[Source: US National Library of Medicine, full page: (LINK). Abstract, edited.]
Am J Epidemiol. 2019 Apr 3. pii: kwz090. doi: 10.1093/aje/kwz090. [Epub ahead of print]
Determinants of transmission risk during the late stage of the West African Ebola epidemic.
Robert A1, Edmunds WJ1, Watson CH1, Henao-Restrepo AM2, Gsell PS2, Williamson E3, Longini IM4, Sakoba K5, Kucharski AJ1, Touré A5, Nadlaou SD5, Diallo B6, Barry MS5, Fofana TO5, Camara L5, Kaba IL5, Sylla L5, Diaby ML5, Soumah O5, Diallo A5, Niare A5, Diallo A5, Eggo RM1.
Author information: 1 Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, UK. 2 World Health Organization, Geneva, Switzerland. 3 Department of Medical Statistics, London School of Hygiene &Tropical Medicine, UK. 4 Department of Biostatistics, University of Florida, USA. 5 WHO Ebola vaccination team, Guinea. 6 WHO Ebola vaccination team, Guinea, Ministry of Health, Guinea.
Understanding risk factors for Ebola transmission is key for effective prediction and design of interventions. We used data on 860 cases in 129 chains of transmission from the latter half of the 2013-16 Ebola outbreak in Guinea. Using negative binomial regression, we determined characteristics associated with the number of secondary cases resulting from each infected individual. We found that attending an Ebola Treatment Unit was associated with a 38% decrease in secondary cases (Incident rate ratio (IRR) 0.62, 95%CI: 0.38, 0.99) in individuals that did not survive. Unsafe burial was associated with a higher number of secondary cases (IRR 1.82, 95%CI: 1.10, 3.02). The average number of secondary cases was higher for the first generation of a transmission chain (mean = 1.77), compared with subsequent generations (mean = 0.70). Children were least likely to transmit (IRR 0.35 (95%CI: 0.21, 0.57) compared with adults, whereas older adults were associated with higher numbers of secondary cases. Men were less likely to transmit than women (IRR 0.71 (95%CI: 0.55, 0.93)). This detailed surveillance dataset provided an invaluable insight into transmission routes and risks. Our analysis highlights the key role that age, receiving treatment, and safe burial played in the spread of EVD.
© The Author(s) 2019. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.
KEYWORDS: Ebola; Guinea; Multiple imputation; Regression analysis; Risk factors
PMID: 30941398 DOI: 10.1093/aje/kwz090
Keywords: Ebola; Ebola-Makona; West Africa.