The new coronavirus (2019-nCoV or COVID-19) outbreak would probably change the consumption habits in China. According to a survey on the virus impact on Chinese consumers released in February 2020, almost 60 percent of the respondents said that they intended to spend more money on medical treatment after the epidemic. About 38.5 percent of the respondents planned to buy more sports products.

According to a survey in June 2020, about 44 percent of Chinese respondents said their financial well-being got worse after the coronavirus outbreak. In comparison, more than half of respondents confirmed that their financial well-being was not affected by the pandemic.

This data package includes the underlying data to replicate the charts presented in Lessons from China's fiscal policy during the COVID-19 pandemic, PIIE Working Paper 24-7.

If you use the data, please cite as: Huang, Tianlei. 2024. Lessons from China's fiscal policy during the COVID-19 pandemic. PIIE Working Paper 24-7. Washington: Peterson Institute for International Economics.

According to the survey conducted by McKinsey, the share of the respondents who were optimistic about the Chinese economic recovery reached 53 percent from May 19 to May 25, 2020, higher than the 43 percent in February. The growth of confidence may result from the resumption of work.

China COVID-19: Confirmed Case data was reported at 118,147.000 Person in 08 Jan 2023. This records an increase from the previous number of 104,874.000 Person for 07 Jan 2023. China COVID-19: Confirmed Case data is updated daily, averaging 978.500 Person from Feb 2020 (Median) to 08 Jan 2023, with 1068 observations. The data reached an all-time high of 118,147.000 Person in 08 Jan 2023 and a record low of 55.000 Person in 09 Jun 2020. China COVID-19: Confirmed Case data remains active status in CEIC and is reported by National Health Commission. The data is categorized under High Frequency Database’s Disease Outbreaks – Table CN.GZ: COVID-19: No of Patient.

China COVID-19: Confirmed Case: New Increase data was reported at 17.000 Person in 10 May 2020. This records an increase from the previous number of 14.000 Person for 09 May 2020. China COVID-19: Confirmed Case: New Increase data is updated daily, averaging 51.000 Person from Jan 2020 (Median) to 10 May 2020, with 112 observations. The data reached an all-time high of 15,152.000 Person in 12 Feb 2020 and a record low of 1.000 Person in 08 May 2020. China COVID-19: Confirmed Case: New Increase data remains active status in CEIC and is reported by National Health Commission. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GZ: COVID-19: No of Patient.

COVID-19: Number of Death: Year to Date: Hubei: Wuhan data was reported at 3,869.000 Person in 13 Dec 2022. This stayed constant from the previous number of 3,869.000 Person for 12 Dec 2022. COVID-19: Number of Death: Year to Date: Hubei: Wuhan data is updated daily, averaging 3,869.000 Person from Jan 2020 (Median) to 13 Dec 2022, with 1069 observations. The data reached an all-time high of 3,869.000 Person in 13 Dec 2022 and a record low of 1.000 Person in 14 Jan 2020. COVID-19: Number of Death: Year to Date: Hubei: Wuhan data remains active status in CEIC and is reported by National Health Commission. The data is categorized under High Frequency Database’s Disease Outbreaks – Table CN.GZ: COVID-19: No of Death. Clinical diagnosis included in since 12Feb 自2月12日起纳入临床诊断

China recorded 86689 Coronavirus Recovered since the epidemic began, according to the World Health Organization (WHO). In addition, China reported 4636 Coronavirus Deaths. This dataset includes a chart with historical data for China Coronavirus Recovered.

Chinese prefectural level governments started to report daily confirmed COVID-19 cases online, starting from January 2020. The disclosures may contain the mobility, potential exposure scenario, epidemiological characteristics, and other useful information of individual cases. We organized a group of content coders since early March 2020, kept monitoring the information updates, manually extracted useful information from the public disclosures, and compiled these datasets.We welcome any form of collaborations with us and non-commercial reuse of our dataset. We highly encourage interested parties to examine the data, report errors in our coding, and help us to keep the data updated.The detailed data description can be found on SSRN preprint server https://dx.doi.org/10.2139/ssrn.3705815.

IntroductionCOVID-19 related stress might vary with the pandemic changes, as well as other associated factors. This study aimed to compare the stress level during the first wave of the pandemic outbreak and 1 year later in China, and to explore the differential roles of social support and perceptions of this disease in affecting pandemic-related stress over time.MethodsCOVID-19 related stress, social support, and perceptions of the pandemic (perceived threat, perceived protection, and perceived controllability) were measured using the Impact of Event Scale-Revised for COVID-19, the Multidimensional Scale of Perceived Social Support, and the Self-Compiled Scale of COVID-19 Related Perception, respectively. Using an online survey, two independent samples were collected during the first wave of the COVID-19 outbreak (Time 1: March 2020, N = 430) and 1 year later (Time 2: April 2021, N = 512).ResultsLevels of COVID-19 related stress and social support were lower at Time 2. Furthermore, at both Time 1 and Time 2, more social support was associated with less stress. Perceived protection and controllability of COVID-19 also mediated the relationship between social support and COVID-19 at both time points. However, the perceived threat of COVID-19 only served as a mediator at Time 1.ConclusionThese results indicate that Chinese people might experience lower COVID-19 related stress as the pandemic progresses. The perceived threat of COVID-19 played a more critical role in stress experienced at Time 1. These findings not only underscore the importance of social support under the context of Chinese society, but also have implications for developing specific interventions targeting different perceptions of COVID-19 to reduce pandemic-related stress during the different waves of this pandemic.

ObjectiveTo examine the COVID-19 vaccination rate among a representative sample of adults from 31 provinces on the Chinese mainland and identify its influencing factors.MethodsWe gathered sociodemographic information, data on people's awareness and behavior regarding COVID-19 and the COVID-19 vaccine, the accessibility of COVID-19 vaccination services, community environmental factors influencing people's awareness and behavior regarding the vaccination, information about people's skepticism on COVID-19 vaccine, and information about people's trust in doctors as well as vaccine developers through an online nationwide cross-sectional survey among Chinese adults (18 years and older). The odds ratios (OR) and 95% confidence intervals (CI) for the statistical associations were estimated using logistic regression models.ResultsA total of 29,925 participants (51.4% females and 48.6% males) responded. 89.4% of the participants had already received a COVID-19 vaccination. After adjusting for demographic characteristics, awareness of COVID-19 pandemic/ COVID-19 vaccine, community environmental factors, awareness and behavior of general vaccinations, we discovered that having no religious affiliation, having the same occupational status as a result of coronavirus epidemic, being a non-smoker, always engaging in physical activity, having a lower social status, perceiving COVID-19 to be easily curable, and having easier access to vaccination are all associated with high vaccination rate (all P

China recorded 5226 Coronavirus Deaths since the epidemic began, according to the World Health Organization (WHO). In addition, China reported 99256991 Coronavirus Cases. This dataset includes a chart with historical data for China Coronavirus Deaths.

Updated to May 13, 2021. World COVID-19 daily cases with basemap, starting from January 22, 2020.

During the COVID-19 epidemic in China in early 2020 - a period starting shortly before the 2020 Chinese Spring Festival holiday and extending to the weeks afterwards - when the majority of Chinese people were confined to their homes, the use of mobile internet saw a strong increase, surging to 7.3 hours per day per user - an increae of more than one hour in comparison to the period prior to the epidemic. Among other factors, the need to work and learn remotely contributed to the increased use of mobile internet.

Objective: In December 2022, the Chinese government announced the further optimization of the implementation of the prevention and control measures of COVID-19. We aimed to assess internet-using public expression and sentiment toward COVID-19 in the relaxation of control measures in China.Methods: We used a user-simulation-like web crawler to collect raw data from Sina-Weibo and then processed the raw data, including the removal of punctuation, stop words, and text segmentation. After performing the above processes, we analyzed the data in two aspects. Firstly, we used the Latent Dirichlet Allocation (LDA) model to analyze the text data and extract the theme. After that, we used sentiment analysis to reveal the sentiment trend and the geographical spatial sentiment distribution.Results: A total of five topics were extracted according to the LDA model, namely, Complete liberalization, Resource supply, Symptom, Knowledge, and Emotional Outlet. Furthermore, sentiment analysis indicates that while the percentages of positive and negative microblogs fluctuate over time, the overall quantity of positive microblogs exceeds that of negative ones. Meanwhile, the geographical dispersion of public sentiment on internet usage exhibits significant regional variations and is subject to multifarious factors such as economic conditions and demographic characteristics.Conclusion: In the face of the relaxation of COVID-19 control measures, although concerns arise among people, they continue to encourage and support each other.

Background: The study sought to assess the changes in physical activity (PA) and sedentary time among Chinese youths at different stages after the COVID-19 outbreak.Methods: It was based on a retrospective online survey conducted in May 2020. More than 10,000 youths voluntarily recalled their PA-related information at three stages: before COVID-19 (January), during lockdown (February), and after lockdown (May). χ2 tests were conducted to evaluate the significance of the differences in participants' characteristics between sexes, and Wilcoxon Rank Sum tests were performed to examine the significance of differences in changes in PA and sedentary behavior levels between sexes.Results: A total of 8,115 participants were included, with a mean age of 20. The percentage of no PA per week increased significantly and then slightly fell, and that of ≥150 min/week substantially decreased and then rebounded partially (all p < 0.001) (for instance, the percentage of ≥150 min/week of PA total decreased from 38.6 to 19.4%, then rebounded back to 25.3%). Means hours per day spent in sedentary behaviors had significantly increased during lockdown comparing to pre-COVID-19 (all p < 0.001). There were more participants reported reduced PA level than those indicated increased, and more participating youths had their sedentary behavior level increased than those who had it decreased.Conclusions: The study found COVID-19 had both immediate and longer-term impacts on self-reported physical activities and sedentary behaviors among Chinese youths. Relevant efforts should be strengthened to get youths physically moving again.

This paper uses a panel data approach to assess the evolution of economic consequences of the drastic lockdown policy in the epicenter of COVID-19-the Hubei Province of China during worldwide curbs on economic activity. We find that the drastic 76-day COVID-19 lockdown policy brought huge negative impacts on Hubei's economy. In 2020:q1, the lockdown quarter, the treatment effect on GDP was about 37% of the counterfactual. However, the drastic lockdown also brought the spread of COVID-19 under control in little more than two months. After the government lifted the lockdown in early April, the economy quickly recovered with the exception of passenger transportation sector which rebounded not as quickly as the rest of the general economy.

ABSTRACT This article seeks to show two interconnected phenomena in China. The first is a historical process that took place in the past 40 years involving institutional and qualitative changes in the state-controlled portion of the Chinese economy. Such changes have brought about new and superior forms of economic planning, based on which a higher stage of development pattern has emerged. We call this new development pattern "New Projectment Economy" and it synthesizes a series of state capacities built over time. The second phenomenon relates to how the state capacities created in the past decades have allowed the country to show adaptive flexibility and rapid efficiency in the containment of Covid-19 crisis internally and thus explain China's successful response in the fight against the coronavirus. Such phenomena, pari passu, show China's potential and projection as an international political actor.

The number of COVID-19 vaccination doses administered in China rose to 3491077000 as of Oct 27 2023. This dataset includes a chart with historical data for China Coronavirus Vaccination Total.

BackgroundThis study aimed to report the prevalence of COVID-19 over-concern and its associated factors after the relaxation of the health-protective measures in China.MethodsA team of seven experts in psychiatry and psychology specializing in COVID-19 mental health research from China, Hong Kong, and overseas reached a consensus on the diagnostic criteria for COVID-19 over-concern. Individuals had to meet at least five of the following criteria: (1) at least five physical symptoms; (2) stocking up at least five items related to protecting oneself during the COVID-19 pandemic; (3) obsessive-compulsive symptoms related to the COVID-19 pandemic; (4) illness anxiety related to the COVID-19 pandemic; (5) post-traumatic stress symptoms; (6) depression; (7) anxiety; (8) stress and (9) insomnia. An online survey using snowball sampling collected data on demographics, medical history, views on COVID-19 policies, and symptoms of COVID-19 over-concern. Multivariate linear regression was performed using significant variables from the previous regressions as independent variables against the presence of COVID-19 over-concern as the dependent variable. Breush-Pagan test was used to assess each regression model for heteroskedasticity of residuals.Results1,332 respondents from 31 regions in China participated in the study for 2 weeks from December 25 to 27, 2022, after major changes in the zero-COVID policy. After canceling measures associated with the dynamic zero-COVID policy, 21.2% of respondents fulfilled the diagnostic criteria for COVID-19 over-concern. Factors significantly associated with COVID-19 over-concern were poor self-rated health status (β = 0.07, p