Bayesian inference for stochastic multitype epidemics in structured populations via random graphs

Summary.  The paper is concerned with new methodology for statistical inference for final outcome infectious disease data using certain structured population stochastic epidemic models. A major obstacle to inference for such models is that the likelihood is both analytically and numerically intractable. The approach that is taken here is to impute missing information in the form of a random graph that describes the potential infectious contacts between individuals. This level of imputation overcomes various constraints of existing methodologies and yields more detailed information about the spread of disease. The methods are illustrated with both real and test data.     

Evaluation of Response Scenarios to Potential Polio Outbreaks Using Mathematical Models

Appropriate response to polio outbreaks represents an important prerequisite for achieving and maintaining global polio eradication. We use an existing dynamic disease transmission model to evaluate the impact of different aspects of immunization campaigns in response to polio outbreaks occurring in previously polio-free areas. This analysis yields several important insights about response strategies. We find that delay in response represents a crucial risk factor for occurrence of large outbreaks and we characterize the tradeoffs associated with delaying the initial response to achieve better population coverage. We also demonstrate that controlling most potential outbreaks will likely require at least three immunization rounds, although the impact of the optimal interval between rounds varies. Finally, long after oral poliovirus vaccine cessation the choice of target age groups during a response represents an important consideration.     

Structural Change in Life Cycle Fertility During the Fertility Transition: France Before and After the Revolution of 1789

This paper explores the hypothesis that the fertility transition in France entailed a structural change in behaviour from natural to controlled fertility. We define the hypothesis in terms of an empirically estimable model of lifetime fertility. The model produces separate estimates of the three main proximate determinants: the hazard rate of conception for ovulating women, the timing of ovulation resumption after a birth, and permanent sterility. Fertility control is defined as responsiveness of the conception hazard to number of surviving children. We demonstrate key features of the model by simulated family histories. The historical application provides support for the transition hypothesis in the south of France, and mixed results for the north. We also find strong evidence of persistent couple-specific heterogeneity even after controlling for unobserved heterogeneity in fecundability. We suggest how future research might improve the model.     

Sex-Structured Dynamic of Multi-Group Herpes Simplex Virus 2

A 3(n + l)-dimensional ordinary differential equation for HSV-2 includes l groups of men and n groups of women with different risks of infection. Global Lyapunov functions based on graph theory and on LaSalle invariance principle show that the model dynamics are completely determined by the basic reproduction number ?₀. The disease-free equilibrium is globally asymptotically stable when ?₀ ≤ 1; a unique endemic equilibrium is globally asymptotically stable in the interior of the feasible region when ?₀ > 1.     

Quantitative risk assessment-epidemic curve prediction model for leafy green outbreak investigation

The objective of this study was to leverage quantitative risk assessment to investigate possible root cause(s) of foodborne illness outbreaks related to Shiga toxin-producing Escherichia coli O157:H7 (STEC O157) infections in leafy greens in the United States. To this end, we developed the FDA leafy green quantitative risk assessment epidemic curve prediction model (FDA-LG QRA-EC) that simulated the lettuce supply chain. The model was used to predict the number of reported illnesses and the epidemic curve associated with lettuce contaminated with STEC O157 for a wide range of scenarios representing various contamination conditions and facility processing/sanitation practices. Model predictions were generated for fresh-cut and whole lettuce, quantifying the differing impacts of facility processing and home preparation on predicted illnesses. Our model revealed that the timespan (i.e., number of days with at least one reported illness) and the peak (i.e., day with the most predicted number of reported illnesses) of the epidemic curve of a STEC O157-lettuce outbreak were not strongly influenced by facility processing/sanitation practices and were indications of contamination pattern among incoming lettuce batches received by the facility or distribution center. Through comparisons with observed number of illnesses from recent STEC O157-lettuce outbreaks, the model identified contamination conditions on incoming lettuce heads that could result in an outbreak of similar size, which can be used to narrow down potential root cause hypotheses.     

Application of a Risk Analysis Tool to Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Outbreak in Saudi Arabia

The Grunow–Finke assessment tool (GFT) is an accepted scoring system for determining likelihood of an outbreak being unnatural in origin. Considering its high specificity but low sensitivity, a modified Grunow–Finke tool (mGFT) has been developed with improved sensitivity. The mGFT has been validated against some past disease outbreaks, but it has not been applied to ongoing outbreaks. This study is aimed to score the outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) in Saudi Arabia using both the original GFT and mGFT. The publicly available data on human cases of MERS-CoV infections reported in Saudi Arabia (2012–2018) were sourced from the FluTrackers, World Health Organization, Saudi Ministry of Health, and published literature associated with MERS outbreaks investigations. The risk assessment of MERS-CoV in Saudi Arabia was analyzed using the original GFT and mGFT criteria, algorithms, and thresholds. The scoring points for each criterion were determined by three researchers to minimize the subjectivity. The results showed 40 points of total possible 54 points using the original GFT (likelihood: 74%), and 40 points of a total possible 60 points (likelihood: 67%) using the mGFT, both tools indicating a high likelihood that human MERS-CoV in Saudi Arabia is unnatural in origin. The findings simply flag unusual patterns in this outbreak, but do not prove unnatural etiology. Proof of bioattacks can only be obtained by law enforcement and intelligence agencies. This study demonstrated the value and flexibility of the mGFT in assessing and predicting the risk for an ongoing outbreak with simple criteria.     

中国经济发展的风险分析与模拟计算

在中国经济增速放缓的背景下,分析了中国经济发展的挑战和中国经济对世界经济的影响,运用牛津全球经济模型对中国经济发展的影响进行了模拟计算。研究表明,较高的债务水平和信贷规模增加了中国经济可持续发展的风险,高位运行的房地产市场加速了金融风险的积累,中美贸易摩擦加剧了外部风险,新冠肺炎疫情造成了中短期风险。随着在贸易、“一带一路”、资金流动、消费、产业融合等方面中国与世界经济的深度融合,中国经济对世界经济的影响逐步加深,模拟结果表明,如果中国的经济增长率每年减缓1%、2%和3%,那么全球经济增长率在2020年分别下降0.2%、0.5%和0.6%。进而,提出了扩大企业融资途径、防控金融风险、抑制房地产杠杆、刺激国内消费、加强宏观审慎监管等政策建议。     

Collapsing of Non‐centred Parameterized MCMC Algorithms with Applications to Epidemic Models

Data augmentation is required for the implementation of many Markov chain Monte Carlo (MCMC) algorithms. The inclusion of augmented data can often lead to conditional distributions from well‐known probability distributions for some of the parameters in the model. In such cases, collapsing (integrating out parameters) has been shown to improve the performance of MCMC algorithms. We show how integrating out the infection rate parameter in epidemic models leads to efficient MCMC algorithms for two very different epidemic scenarios, final outcome data from a multitype SIR epidemic and longitudinal data from a spatial SI epidemic. The resulting MCMC algorithms give fresh insight into real‐life epidemic data sets.     

政府干预下突发事件舆情传播规律与控制决策

通过对突发事件背景下的舆情传播进行多案例研究,界定了群众类型和政府干预作用,并分析了各类群众间的状态转移关系.然后,通过借鉴SEIR传染病模型的构造思路,结合舆情传播的实际特点,建立了政府干预下的舆情传播控制系统,进而运用平均场方法给出了系统的微分方程组模型.进一步,通过研究模型的平衡点和稳定性,得到了政府所应选择的管控方向,并以2011年东日本大地震事件中的舆情传播为例进行了验证.最后,基于该案例,通过设计多个情景,考查了政府的不同应急决策关注点对群众行为的影响,给出了应急方案的制定策略.     

生态危机剖析

生态危机是困扰当代人类的一个根本性问题。拟从生态危机的定义、生态危机爆发的原因、生态危机的实质及特征以及生态危机爆发的意义等几个方面剖析生态危机,以体现深入认识和了解生态危机的必要性和重要性。