scholarly journals Environmental, climatic and host population risk factors of human cystic echinococcosis in southwest of Iran

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Mohammad Amin Ghatee ◽  
Koorosh Nikaein ◽  
Walter Robert Taylor ◽  
Mehdi Karamian ◽  
Hasan Alidadi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Environmental Factors ◽  
Cystic Echinococcosis ◽  
Geographical Information Systems ◽  
Urban Setting ◽  
Geographical Information ◽  
Annual Rainfall ◽  
Fars Province ◽  
Susceptible Population ◽  
Close Proximity

Abstract Background Cystic echinococcosis (CE), a worldwide zoonotic disease, is affected by various biological and environmental factors. We investigated dog/livestock populations, climatic and environmental factors influencing the distribution of human CE cases in Fars province, southwest Iran. Methods We mapped the addresses of 266 hospitalised CE patients (2004–2014) and studied the effects of different temperature models, mean annual rainfall and humidity, number of frosty days, slope, latitude, land covers, close proximity to nomads travel routes, livestock and dog densities on the occurrence of CE using geographical information systems approach. Data were analyzed by logistic regression. Results In the multivariate model predicting CE, living in an urban setting and densities of cattle and dogs were the most important CE predictors, sequentially. Dry (rained) farm, density of camel and sheep, close proximity to nomads travel routes, humidity, and slope also were considered as the determinants of CE distribution, when analyzed independently. Slope had a negative correlation with CE while temperature, frost days and latitude were not associated with CE. Conclusions In our study, an urban setting was the most important risk factor and likely due to a combination of the high density of key life cycle hosts, dogs and livestock, a large human susceptible population and the high number of abattoirs. Farmland and humidity were highly suggestive risk factors and these conditions support the increased survival of Echinococcus granulosus eggs in the soil. These findings support the development of strategies for control of disease. More research is needed test optimal interventions.

Effects of geographical and climatic factors on cystic echinococcosis in south-western Iran

2020 ◽  
Vol 94 ◽  
Author(s):  
A. Jamshidi ◽  
A. Haniloo ◽  
A. Fazaeli ◽  
M.A. Ghatee
Keyword(s):  
Land Cover ◽  
Cystic Echinococcosis ◽  
Geographical Information Systems ◽  
Climatic Factors ◽  
Weather Conditions ◽  
Climatic Conditions ◽  
Geographical Information ◽  
Annual Rainfall ◽  
Mean Annual Temperature ◽  
Western Iran

Abstract Cystic echinococcosis (CE) is caused by the larval form of Echinococcus granulosus that can cause serious health and economic problems in the endemic foci. CE is globally distributed in various climatic conditions from circumpolar to tropical latitudes. Iran is an important endemic area with a spectrum of weather conditions. The aim of this study was to determine the effects of geo-climatic factors on the distribution of livestock CE in south-western Iran (SWI) in 2016 to 2018. Data of livestock CE were retrieved from veterinary organizations of four provinces of SWI. The geo-climatic factors, including mean annual temperature (MAT), minimum MAT (MinMAT), maximum MAT (MaxMAT), mean annual rainfall (MAR), elevation, mean annual evaporation (MAE), sunny hours, wind speed, mean annual humidity (MAH), slope, frost days and land cover, were analysed using geographical information systems (GIS) approaches. The statistical analysis showed that MAR, frost days, elevation, slope and semi-condensed forest land cover were positively and MAE, MAT, MaxMAT, MinMAT and salt and salinity land cover were negatively correlated with CE occurrence. MAE was shown to be a predictive factor in the stepwise linear logistic regression model. In short, the current GIS-based study found that areas with lower evaporation were the main CE risk zones, though those with lower temperature and higher rainfall, altitude and slope, especially where covered with or in close proximity of semi-condensed forest, should be prioritized for consideration by health professionals and veterinarians for conducting control programmes in SWI.

scholarly journals Association between environmental risk factors and campylobacter infections in Sweden

2004 ◽  
Vol 132 (2) ◽  
pp. 317-325 ◽  
Author(s):  
K. NYGÅRD ◽  
Y. ANDERSSON ◽  
J. A. RØTTINGEN ◽  
Å. SVENSSON ◽  
J. LINDBÄCK ◽  
...  
Keyword(s):  
Risk Factors ◽  
Environmental Factors ◽  
Environmental Risk ◽  
Distribution System ◽  
Geographical Information Systems ◽  
Disease Incidence ◽  
Environmental Risk Factors ◽  
Geographical Information ◽  
Pipe Length ◽  
Campylobacter Infections

Campylobacter sp. is the most common cause of acute bacterial gastroenteritis in Sweden and the incidence has been increasing. Case-control studies to identify risk factors have been conducted in several countries, but much remains unexplained. The geographical distribution of campylobacter infections varies substantially, and many environmental factors may influence the observed pattern. Geographical Information Systems (GIS) offer an opportunity to use routinely available surveillance data to explore associations between potential environmental risk factors showing a geographical pattern and disease incidence, complementing traditional approaches for investigating risk factors for disease. We investigated associations between campylobacter incidence and environmental factors related to water and livestock in Sweden. Poisson regression was used to estimate the strength of the associations. Positive associations were found between campylobacter incidence and average water-pipe length per person, ruminant density, and a negative association with the percentage of the population receiving water from a public water supply. This indicates that drinking water and contamination from livestock may be important factors in explaining sporadic human campylobacteriosis in Sweden, and that contamination occurring in the water distribution system might be more important than previously considered.

scholarly journals A Geospatial database of gastric cancer patients and associated potential risk factors including lifestyle and air pollution

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Fatemeh Hashemi Amin ◽  
Mahtab Ghaemi ◽  
Sayyed Mostafa Mostafavi ◽  
Ladan Goshayeshi ◽  
Khadijeh Rezaei ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gastric Cancer ◽  
Cancer Patients ◽  
Spatial Data ◽  
Geographical Information Systems ◽  
Dietary Habits ◽  
Age Groups ◽  
Geographical Location ◽  
Geographical Information ◽  
Point Feature

Abstract Objectives Gastric cancer (GC) is a multifactorial disease and the fifth most frequent diagnosed cancer worldwide. It accounts for one third of cancer-related mortalities. Geospatial analysis using geographical information systems (GIS) can provide an efficient solution to identify spatial disparities associated with GC. As such, GIS enables policymakers to control cancer in a better way and identify the regions where interventions are needed. This study aims to publish a comprehensive dataset, which was applied to conduct a spatial analysis of GC patients in the city of Mashhad, Iran. Data description We provide a personal geodatabase, a Microsoft Access database that can store, query, and manage both spatial and non-spatial data, which contains four feature classes. “Male_Stomach_Cancer_Patients” and “Female_Stomach_Cancer_Patients” are point feature classes, which show the age and geographical location of 1156 GC cancer patients diagnosed between 2014 and 2017. “Air_Polution_Mashhad” is another point feature class that reveals the amount of six air pollutants, which was taken from Mashhad Environmental Pollutants Monitoring Center between 2017 and 2018. Finally, “Stomach_Cancer_and_Risk_Factors” is a polygon feature class of neighborhood division of Mashhad, consisting of contributor risk factors including dietary habits, smoking, alcohol use, body mass index and population by age groups for all 165 city neighborhoods.

scholarly journals Mapping, cluster detection and evaluation of risk factors of ovine toxoplasmosis in Southern Italy

2016 ◽  
Vol 11 (2) ◽  
Author(s):  
Roberto Condoleo ◽  
Vincenzo Musella ◽  
Maria Paola Maurelli ◽  
Antonio Bosco ◽  
Giuseppe Cringoli ◽  
...  
Keyword(s):  
Risk Factors ◽  
Geographical Information Systems ◽  
Southern Italy ◽  
Geographical Information ◽  
Economic Losses ◽  
Common Source ◽  
High Exposure ◽  
Campania Region ◽  
Source Of Infection ◽  
Serological Data

Toxoplasmosis, an important cause of reproductive failure in sheep, is responsible for significant economic losses to the ovine industry worldwide. Moreover, ovine meat contaminated by the parasite <em>Toxoplasma gondii</em> is considered as a common source of infection for humans. The aim of this study was to develop point and risk profiling maps of <em>T. gondii</em> seroprevalence in sheep bred in Campania Region (Southern Italy) and analyse risk factors associated at the flock-level. We used serological data from a previous survey of 117 sheep flocks, while environmental and farm management information were obtained from an analysis based on geographical information systems and a questionnaire purveyance, respectively. An univariate Poisson regression model revealed that the type of farm production (milk and meat vs only meat) was the only independent variable associated with <em>T. gondii</em> positivity (P&lt;0.02); the higher within-flock seroprevalence in milking herds suggests that milking practices might influence the spread of the infection on the farm. Neither environmental nor other management variables were significant. Since a majority of flocks were seasonally or permanently on pasture, the animals have a high exposure to infectious <em>T. gondii</em> oocysts, so the high within-flock seroprevalence might derive from this management factor. However, further studies are needed to better assess the actual epidemiological situation of toxoplasmosis in sheep and to clarify the factors that influence its presence and distribution.

Identification of key environmental variables associated with the presence of Toothed Leionema (Leionema bilobum serrulatum) in the Strzelecki Ranges, Victoria, Australia

2011 ◽  
Vol 59 (3) ◽  
pp. 207
Author(s):  
Wendy Wright ◽  
Xuan Zhu ◽  
Mateusz Okurowski
Keyword(s):  
Environmental Factors ◽  
Habitat Suitability ◽  
Rare Species ◽  
Environmental Variables ◽  
Geographical Information Systems ◽  
Predictive Modelling ◽  
Geographical Information ◽  
Suitable Habitat ◽  
Small Tree ◽  
Disturbed Areas

Toothed Leionema is one of four subspecies of Leionema bilobum from the Rutaceae family. A dense shrub or small tree, growing to ~4 m high, it is a poorly investigated species which is considered rare in Victoria, Australia. This paper presents the results of a study using Geographical Information Systems and Weights-of-Evidence predictive modelling to assess the importance of seven environmental factors in determining habitat suitability for this species in the Strzelecki Ranges, Victoria. This method is particularly useful in understanding the distribution of rare species, especially where the ecology of the species of interest is not well understood. Of the seven environmental factors considered here, four were found to be important: elevation, aspect, distance to water and distance to plantation (disturbed) areas. The modelling results indicate that areas with elevations between 350 and 550 m and a dominant south-western aspect that are close to plantation areas (within 700 m), and to water (within 1100–1200 m), provide potentially suitable habitat for Toothed Leionema in the region.

scholarly journals The Importance of Environmental Factors for the Development of Water Erosion of Soil in Agricultural Land: The Southern Part of Hronská Pahorkatina Hill Land, Slovakia

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1234
Author(s):  
Viera Petlušová ◽  
Peter Petluš ◽  
Michal Ševčík ◽  
Juraj Hreško
Keyword(s):  
Land Use ◽  
Environmental Factors ◽  
Geographical Information Systems ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Water Erosion ◽  
Geographical Information ◽  
Aerial Photographs ◽  
Slope Length ◽  
Erosion Processes

The water erosion research was carried out in the lowland type of hilly landscape. The aim was to monitor and evaluate the importance of environmental factors (steepness of slope, relief shapes, aspect, slope length, combination slope length (L) and slope (S)—LS factor, types of land use changes) for the development of water erosion. We focused on the identification of areas threatened by erosion by interpreting aerial photographs from several time periods. This was followed by verification of erosion using soil probes. We identified 408.44 ha of areas affected by erosion, and measured the depth of soil and “A” horizons thickness. The environmental factors were modeled in geographical information systems by tools for spatially oriented data. Subsequently, the influence and significance of individual environmental factors were compared, and the probability of erosion was statistically estimated. The decisive factors in the formation of erosive surfaces are the LS factor and the slope. We also consider the factor of the relief shape to be important. The shape did not appear to be very significant as a separately evaluated factor, but all convex parts correlate with the identified erosion surfaces. The susceptibility of erosion related to the aspect of the slopes to the cardinal directions has not been confirmed. Types of land use changes with the most significant relation of erosion were confirmed in areas of strong intensification. We confirmed the importance of factors and land use for the development of erosion processes.

scholarly journals Distance from Healthcare Facilities Is Associated with Increased Morbidity of Acute Infection in Pediatric Patients in Matiari, Pakistan

2021 ◽  
Vol 18 (21) ◽  
pp. 11691
Author(s):  
Elise Corden ◽  
Saman Hasan Siddiqui ◽  
Yash Sharma ◽  
Muhammad Faraz Raghib ◽  
William Adorno ◽  
...  
Keyword(s):  
Random Forest ◽  
Environmental Factors ◽  
Geographical Information Systems ◽  
Pearson Correlation ◽  
Acute Infection ◽  
Disease Prevalence ◽  
Geographical Information ◽  
Continuous Variables ◽  
Gis Technology ◽  
Healthcare Facilities

The relationship between environmental factors and child health is not well understood in rural Pakistan. This study characterized the environmental factors related to the morbidity of acute respiratory infections (ARIs), diarrhea, and growth using geographical information systems (GIS) technology. Anthropometric, address and disease prevalence data were collected through the SEEM (Study of Environmental Enteropathy and Malnutrition) study in Matiari, Pakistan. Publicly available map data were used to compile coordinates of healthcare facilities. A Pearson correlation coefficient (r) was used to calculate the correlation between distance from healthcare facilities and participant growth and morbidity. Other continuous variables influencing these outcomes were analyzed using a random forest regression model. In this study of 416 children, we found that participants living closer to secondary hospitals had a lower prevalence of ARI (r = 0.154, p < 0.010) and diarrhea (r = 0.228, p < 0.001) as well as participants living closer to Maternal Health Centers (MHCs): ARI (r = 0.185, p < 0.002) and diarrhea (r = 0.223, p < 0.001) compared to those living near primary facilities. Our random forest model showed that distance has high variable importance in the context of disease prevalence. Our results indicated that participants closer to more basic healthcare facilities reported a higher prevalence of both diarrhea and ARI than those near more urban facilities, highlighting potential public policy gaps in ameliorating rural health.

scholarly journals Diagnostic approaches to malaria in Zambia, 2009-2014

2015 ◽  
Vol 10 (1) ◽  
Author(s):  
Victor M. Mukonka ◽  
Emmanuel Chanda ◽  
Mulakwa Kamuliwo ◽  
Maha A. Elbadry ◽  
Pauline K. Wamulume ◽  
...  
Keyword(s):  
Risk Factors ◽  
Geographical Information Systems ◽  
Temporal Dynamics ◽  
Health Workers ◽  
Clinical Symptoms ◽  
Spatial Regression ◽  
Geographical Information ◽  
Diagnostic Tools ◽  
Control Center ◽  
Spatio Temporal

Malaria is an important health burden in Zambia with proper diagnosis remaining as one of the biggest challenges. The need for reliable diagnostics is being addressed through the introduction of rapid diagnostic tests (RDTs). However, without sufficient laboratory amenities in many parts of the country, diagnosis often still relies on non-specific, clinical symptoms. In this study, geographical information systems were used to both visualize and analyze the spatial distribution and the risk factors related to the diagnosis of malaria. The monthly reported, district-level number of malaria cases from January 2009 to December 2014 were collected from the National Malaria Control Center (NMCC). Spatial statistics were used to reveal cluster tendencies that were subsequently linked to possible risk factors, using a non-spatial regression model. Significant, spatio-temporal clusters of malaria were spotted while the introduction of RDTs made the number of clinically diagnosed malaria cases decrease by 33% from 2009 to 2014. The limited access to road network(s) was found to be associated with higher levels of malaria, which can be traced by the expansion of health promotion interventions by the NMCC, indicating enhanced diagnostic capability. The capacity of health facilities has been strengthened with the increased availability of proper diagnostic tools and through retraining of community health workers. To further enhance spatial decision support systems, a multifaceted approach is required to ensure mobilization and availability of human, infrastructural and technological resources. Surveillance based on standardized geospatial or other analytical methods should be used by program managers to design, target, monitor and assess the spatio-temporal dynamics of malaria diagnostic resources country-wide.

scholarly journals Using ordered weight averaging (OWA) for multicriteria soil fertility evaluation by GIS (case study: southeast Iran)

2016 ◽  
Author(s):  
Marzieh Mokarram ◽  
Majid Hojati
Keyword(s):  
Fuzzy Logic ◽  
Soil Fertility ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Weighted Averaging ◽  
Risk Level ◽  
Soil Parameters ◽  
Fars Province ◽  
Risk Levels ◽  
Distance Weighted

Abstract. The Multi-criteria Decision Analysis (MCDA) and the Geographical Information Systems (GIS) are used to provide more accurate decisions for decision makers in order to evaluate the effective factors of the natural science. One of the popular algorithms of the multi-criteria analysis is the Ordered Weighted Averaging (OWA). The OWA procedure depends on some parameters which can be specified by means of the fuzzy logic. The aim of this study is to take the advantage of incorporating the fuzzy logic into GIS-based soil fertility analysis by OWA in the west of Shiraz, Fars province, Iran. In fact, different soil fertility maps with different risk level are prepared in the present study. This study introduces a method for farmers in case of make balance between their budget and their farm soil parameters. A farmer can accept more risk it can use more areas for farming and also the amount of needed budget increases too. For determining the soil fertility maps, the OWA parameters such as potassium (K), phosphor (P), copper (Cu), iron (Fe), manganese (Mn), organic carbon (OC) and zinc (Zn) were used. After generating the interpolation maps with the Inverse Distance Weighted (IDW), the fuzzy maps were generated by the membership functions for each parameter. Finally, by utilizing OWA, six fertility maps with different risk levels (degrees of uncertainty) were made. The results show that by decreasing the risk (no trade-off), increasing the risk, more area within the study area was suitable in terms of the soil fertility. Therefore, using OWA can generate many maps with different risk levels. This leads to different managements based on different financial conditions of farmers.

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