scholarly journals Epidemiology and spatial distribution of Echinococcus granulosus in sheep and goats slaughtered in a hyperendemic European Mediterranean area

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Antonio Bosco ◽  
Leucio Camara Alves ◽  
Paola Cociancic ◽  
Alessandra Amadesi ◽  
Paola Pepe ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Echinococcus Granulosus ◽  
Interpolation Method ◽  
Mediterranean Area ◽  
Sensu Stricto ◽  
Kriging Interpolation ◽  
Sheep And Goats ◽  
Basilicata Region ◽  
Kriging Interpolation Method ◽  
Target Organs

Abstract Background Cystic echinococcosis (CE) is a worldwide parasitic zoonosis caused by the larval stage of Echinococcus granulosus sensu lato affecting livestock, particularly sheep and goats. However, often this parasitosis is underestimated. For this reason, this study aimed to evaluate the epidemiological features and spatial distribution of CE in sheep and goats slaughtered in a hyperendemic Mediterranean area. Methods A survey was conducted in the Basilicata region (southern Italy) from 2014 to 2019. A total of 1454 animals (1265 sheep and 189 goats) from 824 farms were examined for hydatid cyst detection by visual inspection, palpation and incision of target organs. All the CE cysts were counted and classified into five morphostructural types (unilocular, multiseptate, calcified, caseous and hyperlaminated). Molecular analysis was performed on 353 cysts. For spatial analysis, a kriging interpolation method was used to create risk maps, while clustering was assessed by Moran’s I test. Results CE prevalence of 72.2% (595/824) and 58.4% (849/1454) was observed at the farm and animal levels, respectively, with higher values in sheep (62.9%) than goats (28.0%). The liver and lungs were the most frequently infected organs in both sheep and goats. Most of recovered cysts were of the calcified and multiseptate morphotypes. All the isolates were identified as E. granulosus sensu stricto (genotypes G1–G3). Spatial distribution showed a moderate clustering of positive animals. Conclusion The findings of this study can be used to better understand the eco-epidemiology of echinococcosis and to improve CE surveillance and prevention programs in regions highly endemic for CE. Graphical abstract

scholarly journals Spatial Distribution and Epidemiology of Echinococcus Granulosus Infection in Sheep and Goats Slaughtered in a Hyperendemic European Mediterranean Area

2021 ◽  
Author(s):  
Antonio Bosco ◽  
Leucio Camara Alves ◽  
Paola Cociancic ◽  
Alessandra Amadesi ◽  
Paola Pepe ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Echinococcus Granulosus ◽  
Interpolation Method ◽  
Mediterranean Area ◽  
Sensu Stricto ◽  
Kriging Interpolation ◽  
Sheep And Goats ◽  
Basilicata Region ◽  
Kriging Interpolation Method ◽  
Target Organs

Abstract Background: Cystic echinococcosis (CE) is a parasitic zoonosis caused by the larval stage of Echinococcus granulosus, highly widespread in livestock, particularly sheep and goats. This study aimed to evaluate the spatial distribution of CE in sheep and goats slaughtered in a hyperendemic Mediterranean area.Methods: A survey was conducted in Basilicata region (southern Italy) from 2014 to 2019. A total of 1454 animals (1265 sheep and 189 goats) from 824 farms were examined for hydatid cysts detection by visual inspection, palpation and incision of target organs. All the CE cysts were counted and classified into five morphostructural types (unilocular, multisepted, calcified, caseous and hyperlaminated). The molecular analysis was performed on 50 cysts. For spatial analysis, kriging interpolation method was used to create risk maps, while the clustering was assessed by Moran’s I test.Results: CE prevalence of 72.2% (595/824) and 58.4% (849/1454) were observed at the farm and animal level, respectively, with higher values in sheep (62.9%) than goats (28.0%). The liver and lungs were the most frequently infected organs both in sheep and goats. Most of recovered cysts belonged to the calcified and multisepted morphotypes. All the isolates were identified as E. granulosus sensu stricto (genotypes G1-G3). Spatial distribution showed a moderate clustering of positive animals.Conclusions: The findings of this study can be used to better understand the eco-epidemiology of echinococcosis and to improve the CE surveillance and prevention programs in regions highly endemic for CE.

Three-Dimensional Spatial Simulation and Distribution Characteristics of Soil Organic Matter in Coal Mining Subsidence Area

2020 ◽  
Vol 980 ◽  
pp. 437-448
Author(s):  
Hui Juan Zhang ◽  
Shou Chen Ma ◽  
Wen Kai Liu ◽  
He Bing Zhang ◽  
Song He Yuan
Keyword(s):  
Organic Matter ◽  
Spatial Distribution ◽  
Soil Organic Matter ◽  
Stochastic Simulation ◽  
Interpolation Method ◽  
Soil Depth ◽  
Simulation Method ◽  
Kriging Interpolation ◽  
Kriging Interpolation Method ◽  
Middle Slope

Underground mining has caused drastic disturbances to regional ecosystems and soil nutrients. Understanding the 3D spatial distribution of soil organic matter in coal arable land is crucial for agricultural production and environmental management. However, little research has been done on the three-dimensional modeling of soil organic matter. In this study, 3D kriging interpolation method and 3D stochastic simulation method were used to develop the 3D model of soil organic matter , and the root-mean-square error (RMSE) and mean error (ME) were used as evaluation indexes to compare the simulation accuracy of the two methods. Results showed that the spatial distribution of soil organic matter obtained by using 3D kriging interpolation method is relatively smooth, which reduce the difference of spatial data; while the spatial distribution of soil organic matter obtained by using 3D stochastic simulation method is relatively discrete and highlights the volatility of spatial distribution of raw data, the RMSE obtained by 3D kriging interpolation method and 3D stochastic simulation method respectively is 2.7711 g/kg and 1.8369 g/kg. The prediction accuracy of organic matter interpolation obtained by 3D stochastic simulation method is higher than that by 3D kriging interpolation method; so the 3D stochastic simulation method can reflect the spatial distribution characteristics of soil organic matter more realistically, and more suitable for 3D modeling of soil organic matter. According to the 3D modeling of soil organic matter, the content of soil organic matter has obvious spatial difference in different soil depth（0-20 cm、20-40 cm、40-60 cm） and decreases with the increase of soil depth; The result also showed that the content of soil organic matter decreased rapidly from the upper slope to the middle slope, and gradually increased from the middle slope to the bottom, so the soil organic matter content was obviously lost in the middle slope. This result may provide useful data for land reclamation and ecological reconstruction in coal mining subsidence area.

scholarly journals The Association between the Mapping Distribution of Melioidosis Incidences and Meteorological Factors in an Endemic Area: Ubon Ratchathani, Thailand (2009–2018)

2021 ◽  
Vol 20 (4) ◽  
Author(s):  
Jaruwan Wongbutdee ◽  
◽  
Wacharapong Saengnill ◽  
Jutharat Jittimanee ◽  
Pawana Panomket ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Minimum Temperature ◽  
Meteorological Factors ◽  
Interpolation Method ◽  
Public Health Problem ◽  
Kriging Interpolation ◽  
Maximum Temperature ◽  
Tropical Regions ◽  
Kriging Interpolation Method ◽  
Average Rainfall

Abstract Melioidosis is a public health problem in the tropical regions, occurring to meteorological variability. For 10 years of melioidosis outbreaks, we create probability maps of melioidosis distribution during 2009–2018 and determine the association with meteorological factors. The monthly average rainfall and incidence of melioidosis were high from July to September but they not significantly associated (P = 0.576). However, the monthly maximum and minimum temperature were significantly associated with melioidosis incidence (P = 0.002 and P = 0.029, respectively). We estimated the spatial distribution of rainfall and maximum and minimum temperature using the Co-Kriging interpolation method which found that the spatial distribution of the melioidosis incidence was significantly associated with rainfall in 2009, 2010, and 2015; with the maximum temperature in 2009, 2010, 2011, 2013, and 2015; and with the minimum temperature in 2010, 2011, and 2015. Our finding approach may support information and classify a pattern for melioidosis distribution. Keywords: Incidence, Melioidosis, Meteorological factors

Spatial Distribution of Cutaneous Leishmaniasis Cases Referred to Health Centers of Three Khorasan Provinces in Iran Using Geographical Information System

2020 ◽  
Author(s):  
Mohammad Reza SHIRZADI ◽  
Mohammad JAVANBAKHT ◽  
Nahid JESRI ◽  
Abedin SAGHAFIPOUR
Keyword(s):  
Information System ◽  
Spatial Distribution ◽  
Spatial Analysis ◽  
Cutaneous Leishmaniasis ◽  
Hot Spots ◽  
Interpolation Method ◽  
Disease Incidence ◽  
Kriging Interpolation ◽  
Kriging Interpolation Method ◽  
Risk Areas

Background: Nowadays, geographic information system (GIS) is one of the most useful epidemiological tools for identifying high-risk areas of cutaneous leishmaniasis. The aim of this study was to determine the spatial distribution of cutaneous leishmaniasis in northeastern Iran. Methods: In this cross-sectional study, information on positive cases of cutaneous leishmaniasis in the three provinces located in northeastern Iran during Jul 2011 to Jul 2017 was obtained from the Iranian Ministry of Health. Based on the postal address of each case, the geographical coordinates of each patient were determined for spatial analysis of cutaneous leishmaniasis. For spatial analysis, Moran’s index autocorrelation and Kriging interpolation method were used in GIS software. Results: Moran’s index autocorrelation showed that spatial distribution of disease incidence in the study area was cluster pattern (Z-score > 1). In addition, Kriging interpolation method revealed that 90% of southern parts of North Khorasan province and northern parts of Razavi Khorasan Province formed hot spots. Conclusion: The CL incidence is a function of spatial and geographical trends. In addition, spatial trends in the disease incidence distribution indicate that it is not greatly increased or decreased from one area to another. It appears as hot spots areas. Spatial analysis by showing high risk areas can be useful tools for controlling and preventing CL incidence.

scholarly journals SPATIAL DISTRIBUTION OF BRACKISHWATER POND SOIL CHARACTERISTICS IN PEKALONGAN CITY CENTRAL JAVA PROVINCE

2011 ◽  
Vol 6 (1) ◽  
pp. 91
Author(s):  
Andi Indrajaya Asaad ◽  
Akhmad Mustafa
Keyword(s):  
Spatial Distribution ◽  
Soil Depth ◽  
Research Result ◽  
Soil Characteristics ◽  
Kriging Interpolation ◽  
Total N ◽  
Central Java ◽  
Kriging Interpolation Method ◽  
Brackishwater Pond ◽  
Central Java Province

Spatial distribution of brackishwater pond soil has a vital role in the system of bioenvironment including brackishwater pond environment. This research was aimed to determine the spatial distribution of brackishwater pond soil characteristics in Pekalongan City, Central Java Province. A total of 59 sampling points each with two different soil depth samplings were determined by simple random method. A total of 21 soil characteristics were measured in the field and analyzed further in the laboratory. Geostatistic with Kriging Interpolation method in the ArcGIS 9.3 software were used to depict the distribution of the data across the landscape. Furthermore, the spatial distribution was presented by using ALOS AVNIR-2 image. Research result indicates that in general, pond soil in Pekalongan City can be classified as soil with high variability or relatively heterogenic with the value of variation coefficient more than 36%. Soil characteristics which have similar pattern of spatial distribution are acid sulfate soil and soil nutrient content. High value of pH, organic matter, and total-N of soil, and on the other hand, low value of PO4 were generally found in the pond area of Krapyak Lor Village, while in Pekalongan City, it was found high clayish soil content but relatively homogenous. It is recommended that pond management must be based on soil characteristics which are different from one area to another. The soil characteristics itself can be drawn and assessed through spatial distribution.

Numerical Investigation of the Identifiability of Elastomer Mechanical Properties by Nano-Indentation and Shape-Manifold Approach

2021 ◽  
Author(s):  
Oumaima Ezzaamari ◽  
Guénhaël Le Quilliec ◽  
Florian Lacroix ◽  
Stéphane Méo
Keyword(s):  
Numerical Study ◽  
Interpolation Method ◽  
Structural Characteristics ◽  
Numerical Approach ◽  
Kriging Interpolation ◽  
Nano Indentation ◽  
Kriging Interpolation Method ◽  
Elastomeric Materials ◽  
Hyper Elastic ◽  
Characterization Test

ABSTRACT Various research is covering instrumented nano-indentation in the literature. However, studies on this characterization test remain limited when it comes to the local mechanical behavior of elastomeric materials. The application of nano-indentation on these materials is a difficult task given their complex mechanical and structural characteristics. We try to overcome these experimental limitations and find an effective numerical approach for local mechanical characterization of hyper-elastic materials. For such needs, we carried out a numerical study based on model reduction and shape manifold approach to investigate the parameters identification of different hyper-elastic constitutive laws by using instrumented indentation. Similarly, we studied the influence of the indenter geometry, the friction coefficient variation, and finally the indented material height effect. To this end, we constructed a reduced order model through a design of experiments by proper orthogonal decomposition combined with the kriging interpolation method.

Sign in / Sign up

Export Citation Format

Share Document