Socio-Economic Burden of Disease: The COVID-19 Case - Eduardo Tomé; Thomas Garavan; Ana Dias (MDPI - Multidisciplinary Digital Publishing Institute, 2024)
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.
Keywords: 330; 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