The impact of coronavirus COVID-19 outbreak with a prolonged shutdown of business operation could be devastating on China's economy. Recreation industry was estimated to suffer the most with a drop by 5.8 percentage points form the baseline of no virus outbreak. Transportation, trade and communication services were other hard-hit industries.

ObjectivesTo assess the cost-effectiveness of Paxlovid in reducing severe COVID-19 and its associated morality, and to investigate the affordable price of Paxlovid in China.Materials and methodsUsing a Markov model, two interventions by Paxlovid prescription (with and without prescription) were compared in terms of COVID-19-related clinical outcomes and economic loss. COVID-related costs were collected from the societal perspective. Effectiveness data were obtained from literature. The primary outcomes were total social cost, disability adjusted life-years (DALYs) and net monetary benefit (NMB). Scenario analyses were performed to investigate the affordable price of Paxlovid in China. Deterministic sensitivity analyses (DSA) and probabilistic sensitivity analysis (PSA) were performed to verify the model robustness.ResultsCompared with the non-Paxlovid cohort, the NMBs of the Paxlovid cohort were only higher in the subgroup of patients aged over 80 years old, regardless of their vaccination status. Our scenario analysis found that, the price ceiling of Paxlovid/box for it to be cost-effective was RMB 8,993 (8,970–9,009) in those aged over 80 years old who were not vaccinated, which is the highest; and was RMB 35 (27–45) in those aged 40–59 years old who were vaccinated, which is the lowest. Sensitivity analyses found that the incremental NMB for the vaccinated people aged over 80 years was most sensitive to the efficacy of Paxlovid and the cost-effectiveness probability of Paxlovid increased with its decreasing price.ConclusionUnder the current marketing price of Paxlovid/box (RMB 1,890), using Paxlovid was only cost-effective in people aged over 80 years old regardless of their vaccination status.

BackgroundThe 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.MethodsWe 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.ResultsWe 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.ConclusionLockdown 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.

In 2020, global gross domestic product declined by 6.7 percent as a result of the coronavirus (COVID-19) pandemic outbreak. In Latin America, overall GDP loss amounted to 8.5 percent.

In the past two decades, four major virus outbreaks caused significant economic loss in China. Due to the outbreak of novel coronavirus COVID-19, business and factories were shutdown in the country. Experts estimated that China's GDP could suffer a maximum loss of 500 billion yuan in 2020, five-fold higher compared to Severe Acute Respiratory Syndrome (SARS) between 2002 and 2003.

Economic shocks from COVID-19, coupled with ongoing US-China tensions, have raised debates around supply chain (or global value chain) organisation, with China at the centre of the storm. However, quantitative studies that consider the global and economy-wide impacts of rerouting supply chains are limited. This study examines the economic and emissions impacts of reorganising supply chains, using Australia-China trade as an example. It augments the Hypothetical Extraction Method by replacing traditional Input-Output analysis with a Computable General Equilibrium analysis. The estimation results demonstrate that in both exports and imports, a trade embargo between Australia and China – despite being compensated for by alternative supply chains—will cause gross domestic production losses and emissions increases for both countries and the world overall. Moreover, even though all other economies gain from the markets left by China, many of them incur overall gross domestic production losses and emission increases. The finding that the Association of Southeast Asian Nations and India may also suffer from an Australia-China trade embargo, despite a gain in trade volume, suggests that no country should add fuel to the fire. The results suggest that countries need to defend a rules-based trading regime and jointly address supply chain challenges.

Novel coronavirus (COVID-19) is a new strain of coronavirus first identified in Wuhan, China. As the virus has spread worldwide, China has reduced transmission at a considerable social and economic cost. To minimize the harm to society caused by the lockdown, resuming work safely post-pandemic is a major issue. As the capital of China, Beijing hosts many residents and workers with origins elsewhere, making it a high-risk region in which to resume work. To avoid a second significant outbreak of COVID-19, we simulate the evolution of the pandemic under different stages of resuming work. The transmission model is developed from a modified SEIR model for SARS tailored to the situation of Beijing with the involvement of multi-source data. Because of the strong heterogeneity of population, socio-economic factors and medical capacity of Beijing, the risk assessment is produced spatiotemporally with respect to each district of Beijing. The result suggests that resuming work step by step in Beijing would not bring about a recurrence of the pandemic. However, at different stages of resuming work, special attention should be paid to different parts in Beijing. The proposed relevant pandemic-prevention measures will provide valuable insights for other cities or regions dealing with the outbreak of COVID-19.

China Industrial Enterprise: Number of Loss Making Enterprise data was reported at 176,555.000 Unit in Feb 2025. This stayed constant from the previous number of 176,555.000 Unit for Jan 2025. China Industrial Enterprise: Number of Loss Making Enterprise data is updated monthly, averaging 61,814.500 Unit from Jan 1995 (Median) to Feb 2025, with 338 observations. The data reached an all-time high of 177,737.000 Unit in Mar 2024 and a record low of 30,456.000 Unit in Dec 2011. China Industrial Enterprise: Number of Loss Making Enterprise data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under Global Database’s China – Table CN.BF: Industrial Financial Data. [COVID-19-IMPACT]

The ongoing Coronavirus Disease 2019 (COVID-19), a global pandemic with high infectiousness and high mortality, has seriously threatened human health, life safety and caused enormous economic losses. This study investigates the influencing factors on the case fatality rate (CFR) of COVID-19 at the city level in China.

According to a survey among Chinese companies operating in the United States conducted in March and April 2022, 10 percent of respondents suffered from economic loss due to the anti-China/Asia sentiment during the COVID-19 pandemic, a drop from 36 percent in 2020. About 40 percent of surveyed Chinese companies still found the effects hard to tell, while 16 percent of them expected long-term negative implications.

According to a median projection in July 2025, China's GDP was expected to grow by *** percent in 2025. In the first quarter of 2020, the second-largest economy recorded the first contraction in decades due to the epidemic.  A root-to-branch shutdown of factories To curb the spread of the virus, the Chinese government imposed a lockdown in Wuhan, the epicenter, and other cities in Hubei province on January 23, 2020. A strict nationwide lockdown soon followed. Many factories remained closed in February, resulting in a plunge in manufacturing Purchasing Managers' Index (PMI). The shutdown of the “world’s factory” had severely disrupted global supply chains, especially automobile production. In March 2020, very few industrial sectors reported positive production growth.  The pharmaceuticals sector recorded a production increase, which was mainly driven by the global demand for vital medical supplies. China had exported over seven billion yuan worth of face masks. Ripple effects on global tourism Apart from the manufacturing industry, the prolonged closures of business had caused significant losses in various sectors in China. The travel and tourism sector was massively affected by a drastic decline in flight ticket sales  and hotel occupancy rates. The domestic tourism market expects a loss of 20 percent in revenues for 2020. Industry experts predicted that the global travel and tourism industry could lose about *** trillion U.S. dollars in that year. 

Hong Kong SAR (China) Net Payment Incurred: DB: Year to Date: Pecuniary Loss: Others data was reported at 88,223.000 HKD th in Jun 2024. This records an increase from the previous number of 41,907.000 HKD th for Mar 2024. Hong Kong SAR (China) Net Payment Incurred: DB: Year to Date: Pecuniary Loss: Others data is updated quarterly, averaging 87,524.000 HKD th from Mar 2011 (Median) to Jun 2024, with 54 observations. The data reached an all-time high of 1,373,878.000 HKD th in Dec 2023 and a record low of 8,956.000 HKD th in Mar 2011. Hong Kong SAR (China) Net Payment Incurred: DB: Year to Date: Pecuniary Loss: Others data remains active status in CEIC and is reported by Insurance Authority. The data is categorized under Global Database’s Hong Kong SAR (China) – Table HK.Z018: Insurance Statistics: General Business: Direct Business (Provisional). [COVID-19-IMPACT]

Hong Kong SAR (China) Net Payment Incurred: DB: Year to Date: Pecuniary Loss data was reported at 117,191.000 HKD th in Jun 2024. This records an increase from the previous number of 70,271.000 HKD th for Mar 2024. Hong Kong SAR (China) Net Payment Incurred: DB: Year to Date: Pecuniary Loss data is updated quarterly, averaging 90,233.500 HKD th from Mar 2007 (Median) to Jun 2024, with 70 observations. The data reached an all-time high of 1,422,174.000 HKD th in Dec 2023 and a record low of 2,271.000 HKD th in Mar 2010. Hong Kong SAR (China) Net Payment Incurred: DB: Year to Date: Pecuniary Loss data remains active status in CEIC and is reported by Insurance Authority. The data is categorized under Global Database’s Hong Kong SAR (China) – Table HK.Z018: Insurance Statistics: General Business: Direct Business (Provisional). [COVID-19-IMPACT]

The spill over effect of a disruption in Chinese supply to the Philippines would bring economic effects among different industries in the country. The communication equipment industry in the Philippines is estimated to lose 115 million U.S. dollars from a two percent reduction in China exports of intermediate inputs according to a report in February 2020.

Hong Kong SAR (China) Net Payment Incurred: DB: Year to Date: Pecuniary Loss: Mortgage Guarantee data was reported at 28,968.000 HKD th in Jun 2024. This records an increase from the previous number of 28,364.000 HKD th for Mar 2024. Hong Kong SAR (China) Net Payment Incurred: DB: Year to Date: Pecuniary Loss: Mortgage Guarantee data is updated quarterly, averaging 766.500 HKD th from Mar 2011 (Median) to Jun 2024, with 54 observations. The data reached an all-time high of 48,296.000 HKD th in Dec 2023 and a record low of -19,799.000 HKD th in Dec 2011. Hong Kong SAR (China) Net Payment Incurred: DB: Year to Date: Pecuniary Loss: Mortgage Guarantee data remains active status in CEIC and is reported by Insurance Authority. The data is categorized under Global Database’s Hong Kong SAR (China) – Table HK.Z018: Insurance Statistics: General Business: Direct Business (Provisional). [COVID-19-IMPACT]

Additional costs of rural households deriving from COVID-19 epidemic (RMB).

According to a survey conducted in February 2020 among more than *** lodging enterprises in China, the mid-level and high-end hotels reported a ** percent year-on-year loss of their revenue during the COVID-19 outbreak. Economy hotels lost around ** percent of revenue compared to the same period of 2019.

According to the source, the relocation of some production of semi-finished and finished products from China will result in losses to the Chinese economy in terms of lower value-added generated. Depending on the scenario, the loss of value-added in the Chinese economy could range from 22.4 billion U.S. dollars up to 172 billion U.S. dollars per year after the adjustment period. Through a system of global supply chains, other countries in the world, such as the EU, could gain little from relocating within Asia. Imports of semi-finished or finished products originating in countries in South-East Asia, India, and Taiwan also include the added value from EU countries. The EU-14** would benefit most from relocation if part of China's supplies of semi-finished and finished goods were replaced by domestic production - scenarios S2 and S4. EU-14 countries could also benefit from relocation even if Chinese manufacturing is not shifted to their economies (scenarios S1 and S3). In particular, when part of the supply from China would be replaced by production from the six new Member States. Due to the strong ties with the EU-13, Germany and Austria could benefit most in relative terms. On the other hand, EU-13 countries** could benefit most from Chinese relocation productions in scenario S3 and S4. In absolute terms, Poland could benefit most.

A recent survey from IPSOS found that a large share of people worldwide strongly agree or somewhat agree that the coronavirus (COVID-19) will have a financial impact on themselves or their family. As of March 14, around 89 percent of adults in Vietnam and China thought the coronavirus would impact them personally, compared to 40 percent in Germany. This statistic shows the percentage of respondents worldwide who strongly or somewhat agreed the coronavirus would have a financial impact on them or their family as of March 14, 2020, by country.

Revenue for the Skin Care, Hairdressing and Beauty Services industry in China is expected to decrease at an annualized rate of 2.4% over the five years through 2024 to $5.1 billion. Due to the limited number of people going out in the past few years caused by the COVID-19 pandemic and the economic downturn, many enterprises are unable to support fixed costs. Industry revenue has decreased, and profits have declined.Many industry enterprises are small in scale, providing basic services like haircuts and the curling, straightening, and dyeing of hair. The industry has low investment costs due to the high availability and low cost of equipment and products, as well as numerous upstream product brands. Most enterprises serve consumers within their immediate vicinity. The industry presents characteristics of being very dispersed, with dense store layouts and rapid turnover.Profit is expected to account for 3.8% of industry revenue in 2024. Although profit margin has declined in the past few years, with the recovery of the economy, industry profit margin will gradually increase. The industry is labor-intensive, and it is expected that wage costs will account for 42.1% of the industry revenue in 2024. Total wages are expected to rise by an annualized 1.0% over the five years through 2024 to $2.1 billion.Due to forecast steady increases in disposable income and consumption trends, consumers are projected to continue spending on beauty services over the next five years. Over the five years through 2029, industry revenue is forecast to increase at an annualized 2.5%, totaling $5.8 billion in 2029. Spa services, skin care and hairdressing services are also projected to be provided in a more integrated way, so that customers can enjoy a series of services without changing locations.The industry actively introduces new technologies like AI to provide consumers with a better service experience. AI can provide personalized services and offer suitable solutions to consumers. Meanwhile, AI can also collect sufficient information to help companies understand market trends and promote the healthy development of the industry.