ABSTRACT
The importation of COVID-19 cases in China is due to the returning of Chinese citizens abroad, where the majority of cases stand. This study aimed to evaluate the risk of importing COVID-19 into the Sichuan Province of China and conduct a short-term risk prediction assessment and analysis. Data on COVID-19 cases in each country and Sichuan were collected, as well as visitors to Sichuan, population, area, and medical resources in each city in Sichuan province. According to different control strategies of entry aviation and quarantine control, we built models of epidemic transmission to estimate the risk for imported COVID-19 cases in 21 cities of Sichuan. Within 140 days of the policy change's implementation, the number of susceptible, infected, and recovered people in all cities followed the same pattern over time: (1) the number of susceptible people declined slowly at first, then accelerated to reach a stable value; (2) the number of infections gradually increased to a peak, then decreased; and (3) the number of recovered patients gradually increased to a stable value. Under the four different scenarios, there were no significant differences between the risk peaks because the social distance did not change. However, the peak time would be delayed due to the implementation of flight control and nucleic acid detection measures. The improvement of foreign epidemics (reduction of attenuation factors) all delayed the arrival of the peak risk value in Chengdu by about 20 days; however, the size of the peak value did not change significantly. The improvement of nucleic acid detection accuracy delayed the arrival of the peak risk value in Chengdu, but the size of the peak value did not change significantly. Therefore, flight control and the improvement of nucleic acid detection accuracy and overseas epidemic situations have positively affected the prevention and control of the epidemic in Sichuan.
ABSTRACT
Although coronavirus disease 2019 (COVID-19) remains rampant in many countries, it has recently waned in Sichuan, China. This study examined spatiotemporal variations of the epidemiological characteristics of COVID-19 across its course. Three approaches, i.e. calendar-based, measure-driven and data-driven ones, were applied to all individual cases reported as of 30th November 2020, dividing the COVID-19 pandemic into five periods. A total of 808 people with confirmed diagnosis and 279 asymptomatic cases were reported, the majority of whom were aged 30-49 and <30 years, respectively. The highest risk was seen in Chengdu (capital city), with 411 confirmed and 195 asymptomatic cases. The main sources of infection changed from importation from Hubei Province to importation from other provinces, then local transmission and ultimately importation from foreign countries. The periods highlighted by the three methods presented different epidemic patterns and trends. The calendar-based periods were even with most cases aggregated in the first period, which did not reflect various transmission patterns of COVID-19 due to various sources of infection; the measure-driven and data-driven periods were not consistent with each other, revealing that the effects of implementing prevention measures were reflected on the epidemic trend with a time lag. For example, the decreasing trends of new cases occurred 7, 3 and 4 days later than the firstlevel emergency response, the district-level prevention measures and the second-level emergency response, respectively. This study has advanced our understanding of epidemic course and foreshown all stages of COVID-19 epidemic. Many countries can learn from our findings about what will occur next in their timelines and how to be better prepared.