Coastal erosion and flooding risk assessment based on grid scale: A case study of six coastal metropolitan areas.

Coastal areas, situated at the critical juncture of sea-land interaction, are confronted with significant challenges from coastal erosion and flooding. It is imperative to evaluate these risks and offer scientific guidance to foster regional sustainable development. This article developed a coastal risk assessment model based on grid scale, integrating both coastal exposure and socio-ecological environment. Fourteen indicators were selected, aiming to offer a systematic approach for estimating and comparing disaster risks in coastal areas. This risk assessment model was applied to Shanghai, New York, Sydney, San Francisco, Randstad, and Tokyo metropolitan areas. The results indicate: (1) Accounting for the protective role of habitat types like mangroves and the distance attenuation effect offered a more precise representation of hazard situation; (2) The integration of the Game Theory weighting method with both subjective Analytic Hierarchy Process and objective CRITIC weighting enhanced the scientific validity and rationality of the results by minimizing deviations between subjective and objective weights; (3) Shanghai exhibited the highest average hazard and vulnerability, San Francisco had the lowest average hazard and Sydney had the lowest average vulnerability; In terms of comprehensive risk, Shanghai possessed the highest average risk, while Sydney presented the lowest. The proposed model framework is designed to swiftly identify high-risk zones, providing detailed information references for local governments to devise efficacious risk management and prevention strategies.

The association of urbanicity and travel time with lung cancer screening utilization.

BACKGROUND: To examine 1) the rate of lung cancer screening (LCS) utilization in a large healthcare system in South Carolina; 2) associations of urbanicity and travel time with LCS utilization. METHODS: LCS-eligible patients from 2019 were identified. The outcome was LCS utilization. The exposures were zip-code level urbanicity and travel time from the centroid of zip-code area to the nearest screening site (<10,10-<20, ≥20 min). Covariates included age, sex, race, marital status, insurance, body mass index, chronic obstructive pulmonary disease, Charlson Comorbidity Index (0, 1, 2, ≥3), and zip-code level median income. Chi-square tests and logistic regressions were employed. RESULTS: The analysis included 6930 patients, among whom 1432 (20.66%) received LCS. After adjusting for covariates, living in a non-metropolitan area (adjusted odds ratio: 0.32; 95% confidence interval: 0.26-0.40) and having longer travel time (0.80 [0.65-0.98] and 0.68 [0.54-0.86] for 10-<20 and ≥20 min travel time, respectively, compared to <10 min travel time) were significantly associated with lower odds of LCS utilization. CONCLUSIONS: The LCS utilization rate of a healthcare system was about 20% in 2019. Living in non-metropolitan areas or having longer travel time to LCS site were associated with lower LCS utilization.

Choosing to Stay: Understanding Immigrant Retention in Four Non-metropolitan Counties in Southern Ontario.

Every year, Ontario attracts more international migrants than any other province in Canada. The majority of these immigrants settle in the Greater Toronto Area (GTA). Policymakers at the federal, provincial, and municipal levels have identified a need to reduce the concentration of immigrants and to spread the benefits of immigration more evenly across the province. Despite policy and community interventions, most immigrants continue to move to larger centres. Previous academic research has mostly focused on the challenges smaller cities face in trying to attract and retain immigrants, suggesting that smaller cities lack what larger cities have to offer. We have taken another approach and instead considered what makes some immigrants choose to stay in non-metropolitan areas. Focusing on two sets of adjoining counties in Southern Ontario (Grey & Bruce counties and Lanark & Renfrew counties), we adopted a qualitative case study approach to understand what has led some immigrants to live in one of these regional areas for 3 years or more. The findings reveal that living outside of a metropolitan area comes with many benefits including relative affordability and easy access to nature. Moreover, study participants were inclined to stay in the counties under study because they could meet their needs there, at least for the time being. Interestingly, only some of the study participants viewed social attachments as a reason to stay. These were mostly individuals who had lived in one of the counties for a significant amount of time.

Spatial characteristics and coupling coordination between carbon emission efficiency and industrial structure in three metropolitan areas of Jiangsu Province, China.

It is of great practical significance to study the spatial characteristics of carbon emission efficiency, industrial structure, their coupling and coordination relationship for China's green development and industrial structure transformation in the new era. From the perspective of coupling, coordination and space, this paper analyzes and summarizes the spatial characteristics of carbon emission efficiency and industrial structure of 19 cities in three metropolitan areas of Jiangsu Province during 2009-2019 and their coupling and coordination relationship. The carbon emission efficiency in this study is represented by the carbon emission economic efficiency index and carbon emission social efficiency index. The results show that (a) the high-emission centers in the three metropolitan areas developed from "three centers" in 2009 to "five centers" in 2019. The continuous high-energy consumption of the secondary industry and the growth of the economic aggregate of the third industry kept the regional high carbon dioxide emissions. (b) The average value of carbon emission economic efficiency in 19 cities continued to increase, indicating that the contribution rate of the same amount of carbon emissions to economic income gradually increased; the growth range of carbon emission economic efficiency index is greater than that of carbon emission social efficiency index, indicating that carbon emission has a more significant effect on the improvement of regional economic development than on the improvement of public service level and residents' living quality. (d) The solidification degree of carbon emission efficiency is greater than that of the industrial structure (solidification degree carbon emission social efficiency > carbon emission economic efficiency > industrial structure). The high-grade industrial structure in Xuzhou metropolitan area is closely related to the improvement of carbon emission economic efficiency and carbon emission social efficiency, and both are in moderate antagonism. The rationalizing industrial structure in Nanjing metropolitan area is closely related to the improvement of carbon emission economic efficiency, which is in high coordination run-in. The concentration degree of industrial structure in Suzhou-Wuxi-Changzhou metropolitan area is closely related to the improvement of carbon emission economic efficiency and carbon emission social efficiency, which are in polar coordination coupling and high coordination run-in, respectively. The proposed coupling path of carbon emission efficiency-industrial structure can not only alleviate the dynamic disharmony in different cities but also effectively improve the coupling degree in cities.

Human Papillomavirus (HPV) Vaccination Knowledge, Beliefs, and Hesitancy Associated with Stages of Parental Readiness for Adolescent HPV Vaccination: Implications for HPV Vaccination Promotion.

The vaccination against human papillomavirus (HPV) has shown effectiveness in preventing six different types of cancer. Despite a safe, effective HPV vaccine, vaccination coverage for adolescents remains suboptimal, especially in the Memphis, Tennessee metropolitan area. Parents/Guardians have a substantial influence on adolescent vaccination, but little is known about parental cognitive factors contributing to intent on adolescent HPV vaccination in this region. Thus, this study examined factors associated with stages of parental readiness for adolescent HPV vaccination by applying the transtheoretical model. A cross-sectional, online survey was conducted to collect quantitative data on sociodemographic characteristics; health-related information; HPV vaccination knowledge, beliefs, and hesitancy; and stages of readiness for adolescent HPV vaccination among parents. Convenience sampling was performed to recruit a total of 497 parents of adolescents aged 11-17 years in Shelby and Tipton Counties in Tennessee and DeSoto County in Mississippi. Binary logistic regression analyses showed that greater knowledge of HPV vaccination, greater perceived susceptibility to HPV, and lower levels of HPV vaccination hesitancy, respectively, distinguished higher from lower stages of parental readiness for adolescent HPV vaccination after controlling for other variables. The findings provide implications for developing readiness for stage-specific interventions targeted to effectively influence the parental decision-making process regarding HPV vaccination for adolescents.

Drug Overdose Mortality of Residents and Visitors to Cities.

Background: The ongoing drug epidemic in the United States has shown that there are geographic differences in overdose fatalities. This article introduces a new way to study spatial differences in drug-related mortality, by distinguishing the fatalities of residents and visitors to a region. Methods: Using records of United States deaths from 2001 to 2020, this study examined fatal overdoses among residents and visitors to U.S. metropolitan areas. Results: The findings revealed that the drug fatality levels of residents and visitors differed from one another in many cities. These differences were most pronounced in larger metro areas, where the drug mortality of visitors was disproportionately high. Conclusions: Discussion focuses on implications and possible explanations for these findings, as well as their potential connection to classical conditioning of drug tolerance. More generally, comparing the fatalities of residents and visitors may provide a way to tease apart the roles of person-specific and location-specific contributors to overdose risk.

Behavioral changes of preventive activities of influenza among children in satellite cities of a metropolitan area of Tokyo, Japan, by the COVID-19 pandemic.

OBJECTIVE: In children in a metropolitan area of Tokyo, Japan, behavioral change and influenza infection associated with the frequency of nonpharmaceutical interventions (NPI) was assessed from the 2018-2019 season (Preseason) and the 2020-2021 season (coronavirus disease 2019 [COVID-19] season). METHODS: We conducted an exclusive survey among children attending preschool, elementary school, and junior high school in the Toda and Warabi regions, Japan, during the 2018-2019 (Preseason, distributed via mail) and 2020-2021 seasons (COVID-19 season, conducted online). The proportion of preventive activities (hand washing, face mask-wearing, and vaccination) was compared in the Preseason with that of the COVID-19 season. The multivariate logistic regression model was further applied to calculate the adjusted odds ratio (AOR) with 95% confidence intervals (CIs) for influenza infection associated with NPI frequency (hand washing and face mask wearing) in each Preseason and COVID-19 season. RESULTS: The proportion of vaccinated children who carried out hand washing and face mask wearing was remarkably higher during the COVID-19 season (48.8%) than in the Preseason (18.2%). A significant influenza infection reduction was observed among children who washed hands and wore face masks simultaneously (AOR, 0.87; 95% CI, 0.76-0.99; P = 0.033). CONCLUSIONS: A strong interest and performance in the intensive measures for the prevention of influenza under the COVID-19 pandemic was demonstrated. Positive association was observed from a combination of NPI, hand washing, and face mask-wearing and influenza infection. This study's findings could help in activities or preventive measures against influenza and other communicable diseases in children.

Household Joblessness in U.S. Metropolitan Areas during the COVID-19 Pandemic: Polarization and the Role of Educational Profiles.

The authors use Current Population Survey 2016 to 2021 quarterly data to analyze changes in household joblessness across metropolitan areas in the United States during the coronavirus disease 2019 pandemic. The authors first use shift-share analysis to decompose the change in household joblessness into changes in individual joblessness, household compositions, and polarization. The focus is on polarization, which is the result of the unequal distribution of individual joblessness across households. The authors find that the rise in household joblessness during the pandemic varies strongly across U.S. metropolitan areas. The initial stark increase and subsequent recovery are due largely to changes in individual joblessness. Polarization contributes notably to household joblessness but to varying degree. Second, the authors use metropolitan area-level fixed-effects regressions to test whether the educational profile of the population is a helpful predictor of changes in household joblessness and polarization. They measure three distinct features: educational levels, educational heterogeneity, and educational homogamy. Although much of the variance remains unexplained, household joblessness increased less in areas with higher educational levels. The authors show that how polarization contributes to household joblessness is shaped by educational heterogeneity and educational homogamy.

Spatial Equity of PM2.5 Pollution Exposures in High-Density Metropolitan Areas Based on Remote Sensing, LBS and GIS Data: A Case Study in Wuhan, China.

In-depth studies have been conducted on the risk of exposure to air pollution in urban residents, but most of them are static studies based on the population of residential units. Ignoring the real environmental dynamics during daily activity and mobility of individual residents makes it difficult to accurately estimate the level of air pollution exposure among residents and determine populations at higher risk of exposure. This paper uses the example of the Wuhan metropolitan area, high-precision air pollution, and population spatio-temporal dynamic distribution data, and applies geographically weighted regression models, bivariate LISA analysis, and Gini coefficients. The risk of air pollution exposure in elderly, low-age, and working-age communities in Wuhan was measured and the health equity within vulnerable groups such as the elderly and children was studied. We found that ignoring the spatio-temporal behavioral activities of residents underestimated the actual exposure hazard of PM2.5 to residents. The risk of air pollution exposure was higher for the elderly than for other age groups. Within the aging group, a few elderly people had a higher risk of pollution exposure. The high exposure risk communities of the elderly were mainly located in the central and sub-center areas of the city, with a continuous distribution characteristic. No significant difference was found in the exposure risk of children compared to the other populations, but a few children were particularly exposed to pollution. Children's high-exposure communities were mainly located in suburban areas, with a discrete distribution. Compared with the traditional static PM2.5 exposure assessment, the dynamic assessment method proposed in this paper considers the high mobility of the urban population and air pollution. Thus, it can accurately reveal the actual risk of air pollution and identify areas and populations at high risk of air pollution, which in turn provides a scientific basis for proposing planning policies to reduce urban PM2.5 and improve urban spatial equity.

Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter.

From hourly ozone observations obtained from three regions⸻Houston, Dallas, and West Texas⸻we investigated the contributions of meteorology to changes in surface daily maximum 8-h average (MDA8) ozone from 2000 to 2019. We applied a deep convolutional neural network and Shapely additive explanation (SHAP) to examine the complex underlying nonlinearity between variations of surface ozone and meteorological factors. Results of the models showed that between 2000 and 2019, specific humidity (38% and 27%) and temperature (28% and 37%) contributed the most to ozone formation over the Houston and Dallas metropolitan areas, respectively. On the other hand, the results show that solar radiation (50%) strongly impacted ozone variation over West Texas during this time. Using a combination of the Kolmogorov-Zurbenko (KZ) filter and multiple linear regression, we also evaluated the influence of meteorology on ozone and quantified the contributions of meteorological parameters to trends in surface ozone formation. Our findings showed that in Houston and Dallas, meteorology influenced ozone variations to a large extent. The impacts of meteorology on West Texas, however, showed meteorological factors had fewer influences on ozone variabilities from 2000 to 2019. This study showed that SHAP analysis and the KZ approach can investigate the contributions of the meteorological factors on ozone concentrations and help policymakers enact effective ozone mitigation policies.

Effectiveness of Influenza Vaccination among Children in Satellite Cities of a Metropolitan Area in Tokyo, Japan during the 2014/2015-2018/2019 Season.

Influenza vaccination is recommended for children. In particular, those aged 6 months to 12 years were recommended two vaccinations in Japan, whereas the recommended year range for the twice vaccination is 6 months to 8 years by the World Health Organization (WHO). This study assessed the effectiveness of influenza vaccination and whether the twice vaccinations enhanced preventive effects against influenza infection among children living in two satellite cities of a metropolitan area in Tokyo, Japan. During the influenza season of 2014-2018, parents of all preschool, elementary school, and junior high school children participated in an annual survey. Adjusted odds ratios (AOR) with 95% confidence intervals (CIs) were calculated via multivariate logistic regression analysis to evaluate influenza vaccination effectiveness and trends in the number of vaccinations. Among the 108,362 children who received the research questionnaire, 76,753 (70.8%) responded. After excluding responses without basic information, 64,586 children were included in the analysis. Vaccination was more effective in preschool and lower grade elementary school children given the increase in the number of vaccinations (test for trend: P < 0.001). The AOR of influenza for pre, grade 1 elementary, and grade 2 schoolchildren who received two vaccinations was 0.63 (95% CI, 0.59-0.69), 0.75 (0.67-0.83), and 0.81 (0.71-0.92), respectively, when compared to those without vaccination. However, no trend in vaccinations and their effectiveness was observed in the third and higher-grade school children. Our findings support the recommendation by the WHO, and could help guide influenza vaccination policies for children in Japan.

Land use efficiency of functional urban areas: Global pattern and evolution of development trajectories.

The application of last-generation spatial data modelling, integrating Earth Observation, population, economic and other spatially explicit data, enables insights into the sustainability of the global urbanisation processes with unprecedented detail, consistency, and international comparability. In this study, the land use efficiency indicator, as developed in the Sustainable Development Goals, is assessed globally for the first time at the level of Functional Urban Areas (FUAs). Each FUA includes the city and its commuting zone as inferred from statistical modelling of available spatial data. FUAs represent the economic area of influence of each urban centre. Hence, the analysis of land consumption within their boundary has significance in the fields of spatial planning and policy analyses as well as many other research areas. We utilize the boundaries of more than 9,000 FUAs to estimate the land use efficiency between 1990 and 2015, by using population and built-up area data extracted from the Global Human Settlement Layer. This analysis shows how, in the observed period, FUAs in low-income countries of the Global South evolved with rates of population growth surpassing the ones of land consumption. However, in almost all regions of the globe, more than half of the FUAs improved their land use efficiency in recent years (2000-2015) with respect to the previous decade (1990-2000). Our study concludes that the spatial expansion of urban areas within FUA boundaries is reducing compactness of settlements, and that settlements located within FUAs do not display higher land use efficiency than those outside FUAs.

Distribution of High-Volume Ankle Replacement Surgeons in United States Metropolitan Areas.

BACKGROUND: Ankle osteoarthritis is increasing, thus creating greater demand for high-volume total ankle arthroplasty (TAA) surgeons. The Medicare Provider Utilization and Payment Data Public Use File (MPUPD-PUF) provides volume and reimbursement data for procedures performed by physicians participating in Medicare. This study analyzes surgeon prevalence, surgeon distribution, and factors affecting surgeon prevalence in metropolitan areas. METHODS: The MPUPD-PUF was reviewed from 2012 to 2015, and data were extracted for physicians performing ≥11 TAA procedures. Physicians in metropolitan areas (population >1 million) were grouped together, and reimbursement, number of high-volume surgeons, and procedures were calculated. Presence of an American Orthopaedic Foot and Ankle Society (AOFAS) fellowship program was analyzed for associations with high-volume TAA surgeons. RESULTS: Fifty-three surgeons performed ≥11 TAA procedures (1,960 total) covered by Medicare. Of these surgeons, 66% practice in metropolitan areas with a population >1 million. Fifty-one percent of US major metropolitan areas contained no surgeon who submitted >10 traditional Medicare claims for TAA. Areas with an AOFAS fellowship had nominally more TAA claims submitted. CONCLUSIONS: The distribution of high-volume TAA surgeons among major metropolitan areas in the United States is highly unequal. Analyzing the data with this method aids in targeting TAA surgeons to currently underserved areas. LEVELS OF EVIDENCE: Level IV: Retrospective-comparative study.

The metropolitan context of substance use and substance use disorders among US adults on probation or parole supervision.

Background: Rates of substance use and substance use disorders are higher among adults on probation or parole supervision compared to the general population. Substance use is a risk factor of not adhering to supervision requirements, which may result in revocation and incarceration. Examining associations of metropolitan area status with substance use and substance use disorders may identify specific substance use behaviors that can be targeted in community corrections prevention and treatment services. The present study examined associations of metropolitan area residency with substance use and substance use disorders among adults on probation or parole supervision. Methods: Data came from the 2015 to 2018 National Survey on Drug Use and Health ([NSDUH]; N = 4266 adults on parole or probation). Multivariable logistic regression was run for substance-specific models for each of the two outcomes of past-year use and substance use disorder. Results: Nonmetropolitan residency was associated with higher odds of methamphetamine use and lower odds of cocaine use. Nonmetropolitan residency was associated with higher odds of methamphetamine use disorder and lower odds of opioid use disorder and cocaine use disorder. Conclusions: Study findings highlight the differences of substance use and substance use disorders between levels of metropolitan areas for those on probation or parole. Findings suggest that cocaine use should be emphasized in clinical services in large metropolitan areas, whereas methamphetamine use may be prioritized in nonmetropolitan areas. Further study is needed to investigate the interface of substance use behaviors and community corrections outcomes across metropolitan and nonmetropolitan areas.

Cannabis use, use frequency, and use disorder in large metropolitan, small metropolitan, and nonmetropolitan areas.

BACKGROUND: Despite significant geographical heterogeneity of sociodemographic and clinical characteristics, little is known about potential differences in cannabis use behaviors in U.S. geographic areas. In this study, we examined cannabis use behaviors in large metropolitan, small metropolitan, and nonmetropolitan areas. We focused on interactions between geographic areas and health insurance status and medical cannabis laws (MCL). METHODS: Data came from the 2015-2018 National Survey on Drug Use and Health (NSDUH; N = 171,766 adults; N = 36,175 cannabis users). Weighted chi-squares tests of independence and multivariable Poisson regression models were used to examine study questions. RESULTS: Past-year use was highest in large metropolitan areas (16.08 %). Frequent use was highest among nonmetropolitan area users (48.67 %). Uninsured adults had a higher likelihood of past-year use (RRR = 1.21, 95 % CI = 1.14, 1.29) and frequent use (RRR = 1.27, 95 % CI = 1.14, 1.41), but a lower likelihood of cannabis use disorder (RRR = 0.77, 95 % CI = 0.66, 0.89). Uninsured adults in nonmetropolitan areas had a higher likelihood (RRR = 1.62, 95 % CI = 1.39, 1.88) of past-year use than insured nonmetropolitan area adults. MCL state residency was associated with a higher likelihood of frequent use among nonmetropolitan (RRR = 1.39, 95 % CI = 1.11, 1.74) and small metropolitan users (RRR = 1.30, 95 % CI = 1.15, 1.47). Cannabis use disorder likelihood did not vary by geographic area. CONCLUSIONS: Lack of health insurance and MCL state residency are significant variables affecting cannabis use behaviors in small metropolitan and/or nonmetropolitan areas.

Impact of climatic, demographic and disease control factors on the transmission dynamics of COVID-19 in large cities worldwide.

Approximately a year into the COVID-19 pandemic caused by the SARS-CoV-2 virus, many countries have seen additional "waves" of infections, especially in the temperate northern hemisphere. Other vulnerable regions, such as South Africa and several parts of South America have also seen cases rise, further impacting local economies and livelihoods. Despite substantial research efforts to date, it remains unresolved as to whether COVID-19 transmission has the same sensitivity to climate observed for other common respiratory viruses such as seasonal influenza. Here, we look for empirical evidence of seasonality using a robust estimation framework. For 359 large cities across the world, we estimated the basic reproduction number (R0) using logistic growth curves fitted to cumulative case data. We then assess evidence for association with climatic variables through ordinary least squares (OLS) regression. We find evidence of seasonality, with lower R0 within cities experiencing greater surface radiation (coefficient = -0.005, p < 0.001), after adjusting for city-level variation in demographic and disease control factors. Additionally, we find association between R0 and temperature during the early phase of the epidemic in China. However, climatic variables had much weaker explanatory power compared to socioeconomic and disease control factors. Rates of transmission and health burden of the continuing pandemic will be ultimately determined by population factors and disease control policies.

Dynamic Panel Data Modeling and Surveillance of COVID-19 in Metropolitan Areas in the United States: Longitudinal Trend Analysis.

BACKGROUND: The COVID-19 pandemic has had profound and differential impacts on metropolitan areas across the United States and around the world. Within the United States, metropolitan areas that were hit earliest with the pandemic and reacted with scientifically based health policy were able to contain the virus by late spring. For other areas that kept businesses open, the first wave in the United States hit in mid-summer. As the weather turns colder, universities resume classes, and people tire of lockdowns, a second wave is ascending in both metropolitan and rural areas. It becomes more obvious that additional SARS-CoV-2 surveillance is needed at the local level to track recent shifts in the pandemic, rates of increase, and persistence. OBJECTIVE: The goal of this study is to provide advanced surveillance metrics for COVID-19 transmission that account for speed, acceleration, jerk and persistence, and weekly shifts, to better understand and manage risk in metropolitan areas. Existing surveillance measures coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until, and after, an effective vaccine is developed. Here, we provide values for novel indicators to measure COVID-19 transmission at the metropolitan area level. METHODS: Using a longitudinal trend analysis study design, we extracted 260 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in the 25 largest US metropolitan areas as a function of the prior number of cases and weekly shift variables based on a dynamic panel data model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: Minneapolis and Chicago have the greatest average number of daily new positive results per standardized 100,000 population (which we refer to as speed). Extreme behavior in Minneapolis showed an increase in speed from 17 to 30 (67%) in 1 week. The jerk and acceleration calculated for these areas also showed extreme behavior. The dynamic panel data model shows that Minneapolis, Chicago, and Detroit have the largest persistence effects, meaning that new cases pertaining to a specific week are statistically attributable to new cases from the prior week. CONCLUSIONS: Three of the metropolitan areas with historically early and harsh winters have the highest persistence effects out of the top 25 most populous metropolitan areas in the United States at the beginning of their cold weather season. With these persistence effects, and with indoor activities becoming more popular as the weather gets colder, stringent COVID-19 regulations will be more important than ever to flatten the second wave of the pandemic. As colder weather grips more of the nation, southern metropolitan areas may also see large spikes in the number of cases.

Quantifying the impact of particle matter on mortality and hospitalizations in four Brazilian metropolitan areas.

Air quality management involves investigating areas where pollutant concentrations are above guideline or standard values to minimize its effect on human health. Particulate matter (PM) is one of the most studied pollutants, and its relationship with health has been widely outlined. To guide the construction and improvement of air quality policies, the impact of PM on the four Brazilian southeast metropolitan areas was investigated. One-year long modeling of PM10 and PM2.5 was performed with the WRF-Chem model for 2015 to quantify daily and annual PM concentrations in 102 cities. Avoidable mortality due to diverse causes and morbidity due to respiratory and circular system diseases were estimated concerning WHO guidelines, which was adopted in Brazil as a final standard to be reached in the future; although there is no deadline set for its implementation yet. Results showed satisfactory representation of meteorology and ambient PM concentrations. An overestimation in PM concentrations for some monitoring stations was observed, mainly in São Paulo metropolitan area. Cities around capitals with high modelled annual PM2.5 concentrations do not monitor this pollutant. The total avoidable deaths estimated for the region, related to PM2.5, were 32,000 ± 5,300 due to all-cause mortality, between 16,000 ± 2,100 and 51,000 ± 3,000 due non-accidental causes, between 7,300 ± 1,300 and 16,700 ± 1,500 due to cardiovascular disease, between 4,750 ± 900 and 10,950 ± 870 due ischemic heart diseases and 1,220 ± 330 avoidable deaths due to lung cancer. Avoidable respiratory hospitalizations were greater for PM2.5 among 'children' age group than for PM10 (all age group) except in São Paulo metropolitan area. For circulatory system diseases, 9,840 ± 3,950 avoidable hospitalizations in the elderly related to a decrease in PM2.5 concentrations were estimated. This study endorses that more restrictive air quality standards, human exposure, and health effects are essential factors to consider in urban air quality management.

Spatial Disparities in Coronavirus Incidence and Mortality in the United States: An Ecological Analysis as of May 2020.

PURPOSE: This ecological analysis investigates the spatial patterns of the COVID-19 epidemic in the United States in relation to socioeconomic variables that characterize US counties. METHODS: Data on confirmed cases and deaths from COVID-19 for 2,814 US counties were obtained from Johns Hopkins University. We used Geographic Information Systems (GIS) to map the spatial aspects of this pandemic and investigate the disparities between metropolitan and nonmetropolitan communities. Multiple regression models were used to explore the contextual risk factors of infections and death across US counties. We included population density, percent of population aged 65+, percent population in poverty, percent minority population, and percent of the uninsured as independent variables. A state-level measure of the percent of the population that has been tested for COVID-19 was used to control for the impact of testing. FINDINGS: The impact of COVID-19 in the United States has been extremely uneven. Although densely populated large cities and their surrounding metropolitan areas are hotspots of the pandemic, it is counterintuitive that incidence and mortality rates in some small cities and nonmetropolitan counties approximate those in epicenters such as New York City. Regression analyses support the hypotheses of positive correlations between COVID-19 incidence and mortality rates and socioeconomic factors including population density, proportions of elderly residents, poverty, and percent population tested. CONCLUSIONS: Knowledge about the spatial aspects of the COVID-19 epidemic and its socioeconomic correlates can inform first responders and government efforts. Directives for social distancing and to "shelter-in-place" should continue to stem the spread of COVID-19.

Predictors of historical change in drug treatment coverage among people who inject drugs in 90 large metropolitan areas in the USA, 1993-2007.

BACKGROUND: Adequate access to effective treatment and medication assisted therapies for opioid dependence has led to improved antiretroviral therapy adherence and decreases in morbidity among people who inject drugs (PWID), and can also address a broad range of social and public health problems. However, even with the success of syringe service programs and opioid substitution programs in European countries (and others) the US remains historically low in terms of coverage and access with regard to these programs. This manuscript investigates predictors of historical change in drug treatment coverage for PWID in 90 US metropolitan statistical areas (MSAs) during 1993-2007, a period in which, overall coverage did not change. METHODS: Drug treatment coverage was measured as the number of PWID in drug treatment, as calculated by treatment entry and census data, divided by numbers of PWID in each MSA. Variables suggested by the Theory of Community Action (i.e., need, resource availability, institutional opposition, organized support, and service symbiosis) were analyzed using mixed-effects multivariate models within dependent variables lagged in time to study predictors of later change in coverage. RESULTS: Mean coverage was low in 1993 (6.7%; SD 3.7), and did not increase by 2007 (6.4%; SD 4.5). Multivariate results indicate that increases in baseline unemployment rate (ß = 0.312; pseudo-p < 0.0002) predict significantly higher treatment coverage; baseline poverty rate (ß = - 0.486; pseudo-p < 0.0001), and baseline size of public health and social work workforce (ß = 0.425; pseudo-p < 0.0001) were predictors of later mean coverage levels, and baseline HIV prevalence among PWID predicted variation in treatment coverage trajectories over time (baseline HIV * Time: ß = 0.039; pseudo-p < 0.001). Finally, increases in black/white poverty disparity from baseline predicted significantly higher treatment coverage in MSAs (ß = 1.269; pseudo-p < 0.0001). CONCLUSIONS: While harm reduction programs have historically been contested and difficult to implement in many US communities, and despite efforts to increase treatment coverage for PWID, coverage has not increased. Contrary to our hypothesis, epidemiologic need, seems not to be associated with change in treatment coverage over time. Resource availability and institutional opposition are important predictors of change over time in coverage. These findings suggest that new ways have to be found to increase drug treatment coverage in spite of economic changes and belt-tightening policy changes that will make this difficult.