RAPID: Designing Ebola Interventions for Large Urban Areas through Agent-Based Modeling and Network Analysis

这项研究将构建埃博拉病毒传播的数学模型。该模型将包括基于病原体特征以及人们在疫情期间的行为的参数。该模型的结果将帮助公共卫生官员根据现实的病原体特征和人类行为设计和执行针对当前疫情的有效干预策略，并帮助他们为未来的疫情做好准备。与现有模型不同，调查人员将基于人类行为开发利用显式媒介流动性的接触网络。该模型将产生两种类型的网络：流动和接触网络以及疾病传播网络。该模型将纳入基于不断演变的自我知识的行为，例如，人们在意识到或怀疑自己被感染时采取的一组行为，以及响应干预和消息传递的行为，例如是否遵守隔离建议。这一建模工作与以前关于疾病传播建模的工作形成了对比，因为该模型将基于典型行为生成接触网络，而不是基于理论网络结构或以前的暴发数据应用于该模型。

This research will construct a mathematical model of the spread of the Ebola virus. The model will include parameters based on the characteristics of the pathogen as well as the behavior of people during outbreak situations. The results from this model will help public health officials to design and execute efficient intervention strategies for the current outbreak based on realistic pathogen features and human behaviors and help them prepare for future outbreaks.Stemming from existing models, the investigators will develop contact networks utilizing explicit agent mobility based on human behaviors. The model will generate two types of networks: a mobility and contact network as well as a disease transmission network. The model will incorporate behaviors based on evolving self-knowledge, e.g. the set of behaviors that people employ once they are aware or suspect they are infected; as well as behaviors that are in response to interventions and messaging, e.g. complying with recommendations for quarantine or not. This modeling effort contrasts with previous work on disease transmission modeling, because the contact networks will be generated by this model based on representative behaviors as opposed to being applied to the model based on theoretical network structures or previous outbreak data.