
The study uses rolling regressions, both at global and country level, to analyze the impact of daily Covid-19 case numbers on four (Panic, Sentiment, Media coverage, and Fake news) indices. The indices are obtained from the Ravenpack Finance, while the daily Covid-19 cases and the policy response stringency index data is extracted from the Oxford COVID-19 Government Response Tracker. The results indicate that the impact of the number of daily Covid-19 cases on the indices is quite variable over time. Higher impact on the indices is reflected in periods where there is a significant surge in cases, in particular the initial surge in Spring, Summer and Fall. There is some evidence of diminished (increased) sensitivity of panic and media indices (fake news) to number of cases but this is not consistent across all countries. These results indicate that the public are concerned and respond to changes in the trends of the spread of the virus and highlight the importance of managing trends if halting its spread is not immediately feasible.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
