Levy Benjamin, Edholm Christina, Gaoue Orou, Kaondera-Shava Roselyn, Kgosimore Moatlhodi, Lenhart Suzanne, Lephodisa Benjamin, Lungu Edward, Marijani Theresia, Nyabadza Farai
Department of Mathematics, Fitchburg State University, USA.
Department of Mathematics, University of Tennessee, USA.
Infect Dis Model. 2017 Jun 29;2(3):323-340. doi: 10.1016/j.idm.2017.06.004. eCollection 2017 Aug.
Public involvement in Ebola Virus Disease (EVD) prevention efforts is key to reducing disease outbreaks. Targeted education through practical health information to particular groups and sub-populations is crucial to controlling the disease. In this paper, we study the dynamics of Ebola virus disease in the presence of public health education with the aim of assessing the role of behavior change induced by health education to the dynamics of an outbreak. The power of behavior change is evident in two outbreaks of EVD that took place in Sudan only 3 years apart. The first occurrence was the first documented outbreak of EVD and produced a significant number of infections. The second outbreak produced far fewer cases, presumably because the population in the region learned from the first outbreak. We derive a system of ordinary differential equations to model these two contrasting behaviors. Since the population in Sudan learned from the first outbreak of EVD and changed their behavior prior to the second outbreak, we use data from these two instances of EVD to estimate parameters relevant to two contrasting behaviors. We then simulate a future outbreak of EVD in Sudan using our model that contains two susceptible populations, one being more informed about EVD. Our finding show how a more educated population results in fewer cases of EVD and highlights the importance of ongoing public health education.
公众参与埃博拉病毒病（EVD）预防工作是减少疾病爆发的关键。通过向特定群体和亚人群提供实用的健康信息进行有针对性的教育对于控制该疾病至关重要。在本文中，我们研究了在开展公共卫生教育的情况下埃博拉病毒病的动态变化，目的是评估健康教育引起的行为改变对疫情动态的作用。行为改变的影响力在仅相隔3年于苏丹发生的两次埃博拉病毒病疫情中显而易见。第一次疫情是有记录的首次埃博拉病毒病爆发，导致大量感染。第二次疫情的病例则少得多，据推测是因为该地区的人群从第一次疫情中吸取了教训。我们推导了一个常微分方程组来模拟这两种截然不同的情况。由于苏丹的人群从第一次埃博拉病毒病疫情中吸取了教训，并在第二次疫情之前改变了行为，我们利用这两次埃博拉病毒病疫情的数据来估计与两种不同行为相关的参数。然后，我们使用包含两个易感人群的模型来模拟苏丹未来可能爆发的埃博拉病毒病疫情，其中一个人群对埃博拉病毒病了解更多。我们的研究结果表明，受教育程度更高的人群如何导致埃博拉病毒病病例减少，并凸显了持续开展公共卫生教育的重要性。
