Land scale division and multifunctional evaluation for Fuping County, China, based on DEM-based watershed analysis

Land is the spatial background and basic carrier of human survival and development. The study of land function evaluation at different scales can promote the harmonious coexistence of humans and nature. Taking Fuping County, Hebei Province, China, as an example, this study establishes the theoretical framework of county-level land scale division using a digital elevation model (DEM)-based watershed analysis method and establishes the theory and methodological system of land function evaluation from the perspective of the characteristic scale. The multifunctionality of the land was evaluated using the Carnegie-Ames-Stanford approach (CASA), the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model and comprehensive index evaluation. By using the methods of DEM-based watershed analysis, dominant factor differentiation and layer superposition, a three-level scale system of 'subwatershed scale-land chain scale-land segment scale' and a multifunctional multiscale evaluation index system containing 18 evaluation indices were established. The single-function and multifunction evaluation results of land at different scales were obtained by the comprehensive index method and Getis-Ord Gi* index method. The accuracy of land function evaluation results mainly depends on the selection of the measurement scale. The land measurement scale determined by DEM-based watershed analysis is close to the intrinsic scale of land function evaluation. The scale effect of land function in different temporal and spatial ranges is also evident and shows obvious spatial heterogeneity and difference. At larger scales, individual functions show synergistic effects.

Exploring the coupling and decoupling relationship of urbanization and carbon emissions in China

Burgeoning urbanization is a defining challenge for global carbon emissions mitigation in the coming decades. In this context, achieving low-carbon urbanization remains an urgent issue that demands prompt solutions. The coupling and decoupling relationships between urbanization and carbon emissions play an important role in the coordination of urbanization development and carbon emissions reduction, which has rarely been explored in existing studies, especially in China at the county level. To address this gap, the coupling and decoupling relationship between the urbanization level (UL) and carbon emissions density (CED) was explored using an improved coupling degree model and the Tapio decoupling method in China at the county level from 2000 to 2020. The results showed that the UL and CED of China both exhibited increasing trends, and the spatial distribution was quite similar, with the UL increasing from 0.018 in 2000 to 0.028 in 2020 and the CED increasing from 95.163 ton/km2 in 2000 to 295.746 ton/km2 in 2020. The spatial distribution of hotspots in the UL change differed with time, whereas that in the CED change was relatively stable. However, both of them were concentrated in eastern China. The coupling degrees of the UL and CED in China were 0.348, 0.355, 0.369, 0.370, and 0.338 in 2000, 2005, 2010, 2015, and 2020, respectively, with the moderately unbalanced type (>35%) being dominant at the county level and mainly scattered in eastern China. The changes in the spatial distribution patterns of the 10 subcategories were quite limited, with the systematically balanced type being dominant (89%). The decoupling types of the UL and CED during 2000-2005, 2005-2010, and 2010-2015 were weak decoupling, while those in 2015-2020 were expansive negative decoupling. At the county level, the most significant transition occurred between expansive negative decoupling, strong decoupling, and strong negative decoupling. The proportion of strong decoupling type counties peaked in 2015-2020 (70.86%), whereas that of the strong negative decoupling type counties remained high (17.55%), scattering the country. These findings can advance policy enlightenment of low-carbon urbanization and green development for China against the backdrop of "30·60 dual carbon" goal.

Coupling coordination analysis and spatiotemporal heterogeneity between sustainable development and ecosystem services in Shanxi Province, China

Excessive human activities destroy the structure and function of ecosystem and threaten sustainable development. As a typical resource-based area, Shanxi Province is facing an increasingly serious contradiction between ecosystem and sustainable development, with the overexploitation of resources. In view of this, the coupling coordination degree model was used to measure the association between sustainable development and ecosystem services (SDESs), and geographically and temporally weighted regression model was used to explore the correlation between SDESs and measure the correlation between ecosystem services (ESs) and sustainable development at the county level from 2000 to 2015 in Shanxi Province. The results showed an increase in the sustainable development level and all ESs except soil retention. The coupling coordination degree (CCD) of soil retention and sustainable development decreased, while other services increased. Habitat quality had the strongest negative correlation with sustainable development. There were obvious spatiotemporal heterogeneities in the CCD and correlation of SDESs, which is helpful for promoting regional sustainable development and optimize ecosystem decision-making.

Spatial patterns of HPV and Tdap vaccine dose administration and the association of health department clinic access in Georgia counties

OBJECTIVE

To characterize counties in GA by quantifying administered doses of the HPV and Tdap vaccines collected by the state health department immunization registry and indicators of Health Department (HD) clinic access.

METHODS

Using a cross sectional study design, secondary data were collected from public health data sources for the years 2016 to 2018 for 159 counties of Georgia. The study population was male and female adolescents aged 13-17. The number of administered HPV and Tdap vaccine doses were modeled in relation to number of private and public HD clinics, number of HD clinics registered in the VFC program and the availability of public transportation using Poisson regression, negative binomial regression, and Bayesian spatial analysis.

RESULTS

Choropleth maps showed similar clustering patterns between administered doses of the HPV vaccine and Tdap vaccine and increased counts of administered vaccine doses in counties with both public and private clinics. Administered doses of HPV and Tdap vaccines were found to exhibit spatial dependence across counties. Accounting for spatial dependence, the availability of public transit had a significant positive effect on administered HPV vaccine doses, while the number of private HD clinics had a significant positive effect on administered Tdap vaccine doses.

CONCLUSIONS

Maps at the county level show vaccination variability, clustering patterns and provide additional insights on the access to health care. Bayesian spatial models are needed to accurately identify and estimate factors associated with administering doses of the HPV and Tdap vaccines. Future work is needed to further examine the utilization of HPV vaccination services among urban groupings.

The socio-economic determinants of COVID-19: A spatial analysis of German county level data

The study explores the association of socioeconomic, demographic, and health-related variables at the regional level with COVID-19 related cases and deaths in Germany during the so-called first wave through mid-June 2020. Multivariate spatial models include the 401 counties in Germany to account for regional interrelations and possible spillover effects. The case and death numbers are, for example, significantly positively associated with early cases from the beginning of the epidemic, the average age, the population density and the share of people employed in elderly care. By contrast, they are significantly negatively associated with the share of schoolchildren and children in day care as well as physician density. In addition, significant spillover effects on the case numbers of neighbouring regions were identified for certain variables, with a different sign than the overall effects, giving rise to further future analyses of the regional mechanisms of action of COVID-19 infection. The results complement the knowledge about COVID-19 infection beyond the clinical risk factors discussed so far by a socio-economic perspective at the ecological level.

The socio-economic determinants of COVID-19: A spatial analysis of German county level data

The study explores the association of socioeconomic, demographic, and health-related variables at the regional level with COVID-19 related cases and deaths in Germany during the so-called first wave through mid-June 2020. Multivariate spatial models include the 401 counties in Germany to account for regional interrelations and possible spillover effects. The case and death numbers are, for example, significantly positively associated with early cases from the beginning of the epidemic, the average age, the population density and the share of people employed in elderly care. By contrast, they are significantly negatively associated with the share of schoolchildren and children in day care as well as physician density. In addition, significant spillover effects on the case numbers of neighbouring regions were identified for certain variables, with a different sign than the overall effects, giving rise to further future analyses of the regional mechanisms of action of COVID-19 infection. The results complement the knowledge about COVID-19 infection beyond the clinical risk factors discussed so far by a socio-economic perspective at the ecological level.

Measuring the completeness of death registration in 2844 Chinese counties in 2018

BACKGROUND

Death registration completeness has never been assessed at the county level in China. Such analyses would provide critical intelligence to monitor the performance of the vital registration system and yield adjustment factors to correct death registration data, thereby increasing their policy utility.

METHODS

We estimated the completeness of death registration for 31 provinces and 2844 counties of China in 2018 based on death data from the China Cause of Death Reporting System (CDRS) by using the empirical completeness method. We computed the root mean square difference (RMSD) of county-level completeness compared with provincial-level completeness to study intra-provincial variations. A two-level (province and county) logistic regression model was fitted to explore the association between county-level registration completeness and a set of covariates reflecting socioeconomic status, healthcare quality, and specific strategies and regulations designed to improve registration.

RESULTS

In 2018, the overall death registration completeness for the CDRS in China was 74.2% (95% uncertainty interval [UI] 66.2-80.4), with very little difference for males and females. Geographical differences in completeness were higher across counties than across provinces. The county-level completeness ranged from 2.4% (95% UI 1.0-5.0%) in Burang County, Tibet, to 100.0% (95% UI 99.9-100.0%) in Guandu District, Yunnan. The coastal provinces of Jiangsu, Guangdong, and Fujian, with higher overall completeness, contained counties with low completeness; conversely, the underdeveloped provinces of Guangxi and Guizhou, with lower overall completeness, included some counties with high completeness. GDP, education, population density, minority population, healthcare access, and registration strategies were important drivers of the geographical differences in registration completeness.

CONCLUSIONS

There are marked inequalities in registration completeness at the county level and within provinces in China. The socioeconomic condition, the implementation of specific registration-enhancing initiatives, and the availability and quality of medical care were the primary drivers of the observed geographical variation. A more strategic approach, with more research, is required to identify the main reasons for death under-reporting, especially in the poorer performing counties, to guide remedial action.

Combining habitat area and fragmentation change for ecological disturbance assessment in Jiangsu Province, China

Understanding where and how human land use causes ecological consequences is essential for habitat conservation. However, the assessment of the ecological disturbance caused by human land use is usually shaped by the area change in ecological land. The comprehensive evaluation of ecological disturbance based on the losses and gains of ecological patches is neglected. This paper analyzed the land use change between agricultural land, construction land, and ecological land from 1995 to 2015 in Jiangsu Province of eastern China. The ecological disturbance was quantificationally evaluated by a proposed index that considered both the changes of habitat area and fragmentation caused by the losses and gains of ecological landscape patches. The findings showed that there was a slight increase in area of ecological land in Jiangsu Province; however, ecological fragmentation was becoming severe with the growth of human land use, which, in turn, resulted in increased ecological disturbance. The losses and gains in the area and fragmentation of ecological land were comprehensively reflected using the proposed ecological disturbance index. Negative ecological disturbance was more likely to be observed at the edge of the city centers, ecologically sensitive areas, and counties with low area ratios of ecological land. Ecological governance policies should be formulated and implemented based on quantity, quality, and spatial relationships between human land use and ecological disturbance.

Landscape functional zoning at a county level based on ecosystem services bundle: Methods comparison and management indication

The perspective of ecosystem services bundle is virtually a spatial clustering on landscape to mapping the relationship between ecosystem services and support the spatial strategy of landscape management. However, the efficiency of various clustering algorithms for geographically different regions are still in obscurity. In this study, we provided landscape functional zoning as a planning tool based on the ecosystem services bundles formed by carbon sequestration, soil retention and water yield. Then we used four landscape pattern indices to evaluate the performance of six clustering algorithms on landscape functional zoning. The case counties include Lankao, Jinggangshan and Luquan in China. The results showed the Natural Breaks (Jenks) scheme should be the most reasonable zone because of its high aggregated distribution and low diversity. This scheme was adjusted using some other schemes and has been employed as the final 7 kinds of zoning types. There were 5 types appeared in Lankao and Jinggangshan, and 6 types appeared in Luquan. We discussed that landscape functional zone can be a nexus connecting landscape planning and social policy. Rural reconstructing process on landscape was depicted, and landscape functional zone was proposed a practical planning tool bridged human wellbeing. The task of landscape functional zoning with the management indications may provide interdisciplinary support to decision-makers and natural resource users on landscape management.

Exploring Social Determinants of Health as Predictors of Mortality During 2012-2016, Among Black Women with Diagnosed HIV Infection Attributed to Heterosexual Contact, United States

BACKGROUND

In 2016, black women with HIV infection attributed to heterosexual contact accounted for 47% of all women living with diagnosed HIV, and 41% of deaths that occurred among women with diagnosed HIV in the USA that year. Social determinants of health have been found to be associated with mortality risk among people with HIV. We analyzed the role social determinants of health may have on risk of mortality among black women with HIV attributed to heterosexual contact.

METHODS

Data from the Center for Disease Control and Prevention's National HIV Surveillance System were merged at the county level with three social determinants of health (SDH) variables from the U.S. Census Bureau's American Community Survey for black women aged ≥ 18 years with HIV infection attributed to heterosexual contact that had been diagnosed by 2011. SDH variables were categorized into four empirically derived quartiles, with the highest quartile in each category serving as the reference variable. For black women whose deaths occurred during 2012-2016, mortality rate ratios (MRR) were calculated using age-stratified multivariate logistic regressions to evaluate associations between SDH variables and all-cause mortality risk.

RESULTS

Risk of mortality was lower for black women aged 18-34 years and 35-54 years who lived in counties with the lowest quartile of poverty (adjusted mortality rate ratio aMRR = 0.56, 95% confidence interval CI [0.39-0.83], and aMRR = 0.67, 95% CI [0.58-0.78], respectively) compared to those who lived in counties with the highest quartile of poverty (reference group). Compared to black women who lived in counties with the highest quartile of health insurance coverage (reference group), the mortality risk was lower for black women aged 18-34 years and black women aged 35-54 who lived in counties with the lowest 2 quartiles of health insurance coverage. Unemployment status was not associated with mortality risk.

CONCLUSIONS

This ecological analysis found poverty and lack of health insurance to be predictors of mortality, suggesting a need for increased prevention, care, and policy efforts targeting black women with HIV who live in environments characterized by increased poverty and lack of health insurance.

Agricultural vulnerability over the Chinese Loess Plateau in response to climate change: Exposure, sensitivity, and adaptive capacity

Understanding how the vulnerability of agricultural production to climate change can differ spatially has practical significance to sustainable management of agricultural systems worldwide. Accordingly, this study developed a conceptual framework to assess the agricultural vulnerability of 243 rural counties on the Chinese Loess Plateau. Indicators representing the climate/agriculture interface were selected to describe exposure and sensitivity, while stocks of certain capitals were used to describe adaptive capacity. A vulnerability index for each county was calculated and the spatial distribution was mapped. Results showed that exposure, sensitivity, and adaptive capacity occur independently, with most contributing indicator values concentrated in a narrow range after normalization. Within the 49 most vulnerable counties, which together encompass 81 % of the vulnerability index range, 42 were characterized by high exposure and sensitivity but low adaptive capacity. The most vulnerable area was found to be located in the central northeast-southwest belt of Loess Plateau. Adaptation measures for both ecological restoration and economic development are needed and potential adaptation options need further investigation.