Tag Archive for: spatiotemporal analysis

The rapid and widespread diffusion of relevant and useful knowledge plays a key role in mitigating the effects of shocks (disasters, pandemics, wars, etc.). Despite the fact that in our globalised, interconnected world, information can spread around the globe in hours or days, there are still many factors (enablers and barriers) that influence its spread. These factors show different geographical patterns, which can affect the spread of information and thus the ability to cope with certain shocks._x000D_
The presentation will focus on the COVID-19 pandemic and the spread of information related to it. Within a few months of its outbreak, the Coronavirus had appeared in almost every part of the world but information (e.g., facts, rumours, fake news) related to that has spread faster (mainly via internet), creating an infodemic parallel to the pandemic. The aim of the presentation is to show the spatiotemporal patterns of the spread of these two phenomena (Coronavirus-pandemic and information) and their interactions. The key question is the following: how could the spread of information influence the spread of the virus and mitigate its effects?_x000D_
To answer this, I collected weekly pandemic and GoogleTrends statistics (in regional level) and different socio-economic, mobility and governance indicators from European countries. I subjected these to statistical data analysis: in addition to descriptive statistics and data visualisation, I used a multivariate spatial regression model. It can be concluded that the impact of the information diffusion in spread of the virus is clearly observable: in different ways during each epidemic wave, but it helped the control of the virus. While during the first wave it played an important role in the timing of closures, during the later waves it influenced the dissemination of other solutions (especially vaccines).

András Igari
ELTE Eötvös Loránd University, Institute of Geography and Earth Sciences, Department of Regional Science, Budapest, Hungary – PhD student; HÉTFA Research Institute, Budapest, Hungary – junior analyst


 
ID Abstract: 553