Agusto Folashade B, Teboh-Ewungkem Miranda I, Gumel Abba B
Department of Mathematics and Statistics, Austin Peay State University, Clarksville, 37044, TN, USA.
Department of Mathematics, Lehigh University, Bethlehem, 18015, PA, USA.
BMC Med. 2015 Apr 23;13:96. doi: 10.1186/s12916-015-0318-3.
Ebola is one of the most virulent human viral diseases, with a case fatality ratio between 25% to 90%. The 2014 West African outbreaks are the largest and worst in history. There is no specific treatment or effective/safe vaccine against the disease. Hence, control efforts are restricted to basic public health preventive (non-pharmaceutical) measures. Such efforts are undermined by traditional/cultural belief systems and customs, characterized by general mistrust and skepticism against government efforts to combat the disease. This study assesses the roles of traditional customs and public healthcare systems on the disease spread.
A mathematical model is designed and used to assess population-level impact of basic non-pharmaceutical control measures on the 2014 Ebola outbreaks. The model incorporates the effects of traditional belief systems and customs, along with disease transmission within health-care settings and by Ebola-deceased individuals. A sensitivity analysis is performed to determine model parameters that most affect disease transmission. The model is parameterized using data from Guinea, one of the three Ebola-stricken countries. Numerical simulations are performed and the parameters that drive disease transmission, with or without basic public health control measures, determined. Three effectiveness levels of such basic measures are considered.
The distribution of the basic reproduction number ([Formula: see text]) for Guinea (in the absence of basic control measures) is such that [Formula: see text], for the case when the belief systems do not result in more unreported Ebola cases. When such systems inhibit control efforts, the distribution increases to [Formula: see text]. The total Ebola cases are contributed by Ebola-deceased individuals (22%), symptomatic individuals in the early (33%) and latter (45%) infection stages. A significant reduction of new Ebola cases can be achieved by increasing health-care workers' daily shifts from 8 to 24 hours, limiting hospital visitation to 1 hour and educating the populace to abandon detrimental traditional/cultural belief systems.
The 2014 outbreaks are controllable using a moderately-effective basic public health intervention strategy alone. A much higher (>50%) disease burden would have been recorded in the absence of such intervention. 2000 Mathematics Subject Classifications 92B05, 93A30, 93C15.
埃博拉是最致命的人类病毒性疾病之一,病死率在25%至90%之间。2014年西非的疫情是历史上规模最大、情况最严重的。目前尚无针对该疾病的特效治疗方法或有效/安全的疫苗。因此,防控工作仅限于基本的公共卫生预防(非药物)措施。然而,传统/文化信仰体系和习俗削弱了这些努力,其特点是对政府抗击该疾病的努力普遍不信任和持怀疑态度。本研究评估了传统习俗和公共卫生保健系统在疾病传播中的作用。
设计并使用一个数学模型来评估基本非药物控制措施对2014年埃博拉疫情的人群层面影响。该模型纳入了传统信仰体系和习俗的影响,以及在医疗环境中以及由埃博拉死亡者导致的疾病传播。进行敏感性分析以确定对疾病传播影响最大的模型参数。使用来自三个埃博拉受灾国家之一几内亚的数据对模型进行参数化。进行数值模拟,并确定在有无基本公共卫生控制措施的情况下驱动疾病传播的参数。考虑了此类基本措施的三个有效性水平。
几内亚(在没有基本控制措施的情况下)基本再生数([公式:见原文])的分布情况是,当信仰体系不会导致更多未报告的埃博拉病例时,[公式:见原文]。当此类体系抑制防控工作时,该分布增加到[公式:见原文]。埃博拉病例总数由埃博拉死亡者(22%)、早期(33%)和后期(45%)感染阶段的有症状个体构成。通过将医护人员的日工作时长从8小时增加到24小时、将医院探视时间限制在1小时以及教育民众摒弃有害的传统/文化信仰体系,可以显著减少新的埃博拉病例。
仅使用适度有效的基本公共卫生干预策略就可以控制2014年的疫情。如果没有这种干预,将会记录到高得多(>50%)的疾病负担。2000数学学科分类92B05、93A30、93C15。