Identification Of Risk Areas Research Articles

Identification of risk areas for visceral leishmaniasis in the Amazon Region

Identification of risk areas for visceral leishmaniasis in the Amazon Region

Prospects for the use of moisture-temperature UAV metrics to assess the state of land-use territories in planning and conducting spring field work

In the Central region of the Russian Federation, the favorable period for spring field work is short, but extremely important for obtaining the planned harvest. The possibility of tillage is mainly determined by its humidity after snowmelt. For the preparation and adjustment of plans for mechanized work, operational georeferenced information on the hydrological state of the soil in the land-use area is necessary, for which moisture-temperature UAV-metry can be used. Purpose – to evaluate the possibility of using the data obtained by multisensory UAV-s during the survey of agricultural landscapes to identify economically significant hydrological heterogeneity of territories. Agricultural landscapes in the Yuriev-Polsky district of the Vladimir region on gray forest loams and in the Shatura district of the Moscow region on sod-podzolic and podzolic sandy soils were examined. Their significant hydrological heterogeneity has been revealed, including local waterlogged areas with different causes of water stagnation. It is established that the dynamics of the hydrology of fields and the network of country roads are closely related. The use of UAV sensing data will help to eliminate the problem of difficult passage to the fields by carrying out appropriate measures and establishing the correct order of processing of land plots. To obtain the necessary information by agricultural enterprises, interdepartmental cooperation of the Ministry of Agriculture, the Ministry of Ecology, the Ministry of Forestry, AVTODOR, the Ministry of Emergency Situations, Energy Networks, as well as the use of the “Digital Earth system” is promising. The inclusion of moisture-temperature UAV-s in the production system – a plan for the preparation and conduct of spring field work, opens up new opportunities for their high-quality performance due to the timely identification of risk areas and appropriate adjustments. The priority object of the development application at the first stage should be considered roads – a key factor for rural areas.

Mapping pressures on biodiversity: the contribution of thematic detail to decision making

Mapping pressures to species is key to identify where biodiversity is at risk and providing relevant information to direct conservation actions. Decision-making to minimise pressures requires the determination of specific target actions at a high level of detail. However, the trade-off between cost and effort to generate this information often leads to the production of generalised pressure maps, named coarse maps, covering the most relevant pressures and their proxies. Here we aimed to disentangle whether the cost and effort of mapping fine pressures is worthwhile to inform decision making, by comparing how fine and coarse maps identify “where” and “how” management actions should be derived. Comparing the extend of both map types as well as its capacity to identify risk areas. We focused on three main pressures: agricultural intensification, human intensification, and land abandonment. The study was carried out in Catalonia for local decision-making, but the results can be applied in other EU regions or elsewhere, also for local decisions-making. We found that the Jaccard’s similarity index between coarse and fine pressure maps was always below 0.3 indicating low overlap between fine and coarse maps. In particular, the coincidence between coarse and fine thematic maps within protected areas (PAs) was always below 50%. Both maps differed in the identification of risk areas inside three analysed PAs. Moreover, even when there was a total geographical overlap between coarse and fine maps, coarse maps lack information on which concrete pressure was actually present, making decision on actions needed difficult. Thus, we can conclude that fine maps can estimate more accurately both “where” and “how” to target concrete actions than coarser maps. Even in cases where the answer as to “where” to act is the same, fine maps provide more concrete information to provide guidance on “how” to act. Consequently, despite the high cost and effort involved in mapping pressures at a high level of detail, the final trade-off is positive.

Government drivers of gastric cancer prevention: The identification of risk areas and macro factors in Gansu, China

The threat of gastric cancer remains significant worldwide, especially in Gansu, located in northwestern China. However, the spatiotemporal distribution characteristics and the impacts of macro factors such as social-economic, climatic conditions, and healthcare resources allocation were less reported before. Based on the data from the medical big data platform of the Gansu Province Health Commission, Gansu Province Bureau of Statistics and some public databases, we conducted joinpoint regression analysis, spatial autocorrelation analysis, trend surface analysis, space scanning analysis, geographically and temporally weighted regression (GTWR) analysis with Joinpoint_5.0, ArcGIS_10.8, GeoDa, and SaTScanTM_10.1.1. Finally, we have found that the increasing trend of gastric cancer incidence in Gansu has reached a turning point and is now declining. Moreover, significant spatial heterogeneity exists in the distribution of gastric cancer across Gansu Province. The identified risk areas and the impacts of macro factors on gastric cancer and their temporal trends could provide evidence for governments to develop specific policies for gastric cancer prevention.

A tale of 141 municipalities: the spatial distribution of dengue in Mato Grosso, Brazil.

In recent years, the state of Mato Grosso has presented one of the highest dengue incidence rates in Brazil. The meeting of the Amazon, Cerrado and Pantanal biomes results in a large variation of rainfall and temperature across different regions of the state. In addition, Mato Grosso has been undergoing intense urban growth since the 1970s, mainly due to the colonization of the Mid-North and North regions. We analyzed factors involved in dengue incidence in Mato Grosso from 2008 to 2019. The Moran Global Index was used to assess spatial autocorrelation of dengue incidence using explanatory variables such as temperature, precipitation, deforestation, population density and municipal development index. Areas at risk of dengue were grouped by the Local Moran Indicator. We noticed that areas at risk of dengue expanded from the Mid-North region to the North; the same pattern occurred from the Southeast to the Northeast; the South region remained at low-risk levels. The increase in incidence was influenced by precipitation, deforestation and the municipal development index. The identification of risk areas for dengue in space and time enables public health authorities to focus their control and prevention efforts, reducing infestation and the potential impact of dengue in the human population.

Identification of Risk Areas for Gloydius Snakebites in South Korea.

Snakebites can pose a significant threat to human health as the destruction of natural habitats and increased human intrusion into ecosystems result in more frequent encounters with snakes. Mitigation measures for snakebites are particularly crucial for hiking trails where transportation of snakebite victims to medical facilities is challenging due to limited emergency resources and difficult access. This study employed a random forest-based species distribution model approach to investigate the potential habitats of Gloydius spp., specifically Gloydius saxatilis, Gloydius brevicaudus, and Gloydius ussuriensis, in South Korea and to assess the snakebite risk in national parks. Potential habitats of Gloydius spp. were identified and visualized by overlaying binary maps derived from species distribution models (SDMs) of each Gloydius spp. that corresponded to high-risk snakebite areas. In addition, hiking trails with high snakebite risk in the national parks were identified after demonstrating the statistical correlation between the potential habitat distribution of Gloydius spp. and the actual snakebite incidents in major regions of South Korea. The primary environmental variables determining Gloydius spp. habitat were the topographic position index, slope, and the annual average of the maximum and minimum temperatures. The potential habitat of G. saxatilis generally appeared in high-altitude mountainous areas, mostly in the eastern part of the study area. Favorable habitats for G. brevicaudus and G. ussuriensis were predominantly located in mountainous areas throughout the study area, with the exception of some high-altitude mountainous terrain in the east. The number of snakebite incidents per 10,000 people was significantly correlated with the area ratio of Gloydius spp. potential habitat (Spearman's rho = 0.638, p < 0.01). The proportion of snakebite risk areas among national parks in South Korea ranged from 18% to 57%. This study can support practical solutions to prevent injuries and fatalities among hikers due to snakebites by identifying areas with a high risk of snakebite accidents at the hiking-trail level.

Identification of Risk Areas of Dengue Transmission in Culiacan, Mexico

Dengue is a public health problem in more than 100 countries around the world and in virtually the entire region of the Americas, including Mexico. Mosquitoes of the genus Aedes aegypti transmit dengue; its reproduction requires certain geographical, epidemiological, demographic and socioeconomic conditions. Detailed information on socioeconomic, epidemiological and entomological data is available, but detailed meteorological information is not. The objective of this study was to identify the areas of risk of dengue transmission for each month of the year based on environmental, social, entomological and epidemiological information from 2010 to 2020, in Culiacan, Mexico. LST, NDVI and NDMI were calculated from Landsat 8 satellite images with remote sensing techniques. Additional variables were human population density and overcrowding; mosquito egg density from positive ovitraps; and probable cases of dengue. A descriptive analysis of the study variables and a multiple linear regression analysis were performed to determine the significant variables. In addition, a multicriteria spatial analysis was applied through the AHP technique to identify areas at risk of dengue transmission. The results revealed that the variables NDVI, NDMI and overcrowding were not significant; however, the LST, population density, egg density per positive ovitrap and probable cases were. The highest population in the transmission risk areas was in November, and the highest transmission area was identified in October. In conclusion, it was possible to identify which of the study variables were significant; in addition, monthly maps of risk areas of dengue transmission for Culiacan were obtained. Each geographical area had its own characteristics that influenced, in one way or another, the incidence of dengue, highlighting that the strategies for control of dengue must be specific to each region.

МОДЕЛЮВАННЯ СИСТЕМИ ЕКОНОМІЧНИХ ВТРАТ ЗМЕНШЕННЯ БІЗНЕСУ В УМОВАХ СУЧАСНИХ ГЛОБАЛЬНИХ І ЛОКАЛЬНИХ ВИКЛИКІВ

The systemic and long-term impact of global and local challenges deepens the development of crisis phenomena in all spheres of public life and the national economy of Ukraine, covering production, social and labor, financial and other subsystems. Under such conditions, the problem of modeling the system of reducing the business risk losses, which would be oriented towards preventing crisis manifestations in financial and economic activity and painlessly overcoming negative consequences in order to ensure social and economic development, becomes relevant. The purpose of the article is to model the system of economic losses reducing of business in the conditions of permanent of modern global and local challenges. The object of the research is the economic losses reduction of business that arise as a result of global and local challenges. Methods used in the study: methods of scientific knowledge, namely analysis and synthesis, induction, measurement, observation, formalization, logical-analytical techniques, as well as the methodological apparatus of financial analysis and mathematical statistics. The main hypothesis of the study is the researching that the economic losses reduction of business should be based on methods, which will make it possible to correctly identify probable risks and to develop an effective system for overcoming their negative consequences in a timely manner. Presenting main material. The study analyzed the results of global and local challenges to the activities of business in Ukraine, namely social and behavioral restrictions caused by the global outbreak of the COVID-19 pandemic. In order to prevent the negative impact of uncertainty factors, the authors have developed a conceptual approach to modeling the system of economic losses reducing of business in the conditions of modern global and local challenges. The basic stages of building a system of economic losses leveling have been determined, namely: identification of risks of the business' functioning; survival function construction in the conditions of the crisis phenomena spread; evaluation of the risk situation occurrence probability (experience curve); development of a profile of economic losses limitation; construction of Shewhart's control charts; identification of risk areas; development of a profile of the economic entity's response to crisis phenomena (risk leveling). The originality and practical significance of the research lies in the fact that the developed conceptual scheme for modeling the economic loss reduction system can be used and specified in the management of systemic risks, development a profile of responses and a financial restrictions complex of business in the conditions of global and local challenges. Conclusions and prospects for further research: the need to form an individual complex modeling vector of the economic loss leveling system has substantiated. It will enable business to significantly reduce their level in the conditions of permanent global and local challenges in accordance with the methodological tools, the determinants of which should be economic and mathematical methods

Automatic Processing for Identification of Forest Fire Risk Areas along High-Voltage Power Lines Using Coarse-to-Fine LiDAR Data

This work focuses on the automatic identification of forest fire risk areas along high-voltage power lines through the development of a tool and its validation on a real forest area. The tool allows one to automate the whole process, which includes the classification of the point cloud, the computation of the catenary of the wires using different calculation methods, the estimation of the vegetation growth and the identification of the risk areas. To this end, a coarse-to-fine approach is proposed, so that a preliminary analysis is performed with public airborne LiDAR data, and then a more detailed inspection is provided with drone LiDAR data over those areas classified as high risk. The tool and the methodology developed were validated along a high-voltage power line of 53 km in a real forest area. The results show that although the preliminary analysis based on public airborne LiDAR data is more conservative, it is very useful for selecting those areas of higher risk for further analysis with drone LiDAR data.

Identification of potentially contaminated areas of soil microplastic based on machine learning: A case study in Taihu Lake region, China

Soil microplastic (MP) pollution has recently become increasingly aggravated, with severe consequences being generated. Understanding the spatial distribution characteristics of soil MPs is an important prerequisite for protecting and controlling soil pollution. However, determining the spatial distribution of soil MPs through a large number of soil field sampling and laboratory test analyses is unrealistic. In this study, we compared the accuracy and applicability of different machine learning models for predicting the spatial distribution of soil MPs. The support vector machine regression model with radial basis function (RBF) as kernel function (SVR–RBF) has a high prediction accuracy (R2 = 0.8934). Among the six ensemble models, random forest (R2 = 0.9007) could better explain the significance of source and sink factors affecting the occurrence of soil MPs. Soil texture, population density, and MPs point of interest (MPs–POI) were the main source-sink factors affecting the occurrence of soil MPs. Furthermore, the accumulation of MPs in soil was significantly affected by human activity. The spatial distribution map of soil MP pollution in the study area was drawn based on the bivariate local Moran's I model of soil MP pollution and the normalized difference vegetation index (NDVI) variation trend. A total of 48.74 km2 of soil was in an area of serious MP pollution, mainly concentrated in urban soil. This study provides a hybrid framework that includes spatial distribution prediction of MPs, source-sink analysis, and pollution risk area identification, providing scientific and systematic methods and techniques for pollution management in other soil environments.

The impact of wildfire on property prices: An analysis of the 2015 Sampson Flat Bushfire in South Australia

This research investigates the impact of wildfire occurrence on the price of properties subject to wildfire risk. This is relevant considering anthropogenic climate change is increasing wildfire frequency, size, and severity and the expansion of wildland-urban interface is exposing more people to the costs associated with fires. The study addresses the methodological limitations of prior research by exploiting the difference-in-differences method and a comprehensive dataset comprising transaction data, location and neighbourhood amenity elements, and spatial data on wildfire risk area identification to analyse the impact of the 2015 Sampson Flat Bushfire on housing price differences between the designated Bushfire Prone Area (BPA) and non-BPA within the City of Mitcham in South Australia. The results show that houses in the BPA (i.e., facing bushfire risk) are sold at a 4.96 % discount compared to those within the non-BPA (i.e., not facing bushfire risk) after the fire, suggesting that wildfire risk perception significantly rises following the disaster. Based on a dynamic analysis, houses in BPAs experience an immediate discount of 4.55 % compared to non-BPAs in the first six months following the fire, and this effect continues for at least two years afterward. Most interestingly, a heterogeneity analysis unique to this paper shows that houses within the Medium-Risk BPA are more negatively impacted than those in the High-Risk BPA.

A combined method for human health risk area identification of heavy metals in urban environments

Multi-medium heavy metals pollution is a crucial pathway to destroy the urban environmental resources cycle. In this study, Nanjing of China, a typical mega city, was taken as the study area. Compared with other cities or countries, Cr, Cu and Zn in human nails and hair in the study area have higher concentration characteristics, while Cd and Pb have lower concentration characteristics. By combining the health risk status of heavy metals in soil and dustfall, the spatial clustering characteristics of heavy metals in soil dustfall and the concentration information of heavy metals in humans in the study area, a potential toxic risk area identification method based on soil-dustfall-human (SDB-HR) was established. Through Monte Carlo analysis, it’s found that the risk of Zn and Cr in soil-dustfall to human health is relatively high, with the probability of carcinogenesis reaching 51.2 % and 50.2 %, respectively. By the proposed method, different levels of heavy metal risk areas in urban environments can be more reasonably and effectively identified, which will provide important technical and theoretical support for the precise management of heavy metals in urban environments.

Flood Hazard and Risk Area Identification: A Case of Gelana River Watershed, Southern Ethiopia

Floods are among the most devastating natural disasters in the world, claiming more lives and causing more damage to properties than any other natural phenomena. This study specifies flood hazard areas as well as flood risk areas of Gelana River Watershed. It specifically aims to investigate factors that create good conditions for flood hazard, generate flood hazard and risk areas from environmental and socio-economic factors using integration of Multi-Criteria Evaluation (MCE) and Geospatial Techniques. The research was conducted using quantitative research approach. Therefore, slope, elevation, soil type, land use land cover (LULC), and drainage density were the environmental factors developed for the generation of flood hazard. In addition, flood hazard, LULC and population data factors were developed to generate flood risk areas of Gelana river watershed. As the result, flood hazard map reveals 64.68, 1769.48, 1345.38, 244.37, 10.73 square kilometers of Gelana river watershed, is subjected to very high, high, moderate, low and very low flood hazardous respectively. It is revealed that 46.52% of the watershed has very high to high flood risk. The rest 47.20%, 6.24%, and 0.05% of the study area has medium, low and very low flood risk respectively. Therefore, the area incorporated under very high and high hazardous and risk areas are located around the Main River and lower course of the watershed.

Identification of risk areas for arboviruses transmitted by Aedes aegypti in northern Brazil: A One Health analysis

IntroductionThe complex and growing problem generated by the rapid expansion of unplanned urban areas includes high population density and increased infestation by vectors responsible for the transmission of several diseases. This requires interdisciplinary and intersectoral interventions due to the burden of diseases, especially those caused by arboviruses, which can present severe forms and generate significant pressure on health systems, especially in more vulnerable regions. The objective of this study was to analyze the spatial distribution of arboviruses transmitted by Aedes aegypti (dengue, Zika, and chikungunya) and assess their correlations with demographic, social, and environmental data from the state of Tocantins, Brazil. MethodsThis was an ecological time series study of the dengue, Zika, and chikungunya arboviruses in the state of Tocantins. Local Moran's indices were used to observe the spatial autocorrelation of cases and to delimit clusters of high and low risks, correlating them with socioenvironmental indicators, in addition to analyses to detect case clusters. ResultsThe state reported a mean incidence of 591 annual cases of arbovirus infections per 100,000 inhabitants and a stationary trend with seasonal pattern. Female Pardo individuals aged 20–39 years, with an education level of below college education, were the most affected; Palmas and Araguaína, the two largest cities in the state in terms of economy and population, were the most affected. ConclusionA better understanding of the interaction between social characteristics, the environment, and ecology of wild animals and vectors is important for the development of mechanisms to predict outbreaks as well as to develop strategies to reduce and/or mitigate recurring arboviral epidemics and other diseases.

FEATURES OF ENSURING TRANSPARENT AND EFFICIENT BUDGETARY FUNDING OF EDUCATION UNDER THE MARTIAL LAW

The article addresses current issues related to ensuring transparency and efficiency of budget financing in the education sector under martial law. The authors analyze approaches to ensuring monitoring and transparency in the use of budget funds, which is particularly important during times when Ukraine is facing challenging circumstances, and the issue of rational allocation of available financial resources becomes critical. The article provides an overview of the amount of budgetary funding for education in Ukraine, which has been reduced since the beginning of russia's large-scale war against Ukraine. It is substantiated that one of the ways to address above-mentioned issues is to ensure transparency and effectiveness in budget financing of education by implementing additional financial control measures, primarily by the Ministry of Education and Science of Ukraine. Furthermore, the authors propose the development of relevant performance indicators for educational institutions with a corresponding correlation to the allocated budget financing. At present, the Ministry of Education and Science of Ukraine's control over the designated and efficient use of targeted subventions at the local level has a number of shortcomings: insufficient methodological quality of data in relevant reports, lack of internal automatic data integrity controls, violation of reporting deadlines by respondents, outdated approach of sending out Excel templates for forms and collecting them on the e-mails of authorized specialists, etc. Insufficient use of modern tools for reporting, and consequently, ineffective control over the allocation and use of targeted funding from the state budget by budget managers, limits the effectiveness of managerial decision-making, creates a constant systemic risk of deteriorating education development at the local level. It is necessary to introduce financial reporting for each educational institution, which will allow for an appropriate analysis of the effectiveness of budget spending. In turn, the process of collecting, processing and disseminating such financial statements of educational institutions requires appropriate automation. Automation of the process will enable the quick and efficient processing of reports and the identification of risk areas. In particular, it is advisable to create an information and analytical system for collecting and analyzing financial reports of educational institutions to provide conditions for making management decisions based on reliable and evidence-based data.

Ризик-орієнтований підхід – основа виявлення та запобігання загрозі економічній безпеці держави

Today, in the conditions of martial law in Ukraine and of the deficit of the State budget, the issue of ensuring the economic security of the State as a component of national security is the highest priority and of big importance. Ensuring the economic security of the country is the prerogative of the State, and it should be supported by the entire system of the State bodies, especially law enforcement ones, among which the Economic Security Bureau of Ukraine (ESBU) plays a key role. In order to identify risks that weaken the economic security of the State, the ESBU uses a risk-oriented approach in its work, which is an identifier of the risks of committing criminal offenses in the budgetary, tax, customs, monetary, and investment spheres of the economy. Also, based on the results of the risk assessment, the ESBU develops and implements measures aimed at minimizing or eliminating them. Therefore, taking into account the external and internal threats to the country’s economy, the issue of applying a risk-oriented approach to identify the risks of committing criminal offenses in the field of economics is relevant, needs to be researched and remains a priority for both business and the State as a whole. The objectives of the study are: analysis of the results of the ESBU’s activities; disclosure of the procedure for the introduction and use of a risk-oriented approach in the work of the ESBU units; determination of the feasibility and benefits of using this approach in order to identify the risk of committing criminal offenses in the field of economy and prevent threats that affect the economic security of the State. The place, role and main tasks of the ESBU are considered: identification of risk areas in the field of economy; protection of public finances of the State; assessment of risks and threats to the economic security of the State; development of ways to minimize and eliminate them. It is determined that the most effective in the work of the ESBU analytical units is a risk-oriented approach, which makes it possible to predict threats and promptly take measures to prevent and/or counteract them. An analysis of the risks identified by the ESBU in the field of economy is carried out. It is found that the tax and customs spheres are the most risky for the country’s economy, since they account for almost 2/3 of all identified risks (72%). The necessity and expediency of using a risk-oriented approach in the work of the ESBU is substantiated, taking into account the requirements of the time and international experience. A model for managing risks of economic security of the State using a risk-oriented approach has been proposed. It is proved that today, in the conditions of war, there is a threat to the economic security of the State, and the key role in the protection of the latter is assigned to the ESBU.

A top-down approach for a multi-scale identification of risk areas in infrastructures: particularization in a case study on road safety

IntroductionTransport infrastructures have an important function in society and the development of a country. In Spain, the most used modes of traveler transport are road and rail, far ahead of other means of transport such as air or maritime transport. Both rail and road infrastructures can be affected by numerous hazards, endangering their performance and the safety of users. This study proposes a methodology with a multiscale top-down approach to identify the areas affected by fire, landslide, and safety in road and rail infrastructures in Galicia (Northwest Spain).MethodologyThe methodology is developed in three steps, coinciding with the three scales considered in this work: network-, system-, and object-level. In the first step, risk areas are identified and prioritized, resulting in the most critical safety risk in a motorway section. This area defines a study scenario composed of a location (A-55 motorway) and the associated risk (road safety). In the second step, the road safety factors within this scenario are selected, hierarchized, and weighted using a combination of Multi-Criteria Decision-Making methods including the Analytical Hierarchy Process and the Best–Worst Method. Finally, a risk map is generated based on the weighting of infrastructure-related safety factors and compared to real historical accident data for validation. The methodology is based on road and risk assessment standards and only information in the public domain is used.ResultsResults show that only 3 segments out of 153 were classified incorrectly, which supports a probability higher than 95% of agreement with real data (at 5% significance level). In a conclusion, the overall methodology exhibits a high potential for hazard prevention and road-safety enhancement.

A new method for identifying potential hazardous areas of heavy metal pollution in sediments

The combined effect of pollution source discharge and sediment adsorption leads to the rapid enrichment of heavy metals and other pollutants in lake sediments, which poses a serious threat to the lake ecosystem. Accurately identifying the risk areas of heavy metals in sediments is the key to lake sediment pollution control. Taking Taihu Lake as the study area, combined with the ecological risk status of heavy metals in sediments, the spatial clustering characteristics of pollution sources and the clustering information of sediment attributes, a potential toxic risk area identification method based on sediment source aggregation class (SLISA-SCA) was established. Through the source analysis of heavy metals in sediments, heavy metals such as Cr, Mn, Cu and Zn in Taihu Lake sediments were identified to have originated from natural sources and were subsequently disturbed by human activities to a certain extent. Cd was found to be strongly affected by human activities, and almost all Taihu Lake sediments were affected to varying degrees. In addition, the anthropogenic sources of heavy metals show high concentration clustering characteristics in the lake bay. By K-means cluster analysis of sediment attributes, three significant differences were obtained, which were determined as potential high pollution risk areas, potential medium risk areas and potential low risk areas, and the proportions were 5.6%, 27.6% and 66.8%, respectively. The SLISA-SCA model established in this study, from the perspective of source sinks, comprehensively considers the risks caused by pollution sources and sediment attributes to sediments and divides Taihu Lake into five different risk control areas (high-risk control area, potential high-risk control area, potential risk control area, potential low-risk control area and low-risk control area). This study identified areas with different levels of heavy metal pollution in Taihu Lake sediments, proposes corresponding treatment measures, and provides a scientific and systematic method and technology for the pollution management of other river and lake sediments in the world.

Cryptococcosis: Identification of Risk Areas in the Brazilian Amazon.

The Brazilian Amazon has a specific epidemiological profile for cryptococcosis, considering its social and economic inequality, health reality, and low access to health services. Furthermore, Brazil and Colombia have the highest cryptococcosis incidence rates in Latin America. In this study, we identified the areas of risk for cryptococcosis in the state of Pará in the Brazilian Amazon. This was an ecological study of patients admitted to a referral hospital from 2008 to 2018, aged 13 years or older, and of both sexes. The spatial distribution was determined using ArcGis 10.3.1 software. Cryptococcosis was confirmed in 272 cases. The incidence rate was 3.41 cases/100,000 inhabitants. Spatial distribution was concentrated in the Metropolitana de Belém, Nordeste Paraense, and Marajó mesoregions. The sociodemographic profile consisted of 62% men, aged between 24 and 34 years (36%), without completed secondary education (64.7%), and with occupations varying between agricultural activities (13.8%) and household activities (22%). The mean hospitalization time was 39 days; the prevalent clinical form was neurological (89.7%). The mortality rate among patients with cryptococcosis was up to 40%. Knowledge of the real magnitude of the disease in the Brazilian Amazon makes it possible to identify areas with the greatest risks and to propose control and epidemiological surveillance programs.

Identification of risk areas of malnutrition among school children (0-14 years) in Gujars community of Great Kashmir Himalayas

The present research work was carried out on the identification of Risk Areas of malnutrition among school children (0-14 years) in the Gujjars community of Great Kashmir Himalayas. Nutrition intake was examined in comparison to ICMR recommended dietary allowances (RDA). The weight of all sample children was measured and compared with ICMR (Indian Council for Medical Research) standard and then categorized into different nutritional grades. Data regarding the prevalence of nutrition deficiency diseases were also obtained during the field survey. The composite index method was employed for the categorization of sample villages in risk areas. The investigation reveals that variation in the availability of nutrients in the diet has badly affected the health of school children and leads to malnutrition. Grades of malnutrition vary with altitude and the majority of sample villages of higher altitudinal zones of E and F were areas of I and II category of risk and thus are areas of very high and high priority. Suggestions have been made for the improvement of the nutrition status of children from 0-14 age group in the risk areas