一起流行性脑脊髓膜炎疫情的调查及控制

目的对流行性脑脊髓膜炎疫情进行流行病学分析,以了解流行性脑脊髓膜炎(流脑)发生的特点,评价防控措施的效果。方法采用现场流行病学、血清学调查的方法对发生的流行性脑脊髓膜炎疫情进行调查分析。结果此疫情鉴定为一起C群脑膜炎奈瑟菌引起的聚集性病例,3例病人均已接种过A群流脑多糖疫苗3～4次,而未接种过A群C群流脑多糖疫苗,对C群脑膜炎奈瑟菌无免疫力;采取相应措施后疫情得到控制,没有引起流脑流行。结论对C群脑膜炎奈瑟菌所致疫情,采取以预防性服药、应急接种为主的综合控制措施能得到有效控制。     

Combining syndromic surveillance and ILI data using particle filter for epidemic state estimation

Designing effective mitigation strategies against influenza outbreak requires an accurate prediction of a disease’s future course of spreading. Real time information such as syndromic surveillance data and influenza-like-illness (ILI) reports by clinicians can be used to generate estimates of the current state of spreading of a disease. Syndromic surveillance data are immediately available, in contrast to ILI reports that require data collection and processing. On the other hand, they are less credible than ILI data because they are essentially behavioral responses from a community. In this paper, we present a method to combine immediately-available-but-less-reliable syndromic surveillance data with reliable-but-time-delayed ILI data. This problem is formulated as a non-linear stochastic filtering problem, and solved by a particle filtering method. Our experimental results from hypothetical pandemic scenarios show that state estimation is improved by utilizing both sets of data compared to when using only one set. However, the amount of improvement depends on the relative credibility and length of delay in ILI data. An analysis for a linear, Gaussian case is presented to support the results observed in the experiments.     

2012年大连市流行性角结膜炎疫情的病原鉴定与基因特征分析

目的 鉴定一起大连市流行性角结膜炎疫情的病原体及型别.方法 采用荧光PCR方法针对30份眼拭标本进行检测,确定病原,并针对特定片段扩增产物测序进行分子定型.结果 21份标本荧光PCR检测结果为腺病毒阳性,核苷酸序列与人腺病毒15、29、56及其重组型高度同源,多重序列比对后构建的系统进化树上与人腺病毒56及其重组型位于同一分支.结论 本次疫情的致病病原为D亚属人腺病毒,疑为人腺病毒56型或其重组型.后续需要开展对五邻体(Penton)及纤突(Fi-ber)基因的全核苷酸序列测定及生物信息学分析最终确定型别.     

Nonhomogeneous birth and death models for epidemic outbreak data

In this paper, generalized nonlinear models are proposed in order to incorporate the following considerations in modeling an epidemic disease outbreak statistically. (1) The dependence of the data is handled with a nonhomogeneous death or a nonhomogeneous birth process. (2) The first stage of the outbreak is described with an epidemic susceptibles-infectives-removed (SIR) model. Soon the control measures taken will dominate the process. These measures are in addition to the natural epidemic removal process. The prevalence is related to the censored infection times in such a way that the distribution function and thus the survival function satisfy approximately the first equation of the SIR model. This leads in a natural way to the Burr family of distributions. (3) The nonhomogeneous birth process handles the fact that in practice, with some delay, infecteds are registered, but not susceptibles. (4) Finally, the ending of the epidemic caused by the measures taken is incorporated through a modification of the survival function with a final-size parameter, in the same way as is done in long-term survival models. These models are applied to three outbreaks: The Dutch classical swine fever outbreak from 1997 to 1998, the foot- and-mouth disease outbreak in Great Britain from 2001, and the Dutch avian influenza (H7N7) outbreak from 2003.     

The effect of superspreading on epidemic outbreak size distributions

Recently, evidence has been presented to suggest that there are significant heterogeneities in the transmission of communicable diseases. Here, a stochastic simulation model of an epidemic process that allows for these heterogeneities is used to demonstrate the potentially considerable effect that heterogeneity of transmission will have on epidemic outbreak size distributions. Our simulation results agree well with approximations gained from the theory of branching processes. Outbreak size distributions have previously been used to infer basic epidemiological parameters. We show that if superspreading does occur then such distributions must be interpreted with care. The simulation results are discussed in relation to measles epidemics in isolated populations and in predominantly urban scenarios. The effect of three different disease control policies on outbreak size distributions are shown for varying levels of heterogeneity and disease control effort.     

Epidemiological surveillance of meningococcal infection and the prediction of the development of an epidemic process

The signs necessary for the prognostication of the development of the epidemic process have been formulated on the basis of the epidemiological analysis of materials obtained in the process of trials of the system for the surveillance of meningococcal infection with the use of previously established characteristics. The data on the prevalence of meningococcal infection among different age groups and on the seasonal distribution of the infection as well as on the serogroups of meningococci isolated from patients, have been shown to be of importance for prognostication.     

In-silico prediction and observations of nuclear matrix attachment

The nuclear matrix is a functionally adaptive structural framework interior to the nuclear envelope. The nature and function of this nuclear organizer remains the subject of widespread discussion in the epigenetic literature. To draw this discussion together with a view to suggest a way forward we summarize the biochemical evidence for the modalities of DNA-matrix binding alongside the in-silico predictions. Concordance is exhibited at various, but not all levels. On the one hand, both the reiteration and sequence similarity of some elements of Matrix Attachment Regions suggest conservation. On the other hand, in-silico predictions suggest additional unique components. In bringing together biological and sequence evidence we conclude that binding may be hierarchical in nature, reflective of a biological role in replicating, transcribing and potentiating chromatin. Nuclear matrix binding may well be more complex than the widely accepted simple loop model. Invited paper All referenced websites were verified. URLs and their content are subject to change. The content referenced in this paper can be accessed using internet archive tools such as www.archive.org with the query restricted to November 2005.     

西非防控埃博拉病毒病暴发和流行的分析

埃博拉出血热自1976年首次暴发以来,其高致死率引起了人们的高度重视。2014年的埃博拉病毒病疫情已造成6800多人死亡。其暴发流行既有病原学和流行病学因素,也与西非当地的政治、经济、文化、卫生现状及应对措施密切相关。因此,综合分析造成流行的因素,有利于尽快控制疫情的迅速蔓延。目前包括中国政府在内的国际社会给予了积极帮助,国际社会与西非本国防控力量的有效结合将在更短的时间内控制疫情,并为我国做好埃博拉病毒病疫情的相关防控提供新的思考。     

A nosocomial outbreak of epidemic keratoconjunctivitis due to adenovirus type 37

An outbreak of epidemic keratoconjunctivitis occurred at the department of ophthalmology of a hospital in Yokohama, involving 14 inpatients, 12 outpatients, and 2 doctors. Adenovirus type 37 (Ad-37) was isolated from the conjunctival swab in 12 of 18 cases. In neutralization tests, the isolates showed some cross-reaction with adenovirus type 19 (Ad-19). The Ad-37 isolates were indistinguishable from each other and from the prototype Ad-37, but distinct from the prototype Ad-19 in the restriction endonuclease analysis of viral DNA.     

Protein complex prediction using an integrative bioinformatics approach

Since protein complexes play a crucial role in biological cells, one of the major goals in bioinformatics is the elucidation of protein complexes. A general approach is to build a prediction rule based on multiple data sources, e.g. gene expression data and protein interaction data, to assess the likelihood of two proteins having complex association. We critically revisit the step of predictor construction, i.e. the determination of a proper training set, an optimal classifier, and, most importantly, an optimal feature set. We use an exhaustive set of features, which includes the 2hop-feature as introduced by Wong et al. for predicting synthetic sick or lethal interactions. Post-processing of the likelihoods of protein interaction is then required to extract protein complexes. We propose a new protocol for combining these likelihood estimates. The protocol interprets the probabilities of complex association as output by the prediction rule as distances and employs hierarchical clustering to find groups of interacting proteins. In contrast to the computationally expensive search-and-score approach of Sharan et al., this protocol is very fast and can be applied to fully connected graphs. The protocol identifies trusted protein complexes with high confidence. We show that the 2hop-feature is relevant for predicting protein complexes. Furthermore, several interesting hypotheses about new protein complexes have been generated. For example, our approach linked the protein FYV4 to the mitochondrial ribosomal subunit. Interestingly, it is known that this protein is located in the mitochondrion, but its biological role is unknown. Vid22 and YGR071C were also linked, which corresponds to the new TAP data of Krogan et al.