Zusammenfassung:
In 2020, the world was shaken by a very unexpected development, an unseen virus which could kill millions and spread without control. To reduce the impact of the pandemic and before the vaccine was created, lockdown and other safety measures were implemented. In this context, the socio-economic burden of the disease was, in our opinion, a major issue because we always considered that COVID-19 would have a hard impact on human beings and that that impact would be the most prominent effect of the pandemic. In consequence, when designing this Special Issue, we hoped to receive papers with "tales from the field" that would describe the mentioned socio-economic burden. Therefore, it was deeply rewarding to receive so many contributions of very good quality that ended up composing the Special Issue that is reprinted here. We sincerely thank all the authors and reviewers for the work they produced and we congratulate them for their success. We believe that this reprint of the Special Issue contributes to the understanding of the major consequences of COVID-19 in society. Crucially, the reprint includes papers on global perspectives but also national cases and also sector-specific cases. Finally, we hope the legacy of this volume will be long-lasting and that the papers it contains will be quoted and cited for many years to come.
Schlagwörter:
COVID-19
services value-added
lockdown
word-of-mouth
social distancing
quantile regression
radiographers
radiology and medical imaging
safety protocols
social and economic consequences
CSR
implication
public
health
evolution
stay-at-home order
mitigation efficiency
epidemic stability
quarantine hotel workers
knowledge
attitudes
practices
data mining
college graduates
employment policy
policy evaluation
coronavirus
SARS-Cov-2
teleworking
physical exercise
health policies
pandemic
migrants
sample survey
employment status
remittances
migrants' perception
economic and psychological impacts
coronavirus disease 2019 (COVID-19)
healthcare decisions
perception bias
attitude
long-term care facilities (LTCFs)
cumulative prospect theory (CPT)
COVID-19 pandemic
healthcare sector transformation
research and development
artificial intelligence
economic development
health system resilience
GIS
machine learning
regression
North Carolina
Gilford County