Spatial risk for a superspreading environment: Insights from six urban facilities in six global cities across four continents.

Introduction: This study sets out to provide scientific evidence on the spatial risk for the formation of a superspreading environment. Methods: Focusing on six common types of urban facilities (bars, cinemas, gyms and fitness centers, places of worship, public libraries and shopping malls), it first tests whether visitors' mobility characteristics differ systematically for different types of facility and at different locations. The study collects detailed human mobility and other locational data in Chicago, Hong Kong, London, São Paulo, Seoul and Zurich. Then, considering facility agglomeration, visitors' profile and the density of the population, facilities are classified into four potential spatial risk (PSR) classes. Finally, a kernel density function is employed to derive the risk surface in each city based on the spatial risk class and nature of activities. Results: Results of the human mobility analysis reflect the geographical and cultural context of various facilities, transport characteristics and people's lifestyle across cities. Consistent across the six global cities, geographical agglomeration is a risk factor for bars. For other urban facilities, the lack of agglomeration is a risk factor. Based on the spatial risk maps, some high-risk areas of superspreading are identified and discussed in each city. Discussion: Integrating activity-travel patterns in risk models can help identify areas that attract highly mobile visitors and are conducive to superspreading. Based on the findings, this study proposes a place-based strategy of non-pharmaceutical interventions that balance the control of the pandemic and the daily life of the urban population.

Media Reports on COVID-19 Vaccinations: A Study of Topic Modeling in South Korea.

Early successes in controlling the COVID-19 pandemic have prevented Republic of Korea from implementing a prompt, large-scale vaccine rollout to the public. The influence of traditional media on public opinion remains critical and substantial in Republic of Korea, and there have been heated debates about vaccination in traditional media reports in Korea. Effective and efficient public health communication is integral in managing public health challenges. This study explored media reports on the COVID-19 vaccines during the pandemic in Republic of Korea. 12,399 media news reports from May 2020 to September 2021 were collected. An LDA topic model was applied in order to analyze and compare the topics drawn from each study phase using words from the unstructured text data. Although media reports from before the national vaccination implementation focused on the development and rollout of COVID-19 vaccines, diverse topics were reported without any overlap. After the vaccination rollout, the biggest concern was the side effects of the COVID-19 vaccine. In sum, Republic of Korea's major media outlets reported on diverse topics rather than generating a common discourse about topics related to COVID-19 vaccination.

A metropolitan-scale, three-dimensional agent-based model to assess the effectiveness of the COVID-19 Omicron wave interventions in a hyperdense city: a case study of Hong Kong.

We simulated the COVID-19 Omicron spread in Hong Kong, China, by building a novel three-dimensional agent-based model that incorporates its vertically expanded, hyperdense urban environment. The model examined the effectiveness of the 'zero-COVID' interventions (i.e., Compulsory Universal Testing (CUT) and citywide lockdown) that were for debate during the Omicron wave in Hong Kong. We found that such stringent interventions would be effective only with even faster and stricter implementation. Therefore, flexible long-term strategies should also be considered to contain and prevent future infectious diseases.

Spatial-Temporal Accessibility and Inequality of Veterinary Service in Hong Kong: A Geographic Information System-Based Study.

Veterinary services are vital to the welfare of pets and their owners. Previous studies examined multiple factors affecting pet owners' decision to consult veterinarians, yet few studied the spatial accessibility of veterinary services. This study is one of the pioneering studies on the spatial-temporal accessibility of veterinary service and how it is associated with social and spatial inequality in Hong Kong. We measured the spatial availability and accessibility of both general and 24/7 veterinary clinics (i.e., veterinary clinics offering service for 24 hours, seven days a week or providing emergency services outside of business hours) using Geographic Information System and principal component analysis. We found that the spatial distribution pattern of general and 24/7 veterinary clinics can be explained by the average district-to-district distances and the area of a district. In addition, social and spatial inequality of access to veterinary services were observed. The spatial accessibility of general veterinary clinics within walking distance is negatively correlated with household size and the number of public-housing and subsidized-housing households, but positively correlated with the number of private-housing households. The spatial availability and accessibility of 24/7 veterinary service are positively correlated with the number of private housing households and households with the highest monthly household income, and the latter also positively correlates with a population with a post-secondary degree, further shedding light on the social and spatial inequality issue that communities with wealthier households and highly educated populations have more accessibility to 24/7 veterinary services. Last, we argue that the need-based veterinary support tends to target remote rural areas while overlooking the new growth areas close to the traditional urban core but poor in accessibility to veterinary care. Therefore, a comprehensive investigation into the pet ownership landscape and their needs over space and time will be beneficial to construct a more robust animal welfare system in Hong Kong.

Geographic Clustering of Fast-Food Restaurants Around Secondary Schools in Hong Kong.

INTRODUCTION: Clustering of fast-food restaurants around schools facilitates fast-food consumption among students, which may cause obesity. We examined the prevalence of fast-food restaurants and identified the clusters of fast-food restaurants near secondary schools in Hong Kong. METHODS: We collected data of Western fast-food chain restaurants and 490 secondary schools in Hong Kong. Descriptive statistics and buffer analysis identified the prevalence of fast-food restaurants around the secondary schools within 400-m and 800-m buffers. Additional analyses compared schools stratified by the 3 main regions in Hong Kong, district-level population density, and median monthly household income. We used Getis-Ord GI* hot spot analysis to measure spatial clusters of fast-food restaurants around schools and Global Moran's I to measure the spatial autocorrelation based on each school and the number of fast-food restaurants within the 400-m buffer. RESULTS: The average number of fast-food restaurants within 400 m and 800 m of a school was 2.0 and 6.3, respectively. Seven in 10 secondary schools had at least 1 fast-food restaurant within 400 m. The number of schools with no fast-food restaurants was higher in Hong Kong Island, considered the "rich region" in Hong Kong. Hot spots of clusters were significantly located in the high-density downtown areas. We observed significant spatial autocorrelation between fast-food restaurants and secondary schools in the areas with high density, low income, and high income (P < .001, z > 2.58). CONCLUSION: Fast-food restaurants were substantially clustered around secondary schools in Hong Kong. Territory-wide studies about the health effect of fast-food clusters around schools on children and adolescents are warranted in Hong Kong.

Smart city lifestyle sensing, big data, geo-analytics and intelligence for smarter public health decision-making in overweight, obesity and type 2 diabetes prevention: the research we should be doing.

The public health burden caused by overweight, obesity (OO) and type-2 diabetes (T2D) is very significant and continues to rise worldwide. The causation of OO and T2D is complex and highly multifactorial rather than a mere energy intake (food) and expenditure (exercise) imbalance. But previous research into food and physical activity (PA) neighbourhood environments has mainly focused on associating body mass index (BMI) with proximity to stores selling fresh fruits and vegetables or fast food restaurants and takeaways, or with neighbourhood walkability factors and access to green spaces or public gym facilities, making largely naive, crude and inconsistent assumptions and conclusions that are far from the spirit of 'precision and accuracy public health'. Different people and population groups respond differently to the same food and PA environments, due to a myriad of unique individual and population group factors (genetic/epigenetic, metabolic, dietary and lifestyle habits, health literacy profiles, screen viewing times, stress levels, sleep patterns, environmental air and noise pollution levels, etc.) and their complex interplays with each other and with local food and PA settings. Furthermore, the same food store or fast food outlet can often sell or serve both healthy and non-healthy options/portions, so a simple binary classification into 'good' or 'bad' store/outlet should be avoided. Moreover, appropriate physical exercise, whilst essential for good health and disease prevention, is not very effective for weight maintenance or loss (especially when solely relied upon), and cannot offset the effects of a bad diet. The research we should be doing in the third decade of the twenty-first century should use a systems thinking approach, helped by recent advances in sensors, big data and related technologies, to investigate and consider all these factors in our quest to design better targeted and more effective public health interventions for OO and T2D control and prevention.

The Food Environments of Fruit and Vegetable Consumption in East and Southeast Asia: A Systematic Review.

Fruit and vegetable (FV) consumption benefits the health of populations. This can be especially the case in locations which have undergone significant changes in their food environments, such as East and Southeast Asian countries. This current systematic review is the first to study the food environments-facilitators, barriers, and moderators-associated with FV consumption in East and Southeast Asia. We consulted five electronic academic databases of English peer-reviewed papers published between 2010 and 2020 and found 31 studies. Results of these studies show that individuals strongly perceive FVs as being high-quality and safe, and having trust in their benefits. Food businesses with modernized systems have significantly fostered the consumption of FVs. A main barrier to FV consumption, however, is financial concerns, exacerbated by food businesses with FV unavailability and urbanization-induced FV price inflation and dietary patterns. Demographics and shopping patterns further hinder FV consumption. The fragmented and conditionalized findings of the 31 studies require standardized FV consumption measurements. Unlike the impact of FV consumption determinants and their interactions in Western countries, those in Asia, particularly countries other than China, have been substantially understudied. Therefore, as the research gaps in studies of food environments and FV consumption in East and Southeast Asia urgently demand scholarly attention, this paper proposes recommendations that favour the consumption of FVs.

Explaining Racial Inequality in Food Security in Columbus, Ohio: A Blinder-Oaxaca Decomposition Analysis.

Food insecurity is a leading public health challenge in the United States. In Columbus, Ohio, as in many American cities, there exists a great disparity between Black and White households in relation to food insecurity. This study investigates the degree to which this gap can be attributed to differences in food shopping behavior, neighborhood perception, and socioeconomic characteristics. A Blinder-Oaxaca decomposition method is used to analyze a household survey dataset collected in 2014. We find a 34.2 percent point difference in food security between White and Black households. Variables related to food shopping behavior, neighborhood perception, and socioeconomic characteristics explain 13.8 percent, 11.6 percent, and 63.1 percent of the difference, respectively. These independent variables combined can explain 68.2 percent of the food security gap between White and Black households. Most of this is attributable to socioeconomic variables. Sense of friendship in neighborhood, use of private vehicles, and satisfaction of neighborhood food environment also partially contribute to the food security gap.

Inpatient mortality in transition-aged youth with rheumatic disease: an analysis of the National Inpatient Sample.

BACKGROUND: Transition from pediatric to adult care is a vulnerable time for youth with chronic diseases. In youth with rheumatic disease, studies show high rates of loss to follow up and increased disease activity. However, mortality data are lacking. In this study, we assessed whether transitional age is a risk factor for inpatient mortality. METHODS: We analyzed the 2012-2014 National Inpatient Sample database, a representative sample of discharges in the United States. Individuals with rheumatic diseases were identified by International Statistical Classification of Disease - 9 (ICD-9) codes at time of discharge. Youth were categorized into three age groups: pre-transitional (11-17), transitional (18-24) and post transitional (25-31). We fitted univariable and multivariable logistic regression models to assess whether transitional age was a risk factor for inpatient mortality. RESULTS: There were 30,269 hospital discharges which met our inclusion criteria of diagnosis and age. There were 195 inpatient deaths (0.7%). The most common causes of death were infection (39.5%), pulmonary disease (13.8%), and cardiac disease (11.2%). The Odds ratio for inpatient mortality of a transitional-aged individual was 1.18 compared to controls (p = 0.3). Black race (OR = 1.4), male sex (OR = 1.75), and a diagnosis of systemic sclerosis (OR = 4.81) or vasculitis (OR = 2.85) were the greatest risk factors of inpatient mortality. CONCLUSION: Transitional age was not a risk factor for inpatient mortality in this study. We did identify other risk factors other than age. Further studies are required to assess if there is an increased risk of mortality in outpatients of the transitional age group.

Explained and unexplained racial and regional inequality in obesity prevalence in the United States.

Objective: There are substantial racial and regional disparities in obesity prevalence in the United States. This study partitioned the mean Body Mass Index (BMI) and obesity prevalence rate gaps between non-Hispanic blacks and non-Hispanic whites into the portion attributable to observable obesity risk factors and the remaining portion attributable to unobservable factors at the national and the state levels in the United States (U.S.) in 2010. Design: This study used a simulated micro-population dataset combining common information from the Behavioral Risk Factor Surveillance System and the U.S. Census data to obtain a reliable, large sample representing the adult populations at the national and state levels. It then applied a reweighting decomposition method to decompose the black-white mean BMI and obesity prevalence disparities at the national and state levels into the portion attributable to the differences in distribution of observable obesity risk factors and the remaining portion unexplainable with risk factors. Results: We found that the observable differences in distribution of known obesity risk factors explain 18.5% of the mean BMI difference and 20.6% of obesity prevalence disparities between non-Hispanic blacks and non-Hispanic whites. There were substantial variations in how much the differences in distribution of known obesity risk factors can explain black-white gaps in mean BMI (-67.7% to 833.6%) and obesity prevalence (-278.5% to 340.3%) at the state level. Conclusion: The results from this study demonstrate that known obesity risk factors explain a small proportion of the racial, ethnic and between-state disparities in obesity prevalence in the United States. Future etiologic studies are required to further understand the causal factors underlying obesity and racial, ethnic and geographic disparities.

Adult obesity prevalence at the county level in the United States, 2000-2010: Downscaling public health survey data using a spatial microsimulation approach.

Obesity is a growing public health concern in the United States. There is a need to monitor obesity prevalence at the local level to intervene in place-specific ways. However, national public health surveys suppress the local geographic information of respondents due to small sample sizes and the protection of confidentiality. This study therefore, uses a spatial microsimulation approach to estimate obesity prevalence rates at the county level across the United States to visualize temporal, spatial and spatio-temporal changes from 2000 to 2010 for use in the monitoring of obesity prevalence. This method iteratively replicates the demographic characteristics of public health survey respondents with census data for those areas. Following, Local Moran's I was used to identify clusters of high and low obesity prevalence. The findings showed that obesity prevalence rose dramatically over the last decade with substantial variation across counties and states. Counties in Southern states, especially along the Mississippi River and Appalachian Mountains and counties containing or in proximity to Native American reservation sites showed elevated obesity prevalence rates across the decade. Counties in Midwestern states had higher obesity prevalence rates compared to counties in Western and Northeastern states. This study demonstrated the use of spatial microsimulation modeling as an alternative method to obtain reliable obesity prevalence rates at the local-level using existing health survey and census data.

Designing an Agent-Based Model Using Group Model Building: Application to Food Insecurity Patterns in a U.S. Midwestern Metropolitan City.

Recent advances in computing resources have increased interest in systems modeling and population health. While group model building (GMB) has been effectively applied in developing system dynamics models (SD), few studies have used GMB for developing an agent-based model (ABM). This article explores the use of a GMB approach to develop an ABM focused on food insecurity. In our GMB workshops, we modified a set of the standard GMB scripts to develop and validate an ABM in collaboration with local experts and stakeholders. Based on this experience, we learned that GMB is a useful collaborative modeling platform for modelers and community experts to address local population health issues. We also provide suggestions for increasing the use of the GMB approach to develop rigorous, useful, and validated ABMs.

Impacts of Federally Funded State Obesity Programs on Adult Obesity Prevalence in the United States, 1998-2010.

OBJECTIVES: From 2000 to 2010, the Division of Nutrition, Physical Activity, and Obesity (DNPAO) at the Centers for Disease Control and Prevention (CDC) funded 37 state health departments to address the obesity epidemic in their states through various interventions. The objective of this study was to investigate the overall impacts of CDC-DNPAO statewide intervention programs on adult obesity prevalence in the United States. METHODS: We used a set of an individual-level, interrupted time-series regression and a quasi-experimental analysis to evaluate the overall effect of CDC-DNPAO intervention programs before (1998-1999) and after (2010) their implementation by using data from CDC's Behavioral Risk Factor Surveillance System. RESULTS: States that implemented the CDC-DNPAO program had a 2.4% to 3.8% reduction in the odds of obesity during 2000-2010 compared with states without the program. The effect of the CDC-DNPAO program varied by length of program implementation. A quasi-experimental analysis found that states with longer program implementation did not necessarily have lower odds of obesity than states with shorter program implementation. CONCLUSIONS: Statewide obesity interventions can contribute to reduced odds of obesity in the United States. Future research should evaluate the CDC-DNPAO programs in relation to their goals, objectives, and other environmental obesity risk factors to inform future interventions.