SOCIOECONOMIC FACTORS AND THE 2014-16 EBOLA VIRUS DISEASE OUTBREAK IN GUINEA, LIBERIA, AND SIERRA LEONE
INTRODUCTION: Ebola virus disease (EVD) is an infectious disease transmitted by close contact with an estimated case fatality rate fluctuating around 50%. The most affected countries by the 2013-16 West African Ebola outbreak were Guinea, Liberia, and Sierra Leone. These countries reported a total of 28616 probable, suspected and confirmed cases. However, we are still learning about the sociodemographic factors that contributed to the outbreak characteristics at the subnational level.
METHODS: Data were collected from the World Health Organization, Demographic Health Surveys, and Global Data Lab for 37 districts (8 for Guinea, 15 for Liberia, and 14 for Sierra Leone). The outcome of interest was epidemic size at the district level for Guinea, Liberia, and Sierra Leone (cumulative number of EVD patient confirmed and probable cases). Socio-demographic predictors included household density, sanitation level, mobility, and wealth status. We also controlled for the timing of the start of the outbreak across districts. Pearson’s correlation and multiple linear regression were employed in our analyses. Model building was informed by a review of the relevant literature. Sensitivity analyses were conducted to assess the impact of potential outliers.
RESULTS: In the final multivariable regression model, wealth status and household density were positively associated with the epidemic size while sanitation level and the difference in the outbreak start dates were negatively associated with the outcome. These results did not change in the sensitivity analyses. The regression model explained 57% of the variance in epidemic size (Adj R-Sq=0.57), with the largest contribution from the international wealth index (semi-partial R-square=0.22).
CONCLUSION: District sociodemographic characteristics such as household density, wealth and sanitation levels contributed to the EVD outbreak in Guinea, Liberia, and Sierra Leone, which is in agreement with recent studies. However, further research should consider other sociodemographic indicators as well as the role of migration and connectivity among regions.
Identifer | oai:union.ndltd.org:GEORGIA/oai:scholarworks.gsu.edu:iph_theses-1581 |
Date | 05 May 2017 |
Creators | Mun, Elena |
Publisher | ScholarWorks @ Georgia State University |
Source Sets | Georgia State University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Public Health Theses |
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