Level Administrative Units Research Articles

Air pollution spatial variability in relation to socioeconomic indicators in nine European metropolitan areas.

OPS 04: Environmental justice, Room 117, Floor 1, August 27, 2019, 1:30 PM - 3:00 PM Aim: A limited number of studies have addressed environmental inequality in relation to air pollution, using various study designs and methodologies and often reaching contradictory results. We conducted an ecological study to investigate the spatial association between nitrogen dioxide (NO2), as a surrogate for traffic related air pollution, and ten socioeconomic status indicators (SES). Methods: Following a standardized multi-city process within the European project EURO-HEALTHY we collected SES data at local administrative unit level in nine European Metropolitan Areas for the period 2001-14: Athens, Greece; Barcelona, Spain; Berlin-Brandenburg, Germany; Brussels, Belgium; Lisbon, Portugal; London, UK; Paris, France; Stockholm, Sweden and Turin, Italy. We applied mixed models for the associations under investigation with random intercepts per MA, also accounting for the spatial correlation. Results: The stronger associations were observed between NO2 levels and population density, population born outside the European Union (EU28), total crimes per 100,000 inhabitants and unemployment rate that displayed a highly statistically significant trend of rising concentrations with increasing levels of these indicators. Specifically, the highest vs the lowest quartile of each of the above indicators was associated with 48.7% (95% confidence interval (CI): 42.9%, 54.8%), 30.9% (95%CI: 22.1%, 40.2%), 19.8% (95%CI: 13.4%, 26.6%) and 15.8% (95%CI: 9.9%, 22.1%) increase in NO2 respectively. Conclusions: Higher pollution levels in areas with higher percentages of people born outside EU28, crime or unemployment rates indicate that worse air quality is typically encountered in deprived European urban areas. The association with population density most probably reflects the higher volume of vehicular traffic, which is the main source of NO2 in urban areas. Policy makers should consider spatial environmental inequalities to better inform actions aiming to lower urban air pollution levels that will subsequently lead to improved quality of life, public health and health equity across the population.

Impact of Advocacy, Communication, Social Mobilization and Active Case Finding on TB Notification in Jharkhand, India

Community-level benefits of screening for active tuberculosis (TB) disease remain uncertain. Project Axshya (meaning free of TB) conducted advocacy, communication, social mobilization, and active case finding among vulnerable/marginalized populations of India. Among 15 districts of Jharkhand state, the project was initiated in 36 subdistrict level administrative units — tuberculosis units (TUs) in a staggered manner between April 2013 and September 2014, and continued till the end of 2015. Seven TUs did not implement the project. We assessed the relative change in the quarterly TB case finding indicators (n = 4) after inclusion of a TU within the project. By fitting four multilevel models (mixed-effects maximum likelihood regression using random intercept), we adjusted for secular (over previous five quarters) and seasonal trends, baseline differences within Axshya and non-Axshya TUs, and population size and clustering within districts and within TUs. After inclusion of a TU within the project, we found a significant increase [95% confidence interval (CI)] in TU-level presumptive TB sputum examination rate, new sputum-positive TB Case Notification Rate (CNR), sputum-positive TB CNR, and all forms TB CNR by 12 (5.5, 18.5), 1.1 (0.5, 1.7), 1.3 (0.6, 2.0), and 1.2 (0.1, 2.2) per 100,000 population per quarter, respectively. Overall, the project resulted in an increase (95% CI) in sputum examination and detection of new sputum-positive TB, sputum-positive TB and all forms of TB patients by 22,410 (10,203, 34,077), 2066 (923, 3210), 2380 (1162, 3616), and 2122 (203, 4059), respectively. This provides evidence for implementing project Axshya over and above the existing passive case finding.

Environmental assessment of agricultural activities and groundwater nitrate pollution susceptibility: a regional case study (Southwestern Romania).

Diffuse pollution of water resources from agricultural sources is a major environmental issue in Europe. The nutrients released in groundwater from cultivated fields and livestock production, together with pesticides, are the main source of concern in the framework of the European Nitrates Directive (91/676/EEC). Southern Romania continues to represent one of the most important cereal production areas of the country. The intensive exploitation during the communist period continues to have repercussions for the precarious quality of groundwater. The aim of our study was to establish the environmental conditions, quantify the agricultural activities at the local administrative unit level and afterwards, to highlight areas of susceptibility to nitrate pollution of groundwater within the Oltenia Plain. One of the most efficient methods to evaluate human influences by agricultural activities on groundwater is using different types of indicators, such as land use indicators (cultivated surfaces), animal husbandry indicators (livestock and great beef units), and agri-environmental indicators (use of fertilisers based on nitrogen and phosphorus, quantity/ha). Throughout the paper, GIS methods are used to determine the degree of influence on nitrate pollution of several eco-pedological indicators: soil types and subtypes, slope of the land, soil texture, soil permeability, and groundwater level. Statistics indicate that 85% of the study area is susceptible to nitrate pollution from agriculture. Indicators provide information that can be easily interpreted by decision and policy makers, and they facilitate the process of reducing nitrate pollution. This study shows that the correlation of statistics and GIS modelling is a useful method for guiding prevention practices for groundwater pollution at the regional scale in Southwestern Romania.

Interactive mapping for geographically weighted correlation in big census data

Abstract. Census data are widely available in many countries and are useful in describing socio-economic structures in a map at an administrative unit level. Multiple variables in census data can be investigated, however, selecting a large number of variables often leads to confusion and makes it difficult to discern which should be considered. Correlation analysis is often applied to measure the degree of association of a pair of variables, while a correlation matrix is used to summarize relationships amongst multiple variables at the same time. Although both provide important metrics, the spatial configuration of the data is not taken into account. For the purpose of mapping, it is often of interest to highlight the correlative relationship between a pair of variables across space in order to deal with any spatial heterogeneity hidden in the data. In this sense, geographically weighted correlation and partial correlation analyses have been proposed to map spatial variations of correlations in a spatial data set. The geographically weighted approach uses a moving-window kernel running across geographical space and calculates a statistical model or summary statistic with distance-decayed weighted data. The critical issue of mapping such correlation relationships amongst multiple variables is the large number of resultant maps produced. If we are interested in correlations amongst 100 variables, the correlation matrix has the dimension of 100 by 100, while 4,950 correlation maps are produced when we investigate local correlation relationships. Furthermore, the degree of scale (localness) which is an important parameter to understand the local correlative relationship should be explored. To this end, the purpose of this study is to build an interactive mapping system for visualizing spatial variations of correlative relationships amongst multivariate variables in big census data. This system is built on Shiny in R and an R package for calculating the geographically weighted correlation and partial correlation coefficients across multiple variables (https://github.com/naru-T/GWpcor) is implemented behind this system for analyses. We use the national census data set for 2005 with 204 variables regarding socio-economic structures in 23 wards in Tokyo with 3,134 administrative units as a case study. The system implements geographically weighted correlation and partial correlation analyses with varying scale parameters and produces an interactive spatial surface of the correlation coefficient. We demonstrate how our interactive mapping system enables users to achieve quick visualization of correlative relationships amongst multivariate census data which can be selected and changed easily from pull-down lists (Figure 1). Such a user-friendly interactive mapping system proposed in this study will help those who need to understand the spatial relationships of the data that is being mapped. This study is supported by ROIS-DS-JOINT (006RP2018).

How accurate are modelled birth and pregnancy estimates? Comparison of four models using high resolution maternal health census data in southern Mozambique

BackgroundExistence of inequalities in quality and access to healthcare services at subnational levels has been identified despite a decline in maternal and perinatal mortality rates at national levels, leading to...

СТИМУЛЮВАННЯ РОЗВИТКУ ІННОВАЦІЙНОГО ПІДПРИЄМНИЦТВА НА ЗАСАДАХ ТРАНСКОРДОННОГО ПАРТНЕРСТВА

The paper seeks to explore the pathways for promoting the development of innovative entrepreneurship based on cross-border partnerships. The study has revealed that the conceptual objective of the innovative development regulatory policy is the integration of society through the interactions among government, business, population, media and public organizations for building a single ideological framework for innovative development which will reflect the economic, social, political and cultural capacities of the state as well as the potential benefits they could bring to the country by delivering structural and innovative transformations. It is argued that the guiding principles of innovative development should involve elaboration of a set of the key economic development indicators for the long run which contributes to creating proper motivation and understanding of the ultimate outcomes of the national innovation policy by the society, business community and government authorities. Apparently, an emphasis is made that building a synergistic effect is critical in boosting cross-border partnerships through facilitating better interactions among ministries and institutions in their programs implementation and innovation-driven activities; identifying targeted goals, vectors and instruments of government innovation policy that is carried out at the national level followed by its consistent application at the level of territorial and administrative units. Using the international best practice in promoting innovative entrepreneurship development based on a cross-border partnerships subject to the national specifics, the study exposed the problem areas related to the legislation deficiency, innovative integration funding challenges, lack of qualified workforce in certain regions of Ukraine, etc.

METHODICAL APPROACHES TO THE REFORMING OF ADMINISTRATIVE DISTRICTS IN UKRAINE

Topicality. The need to reform subregional (district) level of administrative and territorial division of Ukraine is urgent as the result of forming of consolidated territorial communities and the change of liabilities division between the basic and district levels. Transition of the majority of liabilities from local governments to consolidated territorial communities has changed the nature and direction of communication links between the residents and authorities at the district level and contributes to reinforcement of district level of administrative and territorial units. Due to reforming of the system of administrative and territorial structure of Ukraine, a district becomes the territory of localization and functioning of state authorities. The major list of administrative, educational, medical, cultural and other public services will be provided at the basic rather than district levels.Aim and tasks. The paper aims to substantiate and outline the suggestions regarding the methodical approaches to reforming of the system of administrative and territorial units at subregional level in the context of local governance reform and authorities’ territorial organization reform conducted in Ukraine.Research results. The author analyzes the use of the concept of “district” in the context of administrative and territorial division and suggests its definition as administrative and territorial unit that is included into the higher-level units (Autonomous Republic of Crimea, oblasts, cities with special status) and is the territorial foundation for organization of activity of state authorities and local governments at subregional levels. District should include all administrative and territorial units of basic level located within its boundaries. Major principles, criteria and requirements to apply while forming the districts are suggested. Among those criteria and requirements, we outline the following: demographic capacity of a territory – usually between 150 and 800 thous. residents; transport accessibility of administrative center of the district from the most remote settlement – up to 1.5 hours (not exceeding 50-60km); the network of districts is reorganized without the change of oblasts’ boundaries; administrative center of a district is usually located closest to geographic (transport-geographical) center of district’s territory; administrative center of a district is usually the settlement with the highest economic and demographic capacity and developed infrastructure, which performed, performs or can perform the functions of subregional administrative center.An algorithm of modeling of new administrative districts is presented as the consequence of steps: 1) finding subregional centers – perspective centers of administrative districts (usually out of oblast significance cities); 2) zone of gravitation to oblast center with the radius up to 60km is considered as the territory of administrative district; 3) outside its boundaries the other districts are allocated according to gravitation zones of other perspective centers of districts; 4) there are also factors that substantially impact their functionality and efficiency of relevant authorities: natural-geographical, transport, economical, managemental, historical, demographic, infrastructural, etc.Conclusion. In author’s opinion, approaches to forming of administrative districts contribute to optimization of their network taking into account the changes in the functions of a district in the system of public authority division. Testing of these methodological approaches in the process of modeling of the new network of administrative regions shows an opportunity and reasonability of their reduction in Lvivska oblast from 20 to 7, in Ivano-Frankivska oblast from 14 to 4, in Ternopilska oblast from 15 to 4.

Spatial variability in air pollution exposure in relation to socioeconomic indicators in nine European metropolitan areas: A study on environmental inequality

A limited number of studies have addressed environmental inequality, using various study designs and methodologies and often reaching contradictory results. Following a standardized multi-city data collection process within the European project EURO-HEALTHY, we conducted an ecological study to investigate the spatial association between nitrogen dioxide (NO2), as a surrogate for traffic related air pollution, and ten socioeconomic indicators at local administrative unit level in nine European Metropolitan Areas. We applied mixed models for the associations under investigation with random intercepts per Metropolitan Area, also accounting for the spatial correlation. The stronger associations were observed between NO2 levels and population density, population born outside the European Union (EU28), total crimes per 100,000 inhabitants and unemployment rate that displayed a highly statistically significant trend of increasing concentrations with increasing levels of the indicators. Specifically, the highest vs the lowest quartile of each indicator above was associated with 48.7% (95% confidence interval (CI): 42.9%, 54.8%), 30.9% (95%CI: 22.1%, 40.2%), 19.8% (95%CI: 13.4%, 26.6%) and 15.8% (95%CI: 9.9%, 22.1%) increase in NO2 respectively.The association with population density most probably reflects the higher volume in vehicular traffic, which is the main source of NO2 in urban areas. Higher pollution levels in areas with higher percentages of people born outside EU28, crime or unemployment rates indicate that worse air quality is typically encountered in deprived European urban areas. Policy makers should consider spatial environmental inequalities to better inform actions aiming to lower urban air pollution levels that will subsequently lead to improved quality of life, public health and health equity across the population.

What Drives People to Complain about Environmental Issues? An Analysis Based on Panel Data Crossing Provinces of China

Strengthening public participation has often proven essential for achieving environmental sustainability goals. The “Xinfang”system, through complaint visits and letters, offers institutional channels through which the public’s grievances can be addressed, and where court judgments can be challenged by filing complaints about environmental problems to Environmental Protection Bureaus. Operating under the monopoly of the state Party, the “Xinfang” system provides the political opportunity for pro-environmental values and interests to be voiced and heard by governments. Importantly, comprehending the evolution of public complaints over a prolonged period of time sheds light on various determinants of this public participation program. This paper seeks to better understand environmental degradation caused by unbridled economic growth in China and the efforts that civic environmentalism has made to reduce the problem. More specifically, it uses panel data on 31 Chinese provincial/first level administrative units, collected over a decade, from 2003 to 2015, to analyze how socioeconomic status in the general public and the political and policy structures have shaped civic environmentalism. We use two Ordinary Least Squares (OLS) models to explore how these actors have propelled the public to protect their environment from discharged industrial wastewater, industrial waste gas, and solid wastes.

Assessing the spatial sensitivity of a random forest model: Application in gridded population modeling

AbstractGridded human population data provide a spatial denominator to identify populations at risk, quantify burdens, and inform our understanding of human-environment systems. When modeling gridded population, the information used for training the model may differ in spatial resolution than what is produced by the model prediction. This case arises when approaching population modeling from a top-down, dasymetric approach in which one redistributes coarse administrative unit level population data (i.e., source unit) to a finer scale (i.e., target unit). However, often overlooked are issues associated with the differing variance across the scale, spatial autocorrelation and bias in sampling techniques. In this study, we examine the effects of intentionally biasing our sampling from the source to target scale within the context of a weighted, dasymetric mapping approach. The weighted component is based on a Random Forest estimator, which is a non-parametric ensemble-based prediction model. We investigate issues of autocorrelation and heterogeneity in the training data using 18 different types of samples to show the variations in training, census-level (i.e., source) and output, grid-level (i.e., target) predictions. We compare results to simple random sampling and geographically stratified random sampling. Results indicate that the Random Forest model is sensitive to the spatial autocorrelation inherent in the training data, which leads to an increase in the variance of the residuals. Sample training datasets that are at a spatial scale representative of the true population produced the best fitting models. However, the true representative dataset varied in autocorrelation for both scales. More attention is needed with ensemble-based learning and spatially-heterogeneous data as underlying issues of spatial autocorrelation influence results for both the census-level and grid-level estimations.

Spatial distribution of the potential forest biomass availability in Europe

BackgroundEuropean forests are considered a crucial resource for supplying biomass to a growing bio-economy in Europe. This study aimed to assess the potential availability of forest biomass from European forests and its spatial distribution. We tried to answer the questions (i) how is the potential forest biomass availability spatially distributed across Europe and (ii) where are hotspots of potential forest biomass availability located?MethodsThe spatial distribution of woody biomass potentials was assessed for 2020 for stemwood, residues (branches and harvest losses) and stumps for 39 European countries. Using the European Forest Information SCENario (EFISCEN) model and international forest statistics, we estimated the theoretical amount of biomass that could be available based on the current and future development of the forest age-structure, growing stock and increment and forest management regimes. We combined these estimates with a set of environmental (site productivity, soil and water protection and biodiversity protection) and technical (recovery rate, soil bearing capacity) constraints, which reduced the amount of woody biomass that could potentially be available. We mapped the potential biomass availability at the level of administrative units and at the 10 km × 10 km grid level to gain insight into the spatial distribution of the woody biomass potentials.ResultsAccording to our results, the total availability of forest biomass ranges between 357 and 551 Tg dry matter per year. The largest potential supply of woody biomass per unit of land can be found in northern Europe (southern Finland and Sweden, Estonia and Latvia), central Europe (Austria, Czech Republic, and southern Germany), Slovenia, southwest France and Portugal. However, large parts of these potentials are already used to produce materials and energy. The distribution of biomass potentials that are currently unused only partially coincides with regions that currently have high levels of wood production.ConclusionsOur study shows how the forest biomass potentials are spatially distributed across the European continent, thereby providing insight into where policies could focus on an increase of the supply of woody biomass from forests. Future research on potential biomass availability from European forests should also consider to what extent forest owners would be willing to mobilise additional biomass from their forests and at what costs the estimated potentials could be mobilised.

CONDITION OF FINANCIAL SUPPORT OF REGIONAL POLICY

The article assesses the financial support of regional policy. The theoretical and methodological foundations of regional financial policy in Ukraine are highlighted. The main instruments for securing this policy are the share of revenues assigned to territories in the budgets at all levels of the budget system, local taxes and fees, the rates of deductions from state taxes to local budgets, as well as subsidies provided to local budgets. It is noted that there is a considerable dependence of the development of the territories on the processes occurring in the higher level administrative units. The essence of regional financial policy as a spatial segment of public financial policy is revealed. Models of financing of regional development are given. The current model of financing regional development is multichannel, multilevel and includes both traditional financial institutions - state, local budget, and new institutions of mixed financing of the transformational economy. At the regional level, one of the main elements of the mechanism for regulating socio-economic development is the development and implementation of integrated regional programs aimed at improving the functioning of a particular sector of the economy. On the example of Kharkiv region, the mechanism of regulation of socio-economic development is analyzed by evaluating the effectiveness of regional financial policy implementation by individual indicators. The influence of local self-government bodies of Kharkiv region on formation of own financial policy is determined. According to the results of the research, the indicators of financial independence of local self-government were calculated: the coefficient of financial autonomy, the coefficient of financial dependence, the coefficient of autonomy, the ratio of the share of local taxes and fees in the structure of tax revenues. Based on the research, it is found that the share of state transfers in local budget revenues is gradually decreasing, financial dependence on public revenues is decreasing, tax revenues in the structure of local budgets are increasing, which indicates an increase in financial autonomy as a whole.

Identification of Smart Regions with Resilience, Specialisation and Labour Intensity of globally Competitive Sector – The Examination of the LAU-1 Regions in Finland

The purpose of the study is to construct smart specialization indicators for LAU-1 regions in Finland. Established indices are based on indicators on region’s revealed comparative advantage, and the degree of diversification in its sub-regional industrial structure. Further, we introduce a measure that can be used to assess the socio-economic importance (employment) of diversification and specialization for a region. The data of indices is based on the Statistic Finland (2015) with Local Administrative Unit level 1 (LAU1), 70 regions in Finland. The potential S3 Indices measured here reveal sub-region’s Smart specialization position within 70 sub-region in Finland in 2015. The common economic knowledge states that manufacturing industries are the most export-oriented, highly productive, and thus, can approximate the region’s success in international trade and competitive advantages. The study is based on smart specialization indices: the Herfindahl-Hirschman Index for regional resilience (HHI), regional relative specialization index (RRSI) based on Balassa-Hoover Index (B-H), and the relative employment volume index in manufacturing sector (LIMI). By index examination, we can obtain knowledge about a region’s smart specialization status and potentials. Results reveal that, firstly, each sub-region has its own smart specialization characters with different risk profile. Secondly, specialization strategy (RRSI) in smart specialization has yielded more secure strategy than sub-regional resilience strategy in Finland. Sub-regions like Helsinki and Tampere have similar industrial structure like Finland as whole and they are resilient: they will benefit from nation-wide economic and industrial policy, and they have good ability to resist economic shocks. Our study reveals that there are some other similar smaller (LAU-1) sub-regions in Finland – like Rauma. As such, this kind of research based basic information is critical to been taken into account while constructing sustainable strategies for regional development. Similar calculations can be performed for all regions in Europe. DOI: http://dx.doi.org/10.5755/j01.eis.0.12.21872

Dynamics of the Entrepreneurial Sector in Territorial Systems with Tourist Functionality – Structural Trends and Changes

Abstract The entrepreneurial sector can play an important role in increasing the functional complexity of the territorial systems with tourist functionality, by increasing the capacity of adapting the local economy to the changes caused by the economic crises. The study aims to analyze the dynamics of the entrepreneurial sector, for the period 2000-2016, and to identify the changes in the entrepreneurial profile, in the territorial systems with tourist functionality from Romania. To quantify this dynamics, a database was created, at the territorial administrative unit level, with the main economic indicators (number of companies, number of employees, turnover and profit). The database was also used for the development of trend matrices on the evolution of the above indicators, at the four-digit NACE code (classification of activities in the national economy), and on the evolution of the ranks held by each economic sector for the analyzed period. The result highlight the importance of the entrepreneurial sector, in the dynamics of local and regional economies of the territorial systems with tourist functionality.

Using Information on Settlement Patterns to Improve the Spatial Distribution of Population in Coastal Impact Assessments

Broad-scale impact and vulnerability assessments are essential for informing decisions on long-term adaptation planning at the national, regional, or global level. These assessments rely on population data for quantifying exposure to different types of hazards. Existing population datasets covering the entire globe at resolutions of 2.5 degrees to 30 arc-seconds are based on information available at administrative-unit level and implicitly assume uniform population densities within these units. This assumption can lead to errors in impact assessments and particularly in coastal areas that are densely populated. This study proposes and compares simple approaches to regionalize population within administrative units in the German Baltic Sea region using solely information on urban extent from the Global Urban Footprint (GUF). Our results show that approaches using GUF can reduce the error in predicting population totals of municipalities by factor 2 to 3. When assessing exposed population, we find that the assumption of uniform population densities leads to an overestimation of 120% to 140%. Using GUF to regionalise population within administrative units reduce these errors by up to 50%. Our results suggest that the proposed simple modeling approaches can result in significantly improved distribution of population within administrative units and substantially improve the results of exposure analyses.

ASAP: A new global early warning system to detect anomaly hot spots of agricultural production for food security analysis

Monitoring crop and rangeland conditions is highly relevant for early warning and response planning in food insecure areas of the world. Satellite remote sensing can obtain relevant and timely information in such areas where ground data are scattered, non-homogenous, or frequently unavailable. Rainfall estimates provide an outlook of the drivers of vegetation growth, whereas time series of satellite-based biophysical indicators at high temporal resolution provide key information about vegetation status in near real-time and over large areas. The new early warning decision support system ASAP (Anomaly hot Spots of Agricultural Production) builds on the experience of the MARS crop monitoring activities for food insecure areas, that have started in the early 2000's and aims at providing timely information about possible crop production anomalies. The information made available on the website (https://mars.jrc.ec.europa.eu/asap/) directly supports multi-agency early warning initiatives such as for example the GEOGLAM Crop Monitor for Early Warning and provides inputs to more detailed food security assessments that are the basis for the annual Global Report on Food Crises. ASAP is a two-step analysis framework, with a first fully automated step classifying the first sub-national level administrative units into four agricultural production deficit warning categories. Warnings are based on rainfall and vegetation index anomalies computed over crop and rangeland areas and are updated every 10 days. They take into account the timing during the crop season at which they occur, using remote sensing derived phenology per-pixel. The second step involves the monthly analysis at country level by JRC crop monitoring experts of all the information available, including the automatic warnings, crop production and food security-tailored media analysis, high-resolution imagery (e.g. Landsat 8, Sentinel 1 and 2) processed in Google Earth Engine and ancillary maps, graphs and statistics derived from a set of indicators. Countries with potentially critical conditions are marked as minor or major hotspots and a global overview is provided together with short national level narratives.

Spatial analysis between particulate matter and emergency room visits for conjunctivitis and keratitis

BackgroundThe concentration of particulate matter in the air varies depending on the region because it is lightweight and generated from a variety of sources. To assess the relationship between particulate matter and eye disease, this study analyzes the concentration data obtained from spatial analysis of particulate matter and emergency visit data.MethodsThe study included 769 residents of Daegu, Korea who had visited an emergency room for the problem of conjunctivitis or keratitis. Concentrations of PM10 and other air pollutants were obtained from the Korean Ministry of the Environment. PM10 concentrations and the number of patients from each of 143 administrative dongs (sub-municipal level administrative units) of the city of Daegu were obtained using spatial analysis. The patient distribution and PM10 concentration were mapped for comparison, and their relationship was examined using scatter plot, regression analysis, and the independent sample t-test.ResultsThe number of patients with conjunctivitis and keratitis was significantly higher in the regions of the top 20% areas than the bottom 20% areas in terms of PM10 concentration. The distribution of PM10 concentration and number of patients was visually similar on the map. The concentration of PM10 and the number of patients showed a dose–response relationship. When the concentrations of other air polluta9nts were controlled for, the numbers of conjunctivitis and keratitis patients were 0.04 per 1000 ER patients and 0.10 per 1000 ER patients, respectively.ConclusionAs PM10 is associated with the prevalence of conjunctivitis and keratitis, measures to reduce particulate matter through environmental methods are needed.

High resolution age-structured mapping of childhood vaccination coverage in low and middle income countries

BackgroundThe expansion of childhood vaccination programs in low and middle income countries has been a substantial public health success story. Indicators of the performance of intervention programmes such as coverage levels and numbers covered are typically measured through national statistics or at the scale of large regions due to survey design, administrative convenience or operational limitations. These mask heterogeneities and ‘coldspots’ of low coverage that may allow diseases to persist, even if overall coverage is high. Hence, to decrease inequities and accelerate progress towards disease elimination goals, fine-scale variation in coverage should be better characterized. MethodsUsing measles as an example, cluster-level Demographic and Health Surveys (DHS) data were used to map vaccination coverage at 1 km spatial resolution in Cambodia, Mozambique and Nigeria for varying age-group categories of children under five years, using Bayesian geostatistical techniques built on a suite of publicly available geospatial covariates and implemented via Markov Chain Monte Carlo (MCMC) methods. ResultsMeasles vaccination coverage was found to be strongly predicted by just 4–5 covariates in geostatistical models, with remoteness consistently selected as a key variable. The output 1 × 1 km maps revealed significant heterogeneities within the three countries that were not captured using province-level summaries. Integration with population data showed that at the time of the surveys, few districts attained the 80% coverage, that is one component of the WHO Global Vaccine Action Plan 2020 targets. ConclusionThe elimination of vaccine-preventable diseases requires a strong evidence base to guide strategies and inform efficient use of limited resources. The approaches outlined here provide a route to moving beyond large area summaries of vaccination coverage that mask epidemiologically-important heterogeneities to detailed maps that capture subnational vulnerabilities. The output datasets are built on open data and methods, and in flexible format that can be aggregated to more operationally-relevant administrative unit levels.

Spatial variation of human cancer incidence across babylon state in (2010)

Cancer is an abnormal growth of the cells of the body, and may move from one place to another and lead to the growth and proliferation of irregular cells to form tumors are on the two types of tumor and benign tumor malignant, and there is no specific reason for the emergence of tumors and factors Environmental, genetic, economic, social, dietary habits such as smoking, drinking alcohol and drugs. The research aims to study cancer in the province of Babylon, one of the Iraqi provinces, the results showed a clear spatial disparity between the administrative units of the province, the rate of cases of cancer in all the province of Babylon in 2010 (43) Of the population, which is more than the rate of cases of infection across Iraq, amounting to (38) injuries per 100 thousand people. The study also showed a difference in the rates of infection according to the ten common types of cancer in Babil province comes on the list of these types is breast cancer, where the rate of infection (9.35) per 100000 population, which is one of the most dangerous types of cancer threat to the population, especially females. Lung cancer and bronchitis come in second place with a rate of (8.45) infections per 100000 population. Then leukemia comes in third place (5.47) per 100000 population. Pancreatic, gastric, and laryngeal cancers are among the lowest-risk cancers for the above-mentioned species (1.97–1.86–1.69), respectively. The level of administrative units, Hala recorded the highest rate of cases infected with the disease (56.18) per 100000 population. Followed by Musayyib (43.51), Mahawil (31.89), and Al-Hashimiah (27. 80).

Improving the sustainability of agricultural land use: An integrated framework for the conflict between food security and environmental deterioration

In rapidly developing countries, intensive agriculture faces the conflict between food security and environmental deterioration. To improve the sustainability of agricultural land use, this paper proposes an integrated framework for risk assessment and conflict coordination to cope with these salient challenges at the administrative unit level. This framework is demonstrated using a case study conducted in the Dongting Lake area in China. Drawing upon diverse sources of statistical data concerning agricultural inputs and outputs, water resources and natural hazards as well as questionnaire surveys conducted at the household level, this paper uses the Cobb-Douglas production function and the water environmental pressure index to assess food insecurity risk and environmental risk from food production, respectively. A double matrix method is used to characterize the degree of sustainability based on the risk assessment. The results indicate that the overall food security of the region can be maintained in the negligible-risk range. However, rising agro-environmental risks from grain production in the coming years are likely to threaten the sustainability of agricultural land use in most administrative units. It is suggested that optimization of land use patterns and mitigation of natural hazards could be effective approaches to improve the sustainability of local agricultural land use.