key: cord-0876183-kh23ancj authors: Weiming, T; Huipeng, L; Gifty, M; Zaisheng, W; Weibin, C; Dan, W; Rongbin, Y title: The changing patter of COVID-19 in China: A tempo-geographic analysis of the SARS-CoV-2 epidemic date: 2020-04-15 journal: Clin Infect Dis DOI: 10.1093/cid/ciaa423 sha: 419a938878e05cb44860b9592a8d72d3e415f613 doc_id: 876183 cord_uid: kh23ancj BACKGROUND: Evaluating whether an infectious disease has reached a turning point is important for planning additional intervention efforts. This study aimed to analyze the changing patterns and the tempo-geographic features of the COVID-19 epidemic, to provide further evidence for real-time responses. METHODS: Daily data on COVID-2019 cases between 31(st) Dec. 2019 and 26(th) Feb. 2020 were collected and analyzed for Hubei and non-Hubei regions. Observed trends for new and cumulative cases were analyzed through joint-point regressions. Spatial analysis was applied to show the geographic distribution and changing pattern of the epidemic. RESULTS: By 26(th) Feb. 2020, 78,630 confirmed COVID-19 cases had been reported in China. In Hubei, an increasing trend (slope=221) was observed for new cases between 24(th) Jan. and February 7(th) Feb. 2020, after which a decline commenced (slope=-868). However, as the diagnosis criteria changed, a sudden increase (slope=5530) was observed on 12(th) Feb., which sharply decreased afterward (slope=-4898). In non-Hubei regions, the number of new cases increased from 20(th) Jan. to 3(rd) Feb. and started to decline afterward (slope=-53). The spatial analysis identified Chongqing, Guangzhou, Shenzhen, Changsha, Nanchang, Wenzhou, Shanghai, Xinyang, Jining, and Beijing as the hotspots outside of Hubei province in China. CONCLUSION AND RELEVANCE: The joint-point regression analysis indicated that the epidemic might have been under control in China, especially for regions outside of Hubei province. Further improvement in the response strategies based on these new patterns is needed. A c c e p t e d M a n u s c r i p t China. The high transmission rate (R0=2‧ 2, ranging between 1‧ 4 and 3‧ 9) and long incubation period (average 6‧ 4 days, ranging from 2‧ 1 to 11‧ 1 days) of the virus coupled with its relatively high mortality rate (2%) made it a global public health emergency event. [1] [2] [3] [4] The situation is further compounded by the high number of presumed hospital-acquired infection, and the potential for secondary transmission through asymptomatic contacts. [2] [3] [4] [5] [6] In response to this epidemic, China issued rapid and comprehensive public health emergency interventions at the national level; upgraded quarantine and isolation guidelines; and expanded its Level One Public Health Emergency Response to 31 provinces within mainland China. All provinces issued the highest level of emergency public health alerts and responses within the national public health management system and cities with high numbers of reported cases went under lockdown with restricted access in most of their communities as part of preventive measures. Due to the high probability of the virus causing a global pandemic, the World Health Organization (WHO) on 30 th Jan. 2020 declared the COVID-19 outbreak a Public Health Emergency of International Concern (PHEIC). 7 Nonetheless, the Chinese government continued to act and implement containment and preventive measures in the global public best interest by reporting the epidemic and improving transparency in data reporting rights from the onset. The ever-increasing flow of A c c e p t e d M a n u s c r i p t 5 information freely available and easily accessible online has allowed the public to understand the emerging epidemic status and the need for compliance. The data has also provided a great opportunity for researchers and public authorities to better understand the epidemic trends, predict the disease patterns, and provide technical support through data analysis. Moreover, the data also provided a better understanding of how SARS-CoV-2 spread temporally and geographically. This study aimed to assess the turning point (which in this study was defined as the time when the rate of case accumulation changes from increasing to decreasing or vice versa) of the epidemic has been reached. The study also aims to identify the tempo-geographic patterns of the epidemic at the provincial and national levels and analyze the changing patterns of the infection. Multiple publicly available data were collected for this data analysis. Daily data on COVID-2019 in China were derived from the national and provincial health commissions' websites (http://www.nhc.gov.cn/). 89 In order to reflect the whole process of the outbreak, the data were systematically collected from 31 st Dec. 2019, when the Hubei health commission first reported about an unknown pneumonia, till 26 th Feb. 2020. The measures collected from these sources included date, the number of new cases reported per day, the cumulative number of cases per day, and the cumulative number of deaths per day at the city, provincial and A c c e p t e d M a n u s c r i p t 6 national levels. Where only cumulative cases were reported by dates, the daily reported number of new cases was estimated by computing the difference between cumulative reported cases in the new day and the previous day. Global data on COVID-2019 from January 13th (when the first COVID-2019 case outside China was reported in Thailand) till February 26 th , 2020 were obtained from the WHO website and other publicly available websites.. 9 As the WHO website did not report daily data about the epidemic outside of China prior to 21 st Jan. 2020, this part of the global data was obtained by searching other websites. 10-12 Global data between 21 st Jan. 2020 and 26 th Feb. 2020 were obtained from the situation report by the World Health Organization 13 and the spatial data on China from GADM version 3.6. 14 All these data sources are freely accessible to the public. All the statistical analyses were carried out using RStudio software (R Core Team, 2016) and Joint-point Trend Analysis version 4.7.0.0 Software (National Cancer Institute, USA). The maps and spatial analysis were generated using ArcGIS 10.2 software (Esri Inc, Redlands, California). Mortality rate was calculated and compared by region (Hubei, non-Hubei in China, and the rest of the world). Since Hubei province being the center of the COVID-2019 outbreak has more reported cases, we hypothesized that its disease trend might differ from non-Hubei regions. Therefore, join-point regression was applied to analyze the trends of new and cumulative cases for Hubei and non-Hubei region and to obtain the dates of the outbreak changing points. Suspected In the hot spot analysis, the conceptualization of spatial relationship was set to inverse distance with the hypothesis that area with smaller distance has higher impact on the calculated field. Z-score, p value, and Gi_Bin were calculated in the hot spot analysis. High z-score with p value <0.01, 0.05, and 0.1 indicated a hotspot. The area where Gi_Bin=3 was the hot spot with 99% confidence; Gi_Bin=2 was hot spot with 95% confidence, Gi_Bin=1 was hot spot with 90% confidence, Gi_Bin =0 was classified as no significant. trend for new cases in Hubei Province increased very slowly at the beginning until January 24 th Jan. 2020 (slope=5) and continued to increase until the first peak was reached around February 7 th (slope =221) after which it started to decrease (slope=-868). However, a sudden peak in the trend was observed with 14,840 cases on 12 th Feb. 2020 , as the disease diagnosis criteria were changed (from laboratory-based confirmation to clinical diagnosis, Graph A) for Hubei province. The number were then returned to 2,420 on 14 th Feb. and continued to decrease to 409 on 26 th Feb. 2020 (slope = 143). Regions out of Hubei province observed a different disease pattern as the trend for daily reported new cases rapidly increased after the new cases were reported on 20 th Jan. 2020 for the first time (slopes=82). The increase of new cases became relatively slow after 29 th Jan. (slope=24) and reached a peak on 3 rd Feb. 2020. The number of newly reported cases in the regions quickly declined after the peak (slope=-53, see Graph B) and was less than 100 after16 th Feb. 2020, when the decreasing trend of new cases became gentle (slope=-9). The cumulative cases showed increasing but different trends Suspected cases for Hubei showed a rapid decreasing trend from 8 th Feb., and the decrease slowed down after 13 th Feb. 2020.(Supplement 1). The number of new cases also decreased in general after 9 th Feb. 2020, except on 12 th Feb. 2020, when the new cases rapidly increased with suspected cases largely decreased. The decreasing trends of both new and suspected cases in Hubei imply that the disease outbreak may be controlled gradually. However, as the number of new cases and suspected cases were still above 400 and 2,000, respectively, more efforts are needed to further reduce COVID-19 infection. The mortality rate for COVID-19 in Hubei provinces, non-Hubei regions in China, overall China, and regions outside of China were 4.0%%, 0.8%%, 3.5%, and 1.5% ‧ respectively (Table 1 ). It is noteworthy that the mortality rate in non-Hubei regions in China and outside of A c c e p t e d M a n u s c r i p t 10 China was much cumulatively lower than that in Hubei and China's national mortality rate was highly impacted by Hubei's (Supplement 2). Dynamic maps of Hubei were produced to show the new cases and cumulative cases changing pattern over time (Supplement 3 and 4) . Huanggang, a neighboring city of Wuhan which recorded 12 cases on 20 th Jan. 2020 was the first city to record a case outside Wuhan. All other cities except Shennongjia started to report new cases from 21 st to 25 th Jan. 2020 and new cases reported in Wuhan increased after 26 th Jan. 2020, followed by Huanggang Xiaogan, and other close by cities. However, Qianjiang,Tianmen and Xiantao, which are also near Wuhan, were not affected as severely as the other neighboring cities. The number of new cases in all the cities were less than 42 from 20 Feb., except for Wuhan; furthermore, over four cities reported zero new case every day since 22 Feb. 2020. Joint-point analysis identified the changing points for cumulative cases in the non-Hubei region to be 26 th Jan., 7 th Feb. 14 th Feb. and this data in addition to 26 th Feb. was used to develop a distribution map to showcase the development of the disease outbreak. Few areas near Hubei and in east China reported COVID-2019 cases in stage A (26 th Jan. 2020, Figure 2 , Graph A) and later evolved into stage B by spreading to most of east China. The disease then spread throughout the country but with less than 20 cases in many cities except for partial north-west China which was unaffected. More cases were found in areas near Hubei, especially Chongqing, where 426 people were infected. Some distant cities from Hubei, such as Guangzhou, Shenzhen, Wenzhou, Shanghai, and Beijing, were also highly affected with over 160 cases (Figure 2, A c c e p t e d M a n u s c r i p t 11 Graph B). The color of the areas near Hubei and highly affected cities gradually and slightly deepened when the outbreak evolved into stage C (Feb. 14) and Stage D (Feb. 26) but all unaffected areas except Yichun in Heilongjiang province remained safe (Figure 3 , Graph C and D). This evidence indicates that although the disease rapidly spread at onset, preventive controlled was achieved. In spatial autocorrelation analysis for non-Hubei regions (Tibet excluded), Moran's I index was 0.13 (P<0.01), demonstrating that the epidemic clusters of COVID-2019 were present. The hotspot analysis ( Figure 3) indicated Chongqing, Guangzhou, Shenzhen, Changsha, Nanchang, Wenzhou, Shanghai, Xinyang, Jining, and Beijing to be epidemic hotspots with about 99% confidence, meaning that these cities are at high risk during the disease outbreak. Harbin was the hotspot with 95% confidence and at relatively high risk. Hangzhou, Hefei, Yueyang, Zhengzhou, Ningbo, Bengbu, Fuyang, Nanyang were also hotspots with 90% confidence and in a moderate risk of the disease. Knowing the epidemic patterns of an infectious disease is important in the planning of public activities. And future studies should aim to evaluate the impact of the dis-quarantine and dis-isolation strategies in these areas. A distinct epidemiological pattern of the COVID-19 epidemic between Hubei province and other regions in China was also observed. For example, whiles the turning point may have been reached by February 3 rd for non-Hubei regions, Hubei province reached this much later and yet recorded another peak on February 12 th . 15 Reasons that may have led to this situation include the fact that Hubei province being the center of the outbreak with over 80% of reported confirmed cases faced the worst impact of the epidemic and recorded higher mortality rates than other regions. 16 Secondary transmission in the region was also hard to control as more time and effort was required to curb the epidemic. Furthermore, prevention reaction to the outbreak was slow at onset as public health authorizes in Hubei province underestimated the potential of the virus and did not fully react even after hundreds of cases had been identified. Due to this slow reaction time, the opportunity for timely prevention of secondary transmission was missed, which in turn led to the global epidemic. The slow reaction time also seriously handicapped the health system of Hubei provinces as over 1700 health care workers got infected, thereby reducing available medical resources for the epidemic control in the region. Other provinces however learnt from Hubei's gaps and reacted early by issuing level one public health emergency responses. This drastic measure at enabled those regions to reach an early turning point during the epidemic before the SARS-CoV-2 could spread further within their regions. In terms of non -Hubei province hotspots, Chongqing, Shanghai, Wenzhou, Shenzhen, A c c e p t e d M a n u s c r i p t 14 Changsha, Langfang, and their neighboring cities were found to be the epidemic hotspots. These cities were prone to being hotspots as they are either close to Hubei provinces or are mega metropolitans in China (especially for Chongqing, Shanghai, and Shenzhen), with over 10 million residents. Thus, even though large amount of prevention effort were instituted in these hotspots, the SARS-CoV-2 prevention and control burden are still extremely high in these regions As such, even after the complete elimination of the infection, preventive measures will still be required in order to minimize the probability of any future epidemic relapse Additionally, public health authorities in these regions should further investigate cases to better understand the facilitating factors of the ongoing transmission in these areas. This study has some limitations. First, as all the data were from publicly available data, it lacked detailed information on patients which prevented us from further assessing the potential driving forces of the epidemic. Secondly, there is a time gap between when a suspected case identification and case confirmation. Therefore, our analysis may not reflect the real-time situation of the epidemic; it still provides time-sensitive information, useful as evidence to aid in further response to the epidemic. Finally, due to the changes in diagnostic criteria for Hubei province on 12 th Feb. 2020, the data reported before and 12 th Feb. 2020 onwards may not be consistent with each other. Our study indicated that the turning point of the COVID-19 epidemic in China have been Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan Epidemiologic and Clinical Characteristics of Novel Coronavirus Infections Involving 13 Patients Outside Wuhan, China Assessing spread risk of Wuhan novel coronavirus within and beyond China Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. The Lancet Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus WHO. Coronavirus disease 2019 (COVID-19) Situation Report-26. 2020. 10. CNBC. China confirms 139 new cases of pneumonia over weekend as coronavirus New SARS-like virus may be spreading outside China. . Medical News Today Screen for New Strain of Coronavirus At 3 U.S. Airports. NPR 2020. 13. (WHO) WHO. Coronavirus disease (COVID-2019) situation reports. 2020. 14. (GADM) DoGAA. GADM maps and data Oxford: GADM Feb 13: Daily briefing on novel coronavirus cases in China Coronavirus COVID-19 Global Cases Baltimore: Johns Hopkins CSSE A c c e p t e d M a n u s c r i p t 16