Determinants of transmission risk during the late stage of the West African Ebola epidemic.

Alexis Robert,W John Edmunds,Conall H Watson,Ana Maria Henao-Restrepo,Pierre-Stéphane Gsell,Elizabeth Williamson,Ira M Longini,Keïta Sakoba,Adam J Kucharski,Alhassane Touré, Sévérine Danmadji Nadlaou,Boubacar Diallo, Mamamdou Saidou Barry,Thierno Oumar Fofana, Louceny Camara, Ibrahima Lansana Kaba, Lansana Sylla, Mohamed Lamine Diaby, Ousmane Soumah, Abdourahime Diallo, Amadou Niare,Abdourahmane Diallo,Rosalind M Eggo

AMERICAN JOURNAL OF EPIDEMIOLOGY(2019)

引用 9|浏览24
暂无评分
摘要
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 2013-2016 Ebola epidemic 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 (incidence rate ratio (IRR) = 0.62, 95% confidence interval (CI): 0.38, 0.99) among 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 data set 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.
更多
查看译文
关键词
Ebola,Guinea,multiple imputation,regression analysis,risk factors
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要