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Statistics Sweden’s Covid-19
response
Jerker Moström (presenter) & Stefan Svanström
Statistics Sweden
Corona GIS webinar 7.5.2020
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.
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
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
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)
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
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
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
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Location
Address locations to which data
on population and workplaces
can be geocoded
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Location
Data on infected indivduals
from PHA geocoded to address
location
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Aggregation
Aggregation on the basis of
location - number of infected
individuals on the same
location/address
Neighborhood
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Use of small areas to construct
neighborhood units
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
Yellow dots = infected
Can we identify
connections between
these dots?
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Connections &
networks
Red square = workplace
Possible connection
Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet
Connections &
networks
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
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)
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

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Jerker statistics sweden covid 19 response

  • 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.
  • 6. 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)
  • 7. 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
  • 8. 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
  • 9. 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
  • 10. Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet Location Address locations to which data on population and workplaces can be geocoded
  • 11. Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet Location Data on infected indivduals from PHA geocoded to address location
  • 12. Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet Aggregation Aggregation on the basis of location - number of infected individuals on the same location/address
  • 13. Neighborhood Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet Use of small areas to construct neighborhood units
  • 14. 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
  • 15. Yellow dots = infected Can we identify connections between these dots? Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet Connections & networks
  • 16. Red square = workplace Possible connection Källa: Bearbetningar © SCB, övrig geodata © SCB, Lantmäteriet Connections & networks
  • 17. 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
  • 18. 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)
  • 19. 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