作者: Gerardo Chowell , Lone Simonsen , Cécile Viboud , Yang Kuang
DOI: 10.1371/CURRENTS.OUTBREAKS.B4690859D91684DA963DC40E00F3DA81
关键词: Sierra leone 、 Data science 、 Logistic function 、 Outbreak 、 Development economics 、 Population 、 Susceptible individual 、 Transmission (mechanics) 、 Medicine 、 Zaire ebolavirus 、 Attack rate
摘要: An unprecedented epidemic of Zaire ebolavirus (EBOV) has affected West Africa since approximately December 2013, with intense transmission on-going in Guinea, Sierra Leone and Liberia increasingly important international repercussions. Mathematical models are proving instrumental to forecast the expected number infections deaths quantify intensity interventions required control transmission; however, calibrating mechanistic an outbreak is a challenging task owing limited availability epidemiological data rapidly changing interventions. Here we project trajectory EBOV by fitting logistic growth cumulative cases. Our model predictions align well latest reports available as October 23, indicates that exponential phase over Liberia, final attack rate ~0.1-0.12%. results indicate simple phenomenological can provide complementary insights into dynamics capture early signs changes population behavior In particular, our underscore need treat effective size susceptible dynamic variable rather than fixed quantity, due reactive throughout outbreak. We show from more earlier stages (such epidemics Guinea). More research warranted compare performances approaches for disease forecasts, before such be fully used public health authorities.