Lee Eva K, Liu Yifan, Pietz Ferdinand H
NSF-Whitaker Center for Operations Research in Medicine and HealthCare; NSF I/UCRC Center for Health Organization Transformation; School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA; eva.lee@gatechedu.
NSF-Whitaker Center for Operations Research in Medicine and HealthCare; NSF I/UCRC Center for Health Organization Transformation; School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA.
AMIA Annu Symp Proc. 2017 Feb 10;2016:743-752. eCollection 2016.
The Zika virus (ZIKV) outbreak in South American countries and its potential association with microcephaly in newborns and Guillain-Barré Syndrome led the World Health Organization to declare a Public Health Emergency of International Concern. To understand the ZIKV disease dynamics and evaluate the effectiveness of different containment strategies, we propose a compartmental model with a vector-host structure for ZIKV. The model utilizes logistic growth in human population and dynamic growth in vector population. Using this model, we derive the basic reproduction number to gain insight on containment strategies. We contrast the impact and influence of different parameters on the virus trend and outbreak spread. We also evaluate different containment strategies and their combination effects to achieve early containment by minimizing total infections. This result can help decision makers select and invest in the strategies most effective to combat the infection spread. The decision-support tool demonstrates the importance of "digital disease surveillance" in response to waves of epidemics including ZIKV, Dengue, Ebola and cholera.
寨卡病毒(ZIKV)在南美国家的爆发及其与新生儿小头畸形和吉兰 - 巴雷综合征的潜在关联,促使世界卫生组织宣布这是一起国际关注的突发公共卫生事件。为了解寨卡病毒疾病动态并评估不同防控策略的有效性,我们提出了一个具有媒介 - 宿主结构的寨卡病毒 compartmental 模型。该模型采用人类种群的逻辑增长和媒介种群的动态增长。利用此模型,我们推导出基本再生数,以深入了解防控策略。我们对比不同参数对病毒趋势和疫情传播的影响。我们还评估不同的防控策略及其组合效果,以通过最小化总感染数实现早期防控。这一结果有助于决策者选择并投资于最有效的抗击感染传播策略。该决策支持工具证明了“数字疾病监测”在应对包括寨卡病毒、登革热、埃博拉和霍乱在内的疫情浪潮中的重要性。