Collection of socio-economic and meteorological indicators as well as travel patterns and cases of H1N1 during the swine flu pandemic in Sweden in 2009. Comprise the supplementary information for the paper titled "Socioeconomic and environmental patterns behind H1N1 spreading in Sweden" by András Bóta, Martin Holmberg, Lauren Gardner and Martin Rosvall, Sci Rep 11, 22512 (2021). https://doi.org/10.1038/s41598-021-01857-4
Corresponding author: András Bóta, Embedded Intelligent Systems Lab, Department of Computer Science, Electrical and Space Engineering, Lulea University of Technology, SE-97181 Lulea, Sweden. andras.bota@ltu.se
András Bóta was supported by the Olle Engkvist Byggmästare Foundation. Martin Rosvall was supported by the Swedish Research Council, grant 2016-00796.

Municipality codes for the municipalities of Sweden can be found here:
https://www.scb.se/en/finding-statistics/regional-statistics/regional-divisions/counties-and-municipalities/counties-and-municipalities-in-numerical-order/

Data available according to Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license

Shared files
Model inputs
1. giim_kommun_graph.csv 
Set of frequent travel routes between the municipalities of Sweden. 
The graph was constructed from "Trafikanalys, 2016. Resvanor. (accessed 26.8.19). Available from: http://www.trafa.se/RVU-Sverige/." using the methodology described in the paper.
Date of construction: 2018-12-01
Format: csv
Structure: edge list in (kommun1;kommun2) format with rows indicating a directed link between two municipalities. Municipalities are denoted according to their official municipal code

2. giim_casecounts.xlsx 
Number of new H1N1 cases in the municipalities of Sweden between 2009 and 2015.
Our data set consists of all laboratory-verified cases of A(H1N1)pdm09 between May 2009 and December 2015, extracted
from the SmiNet register of notifiable diseases, held by the Public Health Agency of Sweden. 
Due to confidentiality reasons, cases are anonymized, and addresses are aggregated at the DeSo level together with
the date of diagnosis, age, and gender. We obtained ethical approval for the data acquisition.
Date of construction: 2018-12-01
Format: xlsx
Structure: Each tab represents a single flu season from the 2009/2010 season to the 2014/2015 season. 
Each tab is a matrix with rows indicating municipalities according to their official municipal code, and columns indicating epidemic weeks. Values of the matruces indicate the number of new laboratory-verified cases of A(H1N1)pdm09

3. giim_kommun_indicators.csv 
Socioeconomic and meteorological indicators assigned to the municipalities of Sweden according to the methodology described in the paper.
Indicators included are: 
a, mean temperature in degree Celsius,
b, absolute humidity in grams per cubic metre,
c, population size as the number of people living in each municipality,
d, population density as the number of people per sq. km of land area,
e, median income per household in thousand SEK,
f, fraction of people on social aid (as a percentage),
g, average number of children younger than 18 years per household.
Meteorological data was obtained from the European Climate Assessment Dataset "Klein Tank A, Wijngaard J, Können G, Böhm R, Demarée G, Gocheva A, et al. Daily dataset of 20th-century surface
air temperature and precipitation series for the European Climate Assessment. International Journal of Climatology: A Journal of the Royal Meteorological Society. 2002;22(12):1441–1453."
Data from the dataset was converted to the municipality level according to the methodology described in the paper. Variables are mean temperature and relative humidity converted to absolute humidity
for all municipalities of Sweden.
Socioeconomic data was collected from Statistics Sweden between 2018 Ocotber and 2019 February. Available from: https://www.scb.se/en/. Variables are: The median household income
as an economic indicator. The average number of children younger than 18 years per household to indicate family size. 
The fraction of people receiving social aid to represent poverty in a municipality. Population size and population density as the number of people per sq. km of land area.
Date of construction: 2018-02-01
Format: csv
Structure:
Each row corresponds to a municipality denoted according to their official municipal code. Columns indicate socioeconomic and meteorological indicators as marked by the header row.

Model outputs
1. giim_export_risk.csv
Exportation risk values for all municipalities from week 37 to week 50 in the fall of 2009 computed using the methodology described in the paper.
Date of construction: 2020-12-01
Format: csv
Structure: Table with rows denoting Swedish municipalities according to their official municipal code, columns denoting epidemic weeks. Values indicate exportation risk values (should not be interpreted as probabilities).

2. giim_import_risk.csv
Importation risk values for all municipalities from week 37 to week 50 in the fall of 2009 computed using the methodology described in the paper.
Date of construction: 2020-12-01
Format: csv
Structure: Table with rows denoting Swedish municipalities according to their official municipal code, columns denoting epidemic weeks. Values indicate importation risk values (should not be interpreted as probabilities).

3. giim_transmission_prob.csv
Transmission probabilities between all municipalities from week 37 to week 50 in the fall of 2009 computed using the methodology described in the paper.
Date of construction: 2020-12-01
Format: csv
Structure: Edge list with multiple edge weights. Rows indicate a directed link between the two municipalities (kommun1;kommun2) in the beginning of the row. The rest of the values in each row denote
the corresponding transmission probabilities for each epidemic week computed according to the methodology described in the paper.