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 Spatio-temporal analysis of innovations diffusion in the agriculture

2020 ◽  
Vol 26 (3) ◽  
pp. 147-158
Author(s):  
Kirill Teslenok ◽  
Sergey Teslenok
Keyword(s):  
Russian Federation ◽  
Diffusion Of Innovations ◽  
Geographical Information Systems ◽  
Temporal Dynamics ◽  
Far East ◽  
Geographic Information ◽  
Geographical Information ◽  
Innovative Development ◽  
The Russian Federation ◽  
Spatio Temporal

The article presents the results of the analysis of the spatio-temporal variability of the processes of diffusion of innovations in the agricultural sector of the Russian Federation by subjects. The application of a group of traditional and mathematical methods in the research process is complemented by the widespread use of the capabilities of geoinformation technologies and, first of all, geoinformation-cartographic modeling. In the process of conducting research, the corresponding specialized GIS databases “Innovations in the Subjects of the Russian Federation” were designed and practically implemented in various software versions. Based on them, the construction and analysis of a complex of geographic information-cartographic models, differing in the degree of complexity, reflecting the innovative processes occurring in agriculture of all regions of the Russian Federation, was performed. Each of the series of obtained analytical base and resulting maps illustrates various aspects of the innovative development of agriculture and the diffusion of innovations at different time periods. The results of geographic information mapping and modeling were also presented in the form of animated maps and cartographic animations reflecting the features of the territorial distribution of innovations and the spatio-temporal dynamics of their diffusion. Spatio-temporal geographic information-cartographic analysis of the diffusion of innovations made it possible to identify some objective laws of this process. First of all, there was a marked movement of innovations in the agriculture of the Russian Federation in the space-time continuum in the direction from innovative nuclei and sub-nuclei to innovative sub-periphery and periphery, and from donor regions of agricultural innovations to recipient regions. Geographically, the diffusion of innovations in agriculture of the Russian Federation occurs mainly in the direction from the largest cities (at the same time being leading scientific and technical centers) and areas of intensive agriculture (primarily farming) to the regions of the east and north of the European part, Siberia and the Far East. The wide use of the capabilities of geographical information systems and geographic information technologies at all stages of the study allowed the formation of cartographic and attributive databases of the GIS “Innovations in the Subjects of the Russian Federation” according to the main indicators of the innovative development of the agricultural industry at the territorial level of the constituent entities of the Russian Federation. On their basis, a significant number of maps and geoinformation-cartographic models of territorial innovative agricultural systems of regional level, the processes of diffusion of innovations occurring in them were constructed and analyzed, and their main spatio-temporal patterns were revealed.

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.

scholarly journals Implementation of geographical information systems for the study of diseases caused by vector-borne arboviruses in Southeast Asia: A review based on the publication record

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Ajib Diptyanusa ◽  
Lutfan Lazuardi ◽  
Retnadi Heru Jatmiko
Keyword(s):  
Information Systems ◽  
Southeast Asia ◽  
Japanese Encephalitis ◽  
Disease Transmission ◽  
Geographical Information Systems ◽  
Temporal Dynamics ◽  
Geographical Information ◽  
Disease Manifestation ◽  
Research Activities ◽  
Vector Distribution

The spread of mosquito-borne diseases in Southeast Asia has dramatically increased in the latest decades. These infections include dengue, chikungunya and Japanese Encephalitis (JE), high-burden viruses sharing overlapping disease manifestation and vector distribution. The use of Geographical Information Systems (GIS) to monitor the dynamics of disease and vector distribution can assist in disease epidemic prediction and public health interventions, particularly in Southeast Asia where sustained high temperatures drive the epidemic spread of these mosquito-borne viruses. Due to lack of accurate data, the spatial and temporal dynamics of these mosquito-borne viral disease transmission countries are poorly understood, which has limited disease control effort. By following studies carried out on these three viruses across the region in a specific time period revealing general patterns of research activities and characteristics, this review finds the need to improve decision-support by disease mapping and management. The results presented, based on a publication search with respect to diseases due to arboviruses, specifically dengue, chikungunya and Japanese encephalitis, should improve opportunities for future studies on the implementation of GIS in the control of mosquito-borne viral diseases in Southeast Asia.

Describing Spatio-Temporal Phenomena for Environmental System Development

2012 ◽  
pp. 211-226
Author(s):  
André Miralles ◽  
François Pinet ◽  
Yvan Bédard
Keyword(s):  
Information Systems ◽  
Geographical Information Systems ◽  
System Development ◽  
Geographic Information ◽  
Information Modeling ◽  
Geographical Information ◽  
Environmental System ◽  
Temporal Properties ◽  
Spatio Temporal

This paper is composed of two parts dealing with the modeling of environmental phenomena. The first part presents the traditional ER and OO formalisms dedicated to geographic information modeling. These languages focus mainly on representing the spatial and temporal properties of this type of information. Many of these languages express these properties visually by using pictograms. After a quick historical presentation of the languages, the authors show the various types of spatiality and temporality usually encountered in these languages. Often qualified as primitive, some of these spatialities and temporalities are simple. Others, which are more complex, result from combinations of simple spatialities and simple temporalities. Still others are used in very specific situations encountered during the development of geographical information systems. These different spatialities and temporalities are presented via examples provided in the field of environmental dynamics.

Spatial Online Analytical Processing (SOLAP)

2011 ◽  
pp. 298-319 ◽  
Author(s):  
Yvan Bedard ◽  
Sonia Rivest ◽  
Marie-Josée Proulx
Keyword(s):  
Information Systems ◽  
Geographical Information Systems ◽  
Temporal Analysis ◽  
Point Of View ◽  
Geographical Information ◽  
Spatial Component ◽  
On Line ◽  
Street Address ◽  
Analytical Processing ◽  
Spatio Temporal

It is recognized that 80% of data have a spatial component (ex. street address, place name, geographic coordinates, map coordinates). Having the possibilities to display data on maps, to compare maps of different phenomena or epochs, and to combine maps with tables and statistical charts allows one to get more insights into spatial datasets. Furthermore, performing fast spatio-temporal analysis, interactively exploring the data by drilling on maps similarly to drilling on tables and charts, and easily synchronizing such operations among these views is nowadays required by more and more users. This can be done by combining Geographical Information Systems (GIS) with On-Line Analytical Processing (OLAP), paving the way to “SOLAP” (Spatial OLAP). The present chapter focuses on the spatial characteristics of SOLAP from a geomatics engineering point of view: concepts, architectures, tools and remaining challenges.

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.

scholarly journals Location-Based Social Network’s Data Analysis and Spatio-Temporal Modeling for the Mega City of Shanghai, China

2020 ◽  
Vol 9 (2) ◽  
pp. 76 ◽  
Author(s):  
Naimat Ullah Khan ◽  
Wanggen Wan ◽  
Shui Yu
Keyword(s):  
Spatial Analysis ◽  
Geographical Information Systems ◽  
Temporal Analysis ◽  
Geographical Information ◽  
Educational Institutions ◽  
Residential Areas ◽  
Temporal Modeling ◽  
Time Frequency ◽  
Usage Patterns ◽  
Spatio Temporal

The aim of the current study is to analyze and extract the useful patterns from Location-Based Social Network (LBSN) data in Shanghai, China, using different temporal and spatial analysis techniques, along with specific check-in venue categories. This article explores the applications of LBSN data by examining the association between time, frequency of check-ins, and venue classes, based on users’ check-in behavior and the city’s characteristics. The information regarding venue classes is created and categorized by using the nature of physical locations. We acquired the geo-location information from one of the most famous Chinese microblogs called Sina-Weibo (Weibo). The extracted data are translated into the Geographical Information Systems (GIS) format, and after analysis the results are presented in the form of statistical graphs, tables, and spatial heatmaps. SPSS is used for temporal analysis, and Kernel Density Estimation (KDE) is applied based on users’ check-ins with the help of ArcMap and OpenStreetMap for spatial analysis. The findings show various patterns, including more frequent use of LBSN while visiting entertainment and shopping locations, a substantial number of check-ins from educational institutions, and that the density extends to suburban areas mainly because of educational institutions and residential areas. Through analytical results, the usage patterns based on hours of the day, days of the week, and for an entire six months, including by gender, venue category, and frequency distribution of the classes, as well as check-in density all over Shanghai city, are thoroughly demonstrated.

scholarly journals GI-Technology

2011 ◽  
pp. 118-137
Author(s):  
Anja Wijffels ◽  
Jos Van Orshoven ◽  
Bart Muys ◽  
Dirk Cattrysse
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
Geographical Information Systems ◽  
Land Evaluation ◽  
Geographical Information ◽  
Temporal Database ◽  
Model Base ◽  
Land Use Allocation ◽  
Spatio Temporal ◽  
Automated Support

To deal with the complexity of land use allocation in a spatio-temporally variable context, a generic framework for automated support to multi-objective land use planning is proposed. The framework is rooted in the discipline of land evaluation which is considered a go-between between land resources survey and land use planning. It draws on own experiences and on lessons learnt from literature. It consists of five integrated and interoperable components. The core three ones, the spatio-temporal database, the engine for data query, transformation and analysis and the user interface are adopted from geographical information systems (GIS). A ‘knowledge and model base’ component adds capability for assessing land performance over time. Finally, a multicriteria decision analysis component allows for identifying optimal land units and optimal land use options. The framework’s applicability and the limitations of geographical information technology (GI-Technology) to generate spatio-temporal decision support systems (stDSS) are illustrated with two cases: one in data rich and one in data poor conditions.

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