The socio-economic distribution of exposure to Ebola: Survey evidence from Liberia and Sierra Leone

Abstract

Socio-economic factors are widely believed to have been an important driver of the transmission of Ebola Virus Disease (EVD) during the West African outbreak of 2014–16, however, studies that have investigated the relationship between socio-economic status (SES) and EVD have found inconsistent results. Using nationally representative household survey data on whether respondents knew a close friend or family member with Ebola, we explore the SES determinants of EVD exposure along individual, household, and community lines in Liberia and Sierra Leone. While we find no overall association between household wealth and EVD exposure, we find that pooled data mask important differences observed within countries with higher wealth households more likely to have been exposed to EVD in Sierra Leone and the opposite relationship in Liberia. Finally, we also generally find a positive association between education and EVD exposure both at the individual and the community levels in the full sample. There is an urgent need to better understand these relationships to examine both why the outbreak spread and to help prepare for future outbreaks.

Estimation of Ebola's spillover infection exposure in Sierra Leone based on sociodemographic and economic factors

“…Still, some results are worth mentioning about these demographic indicators. Young adults (ages between [18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] and adults (ages between 34-50) constituted 77% of the investigated sample, but they constitute 86% of the respondents at risk. Also, 50% of the study respondents have an agriculture-related occupation but when computing the percentage within respondents at risk we obtained 79%.…”

“…In that context, it has been shown that, typically, people with lower socioeconomic status have higher exposure to risk factors than the wealthier segments of the population [28]. While a consensus on the relationship between SDE factors and exposure to infectious diseases has not been reached [29], some modeling studies support the idea that poverty has an effect on the spread of infectious diseases [30][31][32]. However, we point out that this relationship is mostly supported by aggregate data at the country level (e.g., GDP) and not for individuals.…”

Cultural and economic discrimination by the Great Leveller

“…It is argued that growing inequality leads to deteriorating health conditions for the poor and increased exposure to foreign germs by the increasingly more mobile rich (Kohn, 2007; Turchin, 2007). The relevance of these historic studies has been raised in the context of the COVID‐19 case (see Spinney, 2020; Turchin, 2020), and the role of social factors has been demonstrated for other global diseases, such as Ebola (Grepin et al, 2020). Thus, historic or path‐dependent inequality is likely to be associated with the uneven spread of COVID‐19.…”

Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors

“…In that context, it has been shown that, typically, people with lower socioeconomic status have higher exposure to risk factors than the wealthier segments of the population [28]. While a consensus on the relationship between SDE factors and exposure to infectious diseases has not been reached [29], some modeling studies support the idea that poverty has an effect on the spread of infectious diseases [30][31][32]. However, we point out that this relationship is mostly supported by aggregate data at the country level (e.g., GDP) and not at the individual level.…”