Tuncer Necibe, Mohanakumar Chindu, Swanson Samuel, Martcheva Maia
a Department of Mathematical Sciences , Florida Atlantic University , Boca Raton , FL , USA.
b Department of Mathematics , University of Florida , Gainesville , FL , USA.
J Biol Dyn. 2018 Dec;12(1):913-937. doi: 10.1080/17513758.2018.1535095.
The largest outbreak of Ebola to date is the 2014 West Africa Ebola outbreak, with more than 10,000 cases and over 4000 deaths reported in Liberia alone. To control the spread of the outbreak, multiple interventions were implemented: identification and isolation of cases, contact tracing, quarantining of suspected contacts, proper personal protection, safely conducted burials, improved education, social awareness and individual protective measures. Devising rigorous methodologies for the evaluation of the effectiveness of the control measures implemented to stop an outbreak is of paramount importance. In this paper, we evaluate the effectiveness of the 2014 Ebola outbreak interventions. We rely on model selection to determine the best model that explains the 2014 Ebola outbreak data in Liberia which is the simplest model with a social distancing term. We couple structural and practical identifiability analysis with the computation of confidence intervals to pinpoint the uncertainty in the parameter estimations. Finally, we evaluate the efficacy of control measures using the Ebola model with social distancing. Among all the control measures, we find that social distancing had the most impact on the control of the 2014 Ebola epidemic in Libreria followed by isolation and quarantining.
迄今为止最大规模的埃博拉疫情是2014年西非埃博拉疫情,仅利比里亚就报告了10000多例病例和4000多人死亡。为控制疫情蔓延,实施了多项干预措施:病例识别与隔离、接触者追踪、疑似接触者隔离、适当的个人防护、安全的埋葬方式、加强教育、提高社会意识以及个人防护措施。制定严格的方法来评估为阻止疫情爆发而实施的控制措施的有效性至关重要。在本文中,我们评估2014年埃博拉疫情干预措施的有效性。我们依靠模型选择来确定能解释2014年利比里亚埃博拉疫情数据的最佳模型,即带有社交距离项的最简单模型。我们将结构和实际可识别性分析与置信区间的计算相结合,以确定参数估计中的不确定性。最后,我们使用带有社交距离的埃博拉模型评估控制措施的效果。在所有控制措施中,我们发现社交距离对2014年利比里亚埃博拉疫情的控制影响最大,其次是隔离和检疫。