The Urban Environment and Cardiometabolic Health.

Urban environments contribute substantially to the rising burden of cardiometabolic diseases worldwide. Cities are complex adaptive systems that continually exchange resources, shaping exposures relevant to human health such as air pollution, noise, and chemical exposures. In addition, urban infrastructure and provisioning systems influence multiple domains of health risk, including behaviors, psychological stress, pollution, and nutrition through various pathways (eg, physical inactivity, air pollution, noise, heat stress, food systems, the availability of green space, and contaminant exposures). Beyond cardiometabolic health, city design may also affect climate change through energy and material consumption that share many of the same drivers with cardiometabolic diseases. Integrated spatial planning focusing on developing sustainable compact cities could simultaneously create heart-healthy and environmentally healthy city designs. This article reviews current evidence on the associations between the urban exposome (totality of exposures a person experiences, including environmental, occupational, lifestyle, social, and psychological factors) and cardiometabolic diseases within a systems science framework, and examines urban planning principles (eg, connectivity, density, diversity of land use, destination accessibility, and distance to transit). We highlight critical knowledge gaps regarding built-environment feature thresholds for optimizing cardiometabolic health outcomes. Last, we discuss emerging models and metrics to align urban development with the dual goals of mitigating cardiometabolic diseases while reducing climate change through cross-sector collaboration, governance, and community engagement. This review demonstrates that cities represent crucial settings for implementing policies and interventions to simultaneously tackle the global epidemics of cardiovascular disease and climate change.

Spatial analysis of dengue transmission in an endemic city in Brazil reveals high spatial structuring on local dengue transmission dynamics.

In the last decades, dengue has become one of the most widespread mosquito-borne arboviruses in the world, with an increasing incidence in tropical and temperate regions. The mosquito Aedes aegypti is the dengue primary vector and is more abundant in highly urbanized areas. Traditional vector control methods have showing limited efficacy in sustaining mosquito population at low levels to prevent dengue virus outbreaks. Considering disease transmission is not evenly distributed in the territory, one perspective to enhance vector control efficacy relies on identifying the areas that concentrate arbovirus transmission within an endemic city, i.e., the hotspots. Herein, we used a 13-month timescale during the SARS-Cov-2 pandemic and its forced reduction in human mobility and social isolation to investigate the spatiotemporal association between dengue transmission in children and entomological indexes based on adult Ae. aegypti trapping. Dengue cases and the indexes Trap Positive Index (TPI) and Adult Density Index (ADI) varied seasonally, as expected: more than 51% of cases were notified on the first 2 months of the study, and higher infestation was observed in warmer months. The Moran's Eigenvector Maps (MEM) and Generalized Linear Models (GLM) revealed a strong large-scale spatial structuring in the positive dengue cases, with an unexpected negative correlation between dengue transmission and ADI. Overall, the global model and the purely spatial model presented a better fit to data. Our results show high spatial structure and low correlation between entomological and epidemiological data in Foz do Iguaçu dengue transmission dynamics, suggesting the role of human mobility might be overestimated and that other factors not evaluated herein could be playing a significant role in governing dengue transmission.

Exploring spatio-temporal impact of COVID-19 on citywide taxi demand: A case study of New York City.

Coronavirus disease 2019 (COVID-19) has brought dramatic changes in our daily life, especially in human mobility since 2020. As the major component of the integrated transport system in most cities, taxi trips represent a large portion of residents' urban mobility. Thus, quantifying the impacts of COVID-19 on city-wide taxi demand can help to better understand the reshaped travel patterns, optimize public-transport operational strategies, and gather emergency experience under the pressure of this pandemic. To achieve the objectives, the Geographically and Temporally Weighted Regression (GTWR) model is used to analyze the impact mechanism of COVID-19 on taxi demand in this study. City-wide taxi trip data from August 1st, 2020 to July 31st, 2021 in New York City was collected as model's dependent variables, and COVID-19 case rate, population density, road density, station density, points of interest (POI) were selected as the independent variables. By comparing GTWR model with traditional ordinary least square (OLS) model, temporally weighted regression model (TWR) and geographically weighted regression (GWR) model, a significantly better goodness of fit on spatial-temporal taxi data was observed for GTWR. Furthermore, temporal analysis, spatial analysis and the epidemic marginal effect were developed on the GTWR model results. The conclusions of this research are shown as follows: (1) The virus and health care become the major restraining and stimulative factors of taxi demand in post epidemic era. (2) The restraining level of COVID-19 on taxi demand is higher in cold weather. (3) The restraining level of COVID-19 on taxi demand is severely influenced by the curfew policy. (4) Although this virus decreases taxi demand in most of time and places, it can still increase taxi demand in some specific time and places. (5) Along with COVID-19, sports facilities and tourism become obstacles on increasing taxi demand in most of places and time in post epidemic era. The findings can provide useful insights for policymakers and stakeholders to improve the taxi operational efficiency during the remainder of the COVID-19 pandemic.

Wastewater-based estimation of diabetes mellitus prevalence in 237 cities: A cross-China study.

Diabetes mellitus, a metabolic disease characterized by hyperglycemia, has been witnessed as a rapidly escalating worldwide health crisis. China currently had 140.9 million diabetic population in 2021, which was the largest globally. DM has witnessed a significant surge in the past few decades, leading to an alarming rise in the overall burden caused by this disease. To monitor the near real-time DM prevalence and the consumption of first-line anti-diabetic drugs, a wastewater-based epidemiology (WBE) approach based on the back-calculation of metformin concentration was implemented in 237 cities in China. The quantitative analysis of metformin in wastewater was conducted by LC-MS/MS with satisfactory results of method validation. The average concentration of metformin in wastewater was 14.07 ± 13.16 µg/L, and the per capita consumption was 5.16 ± 2.08 mg/day/inh, ranging from 0.90 to 10.36 ± 4.63 mg/day/inh. The calculated metformin prevalence was found to be 0.52 % ± 0.28 %, and the final estimated DM prevalence was 11.33 % ± 4.99 %, which was nearly consistent with the result of the International Diabetes Federation survey of 9.98 %. The results suggested that metformin might be one of the suitable WBE biomarkers in DM monitoring and WBE strategy could potentially enable the estimation of DM prevalence in most of Chinese cities after reasonable correction of associated parameters.

The impact of the COVID-19 pandemic on frail older people ageing in place alone in two Italian cities: Functional limitations, care arrangements and available services.

The study aimed to explore and compare effects of lockdown, due to the COVID-19 pandemic in 2020, on frail older people living alone at home in Brescia and Ancona, two urban cities located respectively in Northern and Central Italy. This country was the Western epicenter of the first wave of the pandemic (February-May 2020), which affected the two cities differently as for infections, with a more severe impact on the former. A follow-up study of the IN-AGE research project (2019) was carried out in July-September 2020, by means of telephone interviews, involving 41 respondents. Semi-structured questions focused on the effects of the first wave of the pandemic on their mobility and functional limitations, available care arrangements, and access to health services. The lockdown and social distancing measures overall negatively impacted on frail older people living alone, to a different extent in Ancona and Brescia, with a better resilience of home care services in Brescia, and a greater support from the family in Ancona, where however major problems in accessing health services also emerged. Even though the study was exploratory only, with a small sample that cannot be considered as representative of the population, and despite differences between the two cities, findings overall suggested that enhancing home care services, and supporting older people in accessing health services, could allow ageing in place, especially in emergency times.

Investigating the spatiotemporal characteristics and medical response during the initial COVID-19 epidemic in six Chinese cities.

In the future, novel and highly pathogenic viruses may re-emerge, leading to a surge in healthcare demand. It is essential for urban epidemic control to investigate different cities' spatiotemporal spread characteristics and medical carrying capacity during the early stages of COVID-19. This study employed textual analysis, mathematical statistics, and spatial analysis methods to examine the situation in six highly affected Chinese cities. The findings reveal that these cities experienced three phases during the initial outbreak of COVID-19: "unknown-origin incubation", "Wuhan-related outbreak", and "local exposure outbreak". Cities with a high number of confirmed cases exhibited a multicore pattern, while those with fewer cases displayed a single-core pattern. The cores were distributed hierarchically in the central built-up areas of cities' economic, political, or transportation centers. The radii of these cores shrank as the central built-up area's level decreased, indicating a hierarchical decay and a core-edge structure. It suggests that decentralized built environments (non-clustered economies and populations) are less likely to facilitate large-scale epidemic clusters. Additionally, the deployment of designated hospitals in these cities was consistent with the spatial distribution of the epidemic; however, their carrying capacity requires urgent improvement. Ultimately, the essence of prevention and control is the governance of human activities and the efficient management of limited resources about individuals, places, and materials through leveraging IT and GIS technologies to address supply-demand contradictions.

Effects of primary health care and socioeconomic aspects on the dispersion of COVID-19 in the Brazilian Northeast: Ecological study of the first pandemic wave.

BACKGROUND: The COVID-19 pandemic has had a negative impact on socioeconomic and public health conditions of the population. AIM: To measure the temporal evolution of COVID-19 cases in cities near the countryside outside metropolitan areas of northeastern Brazil and the impact of the primary care organization in its containment. METHODS: This is a time-series study, based on the first three months of COVID-19 incidence in northeastern Brazil. Secondary data were used, the outcome was number of COVID-19 cases. Independent variables were time, coverage and quality score of basic health services, and demographic, socioeconomic and social isolation variables. Generalizable Linear Models with first order autoregression were applied. RESULTS: COVID-19 spreads heterogeneously in cities near the countryside of Northeastern Brazilian cities, showing associations with the city size, socioeconomic and organizational indicators of services. The Family Health Strategy seems to mitigate the speed of progression and burden of the disease, in addition to measures such as social isolation and closure of commercial activities. CONCLUSION: The spread of COVID-19 reveals multiple related factors, which require coordinated intersectoral actions in order to mitigate its problems, especially in biologically and socially vulnerable populations.

Unmet need for medication for opioid use disorder among persons who inject drugs in 23 U.S. cities.

BACKGROUND: Persons who inject drugs (PWID) are at increased risk of HIV and hepatitis C virus (HCV) infections and premature mortality due to drug overdose. Medication for opioid use disorder (MOUD), such as methadone or buprenorphine, reduces injecting behaviors, HIV and HCV transmission, and mortality from opioid overdose. Using data from National HIV Behavioral Surveillance, we evaluated the unmet need for MOUD among PWID in 23 U.S. cities. METHODS: PWID were recruited by respondent-driven sampling, interviewed, and tested for HIV. This analysis includes PWID who were ≥18 years old and reported injecting drugs and opioid use in the past 12 months. We used Poisson regression to examine factors associated with self-reported unmet need for MOUD and reported adjusted prevalence ratios (aPR) with 95% confidence intervals. RESULTS: Of 10,879 PWID reporting using opioids, 68.8% were male, 48.2% were ≥45 years of age, 38.8% were non-Hispanic White, 49.6% experienced homelessness, and 28.0% reported an unmet need for MOUD in the past 12 months. PWID who were more likely to report unmet need for MOUD experienced homelessness (aPR 1.26; 95% CI: 1.19-1.34), were incarcerated in the past 12 months (aPR 1.15; 95% CI: 1.08-1.23), injected ≥once a day (aPR 1.42; 95% CI: 1.31-1.55), reported overdose (aPR 1.33; 95% CI: 1.24-1.42), and sharing of syringes (aPR 1.14; 95% CI: 1.06-1.23). CONCLUSIONS: The expansion of MOUD provision for PWID is critical. Integrating syringe service programs and MOUD provision and linking PWID who experience overdose, incarceration or homelessness to treatment with MOUD could improve its utilization among PWID.

The association between air pollutions and emergency hospitalizations due to COPD and asthma across 16 Polish cities: population-based study.

OBJECTIVES: In recent years numerous initiatives aimed at reducing air pollution have been undertaken in Poland. The general objective was to examine the correlation between air pollution measured by the level of particulate matter ≤10 µm in diameter (PM10) and emergency hospitalizations due to chronic obstructive pulmonary disease (COPD) and asthma in 16 Polish cities (capitals of the regions). MATERIAL AND METHODS: The authors aimed to diagnose the situation across 16 cities over a 5­year period (2014-2019). Data on the number of hospitalizations was retrieved from the national public insurance system, the National Health Fund. A total number of 22 600 emergency hospitalizations was analyzed (12 000 and 10 600 in 2014 and 2019, respectively). The data on air pollution was accessed via the public register of the Chief Inspectorate for Environmental Protection air quality database. The authors of this article have used the data on PM10 daily exposure in each of the 16 cities in 2014 and 2019. Statistical methods included: non-parametric tests, a 2-stage modelling approach for time-series data, and multivariate meta-analysis of the results. RESULTS: The results indicated that there was a statistically significant decrease in PM10 concentration in 2019 in comparison to 2014 in all cities, mainly in the autumn and winter season. However, the correlation between the improvement in the air quality and a decrease in emergency hospitalizations due to asthma and COPD turned out to not be as strong as expected. The authors observed a strong correlation between PM10 concentrations and hospitalizations due to asthma and COPD, but only when air quality norms were significantly above acceptable levels. CONCLUSIONS: Air pollution measured by PM10 concentration might be used as one of the predictors of the asthma and COPD emergency hospitalization risk, yet other factors like respiratory tract infection, health care organizational aspect, patient self-control, compliance and comorbidities should also be taken into consideration. Int J Occup Med Environ Health. 2024;37(1):110-27.

AIDSVu Cities' Progress Toward HIV Care Continuum Goals: Cross-Sectional Study.

BACKGROUND: Public health surveillance data are critical to understanding the current state of the HIV and AIDS epidemics. Surveillance data provide significant insight into patterns within and progress toward achieving targets for each of the steps in the HIV care continuum. Such targets include those outlined in the National HIV/AIDS Strategy (NHAS) goals. If these data are disseminated, they can be used to prioritize certain steps in the continuum, geographic locations, and groups of people. OBJECTIVE: We sought to develop and report indicators of progress toward the NHAS goals for US cities and to characterize progress toward those goals with categorical metrics. METHODS: Health departments used standardized SAS code to calculate care continuum indicators from their HIV surveillance data to ensure comparability across jurisdictions. We report 2018 descriptive statistics for continuum steps (timely diagnosis, linkage to medical care, receipt of medical care, and HIV viral load suppression) for 36 US cities and their progress toward 2020 NHAS goals as of 2018. Indicators are reported categorically as met or surpassed the goal, within 25% of attaining the goal, or further than 25% from achieving the goal. RESULTS: Cities were closest to meeting NHAS goals for timely diagnosis compared to the goals for linkage to care, receipt of care, and viral load suppression, with all cities (n=36, 100%) within 25% of meeting the goal for timely diagnosis. Only 8% (n=3) of cities were >25% from achieving the goal for receipt of care, but 69% (n=25) of cities were >25% from achieving the goal for viral suppression. CONCLUSIONS: Display of progress with graphical indicators enables communication of progress to stakeholders. AIDSVu analyses of HIV surveillance data facilitate cities' ability to benchmark their progress against that of other cities with similar characteristics. By identifying peer cities (eg, cities with analogous populations or similar NHAS goal concerns), the public display of indicators can promote dialogue between cities with comparable challenges and opportunities.

Epidemiology of visceral leishmaniasis in municipalities of Mato Grosso and the performance of surveillance activities: an updated investigation.

Visceral leishmaniasis (VL) is considered a globally neglected disease. To address the problem of VL endemic to Brazil, the Visceral Leishmaniasis Control Program (VLCP) was created, which recommends the development of health surveillance actions such as the identification of human and canine cases, vector control and prevention of disease. We aimed to investigate the epidemiological situation of VL in municipalities of the State of Mato Grosso (MT) and assess the execution of VLCP activities. Data on human cases were obtained from the Information System for Notifiable Diseases (SINAN), and data from entomological and canine inquiry were provided by the State's Health Department. Analyzes from the period 2019 - 2021 recorded 30 cases of human VL, distributed among 16 municipalities. Vectors were identified in 50% of the municipalities where entomological investigations were carried out, and the predominant specie was Lutzomyia longipalpis. A total of 15,585 dogs were subjected to serological examination, of which 18.91% tested seropositive for Leishmania infantum. However, it must be emphasized that only three municipalities conducted consecutive inquiries involving canine VL. Although VL is distributed widely throughout the State, only a few municipalities have undertaken the actions of the VLCP, thus highlighting the neglected status of the disease.

Unraveling implicit human behavioral effects on dynamic characteristics of Covid-19 daily infection rates in Taiwan.

We investigate the dynamic characteristics of Covid-19 daily infection rates in Taiwan during its initial surge period, focusing on 79 districts within the seven largest cities. By employing computational techniques, we extract 18 features from each district-specific curve, transforming unstructured data into structured data. Our analysis reveals distinct patterns of asymmetric growth and decline among the curves. Utilizing theoretical information measurements such as conditional entropy and mutual information, we identify major factors of order-1 and order-2 that influence the peak value and curvature at the peak of the curves, crucial features characterizing the infection rates. Additionally, we examine the impact of geographic and socioeconomic factors on the curves by encoding each of the 79 districts with two binary characteristics: North-vs-South and Urban-vs-Suburban. Furthermore, leveraging this data-driven understanding at the district level, we explore the fine-scale behavioral effects on disease spread by examining the similarity among 96 age-group-specific curves within urban districts of Taipei and suburban districts of New Taipei City, which collectively represent a substantial portion of the nation's population. Our findings highlight the implicit influence of human behaviors related to living, traveling, and working on the dynamics of Covid-19 transmission in Taiwan.

Haze weather and mortality in China from 2014 to 2020: Definitions, vulnerability, and effect modification by haze characteristics.

Haze weather, characterized by low visibility due to severe air pollution, has aroused great public concern. However, haze definitions are inconclusive, and multicentre studies on the health impacts of haze are scarce. We collected data on the daily number of deaths and environmental factors in 190 Chinese cities from 2014 to 2020. The city-specific association was estimated using quasi-Poisson regression and then pooled using meta-analysis. We found a negative association between daily visibility and non-accidental deaths, and mortality risk sharply increased when visibility was < 10 km. Haze weather, defined as a daily average visibility of < 10 km without a limit for humidity, produced the best model fitness and greatest effect on mortality. A haze day was associated with an increase of 2.53% (95% confidence interval [CI]:1.96, 3.10), 2.84 (95% CI: 2.13, 3.56), and 2.99% (95% CI: 1.94, 4.04) in all non-accident, cardiovascular and respiratory mortality, respectively. Haze had the greatest effect on lung cancer mortality. The haze-associated risk of mortality increased with age. Severe haze (visibility <2 km) and damp haze (haze with relative humidity >90%) had greater health impacts. Our findings can help in the development of early warning systems and effective public health interventions for haze.

Socio-environmental modifiers of heat-related mortality in eight Swiss cities: A case time series analysis.

In the light of growing urbanization and projected temperature increases due to climate change, heat-related mortality in urban areas is a pressing public health concern. Heat exposure and vulnerability to heat may vary within cities depending on structural features and socioeconomic factors. This study examined the effect modification of the temperature-mortality association of three socio-environmental factors in eight Swiss cities and population subgroups (<75 and ≥ 75 years, males, females): urban heat islands (UHI) based on within-city temperature contrasts, residential greenness measured as normalized difference vegetation index (NDVI) and neighborhood socioeconomic position (SEP). We used individual death records from the Swiss National Cohort occurring during the warm season (May to September) in the years 2003-2016. We performed a case time series analysis using conditional quasi-Poisson and distributed lag non-linear models with a lag of 0-3 days. As exposure variables, we used daily maximum temperatures (Tmax) and a binary indicator for warm nights (Tmin ≥20 °C). In total, 53,593 deaths occurred during the study period. Overall across the eight cities, the mortality risk increased by 31% (1.31 relative risk (95% confidence interval: 1.20-1.42)) between 22.5 °C (the minimum mortality temperature) and 35 °C (the 99th percentile) for warm-season Tmax. Stratified analysis suggested that the heat-related risk at 35 °C is 26% (95%CI: -4%, 67%) higher in UHI compared to non-UHI areas. Indications of smaller risk differences were observed between the low vs. high greenness strata (Relative risk difference = 13% (95%CI: -11%; 44%)). Living in low SEP neighborhoods was associated with an increased heat related risk in the non-elderly population (<75 years). Our results indicate that UHI are associated with increased heat-related mortality risk within Swiss cities, and that features beyond greenness are responsible for such spatial risk differences.

Prevalence and circulant genotypes of Chlamydia trachomatis in university women from cities in the Brazilian Amazon.

BACKGROUND: Approximately 80% of infected women infected by Chlamydia trachomatis are asymptomatic, although this infection can lead to serious complications in the female reproductive tract. Few data on Chlamydia infection and genotypes are available in Amazonian communities. OBJECTIVES: To describe the prevalence of and associated factors and to identify the genotypes of sexual C. trachomatis infection in female university students in different urban centers (capital and interiors) in the Brazilian state of Pará, in the eastern Amazon region. METHODS: A cross-sectional study was performed among young women attending public universities in four different urban centers in the eastern Amazon region. They were invited to participate in the studt and cervical secretions were collected for molecular diagnosis of C. trachomatis. We utilized amplification of the ompA gene by nested PCR. Positive samples were genotyped by nucleotide sequencing. Study participants completed a questionnaire on social, epidemiological, and reproductive health variables. A Qui-square and Binominal regression test were used to evaluate the degree of association of these variables with the infection. RESULTS: A total of 686 female students was included in the study. The overall prevalence of C. trachomatis was 11.2% (77/686). The prevalence of this infection was higher in interiors (15.2% vs 9.5%/ p: 0.0443). Female university students who do not have a sexual partner (11.8%/p <0.008), who do not use a condom in their sexual relations (17.8%/p <0.0001) and who reported having suffered a miscarriage (32%/p <0.0001) have high chances of acquiring this sexual infection. The ompA gene was sequenced in only 33 (42.8%) samples, revealing the genotype J was the most frequent (27.2% [9/33]), followed by genotypes D (24.2% [8/33]), and then genotypes F (18.2% [6/33]), E (15.1% [5/33]) K (6.1% [2/33]), Ia (6.1% [2/33]), and G (3.1% [1/33]). CONCLUSIONS: The high prevalence of sexual infection by C. trachomatis in the female university students from the interior of the state of Pará, individuals with no fixed sexual partner, those that had had a miscarriage, the students that do not use condoms in their sexual relations. The genotype J of C. trachomatis genotypes was the most frequent. These data are important to help defining the epidemiological effects of chlamydial infections in Amazonian populations.

Obesogenic environments as major determinants of a disease: It is time to re-shape our cities.

Obesity rates are increasing in almost all high- and low-income countries, and population-based approaches are necessary to reverse this trend. The current global efforts are focused on identifying the root causes of obesity and developing effective methods for early diagnosis, screening, treatment, and long-term management, both at an individual and health system level. However, there is a relative lack of effective options for early diagnosis, treatment, and long-term management, which means that population-based strategies are also needed. These strategies involve conceptual shifts towards community- and environment-focused approaches. This review aimed to provide evidence on how environmental factors contribute to the risk of obesity and how reshaping cities can help slow down obesity prevalence rates and improve long-term management.

The balance between traffic control and economic development in tourist cities under the context of COVID-19: A case study of Xi'an, China.

Selecting an appropriate intensity of epidemic prevention and control measures is of vital significance to promoting the two-way dynamic coordination of epidemic prevention and control and economic development. In order to balance epidemic control and economic development and suggest scientific and reasonable traffic control measures, this paper proposes a SEIQR model considering population migration and the propagation characteristics of the exposed and the asymptomatic, based on the data of COVID-19 cases, Baidu Migration, and the tourist economy. Further, the factor traffic control intensity is included in the model. After determining the functional relationship between the control intensity and the number of tourists and the cumulative number of confirmed cases, the NSGA-II algorithm is employed to perform multi-objective optimization with consideration of the requirements for epidemic prevention and control and for economic development to get an appropriate traffic control intensity and suggest scientific traffic control measures. With Xi'an City as an example. The results show that the Pearson correlation coefficient between the predicted data of this improved model and the actual data is 0.996, the R-square in the regression analysis is 0.993, with a significance level of below 0.001, suggesting that the predicted data of the model are more accurate. With the continuous rise of traffic control intensity in different simulation scenarios, the cumulative number of cases decreases by a significant amplitude. While balancing the requirements for epidemic prevention and control and for tourist economy development, the model works out the control intensity to be 0.68, under which some traffic control measures are suggested. The model presented in this paper can be used to analyze the impacts of different traffic control intensities on epidemic transmission. The research results in this paper reveal the traffic control measures balancing the requirements for epidemic prevention and control and for economic development.

Analyzing the impact of COVID-19 on consumption behaviors through recession and recovery patterns.

The COVID-19 outbreak has dramatically impacted the economy, particularly consumption behaviors. Studies on how consumption responses to COVID-19 can be a powerful aid for urban consumption recovery. In this paper, based on a high-frequency consumption dataset from January 6, 2020, to April 28, 2020 covering 18 sectors and dataset from the corresponding lunar period in 2021, we look at how COVID-19 changed how people spent their money by looking at patterns of recession and recovery during the pandemic. Specifically, we first explore the recession-recovery pattern of national consumption and the effects of various policies and quantify it using regression methods. Then, recession-recovery patterns across cities are widely studied. We also reveal how consumption structures change during a pandemic and the relationship between patterns of change in citizens' consumption and the socioeconomic characteristics of cities. And the specific empirical analysis is provided through panel regression models. In general, national consumption represented a Vshaped pattern during the pandemic, experiencing a dramatic decline and a rapid rebound. Consumption is significantly inhibited by lockdown, while it is stimulated positively but gradually by easing policies. Consumption patterns at the city level are associated with socioeconomic characteristics. Cities with high-income groups experience a more significant decline, and cities with a high share of the secondary sector have a higher recovery rate in consumption. The consumption structure redistributes but does not fundamentally change. During the recession and early recovery phase, consumption related to basic living saw a significant rise, whereas leisure-related consumption dropped dramatically and recovered slowly. Our study can assist policymakers in implementing diversified market provisions and targeted lockdown policy adjustments for consumption recovery in cities with different socioeconomic backgrounds.

Dengue outbreaks in a city with recent transmission in São Paulo state, Brazil.

We investigated the distribution of dengue cases, solid waste deposits (SWDs), forest fragments, water drainage, population income, and the possible association with dengue outbreaks in Presidente Prudente, São Paulo, Brazil. An urban setting with recent transmission. Data were obtained from public agencies. Kernel density maps of the variables were constructed. From 2015 to 2021, 33026 cases of dengue were reported; the incidence and mortality rate were highest in 2016. The number of cases decreased during the COVID-19 pandemic (2020 and 2021) compared with 2019, but alarming rates were registered in 2022. In 2015, 56 points of SWDs were identified, with an increase of 1.6-fold in 2020 and 2021. Multivariate analysis showed a positive correlation between the density of dengue cases and SWDs with the highest correlation (0.70) in 2020. Identifying these areas could guide public health authorities in surveillance measures and improvements in health care infrastructure.

Micro-scale urbanization-based risk factors for dengue epidemics.

Dengue is one of the world's most rapidly spreading mosquito-borne viral diseases. As it is found mostly in urban and semi-urban areas, urbanization and associated human activities that affect the environment and larval habitats could become risk factors (e.g., lane width, conditions of street ditches) for the spread of dengue. However, there are currently no systematic studies of micro-scale urbanization-based risk factors for the spread of dengue epidemics. We describe the study area, two micro-scale environmental risk factors associated with urbanization, and meteorological data. Since the observations involve spatial and temporal correlations, we also use some statistical methods for the analysis of spatial and spatial-temporal data for the relationship between urbanization and dengue. In this study, we analyzed data from Kaohsiung, a densely populated city in southern Taiwan, and found a positive correlation between environmental risk factors associated with urbanization (ditches positive for mosquito larvae and closely packed streets termed "dengue lanes") and clustering effects in dengue cases. The statistical analysis also revealed that the occurrence of positive ditches was significantly associated with that of dengue lanes in the study area. The relationship between climate variables and positive ditches was also analyzed in this paper, indicating a relationship between dengue and both rainfall and temperature, with temperature having a greater effect. Overall, this work is immediately relevant and applicable for policymakers in government, who will need to reduce these favorable habitats for vector-born disease spreaders and implement regulations for new urban constructions to thus reduce dengue spread in future outbreaks.