人工干扰下重大传染病扩散演化的仿真研究——以非典为例

重大传染病发生后若应对不当，往往会借助自然系统或社会系统之间相互依存和相互制约的关系迅速扩散演化，产生一系列次生衍生事件。以重大传染病的发生和发展过程为基础构建其扩散模型，利用系统动力学仿真软件比较不同防控情形下系统演化结果，结果表明：（1）通过对疾病接触系数、自由传播期、开始防控时间进行控制可以改变重大传染病的扩散演化；（2）单独限制人口流动虽可降低传染速率但无法抑制重大传染病的扩散，而同时采取限制人口流动和隔离措施的效果优于单独采取隔离措施。     

Bayesian Inference for Contact Networks Given Epidemic Data

Abstract. In this article, we estimate the parameters of a simple random network and a stochastic epidemic on that network using data consisting of recovery times of infected hosts. The SEIR epidemic model we fit has exponentially distributed transmission times with Gamma distributed exposed and infectious periods on a network where every edge exists with the same probability, independent of other edges. We employ a Bayesian framework and Markov chain Monte Carlo (MCMC) integration to make estimates of the joint posterior distribution of the model parameters. We discuss the accuracy of the parameter estimates under various prior assumptions and show that it is possible in many scientifically interesting cases to accurately recover the parameters. We demonstrate our approach by studying a measles outbreak in Hagelloch, Germany, in 1861 consisting of 188 affected individuals. We provide an R package to carry out these analyses, which is available publicly on the Comprehensive R Archive Network.     

A Risk Analysis Approach to Prioritizing Epidemics: Ebola Virus Disease in West Africa as a Case Study

The 2014 Ebola virus disease (EVD) outbreak affected several countries worldwide, including six West African countries. It was the largest Ebola epidemic in the history and the first to affect multiple countries simultaneously. Significant national and international delay in response to the epidemic resulted in 28,652 cases and 11,325 deaths. The aim of this study was to develop a risk analysis framework to prioritize rapid response for situations of high risk. Based on findings from the literature, sociodemographic features of the affected countries, and documented epidemic data, a risk scoring framework using 18 criteria was developed. The framework includes measures of socioeconomics, health systems, geographical factors, cultural beliefs, and traditional practices. The three worst affected West African countries (Guinea, Sierra Leone, and Liberia) had the highest risk scores. The scores were much lower in developed countries that experienced Ebola compared to West African countries. A more complex risk analysis framework using 18 measures was compared with a simpler one with 10 measures, and both predicted risk equally well. A simple risk scoring system can incorporate measures of hazard and impact that may otherwise be neglected in prioritizing outbreak response. This framework can be used by public health personnel as a tool to prioritize outbreak investigation and flag outbreaks with potentially catastrophic outcomes for urgent response. Such a tool could mitigate costly delays in epidemic response.     

Stochastic differential equation systems for an SIS epidemic model with vaccination and immigration

Two Itô stochastic differential equation (SDE) systems are constructed for a Susceptible-Infected-Susceptible epidemic model with temporary vaccination. A constant number of new members enter the population and total size of the population is variable. Some conditions for disease extinction in the stochastic models are established and compared with conditions in deterministic one. It is shown that the two stochastic models are equivalent in the sense that their solutions come from same distribution. In addition, the SDE models are simulated and the equivalence of the two stochastic models is confirmed by numerical examples. The probability distribution for extinction is also obtained numerically, provided there exists a probability for disease persistence whereas the expected duration of epidemic is acquired when extinction occurs with probability 1.     

Bayesian Inference for a Stochastic Epidemic Model with Uncertain Numbers of Susceptibles of Several Types

A stochastic epidemic model with several kinds of susceptible is used to analyse temporal disease outbreak data from a Bayesian perspective. Prior distributions are used to model uncertainty in the actual numbers of susceptibles initially present. The posterior distribution of the parameters of the model is explored via Markov chain Monte Carlo methods. The methods are illustrated using two datasets, and the results are compared where possible to results obtained by previous analyses.     

Epidemics in heterogeneous communities: estimation of R0 and secure vaccination coverage

A stochastic multitype model for the spread of an infectious disease in a community of heterogeneous individuals is analysed. In particular, estimates of R ₀ (the basic reproduction number) and the critical vaccination coverage are derived, where estimation is based on final size data of an outbreak in the community. It is shown that these key parameters cannot be estimated consistently from data; only upper and lower bounds can be estimated. Confidence regions for the upper bounds are derived, thus giving conservative estimates of R ₀ and the fractions necessary to vaccinate.     

A Multicompartment SIS Stochastic Model with Zonal Ventilation for the Spread of Nosocomial Infections: Detection,Outbreak Management,and Infection Control

In this work, we study the environmental and operational factors that influence airborne transmission of nosocomial infections. We link a deterministic zonal ventilation model for the airborne distribution of infectious material in a hospital ward, with a Markovian multicompartment SIS model for the infection of individuals within this ward, in order to conduct a parametric study on ventilation rates and their effect on the epidemic dynamics. Our stochastic model includes arrival and discharge of patients, as well as the detection of the outbreak by screening events or due to symptoms being shown by infective patients. For each ventilation setting, we measure the infectious potential of a nosocomial outbreak in the hospital ward by means of a summary statistic: the number of infections occurred within the hospital ward until end or declaration of the outbreak. We analytically compute the distribution of this summary statistic, and carry out local and global sensitivity analysis in order to identify the particular characteristics of each ventilation regime with the largest impact on the epidemic spread. Our results show that ward ventilation can have a significant impact on the infection spread, especially under slow detection scenarios or in overoccupied wards, and that decreasing the infection risk for the whole hospital ward might increase the risk in specific areas of the health‐care facility. Moreover, the location of the initial infective individual and the protocol in place for outbreak declaration both form an interplay with ventilation of the ward.     

1941年日军常德细菌战造成城区居民死亡人数的研究

常德细菌战造成常德城区和平居民死亡的人数,日本学者据历史的防疫档案记录认为可以确定的是37人;据常德细菌战受害调查会近七年来的调查是336人;而据当年曾参与常德防疫工作的人士估计:有400人以上、50D人以上和600人以上三种说法。我们依据各种史实分析研究,认为死亡600人以上的说法是可信的,并且还有可能超过这一数字。     

玉米矮花叶病毒生物学特征研究概述

对玉米矮花叶病毒病原特性，侵染循环，寄主范围，发病因素及防治措施等国内外研究进展进行了综述。     

从新冠肺炎疫情防控看我国重大公共卫生事件的预防和应对策略

新型冠状病毒肺炎疫情防控工作开展以来,国家在疫情应对过程中总结了很多成功经验,为其他国家和地区开展疫情防控提供了有益参考。同时,也存在很多问题需要在今后的工作中改进和提高。文章从重大突发公共卫生事件有效预防和应对的视角,梳理了疫情防控工作中的有力举措和存在问题,为进一步完善我国重大公共卫生事件应急管理体系建设提供参考依据。