1.
Statistics Sweden’s Covid-19
response
Jerker Moström (presenter) & Stefan Svanström
Statistics Sweden
Corona GIS webinar 7.5.2020

2.
What do we do?
• Corona realated statistics - Release of tailor-made
statistics and re-packaging of existing data to better
inform government agencies, research, media and the
public
• Support to the Public Health Agency of Sweden with micro
data management and spatial analysis
• Use of mobile network data to assess mobility/activity
changes - part of an existing collaboration with Telia
(experimental data)
Statistics Sweden is a
government agency
responsible for official
statistics and for other
government statistics.
In addition, we
coordinate the system
for the official statistics
in Sweden.

3.
Corona related statistics
• Statistics on risk groups, such as older elderly
population, multi-generation dwelling, overcrowding and
deaths/mortality (weekly releases)
• Statistics to inform on lock-down scenarios (number of
helth care workers with school children, number of
employees in critical sectors etc)
• Statistics to inform on the Covid-19 impact on economy
and labour market

4.
Corona related statistics
• A Covid-19 task force group to coordinate
analyses
• Special ”Corona entry” on the web (also urging
respondents to submit data)
• More than 20 articles published so far
• A map tool launched to visualise local level
population characteristics

5.
Supporting the Public Health
Agency of Sweden (PHA)
• A request for help to enrich micro data on individuals
infected by Covid-19 with background variables from
registers
• A request for help to conduct spatial analyses to
better understand the geography of Corona (patterns
of infection and the role of spatial, temporal and
contexual conditions)

6.
Micro data enrichment
• A large set of variables derrived from a number
of different registers
• Based on personal-ids commonly used as
identifiers across data repositories
• Very sensitive data, only to be shared via safe
environments within the PHA and Statistics
Sweden
Data themes
• Household and dwelling charactersistics (type of
household, number of persons, dwelling type)
• Children (number, age)
• Education (level)
• Profession, occuoation and employment
• Incomes (for household and for individuals)
• Year of birth (for infected and for parents)
• Country of origin (for infected and for parents

7.
Micro data enrichment
• What can background variables explain?
• Correlation with specific dwelling conditions,
socio economic status or background
• Preliminary analyses indicate strong
overrepresentation of people with other
country of origin
Source: Public Health Agency of Sweden

8.
Geography of Corona
• A step further – from data on individuals to
spatial context around indviduals
• Cluster analysis and hot-spots to follow how the
infection evolves over time
• Neighborhood characteristics (population
density, social economic conditions)
• Impact from mobility (Local Labour Markets)?
• Prediction? Is it possible to foresee areas with
high risk of new outbreaks

9.
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Location
Address locations to which data
on population and workplaces
can be geocoded

10.
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Location
Data on infected indivduals
from PHA geocoded to address
location

11.
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Aggregation
Aggregation on the basis of
location - number of infected
individuals on the same
location/address

12.
Neighborhood
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Use of small areas to construct
neighborhood units

13.
Neighborhood
Aggregation of
geocoded data
for all individuals
within the
neighborhood
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Type of dwelling
Dwelling area per capita
Country of origin
Population density
Household types
etc

14.
Yellow dots = infected
Can we identify
connections between
these dots?
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Connections &
networks

15.
Red square = workplace
Possible connection
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Connections &
networks

16.
Mobile network data
• On-going (mutual beneficial) collaboration with
Telia
• We don’t provide rapid response (Telia does this
already, guess you will hear more in a few
minutes…)
• Long-term work to assess usefulness of
network data to complement traditional data
sources
• The Corona pandemic provides an interesting
use case from a methodological point-of-wiew

17.
To wrap up…
• We’re in the middle of the work right now
• New questions and requirements arise along the way
• Mostly trial and error – time will tell if it was useful…
• We expect requests for Corona related data and analysis
to remain high in the near future
• Probably gradually shifting from responding to the
pandemic itself to responding to the aftermath
(economic and social conseqences)

18.
Thank you very much!
Jerker Moström
(did the talk)
Analyst/geospatial expert
Statistics Sweden
jerker.mostrom@scb.se
www.scb.se
Stefan Svanström
(does most of the work)
Analyst/geospatial expert
Statistics Sweden
stefan.svanstrom@scb.se