Johansson Michael A, Powers Ann M, Pesik Nicki, Cohen Nicole J, Staples J Erin
Division of Vector-Borne Diseases, Centers for Diseases Control and Prevention, San Juan, PR.
Division of Vector-Borne Diseases, Centers for Diseases Control and Prevention, Fort Collins, Colorado, United States of America.
PLoS One. 2014 Aug 11;9(8):e104915. doi: 10.1371/journal.pone.0104915. eCollection 2014.
In December 2013, the first locally-acquired chikungunya virus (CHIKV) infections in the Americas were reported in the Caribbean. As of May 16, 55,992 cases had been reported and the outbreak was still spreading. Identification of newly affected locations is paramount to intervention activities, but challenging due to limitations of current data on the outbreak and on CHIKV transmission. We developed models to make probabilistic predictions of spread based on current data considering these limitations.
Branching process models capturing travel patterns, local infection prevalence, climate dependent transmission factors, and associated uncertainty estimates were developed to predict probable locations for the arrival of CHIKV-infected travelers and for the initiation of local transmission. Many international cities and areas close to where transmission has already occurred were likely to have received infected travelers. Of the ten locations predicted to be the most likely locations for introduced CHIKV transmission in the first four months of the outbreak, eight had reported local cases by the end of April. Eight additional locations were likely to have had introduction leading to local transmission in April, but with substantial uncertainty.
Branching process models can characterize the risk of CHIKV introduction and spread during the ongoing outbreak. Local transmission of CHIKV is currently likely in several Caribbean locations and possible, though uncertain, for other locations in the continental United States, Central America, and South America. This modeling framework may also be useful for other outbreaks where the risk of pathogen spread over heterogeneous transportation networks must be rapidly assessed on the basis of limited information.
2013年12月,美洲首次报告了在加勒比地区出现的本地感染基孔肯雅病毒(CHIKV)病例。截至5月16日,已报告55992例病例,疫情仍在蔓延。确定新受影响的地点对于干预活动至关重要,但由于当前疫情数据以及CHIKV传播数据的局限性,这一工作颇具挑战性。考虑到这些局限性,我们基于现有数据开发了模型,以对病毒传播进行概率预测。
我们开发了分支过程模型,该模型考虑了旅行模式、当地感染率、气候相关传播因素以及相关不确定性估计,以预测CHIKV感染旅行者抵达的可能地点以及本地传播开始的地点。许多靠近已发生传播地区的国际城市和地区可能已经接收了感染的旅行者。在预测的疫情爆发前四个月中最有可能引入CHIKV传播的十个地点中,有八个在4月底前报告了本地病例。另外八个地点在4月可能有病毒引入并导致本地传播,但存在很大不确定性。
分支过程模型可以描述当前疫情期间CHIKV引入和传播的风险。目前,CHIKV在加勒比地区的几个地点可能发生本地传播,在美国大陆、中美洲和南美洲的其他地点也有可能发生,尽管存在不确定性。这种建模框架对于其他必须根据有限信息快速评估病原体在异质运输网络中传播风险的疫情也可能有用。