The evaluation of pollen concentrations with statistical and computational methods on rooftop and on ground level in Vienna - How to include daily crowd-sourced symptom data.

ABSTRACT:

Background

It is recommended to position pollen monitoring stations on rooftop level to assure a large catchment area and to gain data that are representative for a regional scale. Herein, an investigation of the representativeness of pollen concentrations was performed for 20 pollen types in the pollen seasons 2015-2016 in Vienna for rooftop and ground level and was compared with weather data and for the first time with symptom data.

Methods

The complete data set was analyzed with various statistical methods including Spearmen correlation, ANOVA, Kolmogorov-Smirnov test and logistic regression calculation: Odds ratio and Yule's Q values. Computational intelligence methods, namely Self Organizing Maps (SOMs) were employed that are capable of describing similarities and inter

SUBMITTER: Bastl M 

PROVIDER: S-EPMC6514368 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature