Dataset Information

Growth and development in prefecture-level cities in China.

ABSTRACT: Nowhere has the scale and scope of urbanization been larger than in China over the last few decades. We analyze Chinese city development between the years 1996 and 2014 using data for the urbanized components of prefecture-level cities. We show that, despite much variability and fast economic and demographic change, China is undergoing transformations similar to the historical trajectory of other urban systems. We also show that the distinguishing signs of urban economies-superlinear scaling of agglomeration effects in economic productivity and economies of scale in land use-also characterize Chinese cities. We then analyze the structure of economic change in Chinese cities using a variety of metrics, characterizing employment, firms and households. Population size estimates remain a major challenge for Chinese cities, as official numbers are often reported based on the Hukou registration system. We use the information in the residuals to scaling relations for economic quantities to predict actual resident population and show that these estimates agree well with data for a subset of cities for which counts of total resident population exist. We conclude with a list of issues that must be better understood and measured to make sense of present urban development trajectories in China.

SUBMITTER: Zund D

PROVIDER: S-EPMC6719855 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Growth and development in prefecture-level cities in China.

Zünd Daniel D Bettencourt Luís M A LMA

PloS one 20190903 9

Nowhere has the scale and scope of urbanization been larger than in China over the last few decades. We analyze Chinese city development between the years 1996 and 2014 using data for the urbanized components of prefecture-level cities. We show that, despite much variability and fast economic and demographic change, China is undergoing transformations similar to the historical trajectory of other urban systems. We also show that the distinguishing signs of urban economies-superlinear scaling of ...[more]

PMID: 31479455

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Project description:BackgroundTuberculosis (TB) is still one of the most serious infectious diseases in the mainland of China. So it was urgent for the formulation of more effective measures to prevent and control it.MethodsThe data of reported TB cases in 340 prefectures from the mainland of China were extracted from the China Information System for Disease Control and Prevention (CISDCP) during January 2005 to December 2015. The Kulldorff's retrospective space-time scan statistics was used to identify the temporal, spatial and spatio-temporal clusters of reported TB in the mainland of China by using the discrete Poisson probability model. Spatio-temporal clusters of sputum smear-positive (SS+) reported TB and sputum smear-negative (SS-) reported TB were also detected at the prefecture level.ResultsA total of 10?200?528 reported TB cases were collected from 2005 to 2015 in 340 prefectures, including 5?283?983 SS- TB cases and 4?631?734 SS?+?TB cases with specific sputum smear results, 284?811 cases without sputum smear test. Significantly TB clustering patterns in spatial, temporal and spatio-temporal were observed in this research. Results of the Kulldorff's scan found twelve significant space-time clusters of reported TB. The most likely spatio-temporal cluster (RR?=?3.27, P?<? 0.001) was mainly located in Xinjiang Uygur Autonomous Region of western China, covering five prefectures and clustering in the time frame from September 2012 to November 2015. The spatio-temporal clustering results of SS+ TB and SS- TB also showed the most likely clusters distributed in the western China. However, the clustering time of SS+ TB was concentrated before 2010 while SS- TB was mainly concentrated after 2010.ConclusionsThis study identified the time and region of TB, SS+ TB and SS- TB clustered easily in 340 prefectures in the mainland of China, which is helpful in prioritizing resource assignment in high-risk periods and high-risk areas, and to formulate powerful strategy to prevention and control TB.

Project description:Coronavirus disease 2019 (COVID-19) has become a worldwide public health threat. Many associated factors including population movement, meteorological parameters, air quality and socioeconomic conditions can affect COVID-19 transmission. However, no study has combined these various factors in a comprehensive analysis. We collected data on COVID-19 cases and the factors of interest in 340 prefectures of mainland China from 1 December 2019 to 30 April 2020. Moran's I statistic, Getis-Ord Gi⁎ statistic and Kulldorff's space-time scan statistics were used to identify spatial clusters of COVID-19, and the geographically weighted regression (GWR) model was applied to investigate the effects of the associated factors on COVID-19 incidence. A total of 67,449 laboratory-confirmed cases were reported during the study period. Wuhan city as well as its surrounding areas were the cluster areas, and January 25 to February 21, 2020, was the clustering time of COVID-19. The population outflow from Wuhan played a significant role in COVID-19 transmission, with the local coefficients varying from 14.87 to 15.02 in the 340 prefectures. Among the meteorological parameters, relative humidity and precipitation were positively associated with COVID-19 incidence, while the average wind speed showed a negative correlation, but the relationship of average temperature with COVID-19 incidence inconsistent between northern and southern China. NO2 was positively associated, and O3 was negatively associated, with COVID-19 incidence. Environment with high levels of inbound migration or travel, poor ventilation, high humidity or heavy rainfall, low temperature, and high air pollution may be favorable for the growth, reproduction and spread of SARS-CoV-2. Therefore, applying appropriate lockdown measures and travel restrictions, strengthening the ventilation of living and working environments, controlling air pollution and making sufficient preparations for a possible second wave in the relatively cold autumn and winter months may be helpful for the control and prevention of COVID-19. Graphical abstract Unlabelled Image

Project description:BackgroundAs one of the most serious types of coronary heart disease, ST-elevation myocardial infarction (STEMI) faces huge challenges in the equal management and care of patients due to its life-threatening and time-critical condition. Health inequalities such as sex and age differences in STEMI care have been reported from developed countries. However, limited outcomes have been investigated and the major drivers of inequality are still unclear, especially in under-developed areas. This study aimed to explore the major drivers of health inequalities in STEMI care before implementation of a new regional network in the south-west of China.MethodsPrefecture-level data of STEMI patients before the implementation of a regional network were analysed retrospectively. Drivers of inequality were identified from six social determinants of health, namely area of residence, ethnicity, sex, age, education and occupation. Outcomes of STEMI care included timely presentation, reperfusion therapy, timely reperfusion therapy, heart failure, inpatient mortality, length of hospital stay, hospital costs, and various intervals of ischaemic time.ResultsA total of 376 STEMI patients in the research area before implementation of the STEMI network were included. Compared with urban residents, rural patients were significantly less likely to have timely presentation (odds ratio [OR]=0.47, 95% CI: 0.28-0.80, P=.004) and timely reperfusion therapy (OR=0.32, 95% CI: 0.14-0.70, P=.005). Rural residents were less likely to present to hospital promptly than urban residents (HR=0.65, 95% CI=0.52-0.82, P<.001). In the first 3 hours of percutaneous coronary intervention (PCI) reperfusion delay and first 6 hours of total ischaemic time, rural patients had a significantly lower probability to receive prompt PCI (hazard ratio [HR]=0.40, 95% CI: 0.29-0.54, P<.001) and reperfusion therapy (HR=0.37, 95% CI: 0.25-0.56, P<.001) compared to urban patients.ConclusionRural residents were a major vulnerable group before implementation of the regional STEMI network. No obvious inequalities in ethnicity, sex, age, education or occupation existed in STEMI care in Chuxiong Prefecture of China.

Dataset Information

Growth and development in prefecture-level cities in China.

Publications

Growth and development in prefecture-level cities in China.

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