[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.

[Risk assessment of exported risk of COVID-19 from Hubei Province].

Objective: To evaluate the exported risk of COVID-19 from Hubei Province and the imported risk in various provinces across China. Methods: Data of reported COVID-19 cases and Baidu Migration Indexin all provinces of the country as of February 14, 2020 were collected. The correlation analysis between cumulative number of reported cases and the migration index from Hubei was performed, and the imported risks from Hubei to different provinces across China were further evaluated. Results: A total of 49 970 confirmed cases were reported nationwide, of which 37 884 were in Hubei Province. The average daily migration index from Hubei to other provinces was 312.09, Wuhan and other cities in Hubei were 117.95 and 194.16, respectively. The cumulative COVID-19 cases of provinces was positively correlated with the migration index derived from Hubei Province, also in Wuhan and other cities in Hubei, with correlation coefficients of 0.84, 0.84, and 0.81. In linear model, population migration from Hubei Province, Wuhan and other cities in Hubei account for 71.2%, 70.1%, and 66.3% of the variation, respectively. The period of high exported risk from Hubei occurred before January 27, of which the risks before January 23 mainly came from Wuhan, and then mainly from other cities in Hubei. Hunan Province, Henan Province and Guangdong Province ranked the top three in terms of cumulative imported risk (the cumulative risk indices were 58.61, 54.75 and 49.62 respectively). Conclusion: The epidemic in each province was mainly caused by the importation of Hubei Province. Taking measures such as restricting the migration of population in Hubei Province and strengthening quarantine measures for immigrants from Hubei Province may greatly reduce the risk of continued spread of the epidemic.

[The definition of heat-wave based on mortality risk assessment in different regions of China].

Objective: To identify the definition of heat wave based on mortality risk assessment in different regions of China. Methods: Daily mortality (from China Information System for Disease Control and Prevention) and meteorological data (from National Meteorological Information Center in China) from 66 counties with a population of over 200 000 were collected from 2006-2011. With the consideration of climate type and administrative division, China was classified as seven regions. Firstly, distributed lag non-linear model (DLNM) was used to estimate community-specific effects of temperature on non-accidental mortality. Secondly, a multivariate meta-analysis was applied to pool the estimates of community-specific effects to explore the region-specific temperature threshold and the duration for definition of heat wave. Results: We defined regional heat wave of Northeast, North, Northwest, East, Central and Southwest China as being two or more consecutive days with daily mean temperature higher than or equal to the P(64), P(71), P(85), P(67), P(75) and P(77) of warm season (May to October) temperature, respectively, while the thresholds of temperature were 21.6, 23.7, 24.3, 25.7, 28.0 and 25.3 ℃. The heat wave in South China was defined as five or more consecutive days with daily mean temperature higher than or equal to the P(93) (30.4 ℃) of warm season (May to October) temperature. Conclusion: The region-specific definition of heat wave developed in our study may provide local government with the guidance of establishment and implementation of early heat-health response systems to address the negative health outcomes due to heat wave.