Addressing Women and Ebola: a Corpus-based Study

Addressing Women and Ebola: a Corpus-based Study When analyzing the incidence of EVD  Ebola Virus Disease  on the African population, there seems to be no biological sex difference in terms of vulnerability. Researches on the spread of the virus also show a relatively fixed pattern, with the virus spreading from person to person through direct contact with body fluids, such as blood, from infected humans or other animals (Menéndes et. al. 2015: 1). Recent studies have, however, begun to point out a series of risks and possible complications derived by EVD and concerning pregnant women in particular. While the overall fertile age ranges from 15 to 44 years (Bebell et. al. 2017: 353), these studies focus on the women living in the sub-Saharan area, who tend to give birth to their first child at the average age of 20.9 years (Bongaarts and Blanc 2015). The cases concerning pregnant women pose, in fact, a further set of issues, in both cultural and healthcare-related matters. From a cultural perspective women act as caregivers in their homes and communities and, as such, assist most infected individuals, a matter that puts them at an increased risk of contracting the virus (Black et. al. 2015: 109). From a strictly medical point of view, it is suggested that pregnant women with active EVD may transmit the virus during childbirth, thus posing the risk of infecting the people around them. Even the fetus is subject to a high risk of mortality due to different possible complications, with some reports going as far as excluding all possibility of survival beyond the neonatal period (WHO Interim Guidance 2018: 1). Keeping this particular situation in mind, the purpose of this study is to explore the language and terminology used to describe the situation of pregnant women during the two most recent EVD outbreaks (starting from the year 2014 until present day), using the research methods of Corpus Linguistics and Corpus-based Terminology. Using the software Sketch Engine (Kilgariff et. al. 2004; Kilgariff et. al. 2004) to process a corpus composed of academic texts, the most frequent keywords will be pointed out and analyzed within the framework of specialized medical discourse.