Municipalities and prefecture-level cities are not each a 'city' in the strictest sense of the term, but instead an administrative unit comprising, typically, both the urban core (a city in the strict sense) and surrounding rural or less-urbanized areas.
Prefecture-level cities nearly always contain multiple counties (县), county-level cities, and other such sub-divisions. To distinguish a prefecture-level city from its actual urban area (city in the strict sense), the term \"市区\" (shì qū; \"urban area\") is used. However, even this term often encompasses large suburban regions often greater than 3,000 square kilometres (1,000 sq mi), sometimes only the urban core whereas the agglomeration overtake the city limits. Thus, the \"urban core\" would be roughly comparable to the American term \"city limit\", the \"shì qū\", or \"urban area\", would be roughly comparable to \"metropolitan area\", and the municipality is a political designation defining regions under control of a municipal government, which has no comparable designation.
aDirect-administered Municipalities.bSub-provincial cities as provincial capitals.cSeparate state-planning cities.1Special economic-zone Cities.2Open Coastal Cities.3Prefecture capital status established by Heilongjiang Province and not recognized by Ministry of Civil Affairs. Disputed by Oroqen Autonomous Banner, Hulunbuir, Inner Mongolia as part of it.4Only administers islands and waters in South China Sea and have no urban core comparable to typical cities in China.5The claimed province of Taiwan no longer have any internal division announced by Ministry of Civil Affairs of PRC, due to lack of actual jurisdiction. See Template:Administrative divisions of Taiwan instead.
If you enjoy the happening atmosphere of big and rapidly growing cities, then China is the place to come. Feel the buzz of the urbanization rush in the fastest developing country in the history of the planet.
Chengdu is an exception among large Chinese cities. The largest city in mostly mountainous or arid West China, it is a concentration of the population of the fertile Sichuan Basin. The pace of life is the most relaxed of China's large cities.
Though industry does play a part in Chengdu's economy and there has been significant domestic investment, its growth is mainly a result of the tide of urbanization driving the rural population towards the cities in search of a better life. With Chengdu being the lone large city in huge Sichuan Province, the province's over 80 million people gravitate there.
Chongqing is famous for its fog and mountains, and the Yangtze River cruise. It's the largest of China's four municipalities besides Beijing, Tianjin, and Shanghai, though by contrast its population is mostly rural. Huge infrastructure and industrial investment has made it one of China's 10 largest cities in the last 5 years.
It's the poorest of China's large cities, dominated by low-wage-earning migrant factory workers. Over a million overseas Chinese and residents of Hong Kong, Macau and Taiwan came from Dongguan. Tourism is virtually unheard-of there, apart from for those returning to their roots.
Wuhan is an interesting large city, plum in the center of the heavily-populated half of China. It once felt less modernized than China's coastal cities, but it is now one of China's main high-tech, education, and financial centers.
In this study, we revised the reported data in Wuhan based on several assumptions to estimate the actual number of confirmed cases considering that perhaps not all cases could be detected and reported in the complex situation there. Then we used the equation derived from the Susceptible-Exposed-Infectious-Recovered (SEIR) model to calculate R0 from January 24, 2020 to February 13, 2020 in 11 major cities in China for comparison. With the calculation results, we conducted correlation analysis and regression analysis between R0 and temperature and humidity for four major cities in China to see the association between the transmissibility of COVID-19 and the weather variables.
It was estimated that the cumulative number of confirmed cases had exceeded 45 000 by February 13, 2020 in Wuhan. The average R0 in Wuhan was 2.7, significantly higher than those in other cities ranging from 1.8 to 2.4. The inflection points in the cities outside Hubei Province were between January 30, 2020 and February 3, 2020, while there had not been an obvious downward trend of R0 in Wuhan. R0 negatively correlated with both temperature and humidity, which was significant at the 0.01 level.
This paper measured the transmissibility of COVID-19 with R0 and analyzed its correlation with temperature and humidity. First, we revised the epidemiological data in Wuhan to make R0 more accurate. Second, we calculated R0 and compared the average value and developing trend of R0 in 11 cities including Wuhan. Third, we conducted correlation and regression analysis between R0 and temperature and humidity to see the association between R0 and weather.
As for other cities outside Hubei Province, it is assumed that the officially reported data is accurate. Based on the relationship ln[Y(t)]=λt, we performed logarithmic fitting between the cumulative number of diagnoses and time and inferred that transmission started on December 27, 2019 outside Hubei Province.
We collected the data of the daily average temperature and relative humidity from January 24, 2020 to February 13, 2020 in four Chinese major cities which were Beijing (the capital of China), Shanghai (the municipality of China), Guangzhou (the capital of Guangdong Province) and Chengdu (the capital of Sichuan Province). We calculated absolute humidity from the temperature and relative humidity.
As can be seen from Fig. 2, R0 in Wuhan is significantly higher than those in cities outside Hubei Province. Besides, R0 in cities outside Hubei Province has begun to decrease, while R0 in Wuhan does not show a significant downward trend.
For a more detailed analysis, the average basic reproduction number of the 21 days in each city and the date of the inflection point are presented in Table 1. The cities are listed by the average R0 from high to low. The inflection point refers to the day after which R0 shows a downward trend.
It can be seen from Table 1 that the average R0 in Wuhan far exceeds those in other cities, which is 0.3 higher than that in Chongqing, the city which ranks second. It should be noted that the average R0 in Wuhan is calculated with the revised data to better fit the real value. In fact, the average basic reproduction number calculated with the officially reported data is also much higher than those in other cities, which is 2.4.
The inflection points of cities outside Hubei Province range from January 30 to February 3, while the inflection point of Wuhan had not appeared because the number of confirmed cases had kept increasing rapidly by February 13, 2020. Although R0 in Wuhan reaches a peak on February 12, it cannot be determined that February 12 is the inflection point. Because since that day, Hubei Province has included the number of clinically diagnosed cases into the number of confirmed cases. The modification of the diagnostic criteria leads to a sudden increase of newly confirmed patients, which explains why R0 is particularly high on February 12.
The correlation was significant in Beijing, Shanghai, and Chengdu, and thus we conducted linear regression on the data of the three cities as well as the summary of all cities. The linear regression results are presented in Table 5. Replace a and b in the equation R0=a+bRH (where RH is relative humidity) with the corresponding actual values in Table 5, and the correlation between R0 and relative humidity can be expressed with a quantitative method.
We conducted linear regression on the data of Beijing, Shanghai, Guangzhou as well as the summary of all cities. The linear regression results are presented in Table 7. Replace a and b in the equation R0=a+bAH (where AH is absolute humidity) with the corresponding actual values in Table 7, and the correlation between R0 and absolute humidity can be expressed with a quantitative method.
Second, although Beijing, Shanghai, Guangzhou, and Chengdu are all first-tier cities in China with many similarities like buildings, there are some differences between Chengdu and the other cities that may help explain the positive correlation with relative humidity. Chengdu is located in the southwest of China, the west of Sichuan Basin and the hinterland of Chengdu Plain with a subtropical monsoon humid climate, different from Beijing which has a warm temperate semi-humid continental monsoon climate. The air is more humid in Chengdu than that in Beijing. The climate in Chengdu is similar to the subtropical monsoon climate in Shanghai and Guangzhou, but Chengdu is an inland city while Shanghai and Guangzhou are coastal cities.
In this paper, we calculated and compared the basic reproduction number of COVID-19 in 11 major cities in China and analyzed its association with temperature and humidity in Beijing, Shanghai, Guangzhou, and Chengdu to find out the transmissibility of COVID-19 in different cities and its changing trend with the weather. We conclude that the spread of COVID-19 is most violent in Wuhan, Hubei Province and R0 negatively correlates with temperature, relative humidity, and absolute humidity. Therefore, effective action should be taken to control the transmission of COVID-19 especially in Hubei Province and the transmissibility is predicted to be reduced as the weather warms.
Objective: The aim of this study was to explore the possibility of using various social media platforms to investigate the existence of the phenomenon of youth social withdrawal in 3 major cities in China. 1e1e36bf2d