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BACKGROUND: Village X, Sierra Leone, underwent village-wide quarantine because of its high incidence of Ebola virus disease (Ebola) despite household quarantines. The village-wide quarantine isolated Village X and offered the opportunity to investigate intra-community Ebola risk factors. We examined geospatial and household determinants of household-to-household Ebola transmission within this village to evaluate and tailor response efforts.
METHODS: We defined a household as a family’s shared living space and a case-household as a household in Village X with at least one resident who became a suspect, probable, or confirmed case of Ebola as defined by the Ministry of Health and Sanitation of Sierra Leone between August 1, 2014 and October 10, 2014. We collected household data through in-person interviews and assigned location data using Google Earth™. We used stepwise logistic regression modeling to calculate odds ratios of household Ebola acquisition associated with households’ geospatial and demographic characteristics.
RESULTS: The population of Village X at the beginning of the observation period was 863 persons living in 64 households (median household size, 10; IQR 6-18); 27/64 households became case-households (42% cumulative attack rate). Location within 10 meters of one case-household was the strongest predictor of becoming a case-household (unadjusted OR=18.00; 95% CI 2.11, 153.30). Inclusion of variables describing household crowding and latrine access in logistic models did not substantially modify the models’ goodness-of-fit.
CONCLUSIONS: Likelihood of household Ebola acquisition was highly associated with proximity to a case-household in Village X, a community that practiced quarantine of case-households. To decrease Ebola transmission, response efforts should include improving the effectiveness of household quarantine through rapid implementation, provision of basic household needs, and targeted outreach to households located near case-households.