Fig 5 - uploaded by Lukas Marek
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Dot density map-dot distribution map based on the quadtree aggregation, each dot represents exactly one case of the salmonella. Left map is based on the quadtree with exactly one case in the leaf, while right map is based on the quadtree with at least 50 cases in the leaf.
Source publication
One of main aims of the spatial analysis of health and medical datasets is to provide additional information in the specialized medical research. These analyses can be used for disease mapping; searching for places with the higher intensity and probability of the disease occurrence; or the influence assessment of selected natural or artificial phen...
Context in source publication
Context 1
... are usually plotted randomly within boundaries of the areal unit. 5 shows two density dot maps, which are based on the quadtree aggregation. By this way it is possible to symbolize the spatial structure of the occurrence of the disease that is not burden by the presence of administrative units. ...
Citations
... The use of patient identifiers such and address could be used to identify patients and Point locations obtained from geocoding or GPS can be used in the same way (Waller and Gotway, 2004). This same data confidentiality is also the reason for the strain between the usefulness of the analysis in the local scale and the protection of the individual person privacy (Marek et al., 2013). For these reasons the volunteers' individual data are secured by the password and encrypting system which is only accessible by the research team. ...
The opportunity of an emerging smart city in post-disaster Christchurch has been explored as a way to improve the quality of life of people suffering Chronic Obstructive Pulmonary Disease (COPD), which is a progressive disease that affects respiratory function. It affects 1 in 15 New Zealanders and is the 4th largest cause of death, with significant costs to the health system. While, cigarette smoking is the leading cause of COPD, long-term exposure to other lung irritants, such as air pollution, chemical fumes, or dust can also cause and exacerbate it. Currently, we do know little what happens to the patients with COPD after they leave a doctor’s care. By learning more about patients’ movements in space and time, we can better understand the impacts of both the environment and personal mobility on the disease. This research is studying patients with COPD by using GPS-enabled smartphones, combined with the data about their spatiotemporal movements and information about their actual usage of medication in near real-time. We measure environmental data in the city, including air pollution, humidity and temperature and how this may subsequently be associated with COPD symptoms. In addition to the existing air quality monitoring network, to improve the spatial scale of our analysis, we deployed a series of low-cost Internet of Things (IoT) air quality sensors as well. The study demonstrates how health devices, smartphones and IoT sensors are becoming a part of a new health data ecosystem and how their usage could provide information about high-risk health hotspots, which, in the longer term, could lead to improvement in the quality of life for patients with COPD.
... The use of patient identifiers such and address could be used to identify patients and Point locations obtained from geocoding or GPS can be used in the same way (Waller and Gotway, 2004). This same data confidentiality is also the reason for the strain between the usefulness of the analysis in the local scale and the protection of the individual person privacy (Marek et al., 2013). For these reasons the volunteers' individual data are secured by the password and encrypting system which is only accessible by the research team. ...
The opportunity of an emerging smart city in post-disaster Christchurch has been explored as a way to improve the quality of life of people suffering Chronic Obstructive Pulmonary Disease (COPD), which is a progressive disease that affects respiratory function. It affects 1 in 15 New Zealanders and is the 4th largest cause of death, with significant costs to the health system. While, cigarette smoking is the leading cause of COPD, long-term exposure to other lung irritants, such as air pollution, chemical fumes, or dust can also cause and exacerbate it. Currently, we do know little what happens to the patients with COPD after they leave a doctor’s care. By learning more about patients’ movements in space and time, we can better understand the impacts of both the environment and personal mobility on the disease. This research is studying patients with COPD by using GPS-enabled smartphones, combined with the data about their spatiotemporal movements and information about their actual usage of medication in near real-time. We measure environmental data in the city, including air pollution, humidity and temperature and how this may subsequently be associated with COPD symptoms. In addition to the existing air quality monitoring network, to improve the spatial scale of our analysis, we deployed a series of low-cost Internet of Things (IoT) air quality sensors as well. The study demonstrates how health devices, smartphones and IoT sensors are becoming a part of a new health data ecosystem and how their usage could provide information about high-risk health hotspots, which, in the longer term, could lead to improvement in the quality of life for patients with COPD.
