A Risk Analysis Approach to Prioritizing Epidemics: Ebola Virus Disease in West Africa as a Case Study

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.

Application of a Risk Analysis Tool to Middle East Respiratory Syndrome Coronavirus (MERS‐CoV) Outbreak in Saudi Arabia

“…During the past decade, serious outbreaks of emerging infectious diseases have occurred in many parts of the world, including the Middle East respiratory syndrome coronavirus (MERS-CoV) in Saudi Arabia (2012-present), Ebola in West Africa (2014)(2015)(2016) (Ajisegiri, Chughtai, & MacIntyre, 2018), Zika virus in Brazil (2015 (Campos, Bandeira, & Sardi, 2015), and the plague in Madagascar in 2017 (European Centre for Disease Prevention and Control, 2017). The default assumption of most outbreaks and epidemics is that they are naturally caused (MacIntyre & Engells, 2016), and public health culture and practice do not routinely consider unnatural causes such as bioterrorism or biowarfare (MacIntyre, 2015a).…”

Recalibration of the Grunow–Finke Assessment Tool to Improve Performance in Detecting Unnatural Epidemics

“…In a risk analysis of Ebola virus disease in West Africa (Ajisegiri, Chughtai, & MacIntyre, ), we showed that a simple assessment tool with fewer criteria can perform as well as a more complex tool with a greater number of criteria. Therefore, in the first stage, we simplified the GFT by removing such criteria that negatively impact its sensitivity.…”

Converging and emerging threats to health security

“…New risk analysis methods are required to flag epidemics for urgent intervention, as illustrated by the catastrophic consequences of inaction with the 2014 Ebola epidemic in West Africa (World Health Organization 2015). We have shown that a simple risk prediction tool can be developed which identifies regions at high risk of severe outcomes of epidemics (Argisiri et al 2017). Such a tool, which considers disease specific, geographic, political, social, situational and contextual factors, could be used to prioritise epidemic response in situations of limited resources and reduce the impact of serious events.…”