Project Details

Description

National-scale, high-quality real-time data on the spread of SARS-Cov-2 is proving powerful in the fight against Covid-19. On 29 April, Lund University launched the COVID Symptom Study in Sweden (covid19app.lu.se), based on a smartphone app that had also recently been launched in the US and UK. Study participants upload a short health declaration and postal code, daily reports on symptoms associated with a Covid-19 infection, and results from PCR of serology tests. Data on risk factors and exposure to Covid-19 are also collected. By fall 2020, almost 200 000 Swedish participants had made about 8 million data entries in the app. Maps detailing the predicted number of Covid-19 cases in Sweden are published in the study dashboard (https://csss-resultat.shinyapps.io/csss_dashboard/) for health authorities, study participants and the general public. Data collected in this study facilitate 1) analyses of temporal and regional trends in the spread of the disease, 2) investigation of Covid-19 symptoms and risk factors for disease severity, 3) impact of public health interventions, and 4) comparisons with the UK and the US (members of the COVID Symptom Study consortium). Data from the COVID Symptom Study have helped predict regional spikes in Covid-19 related hospital admissions roughly a week earlier than conventional monitoring methods. Data from the study also helped identify anosmia (loss of smell), skin rashes and delirium as key symptoms of Covid-19 infection.

Popular science description

The COVID Symptom Study in Sweden is a citizen-scientist project, where members of the Swedish public have been invited to participate by uploading information daily on risk factors, exposures and outcomes related to Covid-19 infection. The study includes almost 200 000 Swedish participants, the data from whom are used to provide weekly reports to public health leaders, information on regional and national infection “hotspots” for the public, and for undertaking epidemiological research on Covid-19.
StatusActive
Effective start/end date2020/04/20 → …

Collaborative partners

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Subject classification (UKÄ)

  • Infectious Medicine
  • Health Sciences