Abstract
Lung cancer is still at the top of the list of commonly preventable diseases, for both men and women, and smoking is the major trigger that causes lung cancer. The Austrian Health Ministry implements different actions to decrease lung cancer in the future. For instance, it offers smoking cessation services; but are these services always located in the right places to efficiently reach the target groups? This paper highlights the advantages of location analysis methods to spatially estimate the need at local level (i.e. where are clusters of smokers distributed at a small spatial level), and correspondingly position (more accurately) the offer of such services. With the help of our solution framework called simSALUD, we estimate the smoking prevalence by using Spatial Microsimulation Modelling in this project. Then, location-allocation modelling can be applied to find the places with the highest demand for smoking cessation services. The results of our project might be highly relevant for future health policy planning to decrease smoking prevalence, and therefore lung cancer.
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