Developing a data-driven spatial approach to assessment of neighbourhood influences on the spatial distribution of myocardial infarction

Abstract The aim of this analysis is to examine the characteristics of the Airbnb network, to verify the share of Airbnb offers that belong to the sharing economy and to identify the differences between the spatial distribution of the Airbnb network and the traditional hotel industry. The article is based on a unique dataset of web-scraped data on Airbnb listings in Warsaw (Poland), combined with district-level official statistics on the hotel industry. The analysis shows that only approximately 11% of offers belong to the sharing economy (“individuals granting each other temporary access to their under-utilised assets”), while at least one third of offers are provided by professional firms. The Airbnb network shows a strong centre-periphery pattern, with 75% of offers located within a range of 4.3 kilometres from the centre. The spatial concentration of Airbnb offers is strongly driven by their distance from metro lines, while it is weakly related to the amount of living space. On the district-level, the spatial distribution of Airbnb listings is correlated with that of the hotel industry, although Airbnb contributes to a more even spread of tourism in the city. The major contribution of this analysis is its presentation of the size and characteristics of the platform, which is essential for data-driven policy making.

Download Full-text

Modeling daily soil temperature using data-driven models and spatial distribution

Theoretical and Applied Climatology ◽

10.1007/s00704-013-1065-z ◽

2014 ◽

Vol 118 (3) ◽

pp. 465-479 ◽

Cited By ~ 41

Author(s):

Sungwon Kim ◽

Vijay P. Singh

Keyword(s):

Spatial Distribution ◽

Soil Temperature ◽

Data Driven ◽

Using Data

Download Full-text

Abstract 1680: Spatial Distribution of Myocardial Infarction in Patients with Diabetes Mellitus

Circulation ◽

10.1161/circ.116.suppl_16.ii_353 ◽

2007 ◽

Vol 116 (suppl_16) ◽

Author(s):

Pallav Garg ◽

Susana Candia ◽

John C Wang ◽

Richard E Kuntz ◽

Laura Mauri

Keyword(s):

Diabetes Mellitus ◽

Myocardial Infarction ◽

Spatial Distribution ◽

Coronary Artery ◽

Coronary Arteries ◽

Diabetic Patients ◽

Circumflex Artery ◽

Left Circumflex Artery ◽

Detection Technology ◽

Patients With Diabetes

BACKGROUND: Acute coronary occlusions occur most frequently as a result of rupture of an atherosclerotic plaque. Previous studies have found greater extent of atherosclerotic disease in the coronary arteries of diabetic patients. While the burden of disease is higher in diabetics, less is known about the spatial distribution of myocardial infarction in this population. METHODS: We sought to compare the spatial distribution of myocardial infarction (STEMI and Non-STEMI) in patients with diabetes mellitus and in those without, based on quantitative coronary and statistical analysis. We analyzed 756 patients with STEMI (n = 556) and NSTEMI (n=200), of which 175 patients comprised the diabetic cohort, and mapped the location of the acute coronary occlusion. RESULTS: Coronary occlusions were not uniformly distributed throughout each of the major epicardial coronary arteries but tended to cluster within the proximal third of each of the vessels in both cohorts. There was no difference in the distribution of occlusions in diabetics vs. non-diabetics in any of the vessels (left anterior descending artery, P=0.35; left circumflex artery; P=0.33 right coronary artery, P=0.20; Figure). CONCLUSIONS: Acute coronary occlusions leading to STEMI and NSTEMI in both diabetics and non-diabetics tend to cluster in predictable “hot spots” within the proximal third of the coronary arteries. Identification of these high-risk zones for acute coronary occlusions will lead to future advances in vulnerable plaque detection technology and potentially locally directed preventive strategies. Spatial distribution of myocardial infarction in diabetics vs. non-diabetics using distance to lesion from the ostium of the coronary artery.

Download Full-text