Geospatial technologies and spatial data analysis: PART 2: Use of geographic information systems and spatial analysis in infectious disease surveillance in North America and East Africa

2013 ◽  
pp. 558-564
Author(s):  
Sunny Mak ◽  
Rebecca J. Eisen
2013 ◽  
Vol 4 (2) ◽  
pp. 54-70 ◽  
Author(s):  
Shaun A. Langley ◽  
Joseph P. Messina ◽  
Sue C. Grady

With the advent of Web 2.0, the public is becoming increasingly interested in spatial data exploration. The potential for Volunteered Geographic Information (VGI) to be adopted for passive disease surveillance and mediated through an enhanced relationship between researchers and non-scientists is of special interest to the authors. In particular, mobile devices and wireless communication permit the public to be more involved in research to a greater degree. Furthermore, the accuracy of these devices is rapidly improving, allowing the authors to address questions of uncertainty and error in data collections. Cooperation between researchers and the public integrates themes common to VGI and PGIS (Participatory Geographic Information), to bring about a new paradigm in GIScience. This paper outlines the prototype for a VGI system that incorporates the traditional role of researchers in spatial data analysis and exploration and the willingness of the public, through traditional PGIS, to be engaged in data collection for the purpose of surveillance of tsetse flies, the primary vector of African Trypanosomiasis. This system allows for two-way communication between researchers and the public for data collection, analysis, and the ultimate dissemination of results. Enhancing the role of the public to participate in these types of projects can improve both the efficacy of disease surveillance as well as stimulating greater interest in science.


2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Marcus Valerius Peixoto ◽  
Andrezza Marques Duque ◽  
Allan Dantas Santos ◽  
Shirley Verônica Almeida Melo Lima ◽  
Társilla Pereira Gonçalves ◽  
...  

Cerebral Palsy (CP) is commonly associated with low socioeconomic status. Use of spatial statistics and a Geographic Information Systems (GIS) are scarce and may contribute to the understanding of CP in a social context. To that end a spatial analysis of CP in children and adolescents was performed to analyze the association of CP with levels of vulnerability in a city (Aracaju, Sergipe) in north-eastern Brazil. In addition, an ecological study was conducted with data obtained from a populationbased survey and secondary data. Exploratory spatial data analysis and linear regression were used. A total of 288 CP cases were identified, with a prevalence of 1.65/1,000 and differences among city neighbourhoods ranging from 0-4/1,000. The mean age of cases studied was 9 years 1 month, with a standard deviation of 5 years 2 months. Most study subjects with cerebral palsy (163) were male (56.4%). The distribution of CP in the study population was not homogeneous throughout the territory. Some areas had clusters, with more cases associated with areas of high vulnerability. Spatial data analysis using GIS was useful to gain an epidemiological understanding of CP distribution that can guide decisionmaking with respect to production, distribution, and regulation of health goods as well as services at the local level.


2016 ◽  
Vol 10 (2) ◽  
Author(s):  
Ilyas Oz ◽  
Fatih Celebioglu

When examining the causes of migration in Turkey, it can be seen that low quality health and education services, imbalanced urbanization, security problem, high level unemployment rate have pivotal role on migration. In the 1950s Turkey, with intensified migration to big cities (mostly to West part of the country), urbanization process has accelerated. This process brought a number of problems with itself.Although many studies have been performed by researchers about migration in Turkey, there is no paper which includes spatial analysis. In this manner, this study purpose to examine the impacts of the factors as unemployment rate, Socio-economic Development Index on migration and their spatial analysis dimensions.To test spatial dimensions of the variables, we perform an exploratory spatial data analysis (ESDA) on migration and other variables among provinces of Turkey. While our choropleth maps indicate that the some part of the country is significantly more developed than the others, the tools of spatial statistics reveal the presence of spatial dependence across provinces. The presence of heterogeneity is reflected in the distribution of LISA statistics. Overall, our results shed new light on the distribution of migration and its relation with the others among provinces across Turkey.


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