Abstract
Since the outbreak of the corona virus in the end of 2019, many worldwide attempts have been made to monitor and control the COVID-19 pandemic. A wealth of empirical data has been collected and used by national health authorities to understand and mitigate the spread and impacts of the corona virus. In various countries this serious health concern has led to the development of corona dashboards monitoring the COVID-19 evolution. The present study aims to design and test an extended corona dashboard, in which—beside up-to-date daily core data on infections, hospital and intensive care admissions, and numbers of deceased people—also the evolution of vaccinations in a country is mapped out. This dashboard system is next extended with time-dependent contextual information on lockdown and policy stringency measures, while disaggregate information on the geographic spread of the COVID-19 disease is provided by means of big data on contact intensity and mobility motives based on detailed Google Mobility data. Finally, this context-specific corona dashboard, named ‘Dutchboard’, is further extended towards the regional and local level so as to allow also for space-specific ‘health checks’ and assessments.
Highlights
COVID-19 has become a disruptive factor in human health conditions all over the world
Corona dashboard data are often reported in daily newspapers; they have frequently been the source of public debate
Decisions become inconsistent and flawed, as can be shown by experimental research. This principle is respected in a car dashboard, and in current corona dashboard applications, where the number of indicators simultaneously included in a corona dashboard is normally four to five
Summary
The currently popular corona dashboards are mainly inspired by dashboard applications in the management sciences. It should be noted that a dashboard is not a miraculous panacea for treating all kinds of diseases (a ‘deus ex machina’) It acts as a lighthouse for consistent decisions or policy making, but it does not imply a decision per se nor function as a compelling choice tool; it offers only an insightful, evidence-based and instrumental interface mechanism for interventions of competent agents. It is not a prediction model: a dashboard captures only in a systematic and condensed form relevant past information. These descriptions will be used as key elements for designing the corona dashboard and to assess its usefulness at the end of this paper
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