Assessing the spread risk of COVID-19 associated with multi-mode transportation networks in China

The spatial spread of COVID-19 during early 2020 in China was primarily driven by outbound travelers leaving the epicenter, Wuhan, Hubei province. Existing studies focus on the influence of aggregated out-bound popula-tion flows originating from Wuhan;however, the impacts of different modes of transportation and the network structure of transportation systems on the early spread of COVID-19 in China are not well understood. Here, we assess the roles of the road, railway, and air transportation networks in driving the spatial spread of COVID-19 in China. We find that the short-range spread within Hubei province was dominated by ground traffic, notably, the railway transportation. In contrast, long-range spread to cities in other provinces was mediated by multiple factors, including a higher risk of case importation associated with air transportation and a larger outbreak size in hub cities located at the center of transportation networks. We further show that, although the dissemination of SARS-CoV-2 across countries and continents is determined by the worldwide air transportation network, the early geographic dispersal of COVID-19 within China is better predicted by the railway traffic. Given the recent emergence of multiple more transmissible variants of SARS-CoV-2, our findings can support a better assessment of the spread risk of those variants and improve future pandemic preparedness and responses.

[Epidemiological characteristics of 2019-nCoV Delta variant in Gansu province].

Objective: To analyze the epidemiological characteristics of COVID-19 caused by 2019-nCoV Delta variant (B.1.617.2) in Gansu province, and provide evidence for the prevention and control of COVID-19. Methods: The information of COVID-19 cases, including demographic characteristics, epidemiological history, onset date, diagnosis date, exposure place, detection way and infection source, in Gansu from 17 October to 25 November, 2021 were collected. Software Excel 2016,SPSS 22 and ArcGIS 10.7 were used for data process and analysis. Results: As of November 25, 2021, a total of 146 COVID-19 cases had been reported in Gansu and the epidemic affected 10 counties (districts) in 5 cities. The epidemic of COVID-19 in Gansu had three stages: imported case stage,imported-local case stage and local case stage. The age of cases ranged from 1 to 87 years,and the cases in age group 18-59 years accounted for 59.59% (87/146). The male to female ratio of the cases was 1∶1.12 (69∶77). The cases were mainly people engaged in business services (17.12%, 25/146),retirees (15.75%, 23/146),students (13.70%, 20/146),the jobless and unemployed (12.33%, 18/146). In 3 epidemic stages, the cases aged 18-59 years accounted for 44.44%,54.41% and 70.00% respectively,showing an upward trend,and there were differences among different populations (trend χ2=23.24, P<0.001). Also, the incubation period of the cases tended to decrease, and severe cases accounted for 33.33% (6/18), 19.12% (13/68) and 3.33% (2/60) respectively, showing a downward trend. Community screening (25.34%, 37/146) and close contact screening were the main ways to detect cases,the cases detected by close contact screening in 3 epidemic stages accounted for 50.00% (9/18), 66.18% (45/68) and 86.67% (52/60) respectively. The epidemic had obvious case clustering in confined places,and the main exposure modes were living together (24.66%), working/studying together (11.64%), taking same transportation (9.59%) and dining together (9.59%). Conclusions: The COVID-19 epidemic in Gansu was caused by 2019-nCoV Delta variant from imported cases. The virus was mainly transmitted through travel, sharing transportation, dining together and home contact. The characteristics of COVID-19 epidemic in Gansu changed with time, the case's clinical symptoms were not obvious and the incubation period became shorter. The infections mainly occurred in group aged 18 years and above.

[Epidemiological characteristics of COVID-19 epidemic in Ejina banner, Inner Mongolia Autonomous Region, October 2021].

Objective: To understand the epidemiological characteristics of COVID-19 epidemic in Ejina banner, Inner Mongolia, in October 2021 and provide evidence for the improvement of COVID-19 prevention and control. Methods: The information about the time, area and population distributions of COVID-19 cases in Ejina before November 13, 2021 and the gene sequencing result of the isolates were collected for a statistical descriptive analysis. Results: The first COVID-19 case in Ejina occurred on 7 October, 2021. A total of 164 COVID-19 cases were reported from October 19 to November 12. Most cases were distributed in 6 communities in Darahub (156 cases, 95.12%). The result of full gene sequencing of the isolates indicted that the pathogen was Delta variant (B.1.617.2). The male to female ratio of the cases was 1.3∶1. The age of cases ranged from 1 to 85 years, and the cases aged 20-59 years accounted for 78.66%. The main clinical symptoms were sore throat (91 cases, 91.92%), cough (49 cases, 49.49%) and fever (23 cases, 23.23%). Most cases were ordinary ones (81 cases, 49.39%) and mild ones (68 cases, 41.46%). The cases were mainly detected at the isolation points (84 cases, 51.22%) and through population based nucleic acid testing (62 cases, 37.80%). The basic reproduction number (R0) of COVID-19 was 5.3, the average incubation period was 3.9 days. The local government rapidly started Ⅳ level emergency response and conducted 10 rounds of nucleic acid tests. The transferring of travelers reduced the risk for the further spread of COVID-19 in Ejina. Conclusions: The epidemic of COVID-19 in Ejina characterized by strong transmission, short incubation period, herd susceptibility and case clustering. Delta variant (B.1.617.2) was the pathogen, which might be imported from Zeke port. Comprehensive prevention and control measures, such as closed-loop management and vaccination, should be continued. The successful transferring of the patients and travelers provided evidence for the effective and precise prevention and control of COVID-19 in a routine manner.

A Heterogeneous Branching Process with Immigration Modeling for COVID-19 Spreading in Local Communities in China

The COVID-19 pandemic spread catastrophically over the world since the spring of 2020. In this paper, a heterogeneous branching process with immigration is established to quantify the human-to-human transmission of COVID-19 in local communities, based on the temporal and structural transmission patterns extracted from public case disclosures by four provincial Health Commissions in China. With proper parameter settings, our branching model matches the actual transmission chains satisfactorily and, therefore, sheds light on the underlying COVID-19 spreading mechanism. Moreover, based on our branching model, the efficacy of home quarantine and social distancing are explored, providing a reference for the effective prevention of COVID-19 worldwide. © 2021 Lin Zhang et al.

Characterizing COVID-19 Transmission: Incubation Period, Reproduction Rate, and Multiple-Generation Spreading

Understanding the transmission process is crucial for the prevention and mitigation of COVID-19 spread. This paper contributes to the COVID-19 knowledge by analyzing the incubation period, the transmission rate from close contact to infection, and the properties of multiple-generation transmission. The data regarding these parameters are extracted from a detailed line-list database of 9,120 cases reported in mainland China from January 15 to February 29, 2020. The incubation period of COVID-19 has a mean, median, and mode of 7.83, 7, and 5 days, and, in 12.5% of cases, more than 14 days. The number of close contacts for these cases during the incubation period and a few days before hospitalization follows a log-normal distribution, which may lead to super-spreading events. The disease transmission rate from close contact roughly decreases in line with the number of close contacts with median 0.13. The average secondary cases are 2.10, 1.35, and 2.2 for the first, second, and third generations conditioned on at least one offspring. However, the ratio of no further spread in the 2nd, 3rd, and 4th generations are 26.2, 93.9, and 90.7%, respectively. Moreover, the conditioned reproduction number in the second generation is geometrically distributed. Our findings suggest that, in order to effectively control the pandemic, prevention measures, such as social distancing, wearing masks, and isolating from close contacts, would be the most important and least costly measures. © Copyright © 2021 Zhang, Zhu, Wang, Yang, Liu and Xu.

Analysis of COVID-19 spreading and prevention strategy in schools based on continuous infection model

After the COVID-19 epidemic leveled off in China, many provinces have started to resume schooling. Long-term contact between students and teachers in such a closed environment in schooling can increase the possibility of the outbreak. Although the school closure can effectively alleviate the epidemic, large-scale students' isolation not only causes social panic but also brings huge social and economic burden, so before the emergence of school epidemics, one should select and adopt more scientific prevention and control measures. In this study, according to the virus excretion of COVID-19 patients in the disease period, the infectious capacity of patients is redefined. After introducing it into the traditional suspected-exposed-infected-removed (SEIR) model, a continuous infection model that is more consistent with the actual transmission of COVID-19 patients is proposed. Secondly, the effective distance between students is calculated through real contact data. Based on the analysis of the effective distance, three types of isolation area prevention and control measures are proposed and compared with the recently proposed digital contact tracking prevention and control measures. Simulating the spread of COVID-19 in schools through real student contact data and continuous infection models, in order to compare the preventions and control effects of various prevention and control measures in the school epidemic situation, and evaluating the social influence of measures by accumulating the number of quarantines when prevention and control measures are adopted, we find that the COVID-19 can lead the cases to happen on a larger scale in the continuous infection model than in the traditional SEIR model, and the prevention and control measures verified in the continuous infection model are more convincing. Using digital contact tracking prevention and control measures in schools can achieve similar results to those in closed schools with the smallest number of quarantines. The research in this paper can help schools choose appropriate prevention and control measures, and the proposed continuous infection model can help researchers more accurately simulate the spread of COVID-19. Copyright © 2020 Acta Physica Sinica. All rights reserved.

[Epidemiological characteristics of COVID-19 in Gansu province].

Objective: To understand the epidemiological characteristics of COVID-19 cases in different epidemic stages in Gansu province. Methods: Epidemiological investigation was conducted to collect the information of confirmed COVID-19 cases, including demographic, epidemiological and clinical information. Results: As of 25 February 2020, a total of 91 confirmed COVID-19 cases had been reported in Gansu. The epidemic of COVID-19 in Gansu can be divided as three different stages, i.e. imported case stage, imported-case plus indigenous case stage, and indigenous case stage. A total of 63 cases were clustered cases (69.23%), 3 cases were medical staff infected with non-occupational exposure. The initial symptoms included fever (54.95%, 50/91), cough (52.75%, 48/91), or fatigue (28.57%, 26/91), the proportion of each symptom showed a decreasing trend along with the three epidemic stages, but only the differences in proportions of fever (trend χ2=2.20, P<0.05) and fatigue (trend χ2=3.18, P<0.05) among the three epidemic stages were statistically significant. The cases with critical severe symptoms accounted for 42.85% (6/14), 23.73% (14/59) and 16.67% (3/18), respectively, in three epidemic stages, showed a decreasing trend (H=6.45, P<0.05). Also, the incubation period prolonged along with the epidemic stage (F=51.65, P<0.01), but the intervals between disease onset and hospital visit (F=5.32, P<0.01), disease onset and diagnosis (F=5.25, P<0.01) became shorter along with the epidemic stage. Additionally, the basic reproduction number (R0) had decreased from 2.61 in imported case stage to 0.66 in indigenous case stage. Conclusions: The COVID-19 epidemic in Gansu was caused by the imported cases, and about 2/3 cases were clustered ones. No medical worker was observed to be infected by occupational exposure. With the progression of COVID-19 epidemic in Gansu, the change in initial symptom and incubation period suggests, the early screening cannot only depend on body temperature monitoring.