The "Major Cities" layer is derived from the "World Cities" dataset provided by ArcGIS Data and Maps group as part of the global data layers made available for public use. "Major cities" layer specifically contains National and Provincial capitals that have the highest population within their respective country. Cities were filtered based on the STATUS (“National capital”, “National and provincial capital”, “Provincial capital”, “National capital and provincial capital enclave”, and “Other”). Majority of these cities within larger countries have been filtered at the highest levels of POP_CLASS (“5,000,000 and greater” and “1,000,000 to 4,999,999”). However, China for example, was filtered with cities over 11 million people due to many highly populated cities. Population approximations are sourced from US Census and UN Data. Credits: ESRI, CIA World Factbook, GMI, NIMA, UN Data, UN Habitat, US Census Bureau Disclaimer: The designations employed and the presentation of material at this site do not imply the expression of any opinion whatsoever on the part of the Secretariat of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries.

China Number of Prefecture Level City: Population 0.5 - 1 Million data was reported at 86.000 Unit in 2020. This records a decrease from the previous number of 88.000 Unit for 2019. China Number of Prefecture Level City: Population 0.5 - 1 Million data is updated yearly, averaging 103.000 Unit from Dec 1978 (Median) to 2020, with 17 observations. The data reached an all-time high of 111.000 Unit in 2007 and a record low of 35.000 Unit in 1978. China Number of Prefecture Level City: Population 0.5 - 1 Million data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Socio-Demographic – Table CN.GE: No of Prefecture Level City by Population.

Clarifying the association between city population size and older adults’ health is vital in understanding the health disparity across different cities in China. Using a nationally representative dataset, this study employed Multilevel Mixed-effects Probit regression models and Sorting Analysis to elucidate this association, taking into account the sorting decisions made by older adults. The main results of the study include: (1) The association between city population size and the self-rated health of older adults shifts from a positive linear to an inverted U-shaped relationship once individual socioeconomic status is controlled for; the socioeconomic development of cities, intertwined with the growth of their populations, plays a pivotal role in yielding health benefits. (2) There is a sorting effect in older adults’ residential decisions; compared to cities with over 5 million residents, unobserved factors result in smaller cities hosting more less-healthy older adults, which may cause overestimation of health benefits in cities with greater population size. (3) The evolving socioeconomic and human-made environment resulting from urban population growth introduces health risks for migratory older adults but yields benefits for those with local resident status who are male, aged over 70, and have lower living standards and socioeconomic status. And (4) The sorting effects are more pronounced among older adults with greater resources supporting their mobility or those without permanent local resident status. Thus, policymakers should adapt planning and development strategies to consider the intricate relationship between city population size and the health of older adults.

BackgroundAs the world’s most rapidly urbanizing country, China now faces mounting challenges from growing inequalities in the built environment, including disparities in access to essential infrastructure and diverse functional facilities. Yet these urban inequalities have remained unclear due to coarse observation scales and limited analytical scopes. In this study, we present the first building-level functional map of China, covering 110 million individual buildings across 109 cities using 69 terabytes of 1-meter resolution multi-modal satellite imagery. The national-scale map is validated by government reports and 5,280,695 observation points, showing strong agreement with external benchmarks. This enables the first nationwide, multi-dimensional assessment of inequality in the built environment across city tiers, geographical regions, and intra-city zones.About dataBased on the Paraformer framework that we proposed previously, we produced the first nationwide building-level functional map of urban China, processing over 69 TB of satellite data, including 1-meter Google Earth optical imagery (https://earth.google.com), 10-meter nighttime lights (SGDSAT-1) (https://sdg.casearth.cn/en), and building height data (CNBH-10m) (https://zenodo.org/records/7827315). Labels were derived from: (1) Building footprint data, including the CN-OpenData (https://doi.org/10.11888/Geogra.tpdc.271702) and the East Asia Building Dataset (https://zenodo.org/records/8174931); and (2) Land use and AOI data used for constructing urban functional annotation are retrieved from OpenStreetMap (https://www.openstreetmap.org) and EULUC-China dataset (https://doi.org/10.1016/j.scib.2019.12.007). The first 1-meter resolution national-scale land-cover map used to conduct the accessibility analysis is available in our previous study: SinoLC-1 (https://doi.org/10.5281/zenodo.7707461). The housing inequality and infrastructure allocation analysis was conducted based on the 100-meter gridded population dataset from China's seventh census (https://figshare.com/s/d9dd5f9bb1a7f4fd3734?file=43847643).This version of the data includes (1) Building-level functional maps of 109 Chinese cities, and (2) In-situ validation point sets. The building-level functional maps of 109 Chinese cities are organized in the ESRI Shapefile format, which includes five components: “.cpg”, “.dbf”, “.shx”, “.shp”, and “.prj” files. These components are stored in “.zip” files. Each city is named “G_P_C.zip,” where “G” explains the geographical region (south, central, east, north, northeast, northwest, and southwest of China) information, “P” explains the provincial administrative region information, and “C” explains the city name. For example, the building functional map for Wuhan City, Hubei Province is named “Central_Hubei_Wuhan.zip”.Furthermore, each shapefile of a city contains the building functional types from 1 to 8, where the corresponding relationship between the values and the building functions is shown below:Residential buildingCommercial buildingIndustrial buildingHealthcare buildingSport and art buildingEducational buildingPublic service buildingAdministrative buildingAbout validationGiven the importance of accurate mapping for downstream analysis, we conducted a comprehensive evaluation using government reports and in situ validation data outlined in the Data Section. This evaluation comprised two parts. First, a statistical-level evaluation was performed for each city based on official reports from the China Urban-Rural Construction Statistical Yearbook (https://www.mohurd.gov.cn/gongkai/fdzdgknr/sjfb/tjxx/jstjnj/index.html) and China Statistical Yearbook (https://www.stats.gov.cn/sj/ndsj/2023/indexch.htm). Second, a building-level geospatial evaluation was conducted by using 5.28 million field-observed points from Amap Inc. (provided in this data version of "Validation_in-situ_points.zip"), and a confusion matrix was calculated to compare the in situ points with the mapped buildings at the same location. The "Validation_in-situ_points.zip" includes the original point sets of each city, named as the city name (e.g., Wuhan.shp and corresponding “.cpg”, “.dbf”, “.shx”, and “.prj” files).

Our data are mainly from two datasets compiled by the National Bureau of Statistics of China and one dataset we compiled. Industry-related variables are from the Chinese Industrial Enterprises Database, a longitudinal micro-level database based on annual surveys of manufacturing, mining, and construction firms with at least five million yuan in annual sales. This database is the most comprehensive source of information on industrial firms and has been used by some leading academic papers (e.g., Hsieh and Klenow, 2009; Song et al., 2011) . In this study, we focus on the manufacturing sector and construct a panel dataset for 30 industries in 268 cities during 1998–2009. City-related control variables are mainly from the Statistical Bulletin for each city, China City Statistical Yearbook, and Statistical Yearbook for each province. These sources are the most comprehensive statistics on the social and economic development of Chinese prefectural cities. Statistics include, for example, GDP, government expenditure, population, employment, and education. Politician profile data are compiled from www.people.cn, XinhuaNet, and Baidu Encyclopedia . The data contain the names of the municipal party committee secretary and the mayor of 268 cities during 1998–2009. The data also contain the previous position of each secretary and mayor. The data are cross-checked with other sources to ensure quality.

Context

Coronaviruses are a large family of viruses found in both animals and humans. Some infect people and are known to cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS).

A novel coronavirus (CoV) is a new strain of coronavirus that has not been previously identified in humans. The new, or “novel” coronavirus, now called 2019-nCoV, had not previously detected before the outbreak was reported in Wuhan, China in December 2019.

Short story: On December 31, 2019, the WHO was informed of an outbreak of “pneumonia of unknown cause” detected in Wuhan City, Hubei Province, China – the seventh-largest city in China with 11 million residents. As of January 23, there are over 800 cases of 2019-nCoV confirmed globally, including cases in at least 20 regions in China and nine countries/territories. The first reported infected individuals, some of whom showed symptoms as early as December 8, were discovered to be among stallholders from the Wuhan South China Seafood Market. Subsequently, the wet market was closed on Jan 1. The virus causing the outbreak was quickly determined to be a novel coronavirus. On January 10, gene sequencing further determined it to be the new Wuhan coronavirus, namely 2019-nCoV, a betacoronavirus, related to the Middle Eastern Respiratory Syndrome virus (MERS-CoV) and the Severe Acute Respiratory Syndrome virus (SARS-CoV). However, the mortality and transmissibility of 2019-nCoV are still unknown, and likely to vary from those of the prior referenced coronaviruses.

See more information on the webpage of World Health Organization

Content

John Hopkins University Google Sheet of time series confirmed|recovered|death case numbers converted to CSV format.

The data operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE).

See also GitHub.

Track virus here.

Acknowledgements

Thanks to
- JHU CCSE
- WHO
- Centers for Disease Control and Prevention (CDC)
- European Centre for Disease Prevention and Control (ECDC)
- DXY
- National Health Commission of the People's Republic of China (NHC)

Abstract

Gallup Worldwide Research continually surveys residents in more than 150 countries, representing more than 98% of the world's adult population, using randomly selected, nationally representative samples. Gallup typically surveys 1,000 individuals in each country, using a standard set of core questions that has been translated into the major languages of the respective country. In some regions, supplemental questions are asked in addition to core questions. Face-to-face interviews are approximately 1 hour, while telephone interviews are about 30 minutes. In many countries, the survey is conducted once per year, and fieldwork is generally completed in two to four weeks. The Country Dataset Details spreadsheet displays each country's sample size, month/year of the data collection, mode of interviewing, languages employed, design effect, margin of error, and details about sample coverage.

Gallup is entirely responsible for the management, design, and control of Gallup Worldwide Research. For the past 70 years, Gallup has been committed to the principle that accurately collecting and disseminating the opinions and aspirations of people around the globe is vital to understanding our world. Gallup's mission is to provide information in an objective, reliable, and scientifically grounded manner. Gallup is not associated with any political orientation, party, or advocacy group and does not accept partisan entities as clients. Any individual, institution, or governmental agency may access the Gallup Worldwide Research regardless of nationality. The identities of clients and all surveyed respondents will remain confidential.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING AND DATA COLLECTION METHODOLOGY With some exceptions, all samples are probability based and nationally representative of the resident population aged 15 and older. The coverage area is the entire country including rural areas, and the sampling frame represents the entire civilian, non-institutionalized, aged 15 and older population of the entire country. Exceptions include areas where the safety of interviewing staff is threatened, scarcely populated islands in some countries, and areas that interviewers can reach only by foot, animal, or small boat.

Telephone surveys are used in countries where telephone coverage represents at least 80% of the population or is the customary survey methodology (see the Country Dataset Details for detailed information for each country). In Central and Eastern Europe, as well as in the developing world, including much of Latin America, the former Soviet Union countries, nearly all of Asia, the Middle East, and Africa, an area frame design is used for face-to-face interviewing.

The typical Gallup Worldwide Research survey includes at least 1,000 surveys of individuals. In some countries, oversamples are collected in major cities or areas of special interest. Additionally, in some large countries, such as China and Russia, sample sizes of at least 2,000 are collected. Although rare, in some instances the sample size is between 500 and 1,000. See the Country Dataset Details for detailed information for each country.

FACE-TO-FACE SURVEY DESIGN

FIRST STAGE In countries where face-to-face surveys are conducted, the first stage of sampling is the identification of 100 to 135 ultimate clusters (Sampling Units), consisting of clusters of households. Sampling units are stratified by population size and or geography and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size, otherwise simple random sampling is used. Samples are drawn independent of any samples drawn for surveys conducted in previous years.

There are two methods for sample stratification:

METHOD 1: The sample is stratified into 100 to 125 ultimate clusters drawn proportional to the national population, using the following strata: 1) Areas with population of at least 1 million 2) Areas 500,000-999,999 3) Areas 100,000-499,999 4) Areas 50,000-99,999 5) Areas 10,000-49,999 6) Areas with less than 10,000

The strata could include additional stratum to reflect populations that exceed 1 million as well as areas with populations less than 10,000. Worldwide Research Methodology and Codebook Copyright © 2008-2012 Gallup, Inc. All rights reserved. 8

METHOD 2:

A multi-stage design is used. The country is first stratified by large geographic units, and then by smaller units within geography. A minimum of 33 Primary Sampling Units (PSUs), which are first stage sampling units, are selected. The sample design results in 100 to 125 ultimate clusters.

SECOND STAGE

Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day, and where possible, on different days. If an interviewer cannot obtain an interview at the initial sampled household, he or she uses a simple substitution method. Refer to Appendix C for a more in-depth description of random route procedures.

THIRD STAGE

Respondents are randomly selected within the selected households. Interviewers list all eligible household members and their ages or birthdays. The respondent is selected by means of the Kish grid (refer to Appendix C) in countries where face-to-face interviewing is used. The interview does not inform the person who answers the door of the selection criteria until after the respondent has been identified. In a few Middle East and Asian countries where cultural restrictions dictate gender matching, respondents are randomly selected using the Kish grid from among all eligible adults of the matching gender.

TELEPHONE SURVEY DESIGN

In countries where telephone interviewing is employed, random-digit-dial (RDD) or a nationally representative list of phone numbers is used. In select countries where cell phone penetration is high, a dual sampling frame is used. Random respondent selection is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to reach a person in each household, spread over different days and times of day. Appointments for callbacks that fall within the survey data collection period are made.

PANEL SURVEY DESIGN

Prior to 2009, United States data were collected using The Gallup Panel. The Gallup Panel is a probability-based, nationally representative panel, for which all members are recruited via random-digit-dial methodology and is only used in the United States. Participants who elect to join the panel are committing to the completion of two to three surveys per month, with the typical survey lasting 10 to 15 minutes. The Gallup Worldwide Research panel survey is conducted over the telephone and takes approximately 30 minutes. No incentives are given to panel participants. Worldwide Research Methodology and Codebook Copyright © 2008-2012 Gallup, Inc. All rights reserved. 9

Research instrument

QUESTION DESIGN

Many of the Worldwide Research questions are items that Gallup has used for years. When developing additional questions, Gallup employed its worldwide network of research and political scientists1 to better understand key issues with regard to question development and construction and data gathering. Hundreds of items were developed, tested, piloted, and finalized. The best questions were retained for the core questionnaire and organized into indexes. Most items have a simple dichotomous ("yes or no") response set to minimize contamination of data because of cultural differences in response styles and to facilitate cross-cultural comparisons.

The Gallup Worldwide Research measures key indicators such as Law and Order, Food and Shelter, Job Creation, Migration, Financial Wellbeing, Personal Health, Civic Engagement, and Evaluative Wellbeing and demonstrates their correlations with world development indicators such as GDP and Brain Gain. These indicators assist leaders in understanding the broad context of national interests and establishing organization-specific correlations between leading indexes and lagging economic outcomes.

Gallup organizes its core group of indicators into the Gallup World Path. The Path is an organizational conceptualization of the seven indexes and is not to be construed as a causal model. The individual indexes have many properties of a strong theoretical framework. A more in-depth description of the questions and Gallup indexes is included in the indexes section of this document. In addition to World Path indexes, Gallup Worldwide Research questions also measure opinions about national institutions, corruption, youth development, community basics, diversity, optimism, communications, religiosity, and numerous other topics. For many regions of the world, additional questions that are specific to that region or country are included in surveys. Region-specific questions have been developed for predominantly Muslim nations, former Soviet Union countries, the Balkans, sub-Saharan Africa, Latin America, China and India, South Asia, and Israel and the Palestinian Territories.

The questionnaire is translated into the major conversational languages of each country. The translation process starts with an English, French, or Spanish version, depending on the region. One of two translation methods may be used.

METHOD 1: Two independent translations are completed. An independent third party, with some knowledge of survey research methods, adjudicates the differences. A professional translator translates the final version back into the source language.

METHOD 2: A translator