Should we remain hopeful? The key 8 weeks: Spatiotemporal epidemic characteristics of COVID-19 in Sichuan Province and its comparative analysis with other provinces in China and global epidemic trends

Should we remain hopeful? The key 8 weeks: Spatiotemporal epidemic characteristics of COVID-19 in Sichuan Province and its comparative analysis with other provinces in China and global epidemic trends | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research article Should we remain hopeful? The key 8 weeks: Spatiotemporal epidemic characteristics of COVID-19 in Sichuan Province and its comparative analysis with other provinces in China and global epidemic trends Xinyin Xu, Jing Zeng, Runyou Liu, Yang Liu, Xiaobo Zhou, Lijun Zhou, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-20551/v4 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Nov, 2020 Read the published version in BMC Infectious Diseases → Version 4 posted 7 You are reading this latest preprint version Show more versions Abstract Background: The COVID-19 spread worldwide quickly. Exploring the epidemiological characteristics could provide a basis for responding to imported cases abroad and to formulate prevention and control strategies in areas where COVID-19 is still spreading rapidly. Methods: The number of confirmed cases, daily growth, incidence and length of time from the first reported case to the end of the local cases (i.e., non-overseas imported cases) were compared by spatial (geographical) and temporal classification and visualization of the development and changes of the epidemic situation by layers through maps. Results: In the first wave, a total of 539 cases were reported in Sichuan, with an incidence rate of 0.6462/100,000. The closer to Hubei the population centres were, the more pronounced the epidemic was. The peak in Sichuan Province occurred in the second week. Eight weeks after the Wuhan lockdown, the health crisis had eased. The longest epidemic length at the city level in China (except Wuhan, Taiwan, and Hong Kong) was 53 days, with a median of 23 days. Spatial autocorrelation analysis of China showed positive spatial correlation (Moran's Index >0, p<0.05). Most countries outside China began to experience a rapid rise in infection rates 4 weeks after their first case. Some European countries experienced that rise earlier than the USA. The pandemic in Germany, Spain, Italy, and China took 28, 29, 34, and 18 days, respectively, to reach the peak of daily infections, after their daily increase of up to 20 cases. During this time, countries in the African region and Southeast Asian region were at an early stage of infections, those in the Eastern Mediterranean region and region of the Americas were in a rapid growth phase. Conclusions: After the closure of the outbreak city, appropriate isolation and control measures in the next 8 weeks were key to control the outbreak, which reduced the peak value and length of the outbreak. Some countries with improved epidemic situations need to develop a continuous "local strategy at entry checkpoints" to to fend off imported COVID-19. Epidemiology Infectious Diseases COVID-19 SARS-CoV-2 Sichuan Province China global temporal and spatial distribution epidemiological characteristics Spatial autocorrelation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Background Faced with unknown infectious diseases, policymakers are always looking for the best point of prevention and control, balancing between underestimating and overestimating the risk. In December 2019, there were reports of unexplained pneumonia infections in Wuhan, China. 1 On December 31, experts from the Chinese Center for Disease Control and Prevention (CDC) went to Wuhan to learn about the situation and collected samples from patients. 2 On January 3, 2020, scientists from the National Institute for Viral Disease Control and Prevention identified the sequence of novel β-genus coronaviruses from specimens taken from patients in Wuhan and later published this information to the public. The study found that the patients were infected with β-genus coronaviruses with genetic characteristics different from SARS-CoV and MERS-CoV that was temporarily named the 2019 novel coronavirus (2019-nCoV) and later renamed "severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease caused by it is called coronavirus disease (COVID-19). 3,4 Subsequently, cases of COVID-19 were reported in 31 provinces of China, Hong Kong, Macao, Taiwan and other countries. Facing the grim situation of the global COVID-19 outbreaks, this study focuses on analysing the overall epidemic characteristics of Sichuan Province, which is close to Wuhan in the east. This study also analysed the overall epidemic characteristics of China, selected key dates for comparison, considered the epidemic laws, and analysed the global epidemic trends to provide a basis for China to cope with imported cases abroad and for other countries to grasp the timing of prevention and control to formulate appropriate strategies. Methods To reflect the actual geographical distribution risk of confirmed cases in Sichuan Province, the current residential addresses of confirmed cases from the Sichuan COVID-19 Surveillance System were selected for distribution analysis. For comparison with neighbouring provinces, the situation of confirmed cases reported by the National Health Commission, 5 Hubei Province, 6 and the health commissions of other provinces were analysed using the address of the reporting unit (usually the hospital or CDC). Data from various countries were taken from the WHO COVID-19 Daily Report published since January 21. 7 The number of cases in China before that first daily report and the first case information in Thailand, Japan, the Republic of Korea, and the USA, mentioned in the previous report of WHO, was taken from their national government websites. 8-11 The number of counties and districts of the cities in Sichuan Province were taken from the Statistical Yearbook of Sichuan Province. 12 The population of various cities in China were taken from the Statistical Yearbook of kinds of provinces. The characteristics of cumulative confirmed cases, daily new cases, morbidity, etc. were compared based on temporal and spatial factors; the length of time from the first case report to the end of the local cases (i.e., nonforeign imported cases), abbreviated hereafter as "epidemic length", was analysed to explore the influencing factors of prevention and control of the outbreaks. Key analysis times and units were set based on key dates of policy and disease incubation periods. The epidemic maps of Sichuan and China were drawn at different times and spaces by SAS software (SAS studio https://welcome.oda.sas.com/) to directly display the development and changes of the epidemic situation and examine the epidemic law by layers. Confirmed case scatter plots, column diagrams and line diagrams were also used to display the time trend. Spatial stratified heterogeneity of incidence rate in China was analysed by R software using the package “Geodetector” 13,14 and was described through q statistic. The city incidence rate was considered as a dependent variable and the province was considered as an explanatory variable in this study. Furthermore, the spatial autocorrelation was analysed by Arcgis software and was described through the Global Moran's Index 15,16 and hot spot analysis. Global Moran's Index was proposed by the Australian statistician Patrick Alfred Pierce Moran 15 to assess the overall pattern and spatial agglomeration. The hot spot analysis could identify statistically significant spatial clusters of high values (hot spots). Results Prevalence in Sichuan Province (non-foreign imported cases) Geographical distribution On March 4, Sichuan Province ended the increase in confirmed cases on the mainland (the first wave). Each city of Sichuan Province (21 in total) reported confirmed cases, with a total mainland case number of 539 and an incidence rate of 0.6462/100,000. Analysis of confirmed cases was based on their current address, with 48.33% in urban and 51.67% in rural areas. The top five cities with confirmed case numbers were Chengdu, Ganzi, Dazhou, Nanchong, and Guang'an. The cities with top five incidence rate were Ganzi, Panzhihua, Guang'an, Chengdu, and Dazhou (Table 1). Moreover, the confirmed cases were distributed in 103 counties, accounting for 56.28% of Sichuan Province (183 in total). Among them, 3 cities (out of 21 cities) found cases reported in all their counties. Geographically, the regions with the highest number of cases and counties were located in the eastern part of Sichuan Province, which is directly adjacent to Chongqing and closer to Hubei Province. Although the number of confirmed cases in the eastern counties was relatively high, a small number of counties in the western part also had a high incidence (Table 1, Figure 1, Figure 2). Time distribution The time of the first confirmed case report in the 21 cities of Sichuan Province mainly came one week after the Wuhan lockdown (January 24-January 31). 1 7 At this stage, the current addresses of the first confirmed cases were distributed in 70 counties, accounting for 68% of the reported counties (103 in total) in Sichuan Province on March 4. The maximum number of cases was on the third and fourth days after the Wuhan lockdown (January 26-27). During those two days, 28 counties (27%) reported their first case. The rapid increase in the confirmed number was concentrated in the four weeks after the closure of Wuhan (January 24-February 20), and the increase was particularly obvious in the first two weeks (Figure 3). Prevalence in neighbouring provinces of Sichuan and other parts of China Spatiotemporal distribution: On December 31, 2019, 27 cases were first reported on the official website of Hubei Province, all in Wuhan; on January 23, 2020, Hubei announced that it had entered a Grade II response and the Wuhan lockdown began. 1 8 Of the 835 cases reported nationwide (including 5 in Hong Kong, Macao, and Taiwan), 549 were in Hubei (495 of these in Wuhan) and 267 were in all provinces outside Hubei. A total of 15 cases in Sichuan Province were distributed in 7 cities (the first imported case was diagnosed on January 21), ranking 9th in China. The number of cases in Chongqing, adjacent in eastern Sichuan, was the only neighbouring province with more cases than Sichuan (27 cumulative cases). The epidemic situation in Yunnan and Guizhou adjacent in southern Sichuan was relatively light. Twenty-eight days later, on February 20, a total of 75,993 cases (including Hong Kong, Macao, and Taiwan, which accounted for 102 cases, the total number of which were corrected based on Hubei's revision) were reported, of which 63,088 were in Hubei (45,346 of these were in Wuhan). The revision was originally made by the Health Commission of Hubei Province website on February 21, raising the total to 12,905 cases in provinces outside Hubei (including in Hong Kong, Macao, and Taiwan). A total of 525 cases in Sichuan Province were distributed in all 21 cities, ranking 11th in China, next to Chongqing. Fourteen days later, on March 5, a total of 80,710 cases (including 158 cases in Hong Kong, Macao, and Taiwan) were reported nationwide, including 67,592 cases in Hubei (49,797 of these in Wuhan) and a total of 13,118 cases in provinces outside Hubei (including Hong Kong, Macau, and Taiwan). A total of 539 cases in Sichuan were distributed in all 21 cities, still ranking 11th in China. The number of new cases nationwide fell below one hundred the next day. The concentrated outbreak time of confirmed cases was the first 4 weeks after the implementation of the lockdown measures (Figure 4). On December 31, cases were only reported in Wuhan. Later, on January 19, the first confirmed case was reported outside Wuhan in Shenzhen of Guangdong Province. From December 31 to January 23 (i.e., 118 cities reported cases on the day of Wuhan lockdown), the number of confirmed cases increased by a factor of 31. In the next four weeks after the Wuhan lockdown, 90% of the cities nationwide were affected, and the number of cases increased by a factor of 91, compared with January 23. In the fifth and sixth weeks, the number of newly confirmed cases and the number of reported areas slowed down significantly, with an increase of only a factor of 0.06 (63 cities except Wuhan increased with a total of 473 cases, and the average daily increase was 0.53 cases/city). In the 7th week (March 5-March 12), there was only a small increase of 62 cases in 10 cities of China except for Wuhan. The q statistics values of spatial stratified heterogeneity of city incidence among provinces in China (excluding Hong Kong, Macao and Taiwan) on January 23, February 20, March 5 and March 12 were 0.16, 0.37, 0.35 and 0.35 (all the p value <0.05), which revealed that the heterogeneity existed and the province as a space factor explained 16%, 37%, 35% and 35% of the city incidence. The Global Moran's Index 15 of spatial autocorrelation analysis on January 23, February 20, March 5 and March 12 were 0.02, 0.20, 0.18 and 0.18 (all the p value <0.05). All the Global Moran's Index values were positive expressed that the epidemic in China tending to cluster spatially. The results also showed that from January 23 to February 20, the epidemic situation was rapidly gathering in space. Besides, the spread of the epidemic slowed down after February 20, and the spatial concentration decreased slightly. Hot spot analysis further demonstrated that the epidemic gathered in Hubei, Hunan, Jiangxi Provinces on February 20 and did not expand, which suggested that the spread of the epidemic was under effective control after February 20 (Figure 5). Distribution of the epidemic length in different region s : On March 12, in the seventh week after the closure of Wuhan, the growth of local cases in the first wave ended in all the cities in China (excluding Wuhan, Taiwan and Hong Kong). Based on statistics at the city level (the districts of municipalities were analysed as a city unit according to the high population density of municipalities), the length calculated by the date of occurrence and the end of local cases in a total of 413 cities were used for analysis. The study shows that the longest date length from the first case confirmed to zero growth in each city was 53 days, and the average and median lengths were 22 and 23 days, respectively. The 1 st quartile and 3 rd quartile were 15 and 28 days, respectively. When the length was 21 days, the frequency of the cities was highest at approximately 26 cities (6.3% in 413 cities). Further analysis of the epidemic length at the county level (regional unit) in Sichuan Province included a total of 103 counties that had epidemics. The results showed that there was no local case increase after March 4. The largest date length from the first confirmed case to zero growth was 33 days, with a mean and median of 9 days. The 1 st quartile and 3 rd quartile were 1 and 16 days, respectively. The highest city frequency of the date length was 1 day for approximately 31 cities (30% in 103 cities) (Figure 6). Taking the migration from Hubei during the two weeks before its lockdown as a possible high-risk factor, this study compared the provinces for which the migration rank was close to Sichuan Province and found that the peak time in Sichuan Province was earlier (occured in the second week according to the weekly analysis, ranked the first in common) and the peak value was lower (26.7 cases average daily increment in that week, only higher than Shaanxi) (Figure 7). According to the daily analysis, the peak of Sichuan appeared only one day later than Zhejiang among the 7 provinces, but its peak value was much lower than Zhejiang Province (35 cases compared to 132 cases). Global situation during the same period The earliest confirmed cases outside China were reported in Thailand on January 13, followed by Japan (January 15), the Republic of Korea (January 20), the USA (January 21), Singapore and Vietnam (January 23). On February 21, four weeks after the first reported case in Korea, the number of confirmed cases began to rise rapidly. In addition, cases in Italy began to rise rapidly two weeks after the first case was reported there, and cases in Iran increased quickly in the second week after the first case report. Furthermore, the USA (5 weeks after the first case) and other European countries such as Spain (3 weeks after the first case), France (5 weeks after the first case), Germany (4 weeks after the first case), and Switzerland (1 week after the first case) began to see a rapid rise in infections. Overall, many European countries experienced that rise earlier than the USA. The length of time from the first case reported to the period of rapid rise in different countries varied. Most of them entered the rapid growth phase within 1 month (Figure 8). The confirmed cases reported in the USA increased sharply in weeks 8 to 9. From the scatter plot of confirmed cases (top 10 countries), it was found that when the daily increase exceeded 20-30 cases, most countries entered an obvious increase stage (Figure 9). From the time point of the first daily increase of 20 cases, Germany, Spain, and Italy reached the peak of daily incremental rising after 28, 29, and 34 days, respectively, and then the daily increment showed a downward trend. The average daily increment of a 7-day rolling timeframe also showed an inflection point in Italy. The countries of France, the UK, and the USA appeared to peak at 36 days, 32 days, and 44 days, respectively. According to the regional division in the WHO report, many countries in the African region and Southeast Asia region were closer to the equator with slow growth or only at the early stage of infection spread. This study also analysed the top 10 countries of confirmed cases in each region (Figure 10, data up to April 21). Firstly, dividing the average daily increment value of the final week by the previous week, to get the change coefficient for each country here. The change coefficient was used to express the growing speed of a country. The average change coefficient value of the countries in a region was used to evaluate the growing speed of a region. The average change coefficient was 1.3 in the Eastern Mediterranean region and was 1.25 in the region of the Americas. Besides, the change coefficient was 1.3 in Russian. Secondly, most European countries presented an inflection point or were at a plateau period in the fourth to fifth weeks but were falling slowly. The curve of cases in China dropped rapidly after the fifth week. On February 13-15, Hubei Province in China reported the clinical diagnosis. The number of clinical diagnosis cases was counted in the WHO COVID-19 Situation Report-28 with a statement that this was only applicable to Hubei Province. If the clinical diagnosis cases were not taken into account, China reached the peak of the daily increment of the epidemic in 18 days, and if such cases were taken into account, China peaked in 27 days. China has been subjected to imported cases since the eighth week, with basically a disappearance of local cases and the rapid rise of epidemics in other countries abroad (Figure 11). The overseas imported cases were first reported in Ningxia Province in China on February 26 and cumulatively included 1610 as of April 21, 21 of which were reported by Sichuan Province. Discussion The eastern region of Sichuan Province is adjacent to Chongqing and Hubei provinces. Many counties there have reported cases, which is related to the fact that imported cases were the main cases in Sichuan Province in the early stage. Combined with the "Baidu Migration Data" analysis, 1 9 the national migration scale index 1 9 on January 23 and earlier was slightly higher than that of the same period last year (January 24 was the Chinese New Year's Eve), but after January 25, the national migration scale index fell slightly until March 12, which was lower than the same time of last year. On January 23, for the proportion of migrants in cities across China (the ratio of the population that moved to a city to the total population that moved into different kinds of cities in whole country), the top 3 were Chongqin, Chengdu, and Zhoukou city. Twelve of the top 100 cities were in Sichuan Province and all of these are located in the eastern part. Among them, Chengdu ranked first in the 26-30-day timeframe. The proportion of emigration place (the ratio of the emigration to a certain city to the total emigration for the whole country), 9 of the top 100 were in Sichuan Province, and were also located in the east. This result suggested that the population flow in eastern Sichuan was relatively large. In addition, the overall low incidence in western Sichuan was also associated with a lower population density in the western region than in the east. In a few of these areas, the incidence was high because a few people, who went back from Chengdu in the incubation period, participated many aggregation activities there. 22 The first reports of the kinds of cities in Sichuan Province were concentrated in the first week after Wuhan instituted a lockdown. This reflected the rapid response and quarantining of Sichuan Province. The number of cases increased significantly in the first 2 weeks, which was in line with the usual incubation period. 21 , 22 This suggested that the first two weeks after the occurrence of the first case was a critical stage for establishing quarantine, prevention and control measures. The spatiotemporal distribution of the country suggests that the virus spreads rapidly during the two incubation periods. The analysis of the length of the epidemic indicates that after China adopted strong prevention and control measures, most regions can control the growth rate of the epidemic in approximately 3 weeks. The average and median of the epidemic length of county-level regional units are significantly lower than the epidemic length of city-state regional units. It suggested that regional units of different levels can combine actual conditions to formulate prevention and control measures, duration of prevention and control, and resumption time. Especially for areas where there is no community outbreak in the local area, production can be resumed early to reduce economic losses. The increased number of COVID-19 case in spatiotemporal distribution showed that the epidemic in China went through mainly two stages of release. In the first stage, the 3 weeks since the Wuhan reported, the confirmed case increased and the epidemic spread rapidly (Part A of Figure 4). In the second stage, the next four weeks after the Wuhan lockdown, the release was accelerated and was then quickly close to the end of the first epidemic wave (Part B, C and D of Figure 4). Results indicated that on March 12, the case incidence in major countries worldwide was still in the first stage, and from March 25 onward, most countries entered the second stage of rising cases. After comparing and analysing the morbidity, we found that the length of time from the first case to the rapid rise of cases varies in different countries. Most countries entered the period of rapid growth after 4 weeks. The delayed entry of rapid growth in a few countries was related to the late launch of extensive testing. China has taken many effective measures to address the epidemic. Very important activities included well-coordinated prevention, control and treatment and reflected 1) centralized and efficient command, 2) a tight prevention and control system involving all sectors of society, 3) an all-out effort to treat patients and save lives, 4) information that was released in an open and transparent manner, and 5) science and technology underpinnings. In addition, the government assembled a powerful effort to beat the virus. This fight mobilized the whole country with a message that lives are precious, which let the people unite as one. During the battle against the virus, the government did much to coordinate prevention and control with social and economic development. Moreover, the whole process of fighting the epidemic could not be separated from the support of the international community and Chinese citizens overseas. COVID-19 is one of the most significant public health emergencies that has occurred in China since the founding of the People's Republic of China. In the early stage of the epidemic, due to insufficient resources for medical treatment and the failure to connect quickly with the disease prevention and control information system in a few newly designated hospitals, as well as the overloaded operations in hospitals and the very busy treatment schedule for medical staff late reports, missed reports and false reports occurred. On March 18, the newly confirmed growth was reported to be zero in Wuhan for the first time. Since then, the spread of the epidemic has been basically blocked, and the control of the travel from Wuhan to other cities has been lifted, creating favourable conditions for the comprehensive and detailed verification and revision of the epidemic data. The revised types included reductions and additions. Among them, 217 cases were removed after verification (some patients had been treated in more than one district or in multiple hospitals, resulting in duplicate reporting), and 542 cases were added (previous cases not reported in time due to late reporting and omission). The total number of confirmed cases was revised from 50,008 to 50,333 on April 17 based on the principles of objectivity and the transparency of data 23 . This part of the newly confirmed number accounted for a small proportion (0.6%) of the total confirmed number in Wuhan. The limitation of this study was that the 0.6% confirmed number was presented centrally on April 17 in figures 8, 9 and 10, because the data released by Health Commission of Hubei Province were not assigned to the date of previous diagnosis. Conclusions Considering the history of the epidemic in China, it is suggested that even if countries take effective and powerful measures, the number of confirmed cases will increase rapidly in the first month, which will inevitably challenge the medical resources and population health of those countries. If no measures are taken, it is difficult to estimate the number of infections and the overall economic losses that would be caused. Combined with the severity of the illness and mortality rates, the health costs of the population would be substantial. In addition, upon entering the period of zero growth and the gradual cure of local cases in China, high vigilance must be maintained. From February 26, 2020, the different provinces of China began to report imported cases from abroad. With the change in the epidemic situation in different countries and the different measures taken by governments, the cases imported into China have soared. A small number of overseas associated cases have appeared. In response, from March 28, 2020, the entry of foreigners holding valid Chinese visas and residence permits were suspended. Some countries with improved epidemic situations also need to quickly formulate a continuous "local strategy of entry checkpoints" to fend off imported COVID-19 in the context of the global epidemic. Until vaccines are widely available, these governments need to be highly vigilant about localized outbreaks. Abbreviations COVID-19: Coronavirus disease; CDC: Centers for Disease Control and Prevention; Korea: Republic of Korea; MERS-CoV: Middle East Respiratory Syndrome Coronavirus; SARS-CoV: Severe acute respiratory syndrome coronavirus; SARS-CoV-2: severe acute respiratory syndrome corona virus 2; UK: the United Kingdom; USA: the United States of America; WHO: World Health Organization; 2019-nCoV: 2019 novel coronavirus, tentatively named SARS-CoV-2 Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials The city-level COVID-19 confirmed case number information for Sichuan was made available from the Health Commission of Sichuan Province website. 20 The county level information of Sichuan was obtained by applying it to the Surveillance System of Sichuan CDC. The confirmed case number information of other provinces was available from the National and province level Health Commission website. 5-6 Data from various countries were from the WHO COVID-19 Daily Report published since January 21, 7, which also contained the confirmed information of the different provinces in China before the date of March 15. The case number information before the first WHO reports came from different national government websites. 8-11 The confirmed number data in the WHO reports could also be downloaded from the GitHub website, collated as a public database continuously updated by the Johns Hopkins University Center for Systems Science and Engineering. 2 4 The population of Sichuan Province was available from the Statistical Yearbook of Sichuan Province. 12 Competing interests The authors declare that they have no competing interests. Funding This study was supported by the Sichuan Province COVID-19 Science and Technology Emergency Project [grant no. 2020YFS0015] and the Tianfu Famous Doctor Fund of Tianfu Famous Doctor. The authors disclose no other sources of funding. The funding body did not participate in the design, collection, analysis, interpretation, and writing of this study. Author Contributions XX and BZ conceived of and designed the study. The data collection was arranged and carried out by XX, JZ, RL, YL, LZ, TD, YC and ZW. YZ, LF and CP provided support for the interpretation of the data. XX analysed the data and used SAS as well as Arcgis software to draw the map and drafted the work. XZ, YD and XW provided substantive revisions. All authors contributed to the manuscript preparation and read and approved the manuscript. Acknowledgements We thank Dr Zhao Xing and Dr Zhang Linghua for the help. Thanks to all the CDC staff and healthcare workers for collecting information on the frontlines. Authors' information The current position of Xinyin Xu is an associate research fellow, working in the Sichuan Centers for Disease Control and Prevention, Chengdu, China. Her primary research interests are the analysis of public health emergencies, as well as the prevention and control of chronic diseases with some nutrition factors. During the period of fighting COVID-19, she worked on the COVID-19 Situation Analysis Task Force of Sichuan Province. Author details 1 Sichuan Centers for Disease Control and Prevention, Chengdu, China, 2 University of Texas Health Science Center at Houston, Houston, USA References Wuhan Municipal Health Commission. B riefing on the pneumonia epidemic situation . Dec 31, http://wjw.wuhan.gov.cn/front/web/showDetail/2019123108989 . Accessed 23 Jan 2020. The 2019-nCoV Outbreak Joint Field Epidemiology Investigation Team, Li Q. 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Baidu migration data. http://qianxi.baidu.com/ . Accessed 23 April 2020. Sichuan province Health Commission. The 16 th Press statement of COVID-19 (in Chinese) . http://wsjkw.sc.gov.cn/scwsjkw/zxft/2020/2/27/0189103808184147b6855bee6a3ac129.shtml . Accessed 23 April 2020. China state Administration of Traditional Chinese Medicine. Chinese Clinnical Guidance for COVID-19 pneumonia diagnosis and treatment (7th edition) (in Chinese) . http://www.nhc.gov.cn/yzygj/s7653p/202003/46c9294a7dfe4cef80dc7f5912eb1989.shtml . Accessed 31 Mar 2020. China Disease Prevention and Control Bureau. Chinese Prevention and control Guidance for COVID-19 pneumonia (6th edition) (in Chinese) . http://www.nhc.gov.cn/jkj/s3577/202003/4856d5b0458141fa9f376853224d41d7.shtml . Accessed 31 Mar 2020. Wuhan city Health Commission. Wuhan revised the number of covid-19 confirmed cases and death cases. http://wjw.wuhan.gov.cn/ztzl_28/fk/tzgg/202004/t20200430_1198388.shtml . Accessed 23 April 2020. Johns Hopkins University Center for Systems Science and Engineering. Novel Coronavirus (COVID-19) Cases. https://github.com/CSSEGISandData/COVID-19 . Accessed 23 April 2020. Table Table 1. Number and incidence of COVID-19 in different cities of Sichuan Province City Population Number of counties Confirmed case number Rank of case number Incidence /100,000 Rank of incidence Cheng Du 1633 20 144 1 0.8818 4 Gan Zi 119.6 18 78 2 6.5217 1 Da Zhou 572 7 42 3 0.7343 5 Nan Chong 644 9 39 4 0.6056 7 Guang An 324.1 6 30 5 0.9256 3 Ba Zhong 332.2 5 24 6 0.7225 6 Lu Zhou 432.4 7 24 6 0.555 9 Nei Jiang 369.9 5 22 8 0.5948 8 Mian Yang 485.7 9 21 9 0.4324 12 De Yang 354.5 6 19 10 0.536 10 Sui Ning 320.2 5 17 11 0.5309 11 Pan Zhi Hua 123.6 5 15 12 1.2136 2 Liang Shan 490.8 17 15 13 0.3056 15 Yi Bin 455.6 10 12 14 0.2634 17 Zi Gong 292 6 9 15 0.3082 14 Mei Shan 298.4 6 8 16 0.2681 16 Ya An 154 8 6 17 0.3896 13 Guang Yuan 266.7 7 6 17 0.225 18 Zi Yang 251.2 3 4 19 0.1592 19 Le Shan 326.7 11 3 20 0.0918 21 A Ba 94.4 13 1 21 0.1059 20 Subtotal 8341 183 539 0.6462 Overseas imported cases 21 Imported case after Wuhan unsealed 1 Total 561 *In Sichuan, up to March 4, a total of 21 cities had been reported (covering all the city-level geographical units), with a subtotal number of 539 confirmed cases and an incidence of 0.6432/100,000. The subtotal number was for the confirmed first wave. It did not contain 21 overseas imported cases reported from March 17 to April 6 and only one was imported from Wuhan after Wuhan was unsealed. Wuhan was unsealed on April 8, and this case was reported on April 17. All 22 cases were discovered in the observation period after they returned to Chengdu and did not cause secondary transmissions. Cite Share Download PDF Status: Published Journal Publication published 05 Nov, 2020 Read the published version in BMC Infectious Diseases → Version 4 posted Editorial decision: Accept 07 Oct, 2020 Editor assigned by journal 25 Aug, 2020 Reviewers invited by journal 25 Aug, 2020 Reviewer # 1 agreed at journal 25 Aug, 2020 Review # 1 received at journal 25 Aug, 2020 Submission checks completed at journal 24 Aug, 2020 Editor invited by journal 24 Aug, 2020 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-20551","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":1707771,"identity":"d9be6439-322d-4346-9f67-215d740afd58","order_by":0,"name":"Xinyin Xu","email":"","orcid":"https://orcid.org/0000-0001-5474-3174","institution":"Sichuan Center for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Xinyin","middleName":"","lastName":"Xu","suffix":""},{"id":1707772,"identity":"fd412078-029a-45db-b5b3-b07749eeea52","order_by":1,"name":"Jing Zeng","email":"","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Zeng","suffix":""},{"id":1707773,"identity":"7b34b1c1-824d-41da-9579-f92bc3b5626b","order_by":2,"name":"Runyou Liu","email":"","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Runyou","middleName":"","lastName":"Liu","suffix":""},{"id":1707774,"identity":"6736bf60-2c58-4566-a1cf-ff2f07dd27f3","order_by":3,"name":"Yang Liu","email":"","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Liu","suffix":""},{"id":1707775,"identity":"70d17483-6ac2-467c-a864-c3186ac62e30","order_by":4,"name":"Xiaobo Zhou","email":"","orcid":"","institution":"University of Texas Health Science Center at Houston","correspondingAuthor":false,"prefix":"","firstName":"Xiaobo","middleName":"","lastName":"Zhou","suffix":""},{"id":1707776,"identity":"92a5497d-dd05-4279-aa61-525cee599afd","order_by":5,"name":"Lijun Zhou","email":"","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Lijun","middleName":"","lastName":"Zhou","suffix":""},{"id":1707777,"identity":"b1979f36-60ad-4b9b-87c0-2341c39e96e6","order_by":6,"name":"Ting Dong","email":"","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Ting","middleName":"","lastName":"Dong","suffix":""},{"id":1707778,"identity":"c96983e8-cc34-47f3-aa8a-6a0768c295b5","order_by":7,"name":"Yuxin Cha","email":"","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Yuxin","middleName":"","lastName":"Cha","suffix":""},{"id":1707779,"identity":"ca4527c2-af41-4d86-876f-e5b63eaeeb62","order_by":8,"name":"Zhuo Wang","email":"","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Zhuo","middleName":"","lastName":"Wang","suffix":""},{"id":1707780,"identity":"673d50d1-b2b9-47b5-b889-b4f0571f1c9e","order_by":9,"name":"Ying Deng","email":"","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Deng","suffix":""},{"id":1707781,"identity":"e61f4ca0-2457-48d6-9df9-184913594dba","order_by":10,"name":"Yu Zhang","email":"","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Zhang","suffix":""},{"id":1707782,"identity":"5ccff481-5983-4ba9-b9ec-ced0c0f7c429","order_by":11,"name":"Liao Feng","email":"","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Liao","middleName":"","lastName":"Feng","suffix":""},{"id":1707783,"identity":"6d18c587-4e5c-463a-8bfa-c719987d4787","order_by":12,"name":"Chen Pu","email":"","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Chen","middleName":"","lastName":"Pu","suffix":""},{"id":1707784,"identity":"b67e7ae2-93f1-40bc-aa21-7fa9eea38e07","order_by":13,"name":"Xianping Wu","email":"","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":false,"prefix":"","firstName":"Xianping","middleName":"","lastName":"Wu","suffix":""},{"id":1707785,"identity":"16447e15-08d8-4efe-b73a-c4af0ac1c89f","order_by":14,"name":"Bo Zhong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYDACCSBmbGDg4WdvPvggoaKGeC0ykj3Hkg0enDlGvBYbgxs+ZpIPW5gJ65Cf3Xzs4dcdNjwGN9jSKhIb2Bj427sT8GphnHMs3Vj2TBqP5O3mYzcSd8gwSJw5uwGvFmaJHDNpybbDPHx3jqXdSDzDxmAgkYtfCxtMC8ONHLOCxDZmwlp4gFokPwK1CAC1MBClRUIiLU2aEeQXYCBLJJw5xkPQL/Izko9J/txhYw+Kyo8/Kmrk+Nt78WsBAWYeZJcSVA4CjD+IUjYKRsEoGAUjFgAAsLhJse8hgvQAAAAASUVORK5CYII=","orcid":"","institution":"Sichuan Centers for Disease Control and Prevention","correspondingAuthor":true,"prefix":"","firstName":"Bo","middleName":"","lastName":"Zhong","suffix":""}],"badges":[],"createdAt":"2020-03-31 16:27:27","currentVersionCode":4,"declarations":"","doi":"10.21203/rs.3.rs-20551/v4","doiUrl":"https://doi.org/10.21203/rs.3.rs-20551/v4","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-020-05494-6","type":"published","date":"2020-11-05T15:01:22+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":2107550,"identity":"c679e342-fb5c-4860-89d0-fbe218f5c1de","added_by":"auto","created_at":"2020-08-27 15:47:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":113880,"visible":true,"origin":"","legend":"City-level distribution of mainland confirmed cases in Sichuan Province (up to March 4)\n*Each city of Sichuan Province (21 in total) has reported confirmed cases, with a total mainland case number of 539 and an incidence rate of 0.6462/100,000. SAS software was used to create the map (SAS studio online, https://welcome.oda.sas.com/).\n\nNote: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-20551/v4/Fig1.png"},{"id":2107551,"identity":"c942d577-3bb2-491b-8259-e9e77bc488e7","added_by":"auto","created_at":"2020-08-27 15:47:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":216969,"visible":true,"origin":"","legend":"County-level distribution of mainland confirmed cases in Sichuan Province (up to March 4)\n*The confirmed cases were distributed in 103 counties, accounting for 56.28% of Sichuan Province. The regions with the highest number of cases and counties are located in the eastern part of Sichuan Province, which is directly adjacent to Chongqing and closer to Hubei Province. SAS software was used to create the map (SAS studio online, https://welcome.oda.sas.com/).\n\nNote: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-20551/v4/Fig2.png"},{"id":2107552,"identity":"e8979b2c-98cd-4934-8291-9966c113ca7c","added_by":"auto","created_at":"2020-08-27 15:47:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":79693,"visible":true,"origin":"","legend":"Time distribution of the number of confirmed cases and counties with the first diagnosed cases in Sichuan Province (mainland cases)\n*The maximum number was the third and fourth days after the Wuhan lockdown. The rapid increase was particularly obvious in the first two weeks. January 21, with the first confirmed case, the Sichuan CDC launched an emergency response. January 24, Sichuan government launched the first-level response to major public health incidents. February 5, commencement of district classification prevention and control at the city level. February 13, commencement of district classification prevention and control at the county level. February 26, Sichuan government reduced the response to level 2. March 4, the last local cases in the first wave of the epidemic. March 18, establishment of a thematic working group on overseas imported cases. March 25 reduced the response to level 3. From March 17 to April 6, a total of 21 overseas imported cases were reported in Sichuan.\n","description":"","filename":"3.PNG","url":"https://assets-eu.researchsquare.com/files/rs-20551/v4/3.PNG"},{"id":2107553,"identity":"50812c2d-a678-4700-8c12-c68b8459c24a","added_by":"auto","created_at":"2020-08-27 15:47:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":163737,"visible":true,"origin":"","legend":"Spatiotemporal distribution of the epidemic (comparison of key dates, local cases)\n*Part A shows the case distribution in each city on January 23 (Wuhan lockdown). Part B shows the case distribution on February 20 (fourth week after the closure of Wuhan). Part C shows the increase in the number of cases in the fifth and sixth weeks after Wuhan lock down. Part D shows the increase in the number in the seventh week. SAS software was used to create the map (SAS studio online, https://welcome.oda.sas.com/).\n\nNote: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"4.PNG","url":"https://assets-eu.researchsquare.com/files/rs-20551/v4/4.PNG"},{"id":2107554,"identity":"2633bca5-eaba-41d1-afa3-34bd828de7a8","added_by":"auto","created_at":"2020-08-27 15:47:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":338057,"visible":true,"origin":"","legend":"Hot spot analysis of the epidemic (comparison of key dates, local cases)\n*Spatial autocorrelation analysis of China showed positive spatial correlation. From January 23 to February 20, the epidemic situation was rapidly gathering in space. In part A, there were 39 level 1 hot spots ,22 level 2 hot spots. The level 1 hot spots were mainly distributed in Hubei, Hunan, Jiangxi Provinces. The level 2 hot spots were mainly distributed in Henan and Anhui Provinces. In part B, all the original level 2 hot spots turned into level 1. After February 20, the hot spots did not expand, which reflected that the spread of the epidemic was effectively controlled.\n\nNote: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"5.PNG","url":"https://assets-eu.researchsquare.com/files/rs-20551/v4/5.PNG"},{"id":2107555,"identity":"7e6aa22e-43ee-4a50-ac37-371968d7885b","added_by":"auto","created_at":"2020-08-27 15:47:14","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":42630,"visible":true,"origin":"","legend":"Analysis of the epidemic length (local cases) in China and Sichuan Province\n*Here, zero growth excludes overseas imported cases as well as their associated cases and a very few cases who leave Wuhan after it was unsealed on April 8. Briefly, the length was calculated by the information of occurrence and the end of local cases in the first wave.\n","description":"","filename":"6.PNG","url":"https://assets-eu.researchsquare.com/files/rs-20551/v4/6.PNG"},{"id":2107556,"identity":"9193739c-376e-4179-81be-c12802e853a9","added_by":"auto","created_at":"2020-08-27 15:47:14","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":113351,"visible":true,"origin":"","legend":"The comparison of average daily increments between Sichuan and the other 6 provinces\n*One unit of the abscissa was a week (7 days). It set the day that the first cases reported in each province as the starting point. During the two weeks before the Hubei lockdown, the top destination of Hubei's emigration population was Henan Province. Sichuan Province ranked seventh. Taking the migration from Hubei at this stage as a possible high-risk factor, this chart selected the provinces that rank close to Sichuan Province (rank 4 to 10) for comparison. The peak time in Sichuan Province was earlier (occured in the second week according to the weekly analysis, ranked the first in common), and the peak was lower (26.7 cases average daily increment in that week, only higher than Shaanxi). The fluctuation after the eighth week of each province mainly came from imported cases abroad. The data go up to April 21 in this figure. ","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-20551/v4/7.png"},{"id":2107557,"identity":"a1d4e30b-f1f7-4bd3-8b33-e8c5bac53952","added_by":"auto","created_at":"2020-08-27 15:47:14","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":89825,"visible":true,"origin":"","legend":"Epidemic trends in major global countries\n*The length of time from the first report to the period of rapid rise in different countries varied based on the difference of applicable conditions of nucleic acid detection and the national control strategies. The ordinate represents the cumulative number of confirmed cases. The lower right curves indicate the countries with the top 10 confirmed cases worldwide on April 21. Most of them entered the rapid growth phase within 1 month. The top left curves indicate the countries with the top 10 populations (except the USA, China, and Russia, which are already in the lower right). Most of them were starting to show a strong upward trend, which suggested a high risk in the next few weeks.\n","description":"","filename":"8.PNG","url":"https://assets-eu.researchsquare.com/files/rs-20551/v4/8.PNG"},{"id":2107558,"identity":"10b6f46f-ebfe-4389-8fbe-6db39c08e909","added_by":"auto","created_at":"2020-08-27 15:47:14","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":96674,"visible":true,"origin":"","legend":"A scatter plot of confirmed cases\n*The ordinate represents the daily growth number of confirmed cases. The solid circles indicate the countries with the top 10 confirmed cases. The hollow circles indicate the countries with the top 10 populations. The solid circles suggest that when the daily increase exceeded 20-30 cases, most countries entered an obvious increase stage.\n","description":"","filename":"9.PNG","url":"https://assets-eu.researchsquare.com/files/rs-20551/v4/9.PNG"},{"id":2107559,"identity":"38b9463f-a8bf-4117-a889-cdf272dd27eb","added_by":"auto","created_at":"2020-08-27 15:47:14","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":275458,"visible":true,"origin":"","legend":"The analysis of the average daily increment, per 7 days, in different countries and regions. One unit of the abscissa was a week (7 days). It set the day when the new cases exceeded 20 as the starting point. According to the regional division in the WHO report, this figure included the top 6-10countries of each region, for which the daily increase exceeded 20, to show the trends of confirmed cases.Countries meeting this condition in the Southeast Asia region and Western Pacific region were just 6 and8, respectively, both less than 10. The countries in parts A and E were closer to the equator with slow growth or at the early stage of infections. In parts B and D, most countries were in the rapid growth phase, as well as Russian in part C. Dividing the average daily increment value of the final week by the previous week, to get the change coefficient for each country here. The average change coefficient value of the countries in a region was used to evaluate the growing speed of a region. The average change coefficient was 1.3 in the Eastern Mediterranean region and 1.25 in the region of the Americas. Besides, the change coefficient was 1.3 in Russian. Most European countries in part C as well as the USA in part D presented an inflection point or at a plateau period in the fourth to fifth weeks but declined slowly.Germany, Spain, Italy, and China (A) took 28, 29, 34, and 18 days, respectively, to reach their peak daily increments. China (B) took 27 days as it contained an increase in clinical diagnoses published in the fifth week. The curve of China dropped rapidly after the fifth week. The two stars in the curve of China indicate the start of reporting imported cases from abroad (starting on February 26) in mainland China(excluding Hong Kong, Macao and Taiwan) and the response of suspending entry of foreigners holding validChinese visas and residence permits (March 28). From February 26 to April 21, mainland China reported approximately 1610 imported cases from abroad, approximately 3 times the Sichuan cumulative cases. During that time, there were 174 newly confirmed local cases in mainland China. All the newly confirmed case numbers were in the period up to April 21 in this figure.","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-20551/v4/10.png"},{"id":2107560,"identity":"dbb23282-fceb-47ad-b136-27a4ad930fe2","added_by":"auto","created_at":"2020-08-27 15:47:14","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":92984,"visible":true,"origin":"","legend":"Global distribution of confirmed cases and source distribution of cases imported into China from abroad\n*With basically the disappearance of local cases in China and the rapid rise of epidemics in other countries abroad, a large number of cases abroad have been re-imported into China. The overseas imported cases were first reported in Ningxia Province in mainland China (excluding Hong Kong, Macao and Taiwan) on February 26 and totalled 1610, imported from 48 overseas countries (1601 cases were collected their information of input countries), on April 21 and distributed in 19 provinces in China. SAS software was used to create the map (SAS studio online, https://welcome.oda.sas.com/).\n\nNote: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"11.PNG","url":"https://assets-eu.researchsquare.com/files/rs-20551/v4/11.PNG"},{"id":13585842,"identity":"ae6838f0-5818-4a65-ad79-7a448e103d91","added_by":"auto","created_at":"2021-09-17 04:44:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1548998,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-20551/v4/c868c6d7-78ff-418b-8780-67044e8c53d1.pdf"}],"financialInterests":"","formattedTitle":"Should we remain hopeful? The key 8 weeks: Spatiotemporal epidemic characteristics of COVID-19 in Sichuan Province and its comparative analysis with other provinces in China and global epidemic trends","fulltext":[{"header":"Background","content":"\u003cp\u003eFaced with unknown infectious diseases, policymakers are always looking for the best point of prevention and control, balancing between underestimating and overestimating the risk. In December 2019, there were reports of unexplained pneumonia infections in Wuhan, China.\u003csup\u003e1\u003c/sup\u003e On December 31, experts from the Chinese Center for Disease Control and Prevention (CDC) went to Wuhan to learn about the situation and collected samples from patients.\u003csup\u003e2\u003c/sup\u003e\u0026nbsp;On January 3, 2020, scientists from the National Institute for Viral Disease Control and Prevention identified the sequence of novel \u0026beta;-genus coronaviruses from specimens taken from patients in Wuhan and later published this information to the public. The study found that the patients were infected with \u0026beta;-genus coronaviruses with genetic characteristics different from SARS-CoV and MERS-CoV that was temporarily named the\u0026nbsp;2019 novel coronavirus\u0026nbsp;(2019-nCoV)\u0026nbsp; and later renamed \"severe acute respiratory syndrome coronavirus 2\u0026nbsp;(SARS-CoV-2). The disease caused by it is called coronavirus disease (COVID-19).\u003csup\u003e3,4\u003c/sup\u003e Subsequently,\u0026nbsp;cases of COVID-19 were reported in 31 provinces of China, Hong Kong, Macao, Taiwan and other countries. Facing the grim situation of the global COVID-19 outbreaks, this study focuses on analysing the overall epidemic characteristics of Sichuan Province, which is close to Wuhan in the east. This study also analysed the overall epidemic characteristics of China, selected key dates for comparison, considered the epidemic laws, and analysed the global epidemic trends to provide a basis for China to cope with imported cases abroad and for other countries to grasp the timing of prevention and control to formulate appropriate strategies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eTo reflect the actual geographical distribution risk of confirmed cases in Sichuan Province, the current residential addresses of confirmed cases from the Sichuan COVID-19 Surveillance System\u0026nbsp;were selected for distribution analysis. For comparison with neighbouring provinces, the situation of confirmed cases reported by the National Health Commission,\u003csup\u003e5\u003c/sup\u003e Hubei Province,\u003csup\u003e6\u003c/sup\u003e and the health commissions of other provinces were analysed using the address of the reporting unit (usually the hospital or CDC). Data from various countries were taken from the WHO COVID-19 Daily Report published since January 21.\u003csup\u003e7\u003c/sup\u003e The number of \u0026nbsp;cases in China before that first daily report and the first case information in Thailand, Japan, the Republic of Korea, and the USA, mentioned in the previous report of WHO, was taken from their national government websites.\u003csup\u003e8-11\u003c/sup\u003e The number of counties and districts of the cities in Sichuan Province were taken from the Statistical Yearbook of Sichuan Province.\u003csup\u003e12\u003c/sup\u003e\u003csup\u003e\u0026nbsp; \u003c/sup\u003eThe population of various cities in China were taken from the Statistical Yearbook of kinds of provinces.\u003c/p\u003e\n\u003cp\u003eThe characteristics of cumulative confirmed cases, daily new cases, morbidity, etc. were compared based on temporal and spatial factors; the length of time from the first case report to the end of the local cases (i.e., nonforeign imported cases),\u0026nbsp;abbreviated hereafter as \"epidemic length\",\u0026nbsp;was analysed to\u0026nbsp;explore the influencing factors of prevention and control of the outbreaks. Key analysis times and units were set based on key dates of policy and disease incubation periods. The epidemic maps of Sichuan and China were drawn at different times and spaces by SAS software (SAS studio https://welcome.oda.sas.com/) to directly\u0026nbsp;display the development and changes of the epidemic situation and examine the epidemic law by layers. Confirmed case scatter plots, column diagrams and line diagrams were also used to display the time trend. \u0026nbsp;Spatial stratified heterogeneity of incidence rate in China was analysed by R software using the package \u0026ldquo;Geodetector\u0026rdquo; \u003csup\u003e13,14 \u003c/sup\u003eand was described through q statistic. The city incidence rate was considered as a dependent variable and the province was considered as an explanatory variable in this study. Furthermore, the spatial autocorrelation was analysed by Arcgis software and was described through the Global Moran's Index\u003csup\u003e15,16\u003c/sup\u003e and hot spot analysis. Global Moran's Index was proposed by the Australian statistician Patrick Alfred Pierce Moran\u003csup\u003e15\u003c/sup\u003e to assess the overall pattern and spatial agglomeration. The hot spot analysis could identify statistically significant spatial clusters of high values (hot spots).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePrevalence in Sichuan Province (non-foreign imported cases)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGeographical distribution\u003c/em\u003e On March 4, Sichuan Province ended the increase in confirmed cases on the mainland (the first wave). Each city of Sichuan Province (21 in total) reported confirmed cases, with a total mainland case number of 539 and\u0026nbsp;an incidence rate of 0.6462/100,000. Analysis of confirmed cases was based on their current address, with 48.33% in urban and 51.67% in rural areas. The top five cities with confirmed case numbers were Chengdu, Ganzi, Dazhou, Nanchong, and Guang'an. The cities with top five incidence rate were Ganzi, Panzhihua, Guang'an, Chengdu, and Dazhou (Table 1). Moreover, the confirmed cases were distributed in 103 counties, accounting for 56.28% of Sichuan Province (183 in total). Among them, 3 cities (out of 21 cities) found cases reported in all their counties. Geographically, the regions with the highest number of cases and counties were located in the eastern part of Sichuan Province, which is directly adjacent to Chongqing and closer to Hubei Province. Although the number of confirmed cases in the eastern counties was relatively high, a small number of counties in the western part also had a high incidence (Table 1, Figure 1, Figure 2).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTime distribution\u003c/em\u003e The time of the first confirmed case report in the 21 cities of Sichuan Province mainly came one week after the Wuhan\u0026nbsp;lockdown (January 24-January 31).\u003csup\u003e1\u003c/sup\u003e\u003csup\u003e7\u003c/sup\u003e At this stage, the current addresses of the first confirmed cases were distributed in 70 counties, accounting for 68% of the reported counties (103 \u0026nbsp;in total) in Sichuan Province on March 4. The maximum number of cases was on the third and fourth days after the Wuhan lockdown (January 26-27). During those two days, 28 counties (27%) reported their first case. The rapid increase in the confirmed number was concentrated in the four weeks after the closure of Wuhan (January 24-February 20), and the increase was particularly obvious in the first two weeks (Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence in neighbouring provinces of Sichuan and other parts of China\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSpatiotemporal distribution:\u003c/em\u003e On December 31, 2019, 27 cases were first reported on the official website of Hubei Province, all in Wuhan; on January 23, 2020, Hubei announced that it had entered a Grade II response and the Wuhan lockdown began.\u003csup\u003e1\u003c/sup\u003e\u003csup\u003e8\u003c/sup\u003e Of the 835 cases reported nationwide (including 5 in Hong Kong, Macao, and Taiwan), 549 were in Hubei (495 of these in Wuhan) and 267 were in all provinces outside Hubei. A total of 15 cases in Sichuan Province were distributed in 7 cities (the first imported case was diagnosed on January 21), ranking 9th in China. The number of cases in Chongqing, adjacent in eastern Sichuan,\u0026nbsp; was the only neighbouring province with more cases than Sichuan (27 cumulative cases). The epidemic situation in Yunnan and Guizhou adjacent in southern Sichuan was relatively light. Twenty-eight days later, on February 20, a total of 75,993 cases (including Hong Kong, Macao, and Taiwan, which accounted for 102 cases, the total number of which were corrected based on Hubei's revision) were reported, of which 63,088 were in Hubei (45,346 of these were in Wuhan). The revision was originally made by the Health Commission of Hubei Province website on February 21, raising the total to 12,905 cases in provinces outside Hubei (including in Hong Kong, Macao, and Taiwan). A total of 525 cases in Sichuan Province were distributed in all 21 cities, ranking 11th in China, next to Chongqing. Fourteen days later, on March 5, a total of 80,710 cases (including 158 cases in Hong Kong, Macao, and Taiwan) were reported nationwide, including 67,592 cases in Hubei (49,797 of these in Wuhan) and a total of 13,118 cases in provinces outside Hubei (including Hong Kong, Macau, and Taiwan). A total of 539 cases in Sichuan were distributed in all 21 cities, still ranking 11th in China. The number of new cases nationwide fell below one hundred the next day.\u003c/p\u003e\n\u003cp\u003eThe concentrated outbreak time of confirmed cases was the first 4 weeks after the implementation of the lockdown measures (Figure 4). On December 31, cases were only reported in Wuhan. Later, on January 19, the first confirmed case was reported outside Wuhan in Shenzhen of Guangdong Province. From December 31 to January 23 (i.e., 118 cities reported cases on the day of Wuhan lockdown), the number of confirmed cases increased by a factor of 31. In the next four weeks after the Wuhan lockdown, 90% of the cities nationwide were affected, and the number of cases increased by a factor of 91, compared with January 23. In the fifth and sixth weeks, the number of newly confirmed cases and the number of reported areas slowed down significantly, with an increase of only a factor of 0.06 (63 cities except Wuhan increased with a total of 473 cases, and the average daily increase was 0.53 cases/city). In the 7th week (March 5-March 12), there was only a small increase of 62 cases in 10 cities of China except for Wuhan.\u003c/p\u003e\n\u003cp\u003eThe q statistics values of spatial stratified heterogeneity of city incidence among provinces in China (excluding Hong Kong, Macao and Taiwan) on January 23, February 20, March 5 and March 12 were 0.16, 0.37, 0.35 and 0.35 (all the p value \u0026lt;0.05), which revealed that the heterogeneity existed and the province as a space factor explained 16%, 37%, 35% and 35% of the city incidence. The Global Moran's Index\u003csup\u003e15\u003c/sup\u003e of spatial autocorrelation analysis on January 23, February 20, March 5 and March 12 were 0.02, 0.20, 0.18 and 0.18 (all the p value \u0026lt;0.05). All the Global Moran's Index values were positive expressed that the epidemic in China tending to cluster spatially. The results also showed that from January 23 to February 20, the epidemic situation was rapidly gathering in space. Besides, the spread of the epidemic slowed down after February 20, and the spatial concentration decreased slightly. Hot spot analysis further demonstrated that the epidemic gathered in Hubei, Hunan, Jiangxi Provinces on February 20 and did not expand, which suggested that the spread of the epidemic was under effective control after February 20 (Figure 5).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDistribution of the epidemic length in \u003c/em\u003e\u003cem\u003edifferent\u003c/em\u003e\u003cem\u003e region\u003c/em\u003e\u003cem\u003es\u003c/em\u003e\u003cem\u003e:\u003c/em\u003e On March 12, in the seventh week after the closure of Wuhan, the growth of local cases in the first wave ended in all the cities in China \u0026nbsp;(excluding Wuhan, Taiwan and Hong Kong). Based on statistics at the city level (the districts of\u0026nbsp;municipalities were analysed as a city unit according to the high population density of municipalities), the length calculated by the date of occurrence and the end of local cases in a total of 413 cities were used for analysis. The study shows that the longest date length from the first case confirmed to zero growth in each city was 53 days, and the average and median lengths were 22 and 23 days, respectively. The 1\u003csup\u003est\u003c/sup\u003e quartile and 3\u003csup\u003erd\u003c/sup\u003e quartile were 15 and 28 days, respectively. When the length was 21 days, the frequency of the cities was highest at approximately 26 cities (6.3% in 413 cities). Further analysis of the epidemic length at the county level (regional unit) in Sichuan Province included a total of 103 counties that had epidemics. The results showed that there was no local case increase after March 4. The largest date length from the first confirmed case to zero growth was 33 days, with a mean and median of 9 days. The 1\u003csup\u003est\u003c/sup\u003e quartile and 3\u003csup\u003erd\u003c/sup\u003e quartile were 1 and 16 days, respectively. The highest city frequency of the date length was 1 day for approximately 31 cities (30% in 103 cities) (Figure 6). Taking the migration from Hubei during the two weeks before its lockdown as a possible high-risk factor, this study compared the provinces for which the migration rank was close to Sichuan Province and found that the peak time in Sichuan Province was earlier (occured in the second week according to the weekly analysis, ranked the first in common) and the peak value was lower (26.7 cases average daily increment in that week, only higher than Shaanxi) (Figure 7). According to the daily analysis, the peak of Sichuan appeared only one day later than Zhejiang among the 7 provinces, but its peak value was much lower than Zhejiang Province (35 cases compared to 132 cases).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGlobal situation during the same period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe earliest confirmed cases outside China were reported in Thailand on January 13, followed by Japan (January 15), the Republic of Korea (January 20), the USA (January 21), Singapore and Vietnam (January 23). On February 21, four weeks after the first reported case in Korea, the number of confirmed cases began to rise rapidly. In addition, cases in Italy began to rise rapidly two weeks after the first case was reported there, and cases in Iran increased quickly in the second week after the first case report. Furthermore, the USA (5 weeks after the first case)\u0026nbsp;and\u0026nbsp;other European countries such as Spain (3 weeks after the first case), France (5 weeks after the first case), Germany (4 weeks after the first case), and Switzerland (1 week after the first case) began to see a rapid rise in infections. Overall, many European countries experienced that rise earlier than the USA. The length of time from the first case reported to the period of rapid rise\u0026nbsp;in different countries varied. Most of them entered the rapid growth phase within 1 month (Figure 8). The confirmed cases reported in the USA increased sharply in weeks 8 to 9.\u003c/p\u003e\n\u003cp\u003eFrom the scatter plot of confirmed cases (top 10 countries), it was found that when the daily increase exceeded 20-30 cases, most countries entered an obvious increase stage (Figure 9). From the time point of the first daily increase of 20 cases, Germany, Spain, and Italy reached the peak of daily incremental rising after 28, 29, and 34 days, respectively, and then the daily increment showed a downward trend. The average daily increment of a 7-day rolling timeframe also showed an inflection point in Italy. The countries of France, the UK, and the USA appeared to peak at 36 days, 32 days, and 44 days, respectively. According to the regional division in the WHO report, many countries in the African region and Southeast Asia region were closer to the equator with slow growth or only at the early stage of infection spread. This study also analysed the top 10 countries of confirmed cases in each region (Figure 10, data up to April 21). Firstly, dividing the average daily increment value of the final week by the previous week, to get the change coefficient for each country here. The change coefficient was used to express the growing speed of a country. The average change coefficient value of the countries in a region was used to evaluate the growing speed of a region. The average change coefficient was 1.3 in the Eastern Mediterranean region and was 1.25 in the region of the Americas. Besides, the change coefficient was 1.3 in Russian. Secondly, most European countries presented an inflection point or were at a plateau period in the fourth to fifth weeks but were falling slowly. The curve of cases in China dropped rapidly after the fifth week. On February 13-15, Hubei Province in China reported the clinical diagnosis. The number of clinical diagnosis cases was counted in the WHO COVID-19 Situation Report-28 with a statement that this was only applicable to Hubei Province. If the clinical diagnosis cases were not taken into account, China reached the peak of the daily increment of the epidemic in 18 days, and if such cases were taken into account, China peaked in 27 days. China has been subjected to imported cases since the eighth week, with basically a disappearance of local cases and the rapid rise of epidemics in other countries abroad (Figure 11). The overseas imported cases were first reported in Ningxia Province in China on February 26 and cumulatively included 1610 as of April 21, 21 of which were reported by Sichuan Province.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe eastern region of Sichuan Province is adjacent to Chongqing and Hubei provinces. Many counties there have reported cases, which is related to the fact that imported cases were the main cases in Sichuan Province in the early stage. Combined with the \"Baidu Migration Data\" analysis,\u003csup\u003e1\u003c/sup\u003e\u003csup\u003e9\u003c/sup\u003e the national migration scale index\u003csup\u003e1\u003c/sup\u003e\u003csup\u003e9\u003c/sup\u003e on January 23 and earlier was slightly higher than that of the same period last year (January 24 was the Chinese New Year's Eve), but after January 25, the national migration scale index fell slightly until March 12, which was lower than the same time of last year. On January 23, for the proportion of migrants in cities across China (the ratio of the population that moved to a city to the total population that moved into different kinds of cities in whole country), the top 3 were Chongqin, Chengdu, and Zhoukou city. Twelve of the top 100 cities were in Sichuan Province and all of these are located in the eastern part. Among them, Chengdu ranked first in the 26-30-day timeframe. The proportion of emigration place (the ratio of the emigration to a certain city to the total emigration for the whole country), 9 of the top 100 were in Sichuan Province, and were also located in the east. This result suggested that the population flow in eastern Sichuan was relatively large. In addition, the overall low incidence in western Sichuan was also associated with a lower population density in the western region than in the east. In a few of these areas, the incidence was high because a few people, who went back from Chengdu in the incubation period, participated many aggregation activities there.\u003csup\u003e22\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe first reports of the kinds of cities in Sichuan Province were concentrated in the first week after Wuhan instituted a lockdown. This reflected the rapid response and quarantining of Sichuan Province. The number of cases increased significantly in the first 2 weeks, which was in line with the usual incubation period.\u003csup\u003e21\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e22\u003c/sup\u003e This suggested that the first two weeks after the occurrence of the first case was a critical stage for establishing quarantine, prevention and control measures.\u003c/p\u003e\n\u003cp\u003eThe spatiotemporal distribution of the country suggests that the virus spreads rapidly during the two incubation periods. The analysis of the length of the epidemic indicates that after China adopted strong prevention and control measures, most regions can control the growth rate of the epidemic in approximately 3 weeks. The average and median of the epidemic length of county-level regional units are significantly lower than the epidemic length of city-state regional units. It suggested that regional units of different levels can combine actual conditions to formulate prevention and control measures, duration of prevention and control, and resumption time. Especially for areas where there is no community outbreak in the local area, production can be resumed early to reduce economic losses. The increased number of COVID-19 case in spatiotemporal distribution showed that the epidemic in China went through mainly two stages of release. In the first stage, the 3 weeks since the Wuhan reported, the confirmed case increased and the epidemic spread rapidly (Part A of Figure 4). In the second stage, the next four weeks after the Wuhan lockdown, the release was accelerated and was then quickly close to the end of the first epidemic wave (Part B, C and D of Figure 4). Results indicated that on March 12, the case incidence in major countries worldwide was still in the first stage, and from March 25 onward, most countries entered the second stage of rising cases. After comparing and analysing the morbidity, we found that the length of time from the first case to the rapid rise of cases varies in different countries. Most countries entered the period of rapid growth after 4 weeks. The delayed entry of rapid growth in a few countries was related to the late launch of extensive testing.\u003c/p\u003e\n\u003cp\u003eChina has taken many effective measures to address the epidemic. Very important \u0026nbsp;activities included well-coordinated prevention, control and treatment and reflected 1) centralized and efficient command, 2) a tight prevention and control system involving all sectors of society, 3) an all-out effort to treat patients and save lives, 4) information that was released in an open and transparent manner, and 5) science and technology underpinnings. In addition, the government assembled a powerful effort to beat the virus. This fight mobilized the whole country with a message that lives are precious, which let the people unite as one. During the battle against the virus, the government did much to coordinate prevention and control with social and economic development. Moreover, the whole process of fighting the epidemic could not be separated from the support of the international community and Chinese citizens overseas.\u003c/p\u003e\n\u003cp\u003eCOVID-19 is one of the most significant public health emergencies that has occurred in China since the founding of the People's Republic of China. In the early stage of the epidemic, due to insufficient resources for medical treatment and the failure to connect quickly with the disease prevention and control information system in a few newly designated hospitals, as well as the overloaded operations in hospitals and the very busy treatment schedule for medical staff late reports, missed reports and false reports occurred. On March 18, the newly confirmed growth was reported to be zero in Wuhan for the first time. Since then, the spread of the epidemic has been basically blocked, and the control of the travel from Wuhan to other cities has been lifted, creating favourable conditions for the comprehensive and detailed verification and revision of the epidemic data. The revised types included reductions and additions. Among them, 217 cases were removed after verification (some patients had been treated in more than one district or in multiple hospitals, resulting in duplicate reporting), and 542 cases were added (previous cases not reported in time due to late reporting and omission). The total number of confirmed cases was revised from 50,008 to 50,333 on April 17 based on the principles of objectivity and the transparency of data\u003csup\u003e23\u003c/sup\u003e. This part of the newly confirmed number accounted for a small proportion (0.6%) of the total confirmed number in Wuhan. The limitation of this study was that the 0.6% confirmed number was presented centrally on April 17 in figures 8, 9 and 10, because the data released by Health Commission of Hubei Province were not assigned to the date of previous diagnosis.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eConsidering the history of the epidemic in China, it is suggested that even if countries take effective and powerful measures, the number of confirmed cases will increase rapidly in the first month, which will inevitably challenge the medical resources and population health of those countries. If no measures are taken, it is difficult to estimate the number of infections and the overall economic losses that would be caused. Combined with the severity of the illness and mortality rates, the health costs of the population would be substantial.\u003c/p\u003e\n\u003cp\u003eIn addition, upon entering the period of zero growth and the gradual cure of local cases in China, high vigilance must be maintained. From February 26, 2020, the different provinces of China began to report imported cases from abroad. With the change in the epidemic situation in different countries and the different measures taken by governments, the cases imported into China have soared. A small number of overseas associated cases have appeared. In response, from March 28, 2020, the entry of foreigners holding valid Chinese visas and residence permits were suspended. Some countries with improved epidemic situations also need to quickly formulate a continuous \"local strategy of entry checkpoints\" to fend off imported COVID-19 in the context of the global epidemic. Until vaccines are widely available, these governments need to be highly vigilant about localized outbreaks.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCOVID-19: Coronavirus disease; CDC: Centers for Disease Control and Prevention; Korea: Republic of Korea; MERS-CoV: Middle East Respiratory Syndrome Coronavirus; SARS-CoV: Severe acute respiratory syndrome coronavirus; SARS-CoV-2: severe acute respiratory syndrome corona virus 2; UK: the United Kingdom; USA: the United States of America; WHO: World Health Organization; 2019-nCoV: 2019 novel coronavirus, tentatively named SARS-CoV-2\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe city-level COVID-19 confirmed case number information for Sichuan was made available from the Health Commission of Sichuan Province website.\u003csup\u003e20\u003c/sup\u003e The county level information of Sichuan was obtained by applying it to the Surveillance System\u0026nbsp;of Sichuan CDC. The confirmed case number information of other provinces was available from the National and province level Health Commission website.\u003csup\u003e5-6\u003c/sup\u003e Data from various countries were from the WHO COVID-19 Daily Report published since January 21,\u003csup\u003e7,\u003c/sup\u003e which also contained the confirmed information of the different provinces in China before the date of March 15. The case number information before the first WHO reports came from different national government websites.\u003csup\u003e8-11\u003c/sup\u003e The confirmed number data in the WHO reports could also be downloaded from the GitHub website, collated as a public database continuously updated by the Johns Hopkins University Center for Systems Science and Engineering.\u003csup\u003e2\u003c/sup\u003e\u003csup\u003e4\u003c/sup\u003e The population of Sichuan Province was available from the Statistical Yearbook of Sichuan Province.\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Sichuan Province COVID-19 Science and Technology Emergency Project [grant no. 2020YFS0015] and the Tianfu Famous Doctor Fund of Tianfu Famous Doctor. The authors disclose no other sources of funding. The funding body did not participate in the design, collection, analysis, interpretation, and writing of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXX and BZ conceived of and designed the study. The data collection was arranged and carried out by XX, JZ, RL, YL, LZ, TD, YC and ZW. YZ, LF and CP provided support for the interpretation of the data. XX analysed the data and used SAS as well as Arcgis software to draw the map and drafted the work. XZ, YD and XW provided substantive revisions. All authors contributed to the manuscript preparation and read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;We thank Dr Zhao Xing and Dr Zhang Linghua for the help. Thanks to all the CDC staff and healthcare workers for collecting information on the frontlines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe current position of Xinyin Xu is an associate research fellow, working in the Sichuan Centers for Disease Control and Prevention, Chengdu, China. Her primary research interests are\u0026nbsp; the analysis of public health emergencies, as well as the prevention and control of chronic diseases with some nutrition factors. During the period of fighting COVID-19, she worked on the COVID-19 Situation Analysis Task Force of Sichuan Province.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eSichuan Centers for Disease Control and Prevention, Chengdu, China,\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eUniversity of Texas Health Science Center at Houston, Houston, USA\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWuhan Municipal Health Commission. \u003cem\u003eB\u003c/em\u003e\u003cem\u003eriefing on the pneumonia epidemic situation\u003c/em\u003e. Dec 31, \u003ca href=\"http://wjw.wuhan.gov.cn/front/web/showDetail/2019123108989\"\u003ehttp://wjw.wuhan.gov.cn/front/web/showDetail/2019123108989\u003c/a\u003e. Accessed 23 Jan 2020.\u003c/li\u003e\n\u003cli\u003eThe 2019-nCoV Outbreak Joint Field Epidemiology Investigation Team, Li Q. Notes from the Field: An Outbreak of NCIP (2019-nCoV) Infection in China \u0026mdash; Wuhan, Hubei Province, 2019\u0026minus; \u003cem\u003eChina CDC Weekly\u003c/em\u003e, 2020,2020.\u003c/li\u003e\n\u003cli\u003eWorld health organization. \u003cem\u003eNaming the coronavirus disease (COVID-19) and the virus that causes it\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e Jan 12, 2020. \u003ca href=\"https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technical-guidance/naming-the-coronavirus-disease-(covid-2019)-and-the-virus-that-causes-it\"\u003ehttps://www.who.int/emergencies/diseases/novel-coronavirus-2019/technical-guidance/naming-the-coronavirus-disease-(covid-2019)-and-the-virus-that-causes-it\u003c/a\u003e. Accessed 20 Jan 2020.\u003c/li\u003e\n\u003cli\u003eAlexander EG, Susan CB, Ralph SB, et al. Severe acute respiratory syndrome-related coronavirus \u0026ndash; The species and its viruses, a statement of the Coronavirus Study Group. \u003cem\u003eBioRxiv [Preprint]\u003c/em\u003e. February 07, 2020 . \u003ca href=\"https://doi.org/10.1101/2020.02.07.937862\"\u003ehttps://doi.org/10.1101/2020.02.07.937862\u003c/a\u003e.\u003c/li\u003e\n\u003cli\u003eChina National Health Commission. \u003cem\u003eN\u003c/em\u003e\u003cem\u003eotification on the pneumonia epidemic situation (in Chinese)\u003c/em\u003e. \u003ca href=\"http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml\"\u003ehttp://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml\u003c/a\u003e. Accessed 23 April 2020.\u003c/li\u003e\n\u003cli\u003eHubei province Health Commission. \u003cem\u003ePress statement by Hubei province Health Commission (in Chinese)\u003c/em\u003e. \u003ca href=\"http://wjw.hubei.gov.cn/bmdt/ztzl/fkxxgzbdgrfyyq/xxfb/\"\u003ehttp://wjw.hubei.gov.cn/bmdt/ztzl/fkxxgzbdgrfyyq/xxfb/\u003c/a\u003e. Accessed 23 April 2020.\u003c/li\u003e\n\u003cli\u003eThe world health organization. \u003cem\u003eCoronavirus disease (COVID-2019) situation reports\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003ca href=\"https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports.\"\u003ehttps://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports\u003c/a\u003e. Accessed 23 April 2020.\u003c/li\u003e\n\u003cli\u003eThailand Ministry of Public Health situation. \u003cem\u003eU\u003c/em\u003e\u003cem\u003epdate on novel coronavirus (in Thai).\u003c/em\u003e \u003ca href=\"https://ddc.moph.go.th/viralpneumonia/index.html\"\u003ehttps://ddc.moph.go.th/viralpneumonia/index.html\u003c/a\u003e. Accessed 23 Mar 2020.\u003c/li\u003e\n\u003cli\u003eMinistry of Health, Labour and Welfare, Japan. \u003cem\u003ePress statementon \u003c/em\u003e\u003cem\u003eof \u003c/em\u003e\u003cem\u003enovel coronavirus \u003c/em\u003e\u003cem\u003e(in Japanese)\u003c/em\u003e. \u003ca href=\"https://www.mhlw.go.jp/stf/newpage_08906.html\"\u003ehttps://www.mhlw.go.jp/stf/newpage_08906.html\u003c/a\u003e. Accessed 23 Mar 2020.\u003c/li\u003e\n\u003cli\u003eKCDC.\u003cem\u003ePress statement \u003c/em\u003e\u003cem\u003eof \u003c/em\u003e\u003cem\u003enovel coronavirus(in Korean)\u003c/em\u003e\u003cem\u003e. \u003c/em\u003e\u003ca href=\"https://www.cdc.go.kr/board/board.es?mid=a20501000000\u0026amp;bid=0015\u0026amp;list_no=365794\u0026amp;act=view\"\u003ehttps://www.cdc.go.kr/board/board.es?mid=a20501000000\u0026amp;bid=0015\u0026amp;list_no=365794\u0026amp;act=view#\u003c/a\u003e. Accessed 23 Mar 2020.\u003c/li\u003e\n\u003cli\u003eCenters for Disease Control and Prevention. \u003ca href=\"https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html\"\u003ehttps://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html\u003c/a\u003e. Accessed 23 April 2020.\u003c/li\u003e\n\u003cli\u003eSichuan Provincial Bureau of Statistics.Sichuan Investigation Team, National Bureau of \u003cem\u003eStatistical Yearbook of Sichuan ,2018.\u003c/em\u003e China Statistics Press. \u003ca href=\"http://tjj.sc.gov.cn/index.shtml\"\u003ehttp://tjj.sc.gov.cn/index.shtml\u003c/a\u003e. Accessed 31 Mar 2020.\u003c/li\u003e\n\u003cli\u003eWang JF, Zhang TL, Fu BJ. A measure of spatial stratified heterogeneity. \u003cem\u003eECOL INDIC\u003c/em\u003e. 2016;67:250-256.\u003c/li\u003e\n\u003cli\u003eGeodetector R package. \u003cu\u003ehttps://CRAN.R-project.org/package=geodetector\u003c/u\u003e. Accessed 16 June\u003c/li\u003e\n\u003cli\u003eMoran PAP. The interpretation of statistical maps. \u003cem\u003eJ R STAT SOC B\u003c/em\u003e, 1948, 37: 243~251.\u003c/li\u003e\n\u003cli\u003eChen YG. New Approaches for Calculating Moran\u0026rsquo;s Index of Spatial Autocorrelation. \u003cem\u003ePLOS ONE. \u003c/em\u003e2013; 8(7): e68336.\u003c/li\u003e\n\u003cli\u003eHubei province Health Commission. \u003cem\u003ePress statement \u003c/em\u003e\u003cem\u003eof 2019-Ncov\u003c/em\u003e\u003cem\u003e(in Chinese).\u003c/em\u003e \u003ca href=\"http://wjw.hubei.gov.cn/bmdt/ztzl/fkxxgzbdgrfyyq/xxfb/202001/t20200124_2014635.shtm\"\u003ehttp://wjw.hubei.gov.cn/bmdt/ztzl/fkxxgzbdgrfyyq/xxfb/202001/t20200124_2014635.shtm\u003c/a\u003e. Accessed 23 Jan 2020.\u003c/li\u003e\n\u003cli\u003eHubei province Health Commission.\u003cem\u003eA letter to the the people of Hubei province (in Chinese)\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003ca href=\"http://wjw.hubei.gov.cn/fbjd/dtyw/202001/t20200123_2014580.shtml.\"\u003ehttp://wjw.hubei.gov.cn/fbjd/dtyw/202001/t20200123_2014580.shtml\u003c/a\u003e. Accessed 24 Jan 2020.\u003c/li\u003e\n\u003cli\u003eBaidu migration data. \u003ca href=\"http://qianxi.baidu.com/\"\u003ehttp://qianxi.baidu.com/\u003c/a\u003e. Accessed 23 April 2020.\u003c/li\u003e\n\u003cli\u003eSichuan province Health Commission.\u003cem\u003eThe 16\u003csup\u003eth\u003c/sup\u003e \u003c/em\u003e\u003cem\u003ePress statement of \u003c/em\u003e\u003cem\u003eCOVID-19\u003c/em\u003e\u003cem\u003e (in Chinese)\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003ca href=\"http://wsjkw.sc.gov.cn/scwsjkw/zxft/2020/2/27/0189103808184147b6855bee6a3ac129.shtml\"\u003ehttp://wsjkw.sc.gov.cn/scwsjkw/zxft/2020/2/27/0189103808184147b6855bee6a3ac129.shtml\u003c/a\u003e. Accessed 23 April 2020.\u003c/li\u003e\n\u003cli\u003eChina state Administration of Traditional Chinese Medicine. \u003cem\u003eChinese Clinnical Guidance for COVID-19 pneumonia diagnosis and treatment (7th edition) (in Chinese)\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003ca href=\"http://www.nhc.gov.cn/yzygj/s7653p/202003/46c9294a7dfe4cef80dc7f5912eb1989.shtml\"\u003ehttp://www.nhc.gov.cn/yzygj/s7653p/202003/46c9294a7dfe4cef80dc7f5912eb1989.shtml\u003c/a\u003e. Accessed 31 Mar 2020.\u003c/li\u003e\n\u003cli\u003eChina Disease Prevention and Control Bureau. \u003cem\u003eChinese Prevention and control Guidance for COVID-19 pneumonia (6th edition) (in Chinese)\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e \u003ca href=\"http://www.nhc.gov.cn/jkj/s3577/202003/4856d5b0458141fa9f376853224d41d7.shtml.\"\u003ehttp://www.nhc.gov.cn/jkj/s3577/202003/4856d5b0458141fa9f376853224d41d7.shtml\u003c/a\u003e. Accessed 31 Mar 2020.\u003c/li\u003e\n\u003cli\u003eWuhan city Health Commission. Wuhan revised the number of covid-19 confirmed cases and death cases.\u003ca href=\"http://www.wh.gov.cn/sy/whyw/202004/t20200420_1032836.shtml.\"\u003ehttp://wjw.wuhan.gov.cn/ztzl_28/fk/tzgg/202004/t20200430_1198388.shtml\u003c/a\u003e. Accessed 23 April 2020.\u003c/li\u003e\n\u003cli\u003eJohns Hopkins University Center for Systems Science and Engineering. \u003cem\u003eNovel Coronavirus (COVID-19) Cases. \u003c/em\u003e\u003ca href=\"https://github.com/CSSEGISandData/COVID-19\"\u003ehttps://github.com/CSSEGISandData/COVID-19\u003c/a\u003e. Accessed 23 April 2020.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp style=\"margin: 0in 0in 10pt;line-height: 29.333335876464844px;font-size:15px;font-family: Calibri, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px; line-height: 32px; font-family: Verdana, Geneva, sans-serif; color: rgb(0, 0, 0);\"\u003eTable 1. Number and incidence of COVID-19 in different cities of Sichuan Province\u003c/span\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" style=\"width: 784px;border-collapse: collapse;border: none;\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86.359375px;border-top-width: 1pt;border-style: solid none;border-top-color: windowtext;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"12.5%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003eCity\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104.71875px;border-top-width: 1pt;border-style: solid none;border-top-color: windowtext;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"15.625%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003ePopulation\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.421875px;border-top-width: 1pt;border-style: solid none;border-top-color: windowtext;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"13.541666666666666%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003eNumber of counties\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108.640625px;border-top-width: 1pt;border-style: solid none;border-top-color: windowtext;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"15.625%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003eConfirmed case number\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89.8125px;border-top-width: 1pt;border-style: solid none;border-top-color: windowtext;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"13.541666666666666%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: middle;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003eRank of case number\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99.84375px;border-top-width: 1pt;border-style: solid none;border-top-color: windowtext;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"14.583333333333334%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003eIncidence\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e/100,000\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100.625px;border-top-width: 1pt;border-style: solid none;border-top-color: windowtext;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"14.583333333333334%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003eRank of incidence\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86.359375px;border: none;padding: 0in 5.4pt;\" width=\"12.5%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 16.866666793823242px;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: top;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u003cspan style=\"line-height: 15.333332061767578px;\"\u003eCheng Du\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104.71875px;border: none;padding: 0in 5.4pt;\" width=\"15.625%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e1633\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.421875px;border: none;padding: 0in 5.4pt;\" width=\"13.541666666666666%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e20\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108.640625px;border: none;padding: 0in 5.4pt;\" width=\"15.625%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e144\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89.8125px;border: none;padding: 0in 5.4pt;\" width=\"13.541666666666666%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: middle;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e1\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99.84375px;border: none;padding: 0in 5.4pt;\" width=\"14.583333333333334%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e0.8818\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100.625px;border: none;padding: 0in 5.4pt;\" width=\"14.583333333333334%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: middle;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e4\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86.359375px;border: none;padding: 0in 5.4pt;\" width=\"12.5%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 16.866666793823242px;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: top;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u003cspan style=\"line-height: 15.333332061767578px;\"\u003eGan Zi\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104.71875px;border: none;padding: 0in 5.4pt;\" width=\"15.625%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e119.6\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.421875px;border: none;padding: 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sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100.625px;border: none;padding: 0in 5.4pt;\" width=\"14.583333333333334%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: middle;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86.359375px;border: none;padding: 0in 5.4pt;\" width=\"12.5%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 16.866666793823242px;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: top;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u003cspan style=\"line-height: 15.333332061767578px;\"\u003eImported case after Wuhan unsealed\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104.71875px;border: none;padding: 0in 5.4pt;\" width=\"15.625%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.421875px;border: none;padding: 0in 5.4pt;\" width=\"13.541666666666666%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108.640625px;border: none;padding: 0in 5.4pt;\" width=\"15.625%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e1\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89.8125px;border: none;padding: 0in 5.4pt;\" width=\"13.541666666666666%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: middle;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99.84375px;border: none;padding: 0in 5.4pt;\" width=\"14.583333333333334%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: bottom;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100.625px;border: none;padding: 0in 5.4pt;\" width=\"14.583333333333334%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: middle;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 86.359375px;border-style: none none solid;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"12.5%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 16.866666793823242px;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: middle;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u003cspan style=\"line-height: 15.333332061767578px;\"\u003eTotal\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104.71875px;border-style: none none solid;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"15.625%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 16.866666793823242px;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: middle;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u003cspan style=\"line-height: 15.333332061767578px;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.421875px;border-style: none none solid;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"13.541666666666666%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 16.866666793823242px;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: middle;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u003cspan style=\"line-height: 15.333332061767578px;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108.640625px;border-style: none none solid;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"15.625%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 16.866666793823242px;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: middle;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u003cspan style=\"line-height: 15.333332061767578px;\"\u003e561\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89.8125px;border-style: none none solid;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"13.541666666666666%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 16.866666793823242px;font-size:15px;font-family: Calibri, sans-serif;text-align: center;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u003cspan style=\"line-height: 15.333332061767578px;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 99.84375px;border-style: none none solid;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"14.583333333333334%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 16.866666793823242px;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: middle;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u003cspan style=\"line-height: 15.333332061767578px;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100.625px;border-style: none none solid;border-bottom-width: 1pt;border-bottom-color: windowtext;padding: 0in 5.4pt;\" width=\"14.583333333333334%\"\u003e\n \u003cp style=\"margin: 0in 0in 10pt;line-height: 12pt;font-size:15px;font-family: Calibri, sans-serif;text-align: center;vertical-align: middle;\"\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style=\"font-family: Verdana, Geneva, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp style=\"margin: 0in 0in 10pt;line-height: 16.866666793823242px;font-size:15px;font-family: Calibri, sans-serif;\"\u003e\u003cspan style=\"font-size: 10px; line-height: 18.399999618530273px; font-family: Verdana, Geneva, sans-serif; color: rgb(0, 0, 0);\"\u003e*In Sichuan, up to March 4, a total of 21 cities had been reported (covering all the city-level geographical units), with a subtotal number of 539 confirmed cases and an incidence of 0.6432/100,000. The subtotal number was for the confirmed first wave. It did not contain 21 overseas imported cases reported from March 17 to April 6 and only one was imported from Wuhan after Wuhan was unsealed. Wuhan was unsealed on April 8, and this case was reported on April 17. All 22 cases were discovered in the observation period after they returned to Chengdu and did not cause secondary transmissions.\u003c/span\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, SARS-CoV-2, Sichuan Province, China, global, temporal and spatial distribution, epidemiological characteristics, Spatial autocorrelation","lastPublishedDoi":"10.21203/rs.3.rs-20551/v4","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-20551/v4","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The COVID-19 spread worldwide quickly. Exploring the epidemiological characteristics could provide a basis for responding to imported cases abroad and to formulate prevention and control strategies in areas where COVID-19 is still spreading rapidly.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e The number of confirmed cases, daily growth, incidence and length of time from the first reported case to the end of the local cases (i.e., non-overseas imported cases) were compared by spatial (geographical) and temporal classification and visualization of the development and changes of the epidemic situation by layers through maps.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e In the first wave, a total of 539 cases were reported in Sichuan, with an incidence rate of 0.6462/100,000. The closer to Hubei the population centres were, the more pronounced the epidemic was. The peak in Sichuan Province occurred in the second week. Eight weeks after the Wuhan lockdown, the health crisis had eased. The longest epidemic length at the city level in China (except Wuhan, Taiwan, and Hong Kong) was 53 days, with a median of 23 days. Spatial autocorrelation analysis of China showed positive spatial correlation\u0026nbsp;(Moran's Index \u0026gt;0, p\u0026lt;0.05). Most countries outside China began to experience\u0026nbsp;a rapid rise in infection rates 4 weeks after their first case. Some European countries experienced that rise earlier than the USA. The pandemic in Germany, Spain, Italy, and China took 28, 29, 34, and 18 days, respectively, to reach the peak of daily infections, after their daily increase of up to 20 cases. During this time, countries in the African region and Southeast Asian region were at an early stage of infections, those in the Eastern Mediterranean region and region of the Americas were in a rapid growth phase.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e After the closure of the outbreak city, appropriate isolation and control measures in the next 8 weeks were key to control the outbreak, which reduced the peak value and length of the outbreak. Some countries with improved epidemic situations need to develop a continuous \"local strategy at entry checkpoints\" to to fend off \u0026nbsp;imported COVID-19.\u003c/p\u003e","manuscriptTitle":"Should we remain hopeful? The key 8 weeks: Spatiotemporal epidemic characteristics of COVID-19 in Sichuan Province and its comparative analysis with other provinces in China and global epidemic trends","msid":"","msnumber":"","nonDraftVersions":[{"code":4,"date":"2020-08-27 15:40:57","doi":"10.21203/rs.3.rs-20551/v4","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accept","date":"2020-10-07T12:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2020-08-25T12:00:00+00:00","index":"","fulltext":""},{"type":"reviewersInvited","content":"","date":"2020-08-25T12:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-08-25T12:00:00+00:00","index":1,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-08-25T12:00:00+00:00","index":1,"fulltext":"Recommendation: Accept without revision\nForm responses:\n---\n\nComments to Author:\n---\nI am satisfied with the authors' responses.* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\n* Declaration of competing interests: **I declare that I have no competing interests**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"checksComplete","content":"","date":"2020-08-24T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-08-24T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}},{"code":3,"date":"2020-07-01 15:05:16","doi":"10.21203/rs.3.rs-20551/v3","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2020-08-18T12:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-07-25T12:00:00+00:00","index":2,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-07-25T12:00:00+00:00","index":2,"fulltext":"Recommendation: Major revisions required\nForm responses:\n---\n\nComments to Author:\n---\n1. identify the lines where you revised\n2. cite the methods you used.* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **No**\n* Declaration of competing interests: **I declare that I have no competing interests**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"editorInvitedReview","content":"","date":"2020-07-23T12:00:00+00:00","index":1,"fulltext":"Recommendation: Accept after discretionary revisions\nForm responses:\n---\n\nComments to Author:\n---\nPlease include all comments for the authors in this box rather than uploading your report as an attachment. Please only upload as attachments annotated versions of manuscripts, graphs, supporting materials or other aspects of your report which cannot be included in a text format.\nPlease overwrite this text when adding your comments to the authors.\n\n\n1. Line 35, \"local strategy at entry checkpoints\" to respond to a possible second local epidemic. I think, the entry checkpoints were targeted on fending off imported COVID-19. Please contemplate these words and make modifications.\n2. Line 46, specimens taken from patients …\n3. Line 53, global COVID-19 outbreaks\n4. Line 147, Global Moran's Index, or national, or another suitable word?\n5. Line 144/155, the expression is not clear.\n6. Line 170, \"time in Sichuan Province was earlier than elsewhere\", it is better to mark the detailed time, such as one day or 23 hours.\n7. Line 193-196, now it is improved, but I still think not very satisfied with the expression, as they are still difficult for readers to understand what you are talking about.\n8. Line 218, Twelve of top 100 … ?\n9. Line 225, \"In a few of these areas, the incidence was also high because of the outbreak.\" Please explain further on the high incidence of a few western cities in the province.\n10. Line 229, \"the usual incubation period …\", better?\n11. Line 241-250, these expressions still need improvement.\n\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\n* Declaration of competing interests: **I declare that I have no competing interests.**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please publish my name with my report.**\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\n* Is the presentation of the work clear?: **Yes**\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\n"},{"type":"reviewersInvited","content":"","date":"2020-07-21T12:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-07-21T12:00:00+00:00","index":1,"fulltext":""},{"type":"editorAssigned","content":"","date":"2020-06-29T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-06-28T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-06-28T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}},{"code":2,"date":"2020-05-06 21:49:57","doi":"10.21203/rs.3.rs-20551/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2020-06-08T12:00:00+00:00","index":2,"fulltext":"Recommendation: Major revisions required\nForm responses:\n---\n\nComments to Author:\n---\nThis is a quick study to compare some key epidemiological parameters of COVID-19 in Sichuan province and others.\nTo the data list presentation, the study would be interesting to calculate several more statistic parameters, with epidemiological interpretation\n1. Spatial stratified heterogeneity q statistic of the incidences among the provinces and its change in time;\n2. Spatial autocorrelation coefficient Moran's I of the incidences among the provinces and its change in time;\n* Are the methods appropriate and well described?: **Yes**\n* Does the work include the necessary controls?: **Yes**\n* Are the conclusions drawn adequately supported by the data shown?: **Yes**\n* Are you able to assess any statistics in the manuscript or would you recommend an additional statistical review?: **I am able to assess the statistics**\n* Quality of written English: **Acceptable**\n* Declaration of competing interests: **'I declare that I have no competing interests**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\n"},{"type":"decision","content":"Major revision","date":"2020-06-08T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-05-25T12:00:00+00:00","index":1,"fulltext":"Recommendation: Major revisions required\nForm responses:\n---\n\nComments to Author:\n---\nPlease include all comments for the authors in this box rather than uploading your report as an attachment. Please only upload as attachments annotated versions of manuscripts, graphs, supporting materials or other aspects of your report which cannot be included in a text format.\nPlease overwrite this text when adding your comments to the authors.\n\n\n\nThis manuscript mainly talked about the spatiotemporal distribution characteristics of COVID-19 in the Sichuan province of China, and its comparative analysis with other provinces of China as well as global epidemic trend of COVID-19 pandemic.\nThe major shortcomings of this manuscript are its bad writing qualities: many sentences are not clearly expressed; there are plenty of grammatical errors; and some expressions are ambiguous. \nPlease find some very professional native speakers of English to help improve the writing.\n\nSuggestions:\n1. Please find a native speaker of English to read and help modify the manuscript. For instance, line 12-15, the first sentence is badly needed for improvement. And many other places also need improvement.\n2. Line 143, better to tell readers the 'interquartile range'.\n3. In Figure 5, are you sure about the counted counties in Sichuan?\n4. Line 148, better to tell readers the 'interquartile range'.\n5. Line 174, \"In Eastern Mediterranean Region and Region of the Americas, most countries were at rapid growth phase, as well as Russian in European Region.\" And in Figure 9, \"in part B and D, most countries were at rapid growth phase, as well as Russian in part C.\"\nMy suggestion is to use specific values to tell readers the growing or decreasing speed across your manuscript (not only the two above-mentioned sentences but also other sentences that were written based on data).\n6. In figure 9, \"China reported about 1610 imported cases abroad, about 3 times of Sichuan cumulative cases.\" It is better to include local cases number during the same period.\n7. Line 177-180, \"China reached the peak of the daily increment of the epidemic in 18 days if do not take into account the clinical diagnosis cases and cost 27 days if take into account (Hubei province in China reported clinical diagnosis on February 13-15, and was counted in the 28th COVID-19 Situation Report by WHO which was only applicable to Hubei province).\" This is a not clear expression. This sort of expressions is common throughout the texts. Please modify them.\n8. Line 206, \"the average incubation period of 14 days\"; as I know, the average incubation time seems around a week. Please find more epidemiological studies to make it sure.\n9. Line 217-222, please mark out the figure number where these descriptions correspond to. \n10. Line 227-230, I think, that is a trivial cause for effective control in China. If you want to explore the deep and influential factors/measures between China and other parts of the world, please read more literatures. China took wide stringent measures (such as lockdown, social distancing …) fast. What the authors discussed is far from enough.\n11. Actually, the discussion section is written in a poor quality.\n\n\n* Are the methods appropriate and well described?: **Yes**\n* Does the work include the necessary controls?: **Unable to assess**\n* Are the conclusions drawn adequately supported by the data shown?: **Yes**\n* Are you able to assess any statistics in the manuscript or would you recommend an additional statistical review?: **Not relevant to this manuscript**\n* Quality of written English: **Not suitable for publication unless extensively edited**\n* Declaration of competing interests: **I declare that I have no competing interests.**\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please publish my name with my report.**\n"},{"type":"reviewerAgreed","content":"","date":"2020-05-19T12:00:00+00:00","index":2,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2020-04-30T12:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-04-30T12:00:00+00:00","index":1,"fulltext":""},{"type":"submitted","content":"","date":"2020-04-27T12:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2020-04-27T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-04-26T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-04-26T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2020-04-02 15:29:17","doi":"10.21203/rs.3.rs-20551/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"873f4c52-5339-4506-a4c1-1371c8989473","owner":[],"postedDate":"August 27th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":138038,"name":"Epidemiology"},{"id":138039,"name":"Infectious Diseases"}],"tags":[],"updatedAt":"2020-11-08T15:02:41+00:00","versionOfRecord":{"articleIdentity":"rs-20551","link":"https://doi.org/10.1186/s12879-020-05494-6","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2020-11-05 15:01:22","publishedOnDateReadable":"November 5th, 2020"},"versionCreatedAt":"2020-08-27 15:40:57","video":"","vorDoi":"10.1186/s12879-020-05494-6","vorDoiUrl":"https://doi.org/10.1186/s12879-020-05494-6","workflowStages":[]},"version":"v4","identity":"rs-20551","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-20551","identity":"rs-20551","version":["v4"]},"buildId":"J0_U0BvcaRcwD8yVFaRlm","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}