[Epidemiological characteristics of COVID-19 epidemic in Ejina banner, Inner Mongolia Autonomous Region, October 2021].

Objective: To understand the epidemiological characteristics of COVID-19 epidemic in Ejina banner, Inner Mongolia, in October 2021 and provide evidence for the improvement of COVID-19 prevention and control. Methods: The information about the time, area and population distributions of COVID-19 cases in Ejina before November 13, 2021 and the gene sequencing result of the isolates were collected for a statistical descriptive analysis. Results: The first COVID-19 case in Ejina occurred on 7 October, 2021. A total of 164 COVID-19 cases were reported from October 19 to November 12. Most cases were distributed in 6 communities in Darahub (156 cases, 95.12%). The result of full gene sequencing of the isolates indicted that the pathogen was Delta variant (B.1.617.2). The male to female ratio of the cases was 1.3∶1. The age of cases ranged from 1 to 85 years, and the cases aged 20-59 years accounted for 78.66%. The main clinical symptoms were sore throat (91 cases, 91.92%), cough (49 cases, 49.49%) and fever (23 cases, 23.23%). Most cases were ordinary ones (81 cases, 49.39%) and mild ones (68 cases, 41.46%). The cases were mainly detected at the isolation points (84 cases, 51.22%) and through population based nucleic acid testing (62 cases, 37.80%). The basic reproduction number (R0) of COVID-19 was 5.3, the average incubation period was 3.9 days. The local government rapidly started Ⅳ level emergency response and conducted 10 rounds of nucleic acid tests. The transferring of travelers reduced the risk for the further spread of COVID-19 in Ejina. Conclusions: The epidemic of COVID-19 in Ejina characterized by strong transmission, short incubation period, herd susceptibility and case clustering. Delta variant (B.1.617.2) was the pathogen, which might be imported from Zeke port. Comprehensive prevention and control measures, such as closed-loop management and vaccination, should be continued. The successful transferring of the patients and travelers provided evidence for the effective and precise prevention and control of COVID-19 in a routine manner.

The Relationship between Pandemic Circumstances and Socioeconomic Factors and Implications for the Government

Research Objective: This research explores the role that socioeconomic factors play on the pandemic development and it provides government with public control implications. Theoretical background: Government of different regions responds to the pandemic with various government policies and interventions. Meanwhile, socioeconomic factors that are long-term results of government policies also impact the development of the pandemic in different regions. We study how these socioeconomic factors are related with the COVID-19 pandemic development. Research Design: Using data from IBGE - Brazilian Institute of Geography and Statistics, Ministry of Health, and Santa Catarina State Department of Health, we conduct a set of regression analyses at the municipality-level using socioeconomic factors as independent variables, and log-transformed confirmed COVID-19 cases and confirmed COVID-19 deaths as dependent variables. Results: We identify several significant indicators of pandemic outcomes and we find that municipalities in the Brazilian state with more basic health units, higher bedroom density, higher autonomy level of municipal revenue tend to have more confirmed cases and deaths due to COVID-19. We also find other socioeconomic factors including sanitation condition and age group diversity as important indicators of COVID-19 confirmed cases and deaths. Originality: This research is one of the first to understand the impact of socioeconomic factors on the development of the COVID-19 pandemic and it utilizes unique datasets that have not been used by other studies to our best knowledge. Practical and theorical contributions: The deliverables of this research will improve the understanding of the ongoing pandemic, predict the pandemic development trend, and prepare the policymakers with improved information provisioning by pointing out the significant impacts of socioeconomic factors.

Research on China's Tax Policy for Responding to Public Health Emergencies under the Background of Big Data

The sudden outbreak of the novel coronavirus pneumonia in early 2020 not only posed a serious threat to the health and safety of people in my country and the world but also caused a significant decline in the global economy. Tax preferential policy is a macro means for the government to regulate the economy and plays an indispensable role in the process of economic development. In the context of the wave of big data technology, how to introduce big data thinking into the taxation process and establish and improve a tax policy system that quickly responds to public health emergencies is extremely important for epidemic prevention and control and subsequent recovery. Based on the background of the novel coronavirus pneumonia, this paper elaborates the necessity of tax policies to deal with public health emergencies, analyzes the current preferential tax policies and limitations of public health emergencies, and proposes the establishment and improvement of China based on the characteristics of the era of big data era on tax incentives for public health emergencies. © 2020 IEEE.