Preprint Open Access
Data of "Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria"
Ledebur, Katharina;
Kaleta, Michaela;
Chen, Jiaying;
Matzhold, Caspar;
Linder, Simon D.;
Weidle, Florian;
Wittmann, Christoph;
Habimana, Katharina;
Kerschbaumer, Linda;
Stumpfl, Sophie;
Heiler, Georg;
Bicher, Martin;
Popper, Nikolaus;
Bachner, Florian;
Klimek, Peter
A data-driven modelling approach based on an age-structured model that compares 116 Austrian regions to a suitably chosen control set of regions to explain variations in local transmission rates through a combination of meteorological factors, non-pharamaceutical interventions and mobility.
Repository contains input data time series of metereological factors, regional measures and mobility used to calculate the effect sizes of these variable groups.
| Name | Size | |
|---|---|---|
|
cloud_mean_Bezirk.csv
md5:4ce3fbb125ce0e417f6552ae0cdc4d81 |
3.1 MB | Download |
|
Edited_Massnahmen.csv
md5:00e09e7eb65e5e2a6761ff7571a6e54b |
155.1 kB | Download |
|
humid_mean_Bezirk.csv
md5:71ff1d812e332bcae529f02915a6343c |
3.6 MB | Download |
|
prec_mean_Bezirk.csv
md5:c312391449bacfa220a4b22f1bf8910e |
2.5 MB | Download |
|
rg_Bezirk.mat
md5:799df20e71847663f5eee76503b00e1b |
410.4 kB | Download |
|
temp_mean_Bezirk.csv
md5:b443ac53729578a510b062e14c39bcb0 |
3.5 MB | Download |
|
wind_mean_Bezirk.csv
md5:0d4ff70285da233f131a98cd764dd642 |
3.5 MB | Download |
| All versions | This version | |
|---|---|---|
| Views | 75 | 75 |
| Downloads | 60 | 60 |
| Data volume | 79.9 MB | 79.9 MB |
| Unique views | 59 | 59 |
| Unique downloads | 32 | 32 |
- Publication date:
- August 13, 2021
- DOI:
-
- Keyword(s):
- Meterological factors Epidemiology SARS-CoV-2 Covid-19 Mobility
- License (for files):
- Creative Commons Attribution 4.0 International