订阅泛读方向 订阅泛读期刊
  • 我的关注
  • 我的关注
  • {{item.title}}


  • {{item.title}}


  • {{item.subscribe_count}}人订阅



An artificially simulated outbreak of a respiratory infectious disease.


  • 影响因子:2.94
  • DOI:10.1186/s12889-020-8243-6
  • 作者列表:"Guo Z","Xu S","Tong L","Dai B","Liu Y","Xiao D
  • 发表时间:2020-01-30

BACKGROUND:Outbreaks of respiratory infectious diseases often occur in crowded places. To understand the pattern of spread of an outbreak of a respiratory infectious disease and provide a theoretical basis for targeted implementation of scientific prevention and control, we attempted to establish a stochastic model to simulate an outbreak of a respiratory infectious disease at a military camp. This model fits the general pattern of disease transmission and further enriches theories on the transmission dynamics of infectious diseases. METHODS:We established an enclosed system of 500 people exposed to adenovirus type 7 (ADV 7) in a military camp. During the infection period, the patients transmitted the virus randomly to susceptible people. The spread of the epidemic under militarized management mode was simulated using a computer model named "the random collision model", and the effects of factors such as the basic reproductive number (R0), time of isolation of the patients (TOI), interval between onset and isolation (IOI), and immunization rates (IR) on the developmental trend of the epidemic were quantitatively analysed. RESULTS:Once the R0 exceeded 1.5, the median attack rate increased sharply; when R0 = 3, with a delay in the TOI, the attack rate increased gradually and eventually remained stable. When the IOI exceeded 2.3 days, the median attack rate also increased dramatically. When the IR exceeded 0.5, the median attack rate approached zero. The median generation time was 8.26 days, (95% confidence interval [CI]: 7.84-8.69 days). The partial rank correlation coefficients between the attack rate of the epidemic and R0, TOI, IOI, and IR were 0.61, 0.17, 0.45, and - 0.27, respectively. CONCLUSIONS:The random collision model not only simulates how an epidemic spreads with superior precision but also allows greater flexibility in setting the activities of the exposure population and different types of infectious diseases, which is conducive to furthering exploration of the epidemiological characteristics of epidemic outbreaks.


背景: 呼吸道传染病暴发往往发生在人员密集的场所。了解一起呼吸道传染病暴发流行的传播规律,为有针对性地实施科学防控提供理论依据,我们试图建立一个随机模型来模拟一个军营的呼吸道传染病爆发。该模型拟合了疾病传播的一般模式,进一步丰富了传染病传播动力学理论。 方法: 我们建立了一个 500 人在军营中暴露于腺病毒 7 型 (ADV 7) 的封闭系统。在感染期间,患者将病毒随机传播给易感人群。利用 “随机碰撞模型” 的计算机模型,模拟了军事化管理模式下的疫情传播,研究了基本繁殖数 (基本传染数) 、时间隔离的患者 (TOI),间隔发病至隔离 (IOI),预防接种率 (IR)对疫情的发展趋势进行了定量分析。 结果: 一旦基本传染数超过 1.5,中位罹患率急剧增加; 当基本传染数 = 3 时,随着TOI的延迟,罹患率逐渐增加并最终保持稳定。当IOI超过 2.3 天时,中位罹患率也急剧增加。当IR超过 0.5 时,中位罹患率接近零。中位世代时间为 8.26 天,(95% 置信区间 [CI]: 7.84-8.69 天)。疫情罹患率与基本传染数、TOI、IOI和IR的偏秩相关系数分别为 0.61 、 0.17 、 0.45 和 0.27。 结论: 随机碰撞模型不仅以较高的精度模拟了流行病的传播方式,而且在设置暴露人群和不同类型传染病的活动方面具有更大的灵活性,有利于进一步探索疫情暴发的流行病学特征。



作者列表:["Lim J","Jeon S","Shin HY","Kim MJ","Seong YM","Lee WJ","Choe KW","Kang YM","Lee B","Park SJ"]

METHODS::Since mid-December of 2019, coronavirus disease 2019 (COVID-19) infection has been spreading from Wuhan, China. The confirmed COVID-19 patients in South Korea are those who came from or visited China. As secondary transmissions have occurred and the speed of transmission is accelerating, there are rising concerns about community infections. The 54-year old male is the third patient diagnosed with COVID-19 infection in Korea. He is a worker for a clothing business and had mild respiratory symptoms and intermittent fever in the beginning of hospitalization, and pneumonia symptoms on chest computerized tomography scan on day 6 of admission. This patient caused one case of secondary transmission and three cases of tertiary transmission. Hereby, we report the clinical findings of the index patient who was the first to cause tertiary transmission outside China. Interestingly, after lopinavir/ritonavir (Kaletra, AbbVie) was administered, β-coronavirus viral loads significantly decreased and no or little coronavirus titers were observed.

作者列表:["Zhang W","Du RH","Li B","Zheng XS","Yang XL","Hu B","Wang YY","Xiao GF","Yan B","Shi ZL","Zhou P"]

METHODS::In December 2019, a novel coronavirus (2019-nCoV) caused an outbreak in Wuhan, China, and soon spread to other parts of the world. It was believed that 2019-nCoV was transmitted through respiratory tract and then induced pneumonia, thus molecular diagnosis based on oral swabs was used for confirmation of this disease. Likewise, patient will be released upon two times of negative detection from oral swabs. However, many coronaviruses can also be transmitted through oral-fecal route by infecting intestines. Whether 2019-nCoV infected patients also carry virus in other organs like intestine need to be tested. We conducted investigation on patients in a local hospital who were infected with this virus. We found the presence of 2019-nCoV in anal swabs and blood as well, and more anal swab positives than oral swab positives in a later stage of infection, suggesting shedding and thereby transmitted through oral-fecal route. We also showed serology test can improve detection positive rate thus should be used in future epidemiology. Our report provides a cautionary warning that 2019-nCoV may be shed through multiple routes.

翻译标题与摘要 下载文献
作者列表:["Cheng ZJ","Shan J"]

METHODS::There is a current worldwide outbreak of a new type of coronavirus (2019-nCoV), which originated from Wuhan in China and has now spread to 17 other countries. Governments are under increased pressure to stop the outbreak spiraling into a global health emergency. At this stage, preparedness, transparency, and sharing of information are crucial to risk assessments and beginning outbreak control activities. This information should include reports from outbreak sites and from laboratories supporting the investigation. This paper aggregates and consolidates the virology, epidemiology, clinical management strategies from both English and Chinese literature, official news channels, and other official government documents. In addition, by fitting the number of infections with a single-term exponential model, we report that the infection is spreading at an exponential rate, with a doubling period of 1.8 days.