Understanding the behaviour of the Dutch population during the COVID-19 pandemic. The value of self-reported data in public health

María Villalobos, Nicholas H. Saadah, Niels H. Chavannes, Jessica C. Kiefte

Keywords: self-reported data, COVID apps, public health, health-protective behaviours, vaccination.

Background:

Public health policies to adopt health-protective behaviours were and continue to be part of the strategy to slow down SARS-CoV-2. A year and a half after the first report of the virus, growing evidence supports the value of some of these policies, but there is still limited understanding of the population’s response to these policies and evidence of the real changes in the population's behaviour.

Research questions:

This study explores the value of self-reported data for understanding behavioural patterns relevant to public health during the COVID-19 pandemic in the Netherlands. Specifically, we researched if this data could be used to track changes and better understand (1) the behaviour of the population through the pandemic, and in response to infection and vaccination; and (2) the population’s compliance with the government’s policies.

Method:

The COVID Radar app, developed by the Leiden University Medical Centre, gathered self-reported data from 284 026 users, from April 2020 until March 2022. Using seven behavioural variables included in the COVID Radar app dataset, a COVID Behaviour Score (CBScore) was generated. Higher CBScores indicate riskier behaviours. Additionally, adherence to two government policies (the number of visitors allowed and the use of facemasks) was analysed.

Results:

We showed that the CBScore changes through time, and that it can be used as a proxy for COVID-19 risky behaviour. There is variability depending on the age group. CBScores change significantly after vaccination and/or testing positive for COVID-19. Similarly, adherence to the government’s policies regarding the number of visitors and the use of facemasks varied depending on age.

Conclusions:

This study contributes to a better understanding of the reach of government policies during the COVID-19 pandemic, but can be translated to other public health issues and policy in general. It provides evidence-ground to analyse and improve policies and better support citizens during healthcare emergencies.

Points for discussion:

Value and quality of self-reported data

Limitations of the study

Value and translation into policy-making

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