased faster than population size from a small city to a large city, resulting in a higher morbidity rate of COVID- 19 in large cities. Temporally, the scaling exponent that reflects the scaling relationship stabilized at around 1.25 after a fast increase from less than one. The scaling exponent gradually decreased until it was close to one. In comparison, deaths caused by the epidemic did not show a super-linear scaling relationship with population size, which revealed that the fatality rate of COVID-19 in large cities was not higher than that in small or medium-sized cities. The scaling exponent of COVID- 19 deaths shared a similar trend with that of COVID- 19 cases but with a lag in time. We further estimated scaling exponents in each wave of the epidemic, respectively, which experienced the common evolution process of first rising, then stabilizing, and then decreasing. We also analyzed the evolution of scaling exponents over time from regional and provincial perspectives. The northeast, where New York State is located, had the highest scaling exponent, and the scaling exponent of COVID- 19 deaths was higher than that of COVID-19 cases, which indicates that large cities in this region were more prominently affected by the epidemic. This study reveals the size effect of infectious diseases based on the urban scaling law, and the evolution process of scaling exponents over time also promotes the understanding of the urban scaling law. The mechanism behind temporal variations of scaling exponents is worthy of further exploration. © 2023 Science Press. All rights reserved.

Critical Commentary: Beyond growth and density: Recentring the demographic drivers of urban health and risk in the global south

Debates within urban studies concerning the relationship between urbanisation and infectious disease focus on issues of urban population growth, density, migration and connectivity. However, an effective long-term risk and wellbeing agenda, without which the threat of future pandemics cannot be mitigated, must also take account of demographic forces and changes as critical drivers of transmission and mortality risk within and beyond cities. A better understanding of the dynamics of fertility, mortality and changing age structures – key determinants of urban decline/growth in addition to migration – provides the foundation upon which healthier cities and a healthy global urban system can be developed. The study of how basic demographic attributes and trends are distributed in space and how they interact with risks, including those of infectious disease, must be incorporated as a priority into a post-COVID-19 urban public health agenda. This perspective concurs with recent debates in urban studies emphasising the demographic drivers of urban change. Moreover, it raises critical questions about the microbial and environmental emphasis of much research on the interface of urban health and governance.

A Tale of Two Counties With the Same Telehealth Story: Experience with Cancer Genetics Testing During COVID-19 at a Community Hospital

Introduction: With the onset of the COVID-19 pandemic in 2020, the utilization of telemedicine now offered an alternative diagnostic and treatment resource to providers in many areas of medicine including oncology and cancer genetics. This care option paired with genetic testing labs' ability to send saliva-based DNA collection kits to patients, enabled our community hospital in Detroit to offer diagnostic testing without the patient coming to a healthcare setting for a host of reasons. Social determinants of health have been found to influence success with telehealth, and this study sought to analyze how successful telehealth cancer genetics care was throughout the Detroit Metro area. Methods: Patient demographics for in person visits six months before COVID were analyzed, and then compared with demographics of patients during the 2020-2021 pandemic period where visits were telehealth. Results: Pre-pandemic there were , 192 unique patients seen in person with the top three cities patients were from were Detroit (12.1%), Clinton Township (8.3%), and Saint Clair Shores (10.4%). During the pandemic, with telehealth as the major modality, the top three cities were Macomb (7.2%), Detroit (7%), and Clinton Township (7%). Detroit is in Wayne County, while St.Clair Shores and Clinton Township are in Macomb County. Per the US Census Bureau Macomb county has a median income of $64,641 and Wayne county has a median income of $49,359, and poverty level in Macomb county is 9.2% versus in Wayne the level is 20%. Conclusions: This paper outlines the challenges of initiating a telemedicine program in an urban community area and highlights the benefits of a concierge service in serving cancer patients who may have economic and historically poor perceived technologic abilities.

Building urban resilience through infrastructure exaptation

This article moves forward with the development of a young research field, aiming to merge urban exaptation processes and the science behind resilience, while facing COVID-19 pandemic, here considered as a symptom of a broader environmental crisis. This involves the understanding of the meaning of the exaptation of urban infrastructures as defined by Stephen Jay Gould. It briefly elucidates resilience science and exaptation processes embedded in socio-ecological systems. Extracted from both fields of study, exaptation processes are placed in the context of the renewal cycle, utilizing a changing framework model, commonly employed in resilience science to picture dynamics of the complex adaptive systems. In such cases, urban systems are considered prime examples. The insights generated in this endeavor are discussed, dealing with some key exaptation aspects in relation to four key attributes of resilience, i.e., "change,” "diversity,” "self-organzation,” and "learning.” Taking Mexico as a case study, we selected 10 examples to illustrate and relate these to the infrastructure exaptation of building functions, such as theaters, convention centers, and/or racecourses into hospitals, as a strategy to cope with the COVID-19 outbreak. The article elaborates a taxonomy of building infrastructure that, given its design features, allowed to be used as hospitals to face the pandemic. As a conclusion, we postulate different ways in which resilience thinking could promote the development of a new line of research for addressing designs for resilient urban social-ecological systems facing external disturbances such as pandemics. © 2023 Elsevier Inc. All rights reserved.

Public Health Framework for Smart Cities within the Comprehensive Approach to Sustainability in Europe: Case Study of Diabetes

European cities should address the climate change challenges, improving quality of life and reducing costs. They need potential smart and digital approaches. Public health (PH) has recognized climate change as a major challenge. The development of urban policies should be guided by evidence-based PH practices. The environmental health determinants and the climate crisis now represent a clear PH threat. The core of the Smart City is sustainability, and its basic condition is active PH. The inclusion of public health into the pillars of the Smart City concept to contribute toward mitigating PH crises, such as the COVID-19 pandemic, is a framework for action. Design Science Research Methodology (DSRM) is used to elicit a Smart Public Health City (SPHEC) framework. A set of PH and smart city experts participated in the DSRM process, using diabetes as a case study. The European Green Deal served as a blueprint for this transformational change toward a healthier and more sustainable city. The SPHEC framework was defined by elucidating clearly the several dimensions of the PH functions within a digital city, via the identification of a set of digital PH services that are required to support the SPHEC framework. This allows for an assessment of the actual benefits that are obtained with the digital health services, and provides evidence for guiding decision-making. The role of digital PH services emerges from the analysis of the SPHEC framework, through the development of proper digital health services within the smart city, strengthening capacity and resilience in future climate emergencies, and motivating policy makers to take this challenge more seriously. © 2023 by the authors.

Rural-Urban Differences in Workers' Access to Paid Sick Leave

Paid sick leave (PSL) is associated with health care access and health outcomes. The COVID-19 pandemic highlighted the importance of PSL as a public health strategy, yet PSL is not guaranteed in the United States. Rural workers may have more limited PSL, but research on rural PSL has been limited. We estimated unadjusted and adjusted PSL prevalence among rural versus urban workers and identified characteristics of rural workers with lower PSL access using the 2014–2017 Medical Expenditure Panel Survey. We found rural workers had lower access to PSL than urban workers, even after adjusting for worker and employment characteristics. Paid sick leave access was lowest among rural workers who were Hispanic, lacked employer-sponsored insurance, and reported poorer health status. Lower rural access to PSL poses a threat to the health and health care access of rural workers and has implications for the COVID-19 public health emergency and beyond.

COVID-19 Health Literacy in Rural and Urban Communities in Nigeria: A Key Strategy for Improving the COVID-19 Outbreak Response

Background: This study aimed to describe COVID-19 health literacy in urban and rural communities in Nigeria. Methods: A descriptive cross-sectional design was used to enrol adults from households in rural and urban communities in Akure, Southwest Nigeria. Nine questions were asked to determine respondents' health literacy, each arranged on a scale of ‘1' (very difficult) to ‘7' (very easy). We defined good health literacy as cumulative scores ≥50 points, and poor health literacy as scores <50 points. Chi-square tests and binary logistic regression were conducted on COVID-19 health literacy. Statistical significance levels were set at p <0.05. Results: The median age of the 691 respondents was 27 years (Range:18-80 years). Overall, 229 (45.8%) individuals had good COVID-19 health literacy. Among them, 143 (49.7%) individuals in urban communities had good COVID-19 health literacy (ᵡ2: 4.062, p = 0.044). Thirty-six (66.7%) adults aged >40 years in urban communities had good COVID-19 health literacy (ᵡ2: 8.995, p = 0.029), compared to 28 (56.0%) adults within the same age group in rural communities (ᵡ2: 8.387, p = 0.039). In urban communities, people >40 years had nearly two times the odds of having good COVID-19 health literacy compared to people aged ≤20 years (AOR: 1.640, 95% CI: 0.769-3.495, p = 0.200). In rural communities, people >40 years had nearly four times the odds of having good COVID-19 health literacy compared to people aged ≤20 years (AOR: 3.523, 95% CI: 1.420-8.742, p = 0.007). Conclusions: COVID-19 health education should be integrated into national health programs to address urban-rural differences in COVID-19 health literacy. © 2022 The Author(s).

Recruitment and Enrollment of Low-income, Minority Residents of Urban Public Housing into Research.

Research participation among vulnerable populations is often limited by the same socioeconomic factors that contribute to poor health. Identifying best practices for inclusion is critical to addressing health disparities. Urban public housing communities bear a disproportionate burden of chronic disease and may represent an opportunity to directly engage historically vulnerable populations in research designed to ultimately reduce that burden. We used mixed-method data to analyze recruitment effectiveness among a random sample of households (N = 380) across two public housing developments in Boston, MA who were approached for participation in a pre-COVID oral health study. Quantitative data from detailed recruitment tracking methods was analyzed to assess the relative efficiency of the methods employed. Field journals of study staff were qualitatively analyzed to identify community-specific recruitment barriers and facilitators. The participation rate among randomly sampled households was 28.6% (N = 131), with participation from primarily Hispanic (59.5%) or Black (26%) residents. Door-to-door knocking with response yielded the highest participation (44.8%), followed by responses to informational study flyers (31%). Primary barriers to enrollment included references to unemployment and employment variations, shift work, childcare responsibilities, time demands, and managing multiple appointments and social services. This study finds active, door-to-door knocking and return visits resolved barriers to participation, and reduced safety concerns and historic distrust. It's time to consider how best to adapt effective pre-COVID recruitment practices for utilization under current and future exposure conditions as effective recruitment of populations such as urban public housing residents into research is only becoming more important.

Exploring the Potential of Big Data Analytics in Urban Epidemiology Control: A Comprehensive Study Using CiteSpace.

In recent years, there has been a growing amount of discussion on the use of big data to prevent and treat pandemics. The current research aimed to use CiteSpace (CS) visual analysis to uncover research and development trends, to help academics decide on future research and to create a framework for enterprises and organizations in order to plan for the growth of big data-based epidemic control. First, a total of 202 original papers were retrieved from Web of Science (WOS) using a complete list and analyzed using CS scientometric software. The CS parameters included the date range (from 2011 to 2022, a 1-year slice for co-authorship as well as for the co-accordance assessment), visualization (to show the fully integrated networks), specific selection criteria (the top 20 percent), node form (author, institution, region, reference cited, referred author, journal, and keywords), and pruning (pathfinder, slicing network). Lastly, the correlation of data was explored and the findings of the visualization analysis of big data pandemic control research were presented. According to the findings, "COVID-19 infection" was the hottest cluster with 31 references in 2020, while "Internet of things (IoT) platform and unified health algorithm" was the emerging research topic with 15 citations. "Influenza, internet, China, human mobility, and province" were the emerging keywords in the year 2021-2022 with strength of 1.61 to 1.2. The Chinese Academy of Sciences was the top institution, which collaborated with 15 other organizations. Qadri and Wilson were the top authors in this field. The Lancet journal accepted the most papers in this field, while the United States, China, and Europe accounted for the bulk of articles in this research. The research showed how big data may help us to better understand and control pandemics.

Racial/ethnic and income disparities in neighborhood-level broadband access in 905 US cities, 2017-2021.

OBJECTIVES: Broadband access is an essential social determinant of health, the importance of which was made apparent during the COVID-19 pandemic. We sought to understand disparities in broadband access within cities and identify potential solutions to increase urban access. STUDY DESIGN: This was a descriptive secondary analysis using multi-year cross-sectional survey data. METHODS: Data were obtained from the City Health Dashboard and American Community Survey. We studied broadband access in 905 large US cities, stratifying neighborhood broadband access by neighborhood median household income and racial/ethnic composition. RESULTS: In 2017, 30% of urban households across 905 large US cities did not have access to high-speed broadband internet. After controlling for median household income, broadband access in majority Black and Hispanic neighborhoods was 10-15% lower than in majority White or Asian neighborhoods. Over time, lack of broadband access in urban households decreased from 30% in 2017 to 24% in 2021, but racial and income disparities persisted. CONCLUSIONS: As an emerging social determinant, broadband access impacts health across the life course, affecting students' ability to learn and adults' ability to find and retain jobs. Resolving lack of broadband access remains an urban priority. City policymakers can harness recent infrastructure funding opportunities to reduce broadband access disparities.

Drawing a pandemic vulnerabilities' map: The SoNAR-global Vulnerabilities Assessment digital and its output.

This paper describes the process, advantages and limitations of a qualitative methodology for defining and analyzing vulnerabilities during the COVID-19 pandemic. Implemented in Italy in two sites (Rome and outside Rome, in some small-medium sized municipalities in Latium) in 2021, this investigation employed a mixed digital research tool that was also used simultaneously in four other European countries. Its digital nature encompasses both processes of data collection. Among the most salient is that the pandemic catalyzed new vulnerabilities in addition to exacerbating old ones, particularly economic. Many of the vulnerabilities detected, in fact, are linked to previous situations, such as the uncertainties of labor markets, having in COVID-19 to the greatest negative effects on the most precarious workers (non-regular, part-time, and seasonal). The consequences of the pandemic are also reflected in other forms of vulnerability that appear less obvious, having exacerbated social isolation, not only out of fear of contagion, but because of the psychological challenges posed by containment measures themselves. These measures created not mere discomfort, but behavioral changes characterized by anxiety, fearfulness, and disorientation. More generally, this investigation reveals the strong influence of social determinants throughout the COVID-19 pandemic, creating new forms of vulnerability, as the effects of social, economic, and biological risk factors were compounded, in particular, among already marginalized populations.

A City Surveillance System for Social Health Inequalities: The Case of Barcelona.

INTRODUCTION: In the past, health inequalities were not prioritised in the political agenda of Barcelona. The change of city government (2015) was an opportunity to develop a Surveillance System for Social Health Inequalities in the city, which is described in this article. METHODS: The design of the Surveillance System formed part of the Joint Action for Health Equity in Europe (JAHEE), funded by the European Union. Various steps were considered by the experts to set up the System: define its objectives, target population, domains and indicators, and sources of information; perform data analysis; implement and disseminate the system; define the evaluation; and perform regular data updates. RESULTS: The System considers the following domains: social determinants of health, health-related with behaviours, use of healthcare, and health outcomes, and includes eight indicators. As axes of inequality, the experts chose sex, age, social class, country of origin, and geographical area. The Surveillance System for Social Health Inequalities is presented on a website including different types of figures. CONCLUSION: The methodology used to implement the Surveillance System can be used to implement similar systems in other urban areas around the world.

Healthy cities initiative in China: Progress, challenges, and the way forward.

China implemented the first phase of its National Healthy Cities pilot program from 2016-20. Along with related urban health governmental initiatives, the program has helped put health on the agenda of local governments while raising public awareness. Healthy City actions taken at the municipal scale also prepared cities to deal with the COVID-19 pandemic. However, after intermittent trials spanning the past two decades, the Healthy Cities initiative in China has reached a crucial juncture. It risks becoming inconsequential given its overlap with other health promotion efforts, changing public health priorities in response to the pandemic, and the partial adoption of the Healthy Cities approach advanced by the World Health Organization (WHO). We recommend aligning the Healthy Cities initiative in China with strategic national and global level agendas such as Healthy China 2030 and the Sustainable Development Goals (SDGs) by providing an integrative governance framework to facilitate a coherent intersectoral program to systemically improve population health. Achieving this alignment will require leveraging the full spectrum of best practices in Healthy Cities actions and expanding assessment efforts. Funding: Tsinghua-Toyota Joint Research Fund "Healthy city systems for smart cities" program.

Public Health Approach to Outdoor Urban Health

Recent years of the Covid-19 pandemic have seen a proportional increase in the amount of time we spend in our homes each day. In spite of this, urban dwellers continue to spend-although varying from area to area of the world-many hours outside their homes for work, daily needs, recreation, and social relationships. This implies that the urban environment, both tangible and intangible, has several factors that can be both protective and risky for health. As highlighted in the 2016 Quito Conference, health can be the pulse of the new urban agenda for sustainable urban development [1]. It is not easy to take stock of where we are. On a global scale, there still seems to be a limited ethical-cultural awareness, a lack of political attention and thus of resource allocation, an insufficient capacity to use innovative choices and technologies and to actively involve local communities in decision-making processes and in the implementation of possible interventions. On the other hand, there are numerous positive experiences of urban realities that have produced convincing efforts in recent decades to make our cities more livable and healthy. Let us hope that the 2030 agenda proposed by the United Nations on the Sustainable Development Goals can really exert a driving role in this direction. A real willingness to set in motion virtuous processes to guarantee us a better quality of urban life, including by agreeing to revise our development and consumption patterns, will make all the difference. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Urban landscape and climate affect residents' sentiments based on big data

Residents' sentiments are a quantitative indicator of human feelings, which is useful for optimizing urban residential environments. Little is known about the spatiotemporal variations and potential drivers of sentiment based on big data. A total of 221,104 Weibo social media data were used to quantify daily sentiment in the Beijing metropolitan area during the COVID-19 pandemic from January 1, 2021 to March 8, 2022. Deep-learning natural language processing was used to extract this dataset to investigate the spatiotemporal sentiment patterns. The density of roads and buildings, normalized difference vegetation index (NDVI), population, sky visibility factor, daily land surface temperature (LST), daily precipitation, and daily air pollution concentrations (CO, NO2, PM2.5, SO2, and O3) were explored as potential drivers of sentiment. Results show that (1) the holiday sentiment was 1.31% higher than on weekends and 4.61% higher than on weekdays. Extreme precipitation, air pollution, and COVID-19 lockdown measures have reduced sentiment. (2) The sentiment in spring was found to be the highest. The numbers of functional zones with high sentiment values (>0.8) in spring were 13.59%, in summer 34.48%, and in autumn 14.71%. (3) Sentiment was highest under conditions of moderate greenness (0.4<NDVI<0.6) and comfortable daily temperature (25 °C < LST<30 °C). (4) Sentiment was negatively associated with daily air pollutants, such as PM2.5, NO2, and CO. This paper presents the effectiveness of sentiment quantification based on social media data and deep-learning techniques. The results provide practical implications and support decisions for sustainable urban health development.

An Iterative, Participatory Approach to Developing a Neighborhood-Level Indicator System of Health and Wellbeing.

Despite increased awareness of the essential role of neighborhood characteristics for residents' health and wellbeing, the development of neighborhood-level indicator systems has received relatively little attention to date. To address this gap, we describe the participatory development process of a small-area indicator system that includes information on local health needs in a pilot neighborhood in the German city of Mannheim. To identify relevant indicators, we partnered with representatives of the city's public health department and used an iterative approach that included multiple Plan-Do-Check-Act cycles with ongoing feedback from local key stakeholders. The described process resulted in a web-based indicator system with a total of 86 indicators. Additionally, 123 indicators were perceived as relevant by stakeholders but could not be included due to data unavailability. Overall, stakeholders evaluated the participatory approach as useful. Even though the onset of the COVID-19 pandemic and the lack of some data elements hindered instrument development, close collaboration with public health partners facilitated the process. To identify and target sub-national health inequalities, we encourage local public health stakeholders to develop meaningful and useful neighborhood-level indicator systems, building on our experiences from the applied development process and considering identified barriers and facilitators.

Perceptions about Nonpharmacological Interventions in the Prevention of COVID-19 in the Field Practice Area of Jawaharlal Nehru Medical College

Introduction: COVID-19 pandemic is a major global public health threat. Coronavirus includes a large group of viruses, which infects both humans and animals. China reported the outbreak on December 31, 2019, to World Health Organization. Center for Disease Control and Prevention, USA, has published nonpharmacological interventions such as social distancing, zonal lockdown, rolling lockdown, wearing masks, and washing hands to combat the spread of COVID-19. The present study was conducted to assess the perceptions of people about nonpharmacological interventions in the prevention of COVID-19. Materials and Methods: A facility-based study was conducted among 220 participants from December 01, 2020, to February 28, 2021, among outpatients in the field practice area of urban primary health care Rukmini Nagar, under the administrative control of J. N. Medical College in Belagavi district, Karnataka. Results: A total of 220 participants were interviewed and analyzed for the study. Out of which, 36 (16.4%) were male and 184 (83.6%) were female. One hundred and seventy (77.2%) of the participants practiced good hand hygiene and personal hygiene. One hundred and forty-five (65.9%) of the participants always wore a face mask, when they were going outside. One hundred and eighty-one (82.2%) of the participants started drinking more fluids in the form of water compared with normal days. Conclusion: There was a lack of awareness about face protection and the use of hand sanitizer among the common public. Grassroots level health-care workers such as Accredited Social Health Activist, Anganwadi workers, and community volunteers should be trained for giving health education about nonpharmacological interventions to the public for COVID-19 prevention.

The correlation between attack rates and urban health indicators during the third wave of the COVID-19 outbreak in Turkey.

This study aims to analyze the inter-provincial variation in the increase of attack rates in the third wave of the COVID-19 outbreak in Turkey and to determine their relationship with potential urban health indicators. In this ecological study, dependent variables were selected as the COVID-19 attack rates of provinces before the third wave and during the third peak and the attack rate increase ratio. Urban health indicators that can function as determinants of health were calculated for each province under five headings: demographic, health capacity, economic, environmental, and socio-cultural. The epidemiologic maps were produced to show the spatial distribution of COVID-19 attack rates pre- and during the third wave. The associations with urban indicators were conducted using bivariate analysis, including Pearson or Spearman correlation analysis. A multiple linear regression model was run with variables significantly associated with increased attack rates. The results of our study show significant regional variations in COVID-19 attack rates both at the beginning and during the third wave of the COVID-19 pandemic in Turkey. Among the provinces, the attack rate increase ratio has only shown significant correlations to education level and some economic indicators, such as income, employment, industrial activity measured by electric consumption, and economic activity in the manufacturing industry. The multivariate analysis determined that the indicator of economic activity in the manufacturing industry is related to the increase of the attack rate in the third wave. Our results show that the COVID-19 cases are higher in more developed cities with more manufacturing sector activity. It makes us think that it is mainly related to inequalities arising from access to health institutions and testing. It can be determined that the partly lockdown strategy, which excluded the industrial activity in the country, concluded the higher increase in the attack rates in highly industrialized provinces.

An Urban Population Health Observatory System to Support COVID-19 Pandemic Preparedness, Response, and Management: Design and Development Study.

BACKGROUND: COVID-19 is impacting people worldwide and is currently a leading cause of death in many countries. Underlying factors, including Social Determinants of Health (SDoH), could contribute to these statistics. Our prior work has explored associations between SDoH and several adverse health outcomes (eg, asthma and obesity). Our findings reinforce the emerging consensus that SDoH factors should be considered when implementing intelligent public health surveillance solutions to inform public health policies and interventions. OBJECTIVE: This study sought to redefine the Healthy People 2030's SDoH taxonomy to accommodate the COVID-19 pandemic. Furthermore, we aim to provide a blueprint and implement a prototype for the Urban Population Health Observatory (UPHO), a web-based platform that integrates classified group-level SDoH indicators to individual- and aggregate-level population health data. METHODS: The process of building the UPHO involves collecting and integrating data from several sources, classifying the collected data into drivers and outcomes, incorporating data science techniques for calculating measurable indicators from the raw variables, and studying the extent to which interventions are identified or developed to mitigate drivers that lead to the undesired outcomes. RESULTS: We generated and classified the indicators of social determinants of health, which are linked to COVID-19. To display the functionalities of the UPHO platform, we presented a prototype design to demonstrate its features. We provided a use case scenario for 4 different users. CONCLUSIONS: UPHO serves as an apparatus for implementing effective interventions and can be adopted as a global platform for chronic and infectious diseases. The UPHO surveillance platform provides a novel approach and novel insights into immediate and long-term health policy responses to the COVID-19 pandemic and other future public health crises. The UPHO assists public health organizations and policymakers in their efforts in reducing health disparities, achieving health equity, and improving urban population health.

Health in the Postpandemic City: Contested Spatializations and Biopolitical Implications

Health and disease have been conceived as problems of urban space throughout history, and public health interventions have repeatedly been employed as spatial strategies. Critical perspectives have already utilized this special relation: Urban health is often a showcase for modes of biopolitics. We follow this example, investigating the current rearticulation of public health in the aftermath of the worldwide COVID-19 pandemic. We draw together the German debate on health in the post-pandemic city, both in the general media and in planning literature, using a discourse-analytical method and fund that two contrasting narratives emerge. The urban is considered either as the expression of pathogenic spatial density or as the site of healthy social interactions. While each narrative prefigures a very different mode of intervention, both encourage a spatialization of health, with powerful implications. Distinguishing the competing rationales thus allows better decisions on ways to promote health in the city.