[Risk assessment and early warning of imported COVID-19 in Guangdong province].

Objective: To assess the imported risk of COVID-19 in Guangdong province and its cities, and conduct early warning. Methods: Data of reported COVID-19 cases and Baidu Migration Index of 21 cities in Guangdong province and other provinces of China as of February 25, 2020 were collected. The imported risk index of each city in Guangdong province were calculated, and then correlation analysis was performed between reported cases and the imported risk index to identify lag time. Finally, we classified the early warming levels of epidemic by imported risk index. Results: A total of 1 347 confirmed cases were reported in Guangdong province, and 90.0% of the cases were clustered in the Pearl River Delta region. The average daily imported risk index of Guangdong was 44.03. Among the imported risk sources of each city, the highest risk of almost all cities came from Hubei province, except for Zhanjiang from Hainan province. In addition, the neighboring provinces of Guangdong province also had a greater impact. The correlation between the imported risk index with a lag of 4 days and the daily reported cases was the strongest (correlation coefficient: 0.73). The early warning base on cumulative 4-day risk of each city showed that Dongguan, Shenzhen, Zhongshan, Guangzhou, Foshan and Huizhou have high imported risks in the next 4 days, with imported risk indexes of 38.85, 21.59, 11.67, 11.25, 6.19 and 5.92, and the highest risk still comes from Hubei province. Conclusions: Cities with a large number of migrants in Guangdong province have a higher risk of import. Hubei province and neighboring provinces in Guangdong province are the main source of the imported risk. Each city must strengthen the health management of migrants in high-risk provinces and reduce the imported risk of Guangdong province.

[Evaluation of the emergency response strategies and measures on the epidemic of COVID-19 in Shenzhen, China].

Objectives: This study aimed to evaluate the effect of the strategies on COVID-19 outbreak control in Shenzhen, and to clarify the feasibility of these strategies in metropolitans that have high population density and strong mobility. Methods: The epidemic feature of COVID-19 was described by different phases and was used to observe the effectiveness of intervention. Hierarchical spot map was drawn to clarify the distribution and transmission risk of infection sources at different time points. The Susceptible-Exposed-Infectious-Asymptomatic-Recovered model was established to estimate case numbers without intervention and compare with the actual number of cases to determine the effect of intervention. The positive rate of the nucleic acid test was used to reflect the risk of human exposure. A survey on COVID-19 related knowledge, attitude and behaviors were used to estimate the abilities of personal protection and emergency response. Results: The epidemic of COVID-19 in Shenzhen experienced the rising, plateau and decline stage. The case number increased rapidly at the beginning, with short duration of peak period. Although the epidemic curve showed human-to-human transmission, the "trailing" was not obvious. From the spot map, during the intervention period, the source of infection was widely distributed. More cases and higher transmission risk were observed in areas with higher population density. After the effective intervention measures, both infection sources and the risk of transmission decreased. After compared with the estimated case numbers without intervention, actual number proved the COVID-19 control strategies were effective. The positive rate of nucleic acid test for high risk populations decreased and no new cases reported since February 16. Shenzhen citizens had high knowledge, attitude and behavior level, and high protection ability and emergency response. Conclusions: Although the response initiated by the health administration department played a key role at the early stage of the epidemic, it was not enough to contain the outbreak of COVID-19. The first-level emergency response initiated by provincial and municipal government was effective and ensured the start of work resumption after the Spring Festival. Metropolitans like Shenzhen can also achieve the goals of strategies and measures for containment and mitigation of COVID-19.

[Clinical outcomes of COVID-19 cases and influencing factors in Guangdong province].

Objective: To analyze the clinical courses and outcomes of COVID-19 cases and the influencing factors in Guangdong province and provide basis for the formulation or adjustment of medical care and epidemic control strategy for COVID-19. Methods: We collected demographic data, medical histories, clinical courses and outcomes of 1 350 COVID-19 patients reported in Guangdong as of 4 March 2020 via epidemiological investigation and process tracking. Disease severity and clinical course characteristics of the patients and influencing factors of severe illness were analyzed in our study. Results: Among 1 350 cases of COVID-19 cases in Guangdong, 72 (5.3%) and 1 049 (77.7%) were mild and ordinary cases, 164 (12.1%) were severe cases, 58 (4.3%) were critical cases and 7 (0.5%) were fatal. The median duration of illness were 23 days (P(25), P(75): 18, 31 days) and the median length of hospitalization were 20 days (P(25), P(75): 15,27 days). For severe cases, the median time of showing severe manifestations was on the 12(th) day after onset (P(25), P(75): 9(th) to 15(th) days), and the median time of severe manifestation lasted for 8 days (P(25), P(75): 4, 14 days). Among 1 066 discharged/fetal cases, 36.4% (36/99) and 1.0% (1/99) of the mild cases developed to ordinary cases and severe cases respectively after admission; and 5.2% (50/968) and 0.6% (6/968) of the ordinary cases developed to severe cases, and critical cases respectively after admission. In severe cases, 11.4% developed to critical cases (10/88). The influencing factors for severe illness or worse included male (aHR=1.87, 95%CI: 1.43-2.46), older age (aHR=1.67, 95%CI: 1.51-1.85), seeking medical care on day 2-3 after onset (aHR=1.73, 95%CI: 1.20-2.50) pre-existing diabetes (aHR=1.75, 95%CI: 1.12-2.73) and hypertension (aHR=1.49, 95%CI: 1.06-2.09). Conclusions: The course of illness and length of hospitalization of COVID-19 cases were generally long and associated with severity of disease clinical outcomes. The severe cases were mainly occurred in populations at high risk. In the epidemic period, classified management of COVID-19 cases should be promoted according to needs for control and prevention of isolation and treatment for the purpose of rational allocation of medical resources.