A Risk Analysis Approach to Prioritizing Epidemics: Ebola Virus Disease in West Africa as a Case Study. Issue 3 (15th August 2017)

• Record Type: Journal Article
• Authors: Ajisegiri, Whenayon Simeon; Chughtai, Abrar Ahmad; MacIntyre, C. Raina
• Is Part Of: Risk analysis. Volume 38:Issue 3(2018)
• Page Start: 429
• Page End: 441
• Publication Date: 2017-08-15
• Subjects: Ebola virus disease -- outbreak -- risk analysis -- risk framework -- West Africa; Technology -- Risk assessment -- Periodicals; 658.403
• DOI: 10.1111/risa.12876
• Languages: English
• ISSNs: 0272-4332

Abstract

Abstract: The 2014 Ebola virus disease (EVD) outbreak affected several countries worldwide, including six West African countries. It was the largest Ebola epidemic in the history and the first to affect multiple countries simultaneously. Significant national and international delay in response to the epidemic resulted in 28, 652 cases and 11, 325 deaths. The aim of this study was to develop a risk analysis framework to prioritize rapid response for situations of high risk. Based on findings from the literature, sociodemographic features of the affected countries, and documented epidemic data, a risk scoring framework using 18 criteria was developed. The framework includes measures of socioeconomics, health systems, geographical factors, cultural beliefs, and traditional practices. The three worst affected West African countries (Guinea, Sierra Leone, and Liberia) had the highest risk scores. The scores were much lower in developed countries that experienced Ebola compared to West African countries. A more complex risk analysis framework using 18 measures was compared with a simpler one with 10 measures, and both predicted risk equally well. A simple risk scoring system can incorporate measures of hazard and impact that may otherwise be neglected in prioritizing outbreak response. This framework can be used by public health personnel as a tool to prioritize outbreak investigation and flag outbreaks with potentially catastrophic outcomes for urgent response. Such a tool could mitigate costly delays in epidemic response.