Mathematical assessment of the effect of traditional beliefs and customs on the transmission dynamics of the 2014 Ebola outbreaks

Abstract

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 () for Guinea (in the absence of basic control measures) is such that , 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 . 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.

Essential information: Uncertainty and optimal control of Ebola outbreaks

“…Conditional on a single model, a conventional approach is to evaluate the sensitivity of outcomes and management recommendations to parametric uncertainty. However, it is increasingly common that there are multiple independent models that can contribute to the evaluation of candidate interventions and policy development (2,3,8,9). Thus, we present a framework for integrating model output to identify actions that are robust to the parametric, structural, and other uncertainties reflected in an ensemble of models.…”

“…Hospital settings and transmission during funeral practices have been identified as critical transmission sources of Ebola. A number of published Ebola compartment models have addressed these transmission mechanisms by explicitly including a hospitalized (H) compartment and a funeral (F) compartment (3,8,9,13). Based on the model structure, we classified 37 models into four categories: models with both H and F explicitly represented (8 models; referred to as SEIHFR), models with only H explicitly represented (5 models; referred to as SEIHR), models with only F explicitly represented (7 models; referred to as SEIFR), and models with neither H nor F compartments (i.e., these mechanisms of transmission were implicitly incorporated in overall transmission; 17 models; referred to as SEIR models).…”

“…By surveying the literature, we selected five interventions that were broadly applied to control Ebola outbreaks: reducing community transmission, increasing hospitalization, reducing hospital transmission, reducing case fatality ratio, and reducing funeral transmission (2,3,8). Reducing community transmission (i.e., transmission in the community) is a general intervention that is achieved in a variety of ways, such as by providing household sanitation kits, improving contact tracing, improving self-quarantine of sick individuals in the community, reducing individual mobility and border crossing, and increasing community awareness through educational campaigns (2,3,8). Hospitalization increase can be realized by improving contact tracing and intensifying campaigns to identify and isolate patients, building more Ebola Treatment Centers, increasing the number of beds, and increasing necessary supplies and public support (3,9).…”

“…Hospitalization increase can be realized by improving contact tracing and intensifying campaigns to identify and isolate patients, building more Ebola Treatment Centers, increasing the number of beds, and increasing necessary supplies and public support (3,9). A reduction in hospital transmission can be achieved by encouraging the use of personal protective equipment for healthcare personnel treating infected cases and reducing hospital visits (8). Hydration of infected individuals has proved to be an important way to reduce mortality of Ebola cases, and various other new pharmaceutical approaches are being explored for future outbreaks.…”

“…To ensure consistency, we recoded all of the models within the same stochastic environment by simulating the epidemic birth and death processes using the Gillespie algorithm with a tau-leaping approximation (3,7). We then identified five management actions that are broadly applied to control Ebola: reducing community transmission, reducing hospital transmission, reducing funeral transmission, increasing hospitalization, and reducing case fatality ratio (2,3,8,9). We projected the caseload under five management interventions and identified the optimum management for each model.…”