Estimating the Basic Reproductive Number in the General Epidemic Model with an Unknown Initial Number of Susceptible Individuals

Abstract. In any epidemic, there may exist an unidentified subpopulation which might be naturally immune or isolated and who will not be involved in the transmission of the disease. Estimation of key parameters, for example, the basic reproductive number, without accounting for this possibility would underestimate the severity of the epidemics. Here, we propose a procedure to estimate the basic reproductive number ( R ₀ ) in an epidemic model with an unknown initial number of susceptibles. The infection process is usually not completely observed, but is reconstructed by a kernel‐smoothing method under a counting process framework. Simulation is used to evaluate the performance of the estimators for major epidemics. We illustrate the procedure using the Abakaliki smallpox data.     

仪式与象征——年都乎岁末傩疫活动的人类学研究

本文在人类学田野工作的基础上 ,运用人类学的知识和社会记忆理论 ,对年都乎虎傩活动的仪式结构和象征意义作了讨论。     

Estimation in Epidemics with Incomplete Observations

The construction of estimating equations by martingale methods is generalized to yield estimators with explicit expressions for the parameters of the birth-and-death and the general epidemic processes when only partial observations are available. (For the birth-and-death process the death process is observed but the number of births is observed only at the end and for the general epidemic process only the removal process is observed.) For large populations, the use of the martingale central limit theorem yields asymptotic confidence regions for the parameters. Explicit expressions are derived for estimators of the variances of the large sample distributions. The range of validity and usefulness of the new estimators is determined by simulation.     

Assessing Interventions to Reduce the Risk of Campylobacter Prevalence in Broilers

As part of a comprehensive risk assessment on the Campylobacter prevalence in the chicken production chain (from young born chicken till chicken fillet) in the Netherlands, we formulated a quantitative model on the transmission dynamics of Campylobacter at Dutch broiler farms. This model is used to quantify the risk of Campylobacter prevalence in broilers at the time that flocks leave the farm for processing. To this end, we assumed that the Campylobacter prevalence is primarily determined by two parameters, that is, the within- and between-flock transmission. The within-flock transmission was assessed fitting experimental data to a logistic growth model and the between-flock transmission was assessed fitting field data to a generalized linear model (GLM), which included three possible infection routes: (1) via an infected flock in the previous cycle, (2) via other infected flocks present on the farm, and (3) from other sources. This model was applied to assess the efficacy of three control scenarios; (1) a ban on other livestock on broiler farms, (2) a ban on thinning, and (3) a reduction of the between-flock transmission. In contrast to the other scenarios, the third one was shown to be most effective. Theoretically, this is accomplished by improved biosecurity. However, the impact of improved biosecurity cannot be specified into specific control measures, and therefore it is not clear what investments are needed. Finally, we also assessed the efficacy of scheduled treatment, that is, fresh meat production solely from test-negative flocks. We found that the reliability of negative test results, which is crucial, strongly depends on the length of time between testing and slaughter. The sensitivity and specificity of the test appeared to be of minor importance.     

Inference in disease transmission experiments by using stochastic epidemic models

Summary.  The paper extends the susceptible–exposed–infective–removed model to handle heterogeneity introduced by spatially arranged populations, biologically plausible distributional assumptions and incorporation of observations from additional diagnostic tests. These extensions are motivated by a desire to analyse disease transmission experiments in a more detailed fashion than before. Such experiments are performed by veterinarians to gain knowledge about the dynamics of an infectious disease. By fitting our spatial susceptible–exposed–infective–removed with diagnostic testing model to data for a specific disease and production environment a valuable decision support tool is obtained, e.g. when evaluating on-farm control measures. Partial observability of the epidemic process is an inherent problem when trying to estimate model parameters from experimental data. We therefore extend existing work on Markov chain Monte Carlo estimation in partially observable epidemics to the multitype epidemic set-up of our model. Throughout the paper, data from a Belgian classical swine fever virus transmission experiment are used as a motivating example.     

新冠疫情背景下文化自信的多维审视

在抗击新冠疫情的过程中,中华文化成为我国开展抗疫工作的力量源泉。伟大的民族精神是抗击新冠疫情的自信之魂,团结精神和爱国情怀、中华民族勇于开拓的创造精神,为中华儿女抗击疫情提供了源源不断的动力支撑。优秀传统文化是抗击新冠疫情的自信之根,自强不息的民族精神、人民至上的价值理念、“和而不同”的文化理念,在疫情防控阻击战中得到了充分的展现。社会主义先进文化是抗击疫情的自信之核,以社会主义先进文化为引领谋划战“疫”布局,体现出我国显著的制度优势、卓越的治理优势。红色革命文化是战胜新冠疫情的基因密码,在抗疫中表现为党和人民群众的血肉相连,是中国人民团结勇敢、积极乐观精神最真切的体现。     

The outbreak mechanisms of the green rice leafhopper,Nephotettix cincticeps Uhler, in northern Japan

Intraspecific regulatory processes keep the population ofNephotettix cincticeps stable at a low density in southern Japan. In northern Japan, however, the yearly population density of the insect fluctuates violently, and large outbreaks occasionally take place. To clarify the difference in the population dynamics between the two regions, we analyzed light-trap and sweep-net sampling records from prefectural and national agricultural experimental stations. The survival rate of the overwintering population decreased with increases in the period of continuous snow cover (PCSC) in the north, and initial population densities in the years of long PCSC were too low for populations to reach equilibrium density by the end of the active breeding season. This made yearly population fluctuations in the north much larger than in the south. The equilibrium density in the north was higher than in the south. The higher equilibrium density presumably permits the higher population density and larger yearly population fluctuations in the north. A major factor responsible for the difference in equilibrium densities between the two regions is the difference in heading dates of the host plant (rice). Qualitative differences among rice plant varieties, and among biotypes ofN. cincticeps, may also be important.     

南京国民政府时期皖省当局开展的防疫活动述论

由于防控疫情的现实需要和卫生强国想象的目标激励,南京国民政府时期,全国范围内展开以防疫行政为重要事务的公共卫生建设。处此历史情境,皖省官方顺应时势,积极推行各项防疫活动,兼顾常态化预防和突发性应对,彰显卫生防疫行政的效能和作用。由于时代的困境,皖省防疫实践终究难免防不胜防的厄运,却多少改善了地方民众的生命状态、形塑了他们的现代卫生防疫观念,促进了安徽卫生防疫事业由传统向现代的演进和嬗变。     

Cross-infection in epidemics spread by carriers

A block-structured transient Markov process is introduced to describe an epidemic spreading within two linked populations, of carriers and susceptibles. The epidemic terminates as soon as there are no more carriers or susceptibles present in the population. Our purpose is to determine the distribution of the final susceptible and carrier states, and of any integral path for the susceptible process. The transient epidemic state is also briefly discussed. Then, the model is extended to allow the recovery of infected individuals. Finally, several particular models, some known, are used for illustration.     

A stochastic graph process for epidemic modelling

A stochastic graph process with a Markov property is introduced to model the flow of an infectious disease over a known contact network. The model provides a probability distribution over unobserved infectious pathways. The basic reproductive number in compartmental models is generalized to a dynamic reproductive number based on the sequence of outdegrees in the graph process. The cumulative resistance and threat associated with each individual is also measured based on the cumulative indegree and outdegree of the graph process. The model is applied to the outbreak data from the 2001 foot‐and‐mouth (FMD) outbreak in the United Kingdom. The Canadian Journal of Statistics 40: 55–67; 2012 © 2012 Statistical Society of Canada