Table_1_Empirical Study of Monthly Economic Losses Assessments for “Standard Unit Lockdown” Due to COVID-19.DOCX

• Main Authors: Houli Zhang, Shibing You, Miao Zhang, Anqi Chen, Zengyun Hu, Ying Liu, Difei Liu, Pei Yuan, Yi Tan
• Format: Dataset
• Language: unknown
• Published: 2022
• Subjects: Mental Health Nursing; Midwifery; Nursing not elsewhere classified; Aboriginal and Torres Strait Islander Health; Aged Health Care; Care for Disabled; Community Child Health; Environmental and Occupational Health and Safety; Epidemiology; Family Care; Health and Community Services; Health Care Administration; Health Counselling; Health Information Systems (incl. Surveillance); Health Promotion; Preventive Medicine; Primary Health Care; Public Health and Health Services not elsewhere classified; Nanotoxicology; Health and Safety; Medicine; Nursing and Health Curriculum and Pedagogy; COVID-19; lockdown; standard unit incident; assessment system; monthly economic losses assessment; Antarc*; Antarctica
• Online Access: https://doi.org/10.3389/fpubh.2022.859751.s001; https://figshare.com/articles/dataset/Table_1_Empirical_Study_of_Monthly_Economic_Losses_Assessments_for_Standard_Unit_Lockdown_Due_to_COVID-19_DOCX/19737352

Background The pandemic of COVID-19 has been shaping economic developments of the world. From the standpoint of government measures to prevent and control the epidemic, the lockdown was widely used. It is essential to access the economic losses in a lockdown environment which will provide government administration with a necessary reference for decision making in controlling the epidemic. Methods We introduce the concept of “standard unit incident” and an economic losses assessment methodology for both the standard and the assessed area. We build a “standard unit lockdown” economic losses assessment system and indicators to estimate the economic losses for the monthly lockdown. Using the comprehensive assessment system, the loss infected coefficient of monthly economic losses during lockdown in the 40 countries has been calculated to assess the economic losses by the entropy weighting method (EWM) with data from the CSMAR database and CDC website. Results We observe that countries in North America suffered the most significant economic losses due to the epidemic, followed by South America and Europe, Asia and Africa, and Oceania and Antarctica suffered relatively minor economic losses. The top 10 countries for monthly economic losses during lockdown were the United States, India, Brazil, France, Turkey, Russia, the United Kingdom, Italy, Spain, and Germany. The United States suffered the greatest monthly economic losses under lockdown ($65.3 billion), roughly 1.5 times that of China, while Germany suffered the least ($56.4 billion), roughly 1.3 times that of China. Conclusion Lockdown as a control and mitigation strategy has great impact on the economic development and causes huge economic losses. The economic impact due to the pandemic has varied widely among the 40 countries. It will be important to conduct further studies to compare and understand the differences and the reasons behind.