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的参数以及疫情期间人们的行为。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，为当前的疫情设计和执行有效的干预策略，并帮助他们为未来的疫情做好准备。在现有模型的基础上，研究人员将开发基于人类行为的明确代理移动性的联系网络。该模型将产生两种类型的网络：流动性和接触网络以及疾病传播网络。该模型将纳入基于不断发展的自我认识的行为，例如，人们在意识到或怀疑自己被感染后采取的一系列行为；以及响应干预措施和信息传递的行为，例如是否遵守隔离建议。这一建模工作与之前的疾病传播建模工作形成对比，因为接触网络将由该模型基于代表性行为生成，而不是应用于基于理论网络结构或先前爆发数据的模型。

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.