Mathematical assessment of the effect of traditional beliefs and customs on the transmission dynamics of the 2014 Ebola outbreaksReportar como inadecuado

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BMC Medicine

, 13:96

First Online: 23 April 2015Received: 02 December 2014Accepted: 10 March 2015DOI: 10.1186-s12916-015-0318-3

Cite this article as: Agusto, F.B., Teboh-Ewungkem, M.I. & Gumel, A.B. BMC Med 2015 13: 96. doi:10.1186-s12916-015-0318-3


BackgroundEbola 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.

MethodsA 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.

ResultsThe distribution of the basic reproduction number \\mathcal {R} {0}\ for Guinea in the absence of basic control measures is such that \\mathcal {R} {0}\in \;0.77,1.35\, 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 \\mathcal {R} {0}\in \;1.15,2.05\. 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.

ConclusionsThe 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.

KeywordsEbola Community Hospital Health-care workers Quarantine AbbreviationsEBOVEbola virus

EVDEbola virus disease

PRCCpartial rank correlation coefficient

WHOWorld Health Organization

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Autor: Folashade B Agusto - Miranda I Teboh-Ewungkem - Abba B Gumel


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