Journal of Infectious Diseases and Medical Microbiology

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Research Article - Journal of Infectious Diseases and Medical Microbiology (2018) Volume 2, Issue 3

Epidemiological modelling of vaccination and reduced funeral rites interventions on the reproduction number, R0 of Ebola virus disease in West Africa.

Introduction: The Ebola virus, the causative agent for Ebola hemorrhagic fever, is one of the deadliest pathogens of record. The last major outbreak of the disease occurred in six countries of West Africa in 2014, with wide-spread transmission in Guinea, Liberia and Sierra Leone. Casualties were also recorded some countries outside Africa. The disease has a mortality rate of up to 90% and may lead to death within 10 days of infection. A lot of concerted efforts were instituted to control the raging epidemic. Materials and Methods: Using existing data on recorded cases and recently available intervention details, we model the impacts of these control measures on the sensitivity of the reproduction number, R0 . Specifically, we study the effects of vaccination and reduced funeral rites. We develop a mathematically-based computational model, incorporating a system of differential equations, which represents compartments of the epidemic population and intervention parameters. Results: Our findings reveal the percentage of the population that needs to be vaccinated, in each of the countries, to ensure containment of the disease outbreak. In addition to other interventions, the reproduction number can be effectively controlled, and the epidemic suppressed, by concentrating on vaccination and streamlined funeral activities. Conclusions: Our model can be used to forecast the duration of Ebola epidemic in any country, using our generic coefficient. Percentage of the population requiring herd immunity, through vaccination can be obtained. If there are no interventions in funeral activities, the R0 will remain above one. R0 will now depend on other interventions and the epidemic will linger for a longer time.

Author(s): Sampson Akwafuo, Xuan Guo, Armin Mikler

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