scholarly journals Geo-epidemiological reporting and spatial clustering of the 10 most prevalent cancers in Iran

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Ebrahim Babaee ◽  
Gholamreza Roshandel ◽  
Meysam Olfatifar ◽  
Arash Tehrani-Banihashemi ◽  
Arezou Ashaari ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Geographical Information Systems ◽  
Spatial Clustering ◽  
Incidence Rates ◽  
Geographical Information ◽  
Breast Cancers ◽  
Contributing Factors ◽  
Index Method ◽  
The North ◽  
Global And Local

Cancer is a problem of both global and local concern. We determined the geo-epidemiological and spatial distribution of the 10 most common cancers in Iran. We used the data of the Iranian Cancer Registry for the year 2014 analysing the prevalence of 112,131 registered cancer cases with the aim of detecting potential geographical underlying causes. The geographic distribution of cancers is reported as standardized incidence rates at the provincial level considering risk with respect to sex and age. A geographical information systems (GIS) approach based on Anselin Local Moran’s index method was used to map clusters and spatial autocorrelation patterns. The mean age of the patients was 55.6 (±17.8) and 61.7 (±18.2) for females and males, respectively, in the database which showed 46.1% (n=51,665) of all cases to be female. Analysis of the spatial distribution of cancers showed significant differences among the different provinces. Stomach and breast cancers were the most prevalent cancers in men and females, respectively. The highest incidence rates of stomach cancer were found in Ardabil and Zanjan provinces, with 48.38 and 48.08 per 100,000 population, respectively, while Tehran and Yazd provinces had the highest incidences of breast cancer, 51.0 and 47.5 per 100,000 population, respectively. Strong clustering patterns for stomach and breast cancers were identified in the north-western provinces and in Semnan Province, respectively. These patterns indicate a diversity of geo-epidemiological contributing factors to cancer incidence in Iran.

scholarly journals Spatial Distribution of Dengue in Honduras during 2016-2019 Using Geographic Information Systems (GIS) – Implications During Epidemic for Public Health and Travel Medicine

2019 ◽  
Author(s):  
Lysien I. Zambrano ◽  
Edith Rodriguez ◽  
Iván Alfonso Espinoza-Salvado ◽  
Itzel Carolina Fuentes-Barahona ◽  
Tales Lyra de Oliveira ◽  
...  
Keyword(s):  
Public Health ◽  
Information Systems ◽  
Incidence Rate ◽  
Geographical Information Systems ◽  
Travel Medicine ◽  
Epidemiological Data ◽  
Incidence Rates ◽  
Geographical Information ◽  
The North ◽  
Disease Characteristics

Background: After serious epidemics of chikungunya (CHIKV) and Zika (ZIKV) in the Americas, dengue (DENV) have reemerged in most countries. We analyzed the incidence, incidence rates, and evolution of DENV cases in Honduras from 2015-2018 and the ongoing 2019 epidemic. Methods: Using epidemiological weeks (EW) surveillance data on the DENV in Honduras, we estimated incidence rates (cases/100,000 population), and developed maps at national, departmental, and municipal levels. Results: From 1 January 2016 to 21 July 2019, a total of 109,557 cases of DENV were reported, 28,603 in 2019, for an incidence rate of 312.32 cases/100,000 pop this year; 0.13% laboratory-confirmed. The highest peak was reached on the EW 28°, 2019 (5,299 cases; 57.89 cases/100,000 pop). The department with the highest number of cases and incidence rate was Cortes (8,404 cases, 479.68 cases/100,000 pop in 2019). Discussion: The pattern and evolution of DENV epidemic in 2019 in Honduras has been similar to that which occurred for in 2015. As previously reported, this epidemic involved the north and central areas of the country predominantly, reaching municipality incidences there >1,000 cases/100,000 pop (1%). Studies using geographical information systems linked with clinical disease characteristics are necessary to attain accurate epidemiological data for public health systems. Such information is also useful for assessment of risk for travelers who visit specific areas in a destination country.

scholarly journals Numerical Modeling for Gully Erosion in the North of Algeria based on Data of Remote Sensing and Geographic Information Systems

2017 ◽  
Vol 25 (1) ◽  
pp. 37-63
Author(s):  
mohammad abbas daoudi mohammad abbas daoudi
Keyword(s):  
Remote Sensing ◽  
Multivariate Analysis ◽  
Information Systems ◽  
Geographical Information Systems ◽  
Univariate Analysis ◽  
Probabilistic Approach ◽  
Geographical Information ◽  
Rainfall Erosivity ◽  
Erosion Risk ◽  
The North

The problems of soil erosion are largely widespread in the countries of the Mediterranean basin. The process of gullying is a complex phenomenon with disastrous consequences. It particularly affects northern Algeria, decreasing the potentialities of the water tanks, reducing cultivable lands availability and degrading infrastructures. Therefore, this work studies the analysis and the prediction of gullying erosion by using a probabilistic approach based on multisource data. The objective of this search is to answer to the three following questions: i) which factors support the process of gullying ? ii) how does a process of gullying develop? iii) which are the zones favourable to gullying ? Works are undertaken on the catchment area of the Isser River. We focused the applications on the upstream part of the basin. In this research, we study a North-South transect which corresponds to three under-basins slopes. The choice of these tests areas answers to four criteria defined in our method: the representativeness, the homogeneity, the availability of former data and, finally, the accessibility. After the completion of the multisource data, modelling and multivariate analysis for the prediction of gullying. The combination factor-process by the univariate analysis allows on the one hand, to highlight the variables controlling the process of gullying, and on the other hand, to analyse the variables on a hierarchical basis and to know their degree of influence. The multivariate analysis, by the logistic regression model (LRM), enabled us to select the significant variables and to locate the most favourable zones for the process of gullying. The validation of the models is evaluated using the curves of lift spin. The results suggest that the factors highlighted by the model to be most influential on gullying erosion are: the lithology, the slope, the morphopedology, the rainfall erosivity and the land cover. The synthesis of this approach is illustrated in the form of charts of gullying erosion risk maps in four classes of probability. The assessment of the study shows the fundamental interest of this approach using geographical information systems and remote sensing, in particular for the watersheds of the southern Mediterranean, with the possibility of extending this methodology to other regions.

scholarly journals Spatial Analysis of Seasonal Precipitation Using Various Interpolation Methods in the Euphrates Basin, Turkey

2021 ◽  
Author(s):  
Okan Mert Katipoğlu
Keyword(s):  
Spatial Distribution ◽  
Geographical Information Systems ◽  
Polynomial Interpolation ◽  
Estimation Method ◽  
Summer Precipitation ◽  
Winter Precipitation ◽  
Geographical Information ◽  
Seasonal Precipitation ◽  
Interpolation Methods

Abstract It is vital to accurately map the spatial distribution of precipitation, which is widely used in many fields such as hydrology, climatology, meteorology, ecology, and agriculture. In this study, it was aimed to reveal the spatial distribution of seasonal long-term average precipitation in the Euphrates Basin by using various interpolation methods. For this reason, Simple Kriging (SK), Ordinary Kriging (OK), Universal Kriging (UK), Ordinary CoKriging (OCK), Empirical Bayesian Kriging (EBK), Radial Basis Functions (Completely Regularized Spline (CRS), Thin Plate Spline (TPS), Multiquadratic, Inverse Multiquadratic (IM), Spline with Tensor (ST)), Local Polynomial Interpolation (LPI), Global Polynomial Interpolation (GPI), Inverse Distance Weighting (IDW) methods have been applied in the Geographical Information Systems (GIS) environment. Long-term seasonal precipitation averages between 1966 and 2017 are presented as input for the prediction of precipitation maps. The accuracy of the precipitation prediction maps created was based on root mean square error (RMSE) values obtained from the cross-validation tests. The method of precipitation by interpolation yielding the lowest RMSE was selected as the most appropriate method. As a result of the study, OCK in spring and winter precipitation, LPI in summer precipitation, and OK in autumn precipitation were determined as the most appropriate estimation method.

Spatial analysis of notified dengue fever infections

2010 ◽  
Vol 139 (3) ◽  
pp. 391-399 ◽  
Author(s):  
W. HU ◽  
A. CLEMENTS ◽  
G. WILLIAMS ◽  
S. TONG
Keyword(s):  
Spatial Distribution ◽  
Empirical Bayes ◽  
Spatial Clustering ◽  
Spatial Association ◽  
Spatial Clusters ◽  
Logistic Regression Models ◽  
The North ◽  
High Incidence ◽  
Spatio Temporal ◽  
Low Incidence

SUMMARYThis study aimed to investigate the spatial clustering and dynamic dispersion of dengue incidence in Queensland, Australia. We used Moran'sIstatistic to assess the spatial autocorrelation of reported dengue cases. Spatial empirical Bayes smoothing estimates were used to display the spatial distribution of dengue in postal areas throughout Queensland. Local indicators of spatial association (LISA) maps and logistic regression models were used to identify spatial clusters and examine the spatio-temporal patterns of the spread of dengue. The results indicate that the spatial distribution of dengue was clustered during each of the three periods of 1993–1996, 1997–2000 and 2001–2004. The high-incidence clusters of dengue were primarily concentrated in the north of Queensland and low-incidence clusters occurred in the south-east of Queensland. The study concludes that the geographical range of notified dengue cases has significantly expanded in Queensland over recent years.

scholarly journals ANALYSIS OF LAND USE CHANGES AND THEIR INFLUENCE ON SOIL FEATURES. CASE STUDY: SECAȘ VILLAGE, TIMIȘ COUNTY (ROMANIA)

2019 ◽  
Vol 13 (2) ◽  
pp. 157-166
Author(s):  
Loredana Copăcean ◽  
Ionut Zisu ◽  
Valentina Mazăre ◽  
Luminiţa Cojocariu
Keyword(s):  
Land Use ◽  
Rural Communities ◽  
Geographical Information Systems ◽  
Agricultural Land ◽  
Scientific Information ◽  
Land Use Changes ◽  
Arable Land ◽  
Geographical Information ◽  
Soil Features ◽  
The North

The soil, regarded as a natural resource, but also as a determinant element of the living standards of rural communities, manly agricultural, may be influenced, directly and indirectly, by the modality of land organizing and use. Starting from this consideration, through this study, the spatial and temporal evolution of land use is being pursued, particularly that of forest areas and wooded grasslands. The goal is to notice the changes that have occurred over a 30-year period and the manner how these changes are reflected on the soil features. The researches presented in this paper have been taking place in the north-eastern hilly area of Timiş County, that area having entirely a rural character. For realizing this study satellite images, topographical and cadastral maps, from different time periods, national and international databases, data from specialty literature were used. To all these we should add direct observations in the field, topographic surveys and information collected from local authorities. The processing of cartographic materials and data and scientific information has been realized with Geographical Information Systems specific applications. The obtained result has been expressed in the form of thematic maps, in graphic form or as statistical analysis. At the level of the analyzed area, the obvious changes in the land use, registered over time, are caused by a number of factors, such as: the organization form, from communist to capitalist policies, leaving agricultural land as fallow ground, reduction in livestock, changing land use etc. All these changes have caused the extension of the wooded grasslands, reduction of arable land, installing inferior forest vegetation in qualitative and quantitative terms etc. As a result, the soil, one of the most important natural resources, is degraded qualitatively, underexploited, and on the other hand, its role as a direct and indirect food producer for local communities is significantly reduced.

scholarly journals Assessing Equity in the Accessibility to Urban Green Spaces According to Different Functional Levels

2020 ◽  
Vol 9 (5) ◽  
pp. 308 ◽  
Author(s):  
Edorta Iraegui ◽  
Gabriela Augusto ◽  
Pedro Cabral
Keyword(s):  
Urban Areas ◽  
Geographical Information Systems ◽  
Spatial Clustering ◽  
Spatial Association ◽  
The Elderly ◽  
Green Spaces ◽  
Geographical Information ◽  
Urban Green ◽  
Urban Green Spaces ◽  
The City

Accessibility of urban residents to different services and amenities is a growing concern for policy makers. Urban green spaces (UGS) provide services and benefits that are particularly important for people having less mobility, such as children, the elderly or the poor. Practical experience has led to the classification of UGS in hierarchic systems reflecting the type and degree of benefits and services or functions they provide to users, which vary, primarily with their size. It is therefore necessary to ensure equity in the spatial distribution of different classes of UGS in the urban areas. In this work, we explore a methodology based in geographical information systems (GIS) to assess equity of access by different population groups to UGS according to its functional levels in the City of Barcelona, Spain, using a spatial clustering method. Results did not support the existence of overall inequalities in the access to UGS by the different groups of the population. However, indicators of spatial association revealed insufficiencies concerning accessibility to nearby UGS by seniors, children and the less wealthy in some parts of the city. This methodology may be used to inform urban planners dealing with the provision of UGS in an equitable manner to different socioeconomic groups of the resident population.

scholarly journals Changes in the spatial pattern of net earnings: Evidence from Serbia

2015 ◽  
Vol 65 (3) ◽  
pp. 351-365 ◽  
Author(s):  
Uglješa Stankov ◽  
Vanja Dragićević
Keyword(s):  
Spatial Autocorrelation ◽  
Spatial Clustering ◽  
Hot Spot ◽  
Spatial Segregation ◽  
Cold Spot ◽  
Spatial Autocorrelation Analysis ◽  
Autocorrelation Analysis ◽  
The North ◽  
Spatial Changes ◽  
Global And Local

Spatial autocorrelation analysis is an important method that can reveal the structure and patterns of economic spatial variables. It can be used to identify not only global spatial patterns in the country, but also characteristic locations at micro levels. In this research, we used spatial autocorrelation methodologies, including Global Moran’s I and Local Getis—Ord Gi statistics to identify the intensity of the spatial clustering of municipalities in Serbia by the level of average monthly net earnings from 2001 to 2010. We identified and mapped local clusters (hot and cold spots) by the level of average monthly net earnings for the same period. The results show that overall spatial segregation between municipalities with high and low average monthly net earnings was predominantly increasing during the investigated period. Local statistics illustrated that overall spatial segregation followed a broad north—south divide, with a concentration of municipalities with high net earnings in the north of Serbia, and low net earnings in the south. Closer inspection showed that at the beginning of the study period, there were three statistically significant hot spots in the north. As time passed, only one highly clustered hot spot remained — the Belgrade region. One cold spot retained a relatively stable position in the country’s southeast. This research shows that spatial changes of net earnings can be successfully studied with respect to statistically significant global and local spatial associations in the variables using spatial autocorrelation analysis.

Spatial Variability in Fertility in Menoufia, Egypt, Assessed through the Application of Remote-Sensing and GIS Technologies

10.1068/a3286 ◽  
2000 ◽  
Vol 32 (4) ◽  
pp. 695-714 ◽  
Author(s):  
John R Weeks ◽  
M Saad Gadalla ◽  
Tarek Rashed ◽  
James Stanforth ◽  
Allan G Hill
Keyword(s):  
Rural Areas ◽  
Diffusion Of Innovations ◽  
Census Data ◽  
Spatial Clustering ◽  
Adult Women ◽  
Spatial Component ◽  
Gis Technologies ◽  
The North ◽  
Lower Fertility ◽  
Global And Local

Fertility in rural areas such as the Governorate of Menoufia in Egypt may be influenced both by spatial factors (including the diffusion of innovations) and by essentially nonspatial factors (such as the availability of education for women and the percentage of adult women who are currently married). The nonspatial variables are available directly from censuses but the spatial component requires an accurate location of the villages to which the census data refer and then appropriate decomposition of the data into spatial and nonspatial components. We use IRS satellite imagery to classify the built area in a rural governorate in Egypt and then assign village-level census data to the centroids of those polygons and incorporate the data into a GIS. We then employ measures of global and local spatial statistics to conclude that in 1976 the combination of female illiteracy, proportion married, and spatial clustering accounted for 39% of the variation in fertility in Menoufia. In 1986 those same factors explained 51% of the variation in fertility. In 1976 about one third and in 1986 about half of the explained variability was due to the spatial component (‘diffusion’) and the other half due to a combination of demographic characteristics. Furthermore, between 1976 and 1986 there was a clear north-to-south drift of fertility, with lower fertility being clustered in the north and higher fertility clustered in the south.

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