Data Fitting and Scenario Analysis of Vaccination in the 2014 Ebola Outbreak in Liberia
Mathematics and Natural Sciences
Objectives: This study aimed to extend an epidemiological model (SEIHFR) to analyze epidemic trends, and evaluate intervention efficacy.
Methods: SEIHFR was modified to examine disease transmission dynamics after vaccination for the Ebola outbreak. Using existing data from Liberia, sensitivity analysis of various epidemic scenarios was used to inform the model structure, estimate the basic reproduction number ℜ0 and investigate how the vaccination could effectively change the course of the epidemic.
Results: If a randomized mass vaccination strategy was adopted, vaccines would be administered prophylactically or as early as possible (depending on the availability of vaccines). An effective vaccination rate threshold for Liberia was estimated as 48.74% among susceptible individuals. If a ring vaccination strategy was adopted to control the spread of the Ebola virus, vaccines would be given to reduce the transmission rate improving the tracing rate of the contact persons of an infected individual.
Conclusion: The extended SEIHFR model predicted the total number of infected cases, number of deaths, number of recoveries, and duration of outbreaks among others with different levels of interventions such as vaccination rate. This model may be used to better understand the spread of Ebola and develop strategies that may achieve a disease-free state.
Osong Public Health and Research Perspectives
(2019). Data Fitting and Scenario Analysis of Vaccination in the 2014 Ebola Outbreak in Liberia. Osong Public Health and Research Perspectives, 10(3), 187-201.
Available at: https://aquila.usm.edu/fac_pubs/16482