The Role of Business Cycles in the Impact of Government Expenditure Components on Income Distribution (MSAR Approach)

The government expenditure in economic affairs can act as a tool for creating and sustaining development by improving income distribution. Therefore, prioritization and optimal allocation of economic expenditures of governments will be so important. In this regard, the present study has investigated the impact of government expenditure on economic sector and related sub-sectors (agriculture, industry and mining, trade, information technology, energy, housing, transportation, environment, cooperatives affairs, and water resources) on income distribution in Iran's economy during business cycles. In this study, Markov Switching Auto Regressive model (MSAR) has been used to estimate time-series data during the time period between 1973 to 2019. The result of the study indicates that economic sector and agricultural, water resources and transportation subsectors during business cycles, “housing, trade, and cooperative affairs” subsectors during the boom periods, and the environment subsector during the recession periods have reduced income inequality significantly. Also, the government expenditure in industrial, mining, and energy subsectors during business cycles and information technology subsector during the boom periods have increased income inequality significantly. Finally, the subsectors of agricultural, water, industry and mining, commerce and cooperation, transportation have been more stable in the recession regime. Meanwhile, the economic sector and subsectors of information technology, housing and development, environment and energy have been more stable in the boom regime. Therefore, the components of government expenditure on income distribution have asymmetric behavior

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population