A multi-group SEIRA model for the spread of COVID-19 among heterogeneous populations

The outbreak and propagation of COVID-19 have posed a considerable challenge to modern society. In particular, the different restrictive actions taken by governments to prevent the spread of the virus have changed the way humans interact and conceive interaction. Due to geographical, behavioral, or economic factors, different sub-groups among a population are more (or less) likely to interact, and thus to spread/acquire the virus. In this work, we present a general multi-group SEIRA model for representing the spread of COVID-19 among a heterogeneous population and test it in a numerical case of study. By highlighting its applicability and the ease with which its general formulation can be adapted to particular studies, we expect our model to lead us to a better understanding of the evolution of this pandemic and to better public-health policies to control it

A multi-group SEIRA model for the spread of COVID-19 among heterogeneous populations

The outbreak and propagation of COVID-19 have posed a considerable challenge to modern society. In particular, the different restrictive actions taken by governments to prevent the spread of the virus have changed the way humans interact and conceive interaction. Due to geographical, behavioral, or economic factors, different sub-groups among a population are more (or less) likely to interact, and thus to spread/acquire the virus. In this work, we present a general multi-group SEIRA model for representing the spread of COVID-19 among a heterogeneous population and test it in a numerical case of study. By highlighting its applicability and the ease with which its general formulation can be adapted to particular studies, we expect our model to lead us to a better understanding of the evolution of this pandemic and to better public-health policies to control it

Evaluation of Targeted Influenza Vaccination Strategies via Population Modeling

Background Because they can generate comparable predictions, mathematical models are ideal tools for evaluating alternative drug or vaccine allocation strategies. To remain credible, however, results must be consistent. Authors of a recent assessment of possible influenza vaccination strategies conclude that older children, adolescents, and young adults are the optimal targets, no matter the objective, and argue for vaccinating them. Authors of two earlier studies concluded, respectively, that optimal targets depend on objectives and cautioned against changing policy. Which should we believe? Methods and Findings In matrices whose elements are contacts between persons by age, the main diagonal always predominates, reflecting contacts between contemporaries. Indirect effects (e.g., impacts of vaccinating one group on morbidity or mortality in others) result from off-diagonal elements. Mixing matrices based on periods in proximity with others have greater sub- and super-diagonals, reflecting contacts between parents and children, and other off-diagonal elements (reflecting, e.g., age-independent contacts among co-workers), than those based on face-to-face conversations. To assess the impact of targeted vaccination, we used a time-usage study\u27s mixing matrix and allowed vaccine efficacy to vary with age. And we derived mortality rates either by dividing observed deaths attributed to pneumonia and influenza by average annual cases from a demographically-realistic SEIRS model or by multiplying those rates by ratios of (versus adding to them differences between) pandemic and pre-pandemic mortalities. Conclusions In our simulations, vaccinating older children, adolescents, and young adults averts the most cases, but vaccinating either younger children and older adults or young adults averts the most deaths, depending on the age distribution of mortality. These results are consistent with those of the earlier studies

Mitigating the Spread of Measles under Constrained Health Care Resources in Tanzania using Social Contact Network Models

Tanzania revaccinates individuals during measles outbreaks, despite having scant healthcare resources. We construct epidemiological models of measles spread by employing a hybrid of existing social contact networks models to develop SEIR simulation model. Using demographic and measles surveillance data from three rural villages in Tanzania, we simulate the spread of measles and examine which vaccination strategies can effectively control outbreaks. Results strongly indicate the spread of measles largely depends on contact rates among infected individuals within a population. Findings indicate a need for targeted vaccination for children of 6 months to 15 years of age, but equally for unvaccinated older age groups who were born before 1957 or missed the second dose. This work contributes theoretically and methodologically to existing applications of social contact network models for airborne infectious diseases in areas with health system constraints. It sets out implications for the design of effective vaccination programs for control of measles in Tanzania and in other developing countries. Keywords: Vaccination strategies, Control strategies, Social contact network models, Airborne infectious diseases, Measles

The Channel Strategy of Social Commerce-Based Business Model Innovation

社会化商务应用正成为企业开展商务模式（商业模式）创新活动、应对经济增速放缓、竞争加剧等严峻挑战的重要手段。社会化商务应用企业通常需要考虑如何在微博、人际交往等应用渠道中做出适合的选择、如何在所选的渠道中开展促销活动。为此，本文对社会化商务模式创新的渠道选择策略、渠道促销策略进行了探讨。在分析社会化商务参与者行为、用户与应用企业价值创造、提出社会化商务狭义、广义概念的基础上，结合广义评论行为、产品价值理性评价程度、广义虚拟经济理论中的使用价值、虚拟价值等，本文就社会化商务应用企业、用户所组成的社会经济复杂系统，运用基于主体的计算实验方法构建了营销领域的社会化商务应用模型，开展了社会化商务模式创新...For the decreasing economy growth rate, low growth rate of demand and more intense competition become the serious challenges of companies in many industries. Social commerce which has the advantages of huge users, low cost and high efficiency is one of what the companies should focus on in business model innovation. The adopter of social commerce often needs to decide how to select suitable social...学位：管理学博士院系专业：管理学院_技术经济及管理学号：1772011015357