The Gross Domestic Product per capita in China was last recorded at 13121.68 US dollars in 2024. The GDP per Capita in China is equivalent to 104 percent of the world's average. This dataset provides - China GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Gross Domestic Product per capita in China was last recorded at 23845.62 US dollars in 2024, when adjusted by purchasing power parity (PPP). The GDP per Capita, in China, when adjusted by Purchasing Power Parity is equivalent to 134 percent of the world's average. This dataset provides - China GDP per capita PPP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset provides key economic indicators for five of the world's largest economies, based on their nominal Gross Domestic Product (GDP) in 2022. It includes the GDP values, population, GDP growth rates, per capita GDP, and each country's share of the global economy.

Columns: Country: Name of the country. GDP (nominal, 2022): The total nominal GDP in 2022, represented in USD. GDP (abbrev.): The abbreviated GDP in trillions of USD. GDP growth: The percentage growth in GDP compared to the previous year. Population: Total population of each country in 2022. GDP per capita: The GDP per capita, representing average economic output per person in USD. Share of world GDP: The percentage of global GDP contributed by each country. Key Highlights: The dataset includes some of the largest global economies, such as the United States, China, Japan, Germany, and India. The data can be used to analyze the economic standing of countries in terms of overall GDP and per capita wealth. It offers insights into the relative growth rates and population sizes of these leading economies. This dataset is ideal for exploring economic trends, performing country-wise comparisons, or studying the relationship between population size and GDP growth.

China GDP per Capita: PPP: 2021 Price data was reported at 22,137.600 Intl $ in 2023. This records an increase from the previous number of 21,011.617 Intl $ for 2022. China GDP per Capita: PPP: 2021 Price data is updated yearly, averaging 7,381.927 Intl $ from Dec 1990 (Median) to 2023, with 34 observations. The data reached an all-time high of 22,137.600 Intl $ in 2023 and a record low of 1,645.579 Intl $ in 1990. China GDP per Capita: PPP: 2021 Price data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Gross Domestic Product: Purchasing Power Parity. GDP per capita based on purchasing power parity (PPP). PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP at purchaser's prices is the sum of gross value added by all resident producers in the country plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2021 international dollars.;International Comparison Program, World Bank | World Development Indicators database, World Bank | Eurostat-OECD PPP Programme.;Weighted average;

The statistic shows the gross domestic product (GDP) per capita in India from 1987 to 2030. In 2020, the estimated gross domestic product per capita in India amounted to about 1,915.55 U.S. dollars. See figures on India's economic growth here. For comparison, per capita GDP in China had reached about 6,995.25 U.S. dollars in 2013. India's economic progress India’s progress as a country over the past decade can be attributed to a global dependency on cheaper production of goods and services from developed countries around the world. India’s economy is built upon its agriculture, manufacturing and services sector, which, along with its drastic rise in population and demand for employment, led to a significant increase of the nation’s GDP per capita. Despite experiencing rather momentous economic gains since the mid 2000s, the Indian economy stagnated around 2012, with a decrease in general growth as well as the value of its currency. Residents and consumers in India have recently shown pessimism regarding the future of the Indian economy as well as their own financial situation, and with the recent economic standstill, consumer confidence in the country could potentially lower in the near future. Typical Indian exports consist of agricultural products, jewelry, chemicals and ores. Imports consist primarily of crude oil, gold and precious stones, used primarily in the manufacturing of jewelry. As a result, India has seen a rather highly increased demand of several gems in order to boost their jewelry industry and in general their exports. Although India does not export an extensive amount of goods, especially when considering the stature of the country, India has remained as one of the world’s largest exporters.

Explore the World Competitiveness Ranking dataset for 2016, including key indicators such as GDP per capita, fixed telephone tariffs, and pension funding. Discover insights on social cohesion, scientific research, and digital transformation in various countries.

Social cohesion, The image abroad of your country encourages business development, Scientific articles published by origin of author, International Telecommunication Union, World Telecommunication/ICT Indicators database, Data reproduced with the kind permission of ITU, National sources, Fixed telephone tariffs, GDP (PPP) per capita, Overall, Exports of goods - growth, Pension funding is adequately addressed for the future, Companies are very good at using big data and analytics to support decision-making, Gross fixed capital formation - real growth, Economic Performance, Scientific research legislation, Percentage of GDP, Health infrastructure meets the needs of society, Estimates based on preliminary data for the most recent year., Singapore: including re-exports., Value, Laws relating to scientific research do encourage innovation, % of GDP, Gross Domestic Product (GDP), Health Infrastructure, Digital transformation in companies is generally well understood, Industrial disputes, EE, Female / male ratio, State ownership of enterprises, Total expenditure on R&D (%), Score, Colombia, Estimates for the most recent year., Percentage change, based on US$ values, Number of listed domestic companies, Tax evasion is not a threat to your economy, Scientific articles, Tax evasion, % change, Use of big data and analytics, National sources, Disposable Income, Equal opportunity, Listed domestic companies, Government budget surplus/deficit (%), Pension funding, US$ per capita at purchasing power parity, Estimates; US$ per capita at purchasing power parity, Image abroad or branding, Equal opportunity legislation in your economy encourages economic development, Number, Article counts are from a selection of journals, books, and conference proceedings in S&E from Scopus. Articles are classified by their year of publication and are assigned to a region/country/economy on the basis of the institutional address(es) listed in the article. Articles are credited on a fractional-count basis. The sum of the countries/economies may not add to the world total because of rounding. Some publications have incomplete address information for coauthored publications in the Scopus database. The unassigned category count is the sum of fractional counts for publications that cannot be assigned to a country or economy. Hong Kong: research output items by the higher education institutions funded by the University Grants Committee only., State ownership of enterprises is not a threat to business activities, Protectionism does not impair the conduct of your business, Digital transformation in companies, Total final energy consumption per capita, Social cohesion is high, Rank, MTOE per capita, Percentage change, based on constant prices, US$ billions, National sources, World Trade Organization Statistics database, Rank, Score, Value, World Rankings

Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Canada, Chile, China, Colombia, Croatia, Cyprus, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, India, Indonesia, Ireland, Israel, Italy, Japan, Jordan, Kazakhstan, Latvia, Lithuania, Luxembourg, Malaysia, Mexico, Mongolia, Netherlands, New Zealand, Norway, Oman, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Saudi Arabia, Singapore, Slovenia, South Africa, Spain, Sweden, Switzerland, Thailand, Turkey, Ukraine, United Kingdom, Venezuela

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IntroductionThe combined populations of China and India were 2.78 billion in 2020, representing 36% of the world population (7.75 billion). Wheat is the second most important staple grain in both China and India. In 2019, the aggregate wheat consumption in China was 96.4 million ton and in India it was 82.5 million ton, together it was more than 35% of the world's wheat that year. In China, in 2050, the projected population will be 1294–1515 million, and in India, it is projected to be 14.89–1793 million, under the low and high-fertility rate assumptions. A question arises as to, what will be aggregate demand for wheat in China and India in 2030 and 2050?MethodsApplying the Vector Error Correction model estimation process in the time series econometric estimation setting, this study projected the per capita and annual aggregate wheat consumptions of China and India during 2019-2050. In the process, this study relies on agricultural data sourced from the Food and Agriculture Organization of the United States (FAO) database (FAOSTAT), as well as the World Bank's World Development Indicators (WDI) data catalog. The presence of unit root in the data series are tested by applying the augmented Dickey-Fuller test; Philips-Perron unit root test; Kwiatkowski-Phillips-Schmidt-Shin test, and Zivot-Andrews Unit Root test allowing for a single break in intercept and/or trend. The test statistics suggest that a natural log transformation and with the first difference of the variables provides stationarity of the data series for both China and India. The Zivot-Andrews Unit Root test, however, suggested that there is a structural break in urban population share and GDP per capita. To tackle the issue, we have included a year dummy and two multiplicative dummies in our model. Furthermore, the Johansen cointegration test suggests that at least one variable in both data series were cointegrated. These tests enable us to apply Vector Error Correction (VEC) model estimation procedure. In estimation the model, the appropriate number of lags of the variables is confirmed by applying the “varsoc” command in Stata 17 software interface. The estimated yearly per capita wheat consumption in 2030 and 2050 from the VEC model, are multiplied by the projected population in 2030 and 2050 to calculate the projected aggregate wheat demand in China and India in 2030 and 2050. After projecting the yearly per capita wheat consumption (KG), we multiply with the projected population to get the expected consumption demand.ResultsThis study found that the yearly per capita wheat consumption of China will increase from 65.8 kg in 2019 to 76 kg in 2030, and 95 kg in 2050. In India, the yearly per capita wheat consumption will increase to 74 kg in 2030 and 94 kg in 2050 from 60.4 kg in 2019. Considering the projected population growth rates under low-fertility assumptions, aggregate wheat consumption of China will increase by more than 13% in 2030 and by 28% in 2050. Under the high-fertility rate assumption, however the aggregate wheat consumption of China will increase by 18% in 2030 and nearly 50% in 2050. In the case of India, under both low and high-fertility rate assumptions, aggregate wheat demand in India will increase by 32-38% in 2030 and by 70-104% in 2050 compared to 2019 level of consumption.DiscussionsOur results underline the importance of wheat in both countries, which are the world's top wheat producers and consumers, and suggest the importance of research and development investments to maintain sufficient national wheat grain production levels to meet China and India's domestic demand. This is critical both to ensure the food security of this large segment of the world populace, which also includes 23% of the total population of the world who live on less than US $1.90/day, as well as to avoid potential grain market destabilization and price hikes that arise in the event of large import demands.

These are research indicators of comparative empirical investigation of South Eastern European Countries (SEECs) and People’s Republic of China (PRC) that were compiled from the criteria and factors of the World Bank. This dataset consists of data for SEECs and PRC for the period of 2000 to 2016. The World Bank Research Indicators consist of (1) GNI, Atlas Method (Current US$); (2) GNI per capita, Atlas; (3) GNI PPP (Current International $); (4) GNI per capita, PPP (Current International $); (5) Energy Use (kg of Oil Equivalent per capita); (6) Electric Power Consumption (kWh per capita); (7) GDP (Current US$); (8) GDP Growth (Annual %); (9) Inflation, GDP Deflator (Annual %); (10) Agriculture, Value Added (% of GDP); (11) Industry, Value Added (% of GDP); (12) Service, etc., Value Added (% of GDP); (13) Exports of Goods and Services (% of GDP); (14) Imports of Goods and Services (% of GDP); (15) Gross Capital Formation (% of GDP); (16) Revenue, excluding Grants (% of GDP); (17) Time Required to Start a Business (Days); (18) Domestic Credit Provided by Financial Sector (% of GDP); (19) Tax Revenue (% of GDP); (20) High-Technology Exports (% of Manufactured Exports); (21) Merchandise Trade (% of GDP); (22) Net Barter Terms of Trade Index (2000 = 100); (23) External Debt Stock, Total (DOD, Current US$); (24) Total Debt Service (% of Exports of Goods, Services and Primary Income); (25) Personal Remittances, Received (Current US$); (26) Foreign Direct Investment, Net Flows (BoP, Current US$); and (27) Net Official Development Assistance and Official Aid Received (Current US$). Furthermore, statistical data of SEECs and PRC were retrieved from Atlas 2.1 – Growth Lab at the Center for International Development at Harvard University and WITS – UNSD COMPTRADE.

Explore the Saudi Arabia World Development Indicators dataset , including key indicators such as Access to clean fuels, Adjusted net enrollment rate, CO2 emissions, and more. Find valuable insights and trends for Saudi Arabia, Bahrain, Kuwait, Oman, Qatar, China, and India.

Indicator, Access to clean fuels and technologies for cooking, rural (% of rural population), Access to electricity (% of population), Adjusted net enrollment rate, primary, female (% of primary school age children), Adjusted net national income (annual % growth), Adjusted savings: education expenditure (% of GNI), Adjusted savings: mineral depletion (current US$), Adjusted savings: natural resources depletion (% of GNI), Adjusted savings: net national savings (current US$), Adolescents out of school (% of lower secondary school age), Adolescents out of school, female (% of female lower secondary school age), Age dependency ratio (% of working-age population), Agricultural methane emissions (% of total), Agriculture, forestry, and fishing, value added (current US$), Agriculture, forestry, and fishing, value added per worker (constant 2015 US$), Alternative and nuclear energy (% of total energy use), Annualized average growth rate in per capita real survey mean consumption or income, total population (%), Arms exports (SIPRI trend indicator values), Arms imports (SIPRI trend indicator values), Average working hours of children, working only, ages 7-14 (hours per week), Average working hours of children, working only, male, ages 7-14 (hours per week), Cause of death, by injury (% of total), Cereal yield (kg per hectare), Changes in inventories (current US$), Chemicals (% of value added in manufacturing), Child employment in agriculture (% of economically active children ages 7-14), Child employment in manufacturing, female (% of female economically active children ages 7-14), Child employment in manufacturing, male (% of male economically active children ages 7-14), Child employment in services (% of economically active children ages 7-14), Child employment in services, female (% of female economically active children ages 7-14), Children (ages 0-14) newly infected with HIV, Children in employment, study and work (% of children in employment, ages 7-14), Children in employment, unpaid family workers (% of children in employment, ages 7-14), Children in employment, wage workers (% of children in employment, ages 7-14), Children out of school, primary, Children out of school, primary, male, Claims on other sectors of the domestic economy (annual growth as % of broad money), CO2 emissions (kg per 2015 US$ of GDP), CO2 emissions (kt), CO2 emissions from other sectors, excluding residential buildings and commercial and public services (% of total fuel combustion), CO2 emissions from transport (% of total fuel combustion), Communications, computer, etc. (% of service exports, BoP), Condom use, population ages 15-24, female (% of females ages 15-24), Container port traffic (TEU: 20 foot equivalent units), Contraceptive prevalence, any method (% of married women ages 15-49), Control of Corruption: Estimate, Control of Corruption: Percentile Rank, Upper Bound of 90% Confidence Interval, Control of Corruption: Standard Error, Coverage of social insurance programs in 4th quintile (% of population), CPIA building human resources rating (1=low to 6=high), CPIA debt policy rating (1=low to 6=high), CPIA policies for social inclusion/equity cluster average (1=low to 6=high), CPIA public sector management and institutions cluster average (1=low to 6=high), CPIA quality of budgetary and financial management rating (1=low to 6=high), CPIA transparency, accountability, and corruption in the public sector rating (1=low to 6=high), Current education expenditure, secondary (% of total expenditure in secondary public institutions), DEC alternative conversion factor (LCU per US$), Deposit interest rate (%), Depth of credit information index (0=low to 8=high), Diarrhea treatment (% of children under 5 who received ORS packet), Discrepancy in expenditure estimate of GDP (current LCU), Domestic private health expenditure per capita, PPP (current international $), Droughts, floods, extreme temperatures (% of population, average 1990-2009), Educational attainment, at least Bachelor's or equivalent, population 25+, female (%) (cumulative), Educational attainment, at least Bachelor's or equivalent, population 25+, male (%) (cumulative), Educational attainment, at least completed lower secondary, population 25+, female (%) (cumulative), Educational attainment, at least completed primary, population 25+ years, total (%) (cumulative), Educational attainment, at least Master's or equivalent, population 25+, male (%) (cumulative), Educational attainment, at least Master's or equivalent, population 25+, total (%) (cumulative), Electricity production from coal sources (% of total), Electricity production from nuclear sources (% of total), Employers, total (% of total employment) (modeled ILO estimate), Employment in industry (% of total employment) (modeled ILO estimate), Employment in services, female (% of female employment) (modeled ILO estimate), Employment to population ratio, 15+, male (%) (modeled ILO estimate), Employment to population ratio, ages 15-24, total (%) (national estimate), Energy use (kg of oil equivalent per capita), Export unit value index (2015 = 100), Exports of goods and services (% of GDP), Exports of goods, services and primary income (BoP, current US$), External debt stocks (% of GNI), External health expenditure (% of current health expenditure), Female primary school age children out-of-school (%), Female share of employment in senior and middle management (%), Final consumption expenditure (constant 2015 US$), Firms expected to give gifts in meetings with tax officials (% of firms), Firms experiencing losses due to theft and vandalism (% of firms), Firms formally registered when operations started (% of firms), Fixed broadband subscriptions, Fixed telephone subscriptions (per 100 people), Foreign direct investment, net outflows (% of GDP), Forest area (% of land area), Forest area (sq. km), Forest rents (% of GDP), GDP growth (annual %), GDP per capita (constant LCU), GDP per unit of energy use (PPP $ per kg of oil equivalent), GDP, PPP (constant 2017 international $), General government final consumption expenditure (current LCU), GHG net emissions/removals by LUCF (Mt of CO2 equivalent), GNI growth (annual %), GNI per capita (constant LCU), GNI, PPP (current international $), Goods and services expense (current LCU), Government Effectiveness: Percentile Rank, Government Effectiveness: Percentile Rank, Lower Bound of 90% Confidence Interval, Government Effectiveness: Standard Error, Gross capital formation (annual % growth), Gross capital formation (constant 2015 US$), Gross capital formation (current LCU), Gross fixed capital formation, private sector (% of GDP), Gross intake ratio in first grade of primary education, male (% of relevant age group), Gross intake ratio in first grade of primary education, total (% of relevant age group), Gross national expenditure (current LCU), Gross national expenditure (current US$), Households and NPISHs Final consumption expenditure (constant LCU), Households and NPISHs Final consumption expenditure (current US$), Households and NPISHs Final consumption expenditure, PPP (constant 2017 international $), Households and NPISHs final consumption expenditure: linked series (current LCU), Human capital index (HCI) (scale 0-1), Human capital index (HCI), male (scale 0-1), Immunization, DPT (% of children ages 12-23 months), Import value index (2015 = 100), Imports of goods and services (% of GDP), Incidence of HIV, ages 15-24 (per 1,000 uninfected population ages 15-24), Incidence of HIV, all (per 1,000 uninfected population), Income share held by highest 20%, Income share held by lowest 20%, Income share held by third 20%, Individuals using the Internet (% of population), Industry (including construction), value added (constant LCU), Informal payments to public officials (% of firms), Intentional homicides, male (per 100,000 male), Interest payments (% of expense), Interest rate spread (lending rate minus deposit rate, %), Internally displaced persons, new displacement associated with conflict and violence (number of cases), International tourism, expenditures for passenger transport items (current US$), International tourism, expenditures for travel items (current US$), Investment in energy with private participation (current US$), Labor force participation rate for ages 15-24, female (%) (modeled ILO estimate), Development

Saudi Arabia, Bahrain, Kuwait, Oman, Qatar, China, India Follow data.kapsarc.org for timely data to advance energy economics research..

Explore macroeconomic statistics and indicators, including GDP, Gross Fixed Capital Formation, National Income, and more. This dataset covers a wide range of countries such as Afghanistan, Albania, Algeria, Australia, Brazil, China, Germany, India, United States, and many more.

GDP, Gross Domestic Product, Capita, GFCF, Gross Fixed Capital Formation, Value, Added, Gross, Output, National, Income, Manufacturing, Agriculture, Population, National Accounts

Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Côte d'Ivoire, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo, Costa Rica, Croatia, Cuba, Cyprus, Czechia, Democratic Republic of the Congo, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kiribati, Kuwait, Kyrgyzstan, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Monaco, Mongolia, Montenegro, Morocco, Mozambique, Myanmar, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Samoa, San Marino, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, Somalia, South Africa, South Sudan, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkmenistan, Tuvalu, Uganda, Ukraine, United Arab Emirates, United Kingdom, United States of America, Uruguay, Uzbekistan, Vanuatu, Venezuela, Yemen, Zambia, Zimbabwe

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China GNI per Capita: USD: 2015 Price data was reported at 12,074.124 USD in 2023. This records an increase from the previous number of 11,457.675 USD for 2022. China GNI per Capita: USD: 2015 Price data is updated yearly, averaging 5,120.608 USD from Dec 1995 (Median) to 2023, with 29 observations. The data reached an all-time high of 12,074.124 USD in 2023 and a record low of 1,498.490 USD in 1995. China GNI per Capita: USD: 2015 Price data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Gross Domestic Product: Real. GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant 2015 U.S. dollars.;World Bank national accounts data, and OECD National Accounts data files.;Weighted average;

BackgroundChina accounted for 87% (9.8 million/11.3 million) of all hand, foot, and mouth disease (HFMD) cases reported to WHO during 2010–2014. Enterovirus 71 (EV71) is responsible for most of the severe HFMD cases. Three EV71 vaccines recently demonstrated good efficacy in children aged 6–71 mo. Here we assessed the cost-effectiveness of routine pediatric EV71 vaccination in China.Methods and FindingsWe characterized the economic and health burden of EV71-associated HFMD (EV71-HFMD) in China using (i) the national surveillance database, (ii) virological surveillance records from all provinces, and (iii) a caregiver survey on the household costs and health utility loss for 1,787 laboratory-confirmed pediatric cases. Using a static model parameterized with these data, we estimated the effective vaccine cost (EVC, defined as cost/efficacy or simply the cost of a 100% efficacious vaccine) below which routine pediatric vaccination would be considered cost-effective. We performed the base-case analysis from the societal perspective with a willingness-to-pay threshold of one times the gross domestic product per capita (GDPpc) and an annual discount rate of 3%. We performed uncertainty analysis by (i) accounting for the uncertainty in the risk of EV71-HFMD due to missing laboratory data in the national database, (ii) excluding productivity loss of parents and caregivers, (iii) increasing the willingness-to-pay threshold to three times GDPpc, (iv) increasing the discount rate to 6%, and (v) accounting for the proportion of EV71-HFMD cases not registered by national surveillance. In each of these scenarios, we performed probabilistic sensitivity analysis to account for parametric uncertainty in our estimates of the risk of EV71-HFMD and the expected costs and health utility loss due to EV71-HFMD. Routine pediatric EV71 vaccination would be cost-saving if the all-inclusive EVC is below US$10.6 (95% CI US$9.7–US$11.5) and would remain cost-effective if EVC is below US$17.9 (95% CI US$16.9–US$18.8) in the base case, but these ceilings could be up to 66% higher if all the test-negative cases with missing laboratory data are EV71-HFMD. The EVC ceiling is (i) 10%–14% lower if productivity loss of parents/caregivers is excluded, (ii) 58%–84% higher if the willingness-to-pay threshold is increased to three times GDPpc, (iii) 14%–19% lower if the discount rate is increased to 6%, and (iv) 36% (95% CI 23%–50%) higher if the proportion of EV71-HFMD registered by national surveillance is the same as that observed in the three EV71 vaccine phase III trials. The validity of our results relies on the following assumptions: (i) self-reported hospital charges are a good proxy for the opportunity cost of care, (ii) the cost and health utility loss estimates based on laboratory-confirmed EV71-HFMD cases are representative of all EV71-HFMD cases, and (iii) the long-term average risk of EV71-HFMD in the future is similar to that registered by national surveillance during 2010–2013.ConclusionsCompared to no vaccination, routine pediatric EV71 vaccination would be very cost-effective in China if the cost of immunization (including all logistical, procurement, and administration costs needed to confer 5 y of vaccine protection) is below US$12.0–US$18.3, depending on the choice of vaccine among the three candidates. Given that the annual number of births in China has been around 16 million in recent years, the annual costs for routine pediatric EV71 vaccination at this cost range should not exceed US$192–US$293 million. Our results can be used to determine the optimal vaccine when the prices of the three vaccines are known.

ObjectivesFrom the perspective of Chinese healthcare system, this study compared the cost-utility of aripiprazole once-monthly (AOM) and paliperidone palmitate once-monthly injectable (PP1M) in the treatment of adult patients with schizophrenia in China.MethodsA 5-state Markov model was developed to evaluate the cost-utility of 10 years of long-acting injections (LAI) treatment for schizophrenia. The long-term costs and quality-adjusted life years (QALYs) were estimated, with the incremental cost-effectiveness ratio (ICER) as the primary outcome. The annual discount rate was set at 5%. A cost-effectiveness threshold (CET) of 0.51 times China’s 2023 gross domestic product (GDP) (US$ 6,394.536) was used to judge the economics of intervention.ResultsThe current price of AOM in China is relatively high (US$418.140). To assess its cost-effectiveness in the context of potential price negotiations with China Healthcare Security Administration (CHS) for inclusion in the National Reimbursement Drug List (NRDL), we simulated a 40% price reduction (US$257.619). At a CET of 0.51 times GDP per capita (US$6,394.536), the base-case analysis showed that the incremental costs of AOM relative to PP1M after 10 years of treatment were US$1,926.373 with an incremental gain of 0.306 QALYs. The ICER for AOM was US$6,285.303 per QALY, which is below the CET, indicating that AOM is cost-effective. One-way sensitivity analysis identified AOM’s drug cost as the parameter with the greatest impact on results. Probabilistic sensitivity analysis revealed that with a 40% price reduction, the probability of AOM being cost-effective is only 41.70%. However, with a 60% price reduction, AOM became dominantly cost-effective, with the probability increasing to 100%. When the CET was relaxed to 0.90 times GDP per capita (US$11,284.476), the probability of cost-effectiveness for AOM after a 40% price reduction rose to 85.10%. Scenario analyses conducted over a time horizon extending from 10 to 30 years showed that the ICER decreased significantly with longer follow-up, gradually approaching the 0.51GDP threshold and remaining below the 0.90 GDP threshold throughout the analysis.ConclusionsThe cost-effectiveness of AOM relative to PP1M is highly influenced by its price and the CET. Healthcare decision makers or clinical users need to balance innovation incentives and accessibility.

Hong Kong HK: GDP: PPP:(GDP) Gross Domestic Productper Capita data was reported at 61,540.158 Intl $ in 2017. This records an increase from the previous number of 58,681.618 Intl $ for 2016. Hong Kong HK: GDP: PPP:(GDP) Gross Domestic Productper Capita data is updated yearly, averaging 31,404.772 Intl $ from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 61,540.158 Intl $ in 2017 and a record low of 17,434.294 Intl $ in 1990. Hong Kong HK: GDP: PPP:(GDP) Gross Domestic Productper Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Hong Kong SAR – Table HK.World Bank.WDI: Gross Domestic Product: Purchasing Power Parity. GDP per capita based on purchasing power parity (PPP). PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current international dollars based on the 2011 ICP round.; ; World Bank, International Comparison Program database.; Weighted average;

Brazilian and Indian share prices became the highest performing of the major developed and emerging economies as of June 2023, with index values of 235.25 and 230.91 respectively in that month. Conversely, the lowest-performing were China and the Germany, both with index values of 86.98 and 113.04 respectively at this time. The index value is calculated with 2015 values as the baseline (i.e. 2015 = 100).

Hong Kong SAR (China) GDP per Capita: PPP: 2021 Price data was reported at 64,467.576 Intl $ in 2023. This records an increase from the previous number of 64,036.787 Intl $ for 2022. Hong Kong SAR (China) GDP per Capita: PPP: 2021 Price data is updated yearly, averaging 52,077.029 Intl $ from Dec 1990 (Median) to 2023, with 34 observations. The data reached an all-time high of 66,993.927 Intl $ in 2018 and a record low of 31,598.894 Intl $ in 1990. Hong Kong SAR (China) GDP per Capita: PPP: 2021 Price data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Hong Kong SAR (China) – Table HK.World Bank.WDI: Gross Domestic Product: Purchasing Power Parity. GDP per capita based on purchasing power parity (PPP). PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP at purchaser's prices is the sum of gross value added by all resident producers in the country plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2021 international dollars.;International Comparison Program, World Bank | World Development Indicators database, World Bank | Eurostat-OECD PPP Programme.;Weighted average;

Macau SAR (China) GDP per Person Employed: 2021 PPP data was reported at 192,410.735 Intl $ in 2023. This records an increase from the previous number of 105,678.629 Intl $ for 2022. Macau SAR (China) GDP per Person Employed: 2021 PPP data is updated yearly, averaging 171,261.619 Intl $ from Dec 1991 (Median) to 2023, with 33 observations. The data reached an all-time high of 286,508.796 Intl $ in 2013 and a record low of 104,630.758 Intl $ in 2020. Macau SAR (China) GDP per Person Employed: 2021 PPP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Macau SAR (China) – Table MO.World Bank.WDI: Employment and Unemployment. GDP per person employed is gross domestic product (GDP) divided by total employment in the economy. Purchasing power parity (PPP) GDP is GDP converted to 2021 constant international dollars using PPP rates. An international dollar has the same purchasing power over GDP that a U.S. dollar has in the United States.;World Bank, World Development Indicators database. Estimates are based on employment, population, GDP, and PPP data obtained from International Labour Organization, United Nations Population Division, Eurostat, OECD, and World Bank.;Weighted average;

CN: GDP per Person Employed: 2017 PPP data was reported at 34,574.584 Intl $ in 2022. This records an increase from the previous number of 33,481.505 Intl $ for 2021. CN: GDP per Person Employed: 2017 PPP data is updated yearly, averaging 11,329.341 Intl $ from Dec 1991 (Median) to 2022, with 32 observations. The data reached an all-time high of 34,574.584 Intl $ in 2022 and a record low of 2,794.914 Intl $ in 1991. CN: GDP per Person Employed: 2017 PPP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Employment and Unemployment. GDP per person employed is gross domestic product (GDP) divided by total employment in the economy. Purchasing power parity (PPP) GDP is GDP converted to 2017 constant international dollars using PPP rates. An international dollar has the same purchasing power over GDP that a U.S. dollar has in the United States.;World Bank, World Development Indicators database. Estimates are based on employment, population, GDP, and PPP data obtained from International Labour Organization, United Nations Population Division, Eurostat, OECD, and World Bank.;Weighted average;

Hong Kong SAR (China) GDP per Person Employed: 2021 PPP data was reported at 129,600.445 Intl $ in 2023. This records a decrease from the previous number of 129,856.935 Intl $ for 2022. Hong Kong SAR (China) GDP per Person Employed: 2021 PPP data is updated yearly, averaging 106,931.631 Intl $ from Dec 1991 (Median) to 2023, with 33 observations. The data reached an all-time high of 133,018.796 Intl $ in 2021 and a record low of 67,118.804 Intl $ in 1991. Hong Kong SAR (China) GDP per Person Employed: 2021 PPP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Hong Kong SAR (China) – Table HK.World Bank.WDI: Employment and Unemployment. GDP per person employed is gross domestic product (GDP) divided by total employment in the economy. Purchasing power parity (PPP) GDP is GDP converted to 2021 constant international dollars using PPP rates. An international dollar has the same purchasing power over GDP that a U.S. dollar has in the United States.;World Bank, World Development Indicators database. Estimates are based on employment, population, GDP, and PPP data obtained from International Labour Organization, United Nations Population Division, Eurostat, OECD, and World Bank.;Weighted average;

Macau MO: GDP: PPP:(GDP) Gross Domestic Productper Capita data was reported at 115,123.078 Intl $ in 2017. This records an increase from the previous number of 105,420.354 Intl $ for 2016. Macau MO: GDP: PPP:(GDP) Gross Domestic Productper Capita data is updated yearly, averaging 46,862.114 Intl $ from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 140,037.059 Intl $ in 2013 and a record low of 26,089.457 Intl $ in 1990. Macau MO: GDP: PPP:(GDP) Gross Domestic Productper Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Macau SAR – Table MO.World Bank.WDI: Gross Domestic Product: Purchasing Power Parity. GDP per capita based on purchasing power parity (PPP). PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current international dollars based on the 2011 ICP round.; ; World Bank, International Comparison Program database.; Weighted average;