ABSTRACT
Objective: To explore the temporal and spatial distribution characteristics of confirmed cases of coronavirus disease(COVID-19)in Zhejiang Province and to determine the correlation between number of confirmed cases and geographical demographic factors, so as to provide theoretical basis for the prevention and control of COVID-19.
ABSTRACT
Objective: To analyze the epidemiological characteristics and spatial-temporal clustering of coronavirus disease 2019(COVID-19)in Hebei Province in order to provide scientific basis for the formulation of prevention and control measures.
ABSTRACT
Objective: To analyze the epidemiological characteristics and incubation of coronavirus disease 2019(COVID-19)from Jan. 22 to Mar. 8, 2020 in Anhui Province, in order to provide the basis for further understanding of the transmission pattern of COVID-19 and formulating regional control measures.
ABSTRACT
Objective: To explore the spatiotemporal distribution of COVID-19 in Wenzhou and to provide theoretical basis for the formulation of preventive and control measures.
ABSTRACT
Objective: To explore the related influence factors of coronavirus diseases 2019(COVID-19)in Shandong Province and understand the regional distribution characteristics of the epidemic situation, and to provide a scientific basis for guiding prevention and control strategies.
ABSTRACT
Objective: To explore the epidemic dynamics of coronavirus disease 2019(COVID-19)in Shandong Province, and to provide a scientific basis for the future prevention and control of new outbreaks of COVID-19 and other emerging infectious diseases.
ABSTRACT
Objective: To explore epidemic dynamics of coronavirus disease 2019 (COVID-19) in Xinyang City so as to provide scientific basis for optimizing the prevention and control strategies and evaluating the effects of intervention.
ABSTRACT
Background: Novel coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), is now sweeping across the world. A substantial proportion of infections only lead to mild symptoms or are asymptomatic, but the proportion and infectivity of asymptomatic infections remains unknown. In this paper, we proposed a model to estimate the proportion and infectivity of asymptomatic cases, using COVID-19 in Henan Province, China, as an example. Methods: We extended the conventional susceptible-exposed-infectious-recovered model by including asymptomatic, unconfirmed symptomatic, and quarantined cases. Based on this model, we used daily reported COVID-19 cases from January 21 to February 26, 2020, in Henan Province to estimate the proportion and infectivity of asymptomatic cases, as well as the change of effective reproductive number, R t . Results: The proportion of asymptomatic cases among COVID-19 infected individuals was 42% and the infectivity was 10% that of symptomatic ones. The basic reproductive number R 0 = 2.73, and R t dropped below 1 on January 31 under a series of measures. Conclusion: The spread of the COVID-19 epidemic was rapid in the early stage, with a large number of asymptomatic infected individuals having relatively low infectivity. However, it was quickly brought under control with national measures.
ABSTRACT
Background: The asymptomatic proportion is a critical epidemiological characteristic that modulates the pandemic potential of emerging respiratory virus, which may vary depending on the nature of the disease source, population characteristics, source-host interaction, and environmental factors. Methods: We developed a simple likelihood-based framework to estimate the instantaneous asymptomatic proportion of infectious diseases. Taking the COVID-19 epidemics in Hong Kong as a case study, we applied the estimation framework to estimate the reported asymptomatic proportion (rAP) using the publicly available surveillance data. We divided the time series of daily cases into four stages of epidemics in Hong Kong by examining the persistency of the epidemic and compared the rAPs of imported cases and local cases at different stages. Results: As of July 31, 2020, there were two intermittent epidemics in Hong Kong. The first one was dominated by imported cases, accounting for 63.2% of the total cases, and the second one was dominated by local cases, accounting for 86.5% of the total cases. The rAP was estimated at 23.1% (95% CI: 10.8-39.7%) from January 23 to July 31, and the rAPs were estimated at 22.6% (95% CI: 11.1-38.9%) among local cases and 38.7% (95% CI: 9.0-72.0%) among imported cases. Our results showed that the rAPs of local cases were not significantly different between the two epidemics, but increased gradually during the first epidemic period. In contrast, the rAPs of imported cases in the latter epidemic period were significantly higher than that in the previous epidemic period. Conclusion: Hong Kong has a high rAP of imported COVID-19 cases and should continue to strengthen the detection and isolation of imported individuals to prevent the resurgence of the disease.
Subject(s)
COVID-19 , Hong Kong/epidemiology , Humans , Likelihood Functions , Pandemics , SARS-CoV-2ABSTRACT
The ongoing pandemic of 2019 novel coronavirus disease (COVID-19) is challenging global public health response system. We aim to identify the risk factors for the transmission of COVID-19 using data on mainland China. We estimated attack rate (AR) at county level. Logistic regression was used to explore the role of transportation in the nationwide spread. Generalized additive model and stratified linear mixed-effects model were developed to identify the effects of multiple meteorological factors on local transmission. The ARs in affected counties ranged from 0.6 to 9750.4 per million persons, with a median of 8.8. The counties being intersected by railways, freeways, national highways or having airports had significantly higher risk for COVID-19 with adjusted odds ratios (ORs) of 1.40 (p = 0.001), 2.07 (p < 0.001), 1.31 (p = 0.04), and 1.70 (p < 0.001), respectively. The higher AR of COVID-19 was significantly associated with lower average temperature, moderate cumulative precipitation and higher wind speed. Significant pairwise interactions were found among above three meteorological factors with higher risk of COVID-19 under low temperature and moderate precipitation. Warm areas can also be in higher risk of the disease with the increasing wind speed. In conclusion, transportation and meteorological factors may play important roles in the transmission of COVID-19 in mainland China, and could be integrated in consideration by public health alarm systems to better prevent the disease.